ABC vol 39.1 (2016) by Museu Ciències Naturals de Barcelona MCNB

Editor en cap / Editor responsable / Editor in Chief

2Joan Carles Senar

Editors temàtics / Editores temáticos / Thematic Editors Ecologia / Ecología / Ecology: Mario Díaz (Asociación Española de Ecología Terrestre – AEET) Comportament / Comportamiento / Behaviour: Adolfo Cordero (Sociedad Española de Etología y Ecología Evolutiva – SEEEE) Biologia Evolutiva / Biología Evolutiva / Evolutionary Biology: Santiago Merino (Sociedad Española de Biología Evolutiva – SESBE) Editors / Editores / Editors Pere Abelló Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Javier Alba–Tercedor Univ. de Granada, Granada, Spain Russell Alpizar–Jara Univ. of Évora, Évora, Portugal Marco Apollonio Univ di Sassari, Sassari, Italy Xavier Bellés Inst. de Biología Evolutiva UPF–CSIC, Barcelona, Spain Salvador Carranza Inst. Biologia Evolutiva UPF–CSIC, Barcelona, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Pablo Castillo Institute for Sustainable Agriculture–CSIC, Córdoba, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain José A. Donazar Estación Biológica de Doñana–CSIC, Sevilla, Spain Arnaud Faille Museum National histoire naturelle, Paris, France Jordi Figuerola Estación Biológica de Doñana–CSIC, Sevilla, Spain Gonzalo Giribet Museum of Comparative Zoology, Harvard Univ., Cambridge, USA Susana González Univ. de la República–UdelaR, Montivideo, Uruguay Sidney F. Gouveia Univ. Federal de Sergipe, Sergipe, Brasil Gary D. Grossman Univ. of Georgia, Athens, USA Jacob Höglund Uppsala Univ., Uppsala, Sweden Joaquín Hortal Museo Nacional de Ciencias Naturales-CSIC, Madrid, Spain Damià Jaume IMEDEA–CSIC, Univ. de les Illes Balears, Spain Jennifer A. Leonard Estación Biológica de Doñana-CSIC, Sevilla, Spain Jordi Lleonart Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Josep Lloret Univ de Girona, Girona, Spain Jorge M. Lobo Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Pablo J. López–González Univ. de Sevilla, Sevilla, Spain Jose Martin Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Santiago Merino Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Juan J. Negro Estación Biológica de Doñana–CSIC, Sevilla, Spain Vicente M. Ortuño Univ. de Alcalá de Henares, Alcalá de Henares, Spain Miquel Palmer IMEDEA–CSIC, Univ. de les Illes Balears, Spain Reyes Peña Santiago Univ. de Jaén, Jaén, Spain Javier Perez–Barberia Estación Biológica de Doñana–CSIC, Sevilla, Spain Oscar Ramírez Inst. de Biologia Evolutiva UPF–CSIC, Barcelona, Spain Montserrat Ramón Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Ignacio Ribera Inst. de Biología Evolutiva UPF–CSIC, Barcelona, Spain Alfredo Salvador Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Diego San Mauro Univ. Complutense de Madrid, Madrid, Spain Constantí Stefanescu Museu de Ciències Naturals de Granollers, Granollers, Spain Diederik Strubbe Univ. of Antwerp, Antwerp, Belgium José L. Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Ciències Naturals de Barcelona, Barcelona, Spain José Ramón Verdú CIBIO, Univ de Alicante, Alicante, Spain Carles Vilà Estación Biológica de Doñana–CSIC, Sevilla, Spain Rafael Villafuerte Inst. de Estudios Sociales Avanzados (IESA–CSIC), Cordoba, Spain Rafael Zardoya Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer Assistència Tècnica / Asistencia Técnica / Technical Assistance Eulàlia Garcia Anna Omedes Francesc Uribe

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Assessorament lingüístic / Asesoramiento lingüístico / Linguistic advisers Carolyn Newey Pilar Nuñez Animal Biodiversity and Conservation 39.1, 2016 © 2016 Museu de Ciències Naturals de Barcelona, Consorci format per l'Ajuntament de Barcelona i la Generalitat de Catalunya Autoedició: Montserrat Ferrer Fotomecànica i impressió: Inspyrame Printing ISSN: 1578–665 X eISSN: 2014–928 X Dipòsit legal: B. 5357–2013 Animal Biodiversity and Conservation es publica amb el suport de: l'Asociación Española de Ecología Terrestre, la Sociedad Española de Etología y Ecología Evolutiva i la Sociedad Española de Biología Evolutiva The journal is freely available online at: www.abc.museucienciesjournals.cat Dibuix de la coberta: Lucanus cervus, escanyapolls o cèrvol volant, ciervo volante, stag beetle (Jordi Domènech)

Animal Biodiversity and Conservation 39.1 (2016)

Diversity of Andean amphibians of the Tamá National Natural Park in Colombia: a survey for the presence of Batrachochytrium dendrobatidis A. A. Acevedo, R. Franco & D. A. Carrero

Acevedo, A. A., Franco, R. & Carrero, D. A., 2016. Diversity of Andean amphibians of the Tamá National Natural Park in Colombia: a survey for the presence of Batrachochytrium dendrobatidis. Animal Biodiversity and Conservation, 39.1: 1–10. Abstract Diversity of Andean amphibians of the Tamá National Natural Park in Colombia: a survey for the presence of Batrachochytrium dendrobatidis.— Changes in diversity and possible decreases in populations of amphibians have not yet been determined in many areas in the Andes. This study aimed to develop an inventory of the biodiversity of amphibians in the Andean areas of the Tamá National Natural Park (Tamá NNP) and to evaluate the patterns of infection by Batrachochytrium dendrobatidis (Bd) in preserved and degraded areas. We performed samplings focused on three habitats (forest, open areas and streams) in four localities from 2,000 to 3,200 m in altitude. Fourteen species were recorded, 12 of which were positive for Bd. A total of 541 individuals were diagnosed and 100 were positive. Our analyses showed that preserved areas play an important role in keeping many individuals Bd–free as compared to those in degraded areas. This was the first study to evaluate diversity and infection by Bd in the northeast region of Colombia. Our findings may help improve our knowledge of the diversity of amphibian species in the area and facilitate the implementation of action plans to mitigate the causes associated with the decrease in amphibian populations. Key words: Amphibians, Conservation, Chytridiomycosis, Diversity, Protected natural areas Resumen Diversidad de anfibios andinos del Parque Nacional Natural Tamá en Colombia: un estudio para determinar la presencia de Batrachochytrium dendrobatidis.— Son muchas las zonas de los Andes en las que aún no se han determinado los cambios en la diversidad ni la posible disminución de las poblaciones de anfibios. Este estudio pretende elaborar un inventario de la biodiversidad de anfibios en las áreas andinas del Parque Nacional Natural Tamá (PNN Tamá) y evaluar los patrones de infección por Batrachochytrium dendrobatidis (Bd) en áreas conservadas y degradadas. Se realizaron muestreos en tres hábitats (bosque, áreas abiertas y arroyos) en cuatro localidades entre los 2.000 y 3.200 m de altitud. Se registraron 14 especies de las cuales 12 fueron positivas para Bd; se diagnosticaron un total de 541 individuos de los que 100 resultaron positivos. Los análisis ponen de manifiesto que las áreas conservadas desempeñan un papel importante en el mantenimiento de un mayor número de individuos sin Bd en relación con las áreas degradadas. Este es el primer estudio en el que se evalúa la diversidad y la infección por Bd en la región nororiental de Colombia. Los resultados obtenidos pueden ayudar a mejorar nuestro conocimiento sobre la diversidad de especies de anfibios en la zona y facilitar la implementación de planes de acción encaminados a mitigar las causas asociadas con la disminución de las poblaciones de anfibios. Palabras clave: Anfibios, Conservación, Quitridiomicosis, Diversidad, Áreas naturales protegidas Received: 24 IV 14; Conditional acceptance: 21 VII 14; Final acceptance: 15 X 15 Aldemar A. Acevedo, Rosmery Franco & Diego A. Carrero, GIEB–Univ. de Pamplona, km 1 vía Bucaramanga, Pamplona, Norte de Santander, Colombia. Corresponding author: A. A. Acevedo. E–mail: bioaldemar@gmail.com ISSN: 1578–665 X eISSN: 2014–928 X

Acevedo et al.

Introduction At least one–third of the 6,260 amphibian species assessed by the International Union for the Conservation of Nature are globally threatened (Zippel & Mendelson, 2008). Additionally, 159 species may be extinct, and 38 are confirmed as extinct (IUCN, 2012). The loss of amphibian diversity is associated with multiple factors such as destruction of habitat, introduction of competitors or predators, pollution, and other environmental risks (Alford & Richards, 1999; Blaustein & Kiesecker, 2002; Collins & Storfer, 2003; Corn, 2005; Allentoft & O’Brien, 2010; Hof et al., 2011). The major cause of amphibian species’ decline towards extinction —occurring at an unprecedented rate in any taxonomic group in history— has been attributed to emerging diseases such as chytridiomycosis, caused by the fungus Batrachochytrium dendrobatidis (Bd) (Longcore et al., 1999; Daszak et al., 1999; Lips, 1999; Gardner, 2001; Lips et al., 2005; Skerratt et al., 2007). Batrachochytrium dendrobatidis colonizes the keratinized surfaces of larval amphibians causing mutations in the oral disk structures of larval mouthparts that limit feeding. In later stages, chytridiomycosis causes thickening in the epidermis of juvenile and adult amphibians that often results in suffocation and heart failure leading to death (Berger et al., 1998; Bosch, 2003). Few studies, however, have linked other threats with possible increases in Bd infection, which could synergistically facilitate the spread of this pathogenic agent, and together negatively impact the ecology and long–term survival of various species (Kiesecker et al., 2001; Blaustein et al., 2003; Burrowes et al., 2004; Pounds et al., 2006; Lampo et al., 2006b; Alford et al., 2007). Moreover, it has been documented that amphibian declines are also occurring in protected areas where human impact is very low or absent (Gardner, 2001; Stuart et al., 2004; La Marca, 2007). Colombia has 793 spp. of amphibians (Acosta–Galvis & Cuentas, 2016), ranking second place in amphibian diversity worldwide. As many as 275 of these species are under some level of threat, and 144 are data deficient (DD) (IUCN, 2012). As few studies have been conducted to date on the natural history, distribution, ecology and diversity of amphibians the process of assessing threats and documenting overall declines is limited, accounting for a lack of adequate management and conservation plans (Urbina–Cardona, 2008). At the regional level, the Department of Norte de Santander is a well–studied region, but there are great gaps in biological and ecological data that limit our knowledge of the conservation status of most species of amphibians in the region (Grant et al., 1994; Urbina–Cardona, 2008). Moreover, the number of species known to occur in Norte de Santander represents only 5.32% (38 spp.) of the amphibians described from Colombia (Acosta–Galvis, 2000; Armesto et al., 2009; Acevedo et al., 2011, 2013, 2014). This lack of information is due to multiple factors, such as political instability, societal problems, and lack of active herpetological research groups. This study was designed to develop an inventory of the amphibian biodiversity in Andean areas of the

Tamá National Natural Park (Tamá NNP) and to assess the conservation status of amphibians in this area, with particular emphasis on Bd infections. Our goal was to improve our knowledge about the richness of amphibian species in order to implement immediate action plans to mitigate the causes associated with their decline. Material and methods Study sites Tamá National Natural Park consists of 48,000 hectares and is located in the northeastern corner of Colombia, in the municipalities of Toledo and Herrán, Department of Norte de Santander. The temperature varies between 5–25°C, with elevations ranging from 350 to 3,450 m (Londoño, 2005). The study area was divided into four sampling localities (fig. 1): (1) Paramo of Tamá (7° 23' 31.04'' N–72° 23' 32.99'' W) at 3,200 m of elevation with a mean temperature of 10.3°C and relative humidity of 94.62%, the vegetation type is dominated by Espeletia brassicoidea, the following areas correspond to Andean and high Andean forests; (2) Orocué (7° 25' 7.44'' N–72° 26' 2.05'' W), located in the municipality of Herrán from 2,400 to 2,600 m of elevation, the mean temperature is 12.34°C, and the relative humidity is 97.19%; (3) Asiria de Belén (7° 18' 20.07'' N–72° 22' 21.73'' W), located in the municipality of Toledo at 2,700 m of elevation, with a mean temperature of 16.19°C and a relative humidity of 79.79%; and (4) Los Remansos (7° 21' 23.69'' N–72° 28' 18.84'' W), located in the municipality of Toledo from 2,000 to 2,300 m of elevation, with a mean temperature of 15.6°C and relative humidity of 94.27%. Fieldwork Between August 2010 and April 2011, we made monthly visits to Orocué, La Asiria, Los Remansos and the Paramo of Tamá, additional visits were conducted between February 2014 and August 2015. In each area, we took samples from three habitat types (Andean forests, streams and open areas). Sampling was conducted along three replicated linear transects within each habitat type, with a distance of 100 m long and 2 m wide, between 9:00 h–12:00 h, 14:00 h–16:00 h and 18:00 h–24:00 h. We looked for amphibians among leaf litter and under rocks and fallen trees using Visual Encounter Surveys–VES (Crump & Scott, 1994; Heyer et al., 1994; Urbina–Cardona et al., 2006; Caceres–Andrade & Urbina–Cardona, 2009). For each amphibian recorded we drew a circular area of 100 m in diameter around it, and we quantified the degree of habitat loss, measured as the percentage of non–natural vegetation cover (Becker & Zamudio, 2011). Amphibian swabbing We collected skin swabs to detect Bd on individual amphibians. We used a sterile swab (Fine Tip Sterile MW100–Medical Wire) to rub the groin, palms, fingers

Animal Biodiversity and Conservation 39.1 (2016)

–72.586792

–72.465264

–72.343736

–72.222208

–72.100680 Venezuela

7.458884

Orocué Páramo of Tamá

7.354678

Los Remansos

La Asiria

7.250472 Colombia 7.146266 N 7.042060

0 3.5 7

28 km

Fig. 1. Study area and sampling localities. Tamá National Natural Park, Colombia. Fig. 1. Área de estudio y localidades de muestreo. Parque Nacional Natural Tamá, Colombia.

and legs 30 times. Samples were stored at 4°C (Hyatt et al., 2007). Samples were processed in the Laboratory of Ecophysiology, Behavior and Herpetology at the Universidad de los Andes and the Laboratory of Ecology and Biogeography at the Universidad de Pamplona in Colombia, and conventional polymerase chain reaction (PCR) was used to identify Bd (Annis et al., 2004; Hyatt et al., 2007). We used the primers developed by Annis et al. (2004) to amplify the ITS1–ITS2 region specifically in B. dendrobatidis: Bd1a (5'– CAGTGTGCCATATGTCACG–3') and Bd2a (5’–CATGGTTCATATCTGTCCAG–3'). Data analysis Diversity analyses were performed assigning the samples to the different habitats (Andean forests, streams and open areas). Species richness was analyzed using coverage of extrapolation and interpolation of the collected species (Chao & Jost, 2012). For each habitat, we estimated 0D true diversity index (species richness), 1D represented by relative abundances Shannon (exp H') and 2D represented by abundant species (inverse of Simpson) (Jost, 2007). Prevalence of Bd was calculated by dividing the number of positive amphibians by the total number of amphibians sampled. To examine the structure of each habitat we constructed rank–abundance curves to compare patterns of abundance–dominance for the whole data

set and for the Bd infected amphibians alone. To identify differences between amphibian abundances we performed a Kruskal–Wallis analysis. Finally, we performed a Spearman rank correlation between the abundance of amphibian species diagnosed (positive and negative) in conserved areas (with a continuous Andean forest area) and degraded areas (fragmented forests, pastures, crops and forests is done burnt). Biosecurity protocols All biosecurity measures were applied throughout this investigation to prevent accidental spread of amphibian pathogens both among amphibians and places (Phillott et al., 2010). Each collected specimen was handled using a new pair of disposable gloves, and transported in separate bags. A bleach solution was used to wash all materials and clothes exposed to field amphibians or environmental substrates before leaving each study site. Results We recorded 541 individuals belonging to 14 species of five families. The family with the most species records and number of individuals was Craugastoridae (9 spp.), representing 81% of the individuals sampled in the Tamá NNP, followed by the families Plethodontidae (1 sp., 10%) and Hylidae (2 spp., 6%) (table 1).

Acevedo et al.

Table 1. Amphibian species recorded in the Tamá NNP, Colombia: HBd. Habitats with Bd prevalence; 1. Orocué; 2. Paramo of Tamá; 3. La Asiria; 4. Los Remansos; F. Andean forest; S. Streams; O. Open areas. (The letter in parentheses for each of the species represent its location in the rank–abundance, fig. 4.) Tabla 1. Especies de anfibios registradas en el PNN Tamá, Colombia: HBd. Hábitats con prevalencia de Bd; 1. Orocué; 2. Páramo del Tamá; 3. La Asiria; 4. Los Remansos; F. Bosque andino; S. Arroyos; O. Áreas abiertas. (La letra entre paréntesis en cada una de las especies representa su ubicación en el rango abundancia, fig. 4.)

Sites

Family

Species

Craugastoridae

Tachiramantis douglasi (g)

HBd

Pristimantis melanoproctus (j) X

Pristimantis mondolfii (k)

Pristimantis anolirex (f)

Pristimantis frater (h)

Pristimantis nicefori (l)

Pristimantis gryllus (i)

Pristimantis sp. 1 (m)

Pristimantis sp. 3 (n)

Hylidae

X X

0 4 5

Gastrotheca helenae (e)

Plethodontidae

Bolitoglossa tamaense (a)

The true diversity index 0D, which represents richness of species, shows that the Andean forest had the most effective species (9 sp.), followed by the open area (8 sp.), and finally streams (7 sp.) (fig. 3). The diversity of order 1D, represented by the most frequent species according to Shannon, indicated that the open area had the highest diversity with 4.9 effective species, leaving a maximum of 3.5 and 3.4 effective species for Andean forest and streams areas, respectively (fig. 3). Finally, the diversity index of order 2D, based

Centrolene daidaleum (d)

Diversity profiles

Hemiphractidae

The entire sampling for each habitat showed values of 92% for the Andean forest habitat, 86% for the stream habitat and 75% for the open area habitat, meaning that a representative proportion of amphibians in the Andean areas from the Tamá were captured (fig. 2). By comparing the richness (Sobs: number of species observed) between habitats we observed that the Andean forest had the highest abundance with nine species, followed by the open area with eight species. The stream area had seven species, and the richness observed as the estimate was similar, indicating no differences in habitat (df = 3, p = 0.058).

Centrolenidae

Species richness

Dendropsophus labialis (c) Dendropsophus pelidna (d)

on the species dominance according to the inverse of Simpson, revealed very similar trends to 1D, with the open area having the highest number of effective species (4.3). Streams and Andean forest areas showed differentiation based on common species, with Andean forest showing the highest equitability and open area showing the lowest equitability and highest dominance of two species (fig. 3). According to the order 0D, the highest contrast was between Andean forest, being 1.28 times more diverse than streams, and open areas covering 88% of the diversity of order 0D present in the Andean forest. Finally, based on the most frequent species in the Shannon index (exp H') of order 1D, the open area had 1.36 times more diversity than Andean forest and stream (fig. 3). Survey of Batrachochytrium dendrobatidis We found 100 individuals from 12 species were infected with Bd out of 541 (table 1). The locality of Los Remansos had the largest prevalence of Bd (30%, n = 132), followed by the locality of Paramo of Tamá (25%, n = 31), Asiria (22%, n = 23) and Orocué (12%, n = 29). The most prevalent species were Bolitoglossa tamaense (26%), Pristimantis mondolfii (22%) and Tachiramantis douglasi (9%) (table 1).

Animal Biodiversity and Conservation 39.1 (2016)

Sample coverage

0.8 0.6 0.4 0.2 0 5

10 15 Number of samples

Fig. 2. Plot of sample coverage for amphibian species, with 95% confidence intervals: l Andean forest; n Streams; • Open areas. Fig. 2. Cobertura de la muestra para las especies de anfibios, con intervalos de confianza del 95%: l Bosque andino; n Arroyos; • Áreas abiertas.

Pristimantis; moreover, T. douglasi was the most abundant followed by P. melanoproctus, P. mondolfii and P. gryllus. On the other hand, for the Stream habitat only B. tamaense presented high values of abundance,

Variations between the abundance of the species recorded for the Andean Forest were similar for both the non–infected (fig. 4A) and the infected species (fig. 4B), with high prevalence of species of the genus

Effective number of species

10 Open area

Andean forest

Streams

7 6 5 4 3 2 1 0

Fig. 3. Diversity profiles for three types of habitat (Andean forest, streams and open area) of Tamá NNP: 0 D. Species richness; 1D. Relative abundance, exp H'; and 2D. Abundant species. Fig. 3. Perfiles de diversidad para tres tipos de hábitat (bosque andino, arroyos y área abierta) del PNN Tamá: 0D. Riqueza de especies; 1D. Abundancia relativa, exp H'; 2D. Especies abundantes.

Acevedo et al.

Log_Abundance

Log_Abundance with Bd

2.6 2.4 2.2 2 1.8 1.6 1.4 1.2 1 0.8 0.6 0.4 0.2 0 1.6 1.4 1.2 1

Andean forest

Streams

Open areas

i h

j m

g k

0.8 0.6 0.4

b h

0.2

f a

Fig. 4. Rank–abundance distributions for amphibian species in habitats of Andean forest, streams and open areas at the Tamá NNP: A. Bd negative species; B. Bd positive species. (For the abbreviations of species, see table 1.) Fig. 4. Distribución de rango abundancia de las especies de anfibios presentes en los hábitats de bosque andino, arroyos y zonas abiertas en el PNN Tamá: A. Especies negativas para Bd; B. Especies positivas para Bd. (Para las abreviaturas de las especies, véase la tabla 1.)

both as infected and non–infected species; however, P. mondolfii and P. gryllus showed low values of abundance in both ranges, which is opposite to the results for the Andean forest. For the open areas, habitat species of the genus Dendropsophus were the most common, also having the highest abundance ranges of infection in such habitat, although some species of the genus Pristimantis and B. tamaense are less frequent in this habitat. Even though we observed differences in the variation of dominance of infected and non–infected species for Bd across habitats, such differences were not significantly different (x2 = 0.85, df = 1, p = 0.35). Bd infection: preserved vs. degraded areas Assessing the presence of positive and negative individuals for Bd in relation to the conserved and degraded areas, we observed a significant difference (ANOVA, F = 2.27, p = 0.05) for negative individuals for Bd (3.37 ± 0.5) and positive individuals for Bd (1.73 ± 0.5) recorded in the conserved areas (fig. 5). While in the degraded areas there were not significant

differences in the variation of positive and negative individuals for Bd (fig. 5). In addition, when comparing negative individuals from conserved areas with negative individuals from degraded areas, we observed a significant difference (ANOVA, F = 2.53, p = 0.05), which suggests conserved areas play an important role in limiting infection events (fig. 5). Discussion The high areas of the Tamá NNP (above 2,000 m) are home to a wide diversity of amphibians representative of the Andean areas of the Colombian northeast, with predominance of species of the families Craugastoridae, and to a lesser degree, Hylidae, Centrolenidae, Hemiphractidae and Plethodontidae. The Colombian Andean mountain range is considered one of the richest in amphibian diversity (Lynch, 1998). However, the Eastern mountain range has been considered one of mountain chains with least diversity of amphibians with approximately 131 species. The high number of endemic species is emphasized

Animal Biodiversity and Conservation 39.1 (2016)

4.29

F = 2.53, df = 3, p = 0.05

Abundance

3.51 2.74 1.96 1.10

Negative Bd Positive Bd Preserved

Negative Bd Positive Bd Degraded

Fig. 5. Spearman rank correlation between amphibians diagnosed (negative, positive) in preserved and degraded areas. Fig. 5. Correlación de rangos de Spearman entre anfibios diagnosticados (positivo y negativo) en áreas conservadas y degradadas.

(76 species) (Bernal & Lynch, 2008). However, the diversity of amphibians tends to decrease the higher the altitude (above 2,500 m), possibly associated with restrictive environmental conditions and physiological conditions for the amphibians (Navas, 1999, 2003). The Earth’s elevated transformation processes can generate drastic changes in the diversity and stability of Andean amphibian populations. The results of our evaluation of infection by Bd show a differential pattern between infection events that occur in preserved areas and those in areas with some degree of intervention. Here, preserved areas may play an important role in safeguarding several species and decreasing possible events of contagion, as is the case of species of the genus Pristimantis, Bolitoglossa, and Gastrotheca. This observation contrasts with the intervened areas where no significant differences were seen between the number of positive and negative individuals for Bd. These results support previous studies showing that loss of habitat is negatively associated with the occurrence of Bd, and the prevalence and intensity of infection in populations of tropical amphibians (Becker & Zamudio, 2011; Becker et al., in press). Therefore, the decreases that have occurred in pristine areas present a non–random pattern with regards to ecological preferences, geographic intervals and taxonomical groups of the species affected (Stuart et al., 2004; Skerratt et al., 2007). The conservation status of the landscape within Tamá NNP is considered to be good, with 70% of its forests in pristine condition (Londoño, 2005). However, most amphibian species reported in this study face ongoing threats, which vary in their long–term impacts on conservation. El Tamá NNP has moderate human disturbance due to agriculture, cattle, and deforestation (Garavito et al., 2012); the isolated forest

remnants have undergone modifications in their biotic components due to edge effects, potentially altering the distributional patterns of species and negatively impacting population dynamics (Marsh & Pearman, 1997). While the impacts of human activities are considered to be the major threats to amphibians living within Tamá NNP, this study indicates the fungus Batrachochytrium dendrobatidis (Bd), known to occur in 37 countries across five continents (Kriger & Hero, 2009) and cause rapid irreversible amphibian extinctions, is also a serious threat in the park. This study detected Bd in 12 out of 14 species. Moreover, the locality of Los Remansos has a high percentage of Bd infection in the three habitats. In the locality of Paramo of Tamá, the incidence of Bd was relatively low. The presence of Bd has not been well documented in Colombia even though the country has one of the richest diversities of amphibians in the world. None of amphibians showed external signs of chytridiomycosis disease from Bd, such as lethargy, abnormal body position, loss of reflexes, or anorexia (Berger et al., 1998). However, it is important to note that Bd is known to kill rapidly. Therefore this is the most alarming report of Bd infection in Colombia to date. The first report of Bd from Colombia was made from the histological inspection of 672 specimens preserved in scientific collections. However, only three of the 53 frog species examined were infected with Bd (Ruiz & Rueda–Almonacid, 2008). A second histological study was conducted in the Western Cordillera in the Department of Valle de Cauca, where 22 out of 466 individuals were infected with Bd (Velasquez et al., 2008). In the Eastern Andean region of Colombia, 222 amphibians were tested for the presence of Bd. Sixteen of the 222 individuals tested positive for Bd (Quintero, 2008). The most recent report from the

Central Andean, Eastern Orinoco, and Colombian Amazon analyzed 336 samples of 57 species, and three species were diagnosed as infected with Bd (Vasquez–Ochoa et al., 2012). Recent studies in the Venezuelan Andes (Hanselmann et al., 2004; Lampo et al., 2006a, 2006b) suggest that Bd has been present in the state of Mérida for the last 24 years and is currently at endemic levels in several species of amphibians (Sánchez et al., 2008). The possible expansion from the Venezuelan Andes to the northeastern area of the Colombian Andes could thus explain the cases of infection reported in this study. However, as historic comparative data about the levels of amphibians populations in the region are lacking, we cannot estimate the possible time span when Bd first appeared in the area. It is therefore essential to implement an epidemiological supervision plan for the species reported here. Such a plan could detect increases in the prevalence of infection in populations of amphibians that might indicate the appearance of an epidemic at an early stage, facilitating strategies or measures to lower the impact that this may have on amphibian population sizes and possible extinction events. Changes in vegetation cover due to accelerated anthropic processes may generate imbalances in the intrinsic response of each population of amphibians in Andean areas. Fragmentation of Andean ecosystems could consequently increase the rates of infection by Bd in amphibians of the high Andes. Thus, the generation of ecological restoration programs would function as an adequate strategy to buffer the accelerated effects of infection by Bd, allowing the recovery of species that are vulnerable to population decline. Acknowledgements Special thanks to Liliana Solano, Diego J. Lizano, Orlando Armesto and Karen Silva for their help in the Tamá Amphibians project. We also thank the Tamá Park rangers, especially Harold Valderrama and Cesar Leal, for logistical support. Thanks too to the Rico family and Gonzales Pabón family for their cooperation in field work, and Ted R. Kahn for comments and suggestions on this paper. Funding for this work was provided by La Universidad de Pamplona (Colombia grants 2013), the Conservation Leadership Programme and Save Our Species (project 0621310–2010) and Idea Wild for the donation of field equipment. References Acevedo, A., Franco, R. & Silva, K., 2014. Nuevos registros de especies del género Pristimantis (Anura: Craugastoridae) para el nororiente de Colombia. Revista de Biodiversidad Neotropical, 4: 162–169. Acevedo, A., Silva, K., Franco, R. & Lizcano, D., 2011. Distribución, historia natural y conservación de una rana marsupial poco conocida, Gastrotheca helenae (Anura: Hemipractidae), en el Parque Nacional Natural Tamá – Colombia. Bol. Cient. Mus. Hist.

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Isolation and characterization of novel polymorphic microsatellite markers for the white stork, Ciconia ciconia: applications in individual–based and population genetics S. Feldman Turjeman, A. Centeno–Cuadros & R. Nathan

Feldman Turjeman, S., Centeno–Cuadros, A. & Nathan, R., 2016. Isolation and characterization of novel polymorphic microsatellite markers for the white stork, Ciconia ciconia: applications in individual–based and population genetics. Animal Biodiversity and Conservation, 39.1: 11–16. Abstract Isolation and characterization of novel polymorphic microsatellite markers for the white stork, Ciconia ciconia: applications in individual–based and population genetics.— The white stork, Ciconia ciconia, is a model species for studies of bird migration and behavior, but previously published genetic markers are not informative enough to perform individual–based genetic studies. Following discovery using next generation sequencing, 11 polymorphic markers were selected and tested in samples from two study sites. The number of alleles per locus ranged from 2–10 with an average of 5.3. The mean observed and expected heterozygosities were 0.519 and 0.565 respectively. PID was adequately sensitive for population– and individual–based genetic studies. There was no significant evidence of allelic drop–out, null alleles, or other errors; one sample site deviated from Hardy–Weinberg equilibrium for two loci, but no loci deviated in both samples, suggesting utility of these markers. These markers can be used to answer a range of ecological questions including those related to genetic diversity, degree of natal philopatry, and genetic mating strategies. Key words: Genetic markers, Short tandem repeats, Relatedness, Probability of identity, Polymorphism, Genetic diversity Resumen Aislamiento y caracterización de nuevos marcadores de microsatélites polimórficos para la cigüeña blanca, Ciconia ciconia: aplicaciones de la genética basada en individuos y de poblaciones.— A pesar de que la cigüeña blanca, Ciconia ciconia, es una especie modelo en estudios de migración y comportamiento, los marcadores moleculares publicados hasta ahora no son lo suficientemente polimórficos para poder realizar estudios genéticos basados en el individuo. Utilizando la secuenciación de nueva generación hemos seleccionado 11 marcadores polimórficos y los hemos utilizado en cigüeñas de dos localidades de estudio. El número medio de alelos por locus fue de 5,3 con un mínimo de dos y un máximo de diez. La heterocigosidad media observada y esperada fue de 0,519 y 0,565, respectivamente. La PID (probabilidad de identidad) resultó ser suficientemente sensible para los estudios sobre genética basada en individuos y genética de poblaciones. No hemos encontrado evidencias de pérdida alélica, alelos nulos ni ningún otro error, y ningún locus estaba en desequilibrio de Hardy–Weinberg en ambas localidades a pesar de que dos loci sí que lo estuvieran en una única localidad. Estos marcadores son útiles para dar respuesta a una serie de preguntas relacionadas con la diversidad genética, el grado de filopatria y las estrategias genéticas de reproducción. Palabras clave: Marcadores moleculares, Repeticiones cortas en tándem, Parentesco, Probabilidad de identidad, Polimorfismo, Diversidad genética Received: 6 VII 15; Conditional acceptance: 29 X 15; Final acceptance: 4 XI 15 Sondra Feldman Turjeman, A. Centeno–Cuadros & R. Nathan, Movement Ecology Lab., Dept. of Ecology, Evolution and Behavior, Fac. of Life Science, Hebrew Univ., Jerusalem, Israel.– A. Centeno–Cuadros, Dept. of Molecular Biology & Biochemical Engineering, Univ. Pablo de Olavide, Seville, Spain. Corresponding author: Sondra Feldman Turjeman. E–mail: sondra.feldman@mail.huji.ac.il ISSN: 1578–665 X eISSN: 2014–928 X

Introduction The white stork, Ciconia ciconia, is a model species for studies of bird migration and behavior because of its long life span, suspected monogamy and philopatry, proximity to human settlements, ubiquity, ease of identification, and magnificent migratory journeys. Much is known about the species through observation and biotelemetry tracking, although these approaches might be biased (ring–resightings) or suitable for just a few tens of individuals because of high monetary investments and associated costs (e.g., tracking: data download, GPS trackers). While one population genetics study has been performed (Shephard et al., 2013), the mean number of alleles for the 18 populations considered was very low: 3.01 ± 0.75 (mean ± SD); furthermore, little is known about genetic mating strategies, nest fidelity, and levels of natal philopatry in white storks although these behaviors are relatively easy to study using a powerful set of molecular markers. Therefore, coordination between international research groups at the time of ringing (an annual occurrence at thousands of nests throughout Europe and the Middle East) in order to collect genetic samples (feather collection) and use of a highly polymorphic microsatellite panel can provide vast data useful for a variety of ecological and behavioral studies. A preliminary test of microsatellite markers published by Shephard et al. (2009), using genetic material from wild individuals, showed even lower polymorphism levels than originally reported. From the initial (published) panel of 13 microsatellites, only seven remained after removing markers where null alleles (n = 2), linkage disequilibrium (n = 1), and amplification issues (n = 3) were found. This reduced panel of largely dimorphic markers is insufficient to elucidate individual behavioral strategies and population dynamics in this model species. The development of new markers, pivotal to future genetic–based studies, is therefore essential. Here, we present 11 polymorphic markers —selected and tested in samples from two wild study sites— that can be used to answer a range of ecological questions on white storks. Material and methods We developed microsatellites using a next generation sequencing approach performed by EcoGene NZ: DNA–based diagnostics (Auckland, New Zealand) in 2013 from DNA extracted from blood samples of two white storks, one from a wild population in northern Israel and one from a wild population in northeast Germany. We discovered over 100 potentially polymorphic microsatellite loci with a throughput of 35M bases, an average read length of 441.6 base pairs, and a total of 170,969 reads (64,583 and 106,139 reads per run, respectively); primers were designed by EcoGene NZ using msatcommander (Faircloth, 2008). Sixty–four microsatellite loci were chosen based on size (optimal length was considered as

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100–350 base pairs) and number of bases repeated (loci with tetra–base repeat motifs were preferred). These 64 markers were tested for amplification and polymorphism with PCR using the M13 method for fluorescent labeling (Schuelke, 2000) in a subset of 94 stork samples (see below for sampling information). PCR was performed in 20 µL volumes with 2.7 µL DNA (1:20 dilution of an NaOH extraction; Zhang et al., 1994), 10 µL Taq Plus Master Mix 2x (Lamda Biotech; contains 1.5 mM MgCl2), 0.5 µL (final concentration: 0.25 µM) fluorescent–labeled M13 (either 6FAM or TAMRA), 0.5 µL (0.25 µM) reverse primer, 0.342 µL (0.0175 µM) forward primer, and 5.96 µL double distilled water. PCR conditions were as follows: an initial step at 94°C for five minutes followed by a 'touchdown' cycling program of 16 cycles with 92°C for 30 seconds; annealing for 30 seconds, starting at 60°C and decreasing by 1°C for each of the 16 cycles to 45°C; and 72°C for 30 seconds, followed by 30 cycles continued at an annealing temperature of 45°C, all followed by a final step at 72°C for 10 min. We also applied a similar 'touchdown' cycling from 55ºC to 45ºC with the last 30 cycles at an annealing temperature of 45ºC and/or increased MgCl2 concentrations to 2.5 mM for those loci that did not amplify (see table 1). Genotyping was performed using an ABI PRISM™ 3730 xl DNA Analyzer by the Hebrew University Center for Genomic Technologies (Jerusalem, Israel). Allele calling and binning were obtained using GeneMap per 4.0 software (Applied Biosystems, Foster City, CA, USA). Of the 64 loci initially tested, 11 loci were selected based on consistency of amplification and number of alleles per locus (Cc10, Cc15, Cc18, Cc37, Cc42, Cc44, Cc50, Cc58, Cc61, Cc69, and Cc72), and PCR conditions for these loci were then further optimized (see table 1). Following marker selection, we genotyped 213 individuals using the NaOH extraction method mentioned above. Feathers (five) were collected from juveniles from two sample sites prior to fledging; only one individual per nest was included in this analysis. Samples were collected in 2012 from northeast Germany (n = 152; center point of sampling: 52.7383o N, 11.6681o E) and in 2015 from eastern Greece (n = 61; center point of sampling: 41.0520o N, 25.1223o E). Following PCR amplification, genotyping, and scoring (as described above), and tests of Hardy–Weinberg equilibrium (Cervus 3.0.3; Kalinowski et al., 2007) were performed as were tests of genotyping error (GIMLET; Valière, 2002), null alleles (FreeNA; Chapuis & Estoup, 2007), allelic drop–out (GIMLET), inbreeding (FIS; Genetix 4.05.2; Belkhir et al., 2004), linkage disequilibrium (GENEPOP with Bonferroni correction for significance; Raymond & Rousset, 1995; Rousset, 2008), and genetic structure (FST; Genetix 4.05.2). Rates of expected and observed heterozygosities, the mean polymorphic information content (PIC) and PID and PID–Sib (probability of identity, the likelihood that two unrelated or sibling–related individuals, respectively, will have the same genotype profile by chance) were also calculated (Cervus 3.0.3).

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Table 1. Characterization of 11 species–specific microsatellite loci with conditions for PCR optimization based on 213 individuals from Germany (n = 152) and Greece (n = 61). Primer sequences (F. Forward, R. Reverse; *M13 Sequence: 5'–TGTAAAACGACGGCCAGT–3'); RM. Repeat motif; GB. GeneBank accession number; TD. 'Touchdown' annealing temperatures (ºC); T[MgCl2]. Final MgCl2 concentration in PCR reaction (mM); SR. Size range (bp); Na. Number of alleles; HObs. Observed heterozygosity; HExp. Expected heterozygosite; PIC. Polymorphic information content (PIC). Tabla 1. Caracterización de 11 loci de microsatélites específicos de una especie con condiciones de optimización de la PCR basada en 213 individuos de Alemania (n = 152) y Grecia (n = 61). Secuencias del cebador (F. Adelante, R. Atrás; *Secuencia de M13: 5'–TGTAAAACGACGGCCAGT–3'); RM. Secuencia repetida; GB. Número de acceso a GeneBank; TD. temperaturas de hibridación de la PCR con rampa decreciente de temperaturas; T[MgCl2]. Concentración final de MgCl2 en la PCR (mM); SR. Intervalo de longitud (pares de bases); Na. Número de alelos; HObs. Heterocigosidad observada; HExp. Heterocigosidad esperada; PIC. Índice de contenido polimórfico. Locus primer sequences (5'–3')

T[MgCl2]

HObs

HExp

PIC

0.804

0.774

0.136

0.127

0.471

0.359

0.57

0.485

0.468

0.437

0.524

0.429

0.448

0.42

0.768

0.729

0.572

0.476

0.827

0.802

Cc10 F–M13–TGTGACAGATGCAAAGCTCC R–GTGTTTACTAGTTGGCTGTTCC (AGAT)9

KT232056

60–45

1.5

95–147

0.784

Cc15 F–M13–ATAGCAACGATGTTCCACCC R–AAACCCAGCTTTGTTCTGCC (AAAC)8

KT232057

60–45

1.5

155–159

0.118

Cc18 F–M13–AGGGTGGTTATGTGCTCAGG R–ACTCTGACTGGGATGTGCTC (ACAT)6

KT232058

60–45

1.5

237–287

0.468

Cc37 F–M13–CCTGCCTGACAAGAGAATGC R–GCAAGTGTATCAGTCCAAATGG (AC)8

KT232059

60–45

1.5

244–252

0.512

Cc42 F–M13–GCAGGAAAGGAGGAAAGGTG R–GCATCACAGTATGCAAACGC (AGAT)8

KT232060

60–45

2.5

286–346

0.49

Cc44 F–M13–TGCATCCTTTGTCTTGCCAG R–CTGCCCTCCTGATATGTCCC (ACAG)6

KT232061

60–45

1.5

331–339

0.525

Cc50 F–M13–CTAATCTGTCCTGCCCTCCC R–CACAGAGCCAGCAAGACAAG (AC)10

KT232062

60–45

2.5

209–215

0.335

Cc58 F–M13–ACGAGGGTTGCTTAAGGAGG R–AAATCTGTGCGCCAACTCAC (AC)16

KT232063

60–45

2.5

245–265

0.662

Cc61 F–M13–GCTGCCTGACCAAGAGAAAC R–TCCTGCTTGTTTCCTTCCTC (AC)9

KT232064

55–45

Cc69 F–M13–ACAATGCCTGGACCACAATG (AT)12

KT232065

55–45

2.5

265–271

0.545

R–CTCATTCTTGGCACGAACCC 2.5

312–322

0.638

Cc72 F–M13–CATTGAAGATACTGGGCAGCC R–GATCCCTTCATCACCAGCAG (AT)8 Mean

KT232066

60–45

1.5

Results Overall polymorphism for the two samples together ranged from two to ten alleles per locus, with a mean of 5.3 alleles and a median of 5 (see table 1 for overall values; see table 2 for data regarding the two populations). Observed and expected heterozygosi-

216–228

0.634

0.621

0.569

5.3

0.519

0.565

0.510

ties ranged from 0.118–0.784 and 0.136–0.827, respectively, with overall mean observed and expected heterozygosities of 0.519 and 0.565. The mean PIC was 0.510 and the PID and PID–Sib were 0.00000005 and 0.0007678, respectively. Two markers, Cc15 and Cc18, had low polymorphism but had a positive influence on PID (see Discussion). Removing

Feldman Turjeman et al.

Table 2. Summary of locus diversity (L) and panel specificity per study site: SR. Sample region (Ge. Germany, Gr. Greece); Na. Number of allelles; HObs. Observed heterozygosity; HExp. Expected heterozygosity; PIC. Polymorphic information content; HWE. Deviations from Hardy–Weinberg equilibrium (NS. Not significant, ND. Not performed; * 0.01 < p < 0.05; ** 0.001 < p < 0.01; *** p < 0.001); Ni. Number of individuals; MT. Mean proportion typed. Tabla 2. Resumen de la diversidad de locus (L) y especificidad del panel por lugar de estudio: SR. Región de la muestra (Ge. Alemania, Gr. Grecia); Na. Número de alelos; HObs. Heterocigosidad observada; HExp. Heterocigosidad esperada; PIC. Índice de contenido polimórfico; HWE. Desviaciones del equilibrio de Hardy–Weinberg (NS. No significativo, ND. No realizado; * 0,01 < p < 0,05; ** 0,001 < p < 0,01; *** p < 0,001); Ni. Número de individuos; MT. Proporción media de individuos genotipados. L

Cc10 All

HObs HExp

PIC

HWE

7 0.784 0.804 0.774

Ge 7 0.816 0.810 0.780

SR Na

Cc50 All

HObs

HExp

PIC

HWE

5 0.335 0.448 0.420

Ge 5 0.333 0.449 0.420

7 0.705 0.785 0.745

3 0.339 0.426 0.374

0.118 0.136 0.127

Cc58 All 10 0.662 0.768 0.729

***

Ge 2 0.079 0.101 0.095

Ge 10 0.685 0.779 0.743

***

2 0.217 0.221 0.195

8 0.603 0.723 0.666

Cc18 All

2 0.468 0.471 0.359

Cc61 All

Ge 2 0.483 0.457 0.352

Cc15 All

3 0.545 0.572 0.476

Ge 3 0.577 0.575 0.479

2 0.429 0.499 0.372

3 0.467 0.561 0.464

Cc37 All

5 0.512 0.570 0.485

Cc69 All

8 0.638 0.827 0.802

***

Ge 5 0.500 0.585 0.507

Ge 6 0.698 0.757 0.713

4 0.542 0.526 0.410

6 0.479 0.676 0.610

Cc42 All

7 0.490 0.468 0.437

Cc72 All

6 0.634 0.621 0.569

Ge 7 0.470 0.458 0.423

Ge 6 0.699 0.651 0.594

7 0.544 0.497 0.466

Cc44 All

3 0.525 0.524 0.429

Ge 3 0.549 0.515 0.432

SR (all loci)

3 0.466 0.521 0.400

6 0.464 0.513 0.469

Na (mean)

HObs (mean)

HExp (mean)

PIC (mean)

Combined PID

Combined PID–SIB

All

5.3

0.519

0.565

0.510

0.00000005

0.0007675

213

0.9522

Germany

5.1

0.535

0.558

0.504

0.00000008

0.0008538

152

0.9563

Greece

4.6

0.478

0.541

0.470

0.00000046

0.0013198

0.9419

these markers from the analysis resulted in slight shifts in the overall mean observed and expected heterozygosities to 0.512 and 0.581, respectively; PIC was 0.512. We found no consistent significant evidence of genotyping error, null alleles, or allelic drop–out in either sample (see table 3). When grouping the two samples together, Cc50 and Cc58 deviated from Hardy–Weinberg equilibrium (HWE), but individually, only the sample from northeast Germany exhibited

this deviation (see table 2). Furthermore, no evidence of linkage disequilibrium was found across the two samples or for a single study site across all loci (see table 3). Heightened inbreeding was found in the Greek sample from high FIS, a deficit of heterozygosity, and a high frequency of null alleles compared to the German sample. Overall, there was significant genetic structure between study sites (FST = 0.04877, p–value < 0.001; permutations test, 1,000 permutations; see table 3).

Animal Biodiversity and Conservation 39.1 (2016)

Table 3. Summary of tests of genetic structure, proportion of null alleles, allelic drop–out, inbreeding, and linkage disequilibrium: † For 1,000 permutations (* 0.01 < p < 0.05; ** 0.001 < p < 0.01; *** p < 0.001); †† Based on pairs of retyped individuals (n = 19–38, mean ± SD 28.55 ± 08.02); ††† Bonferroni correction (α/55 = 0.000909091). Tabla 3. Resumen de las pruebas de estructura genética, alelos nulos, pérdida de alelos, endogamia y desequilibrio de ligamiento: † Para 1.000 permutaciones (* 0,01 < p < 0,05; ** 0,001 < p < 0,01; *** p < 0,001); †† Basado en pares de individuos que se volvieron a genotipar (n = 19–38, mean ± DE 28.55 ± 08.02); ††† Corrección de Bonferroni (α/55 = 0.000909091).

Genetic structure FST† Ge vs. Gr

Cc10

Proportion of null alleles Ge

Allelic

Inbreeding FIS†

drop–out††

Ge –0.00777

Linkage disequilibrium††† Ge

0.10261*

0.02716**

0.00001

0.03724

0.000

Cc15

0.00900

0.04774

0.00324

0.000

0.21122

0.01793

Cc18

0.03098*

0.00002

0.04425

0.000

–0.05765

0.14174

Cc37

0.03179**

0.08457

0.00001

0.000

Cc50, Cc58

Cc42

0.00448

0.00001

0.00000

0.077

–0.02735

–0.09492

Cc44

0.01337

0.00001

0.02865

0.000

–0.06596

0.10757

Cc69

Cc50

0.03346**

0.09735

0.06924

0.000

0.25843*** 0.20657* Cc58, Cc37

Cc58

0.00034

0.05805

0.05039

0.000

0.12153**

Cc61

0.00405

0.01796

0.05980

0.000

Cc69

0.23773***

0.03976

0.11330

Cc72

0.01420*

0.00000

0.01632

–

Overall 0.04877***

0.14499* –0.03082

0.16632*

Cc50, Cc37

–0.00343

0.16964

0.000

0.07815

0.29346**

Cc44

0.000

–0.07271

0.09580

–

Discussion We successfully characterized a novel, polymorphic set of microsatellite markers for the white stork. When comparing mean number of alleles per locus (MNA = 5.3) and mean expected heterozygosity (HExp = 0.565) from this marker discovery with that from the set of markers originally published (MNA = 3.5; HExp=0.41; Shephard et al., 2009), this new set of markers is more polymorphic, has greater heterozygosity, and thus heightened power in genetic studies. Furthermore, the PIC is considered at least moderately informative (Hildebrand et al., 1992), the PID is highly informative for population–based and individual–based studies, and PID–Sib is moderately to highly informative (Waits et al., 2001) and more so when used in conjunction with markers previously reported (PID–Sib < 0.0001; Feldman et al., in preparation); alone, PID–SIB for these markers is sufficient for individual–based sibship studies. Although marker Cc15 and Cc18 have only two alleles and Cc15 has low observed and expected heterozygosities (0.118 and 0.136, respectively), removing these loci from the panel substantially increased the likelihood that two sibling–related individuals would share the same genotype profile by chance (change in PID–Sib from 0.0007678 to

0.04036*

0.11760***

0.0027647). We thus decided to include them in the final panel due to their utility in individual–based relatedness studies. Deviations in HWE were not seen in both samples for any markers and in cases where deviation was found, a sample–level explanation was also present (e.g., inbreeding at the given locus was also found). We thus concluded that all the markers are well suited for genetic–based studies and any deviations are likely due to sample site characteristics. The FST between the German and Greek samples implies that the samples are significantly different, suggesting a weak genetic differentiation between these two regions. This differentiation was not found by Shephard et al. (2013) in comparisons of multiple populations using the previously published panel of markers (overall FST = 0.005; p–value > 0.05). We believe this difference shows the greater sensitivity of the newly developed panel of markers. This set of markers, either alone or in combination with markers previously tested in this species, allows researchers to distinguish between genotypes at the individual level, thus providing a tool for relatedness studies in addition to more exact population genetics studies. By adding these markers to the white stork molecular tool kit, questions at both the within– and between–population scales related to reproduction,

nest fidelity, migration flyway segregation, and plasticity of philopatry can be much more feasibly and accurately assessed. Acknowledgements We would like to acknowledge the contribution of Ute Eggers, Shay Rotics, and all the volunteers and ringers in Germany for helping in sample collection. Additional thanks to Eva Stents, Eleni Makrigianni (Management Body of National Park Delta Evros), Lila Karta (Management Authority of Lakes Koroneia–Volvi), and Sasa Michailidou (Management Body of National Park Delta Nestos Lakes Vistonida–Ismarida) for providing genetic samples from Greece. We acknowledge the generous funding of DIP grants (DFG) NA 846/1–1 and WI 3576/1–1 to RN, Florian Jeltsch, and Martin Wikelski. This study was also supported by the Minerva Center for Movement Ecology granted to RN. We would also like to express our gratitude to Meira Shlepakov of the Hebrew University Center for Genomic Technologies for her genotyping work. References Belkhir, K., Borsa, P., Chikhi, L., Raufaste, N. & Bonhomme, F., 2004. GENETIX 4.05, Population genetics software for WindowsTM. Université de Montpellier II, Montpellier. Chapuis, M. P. & Estoup, A., 2007. Microsatellite null alleles and estimation of population differentiation. Molecular Ecology, 24: 621–631. Faircloth, B. C., 2008. msatcommander: detection of microsatellite repeat arrays and automated, locus–specific primer design. Molecular Ecology Resources, 8: 92–94. Hildebrand, C. E., Torney, D. C. & Wagner, R. P., 1992. Informativeness of polymorphic DNA markers. Los

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Alamos Science, 20: 100–102. Kalinowski, S. T., Taper, M. L. & Marshall, T. C., 2007. Revising how the computer program CERVUS accommodates genotyping error increases success in paternity assignment. Molecular Ecology, 16: 1099–1106. Raymond, M. & Rousset, F., 1995. GENEPOP (version 1.2): Population genetics software for exact tests and ecumenicism. Journal of Heredity, 86: 248–249. Rousset, F., 2008. GENEPOP'007: a complete reimplementation of the GENEPOP software for Windows and Linux. Molecular Ecology Resources, 8: 103–106. Sambrook, J. & Russell, D. W., 2001. Molecular Cloning: A Laboratory Manual. Cold Spring Harbor Laboratory Press, New York. Schuelke, M., 2000. An economic method for the fluorescent labeling of PCR fragments. Nature Biotechnology, 18: 233–234. Shephard, J. M., Galbusera, P., Hellemans, B., Jusic, A. & Akhandaf, Y., 2009. Isolation and characterization of a new suite of microsatellite markers in the European White Stork, Ciconia ciconia. Conservation Genetics, 10: 1525–1528. Shephard, J. M., Ogden, R., Tryjanowski, P., Olsson, O. & Galbusera, P., 2013. Is population structure in the European white stork determined by flyway permeability rather than translocation history? Ecology and Evolution, 3: 4881–4895. Valière, N., 2002. GIMLET: A computer program for analysing genetic individual identification data. Molecular Ecology Notes, 2: 377–379. Waits, L. P., Luikart, G. & Taberlet, P., 2001. Estimating the probability of identity among genotypes in natural populations: cautions and guidelines. Molecular Ecology, 10: 249–256. Zhang, Q., Tiersch, T. R. & Cooper, R. K., 1994. Rapid isolation of DNA for genetic screening of catfishes by polymerase chain reaction. Transactions of the American Fisheries Society, 123: 997–1001.

Animal Biodiversity and Conservation 39.1 (2016)

Dramatic decline of the bearded reedling, Panurus biarmicus, in Spanish Mediterranean wetlands R. Belenguer Barrionuevo, G. M. López–Iborra, J. I. Dies & J. Castany i Alvaro

Belenguer Barrionuevo, R., López–Iborra, G. M., Dies, J. I. & Castany i Alvaro, J., 2016. Dramatic decline of the bearded reedling, Panurus biarmicus, in Spanish Mediterranean wetlands. Animal Biodiversity and Conservation, 39.1: 17–27. Abstract Dramatic decline of the bearded reedling, Panurus biarmicus, in Spanish Mediterranean wetlands.— The appa� rent stability of the bearded reedling in Spanish inland wetlands contrasts with its threatened status in Spanish coastal wetlands. The species has already disappeared from some coastal areas in Catalonia and its situation is critical in the region of Valencia. In 2013 we studied the breeding populations in three wetlands in Valencia using two methods: census by exhaustive search of individuals (territory mapping) and distance sampling using line transects. We estimated the trend of these populations from data obtained in previous censuses (2005 and 2006), and assessed their viability in the medium and short term using count–based population viability analysis (PVA). Results were alarming in the three studied wetlands, especially in the Albufera de Valencia, where only one breeding pair was found. The percentage of decrease of estimated pairs was similar in all wetlands: ca. 90% between 2005 and 2013. Results from the PVAs predicted a 90% probability of reaching the quasi–extinction threshold before 2024 or 2028 for the largest population of bearded reedling in the Valencia region, El Hondo, while for the Santa Pola population this threshold would be reached before 2016 or 2017. The parallel trend and generalized decline in the Spanish coastal wetlands suggests that these Mediterranean wetlands probably share some specific factors that have adversely affected their populations. Given that all these natural spaces are surrounded by intensively irrigated crops that are subjected to the intense use of pesticides, we hypothesize that these products could have had a detrimental effect on the bearded reedling. This hypothesis is supported by the fact that the healthiest populations are situated in Iberian inland wetlands that are surrounded by dry crops where the use of pesticides is less intense. We propose cataloguing the species as Endangered at regional level. Key words: Panurus biarmicus, Population decline, Censuses, Coastal wetlands Resumen Descenso acusado del bigotudo, Panurus biarmicus, en el litoral mediterráneo español.— La delicada situación del bigotudo en los humedales litorales españoles contrasta con la aparente estabilidad de la especie en los humedales interiores. La especie ha desaparecido de algunos enclaves costeros de Cataluña y su situación es crítica en la Comunidad Valenciana. En 2013 estimamos las poblaciones reproductoras en tres humeda� les de esta última comunidad usando dos métodos: un censo mediante búsqueda exhaustiva de individuos reproductores (mapeo de territorios) y un muestreo de distancia mediante transectos. Además, con los datos obtenidos en censos anteriores (2005 y 2006) estimamos la tendencia de estas poblaciones y calculamos su viabilidad a corto y medio plazo mediante un análisis de viabilidad poblacional (AVP) basado en conteos. Los resultados fueron muy preocupantes en los tres humedales estudiados, especialmente en La Albufera de Valencia, donde tan solo se encontró una pareja reproductora. El porcentaje de disminución de las parejas estimadas entre 2005 y 2013 en todos los humedales fue muy parecido, alrededor del 90%. Los resultados de los AVP para la mayor población de la Comunidad Valenciana, El Hondo, predicen un 90% de probabilidad de alcanzar el umbral de cuasi–extinción antes de 2024 o 2028, según el método de censo empleado. En el caso de Santa Pola, este umbral se alcanzaría antes de 2016 o 2017. El descenso generalizado y paralelo

ISSN: 1578–665 X eISSN: 2014–928 X

Belenguer Barrionuevo et al.

en los humedales costeros españoles sugiere que probablemente estos hábitats comparten algunos factores específicos que han afectado negativamente a sus poblaciones de bigotudo. Puesto que todos estos espa� cios naturales están rodeados de cultivos intensivos de regadío sometidos a un elevado uso de plaguicidas, hipotetizamos que estos productos podrían haber tenido un efecto perjudicial en el bigotudo. Esta hipótesis se ve apoyada por el hecho de que las poblaciones más saludables están situadas en el interior peninsular, en humedales rodeados de cultivos de secano, en los que el uso de plaguicidas es menos intenso. Se propone recatalogar la especie a escala regional como En Peligro de Extinción. Palabras clave: Panurus biarmicus, Descenso poblacional, Censos, Humedales litorales Received: 1 VII 15; Conditional acceptance: 9 IX 15; Final acceptance: 9 XI 15 Roque Belenguer Barrionuevo & Germán M. López–Iborra, Depto. de Ecología, Univ. de Alicante, Apdo. de correos 99, 03080 Alicante, Spain.– J. Ignacio Dies Jambrino, Brigada de Calidad Ambiental, Servicio Devesa– Albufera del Ayuntamiento de Valencia, ctra. CV–500 km 14,5, 46012 Valencia, Spain.– Joan Castany i Alvaro, Associació Grup Au d’ornitologia, c/Mestre Ripollés 40, 24, 12003 Castelló, Spain. Corresponding author: R. Belenguer Barrionuevo. E–mail: roque.belenguer@ua.es

Animal Biodiversity and Conservation 39.1 (2016)

Introduction Mediterranean reed–beds of common reeds, Phragmites australis, are particularly sensitive habitats with a high value for biodiversity conservation in Europe (Bibby & Lunn, 1982; Barbraud et al., 2002; Martínez–Vilalta et al., 2002; Poulin et al., 2002). They play an important role in the reproduction of many endangered passerine species, such as the moustached warbler, Acrocephalus melanopogon, the aquatic warbler, Acrocephalus paludicola, and the Eastern Iberian reed bunting, Emberiza schoeniclus witherbyi (Atienza & Copete, 2004; Castany & López, 2004; Tanneberger et al., 2010). In recent years the extension and quality of this habitat in Europe has decreased for several reasons, mainly due to threats of human origin, such as pes� ticides, eutrophication, changes in land uses, altera� tions in water levels, and salinization (Poulin et al., 2002; López–Iborra & Monrós, 2004; Valkama et al., 2008). The reduction of reed–beds is one of the great� est threats for their dependent bird communities. The decrease and fragmentation of bird populations, along with the scarce exchange of individuals between these populations, could lead to loss of genetic diversity by endogamy, thereby reducing fitness (Johnson, 2001). The bearded reedling, Panurus biarmicus, is a passerine occurring throughout Asia and Europe that lives in dense and well–preserved reed–beds (Rob� son, 2007). The European population is estimated at 240,000–480,000 breeding pairs, of which only around 1000 are found in Spain, inhabiting three main areas: Mediterranean coastal wetlands, inland wetlands in La Mancha, and northern small lakes (López–Iborra & Monrós, 2003; Birdlife International, 2012). In the Spanish Mediterranean coast, the bearded reedling appears irregularly in reed–beds from Catalonia to the south of Alicante, its southern limit of distribution in Europe. Until recently, it bred in the wetlands of l’Empordà, Utxesa, Ebro Delta, Albufera de Valencia, Salinas de Santa Pola and El Hondo (López–Iborra & Monrós, 2003). However, the main population in Catalonia (Ebro Delta) has reached extinction in the last decade, and populations reported for the wetlands in the Valencia region are small (López–Iborra et al., 2007). These Mediterranean populations seem to be virtually isolated because there is no evidence of movements of individuals between them (García–Peiró & López–Macià, 2002; López–Iborra & Monrós, 2004). Given the concern regarding the situation of the species in Iberian Mediterranean wetlands it is neces� sary to periodically evaluate the size of populations in order to adopt conservation measures if needed. This task is complicated by the lack of a standardized methodology for use by diverse authors and repea� ted over time to obtain comparable results. Bearded reedling populations have been estimated by territory mapping in England (Gilbert et al., 1998; Ogilvie et al., 2004) and by line transects in Spain (López–Iborra et al., 2007). In the latter case, the mean density calculated for reed–beds or other potential habitats is extrapolated to the total area of these habitats in the studied wetlands. However, to our knowledge, the reliability of this approach has not been tested in

wetlands. Thus, the main objectives of the present study were (1) to estimate the breeding populations in the study area using two methods: census by exhaustive search of individuals (territory mapping) and distance sampling using line transects, and (2) to assess the viability of the remaining Spanish po� pulations nesting in coastal Mediterranean wetlands in the medium and short term. Material and methods Study area This work was undertaken in the natural parks of Albufera de Valencia (39º 20' N, 0º 21' W), Salinas de Santa Pola (38º 11' N, 0º 38' W) and El Hondo (38º 11' N, 0º 45' W). All of three parks are protected wetlands on the Spanish Mediterranean coast (fig. 1). Albufera de Valencia is a shallow coastal lagoon situa� ted south of Valencia city. Salinas de Santa Pola and El Hondo belong to an ancient lagoon south of the Alicante province. Santa Pola is taken up by artificial salt lakes built for sea salt production and game and fishing estates. El Hondo is occupied by two major re� gulating irrigation reservoirs and smaller ponds placed around the main ones. The predominant vegetation is the common reed in all the wetlands, but southern cattail, Typha domingensis, great fen–sedge, Cladium mariscus, and rushes, Juncus spp., Scirpus spp. form some significant patches in Albufera de Valencia. Population estimates Transects were performed by walking close to the pond shores in Salinas de Santa Pola and El Hondo and by using a small boat in Albufera de Valencia. All potential habitats formed by reed–beds surrounding the major water bodies were sampled. Transects were aimed at covering the species' potential habitats during the breeding season (April to June) of 2005, 2006 and 2013. All transects were visited once in 2005 and 2006 (López–Iborra et al., 2006, 2007) and twice in 2013 (see location and length of transects in figure 1 and table 1). All passerines were counted and their perpen� dicular distance to the transect line was estimated. The distribution of these distances was used to fit a detection function that estimates detection probability and species density, under a number of assumptions, using the software DISTANCE 6.0 (Buckland et al., 2001; Thomas et al., 2010). The detection curve was fitted using two of the key functions available in the software, half–normal and uniform, and cosine series expansion. Akaike Information Criterion (AIC) was used to select which of the two provided the best fit (Burnham & Anderson, 2002). We calculated 84% and 95% confidence intervals that robustly mimic 0.05 and 0.01 α values in statistical tests, respectively, for asymmetric confidence intervals (MacGregor–Fors & Payton, 2013). The reed–bed patches (including southern cattail and great fen–sedge when present)

Belenguer Barrionuevo et al.

were digitized from 1:5,000 orthophotos, resulting in 773 hectares in El Hondo, 212 in Santa Pola and 121 in Albufera de Valencia. Territory mapping was carried out only in April and May of 2013. All the potential habitats were exhaus� tively searched in an attempt to locate the maximum number of bearded reedlings. In El Hondo and Albu� fera de Valencia, routes were made by boat, carefully prospecting the perimeter of the lagoons and large reed islands twice during the breeding season. A total distance of 73 km was covered in El Hondo and 21 km in Albufera. We also surveyed 29 points uniformly dis� tributed through potential habitats in El Hondo, where the habitat is more closed and inaccessible than in the other studied wetlands, to discard the presence of birds that could have gone unnoticed during the censuses. Five–minute observations, with song and call broadcasting, were performed at these points, following the method described in Atienza (2006).

which is reasonable in small declining populations that are well below the carrying capacity, as is the case here. To apply this model we used the popbio package (Stubben & Milligan, 2007) in R (R Development Core Team, 2009). We estimated instantaneous population growth rate and variance for each wetland applying the regression procedure described in Morris & Doak (2002) for variable time intervals between censuses. As in the previous method, we considered a quasi– extinction threshold of two individuals. Both methods were applied three times in each locality, using the population size obtained in each study year as the initial population. The exception was Albufera, where population in 2013 had reached the quasi–extinction threshold (one pair). For simulations starting in 2005 and 2006 we used the population estimated from transects but for 2013 we used the results from exhaustive censuses.

Population viability analysis

Results

We evaluated quasi–extinction likelihoods of the bearded reedling at every wetland by extrapolating population trends from available census data (the so called count–based population viability analysis; Morris & Doak, 2002). For this purpose we used two methods. In the first, we estimated the instantaneous population growth rate (r) between two consecutive censuses using the equation

Population estimate

r = (ln(Nt+a) – ln(Nt))/a where Nt is the population size in year t and a is the number of years between two consecutive censuses in the same wetland. We used the results of the po� pulation estimates of 2005 and 2006 (López–Iborra et al., 2006, 2007) and 2013, obtaining a total of six estimates of r (two per wetland). Population decline was simulated by multiplying the estimated number of pairs in each wetland by the value of λ λ = er where the value of r was randomly selected between the six estimates previously described. This process was iterated to simulate a 50–year period. Since the declining rate was very similar between wetlands (see results) we considered that these six estimates repre� sent a sample of the existing variability in instantaneous population growth rate in the set of studied wetlands. We repeated this procedure 1,000 times and recorded the year when the population reached two individuals, considered as the quasi–extinction threshold. The second method we applied was the diffusion model of Morris & Doak (2002), which estimates the extinction probability from the instantaneous population growth rate and its variance. These parameters were obtained from the series of abundance estimates (2005, 2006, and 2013) at each wetland. This model assumes that these parameters are constant over time, so that the resulting extinction probability corresponds to that expected if the population trend does not change, a condition shared with the previous model. Additionally, it is supposed that density–dependence does not exist,

To estimate density, we first fitted a different detection probability to the original distance data at every loca� lity (all years pooled) using the half–normal function. The Kolmogorov–Smirnov test for the q–q graphic was not–significant at any locality (p > 0.4), nor was the x2–test for any distance interval defined by the program (p > 0.18 in the worst case), so we worked with the original distances recorded in the field. The detection probabilities estimated by these models were very similar between localities (Albufera: 0.386; El Hondo: 0.383; Santa Pola: 0.383) and showed considerable overlap in their confidence intervals. We then fitted models with the same detection probability for all the study wetlands and tested the uniform and half–normal functions. The uniform function produced a lower AIC value, although the difference with the half–normal function was small (0.89), so the former was used to estimate density and population size for each year. The detection probability estimated by this model was 0.381 (confidence interval 95%: 0.336–0.437). Densities were similar in the three wetlands. No sta� tistically significant differences were found regarding density with the exception of Albufera in 2013, when no bearded reedlings were detected in the transects (table 2). Comparing years within wetlands, the 2005 and 2006 densities were not statistically different, according to the 84% confidence intervals (p < 0.05). However, the 84% confidence intervals for density in 2013 did not overlap with those of 2006, indicating a significant decrease between these years. The decrease in estimated pairs during these years was similar in the three wetlands: 88.9% in Albufera de Valencia (considering in this place the pairs estimated in 2013 by territory mapping), 86.6% in El Hondo, and 92.3% in Salinas de Santa Pola. Population sizes estimated in 2013 using the terri� tory mapping method were similar to those estimated from transects and well within their confidence inter�

Animal Biodiversity and Conservation 39.1 (2016)

0 0.5 1 km

4500000

Spain

1 2 3

0.5

1 km

a Se an e n a err dit Me

4000000

100000

600000

Fig. 1. Distribution of the transects in each wetland (black lines on aerial photographs) and location of the studied wetlands in SE Spain: 1. Albufera de Valencia; 2. El Hondo; 3. Salinas de Santa Pola. Fig. 1. Distribución de los transectos en cada humedal (líneas negras en las fotografías aéreas) y localización de los humedales estudiados en el SE de España: 1. Albufera de Valencia; 2. El Hondo; 3. Salinas de Santa Pola.

vals in El Hondo and Santa Pola (table 2). However, territory mapping tended to give slightly higher values in all wetlands, including Albufera where only this method detected the presence of the species. The additional effort invested in El Hondo through the counting points with vocalization broadcasting did not produce any extra contacts. Count–based population viability analysis (PVA) The instantaneous growth rates estimated in each wetland by the Morris & Doak (2002) method were similar: Albufera r = –0.2747 (SE = 0.0542), El Hondo r = –0.2515 (SE = 0.0293), and Salinas de Santa Pola r = –0.3206 (SE = 0.0039). The PVA based on the diffusion model was done using the specific estimate of each locality. For the PVA based on simulations we used the set of the six estimates of instantaneous population growth rates estimated for the three wet�

lands. In this way we attempted to approximate to the existing variability in growth rates. These estimates average –0.2822 (SE = 0.0532), a value placed within the range of rates estimated by the previous method. Figure 2 shows the cumulative probability extinction function, i.e., the probability that the population will have hit the quasi–extinction threshold at or before a given future time. The PVA results tended to be slightly more optimistic when population estimates of later years were used as initial values, although the predictions calculated using 2005 and 2006 values were very si� milar (table 3, fig. 2). The slightly later extinction times obtained with calculations starting in 2013 were due in part to the fact that we used the population estimated from the mapping method, which was somewhat larger than the results from transects. Comparison of the two models showed that the simulation procedure yielded more pessimistic results because the 0.5 and 0.9 thresholds of extinction probability were reached 3–5

Belenguer Barrionuevo et al.

Table 1. Total length of transects and number of individuals detected in each location and year of study. Tabla 1. Longitud total de los transectos y número de individuos detectados en cada localidad y año de estudio.

Zone Albufera

Locality

2005 Length

Individuals

2006

2013

Length Individuals Length Individuals

Norte

2.06

Sur

1.35

Este

4.02

3.52

Oeste

1.25

Total

El Hondo

Levante

4.10

4.05

Poniente

2.10

Charca SW

0.60

0.65

Reserva

1.10

1.15

La Raja

5.30

5.50

5.45

Claudio

2.20

Franja

0.50

Total

Santa Pola

Santafé

4.22

4.49

5.45

Flota Alta

2.00

1.47

1.45

Múrtulas

2.96

2.65

Charcol

1.51

1.50

Bras del Port

1.56

Total

years earlier than in the diffusion model, except in Santa Pola where both models provided very similar results. Models estimate that the quasi–extinction threshold will be reached with 0.9 probability in a maximum of 11 years (simulation models) or 15 years after the last census (diffusion models). Discussion The two methods used in this survey (territory mapping and density estimation based on transects) produced consistent results across wetlands, although the transect method yielded slightly lower estimates in all cases. This, and the fact that in Albufera the species was detected only by territory mapping, suggests that this method was the most accurate. Territory mapping has been often used in other studies. In England, the national population of bearded reedling was estimated for the first time in 2002, using territory mapping and prospecting 71 localities (Gilbert et al., 1998; Olgivie et al., 2004). This methodology seems more feasible in small wetlands and with a high number of partici� pants. However, in the case of large wetlands such as the Ebro Delta, Albufera de Valencia or El Hondo, transect methodology seems more practical and more

0 23

economical because it can be carried out by a small team or a single person within a limited time given that it does not need to cover all the available habitat. The results of line transects performed in the last years depict a population size reduction of 90% from 2005 to 2013 in all wetlands studied, indicating the criti� cal situation of the species in this region. The results of the two different PVA methods that we used were very similar, and for the locality including the largest population of the bearded reedling in the Valencia region (El Hondo) they predicted a 90% probability of reaching the quasi–extinction threshold before 2024 or 2028, while for the Santa Pola population this threshold would be reached by 2017. The case of Albufera de Valencia is even more worrying because in 2005–2006 only between five and nine pairs were detected, and seven years later only one pair was found, indicating that this population is on the brink of extinction. Results are based on only three estimates of breeding population sizes in each wetland, unevenly distributed along time, and thus they may have been influenced by the reduced population size estimated in the last study year, which could give a biased picture of the trend of the species. More censuses are therefore needed to have a better evaluation of the extinction probabilities. However, the fragmentary information

Animal Biodiversity and Conservation 39.1 (2016)

available for the years after our study supports our results. Although no more bearded reedling censuses have been carried out in Santa Pola and El Hondo, appropriate habitats of this last wetland are frequently surveyed by birdwatchers and researchers and this species continues to be very difficult to observe. In Albufera, the same transects used in this study were visited by JIDJ and JCA in 2014 and 2015 and they only detected one individual in 2014 and none in the last year. In this same wetland, independent birdwatchers and the staff of the Tancat de la Pipa Reserve have estimated 1–2 pairs in these two years (P. Vera, SEO/BirdLife, pers. comm.). Therefore, for� tunately the species is still present in Albufera, but its numbers remain at or very close to the population size we estimated in 2013, which is the quasi–extinction threshold considered in our PVA models. Given that the Albufera population had reached the quasi–extinction threshold by 2013, we used this result to test which of the two PVA models produced more realistic predictions. The simulation model gave a probability of 0.64 that the species would reach quasi–extinction threshold by 2013 starting with the 2005 population and 0.832 with the 2006 population, and the maximum probability of extinction was pre� dicted to occur in 2014 and 2013 respectively. The equivalent values obtained from the diffusion model were 0.175 (2005) and 0.262 (2006) and the years of maximum probability of extinction were 2014 and 2015, respectively. These results suggest that the simulation model predicted the probability of extinc� tion in Albufera more closely, although the differences between the two models are not very large due to uncertainties associated with this type of analysis. A similar severe negative trend occurred before in another Spanish coastal wetland, the Ebro Delta, where in the eighties the species was considered a common breeder but is currently extinct (Martínez, 1983; Martínez & Elliot, 2004; Clarabuch, 2011; R. Gutiérrez, pers. comm.). This situation contrasts with the Iberian inland wetlands where the populations of this passerine are stable, as in the case of Castilla–La Mancha, and even experienced a recent expansion, as in northern Spain (Gutiérrez Expósito, 1998). Although the population trends in the French Mediterranean wetlands have not estimated as far as we know, the results of the census carried out in 2012 in southern France by the Tour du Valat research center, suggest that the bearded reedling is still relatively common there (B. Poulin, pers. comm.). The existence of movements of individuals between wetlands would make a rescue effect possible and would be important for the viability of the Mediterra� nean populations. However, recoveries in Cataluña of birds ringed in southern France are scarce (only one occurrence connecting Aiguamolls de l’Empordà with the French Mediterranean wetlands), suggesting that movements between these wetlands have little relevance and that birds arriving from France are unlikely to have a rescue effect on the Catalonian populations (López–Iborra & Monrós, 2004). In north Spain, in contrast, despite the absence of recover� ies, it is thought that the species’ expansion in this

Table 2. Densities (D, ind/ha) and standard errors (in parentheses) of bearded reedling estimated from the models generated by the program Distance. The population (numbers of pairs) estimated from the density values, P(D), with several confidence intervals (CI) is also shown, as well as the number of pairs estimated in 2013 by territory mapping (TM). Tabla 2. Densidades (D, ind/ha) del bigotudo estimadas a partir de los modelos generados por el programa Distance, entre paréntesis se muestra el error estándar. Se muestran la población (número de parejas) estimada a partir de la densidad, P(D), con varios intervalos de confianza (CI) y las parejas estimadas en 2013 mediante el mapeo de territorios (TM).

Year

2005

2006

2013

Albufera D

0.15 (0.07) 0.09 (0.04)

CI 95%

0.06–0.38 0.04–0.20

CI 84%

0.08–0.28 0.05–0.16

CI 76%

0.09–0.25 0.05–0.14

P(D)

5.5

CI 95%

3.5–23

2.5–12

CI 84%

4.5–17

3–9.5

CI 76%

5–15.5

3–8.5

0.00

El Hondo D

0.22 (0.10) 0.20 (0.10) 0.03 (0.01)

CI 95%

0.08–0.64 0.06–0.64 0.01–0.09

CI 84%

0.11–0.45 0.09–0.43 0.01–0.06

CI 76%

0.13–0.39 0.11–0.38 0.02–0.05

P(D)

78.5

11.5

CI 95%

30–248.5

24.5–249

4–34

CI 84%

43–173

36.5–167.5

5.5–24

CI 76%

49–152

42–145.5

6.5–21

Santa Pola D

0.18 (0.13) 0.14 (0.07) 0.01 (0.01)

CI 95%

0.05–0.70 0.05–0.37 0.00–0.05

CI 84%

0.07–0.46 0.07–0.28 0.01–0.03

C 76%

0.09–0.39 0.08–0.25 0.01–0.03

P(D)

19.5

1.5

CI 95%

5–74.5

6–39.5

0.5–5.5

CI 84%

7.5–49

7.5–29.5

0.5–3.5

CI 76%

9–41.5

8.5–26.5

0.5–3

Belenguer Barrionuevo et al.

Table 3. Years in which the maximum probability of quasi–extinction and cumulative quasi–extinction probability thresholds of 0.5 and 0.9 were reached for each model and starting year. Tabla 3. Años en los que se alcanzaron los umbrales de máxima probabilidad de cuasi–extinción y de probabilidad acumulada de cuasi–extinción, de 0,5 y 0,9 respectivamente, para cada modelo y año inicial.

Diffusion model

2005

2006

2013

Simulation model 2005

2006

2013

Albufera Extinction P 0.5

2015–2016 2014–2015

2012–2013 2012–2013

Extinction P 0.9

2019–2020 2018–2019

2014–2015 2013–2014

Max. Extinction P

2015

2014

2013

El Hondo Extinction P 0.5

2022–2023 2023–2024 2023–2024

Extinction P 0.9

2026–2027 2027–2028 2026–2027

Max. Extinction P

2023

2024

2019

2019–2020 2021–2022

2021–2022 2022–2023 2023–2024 2019

2020

2022

Santa Pola Extinction P 0.5

2014–2015 2014–2015 2015–2016

2015–2016

Extinction P 0.9

2015–2016 2015–2016 2015–2016

2016–2017 2016–2017 2016–2017

Max. Extinction P

2015

2016

2015 2015

2015–2016 2016

region has been due to the arrival of individuals from the Atlantic wetlands of France (Gutiérrez Expósito, 1998; López–Iborra & Monrós, 2004). In the case of La Mancha, recaptures connecting wetlands in this region are more frequent and it has been suggested that they behave as a metapopulation system (López–Iborra & Monrós, 2004), which could facilitate the stability of their populations. In contrast, there are no recoveries of ringed birds between coastal and inland wetlands. The movements between Spanish Mediterranean wetlands seem to be rare and there are only sporadic sights in some wetlands where the species does not breed (López–Iborra et al., 2007). This situation makes it very unlikely that the minimum abundance found simultaneously in the studied wetlands in the last study year is a consequence of temporal movements to other wetlands and increases the vulnerability of these populations to environmental changes. Taken together, all these observations indicate that the Mediterranean bearded reedling populations in the Iberian peninsula have suffered a strong decline that contrasts with the steady situation, or even increasing trend in the other populations. These Mediterranean wetlands probably share some specific factors that have negatively affected other Iberian coastal popula� tions of this species. All these wetlands are surrounded by intensively irrigated crops (rice, vegetables and fruit trees) where the use of pesticides is intense. The Ebro Delta and Albufera de Valencia are surrounded by rice fields extending to the very shore of the wetlands. In the Ebro Delta, concentrations of pesticides in waters and soils after treatments in the surrounding rice fields

are high (Mañosa et al., 2001) and are suspected of being cause of bivalve mortality episodes (�� Köck–Schul� meyer et al., 2011). In Albufera de Valencia, a study of soils within this natural park detected the presence of pesticides whose origin were the citrus groves and rice fields (Gamón et al., 2003). El Hondo reservoirs are fed with water that has irrigated intensive vegetable crops before it enters channels that carry it to reser� voirs for re–cycling. The excess of this same water is transported to the Salinas de Santa Pola to flood the fishing and hunting reserves where a small popula� tion of bearded reedlings remains. The potential for pesticide concentration in these two wetlands is thus very high, although studies are needed to evaluate this more precisely. However, studies on the water quality at El Hondo showed a high degree of eutrophication (Colmenarejo et al., 2007) and occasional mortalities of birds and fish have been attributed to illegal dis� charges of pesticides into the channel net connecting these wetlands (Sehumed, 1997). On the contrary, the largest Spanish populations are in areas of dry farming (cereals and vineyards) with less intense ag� ricultural activities (Urbano, 2008). Chemical products not only affect fertility and survival of wildlife, but also decrease the abundance of invertebrates consumed by insectivorous species (Brikle et al., 2000; Boatman et al., 2004; Morris et al., 2005; Taylor et al., 2006; Henderson et al., 2009). Given this contrast between the use of pesticides in the areas surrounding the La Mancha and in the Mediterranean coastal wetlands, it seems reasonable to consider that this factor could have negatively affected coastal populations, because

Animal Biodiversity and Conservation 39.1 (2016)

Diffusion model 2005

A 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

2005

Simulation model

2010 2015

2020

2025

2030

2035

2006

2040

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

2005

2013

2010

2015

2020

2025

2030

2035 2040

2010

2015

2020

2025

2030

2035 2040

2010

2015

2020

2025

2030

2035 2040

B 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

2005

2010 2015

2020

2025

2030

2035

2040

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

2005

C 1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

2005

2010 2015

2020

2025

2030

2035

2040

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0

2005

Fig. 2. Cumulative quasi–extinction probability curves of the populations of bearded reedling in the three studied wetlands: A. Albufera; B. El Hondo; C. Santa Pola. Both PVA methods were applied using the population estimated in each census year as starting value (identified by colors). In Albufera in 2013, the population had already reached the threshold of quasi–extinction (two individuals); thus PVA was not conducted for that year and the vertical red dashed line marks the year 2013 to facilitate the interpretation of the curves. Fig. 2. Curvas acumulativas de probabilidad de cuasi–extinción de las poblaciones de bigotudo de los tres humedales estudiados: A. Albufera; B. El Hondo; C. Santa Pola. Ambos métodos de AVP se han aplicado usando la población estimada en cada año de estudio como valor inicial (identificados con colores). Como en la Albufera de Valencia, la población ya había alcanzado el umbral de cuasi–extinción (dos individuos) en 2013; ese año no se realizó el AVP. La línea roja vertical discontinua marca el año 2013 para facilitar la interpretación de las curvas.

they are more exposed to pollutants than populations in inland wetlands. However, other causes of decline can not be discarded, such as increased predation by rats, which are effective predators of small passerine bird nests (Batáry et al., 2004; López–Iborra et al., 2004), and the degradation of reed–beds (Fernán� dez–Núñez, 2014). Given the reduced population size, the negative trend and the high extinction probability of bearded ree� dlings in Mediterranean coastal wetlands, it is urgent to implement effective measures to preserve the species. These should include appropriate management of the habitats to reduce nest losses during breeding. Water flow is mainly artificial in El Hondo and Santa Pola, and should thus be regulated to avoid strong water oscillations during the breeding season. Proliferation of opportunist predators, such as rodents, needs to be prevented and small reed islands for nesting should be promoted through reed management. However, for these measures to be effective the causes of the decline in these wetlands should be better understo� od. A decline of the magnitude observed in our study area corresponds to an 'Endangered' species status, according to the IUCN criteria (population size reduction of ≥ 50% over the last 10 years or three generations; IUCN, 2001). Therefore, we recommend that bearded reedling in Mediterranean regions (Catalonia and Va� lencia region) be upgraded from Vulnerable to Endan� gered. In addition, systematic and periodic censuses should be established in all the Spanish reproductive localities to detect future population regressions. Acknowledgements This work was partly funded by the Consellería d’Infraestructures, Territori i Medi Ambient de la Gen� eralitat Valenciana though the project 'Recerca aus passeriformes amenaçades 2012'. We wish to thank to the staff of El Hondo and Salinas de Santa Pola Natural Parks who helped us during the censuses. Comunidad de Riegos de Levante allowed us to ac� cess to their property in El Hondo. The wardens and owners of the game estates in Santa Pola allowed us to access to: Charcol, Santa Fe, Flota Alta and Múrtulas. José Emilio Martínez Pérez drew maps and transects of figure 1. Alfons Domínguez, from the Agricultural Experiment Station of Carcaixent, guided us on the use of pesticides in agriculture. Ricard Gutiérrez and Brigitte Poulin provided information about situation of Bearded Reedling in Cataluña and southern France, respectively. We apreciate the detailed and valuable comments and editing provided by A. Lendvai and an anonymous referee. References Atienza, J. C., 2006. El escribano palustre en España. I Censo Nacional (2005). SEO/BirdLife, Madrid. Atienza, J. C. & Copete, J. L., 2004. Escribano Pa� lustre Iberoriental Emberiza schoeniclus witherbyi. In: Libro Rojo de las Aves de España: 379–379

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Panurus biarmicus. In: Atles dels ocells nidificants de Catalunya 1999–2002: 450–451 (J. Estrada, V. Pedrocchi, Ll. Brotons & S. Herrando, Eds.). Institut Català d’Ornitologia (ICO) / Lynx Edicions, Barcelona. Martínez–Vilalta, J., Bertolero, A, Bigas, D., Paquet Jean–Yves & Martínez–Vilalta, A., 2002. Habitat selection of passerine birds nesting in the Ebro Delta reedbeds (NE Spain): management implica� tions. Wetlands, 22–2: 318–325. Morris, W. & Doak, D., 2002. Quantitative Conservation Biology. Theory and practice of population viability analysis. Sinauer Associates Inc., Sunderland. Morris, A., Wilson, J., Whittingham, M. & Bradbury, R., 2005. Indirect effects of pesticides on breeding yellowhammer (Emberiza citrinella). Agriculture, Ecosystems and Environment, 106: 1–16. Olgivie, M. & the Rare Breeding Birds Panel, 2004. Rare breeding birds in the United Kingdom in 2002. British Birds, 97: 492–536. Poulin, B., Lefebvre, A. & Mauchamp, A., 2002. Habitat requirements of passerines and reedbed manage� ment in southern France. Biological Conservation, 107: 315–325. R Development Core Team, 2009. R: A language and environment for statistical computing. R Foundation for Statistical Computing, Vienna, Austria. ISBN 3–900051–07–0, URL http://www.R–project.org. Robson, C., 2007. Bearded Tit. In: Handbook of the birds of the World, vol. 12: 308–309 (J. del Hoyo, A. Elliott, D. A. Christie, Eds.). Lynx Editions, Barcelona. Sehumed, 1997. Bird mortality in the Hondo (El� che, Spain). Boletín SEHUMED, vol. 3. Servidor d’informació ornitològica de Catalunya (SIOC, 2013). ICO, Barcelona (http://www.sioc.cat). Stubben, Ch. & Milligan, B., 2007. Estimating and Analyzing Demographic Models Using the popbio Package in R. Journal of Statistical Software, 22: 1–23. Tanneberger, F., Flade, M., Preiksa, Z. & Schröder, B., 2010. Habitat selection of the globally threa� tened Aquatic Warbler Acrocephalus paludicola at the western margin of its breeding range and implications for management. Ibis, 152: 347–358. Taylor, R., Maxwell, B. & Boik, R., 2006. Indirect effects of herbicides on bird food resources and beneficial arthropods. Agriculture, Ecosystems and Environment, 116: 157–164. Thomas, L., Buckland, S. T., Rexstad, E. A., Laake, J. L., Strindberg, S., Hedley, S. L., Bishop, J. R., Marques, T. & Burnham, K. P., 2010. Distance software: design and analysis of distance sampling surveys for estimating population size. Journal of Applied Ecology, 47: 5–14. Urbano, P., 2008. Fitotecnia. Ingeniería de la producción vegetal. Ed. Mundiprensa, Madrid. Valkama, E., Lyytinen, S. & Koricheva, J., 2008. The impact of reed management on wildlife: A meta– analytical review of European studies. Biological Conservation, 141: 364–374.

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Animal Biodiversity and Conservation 39.1 (2016)

Identifying a preservation zone using multi–criteria decision analysis A. Farashi, M. Naderi & N. Parvian

Farashi, A. & Naderi, M. & Parvian, N., 2016. Identifying a preservation zone using multi–criteria decision analysis. Animal Biodiversity and Conservation, 39.1: 29–36. Abstract Identifying a preservation zone using multi–criteria decision analysis.— Zoning of a protected area is an approach to partition landscape into various land use units. The management of these landscape units can reduce conflicts caused by human activities. Tandoreh National Park is one of the most biologically diverse, protected areas in Iran. Although the area is generally designed to protect biodiversity, there are many conflicts between biodiversity conservation and human activities. For instance, the area is highly controversial and has been considered as an impediment to local economic development, such as tourism, grazing, road construction, and cultivation. In order to reduce human conflicts with biodiversity conservation in Tandoreh National Park, safe zones need to be established and human activities need to be moved out of the zones. In this study we used a systematic methodology to integrate a participatory process with Geographic Information Systems (GIS) using a multi–criteria decision analysis (MCDA) technique to guide a zoning scheme for the Tandoreh National Park, Iran. Our results show that the northern and eastern parts of the Tandoreh National Park that were close to rural areas and farmlands returned less desirability for selection as a preservation area. Rocky Mountains were the most important and most destructed areas and abandoned plains were the least important criteria for preservation in the area. Furthermore, the results reveal that the land properties were considered to be important for protection based on the obtained preservation zone. However, these parts are not fully covered under the current protection plans for the area. Key words: Tandoreh National Park, Preservation zone, MCDA, Zoning Resumen Establecimiento de una zona de conservación utilizando el análisis de decisiones basadas en criterios múltiples.— La zonificación de una área protegida es un instrumento para dividir un paisaje en varias unidades de uso de la tierra. La gestión de estas unidades paisajísticas puede reducir los conflictos provocados por las actividades humanas. El parque nacional de Tandoreh es una de las áreas protegidas de Irán más diversas desde el punto de vista biológico. Si bien en general la zona está concebida para proteger la biodiversidad, existen numerosos conflictos entre la conservación de la misma y las actividades humanas. Por ejemplo, la zona ha suscitado muchas controversias y se ha considerado un impedimento para el desarrollo económico local, como el turismo, el pastoreo, la construcción de carreteras y el cultivo. Para reducir los conflictos entre las personas y la conservación de la biodiversidad en el parque nacional de Tandoreh, es preciso establecer zonas seguras y desplazar las actividades humanas fuera de ellas. Con vistas a establecer un plan de zonificación en el parque nacional de Tandoreh, en Irán, en el presente estudio hemos utilizado una metodología sistemática (SIG) que integra un proceso participativo con sistemas de información geográfica mediante el análisis de decisiones basadas en criterios múltiples (MCDA). Los resultados obtenidos ponen de manifiesto que las zonas septentrionales y orientales del parque situadas cerca de zonas rurales y tierras agrícolas resultaron ser menos adecuadas para establecer una zona de conservación. Las montañas rocosas fueron las zonas más importantes, mientras que las zonas más destruidas y las llanuras abandonadas constituían los criterios menos importantes para la conservación en la zona. Además, los resultados revelan que las tierras de propiedad son importantes para la protección dada el área de conservación obtenida. No obstante, estas partes no están totalmente cubiertas por los planes vigentes de protección de la zona. Palabras clave: Parque nacional de Tandoreh, Área de conservación, MCDA, Zonificación Received: 27 VII 15; Conditional acceptance: 12 X 15; Final acceptance: 9 XI 15 Azita Farashi & Naser Parvian, Dept. of Environmental Sciences, Fac. of Natural Resource and Environment, Ferdowsi Univ. of Mashhad, Iran.– Morteza Naderi, Fac. of Geo–Information Science and Earth Observation (ITC), Univ. of Twente, Enschede, the Netherlands. Corresponding author: Azita Farashi. E–mail: farashi@um.ac.ir ISSN: 1578–665 X eISSN: 2014–928 X

Introduction The zoning of protected area is an approach to reduce conflict by designating areas into different management and land use units (Hjortsø et al., 2006; Geneletti & van Duren, 2008; Zhang et al., 2013). Identification and delineation of management zones is necessary for effective management of protected areas. Detailed strategies and activities for different zones can only be defined after management zones are delineated. Multiple land characteristics can be evaluated using zoning, a complex decision–making process (Zhang et al., 2013). Typical zoning sche� mes include a preservation zone with a high level of protection. This kind of zoning can largely exclude human activities surrounded by zones that allow for increasing levels of human activities. Most protected areas in developing countries are suffering from the lack of zoning (Sabatini et al., 2007; Hull et al., 2011), which has now become a challenge for governments and land managers. The evaluation of multiple land attributes based on multiple objectives that inherently involve conflicts is necessary for decision–making regarding land use zoning. Multi–criteria decision analysis (MCDA) has been used to support complex decision making con� strained by multiple conflicting objectives and criteria (Massam, 1988). The field of multi–criteria decision aiding (MCDA) has been developed since the 1960s. Methodological work focused on discreet methods has been carried out by Roy (Roy & Vincke, 1981; Roy, 1985, 1991) who took the lead in using multi–criteria assessment with the ELECTRE family of methods. The PROMETHEE method has been created by Brans (Brans et al., 1986). A REGIME method has been developed by Hinloopen & Nijkamp (1990), while the DEFINITE package has been developed by Janssen (Janssen, 1993). The NAIADE method has been de� veloped by Munda (1995, 2008). Figueira et al. (2005) presented a survey of multi–criteria analysis methods. MCDA has the potential to be applied to a range of regional issues, such as. industrial development, waste management, and renewable energy. Moreover, the issues of sustainability assessment on the macro scale have been analyzed using MCDA methods. Guitouni & Martel (1998) offered an extensive survey of MCDA methods. Furthermore, a review of several MCDA sustainability applications was undertaken by De Montis et al. (2004). A good overview of existing approaches to multi–criteria evaluation of biodiversity in conservation planning has been done by Moffet & Sarkar (2008). The classical goal of finding an optimal solution is subject to a set of constraints that are characteristic of operations research, differing from the new paradigm in MCDA. The primary purpose of analysis in the MCDA paradigm is to search for a compromise solution that satisfies the decision maker, rather than some illusory optimum (Guitouni & Martel, 1998; Shmelev, 2012). MCDA with geographic information systems (GIS) has been considered an important improvement to the conventional map overlay approach (Malczewski, 1999; Eastman, 2001; Malczewski, 2006; Hajkowicz,

Farashi et al.

2008; Greene et al., 2010). The method has been widely applied to land management planning (Phua & Minowa, 2005; Chang et al., 2008; Briceño–Elizondo et al., 2008; Dudley, 2008) and protected area zoning (Hjortsø et al., 2006; Portman, 2007; Geneletti & van Duren, 2008; Hull et al., 2011; Zhang et al., 2013). Development and implementation of zoning meth� odology for protected areas is a critical strategy to enhance the appropriate conservation system. The lack of zoning in protected areas in Iran can stop many conservations activities, which may cause ir� reversible damage to local biodiversity. Therefore, a practical quantitative method needs to be developed to design zoning for protected areas in Iran. This zoning is easy to implement and is transferable to various national parks and protected areas. This study aimed to evaluate the utility of MCDA for zoning the Tandoreh National Park in Iran. Specifically, we tried to illustrate how an MCDA framework can identify the preservation zones of a protected area. Material and methods Study area Tandoreh National Park is located in north–east Iran (58º 33' – 58º 54' N and 37º 19' – 37º 33' E) near the Turkmenistan border. It covers approximately 44,848 ha and includes the national park and protected area (fig. 1). In view of the lack of river flows, springs are the main water resource in this area. Tandoreh National Park also has some waterways and streams, but there is no continuous flow in its stream bed all year round due to lack of rain and snow falls in the area. The park has a wide diversity of plants, encompassing 373 spe� cies from 60 families. The study area includes part of the highlands, hills and mountains of north Khorasan province. The existence of high mountains and deep valleys in Tandore National Park creates good habitats for mountainous wildlife. Five of seven feline species in Iran live in this area, such as the Persian leopard, Panther pardus saxicolor, the jungle cat, Felis chaus, the Pallas' cat, Felis manual, and the Eurasian lynx, Lynx lynx. Tandore National Park is one of the best habitats for Persian leopards in Iran. A total of 134 leopards were observed in the area in year 1991 and 60 in 2008. From the wild ungulates in the area, special mention is given to wild goats that live in herds of up to 100–150 in the highlands and wild sheep, Ovis orientalis arkali, that are the purest race of this species in Iran. Wolves can be observed in groups of two or five in the lowlands. The other mammals in this park are red fox, jackal, beech marten, hyena, and rodents such as pica. Birds can be seen in the lowlands, valleys, and near springs. Gypaetus barbatus, Eurasian griffon and Pheasanidae are considered endangered species in the park. Tandoreh National Park is a good example of tradeoffs between achieving biodiversity and human activities. The main disturbance in the area is gra� zing, which has a high negative effect on vegetation. The area was used as a pastureland before it was designated as a national park. We still can see gra�

Forest Meadow Tall shrub Mixed frost Agriculture land Rocky mountain Destroyed and abandoned plain area 0 1.5 3

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Fig. 1. Land cover map (left) and digital elevation map (right) of the study area. Fig. 1. Mapa de la cobertura terrestre (izquierda) y mapa digital de elevación (derecha) de la zona de estudio.

zing in the park, but with less intensity. The other disturbances in the national parks are rural areas and roads that lead into or around the park. In this study we used three ways to show the conflict between human development and conservation goals: (1) the areas under high grazing were entered into the model as unsuitable areas for protection; (2) rural areas, roads and a 2 km buffer area around them have been removed from the model; and (3) rural areas and roads were used in the models as indexes with negative effects on the safe zone. Defining the criteria Semi–structured interviews and participatory meetings were designed to elicit knowledge, point of view, un� derstandings, interpretations, and experiences of diffe� rent stakeholders and academic experts in relation to the preservation zone. Criteria were identified according to the interviews and meetings. Table 1 shows criteria impacting the preservation zone. Although endangered species are included as important targets, the data for this kind of species are limited. This is especially true for the animals for whom knowledge of their their population size and distribution is poor. Ecologists and conservationists believe the habitat of endangered species is an essential criteria for survival. Therefore, in this study we used the map of habitat type rather than the distribution map of endangered species. Selecting criteria We used the Delphi method to select the correct criteria. Delphi is a systematic and interactive method which relies on a panel of independent experts (Ye et

al., 2006; Guo, 2007). It is based on the principle that a structured group of experts achieve more accurate forecasts than unstructured groups or individuals (Rowe & Wright, 2001). The carefully selected experts an� swered questionnaires for criteria selection to evaluate preservation zone in three steps. After each step, the summaries of the experts' selection from the previous round and the reasons they provided for their judgments were fed back to the experts. The range of selected criteria decreased during this process and the group converged towards the 'appropriate' criteria. Finally, the process was ended after pre–defined stop criteria (e.g., number of rounds, achievement of consensus, and stability of results). Weighting criteria To obtain the important weights for each criterion, we used the analytic network process (ANP) approach to rank the criteria with respect to the objective. Many studies have used this method to determine the weight of a criterion (Mohanty et al., 2005; Ramik, 2006; Dag� deviren et al., 2008; Aznar et al., 2010; Catron et al., 2013; Tavana et al., 2013; Yeh & Huang, 2014; Tadić et al., 2014). The ANP method is an improved version of the AHP method and it is more accurate for many complicated models using many criteria feedback and interrelations among criteria. It evaluates all relation� ships systematically by adding potential interactions, interdependences, and feedbacks in the decision–ma� king system. The powerful side of this method is that it approaches a decision–making problem involving many complicated relationships in a simple way. This technique not only enables pair–wise comparisons of the sub–criteria under main criteria, but also allows

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Tabla 1. Criteria and their weights for preservation. Tabla 1. Criterios para la conservación y sus pesos.

Factors

Descriptions

Weights

Sources of disturbance For the success of conservation actions, a key factor is the distance

from sources of disturbance (Valente & Vettorazzi, 2008) Village

Rural areas are not located inside a national park

However, four villages near the park have negative

environmental effects due to the agricultural activities

Road

The roads inside the park are trails that are used for walking

and ecotourism purpose

0.071

Agriculture land

13% of the park area is agriculture land

0.070

Destroyed and

These places are destroyed by tourists

abandoned

0.4% of the park area is damaged and plains are abandoned

0.001

Slope

Higher slops are more sensitive to disturbance

0.055

Altitude

Higher elevation areas are less accessible with fewer

disturbances

Springs

Springs have an ecological importance, allowing movement

of fauna and contributing to dispersion of biota (Eastman, 2001)

0.131

Natural variables

Species habitat

0.024 0.073

Habitat species are critical for conservation

Rocky mountain

This area is habitat to Panthera pardus, Capra aegagrus

and Ovis orientalis vignei

41% of the park’s area is rocky mountain

Meadow

This area is habitat to Vipera ammodytes and Ophisaurus apodus

The 11.5% of the park area is meadow

Tall shrub

This area is habitat to Testudo graeca

16% of the park area is tall shrub

Forest

This area is habitat to many birds such as Parus major,

Upupa epops, Merops apiaster, Otus scops, Cuculus canorus

More than 80 bird species live in this habitat

0.1% of the park area is forest

Mixed forest

This area is habitat to Ochotona rufescens and Spermophilus fulvus

18% of the park area is mixed forest

the decision–maker to independently compare all the sub–criteria within interactions. Figure 2 shows a com� parison of AHP and ANP methods. Decision–making problems that occur in firms cannot be explained by hierarchical structure alone. The criteria and alterna� tives in a problem can lie in interactions. Under such circumstances, a complicated analysis would be neces� sary to determine the weights of all the components. The ANP method is used for such problems and it is based on the same pair–wise comparisons as the AHP (Sevkli et al., 2012). For pair–wise comparisons, the 1–9 scale of Saaty (1980) is used as shown in Saaty

0.190 0.104 0.099

0.092 0.091

(2008, table 1). In the ANP model, all the components and relationships are defined and the relationships are determined as two–way interactions. In the model, the network structure is used and all the relationships in a cluster (namely, relationships among sub–criteria in a cluster and relationships between sub–criteria under different clusters) are considered. Because of the in� volvement of relationships among sub–criteria under a cluster and interactions among different criteria, the ANP method is useful to obtain more accurate and more effective results such as those in a complex and crucial decision–making problem. The ANP method has three

Animal Biodiversity and Conservation 39.1 (2016)

AHP structure

ANP structure

Goal

W1 Factors

Factors W3

Sub–factors XXX W4

Cluster

External relationship Internal relationship

W2 Feedback

Sub–factors Elements

Strategies

W4 Strategies

Fig. 2. A high–level comparison of AHP and ANP (W1 is a vector that represents the impact of the goal, namely, selecting the best strategy according to SWOT factors, W2 is a matrix that represents the inner dependence of the SWOT factors, W3 is a matrix that denotes the impact of the SWOT factor on each of the SWOT sub–factors, and W4 is a matrix that denotes the impact of the SWOT sub–factors on each of the strategies). Fig. 2. Comparación de alto nivel entre los procesos analítico jerárquico (AHP) y analítico en red (ANP) (donde W1 es un vector que representa los efectos del objetivo, esto es, seleccionar la mejor estrategia de acuerdo con los factores de DAFO, W2 es una matriz que representa la dependencia interna de los factores de DAFO, W3 es una matriz que indica los efectos del factor de DAFO en cada uno de los subfactores de DAFO y W4 es una matriz que indica los efectos de los subfactores de DAFO en cada una de las estrategias).

matrix analyses: super matrix, weighted super matrix, and limit matrix. The super matrix provides relative importance of all the components and the weighted super matrix is used to determine the value that is obtained by the super matrix values and the value of each cluster. In the limit matrix, the constant values of each value are determined by taking the necessary limit of the weighted super matrix. The results of the decision–making problem are gained from the limit matrix scores. It is important to value the criteria and alternatives of the experts and experienced people to achieve more consistent and reliable results (Saaty, 1999, 2003). In our study, the relative importance weights were calculated from freely available software for academic purposes known as Super Decisions Software (http://www.superdecisions.com). Determining preservation zone A suitability evaluation using the GIS–based MCDA has been developed as a tool to support decision–ma� king systems for management policies and strategies (Malczewski & Jackson, 2000; Geertman & Stillwell, 2004; Malczewski, 2004; Gerber et al., 2008). Infor� mation about several criteria is combined by MCDA to form a single index of evaluation. To combine con� tinuous factors by applying a weight to each factor, a linear combination is used followed by a summation

of the results to yield a suitability map (Malczewski, 2000; Eastman, 2001). n

i=1

j=1

S = 3wi xi J cj

Eq (1)

where S is the suitability, wi the weight of factor i, n the number of factors, xi the criterion score of factor i in continued range. Since the scales on which criteria are measured are different, standardization must be performed for all factors before combining them using Eq (1). Moreover, if necessary, all factors must be transformed so that they are positively or negatively correlated with suitability. In this study, standardization was performed using a GIS fuzzy set membership function on to a 0–255–byte scale through the IDRISI program (Eastman, 2001) with 0 as the lowest and 255 as the highest suitability. Herein, we categorized the continuous suitability map into suitable and unsuitable classes. Results Table 1 shows the list of selected criteria. The criteria were divided into three groups: (1)�� sources �� of distur� bance, (2) slope, altitude and spring, and (3) species habitat. Species habitat was the most important criteria for preservation (table 1). Rocky Mountain, meadow,

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Village Spring Road Panther habitat Preservation area Old preservation area

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Fig. 3. Suitability map for preservation in the Tandoreh National Park. Fig. 3. Mapa de idoneidad para la conservación en el parque nacional de Tandoreh.

tall shrubs, forest and mixed forest were the second most important, and sources of disturbance such as rural area, road, and agriculture land and destroyed and abandoned plains were the third most important criteria for preservation. A suitability map was created to show the areas with the highest priority for preservation based on the weighted criteria (table 1). Generally, the area with high suitability values for preservation was found at elevations above 1,300 m (fig. 3). The highest suita� bility values were observed in the south and central parts of the park. In contrast, the lowest suitability values were found at lower elevations along the north and east boundaries of the park, which is close to rural areas (fig. 3). Discussion and conclusion Tandoreh National Park is one of the most biologi� cally and culturally diverse protected areas in Iran. The area was designed for biodiversity conservation; however human activates effect the ecosystem of the park in a negative way. In other words, there is a huge conflict between conservation goal, and local economic development such as tourism, road cons� truction, cultivation, and grazing. Therefore, it is highly demanded to determine a safe zone for biodiversity conservation and ensuring that human activities are located outside the zone. Our results showed that the eastern and northern areas of the park, which are close to human activities such as villages and agri� cultural land, returned the lowest suitability. Because Tandoreh is one of the best habitats for the Persian panther, Panther pardus saxicolor (Ziaee, 2009) the park managers put a lot of effort into protecting their

habitats. We used the habitats of panthers as an important factor to define the safe zone. As shown in figure 3, the habitats of this species are located inside the safe zone, indicating that the protection of these animals depends on protection of safe zone. The results revealed the importance of land prop� erties for protection. However, these areas are not fully covered by the current protection plan (fig. 3). As can be observed from figure 3, the new zoning is completely different from the old zoning. The area which was considered as safe zones in the old zon� ing retrieved lower protection priority in our results. However, this result was expected because the sys� tematic methodology did not play any role in the old zoning, and it was based on expert knowledge alone. The availability of habitat maps can be a solid base for the suitability analysis of the zone. In this sense we could make use of a good quality dataset and the experience of local and thematic experts, which has a very strong effect in the analyses. Future improve� ments will likely require more accurate distribution maps for individual speciesand assessment of the fragility and sensitivity of the different habitat types. The IUCN recommends that the primary manage� ment objectives in a protected area are to preserve its natural ecosystems and species and their associated habitat in at least 75% of the land or water bodies therein (called 75% rule) (Dudley, 2008). Moreover, Dudley (2008) mentioned that 'hard' zones can be assigned to an IUCN category when they are clearly mapped, recognized by legal or other effective means, and have distinct and unambiguous management aims that can be assigned to a particular protected area category (the 75% rule is not relevant). In this study, about 42% of land in the national park is protected areas based on the 'preservation zone'. We presen�

Animal Biodiversity and Conservation 39.1 (2016)

ted a systematic method that combines participatory planning with a GIS–based MCDA technique to ob� jectively design land use zones in the protected area. The zoning of protected areas that considers both socioeconomic and biodiversity factors has moved to the forefront of conservation planning (Stewart & Possingham, 2005; Klein et al., 2008). Here we have described a method to evaluate zoning plans that shows the tradeoffs between biodiversity conservation goals and human developments. Tradeoffs between conservation and socioeconomic interests must be considered in any planning process in order to ade� quately conserve ecosystems. References Aznar, J., Ferrís–Oñate, J. & Guijarro, F., 2010. An ANP framework for property pricing combining quantitative and qualitative attributes. The Journal of the Operational Research Society, 61: 740–755. Brans, J. P., Vincke, P., Mareschal, B., 1986. How to select and how to rank projects: the method. European Journal of Operational Research, 24(2): 228–238. Briceño–Elizondo, E., Jäger, D., Lexer, M., Garcia– Gonzalo, J., Peltola, H. & Kellomäki, S., 2008. Multi–criteria evaluation of multi–purpose stand treatment programmes for Finnish boreal forests under changing climate. Ecological Indicators, 8: 26–45. Catron, J., Stainback, G. A., Dwivedi, P. & Lhotka, J. M., 2013. Bioenergy development in Kentucky: A SWOT–ANP analysis. Forest Policy and Economics, 28: 38–43. Chang, N. B., Parvathinathan, G. & Breeden, J. B., 2008. Combining GIS with fuzzy multicriteria de� cision–making for landfill siting in a fast–growing urban region. Journal of Environmental Management, 87: 139–53. Dagdeviren, M., Yuksel, I. & Kurt, M., 2008. A Fuzzy analytic network process (ANP) model to identify faulty behavior risk (FBR) in work system. Safety Science, 46: 771–783. De Montis, A., De Toro, P., Droste-Franke, B., Omann, I., Stagl, S.,�� 2004. Assessing the Quality of Differ� ent MCDA Methods In: Alternatives for Environmental Valuation: 99–133. Routledge, London. Dudley, N., 2008. Guidelines for applying protected area management categories. IUCN, Gland, Switzerland. Eastman, J. R., 2001. IDRISI 32: Guide to GIS and image processing. Clark Labs, Clark University, Worcester. Figueira, J., Greco, S. & Ehrgott, M. (Eds.), 2005. Multiple Criteria Decision Analysis, State of the Art Surveys. Kluwer Academic Publishers, Boston/ Dordrecht/London. Geertman, S. & Stillwell, J., 2004. Planning sup� port systems: An inventory of current practice. Computers, Environment and Urban Systems, 28: 191–310. Geneletti, D. & van Duren, I., 2008. Protected area

zoning for conservation and use: A combination of spatial multicriteria and multiobjective evaluation. Landscape and Urban Planning, 85: 97–110. Gerber, P. J., Carsjens, G. J., Pak–uthai, T. & Rob� inson, T. P., 2008. Decision sup–port for spatially targeted livestock policies: Diverse examples from Uganda and Thailand. Agricultural Systems, 96: 37–51. Greene, R., Luther, J. E., Devillers, R. & Eddy, B., 2010. An approach to GIS–based multiple criteria decision analysis that integrates exploration and evaluation phases: case study in a forest–domi� nated landscape. Forest Ecology and Management, 260: 2102–2114. Guitouni, A. & Martel, J., 1998. Tentative guidelines to help choosing an appropriate MCDA method. European Journal of Operational Research, 109(2): 501–521. Guo, Y. J., 2007. System synthetical evaluation theory, methods and application. Science Press, Beijing. Hajkowicz, S. A., 2008. Supporting multi–stakeholder environmental decisions. Environmental Management, 88: 607–614. Hinloopen, E. & Nijkamp, P., 1990. Qualitative multi� ple criteria choice analysis. Quality and Quantity, 24(1): 37–56. Hjortsø, C. N., Stræde, S. & Helles, F., 2006. Applying multi–criteria decision–making to protected areas and buffer zone management: A case study in the Royal Chitwan National Park, Nepal. Journal of Forest Economics, 12: 91–108. Hull, V., Xu, W., Liu, W., Zhou, S., Viٌa, A., Zhang, J., Tuanmu, M. N., Huang, J., Linderman, M., Chen, X., Huang, Y., Ouyang, Z., Zhang, H. & Liu. J., 2011. Evaluating the efficacy of zoning designa� tions for protected area management. Biological Conservation, 144(12): 3028–3037. Janssen, R., 1993. Multiobjective Decision Support for Environmental Management. Kluwer Academic Publishers, Netherlands. Klein, C., Chan, A., Kircher, L., Cundiff, A. J., Gardner, N., Hrovat, Y., Scholz, A., Kendall, B. E. & Airamé, S., 2008. Striking a balance between biodiversity conservation and socioeconomic viability in the design of marine protected areas. Conservation biology, 22: 691–700. Malczewski, J., 1999. GIS and Multicriteria Decision Analysis. John Wiley & Sons, Toronto. – 2000. On the use of weighted linear combination method in GIS: Common and best practice ap� proaches. Transactions in GIS, 4: 5–22. – 2004. GIS–based land–use suitability analysis: A critical overview. Progress in Planning, 62: 3–65. – 2006. GIS–based multicriteria decision analysis: a survey of the literature. International Journal of Geographical Information Science, 20: 703–726. Malczewski, J. & Jackson, M., 2000. Multicriteria spatial allocation of educational resources: An overview. Socio–Economic Planning Sciences, 34: 219–235. Massam, B. H., 1988. Multi–criteria decision making techniques in planning. Programme Planning, 30: 1–84.

Moffett, A. & Sarkar, S., 2006. Incorporating multiple criteria into the design of conservation area networ� ks: a minireview with recommendations. Diversity and Distribution. 12: 125–37 Mohanty, R. P., Agarwal, R., Choudhury, A. K. & Ti� wari, M. K., 2005. A fuzzy–ANP based approach to R&D project selection: A case study. International Journal of Production Research, 43: 5199–5216. Munda, G., 1995. Multicriteria Evaluation in a Fuzzy Environment. State of the Art Surveys. Springer, New York. – 2008. Social Multi–Criteria Evaluation for a Sustainable Economy. Springer, Berlin. Phua, M. & Minowa, M., 2005. A GIS–based multi–cri� teria decision making approach to forest conserva� tion planning at a landscape scale: A case study in the Kinabalu Area, Sabah, Malaysia. Landscape and Urban Planning, 71: 207–222. Portman, M. E., 2007. Zoning design for cross–border marine protected areas: The Red Marine Peace Park case study. Ocean Coastal Management, 50: 499–522. Ramik, J., 2006. A decision system using ANP and fuzzy inputs. In: The 12th International Conference on the Foundations and Applications of Utility, Risk, and Decision Theory. Roma. Rowe, G. & Wright, G., 2001. Expert opinions in forecasting: role of the Delphi technique. In: Principles of forecasting: a handbook of researchers and practitioners (J. S. Armstrong, Ed.). Kluwer Academic Publishers, Boston. Roy, B., 1985. Méthodologie multicritère d'aide à la décision. Economica, Paris. – 1991. The outranking approach and the foundations of electre methods. Theory and Decision, 31(1): 49–73. Roy, B. & Vincke, P., 1981. Multicriteria analysis: Survey and new directions. European Journal of Operational Research, 8: 207–218. Saaty, T., 1980. The analytic hierarchy process. Mc� Graw–Hill, New York. – 2008. Decision making with the analytic hierarchy

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Animal Biodiversity and Conservation 39.1 (2016)

Reproductive data and analysis of recoveries in a population of white stork, Ciconia ciconia, in southern Spain: a 24–year study M. Cuadrado, Í. Sánchez, M. Barcell & M. Armario

Cuadrado, M., Sánchez, Í., Barcell, M. & Armario, M., 2016. Reproductive data and analysis of recoveries in a population of white stork, Ciconia ciconia, in southern Spain: a 24–year study. Animal Biodiversity and Conservation, 39.1: 37–44. Abstract Reproductive data and analysis of recoveries in a population of white stork, Ciconia ciconia, in southern Spain: a 24–year study.— Changes in nest density and reproductive success of a free–ranging population of white stork, Ciconia ciconia, in the Gardens of ZooBotánico Jerez (Cádiz) were studied from 1990 to 2013. Reproductive data (number of nests and number of chicks per nest) and the effect of rainfall on the reproductive success were analyzed. In addition, a number of chicks were colour–ringed each year and the recovery data were also analyzed. The number of nests found in the area steadily increased during the study period and varied greatly from year to year from 2001 onwards (mean 19, range = 4–35, N = 22 years). Reproductive success also varied greatly among years. Overall, the mean number of chicks per nest was 1.78 ± 1.2 (range = 0–5, N = 439 nests). Reproductive success was strongly influenced by rainfall. It was highest (1.88) in years classified as rainy, medium (1.62) in years classified as normal, and lowest (1.24) in dry years. A total of 404 white storks were ringed, 110 of which were observed a total of 308 times (2.8 + 2.8 times per bird, range 1–12, all year data pooled). Recovery data show that with one exception, all ringed birds were recorded at different habitats of S Spain throughout the year. Remarkably, none was observed at traditional wintering quarters, south of the Sahara in Africa. Juveniles remained in the area (from July to October) soon after leaving our colony, and virtually all of them disappeared from November to January (their first winter) but were recorded again during their first breeding season. On the contrary, adults were repeatedly recorded at different sites in Cádiz, Sevilla and Huelva all year round. These birds showed a strong philopatry as some of them were recorded as breeders in our colony, up to 11 years after ringing. Our data emphasize the importance of both refuse damp and wetland areas for the species, especially in winter, and a shift in the timing of the reproductive season as birds were recorded from November to July each year. Our study provides evidence of the increase in the population, a significant effect of rainfall on their reproductive success, and the non–migratory habits of adult white storks in our colony. To our knowledge, this is the first time that such long–term reproductive data for a Mediterranean population of white storks is shown. Key words: Long–term, Nest density, Recovery data, Reproduction, Breeding success, Ciconia ciconia Resumen Historial reproductivo y análisis de las recapturas de una población de cigüeñas blanca, Ciconia ciconia, del sur de España: un estudio de 24 años.— Entre 1990 y 2013 se estudiaron los cambios en la densidad de nidos y el éxito reproductor de una población de cigüeñas blancas, Ciconia ciconia, que viven en libertad en los jardines del Zoobotánico de Jerez (Cádiz). Se analizaron datos relativos a la reproducción (número de nidos y número de pollos volantones por nido) y el efecto de la pluviometría en el éxito reproductor. Asimismo, cada año se marcaron con anillas de colores varios pollos y también se analizaron los datos de recaptura. El número de nidos hallados en la zona aumentó de forma constante durante el periodo de estudio y varió notablemente entre años a partir de 2001 (media = 19; intervalo = 4–35; N = 22 años). El éxito reproductor también varió considerablemente entre años. En total, la media de pollos volantones por nido fue de 1,78 ± 1,2 (intervalo = 0–5; N = 439 nidos). La precipitación influyó en gran medida en el éxito reproductor, que fue máximo (1,88) en los años clasificados como lluviosos, medio (1,62) en los años clasificados como normales y mínimo (1,24) en los años secos. Se anillaron un total de 404 cigüeñas blancas de las cuales 110 se observaron en 308 ocasiones (2,8 + 2,8 veces por ave; intervalo = 1–12, ISSN: 1578–665 X eISSN: 2014–928 X

Cuadrado et al.

datos de todos los años). Los datos de recaptura mostraron, con una única excepción, que todas las aves anilladas se habían registrado en distintos hábitats del sur de España durante todo el año. Cabe resaltar que no se observó ningún ave en las tradicionales zonas de invernada del Sáhara meridional, en África. Los jóvenes permanecieron en zonas próximas a su lugar de nacimiento (entre julio y octubre) poco después de abandonar nuestra colonia y la inmensa mayoría de ellos desaparecieron entre noviembre y enero (su primer invierno); sin embargo, se registraron de nuevo durante la primera estación reproductora. Por el contrario, los adultos se siguieron registrando en distintos lugares de Cádiz, Sevilla y Huelva durante todo el año. Estas aves mostraron una gran filopatria, ya que algunas de ellas se registraron como reproductoras en nuestra colonia (hasta 11 años después del anillamiento). Nuestros datos ponen de relieve la importancia de los vertederos y los humedales para la especie, especialmente en invierno, y el cambio en la fenología reproductora, puesto que las aves se registraron entre noviembre y julio de todos los años. En resumen, en este trabajo se aportan datos que respaldan el incremento de la población, el efecto significativo de la precipitación en el éxito reproductivo y el comportamiento no migratorio de los adultos de cigüeña blanca en nuestra colonia. Que sepamos, es la primera vez que se aportan datos a tan largo plazo sobre la reproducción de esta especie para una localidad mediterránea del sur de Europa. Palabras clave: Largo plazo, Densidad de nidos, Datos de recaptura, Reproducción, Éxito reproductor, Ciconia ciconia Received: 19 V 15; Conditional acceptance: 19 V 15; Final acceptance: 12 XI 15 Mariano Cuadrado, Íñigo Sánchez, Manuel Barcell & María Armario, Depto. Técnico, ZooBotánico de Jerez, Madreselva s/n., 11408 Jerez de la Frontera (Cádiz), Spain. Corresponding author: M. Cuadrado. E–mail: tecnicos.zoo@aytojerez.es

Animal Biodiversity and Conservation 39.1 (2016)

Introduction The study of the number of breeding pairs per unit area and the reproductive traits for a species in a given season is a basic issue in ornithology. In most cases, studies search for correlations across seasons or differences between years in an attempt to correlate either the density of nests or reproductive traits with a number of environmental variables such as rainfall (e.g., Green, 1988; Steenhof et al., 1997; Chase et al., 2005). Most studies consider a relatively low number of breeding seasons (< 5 yrs), with long–term studies (> 10 yrs) being scarce (but see Holmes et al., 1986; Dallinga & Schoenmakers, 1989; Clark & Mednis, 2002; Chase et al., 2005; Wilkin et al., 2006; see Woller et al., 1992 for a review). The analyses of long–term data sets have allowed the development of a number of disciplines such as demography, population dynamics and ecology, of much concern in the current scenario of climatic change (Brereton et al., 1995; Root et al., 2003; Parmesan, 2006). The white stork, Ciconia ciconia, is, perhaps, one of the most studied bird species. Many aspects of its distribution range, migratory habits, and reproductive traits are remarkably well known (Schulz, 1998, see del Hoyo et al., 1992 for a review). Undoubtedly, its preference to reproduce at human–made habitats has favored this knowledge. In the Iberian peninsula, the population of white storks has been monitored since the middle of the last century (Bernis, 1995). In 2004, SEO Birdlife performed the first Spanish population census as part of the VI International Census of the species (Molina & del Moral, 2005). The Spanish population has notably increased in the last decades (Molina & del Moral, 2005). Some authors have hypothesized that such an increase is linked to a change in both feeding habits (by using new resources such as refuse rubbish dumps or crayfishes on rice fields, Purroy, 1997; Tortosa et al., 2002; Sanz–Aguilar et al., 2015) and a shift in their migratory habits (now many birds do not migrate to overwinter in Africa but remain in southern Spain during the winter months (Máñez et al., 1994; Sanz–Aguilar et al., 2015). According to available information, this shift in migratory habits started about 1985 (Máñez et al., 1994; Purroy, 1997; Barjola, 2001). In this note, we present reproductive data (both number of nests and breeding success) of a free– living white stork population settled at the gardens of ZooBotánico Jerez (Cádiz, S Spain) from 1990 to 2013 (N = 24 years). We analyzed the influence of rainfall in the reproductive success (number of chicks per nest), predicting that breeding success would be higher in wet years when feeding opportunities are presumably better (Dallinga & Schoenmakers, 1987; Carrascal et al., 1993, Tortosa et al., 2003; Jovani & Tella, 2004). Finally, as a number of chicks were colour–ringed at our colony each year, we analyzed the ringing recovery data in order to clarify the migratory status of this population. Specifically, we analyzed whether white storks spent the winter in the area and the extent of breeding philopatry, a pattern common to this species (del Hoyo et al., 1992).

Although several studies have analyzed the variation in the number of pairs and their reproductive traits for remarkably long–term data sets in white stork (Dallinga & Schoenmakers, 1989; Tryjanowski et al., 2005; Gordo et al., 2013), to our knowledge, this is the first time that such long–term reproductive and ringing recovery data are reported for a population in the Mediterranean area. Material and methods Study site A wild population of white storks reproduces at the gardens of ZooBotánico Jerez every year. The gardens of ZooBotánico Jerez cover an area of 6.5 has, located in the western part of the city of Jerez de la Frontera (Cádiz, S Spain, coordinates: 36.689009º N, –6.150112º W). The gardens are characterized by a dense canopy composed of many species of trees (some over 140 years old and higher than 30 metres). Each year, white stork locate their nests in large trees to and on artificial platforms erected above some animal enclosures to facilitate their reproduction. Field work This colony was studied from 1990 to 2013. Each year, the whole area was prospected for nests at least once a week during the reproductive season (from February to July) to assess the reproductive activity of white stork in the colony. In each survey, we followed a fixed route (ca. 2 km in length) on days with good weather (no wind and no rain). We used standard 10 x 40 binoculars to observe of the nests. All nests found were noted on a scaled map. We also noted the presence of adults (and their identification number if ringed) and the number of chicks found at each nest. Clutch size or hatchling date were not recorded as many nests were too high to effectively record these variables. We measured reproductive success as the number of fledglings (juveniles that completed the reproduction and abandoned the nests), the procedure used in other studies (e.g., Lázaro et al., 1986). Only those nests for which information was accurately recorded were included in the reproductive success analyses. Reproductive data of years 2004 and 2007 were not available. Climatologic data Rainfall data was obtained from Jerez Airport Station (AEMET, Spanish Meteorological Agency, sequence 1974–2013). For the analyses, we used the rainfall of the period October (year n–1) to April (year n) for a reproductive season (year n). The rainfall accumulated during this period is likely to influence feeding opportunities and hence influence the reproduction of white stork during a reproductive season. According to the rainfall data, the reproductive season (year n) was classified as dry (< 400 mm of rainfall), normal (400–600 mm) or wet (> 600 mm).

Ringing of chicks and the analysis of recovery data In May–June each year, we visited several of the more accessible nests and ringed all the chicks. Each chick received a metallic ring and a standard colored plastic ring with an alphanumerical code for identification at a distance. First, we analyzed the recoveries of juveniles during their first year of life. For our convenience, this period was considered from July (the month when most juveniles leave the colony, year n) to October (year n+1). Three periods were considered: the post–fledging period (from July to October, year n), the winter period (from November to January, year n+1) and the breeding season (from February to October, year n+1). Second, we analyzed the recoveries of adult white storks (i.e., those that occurred during the second reproductive season or more). Again, we considered winter (between November to January) and breeding (from February to October) recoveries. A total of 404 chicks were ringed from 1996 to 2011. The Spanish Ringing Office at Estación Biológica Doñana–CSIC, provided white stork (period 1994–2011) recovery data. Statistical analyses We used standard parametric statistics according to Sokal & Rohlf (2005). We analyzed the hypothesis that reproductive success was influenced by type of year. To achieve this, we introduced the number of fledglings per nest as the dependent variable and the type of year (humid, normal or dry) as a factor in an ANOVA analysis. Data from all years were pooled for the analyses. Statistics were performed using SPSS vs. 15.0. The results are reported as mean ± SE. The significance was set a P < 0.05. Results Number of nests and reproductive success The white stork colony at ZooBotánico de Jerez increased during the study period (table 1). The number of nests varied greatly among years from 4 (in 1990) to 35 nests (in 2006). A single nest was recorded in Jerez city in 1985 (before this study started) and this nest was located in the gardens of ZooBotánico Jerez (own data). The colony grew exponentially until 2001 when a total of 32 nests were recorded. From 2002 to 2013, the size of the colony was also high but with great variations between years (table 1). Overall, the mean number of nests per year was 19 (range = 4–35, N = 22 yr). Reproductive success also varied greatly between years (table 1). It was low (< 1 chick/nest, in 1999, 2005, and 2012), medium (ca. 1.5 chicks/nest in 1992, 1993, 2002, and 2003) and high (> 2 chicks/ nest in 1991, 1996, 2001, and 2003). The mean number of chicks was minimum in 2012 (0.7 + 0.9, range = 0–2, N = 17) and maximum in 2001 (2.4 + 1.1, range = 0–5, N = 32). Overall, reproductive success was 1.78 ± 1.20 (range = 0–5, N = 439). Colony size

Cuadrado et al.

had little effect on mean reproductive success as the correlation between total number of nests and the mean number of fledglings per nest did not reach statistical significance (Pearson product–moment correlation, rp = – 0.18, P = 0.43, N = 22). The effect of rainfall Reproductive success was significantly influenced by rainfall (one factor ANOVA, F2, 437 = 10.7, P < 0.001). The mean number of fledglings recorded per nest was low in dry years (1.24 ± 1.18, N = 199), medium in years considered to have a normal rainfall (1.62 ± 1.17, N = 116), and high in wet years (1.88 ± 1.39, N = 94). The effect of rain on fledgling success was highly significant as rain and the mean number of fledglings per nest (mean values of all nests in a year) were highly correlated (Pearson product moment, rp= 0.50, P = 0.017, N = 22). Analysis of recoveries A total of 404 chicks were ringed during the study period. Of these 110 white storks were observed a total of 308 times (2.8 + 2.8 times per bird, range = 1–12, N = 110, data of all years pooled). With one exception (code RU2, ringed in May 1997 was recorded 12 months later in Algeria), all these recoveries occurred in Cádiz, Huelva or Sevilla (all in S Spain). The analysis of recoveries classified as juveniles (see methods) showed that: (1) a total of 33 birds (or 30%) were observed 1.2 + 0.5 times (range = 1–3, N = 33, all year data pooled) soon after leaving our colony (from July to October in the same year as ringing). Most of these birds (N = 24) were consistently observed at Miramundo (a well known urban dumping site in Medina Sidonia, Cádiz, ca. 25 km SE of our colony), suggesting that many post–fledgling white storks remained in Cádiz province for a few months after leaving our colony; (2) nearly all juveniles abandoned the study area in their first winter as only two birds (or 1.8%) were recorded during this period; and (3) 46 birds (or 41.8%) were recorded during their first breeding season (from February to October year n+1) in the area. Similarly, the analysis of recoveries of birds classified as adults (see methods) showed that: (1) 27 white storks (or 24%) were recorded in winter (from November to January). These birds were consistently observed at wetland habitats in S Spain (especially Doñana National Park and wetland areas of Sevilla and Cádiz) and various dumping sites in Cádiz (especially Miramundo and Los Barrios); and (2) a total of 57 white storks (or 51%) were recorded during the second breeding season (year n+2 or more). Overall, the number of years elapsed between the year of ringing and breeding was 3.6 + 2.5 years (range = 1–11, N = 81, all years pooled). As expected, a few ringed birds showed a strong philopatry as 10 white storks (or 9%) were recorded breeding again in our colony in the following season. The number of years elapsed between breeding and first ringing of these birds was 4.4 + 3.6 years (range = 1–11, N = 10).

Animal Biodiversity and Conservation 39.1 (2016)

Table 1. Colony size and reproductive data of the white stork colony at ZooBotánico Jerez per year in relation to type of climatic year. Years were classified as: rainy (> 600 mm of rainfall), normal (between 400 and 600 mm), or dry (< 400 mm). Data include the number of nests (Nn) found each year and the number of fledglings (Nf, mean ± SD and range). Rainfall was measured as the total monthly data from September to April of the following year: (a) Data not available. Tabla 1. Datos sobre el tamaño y la reproducción de la colonia de cigüeña blanca del Zoobotánico de Jerez por año en relación con el tipo de año climático. Los años se clasificaron en: lluviosos (> 600 mm de precipitación), normales (entre 400 y 600 mm) y secos (< 400 mm). Los datos comprenden el número de nidos (Nn) encontrados cada año y el número de pollos volantones (Nf, media ± DE e intérvalo). La precipitación se midió como el valor mensual total entre septiembre y abril del año siguiente: (a) Datos no disponibles. Year Nn

Nf (mean ± SD) Range Rainfall (mm)

Type of climatic year

1990

1.75 ± 1.25

0–3

639.0

Rainy

1991

2.2 ± 1.30

0–4

494.9

Normal

1992

1.57 ± 1.27

0–3

291.8

Dry

1993

1.57 ± 0.97

0–3

369.4

Dry

1994

1.30 ± 1.06

0–3

311.8

Dry

1995

1.45 ± 1.21

0–4

220.6

Dry

1996

2.00 ± 1.62

0–4

752.2

Rainy

1997

1.19 ± 1.11

0–3

881.7

Rainy

1998

1.59 ± 1.54

0–5

513.6

Normal

1999

0.74 ± 0.96

0–3

92.4

Dry

2000

1.07 ± 0.93

0–3

402.2

Normal

2001

2.47 ± 1.19

0–5

680.3

Rainy

2002

1.43 ± 0.89

0–3

368.9

Dry

2003

2.69 ± 1.03

0–4

534.0

Normal

2004

(a)

2005

0.88 ± 0.81

0–3

155.0

Dry

2006

1.80 ± 1.51

0–4

331.4

Dry

2007

(a)

2008

1.38 ± 1.30

0–4

270.9

Dry

2009

1.52 ± 1.09

0–4

499.2

Normal

2010

0–4

815.1

Rainy

2011

1.65 ± 0.94

0–4

575.9

Normal

2012

0.70 ± 0.92

0–2

257.4

Dry

2013

1.96 ± 1.09

0–4

495.0

Normal

Total

439

1.78 ± 1.20

0–5

1.57 ± 1.45

Discussion Our study provides some interesting results. First, the number of white stork nests in our colony increased between 1990 and 2013. In fact, this increase started earlier as only one nest (located at ZooBotánico Jerez) was found in Jerez city in 1985 (own data). White stork populations in other parts of Spain have undergone a

similar increment in the last decades. The VI International Census performed by SEO–BirdLife (Molina & del Moral, 2005) showed a decline from 1948 to 1984 (from 14,503 to 6,753 nests,) and a notable increase from 1994 to 2004 (from 16,643 to 33,217 nests, respectively). In addition, a number of local studies have reported the same trend (Lázaro et al., 1986; Pedrochi, 1993; Bernis, 1995; García García, 1997;

Nalda et al., 1994; Prieto Martín, 2002). Interestingly, several authors noted that this shift in the density of the population trend occurred in 1985 (Purroy, 1997; Prieto Martin, 2002; Molina & del Moral, 2005). Our data strengthen this idea and report a steady increment in white stork populations from 1985 onwards, a finding similar to that reported in many other white stork breeding populations in the Iberian peninsula. Second, reproductive success varied greatly between years and was significantly influenced by rainfall. As reported for many bird species, weather conditions (especially rainfall) are known to have a significant impact on the reproductive success of white storks (Dallinga & Schoenmakers, 1987; Tortosa et al., 2003; Jovani & Tella, 2004; Massemin–Chalet et al., 2006). Another study, however, suggested that local livestock farming, rather than the water level, was the most significant variable (cf. Tryjanowski et al., 2005). In our case, rainfall —and consequently, the availability of wetlands— seemed to increase feeding opportunities for white storks because the species prefer wetlands and pastures to forage (del Hoyo et al., 1992; Carrascal et al., 1993; pers. obs.) Third, the recovery data provide some clues about the non–migratory habits of the species in our colony. Remarkably, none of the ringed birds were observed in Africa, south of the Sahara, a traditional overwintering area for the species (cf. del Hoyo et al., 1992). However, we do not exclude the possibility that the absence of recoveries in Africa was simply due to the low number of birds ringed in our study site. Juveniles, however, disappeared during their first winter but returned to their breeding grounds within their first year of life. Adults, on the contrary, were resident in the area and were frequently recorded in the area all year round. It has been suggested that white stork populations breeding in the Iberian peninsula have changed their migratory habits over recent decades (Máñez et al., 1994; Purroy, 1997; Barjola, 2001; Archaux et al., 2004). Our recovery data clearly support this notion in the the case of adult white storks. Other studies have also reported a change in the migratory habits of white stork breeding populations (Máñez et al., 1994; Purroy, 1997; Barjola, 2001; Molina & del Moral, 2005; Manuel Fernández Cruz, pers. comm.; see also Archaux et al., 2004 for a similar case reported in France). Available information on more than 60 radio–tagged white storks controlled by satellites, a new method extensively used today, provides similar results (see MIGRA Program, developed by SEO–BirdLife; Anonimous, 2015). And fourth, breeding philopatry seems to be the general trend, as a few white storks were recorded at our colony in a subsequent breeding season, a pattern similar to that observed in many other white stork colonies (del Hoyo et al., 1992; see Prieto Martín, 2002 for a similar case in another Spanish population). There are a number of reasons for this change in the migratory habitats of white stork. First of all, the species became strictly protected by Spanish law in 1975 (cf. R. D. 2573 from BOE, dated 5 November 1973), favoring the conservation of both individuals and their nests. The second reason is the shift in their feeding habits, with an increment in the use of urban

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waste dumps (Tortosa et al., 2002; Peris, 2003; Ciach & Kruszyk, 2010; this study; see also Purroy, 1997 and references therein). Interestingly, some studies suggest that the shift in migratory behavior occurred from 1985 onwards. Our recovery data (performed from 1995 onwards) also support this view. And third, the introduction of the exotic crayfish, Procambarus clarkii, at many wetland habitats of southern Spain occurred in 1974. This species has become the base of the diet of many mammals and bird species including white storks (Machamalo de Blas, 1995; Tablado et al., 2010). Our recovery data analysis also highlight the relevance that some refuse damps (especially Miramundo and Los Barrios, both in Cádiz) and wetland areas (all located around Doñana National Park both in Huelva and Sevilla and Cádiz Bay area) have for white storks, especially for post–fledgling juveniles and adult birds in winter. The importance of these habitats has been reported in many other studies (Purroy, 1997; Tortosa et al., 2002; Molina & del Moral, 2005; Sanz–Aguilar et al., 2015). Another point of note is that white storks have also changed the timing of their reproductive season; both juveniles and adults leave our colony in early July and return to their same breeding quarters early in November (own data), similar to observations in other white stork colonies (Barjola, 2001; Prieto Martín, 2002; Gordo & Sanz, 2006). In conclusion, our study provides evidence of the steady increase in the population and non–migratory habits of adult white storks in our colony and emphasized the impact urban waste sites and and wetlands in the maintenance of their populations, especially in non–breeding periods. White storks seem to be a plastic, highly adaptable species that exhibits relatively rapid changes in migratory habits. To our knowledge, this is the first study to provide such long–term reproductive data for a white stork population in a Mediterranean habitat. Acknowledgments José Antonio Masero and Oscar Gordo kindly provided interesting comments on an early draft of this paper. We wish to thank the many students at the Zoo who performed most of the field work over the study period for their collaboration. We also acknowledge Manuel Lobón and the Colectivo Ornitológico Cigüeña Negra for their role in ringing of the colony from 2007 to date. References Anonimous, 2015. Los secretos de la migración de las aves al descubierto. Available at http://www. ecoticias.com/naturaleza/103173/los–secretos– de–la–migracion–de–las–aves–al–descubierto. [Accessed on 11 May 2015]. Archaux, F., Balança, G., Henry, P. Y. & Zapata, G., 2004. Wintering of White Storks in Mediterranean France. Waterbirds, 27: 441–445. Barjola, M., 2001. Los hábitos y costumbres de estas

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aves migratorias se han modificado. ¿Ya no invernan las cigüeñas? Ambienta Julio–Agosto: 24–29. Bernis, F., 1995. Iberian White Storks: their ecographical context and recent population trends. In: Proceedings of the International Symposium on the White Stork (Western population): 17–20 (O. Biber, P. Enggist, C. Marti & T. Salathé, Eds.). Sempach, Schweizerische Vogelwarte, Basel. Brereton, R., Bennett, S. & Mansergh, I., 1995. Enhanced greenhouse climate change and its potential effect on selected fauna of south–eastern Australia: a trend analysis. Biological Conservation, 72: 339–354. Carrascal, L. M., Bautista, L. M. & Lázaro, E., 1993. Geographical variation in the density of the white stork Ciconia ciconia in Spain: Influence of habitat structure and climate. Biological Conservation, 65: 83–87. Chase, M. K., Nur, N. Geupel, G. R. & Stouffer, P. C., 2005. Effects of weather and population density on reproductive success and population dynamics in a song sparrow (Melospiza melodia) populations: a long–term study. Auk, 122: 571–592. Ciach, M. & Kruszyk, R., 2010. Foraging of White Storks Ciconia ciconia on rubbish dumps on non–breeding grounds. Waterbirds, 33: 101–104. Clark, R. G. & Mednis, A., 2002. Patterns of reproductive effort and success in birds: path analyses of long–term data from European ducks. Journal of Animal Ecology, 71: 1365–2656. Dallinga, J. H. & Schoenmakers, S., 1987. Regional decrease in the number of white storks (Ciconia c. ciconia) in relation to food resources. Colonial Waterbirds, 10: 167–177. – 1989. Population change of the white stork Ciconia ciconia since the 1850s in relation to food resources. Scriftenreihe des Dachverbanden Deutscher Avifaunisten, 10: 231–262. Del Hoyo, J., Elliot, A. & Sargatal, J. (Eds.), 1992. European White Stork. In: Handbook of the birds of the world, Vol. 1: 460–461. Lynx Ed., Barcelona. García García, J. M., 1997. Evolución y situación actual de la población calagurritiana de Cigüeña blanca (Ciconia ciconia). Kalakorikos, 2: 233–248. Gordo, O. & Sanz, J. J., 2006. Climate change and bird phenology: a long–term study in the Iberian Peninsula. Global Change Biology, 12: 1993–2004. Gordo, O., Tryjanowski, P., Kosicki, J. Z. & Fulin, M., 2013. Complex phenological changes and their consequences in the breeding success of a migratory bird, the white stork Ciconia ciconia. Journal of Animal Ecology, 82: 1072–1086. Green, R. E., 1988. Effects of environmental factors on the timing and success of breeding of common snipe Gallinago gallinago (Aves: Scolopacidae). Journal of Applied Ecology, 25: 79–93. Holmes, R. T., Sherry, T. W. & Sturges, F. W., 1986. Bird community dynamics in a temperate deciduous forest: long–term trends at Hubbard Brook. Ecological Monographs, 56: 201–220. Jovani, R. & Tella, J. L., 2004. Age–related environmental sensitivity and weather mediated nestling mortality in white storks Ciconia ciconia. Ecography,

27: 611–618. Lázaro, E., Chozas, P. & Fernández Cruz, M., 1986. Demografía de la cigüeña blanca (Ciconia ciconia) en España. Censo nacional de 1984. Ardeola, 33: 131–169. Marchamalo de Blas, J., 1995. Wintering of the White Stork in Spain. In: Proceedings of the International Symposium on the White Stork (Western population): 77–80 (O. Biber, P. Enggist, C. Marti & T. Salathé, Eds.). Sempach, Schweizerische Vogelwarte, Basel. Máñez, M., Sánchez Tortosa, F., Barcell, M. & Garrido, H., 1994. La invernada de la Cigüeña blanca en el suroeste de España. Quercus, 103: 10–12. Massemin–Chalet, S., Gendner, J. P., Samtmann, S., Pichegru, L., Wulgué, A. & Le Maho, Y., 2006. The effect of migration strategy and food availability on White Stork Ciconia ciconia breeding success. Ibis, 148: 503–508. Molina, B. & Del Moral, J. C., 2005. La Cigüeña Blanca en España. VI Censo Internacional (2004). SEO/ BirdLife, Madrid. Nalda, F. J., Nalda, J. V. & Ruiz, A., 1994. La Cigüeña blanca en la Rioja, 1986–1993. Zubia Monográfico, 5: 305–330. Parmesan, C., 2006. Ecological and evolutionary responses to recent climate change. Annual Review of Ecology, Evolution, and Systematics, 37: 637–669. Pedrochi, C., 1993. El censo de cigüeñas comunes (Ciconia ciconia) de 1992 en la provincia de Huesca. Lucas Mallada, 5: 121–125. Peris, S. J., 2003. Feeding in urban refuse dumps: ingestion of plastic objects by the White stork (Ciconia ciconia). Ardeola, 50: 81–84. Prieto Martín, J., 2002. Las cigüeñas de Alcalá. Naturaleza en Alcalá. No. 3. Ayuntamiento de Alcalá de Henares. Purroy, F. J. (Coord.), 1997. Cigüeña blanca Ciconia ciconia. In: Atlas de las aves de España (1975– 1995): 58. SEO Birdlife–Lynx Ediciones, Barcelona. Root, T. L., Price, J. T., Hall, K. R., Schneider, S. H., Rosenzweig, C. & Pounds, J. A., 2003. Fingerprints of global warming on wild animals and plants. Nature, 421: 57–60. Sanz–Aguilar, A., Jovani, R., Melián, C. J., Pradel, R. & Tella, J. L., 2015. Multi–event capture–recapture analysis reveals individual foraging specialization in a generalist species. Ecology, 96: 1650–1660. Schulz, H., 1998. Ciconia ciconia White Stork. BWP Update 2: 69–105. Sokal, R. R. & Rohlf, F. J., 2005. Biometry. The principles and practice of statistics in biological research. 3rd. edition. W. H. Freeman & Co., New York. Steenhof, K., Kochert, M. N. & Mcdonald, T. L., 1997. Interactive effects of prey and weather on golden eagle reproduction. Journal of Animal Ecology, 66: 350–362. Tablado, Z., Tella, J. L., Sánchez–Zapata, J. A. & Hiraldo, F., 2010. The paradox of the long–term positive effects of a North American Crayfish on a European community of predators. Conservation Biology, 24: 1230–1238.

Tortosa, F. S., Caballero, J. M. & Reyes–López, J., 2002. Effect of rubbish dumps on breeding success in the White Stork in southern Spain. Waterbirds, 25: 39–43. Tortosa, F. S., Pérez, L. & Hillströom, L., 2003. Effect of food abundance on laying date and clutch size in the White Stork Ciconia ciconia. Bird Study, 50: 112–115. Tryjanowski, P., Jerzak, L. & Radkiewicz, J., 2005. Effect of water level and livestock on the pro-

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ductivity and numbers of breeding white storks. Waterbirds, 28: 378–382. Wilkin, T. A., Garant, D., Gosler, A. G. & Sheldon, B. C., 2006. Density effects on life–history traits in a wild population of the great tit Parus major: analyses of long–term data with GIS techniques. Journal of Animal Ecology, 75: 604–615. Wooller, R. D., Bradley, J. S. & Croxall, J. P., 1992. Long–term population studies of seabirds. Trends in Ecology and Evolution, 7: 111–114.

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The status of Rhionaeschna galapagoensis (Currie, 1901) with notes on its biology and a description of its ultimate instar larva (Odonata, Aeshnidae) A. Cordero–Rivera, A. C. Encalada, R. A. Sánchez–Guillén, S. Santolamazza–Carbone & N. von Ellenrieder Cordero–Rivera, A., Encalada, A. C., Sánchez–Guillén, R. A., Santolamazza–Carbone, S. & von Ellenrieder, N., 2016. The status of Rhionaeschna galapagoensis (Currie, 1901) with notes on its biology and a description of its ultimate instar larva (Odonata, Aeshnidae). Animal Biodiversity and Conservation, 39.1: 45–63. Abstract The status of Rhionaeschna galapagoensis (Currie, 1901) with notes on its biology and a description of its ultimate instar larva (Odonata, Aeshnidae).— A morphological, molecular, and behavioural characterization of Rhionaeschna galapagoensis is presented, based on a series of specimens and observations from San Cristóbal Island, Galápagos, including both adults and larvae. Several of the characters proposed earlier to distinguish between the adults of this species and its closest relative, R. elsia, are found to be variable, but the presence of a black band over the fronto–clypeal suture is confirmed as a good diagnostic character. The ultimate instar larvae of R. galapagoensis is described for the first time, and diagnosed from its closest relatives by a combination of characters, including the acute angle between the prothoracic apophyses, absence of lateral spines on abdominal segment 6, and length of cerci relative to paraprocts. Molecular analysis confirmed that R. galapagoensis and R. elsia are sister species, and showed that their genetic distance is the closest among the analyzed species, which is to be expected given the young age of the Galápagos Islands. The larvae of R. galapagoensis were very common and widespread in the mountain streams and a pond in the southwest of San Cristóbal. Swarms of tens of individuals formed at sunrise in the coastal vegetation, together with adults of Tramea cf. cophysa, feeding on small flying insects. Males showed patrolling behaviour on small sections of the streams and at a pond. Only one copulation was observed, lasting 10 minutes. Females oviposited alone on floating vegetation in running and standing waters. Our observations corroborate that R. galapagoensis and R. elsia are parapatric species, that are morphologically and genetically close. In San Cristóbal, R. galapagoensis had large populations, apparently not threatened. Key words: Odonata, Aeshnidae, Island species, Sibling species, Endemism, Rhionaeschna Resumen El estado de Rhionaeschna galapagoensis (Currie, 1901) con notas sobre su biología y una descripción de su último estadío larvario (Odonata, Aeshnidae).— Se presenta una caracterización morfológica, molecular y comportamental de Rhionaeschna galapagoensis, basada en una serie de especímenes, tanto adultos como larvas, y observaciones realizadas en la isla de San Cristóbal, en las Galápagos. Se ha observado que varios de los caracteres propuestos anteriormente para distinguir entre los adultos de esta especie y los de su pariente más próximo, R. elsia, son variables; sin embargo, se ha confirmado que la presencia de una banda negra en la sutura frontoclipeal es un buen carácter diagnóstico. Se describe por primera vez el último estadio larvario de R. galapagoensis y se distingue de sus parientes más cercanos mediante una combinación de caracteres que incluye el ángulo agudo entre las apófisis protorácicas, la ausencia de espinas laterales en el sexto segmento abdominal y la longitud de los cercos en relación con los paraproctos. El análisis molecular confirmó que R. galapagoensis y R. elsia son especies hermanas, y mostró que la distancia genética entre ellas es la menor entre las especies analizadas, lo cual es previsible dada la edad reciente de las islas Galápagos. Las larvas de R. galapagoensis eran muy comunes y estaban ampliamente distribuidas en los arroyos de montaña y en un estanque en el suroeste de San Cristóbal. Se observó la formación de enjambres de decenas de individuos en la vegetación costera al amanecer que, junto con adultos de Tramea cf. cophysa, se alimentaban de pequeños insectos. Los machos patrullaban pequeñas secciones de los arroyos y en un estanque. Solo ISSN: 1578–665 X eISSN: 2014–928 X

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se observó una cópula, que duró unos 10 minutos. Las hembras ovipositaron solas en la vegetación flotante de los arroyos y el estanque. Nuestras observaciones corroboran que R. galapagoensis y R. elsia son dos especies parapátricas, morfológica y genéticamente cercanas. Las poblaciones de R. galapagoensis en San Cristóbal son grandes y aparentemente no están amenazadas. Palabras clave: Odonata, Aeshnidae, Especies insulares, Especies gemelas, Endemismo, Rhionaeschna Received: 14 IX 15; Final acceptance: 20 XI 15 A. Cordero–Rivera, R. A. Sánchez–Guillén & S. Santolamazza–Carbone, Grupo de Ecoloxía Evolutiva e da Conservación, EUE Forestal, Univ. de Vigo, Campus universitario, 36005 Pontevedra, Spain.– A. C. Encalada, Lab. de Ecología Acuática, Colegio de Ciencias Biológicas y Ambientales, Univ. San Francisco de Quito, LEA–USFQ, Ecuador.– R. A. Sánchez–Guillén, Ecology, Biology Dept., Lund Univ., Sweden.– N. von Ellenrieder, Plant Pest Diagnostics Center, California Dept. of Food & Agriculture, 3294 Meadowview Road, Sacramento, CA 95832–1448, USA. Corresponding author: A. Cordero–Rivera. E–mail: adolfo.cordero@uvigo.es

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Introduction Islands are evolutionary laboratories where speciation occurs at a high rate due to isolation (MacArthur & Wilson, 1967; Whittaker, 1998). The Galápagos are especially significant in this context in view of their effect on Charles Darwin’s theory of evolution by natural selection (Darwin, 1901). Flying animals, with their high dispersal ability, are less prone to island endemism, but archipelagos situated far from the mainland are sufficiently isolated to promote speciation and evolution of novel traits. This is the case of the Azores Islands, whose poor odonata fauna (only four resident species) harbors the only case of parthenogenesis known in the entire order of Odonata (Cordero Rivera et al., 2005). The Odonata of the Galápagos, with only nine species currently known for the archipelago (Peck, 1992; Muddeman, 2007), are a clear example of the effect of isolation on colonization events. Only one Rhionaeschna species, R. galapagoensis, has been described from the Galápagos Islands, and it is currently considered the only endemic species of the order in the Galápagos archipelago. Rhionaeschna galapagoensis was described by Currie (1901) as Aeshna galapagoensis from a male and a female collected in the Galápagos Island of San Cristóbal. It was later also described from the islands of Santa Cruz and Isabela (Calvert, 1956; Turner Jr., 1967). The male caudal appendages were depicted in Martin (1908), and the species was listed by Campos (1922) from Ecuador. Calvert (1956) included it in the subgenus Neureclipa Navás and provided a redescription and illustrations of the caudal appendages of males and females. Turner (1967) provided a new island record, and Belle (1991) published a few observations about its behaviour. Aeshna galapagoensis was transferred by von Ellenrieder (2003) to the genus Rhionaeschna, accompanied by a characterization, diagnosis, and illustrations of various morphological characters based on examination of the type specimens. The preliminary phylogenetic analysis of the genus based on morphological characters of the adults (von Ellenrieder, 2003) placed R. galapagoensis as the sister species of R. elsia (Calvert) within a clade including the other species previously included in the subgenus Neureclipa by Calvert (1956). These species share the combination of supratriangles usually free, two rows of cells between RP1 and RP2 in Hw beginning at the distal end of the pterostigma or further distally, and male cercus with dorso–distal crest as high or higher than the width of cercus at base, a prominent sub–basal tooth, and external margin concave (von Ellenrieder, 2003). Both species can be distinguished from all remaining species of Rhionaeschna by the combination of rounded clypeal lobes and ventral tubercle of S1 bearing only a few denticles (10 or less) restricted to its apex (von Ellenrieder, 2003). Calvert (1952) described R. elsia without providing any diagnosis from R. galapagoensis. In his monograph of the group (Calvert, 1956), he used the thoracic and membranule color pattern and shape of

male caudal appendages in dorsal view to separate them. Von Ellenrieder (2000) redescribed R. elsia, and later (von Ellenrieder, 2003) showed that thoracic color pattern and dorsal shape of male cerci were variable in R. elsia and unreliable as diagnostic characters, proposing the presence or absence of a black band over the fronto–clypeal suture, and the shape of the anterior hamule anterior tip, female cercus tip, and male cercus dorso–distal crest in lateral view to distinguish between the two species. Needham (1904) provided a brief larval description of R. galapagoensis based on an early instar larva. The ultimate instar larvae of slightly over half of the known species of Rhionaeschna were described by Calvert (1956), Walker (1958), Musser (1962), Santos (1966), Rodrigues Capítulo (1980), De Marmels (1982, 1990, 2001), Limongi (1983), Novelo–Gutiérrez & González–Soriano (1991), von Ellenrieder (1999, 2001), von Ellenrieder & Costa (2002), von Ellenrieder & Muzón (2003), Müller & Schiel (2012) and Rodriguez & Molineri (2014). Given the scarcity of specimens of R. galapagoensis available for study to date, further data were needed to assess the status of R. galapagoensis as a different taxon from R. elsia. To this end, we: (i) examined morphological characters of adult and ultimate instar larvae, (ii) provided some observations on general and reproductive behaviour, and (iii) used nuclear and mitochondrial DNA sequences to contrast the specific status for these sister taxa. Material and methods All observations were performed at San Cristóbal Island (Galápagos Archipelago) between 20 II and 6 III 2014. Most of the island has no road access so we were limited to the populated areas in the southwest of the island. We sampled permanent streams and ponds around the 'Hacienda El Cafetal'. Further observations were carried out at Punta Carola, where young and mature adults were found in swarms feeding on shrubs of Hippomane mancinella Linnaeus. Specimens collected were preserved in 80% ethanol for further study. Acronyms for collections are as follows: ACR. Adolfo Cordero Rivera, Pontevedra, Spain; CSCA. California State Collection of Arthropods, Sacramento, California, USA; RWG. Rosser W. Garrison, Sacramento, California, USA; USFQ. Museo de Entomología Acuática, Universidad San Francisco de Quito, Ecuador. In the laboratory, the variability of characters of adult specimens of R. galapagoensis was studied, documented and compared with those of a series of adult R. elsia in order to re–evaluate which diagnostic characters reliably identified the two species. Illustrations were made with the aid of a camera lucida coupled to a Nikon SMZ1500 stereomicroscope. Exuviae were photographed using a Canon Eos 7D mark II camera, and images were combined by means of a procedure of photo–stacking using Adobe Photoshop CS6 software (www.adobe.com).

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Ultimate instar larvae were photographed and measured with an AxionCam ICc3 coupled to a ZEISS Discovery V12 and the software Axion Vision version 4.8. Mandibular formula follows Watson (1956). All measurements are given in millimeters; average dimensions are given as average ± standard deviation; hind wing measurement excludes basal sclerites; total length includes caudal appendages; larval wing cases, lateral spines on abdomen, cercus, and paraproct were measured along their inner margin. Abbreviations used throughout the text are as follows: Dept.: Department; Prov.: Province; Fw: forewing; Hw: hindwing; pnx: postnodal crossveins; S1–10: abdominal segments 1 to 10. Material studied is detailed in appendix 1. Molecular analysis and phylogenetic reconstruction DNA extraction and sequencing DNA was extracted from one leg of each adult dragonfly using a GeneJet Genomic DNA Purification kit (Thermo Scientific, Waltham, USA). Three genes were amplified: mitochondrial cytochrome oxidase I (COI); hypervariable D7 region of the large–subunit 28S (rDNA) (28S); and nuclear Histone 3 (H3), using PCR according to Kohli’s et al. (2014) protocol. We selected two mitochondrial and one nuclear gene based on their diverse evolutionary rates, to allow us to reconstruct both internal and external branches, respectively (Fritz et al., 1994). Successfully amplified samples were sent to Macrogen (www.macrogen.com) for bidirectional sequencing. Genetic distances and phylogenetic reconstruction Forward and reverse sequences were edited in BioEdit version 7.5.0.3 (Hall, 1999) and consensus sequences aligned with SeqMan DNAStar version 5.03 (www. dnastar.com). Variable positions were revised by eye, and only high quality sequences were considered for further analyses. Genetic distances among the seven Rhionaeschna species sequenced were estimated by using Kimura 2–parameter genetic distances (Kimura, 1980) of the three genes separately; COI (20 sequences, 367 bp), nuclear H3 (21 sequences, 251 bp), and 28S (20 sequences, 454 bp). All samples of each species clustered in the same species–group, and genetic distances were estimated between groups. The gamma distribution (shape parameter = 1) was used to modulate the rate of variation among sites with MEGA 6 (Tamura et al., 2013). A Neighbor–Joining tree (based on Maximum composite Likelihood method; Tamura et al., 2004) and a Maximum Likelihood tree (based on Tamura–Nei model; Tamura & Nei, 1993) were generated for the three concatenated genes: COI (19 sequences, 367 bp), H3 (19 sequences, 251 bp), and 28S (19 sequences, 454 bp) using MEGA 6 (Tamura et al., 2013). After deleting all positions containing gaps and missing data, we performed both phylogenetic reconstructions based on 1,065 positions.

Phylogenetic relationships among haplotypes were also estimated using Bayesian inference with the program MrBayes version 3.0 (Huelsenbeck & Ronquist, 2001). To this end, we investigated models of nucleotide substitution of the three genes and ranked them by Akaike information criterion implemented in the program jModelTest (Posada, 2008). The model Generalized Time–Reversible plus Gamma (GTR)+G (Tavaré, 1986) was inferred as the most appropriate model to estimate nucleotide substitutions for two genes (COI and H3) because it allows for a different rate of transitions and transversions as well as unequal frequencies of the four nucleotides (base frequencies). However, the model of nucleotide substitution inferred for the nDNA gene 28S was the Hasegawa–Kishino–Yano model (HKY)+G (Hasegawa et al., 1985), a model that also allows for a different rate of transitions and transversions as well as unequal frequencies of the four nucleotides (base frequencies). Thus, because the nDNA gene 28S has a different model of nucleotide substitution and a low percentage of informative positions to be analyzed alone (see details in Results section) it was not included in the Bayesian analyses. Therefore, only two genes, COI and H3, were concatenated and analyzed together. We conducted two independent runs that consisted of four Markov chains (one cold and three heated chains) each. We ran 100,000 generations, sampling every 10 generations and discarding the first 2,500 (25%) generations (burn–in time). The resulting phylogenetic tree was rooted with Anax amazili and drawn with FigTree version 1.3.1 (http://tree. bio.ed.ac.uk/). Results Morphological characterization of the adults Clypeal lobes rounded; clypeus and frons light blue to pale brown, brown spots lateral to yellow area surrounding T–spot stem; T–stem widening posteriorly, with convex sides; vertex yellow or light blue with latero–posterior margins black, with a black stripe on fronto–clypeal suture (fig. 1A); wide black stripe on fronto–ocular groove. Pale mesanepisternal stripes present at basal 25% in teneral specimens to absent in older specimens; mesepimeral and metepimeral stripes whitish, wide, and complete in teneral specimens to light blue, narrow, and faint or incomplete to absent in older specimens. Membranule dark except basal 15% (fig. 2A) to 30% white (fig. 2B). Abdomen dark brown with light blue spots; female S2 with a narrow medio–longitudinal dorsal yellow stripe usually spanning along anterior 0.75 of segment length, rarely along entire length or limited to anterior 0.50 of segment. Abdominal ventral terga narrow (length/ width of S5 at basal 25% higher than 4), maximum width of S5–6 at distal 66%, basal 30% of inner and outer lateral carinae of S4 concave. Ventral tubercle of S1 bearing few denticles (10 or less) restricted to its apex; dorsal margin of anterior lamina spine concave;

Animal Biodiversity and Conservation 39.1 (2016)

Fig. 1. A. A pair of Rhionaeschna galapagoensis in copula photographed by Adolfo Cordero–Rivera on 24 II 2014 in Ecuador, San Cristóbal Island, Camarones stream at Hacienda El Cafetal (arrow in insert points at black band over fronto–clypeal suture); B. Male of Rhionaeschna elsia photographed by Dennis Paulson on 26 IV 2014 in Peru, Lima Department, Chorrillos, Pantanos de Villa near Lima (arrow in insert points at fronto–clypeal suture, devoid of a black band). Fig. 1. A. Pareja de Rhionaeschna galapagoensis en cópula fotografiada por Adolfo Cordero–Rivera el 24 II 2014 en Ecuador, en la isla de San Cristóbal, arroyo Camarones, dentro de la Hacienda El Cafetal (la flecha en el detalle indica la banda negra de la sutura frontoclipeal); B. Un macho de Rhionaeschna elsia fotografiado por Dennis Paulson el 26 IV 2014 en Perú, departamento de Lima, Chorrillos, Pantanos de Villa, cerca de Lima (la flecha en el detalle indica la sutura frontoclipeal, sin banda negra).

tip of hamular anterior process rounded (fig. 3A) to pointed in ventro–lateral view (fig. 3B); auricles with two teeth. Male cercus black, lacking pale basal spot in outer surface; dorso–distal crest rising gradually, as high as base of cercus in lateral view, extending along distal 0.30–0.35 of cercus length (figs. 4A, 4B). Tip of female cercus rounded to pointed (figs. 5A, 5B).

Dimensions: head width: 8–8.9 male, 8.5–8.7 female; Hw length: 37.6–40.8 male, 38.5–40.5 female; Hw width: 12–13.2 male, 13–13.9 female; Hw pterostigma length: 2.8–3.2 male, 2.9–3.4 female; cerci length: 4.5–5.3 male, 3.9–4.5 female; female cerci maximum width: 0.65–0.75; total length: 57–61.8 male, 55.7–59.7 female.

Cordero–Rivera et al.

Fig. 2. Variability in extension of white coloring in hind wing membranule in Rhionaeschna galapagoensis: A. Female from pond, Hacienda El Cafetal (#883); B. Male from Camarones stream, Hacienda El Cafetal (#869). Fig. 2. Variabilidad en la extensión del color blanco en la membránula del ala posterior de Rhionaeschna galapagoensis: A. Hembra del estanque, Hacienda El Cafetal (#883); B. Macho del arroyo Camarones, Hacienda El Cafetal (#869).

Morphological description of ultimate instar larva Head (figs. 6A, 6B) Approximately 1.34–1.42 times as wide as long. Occipital margin slightly concave with 7–8 pilose patches on each side; posterolateral portion of occipital lobes rounded. Antennae 7–segmented, the third antennomere the longest. Prementum reaching caudad base to midlevel between second coxae; prementum (figs. 6C, 6D) as wide as 0.91–1 of its length, border of medial lobe of ligula with fringe of setae and with two small tubercles, one on each side of median cleft, both shorter than setae. Labial palp (fig. 6D) with a small infra–apical tooth, inner margin with 25–30 denticles; movable hook 1.2–1.3 times as long as inner margin

galapagoensis

of palp. Mandibles (fig. 7) with no accessory tooth k below the molar crest, only a swollen area on the equivalent position, and no accessory tooth y between the incisive and the molar crest on left mandible. Molar crest with two small accessory denticles on the right mandible, none on the left mandible. Mandibular formula: L 1234 0 a b/ R 1234 y a(m1,2)b. Thorax Prothoracic supracoxal apophyses with apices blunt, posterior longer and broader at base than anterior, cleft between them forming an acute angle (fig. 6B); wing pads nearly parallel, the external pad reaching caudad base of S4; femora and tibiae with four diffuse dark rings (fig. 6A).

elsia

Fig. 3. Variability in shape of anterior hamule anterior process in Rhionaeschna galapagoensis (A–C) and R. elsia (D–E): A. Santa Cruz Island (redrawn from fig. 293b in von Ellenrieder, 2003); B. Camarones stream, Hacienda El Cafetal (#851); C. Camarones stream, Hacienda El Cafetal (#852); D. Peru, humedales de Ite (RWG); E. Chile, Arica (redrawn from fig. 292b in von Ellenrieder, 2003). Fig. 3. Variabilidad en la forma del proceso anterior del hámulo anterior de Rhionaeschna galapagoensis (A–C) y R. elsia (D–E): A. Isla de Santa Cruz (redibujado de la fig. 293b en von Ellenrieder, 2003); B. Arroyo Camarones, Hacienda El Cafetal (#851); C. Arroyo Camarones, Hacienda El Cafetal (#852); D. Perú, humedales de Ite (RWG); E. Chile, Arica (redibujado de la fig. 292b en von Ellenrieder, 2003).

Animal Biodiversity and Conservation 39.1 (2016)

galapagoensis

elsia

Fig. 4. Variability in shape of male cercus dorso–distal crest in Rhionaeschna galapagoensis (A–B) and R. elsia (C–D): A. Lectotype, San Cristóbal Island (redrawn from fig. 374b in von Ellenrieder, 2003); B. Camarones stream, Hacienda El Cafetal (#851); C. Peru, humedales de Ite (RWG); D. Paratype, Peru near Villa (redrawn from fig. 373b in von Ellenrieder, 2003). Fig. 4. Variabilidad en la forma de la cresta dorsodistal del cerco del macho de Rhionaeschna galapagoensis (A–B) y R. elsia (C–D): A. Lectotipo, isla de San Cristóbal (redibujado de la fig. 374b en von Ellenrieder, 2003); B. Arroyo Camarones, Hacienda El Cafetal (#851); C. Perú, humedales de Ite (RWG); D. Paratipo, Perú, cerca de Villa (redibujado de la fig. 373b en von Ellenrieder, 2003).

Abdomen Widest on S6–7. Dorsal color pattern as in figure 6A. Lateral spines present on S7–9, those on S8 the longest. Female gonapophyses (fig. 8A) not reaching posterior margin of S9. Cerci (fig. 8B) shorter than

galapagoensis

epiproct, epiproct with middorsal ridge and two apical short spines; male basal lamina with blunt tip, as long as 0.42–0.45 of epiproct. Measurements are presented in table 1.

elsia

Fig. 5. Variability in shape of female cercus tip in Rhionaeschna galapagoensis (A–B) and R. elsia (C–D): A. Paralectotype, San Cristóbal Island (redrawn from fig. 374c in von Ellenrieder, 2003); B. Puerto Baquerizo Moreno, Punta Carola Beach (#879); C. Peru, humedales de Ite (CSCA); D. Peru, Lima (redrawn from fig. 373c in von Ellenrieder, 2003). Fig. 5. Variabilidad en la forma del extremo del cerco de la hembra de Rhionaeschna galapagoensis (A–B) y R. elsia (C–D): A. Paralectotipo, isla de San Cristóbal (redibujado de la fig. 374c en von Ellenrieder, 2003); B. Puerto Baquerizo Moreno, playa de Punta Carola (#879); C. Perú, humedales de Ite (CSCA); D. Perú, Lima (redibujado de la fig. 373c en von Ellenrieder, 2003).

Cordero–Rivera et al.

5 mm

1 mm

5 mm

Fig. 6. Ultimate larval instar of Rhionaeschna galapagoensis: male exuvia from Ecuador, San Cristóbal Island, Hacienda El Cafetal, Camarones stream, 20 II 2014 (ACR) (A, C–D); male exuviae from same locality but pond, 27 II 2014 (ACR) (B): A. General view of body, dorsal view; B. Head and pronotum, dorsal view; C. Prementum, ectal view; D. Detail of labial palps and ligula, ental view. Fig. 6. Último estadio larvario de Rhionaeschna galapagoensis: exuvia del macho de Ecuador, isla de San Cristóbal, Hacienda El Cafetal, arroyo Camarones, 20 II 2014 (ACR) (A, C–D); exuvia del macho de la misma localidad pero del estanque, 27 II 2014 (ACR) (B): A. Vista general del cuerpo en vista dorsal; B. Cabeza y pronoto en vista dorsal; C. Prementón en vista ectal; D. Detalle de los palpos labiales y la lígula en vista ental.

Animal Biodiversity and Conservation 39.1 (2016)

1 mm

Fig. 7. Ultimate larval instar of Rhionaeschna galapagoensis, female larva from Ecuador, San Cristóbal Island, pond at El Cafetal, 22 II 2014 (USFQ): A. Right mandible, lateral view; B. Right mandible, medial view; C. Left mandible, medial view; D. Left mandible, lateral view. Fig. 7. Último estadio larvario de Rhionaeschna galapagoensis, larva hembra de Ecuador, isla de San Cristóbal, estanque en El Cafetal, 22 II 2014 (USFQ): A. Mandíbula derecha en vista lateral; B. Mandíbula derecha en vista medial; C. Mandíbula izquierda en vista medial; D. Mandíbula izquierda en vista lateral.

2 mm

substrate. Water transparency varied from clear to milky (1.97 to 10.49 NTU), average conductivity was 99.6 ± 2.3 µS/cm, water temperature varied from 20 to 23ºC and discharge values ranged from 1 to 3 L/s (Ochoa, pers. comm.). Vegetation around streams was composed mostly of ferns (e.g., Diplazium subobtusum) and planted trees of Coffea arabica

2 mm

Larval habitat Larvae were found commonly at streams (fig. 9A) but also at a pond (fig. 9B) near the Hacienda El Cafetal. The streams were generally small (width from 90 to 130 cm), most with pool and riffle sections and substrate composed mostly of pebble and cobble, but some streams also had sand and lime

Fig. 8. Ultimate larval instar of Rhionaeschna galapagoensis: A. Female gonapophyses, ventral view, larva from Ecuador, San Cristóbal Island, pond at El Cafetal, 22 II 2014 (USFQ); B. Male S10 and caudal appendages, dorsal view, exuvia from Ecuador, San Cristóbal Island, Hacienda El Cafetal, Camarones stream, 20 II 2014 (ACR). Fig. 8. Último estadio larvario de Rhionaeschna galapagoensis: A. Gonapófisis femeninos en vista ventral, larva de Ecuador, isla de San Cristóbal, estanque en El Cafetal, 22 II 2014 (USFQ); B. S10 y apéndices caudales del macho en vista dorsal, exuvia de Ecuador, isla de San Cristóbal, Hacienda El Cafetal, arroyo Camarones, 20 II 2014 (ACR).

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Table 1. Measurements of ultimate instar larvae of Rhionaeschna galapagoensis. Measurements are given in mm, as average ± standard deviation followed by range in square brackets. Tabla 1. Medidas del último estadio larvario de Rhionaeschna galapagoensis. Las medidas se dan en mm, como media ± desviación estándar, seguidas del intervalo entre corchetes.

♂ (N = 3)

♀ (N = 2)

Total length

33.5 ± 0.71 [34–33]

32.8 ± 0.28 [32.6–33]

Maximum head width

7.81 ± 0.18 [7.64–8]

7.6 ± 0.05 [7.56–7.63]

Maximum head length

5.72 ± 0.08 [5.65–5.8]

5.67 ± 0.06 [5.63–5.71]

4.8 ± 0 [4.8]

4.65 ± 0.07 [4.6–4.7]

Maximum prementum width Maximum prementum length

5.1 ± 0.28 [4.9–5.3]

4.69 ± 0.02 [4.67–4.7]

1.70 ± 0.05 [1.65–175]

1.66 ± 0 [1.66]

Antennomere I

0.30 ± 0 [0.27–0.33]

0.30 ± 0.04 [0.27–0.33]

Antennomere II

0.37 ± 0.03 [0.35–0.40]

0.33 ± 0.04 [0.30–0.35]

Antennomere III

0.92 ± 0.08 [0.85–1]

0.83 ± 0.11 [0.75–0.90]

Antennomere IV

0.38 ± 0.03 [0.36–0.41]

0.32 ± 0.02 [0.30–0.33]

Antennomere V

0.42 ± 0.03 [0.39–0.45]

0.38 ± 0.01 [0.37–0.38]

Antennomere VI

0.48 ± 0.02 [0.47–0.50]

0.44 ± 0.01 [0.43–0.45]

Antennomere VII

0.50 ± 0.01 [0.49–0.51]

0.47 ± 0.04 [0.44–0.49]

Femur I length

3.63 ± 0.15 [3.5–3.8]

3.65 ± 0.07 [3.6–3.7]

Femur II length

4.8 ± 0.2 [4.6–5]

4.6 ± 0 [4.6]

Femur III length

5.93 ± 0.15 [5.8–6.1]

5.75 ± 0.07 [5.7–5.8]

Tibia I length

4.73 ± 0.06 [4.7–4.8]

4.75 ± 0.07 [4.7–4.8]

Tibia II length

5.07 ± 0.06 [5–5.1]

5.1 ± 0.14 [5–5.2]

Tibia III length

6.18 ± 0.1 [6.1–6.3]

6.05 ± 0.35 [5.8–6.3]

Internal wing pad length (inner margin)

7.4 ± 0.1 [7.3–7.5]

7.2 ± 0 [7.2]

External wing pad length (inner margin)

Labial palp movable hook

6.77 ± 0.12 [6.7–6.9]

6.6 ± 0.14 [6.5–6.7]

Maximum length of S5

2.4 ± 0.1 [2.3–2.5]

1.88 ± 0.18 [1.75–2]

Maximum length of S6

2.57 ± 0.15 [2.4–2.7]

2.67 ± 0.15 [2.5–2.8]

Maximum length of S7

2.67 ± 0.15 [2.5–2.8]

2.22 ± 0.31 [2–2.44]

Maximum length of S8

2.43 ± 0.21 [2.2–2.6]

1.93 ± 0.11 [1.85–2]

Maximum length of S9

2.13 ± 0.12 [2–2.22]

1.9 ± 0.07 [1.85–1.95]

Maximum length of S10

1.38 ± 0.03 [1.35–1.4]

1.03 ± 0.04 [1–1.05]

Lateral spines (inner margin) on S7

0.56 ± 0.04 [0.52–0.6]

0.58 ± 0.04 [0.55–0.6]

Lateral spines (inner margin) on S8

0.9 ± 0 [0.9]

0.96 ± 0.01 [0.95–0.96]

Lateral spines (inner margin) on S9

0.85 ± 0 [0.85]

0.9 ± 0 [0.9]

3.03 ± 0.06 [3–3.1]

3.26 (one malformed)

Cercus length (inner margin)

2.7 ± 0.17 [2.6–2.9]

2.68 ± 0.04 [2.65–2.7]

Paraproct length (inner margin)

3.63 ± 0.06 [3.6–3.7]

3.88 ± 0.11 [3.8–3.96]

Epiproct length

Inner gonapophyses (inner margin)

and some introduced trees (i.e., Cedrella odorata). The only other odonate larva sharing the habitat in the streams was Ischnura hastata Say and several aquatic invertebrate species including Chironomus sp., Orthocladiinae unind. (Diptera, Chironomidae), Simulium ochraceum Walker (Diptera, Simuliidae),

1.93 ± 0.25 [1.75–2.1]

Geranomyia tibialis (Loew) (Diptera, Limoniidae), Haliplus gravidus Aubé (Coleoptera, Haliplidae), Gyrinus galapagoensis Van Dyke (Coleoptera, Gyrinidae), Typhlatya galapagoensis Monod & Cals (Decapoda, Atyidae) and Macrobrachium hancocki Holthuis (Decapoda, Palaemonidae).

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Table 2. Localities where Rhionaeschna galapagoensis was found at San Cristóbal Island, Galápagos, II 2014: Long. Longitude; Lat. Latitude; Alt. Altitude (in m). (Coordinates in the WGS84 datum.) Tabla 2. Localidades donde se encontró Rhionaeschna galapagoensis en la isla de San Cristóbal, Galápagos, II 2014: Long. Longitud; Lat. Latitud; Alt. Altitud (en m). (Datum de coordenadas WGS84.)

Life stage

Habitat

Adults

Waterfall in stream El Chino

Adults, larvae, exuviae Pond

Locality

Long.

Lat.

Alt.

–89.458717 –0.911821 210

Hacienda el Cafetal

–89.538821 –0.924274 191

Adults, larvae, exuviae Camarones stream Hacienda el Cafetal

–89.539510 –0.925664 282

Adults, larvae

Camarones stream Hacienda el Cafetal

–89.538821 –0.924274 191

Adults, larvae

Stream

–89.522702 –0.918473 348

Adults

Punta Carola beach Puerto Baquerizo Moreno –89.611999 –0.890603 3

Adults

Tijeretas beach

Puerto Baquerizo Moreno –89.603032 –0.883341 2

Adults

Stream

Unnamed

Nariz del Diablo

The pond had a surface of approximately 10 m2, turbid water. It was surrounded by native junco (Junco pallescens), other shrubs and herbaceous plants (i.e., Ludwigia erecta), and introduced vegetation (Psidium guajava, Rubus niveus, Cedrella odorata). Other odonate sharing the habitat were Ischnura hastata, Anax amazili, Brachymesia herbida, and Tramea cf. cophysa. Several other aquatic invertebrate species were present, including Tanyponus sp. (Diptera, Chironomidae), Trichocorixa reticulata (Guerin–Meneville) (Heteroptera, Corixidae), Copelatus galapagoensis Waterhouse and Rhantus galapagoensis Balke & Peck (Coleoptera, Dytiscidae). Diagnosis Adults of R. galapagoensis and R. elsia can be distinguished from all other species of Rhionaeschna by the combination of clypeal lobes rounded and ventral tubercle of S1 bearing only a few denticles (10 or less) restricted to its apex (von Ellenrieder, 2003). Adults of R. galapagoensis differ from those of R. elsia by the presence of a wide black band over the fronto–clypeal suture (fig. 1A). In R. elsia, there is no dark color over the fronto–clypeal suture at all or only a faint narrow brown line (fig. 1B). Among the known ultimate instar larvae of Rhionaeschna, still only about 57% of the species in the genus, R. galapagoensis shares only with R. brasiliensis (von Ellenrieder & Costa), R. elsia, and R. marchali the absence of the lateral spines on S6 (Limongi, 1983; von Ellenrieder & Costa, 2002; Müller & Schiel, 2012). Ultimate instar larvae of R. galapagoensis can be recognized from those of R. brasiliensis and R. elsia by the acute angle between the prothoracic supracoxal apophyses (orthogonal to obtuse in R. brasiliensis and R. elsia), and from R. marchali by the well developed prothoracic supracoxal apophyses (absent in R. marchali). Ultimate instar larvae of R. galapagoensis differ further from those

–89.491606 –0.908980 431

of R. elsia by the longer lateral spines on S7–9 and shorter cerci in relation to paraproct length (values of R. galapagoensis first): length of lateral spine on S7: 0.52–0.6 vs. 0.4; length of lateral spine on S8: 0.9–0.96 vs. 0.63; length of lateral spine on S9: 0.85–0.9 vs. 0.63; length cerci/ length paraprocts: 0.68–0.78 vs. 0.64. Both adults and ultimate instar larvae of R. galapagoensis are overall larger than those of R. elsia, although some of their ranges overlap partly: total length of adults: 57–61.8 in males, 55.7–59.7 in females (vs. 54.3–58.2 in males, 54.3–56.4 in females in R. elsia); Hw length 37.6–40.8 in males, 38.5–40.5 in females (vs. 35.8–38.7 in males, 35.9–39 in females in R. elsia); adult male cercus length of 4.5–5.3 (vs. 4.3–4.6 in R. elsia); total length of ultimate instar larvae: 33–34 in males, 32.6–33 in females (vs. 27.5–28.7 in males, 26.9–31 in females in R. elsia); head width of ultimate instar larvae: 7.64–8 in males, 7.56–7.63 in females (vs. 6.67–6.99 in males, 6.65–6.97 in females in R. elsia); length cercus of ultimate instar larvae: 2.6–2.9 in males, 2.65–2.7 in females (vs. 1.75–2.21 in males, 1.93–2.43 in females in R. elsia); length paraproct of ultimate instar larvae: 3.6–3.7 in males, 3.8–3.96 in females (vs. 3.09–3.39 in males, 3.11–3.33 in females in R. elsia). Distribution and biological observations Rhionaeschna galapagoensis was found in all streams visited, both as adults and as larvae of various instars (table 2). We recorded abundant specimens at the Camarones Stream inside the 'Hacienda el Cafetal' and in a nearby pond (fig. 9B). Teneral and mature specimens were found near roads and in the village of Puerto Baquerizo but were particularly common along the coast at Punta Carola and nearby places. Larvae and exuviae were found in the Camarones Stream but also in the pond, indicating that

Cordero–Rivera et al.

Fig. 9. Habitat of Rhionaeschna galapagoensis in San Cristóbal Island, Ecuador: A. Waterfall at El Chino stream; B. Pond at Hacienda El Cafetal. Photos by Adolfo Cordero–Rivera. Fig. 9. Hábitat de Rhionaeschna galapagoensis en la isla de San Cristóbal, Ecuador: A. Cascada en el arroyo El Chino; B. Estanque en la Hacienda El Cafetal. Fotos de Adolfo Cordero–Rivera.

the species is able to complete development in both running and still water. Analyses of gut content of 20 larvae suggested a highly diverse diet, including several Chironomidae, Gyrinidae, Dytiscidae, and also specimens of Ischnura hastata. In agreement with larval habitat preference, males were seen patrolling sections of streams and around the pond, and females were seen laying eggs in both types of habitat. Nevertheless, individuals were more commonly observed at the streams than at the pond. Mate–searching males patrolled sections of the stream of a few meters, flying at about 30–50 cm above the surface of the water. They remained at the stream for short periods (a few minutes) and were observed in the morning and afternoon. Females approached the stream and oviposited on floating vegetation. One female was

observed laying eggs at 16:00 h. Another female approached the stream at mid–day (12:20 h), was captured in tandem by a patrolling male, and the pair mated perched in a nearby tree for about 10 min (fig. 1A). Swarms of tens of individuals (fig. 10A, video) were observed feeding just after sunrise around the beaches and shrubland at Punta Carola. The total number of individuals swarming in the area was clearly enormous, although not easily quantifiable. These swarms appeared at about 6:00 h, immediately after sunrise, and dispersed at about 7:00 h, when the sun became stronger. Some specimens of Tramea cf. cophysa were found in the same swarms. These swarms attracted bird predators, and one successful predation event (on a teneral R. galapagoensis) was observed (fig. 10B).

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Fig. 10. Swarm of adults of Rhionaeschna galapagoensis: A. Feeding just after sunrise around the beaches and shrubland at Punta Carola; B. Documented predation event of birds (a Galapagos flycatcher, Myiarchus magnirostris) on a teneral R. galapagoensis. Photos by Adolfo Cordero–Rivera. Fig. 10. Enjambre de adultos de Rhionaeschna galapagoensis: A. Alimentándose al amanecer alrededor de la playa y en los arbustos en Punta Carola; B. Caso documentado de depredación por aves (un atrapamoscas de Galápagos, Myiarchus magnirostris) sobre un individuo recién emergido de R. galapagoensis. Fotos de Adolfo Cordero–Rivera.

Genetic characterization and phylogenetic reconstruction Alignments of mtDNA COI, H3, and nDNA 28S fragments included 367, 251, and 454 bp positions respectively. Sequences can be accessed at GenBank under accession numbers provided in table 3. The mtDNA COI fragment showed 56 parsimony–informative positions, while there were only 23 and 17 in

nDNA H3 and nDNA 28S. Pairwise genetic distances between the seven Rhionaeschna species ranged from 1.7 to 8.8% for mtDNA A, 1.2 to 4.0% mtDNA C and 0.01 to 0.04% for mtDNA B (table 4). Similar topologies were obtained from Bayesian and maximum likelihood phylogenetic reconstructions. The Bayesian posterior probability approach produced a tree with a topology (based on COI and H3) largely resolved, but the two main clades were not well–supported

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Table 3. GenBank accession numbers for COI (367 bp), 28S (454 bp), and H3 (259 bp) sequences. Tabla 3. Números de accesión de la genoteca GenBank para las secuencias COI (367 bp), 28S (454 bp) y H3 (259 bp).

Species

GenBank accession numbers Code

COI

28S gene

Histone 3

Anax amazili

871

KR110051

KP793444

KR864847

Rhionaeschna absoluta

Ra1

–

KP895577

KR864853

Rhionaeschna absoluta

Ra2

KR189020

KP992515

–

Rhionaeschna bonariensis

Rb1

KR110055

KP793448

KR864843

Rhionaeschna bonariensis

Rb2

KR189017

KP992512

KR864854

Rhionaeschna bonariensis

Rb3

KR189021

KP992516

KR864857

Rhionaeschna bonariensis

Rb4

KR110054

KP793447

KR864844

Rhionaeschna cornigera

234

KR139935

KP793439

KR864851

Rhionaeschna cornigera

240

KR011722

KP793440

KR864860

Rhionaeschna cornigera

241

KR011723

KP793441

KR864850

Rhionaeschna diffinis

Rd1

KR110052

KP793449

KR864842

Rhionaeschna diffinis

Rd2

KR189018

KP992513

KR864855

Rhionaeschna diffinis

Rd3

KR189022

KP992517

KR864858

Rhionaeschna elsia

Re1

KR189016

KP895576

KR864852

Rhionaeschna elsia

Re2

KR189019

KP992514

KR864856

Rhionaeschna elsia

Re3

KR189023

KP992518

KR864859

Rhionaeschna galapagoensis

851

KR011724

KP793442

KR864849

Rhionaeschna galapagoensis

852

KR066402

KP793443

KR864848

Rhionaeschna galapagoensis

877

KR110050

KP793445

KR864846

Rhionaeschna galapagoensis

878

KR110053

KP793446

KR864845

Rhionaeschna marchali

222

–

KP723677

KR259168

Rhionaeschna marchali

223

KP866411

KP749923

KR259169

(see fig. 11A): (i) the 'marchali–clade' that included four species (R. elsia, R. galapagoensis, R. cornigera and R. marchali); and (ii) the 'absoluta–clade' that included the remaining three species (R. bonariensis, R. diffinis, and R. absoluta). Although both clades presented well–supported species–clades, in the 'marchali–clade' R. elsia and R. galapagoensis positions were relatively unresolved, likely due to their recent speciation. However, their close position respect to the remaining two species in the clade (R. cornigera and R. marchali) was well–supported. Similar topologies were obtained from neighbor–joining and maximum likelihood phylogenetic reconstructions. The neighbor–joining tree based on the three genes (COI, H3, and 28S) (see fig. 11B) identified three clades: (i) the 'marchali–clade' (R. elsia, R. galapagoensis, and R. marchali); the 'cornigera–clade' (R. cornigera and R. bonariensis); and (iii) the 'absoluta–clade' (R. diffinis

and R. absoluta). Moreover, the neighbor–joining tree confirmed the close position of both species R. elsia and R. galapagoensis, which were placed in the same cluster but in different branches. However, in the maximum likelihood tree, R. elsia and R. galapagoensis positions were relatively unresolved. Discussion Several diagnostic characters to differentiate between R. galapagoensis and R. elsia, based on examination of type specimens, have been proposed (von Ellenrieder, 2003). These include the color of membranule (fig. 2), the shape of anterior hamule anterior tip fig. 3), dorso–distal crest of male cercus (fig. 4) and female cercus tip (figs. 5). However, we found that these characters are variable in the larger

Animal Biodiversity and Conservation 39.1 (2016)

Table 4. Average genetic distances (%) (Kimura 2–parameter) between the seven Rhionaeschna species sampled for COI (367 bp, 21 sequences), H3 (259 bp, 20 sequences), and 28S (454 bp, 20 sequences). Tabla 4. Distancias genéticas medias (%) (parámetro Kimura–2) entre las siete especies de Rhionaeschna muestreadas para COI (367 bp, 21 secuencias), H3 (259 bp, 20 secuencias) y 28S (454 bp, 20 secuencias).

COI

1. R. absoluta 2. R. bonariensis

0.031

3. R. cornigera

0.086

0.063

4. R. diffinis

0.025

0.022

0.082

5. R. elsia

0.056

0.051

0.088

0.053

6. R. galapagoensis

0.052

0.043

0.086

0.049

0.017

7. R. marchali

0.054

0.039

0.082

0.045

0.055

0.043

1. R. absoluta 2. R. bonariensis

0.020

3. R. cornigera

0.018

0.022

4. R. diffinis

0.005

0.026

0.023

5. R. elsia

0.033

0.028

0.034

0.035

6. R. galapagoensis

0.020

0.016

0.022

0.026

0.012

7. R. marchali

0.024

0.020

0.026

0.028

0.040

0.028

28S

1. R. absoluta 2. R. bonariensis

0.002

3. R. cornigera

0.004

0.003

4. R. diffinis

0.002

0.001

0.004

5. R. elsia

0.002

0.001

0.003

0.001

6. R. galapagoensis

0.002

0.001

0.002

0.001

7. R. marchali

0.002

0.003

0.002

series of specimens of both species available in this study, and cannot be used as diagnostic. The only seemingly reliable character to distinguish between adults of the two species was the black band over the fronto–clypeal suture. The presence or absence of a black band over the fronto–clypeal suture has been found to be a stable character in other species of this genus, always either present or absent in all specimens of a particular species (von Ellenrieder, 2003). The ultimate instar larvae of both species can be recognized from all other Rhionaeschna larvae so far described except for R. brasiliensis and R. marchali by the obsolete to absent lateral spines on S6. These two species differ in the shape of the angle formed between the prothoracic supracoxal apophyses, the length of the lateral spines on S7–9, and of

0.001

the length of cerci relative to paraprocts, as detailed above. As these color and morphological differences between the two species were consistent in all adult and larval specimens available to us in this study, we consider that R. galapagoensis and R. elsia can be maintained as separate species, although they are very close due to their recent speciation. Rhionaeschna galapagoensis was commonly found in streams, far from the coast, perhaps because freshwater ponds are scarce in San Cristóbal. In contrast, the typical habitat of R. elsia is brackish waters in coastal deserts (Müller & Schiel, 2012). Therefore, our results also suggest that the two taxa have different ecological preferences. Further field studies in other islands and other areas of San Cristóbal are needed to confirm our findings.

Cordero–Rivera et al.

A 56

ACR–00223_marchali ACR–00234_cornigera ACR–00240_cornigera ACR–00241_cornigera Re1_elsia Re2_elsia Re3_elsia ACR–00878_galapagoensis ACR–00851_galapagoensis ACR–00852_galapagoensis ACR–00877_galapagoensis Rb4_bonariensis Rb1_bonariensis Rb3_bonariensis Rb2_bonariensis Rd1_diffinis Rd2_diffinis Rd3_diffinis Ra2_absoluta ACR–00871_Anax amazili

100

100 66 100

100 53

96 82

1 change per site

100 99 65

71 61

0.1 substitutions

ACR–00223_marchali Re1_elsia Re2_elsia ACR–00878_galapagoensis ACR–00851_galapagoensis ACR–00852_galapagoensis ACR–00877_galapagoensis ACR–00240_cornigera ACR–00241_cornigera ACR–00234_cornigera Rb4_bonariensis Rb1_bonariensis Rb3_bonariensis Rb2_bonariensis Rd2_diffinis Rd3_diffinis Rd1_diffinis Ra2_absoluta ACR–00871_Anax amazili

Fig. 11. Phylogenetic relationships within Rhionaeschna derived by: A. Bayesian inference based on mtDNA (COI) and nDNA (H3) concatenated sequences from 19 samples under a GTR+G model of evolution; B. Maximum likelihood tree based on mtDNA (COI), nDNA (H3) and nDNA (28S) concatenated sequences from 18 samples. (Numbers at nodes indicate posterior probabilities higher than 50%.) Fig. 11. Relaciones filogenéticas dentro de Rhionaeschna obtenidas mediante inferencia Bayesiana: A. Basada en secuencias concatenadas de ADNmt (COI) y ADNn (H3) de 19 muestras con el modelo evolutivo GTR+G; B. Árbol de máxima verosimilitud basado en secuencias concatenadas de ADNmt (COI) ADNn (H3) y ADNn (28S) obtenido a partir de 18 muestras. (Los números en los nodos indican probabilidades a posteriori mayores del 50%.)

Although the genetic distances between R. galapagoensis and R. elsia are less than the most common 2% divergence between congeneric pairs of animal species (Hebert et al., 2003), other odonate species considered to be good species show similar levels of interspecific divergence. This is the case of

the Ischnura elegans–group of species (I. elegans, I. genei, I. graellsii, and I. saharensis) which show less than 1% divergence (Sánchez–Guillén et al., 2014). Consistently with their low genetic divergence, which is to be expected given the young age of the Galápagos Islands, phylogenetic reconstruction confirms the

Animal Biodiversity and Conservation 39.1 (2016)

monophyletic origin of R. elsia and R. galapagoensis as it had been suggested in the preliminary phylogeny of the genus based on morphology (von Ellenrieder, 2003), with both species clustering together in the three reconstructed trees (Bayesian, Maximum likelihood, and Neighbor–Joining). Even though there was no absolute agreement on the position of all species, all three phylogenetic reconstructions also hint at the paraphyletic nature of the Neureclipa–group, with R. galapagoensis and R. elsia clustering with R. marchali or with R. cornigera and R. marchali, rather than with the remaining species of the Neureclipa–group. In conclusion, morphological, ecological and genetic evidence indicate that R. galapagoensis and R. elsia can be maintained as closely related but separate species. Acknowledgements Many thanks to Dennis Paulson for the picture of male R. elsia on figure 1. We thank Jeffreys Málaga for help with fieldwork, and the Galápagos National Park for permits to work in San Cristóbal. Wilson A. González, president of Procafé, made our work possible in the 'Hacienda El Cafetal', an organic coffee plantation that maintains a suitable habitat for the Odonates of San Cristóbal. Many thanks also to the staff at Procafé and to the personnel of the Galápagos Science Center at USFQ for their help with logistics, to Ana Dolenc (LEA–USFQ) for taking stereoscope pictures of larvae and to Valeria Ochoa (USFQ) for sharing her data on water quality of the streams at El Cafetal. This work was partially funded by a grant from the Spanish Ministry with competence in Science, including FEDER funds (CGL2011–22629), and a Galápagos Science Center grant to ACE. References Belle, J., 1991. A visit to the Galapagos islands. Selysia, 20: 2. Calvert, P. P., 1952. New taxonomic entities in Neotropical Aeshnas (Odonata: Aeshnidae). Entomological News, 63: 253–264. – 1956. The Neotropical species of the 'subgenus Aeschna' sensu Selysii 1883 (Odonata). Memoirs of the American Entomological Society, 15: 1–251. Campos, F. R., 1922. Catálogo sistemático y sinonímico de los Odonatos del Ecuador. Revista del Colegio Nacional Vicente Rocafuerte, 8–9: 1–75. Cordero Rivera, A., Lorenzo Carballa, M. O., Utzeri, C. & Vieira, V., 2005. Parthenogenetic Ischnura hastata (Say, 1839), widespread in the Azores Islands (Zygoptera: Coenagrionidae). Odonatologica, 34: 1–9. Currie, R. P., 1901. Papers from the Hopkins Satndford Galapagos expedition, 1898–1899. III. Entomological results (3): Odonata. Proceedings Washington Academy Sciences, 3: 381–389. Darwin, C., 1901. The origin of species. �� John Murray, London.

De Marmels, J., 1982. Dos náyades nuevas de la familia Aeshnidae (Odonata: Anisoptera). Boletín de Entomología de Venezuela, Nueva Serie, 2(12): 102–106. – 1990. Nine new Anisoptera larvae from Venezuela (Gomphidae, Aeshnidae, Corduliidae, Libelulidae). Odonatologica, 19(1): 1–15. – 2001. Aeshna (Hesperaeschna) condor sp. nov. from the Venezuelan Andes, with a redescription of A (H.) joannisi, comments on other species and descriptions of larvae (Odonata, Aeshnidae). International Journal of Odonatology, 4(2): 119–134. Fritz, G. N., Conn, J., Cockburn, A. & Seawright, J., 1994. Sequence analysis of the ribosomal DNA internal transcribed spacer 2 from populations of Anopheles nuneztovari (Diptera: Culicidae). Molecular Biology and Evolution, 11: 406–416. Hall, T. A., 1999. BioEdit: a user–friendly biological sequence alignment editor and analysis program for windows 95/98/T. Nucleic Acids Symposium Series, 41: 95–98. Hasegawa, M., Kishino, K. & Yano, T., 1985. Dating the human–ape splitting by a molecular clock of mitochondrial DNA. Journal of Molecular Evolution, 22: 160–174. Hebert, P. D. N., Ratnasingham, S. & de Waard, J. R., 2003. Barcoding animal life: Cytochrome c oxidase subunit 1 divergences among closely related species. Proceedings of the Royal Society of London B (Suppl.), 270: 96–99. Huelsenbeck, J. P. & Ronquist, F., 2001. MRBAYES: Bayesian inference of phylogenetic trees. Bioinformatics, 17: 754–755. Kimura, M., 1980. A simple method for estimating evolutionary rate of base substitutions through comparative studies of nucleotide sequences. Journal of Molecular Evolution, 16: 111–120. Kohli, M. K., Schneider, T., Müller, O. & Ware, J. L., 2014. Counting the spots: a molecular and morphological phylogeny of the spotted darner Boyeria (Odonata: Anisoptera: Aeshnidae) with an emphasis on European taxa. Systematic Entomology, 39: 190–195. Limongi, J., 1983 [1985]. Estudio morfo–taxonómico de nayades en algunas especies de Odonata (Insecta) en Venezuela. Memorias de la Sociedad de ciencias naturales 'La Salle', 43(119): 95–117. MacArthur, R. H. & Wilson, E. O., 1967. The theory of island biogeography. Princeton University Press, Princeton. Martin, R., 1908. Aeschnines. Collections zoologiques du Baron Edmund de Sélys–Longchamps, Catalogue Systématique et Descriptif, 18: 1–84. Muddeman, J., 2007. A new species for the Galapagos Islands: Great Pondhawk (Erythemis vesiculosa). Argia, 19: 17–18. Müller, O. & Schiel, F.–J., 2012. Description of the final instar larva of Rhionaeschna elsia (Calvert, 1952) (Odonata: Aeshnidae). Libellula Supplement, 12: 133–142. Musser, R. J., 1962. Dragonfly nymphs of Utah (Odonata: Anisoptera). University of Utah Biological Series, 12(6): vii + 74 pp.

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Appendix 1. Material studied: * Specimens for which DNA was sequenced. Apéndice 1. Material estudiado: * Especímenes para los que se secuenció el ADN. Anax amazili (Burmeister). 1♀ (#871)*, Ecuador, Colón Prov., San Cristóbal Island, unnamed stream (0º 54' 32.69'' S, 89º 29' 29.78'' W, 431 m), 26 II 2012, A. Cordero Rivera leg. [ACR]. Rhionaeschna absoluta (Calvert). 1♂ (#Ra1)*, Argentina, Salta Prov., pond at Finca Los Sauces (24° 28' 24'' S, 65° 22',45'' W, 1,568 m), 2 XII 2013, R. W. Garrison & N. von Ellenrieder leg. [RWG]; 1♂ (#Ra1)*, Argentina, Salta Prov., Chicoana, Quebrada de Tilián (25° 7' 51'' S, 65°32' 24'' W, 1,350 m), 26 I 2012, R. W. Garrison & N. von Ellenrieder leg. [RWG]. Rhionaeschna bonariensis (Rambur). 1♂ (#Rb4)*, Argentina, Salta Prov., pond at Finca Los Sauces (24° 28' 24'' S, 65° 22' 45'' W, 1,568 m), 2 XII 2013, R. W. Garrison & N. von Ellenrieder leg. [CSCA]; 1♀ (#Rb1)*, Uruguay, Paysandu Dep., arroyo Soto, ruta 26, km 52 (32° 3' 10'' S, 57° 40' 23'' W, 43 m), 12 IX 2008, D. Emmerich leg. [CSCA]; 1♀ (#Rb2)*, Argentina, Salta Prov., Chicoana, Quebrada de Tilián (25° 7' 51'' S, 65° 32' 24'' W, 1,350 m), 26 I 2012, R.W. Garrison & N. von Ellenrieder leg. [RWG]; 1♀ (#Rb3)*, Argentina, Salta Prov., Dique El Tunal, pond below dam (25° 13' 18'' S, 64° 28' 31'' W, 460 m), 27 I 2012, N. von Ellenrieder & R. W. Garrison leg. [RWG]. Rhionaeschna cornigera (Brauer). 1♂ (#234)*, Ecuador, Pichincha prov., river at Mindo (0° 04' 27'' S, 78° 45' 49'' W, 1,517 m), 15 V 2011, A. Cordero Rivera leg. [ACR]; 1♂ (#240)*, same data but (0° 04' 33'' S, 78° 34' 39'' W, 1,528 m) [ACR]; 1♂ (#241)*, Pichincha prov., Santa Rosa River, Maquipucuna (#241, 0º 07' 15'' N, 78º 37' 58'' W, 1,313 m), 7 V 2011, A. Cordero Rivera leg. [ACR]. Rhionaeschna diffinis (Rambur). 1♀ (Rd1)*, Chile, De Los Lagos Region, Valdivia Prov., río by road Coñaripe–Carrigüe, 5 II 1999, N. von Ellenrieder leg. [CSCA]; 1♀ (Rd2)*, Chile, De Los Lagos Region, Valdivia Prov., road San José de Mariquina–Valdivia, 30 km N Valdivia, 7 II 1999, N. von Ellenrieder leg. [CSCA]; 1♂ (Rd3)*, Chile, De Los Lagos Region, Osorno Prov., road Hueyusca–Bahía de San Pedro, 9 II 1999, N. von Ellenrieder leg. [CSCA]. Rhionaeschna elsia (Calvert). 7♂, 4♀: Peru, Arequipa Dept.: 1♂, Majes Canyon at Puerta Colorada (16° 16' 29'' S, 72° 27' 22'' W, 628 m), 22 I 1981, D. A. L. Davies leg. [RWG]; Lima Dept.: 1♂ paratype, vicinity of Villa (12° 12' S, 77° 1' W, 120 m), 15 III 1936, F. Woytkowski leg. [RWG]; Huanuco Dept.: 1♀, vicinity of Huanuco (9° 55' S, 76° 14' W, 1,793 m), 2 IX 1937, F. Woytkowski leg. [RWG]; 2♂ (Re1)*, 1♀ (Re2)*, Tacna Dept., Ite Wetlands (17° 55' 32'' S, 70° 56' 11'' W, 68 m), 2005, N. Flores leg. [CSCA]; 1♂ (Re3)*, same but [RWG]. Chile: Tarapacá Region, Arica Prov.: 1♀, Pampa de Chaca (18° 34' S, 70° 10' W), 5–8 XI 1955, L.E. Peña leg. [RWG]; 1♂, Azapa (18° 34' S, 70° 0' W), 8–10 XI 1955, L. E. Peña leg. [RWG]; 1♂ 1♀, Camarones, fertile valley in the middle of the desert (19° 0' S, 69° 47' W), 27–30 XI 1952, L. E. Peña leg. [CSCA]. Rhionaeschna galapagoensis (Currie). 6♂, 6♀, 3♂ ultimate instar exuviae, 2♀ ultimate instar larvae: �� Ecuador, Colón Prov., San Cristóbal Island: 2♂ (#851–#852)*, 1♀ (#853), 1♂ ultimate instar exuviae (#854), Hacienda El Cafetal, Camarones Stream (0° 55' 32'' S, 89° 32' 22'' W, 282 m), 20 II 2014, A. Cordero Rivera leg. [ACR]; 1♀ (#870), same data but 25 II 2014 [USFQ]; 1♂ (#869), same data but (0° 55' 27'' S, 89° 32' 20'' W, 191 m), J. Málaga leg. [USFQ]; 1♀ (#883), 2♂ ultimate instar exuviae (#860), same data but pond, 28 II 2014, A. Cordero Rivera leg. [ACR]; 1♂ (#884), same data but 3 III 2014 [RWG]; 2♀ ultimate instar larvae, same data but 22–23 II 2014, A. C. Encalada leg. [USFQ]. 1♂ (#866), Puerto Baquerizo Moreno, Playa Tijeretas (0° 53' 0'' S, 89° 36' 11'' W, 2 m), 24 II 2014, A. Cordero Rivera leg. [USFQ]; 1♀ (#878)*, Puerto Baquerizo Moreno, Playa Punta Carola (0° 53' 26'' S, 89° 36' 43'' W, 3 m), 27 II 2014, A. C. Encalada leg. [USFQ]; 1♂ (#880), 1♀ (#879), same data but [CSCA]; 1♀ (#877)*, same data but [RWG]. Rhionaeschna marchali (Rambur). 1♂, 1♀ (#222)*: Ecuador, El Ángel, Carchi prov.: 1♂ (0º 42' 59'' N, 78º 00' 54'' W, 3,669 m), 4 V 2011, A. Cordero Rivera leg. [ACR]; 1♀ (#223)*, Pichincha prov.: Paluguillo (0º 18' 11.2'' N, 78º 13' 41'' W, 3,966 m), 4 V 2011, A. Cordero Rivera leg. [ACR].

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Animal Biodiversity and Conservation 39.1 (2016)

Changing the pupal case architecture as a survival strategy in the caddisfly, Annitella amelia Sipahiler, 1998 (Insecta, Trichoptera) J. Alba–Tercedor, M. Sáinz–Bariáin & C. Zamora–Muñoz

Alba–Tercedor, J., Sáinz–Bariáin, M. & Zamora–Muñoz, C., 2016. Changing the pupal case architecture as a survival strategy in the caddisfly, Annitella amelia Sipahiler, 1998 (Insecta, Trichoptera). Animal Biodiversity and Conservation, 39.1: 65–75. Abstract Changing the pupal case architecture as a survival strategy in the caddisfly, Annitella amelia Sipahiler, 1998 (Insecta, Trichoptera).— In early autumn, pupal cases of the scarce caddisfly species, Annitella amelia Sipahiler, 1998 were collected on the shore of a narrow, shallow brook in the northwestern Iberian peninsula, in Spain. Some of the pupal cases had been built as a new tube inside an existing tubular case. Moreover, for pupation, the last instar larvae clearly changed the architecture of the cases by adding internal and/or external grains of substrate at the tips. An architectural study with micro–CT techniques made it possible to divide each case into equal halves and to indirectly measure the weight of each. As no significant differences were found, it was concluded that pupa balances its case, ensuring that it will lie horizontally on the substrate of the brook and thus avoid more vertical positions that might risk air exposure. The architectural changes could represent a survival strategy during pupation, in which the pupae remain in shallow channels ditches of small brooks. Key words: Caddisfly, Trichoptera, Micro–CT, Pupal case architecture, Survival strategy Resumen Cambio de la arquitectura del estuche pupal como estrategia de supervivencia en el tricóptero, Annitella amelia Sipahiler, 1998 (Insecta, Trichoptera).— A principios de otoño, se recogieron estuches pupales de Annitella amelia Sipahiler 1998, una especie muy poco frecuente de tricóptero, en las orillas de una pequeño arroyo de cabecera situado en el noroeste del península ibérica, en España. Algunos de los estuches se habían construido como un nuevo tubo dentro de otro. Asimismo, para la pupación, la larva cambiaba la arquitectura agregando granos de sustrato en los extremos, interna o externamente. Mediante técnicas de microtomografía computerizada, se estudió la arquitectura de las construcciones y fue posible dividir cada estuche en dos mitades iguales y medir de forma indirecta el peso de cada una de ellas. Al no observarse diferencias significativas, se concluyó que las pupas equilibran el peso de las dos mitades de forma que el estuche se deposite horizontalmente en el fondo del arroyo, lo que evita el riesgo que supondría que permaneciese expuesto al aire si quedasen en una posición más vertical. Los cambios arquitectónicos podrían ser una estrategia de supervivencia durante el período de pupación, en el que las pupas permanecen en las orillas de diminutos arroyos de escasa profundidad. Palabras clave: Tricópteros, Micro–TC, Arquitectura de estuches pupales, Estrategia de supervivencia Received: 29 IX 15; Conditional acceptance: 3 XI 15; Final acceptance: 16 XI 15 J. Alba–Tercedor, M. Sáinz–Bariáin & C. Zamora–Muñoz. Dept. of Zoology, Fac. of Sciences, Univ. of Granada, Campus de Fuentenueva, 18071 Granada, Spain. Corresponding author: J. Alba–Tercedor. E–mail jalba@ugr.es

ISSN: 1578–665 X eISSN: 2014–928 X

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Introduction Caddisfly (Trichoptera) larvae have been living in freshwater for some 200 million years. Evolutionarily, Trichoptera are closely related to Lepidoptera. The larvae resemble caterpillars that secrete silk, which is aggregated to different elements of substrate to build protective cases. After the larval period, to carry out pupation for complete underwater metamorphosis, the insects have to sealing themselves off for long periods in locations where they are vulnerable to predators, parasitoids, and environmental changes (Wiggins, 2004). Annitella amelia Sipahiler, 1998, a scarce European caddisfly species (Trichoptera, Limnephilidae) considered to be distributed in Portugal only, was recently recorded in a region of Galicia in Spain (Sáinz–Bariáin & Zamora–Muñoz, 2012). Pupal cases were collected in a narrow brook. Some of the pupal cases had been built as a new tube inside an already existing tubular case. Moreover, for pupation, the last instar larva clearly changed its architecture by adding internal and/or external grains of substrate. Thus, we made a detailed study of its architecture using the micro–CT facilities in our laboratory. We hypothesize that the last instar larva changes the architecture of the case by adding substrate elements to ensure that each half has a similar weight, thereby increasing the likelihood that the case will lie horizontally. This survival strategy helps to guarantee that the pupa remains submerged in the water until the adult can emerge and fly. Material and methods Six pupal cases from the specimens of A. amelia collected in a previous study (Sáinz–Bariáin & Zamora–Muñoz, 2012) were scanned using the micro–CT SkyScan 1172 C (with a 0.5 mm aluminum filter, source voltage = 64 KV, source current = 100 µA, and image voxel size = 13–15 µm. Rotation step = 0.5º, 180º of rotation scan) (figs. 1, 2). Bruker–Skyscan free software (®NRecon, ®CTan, ®DataViewer, and ®CTvox) was used to reconstruct and process the images, enabling not only reconstruction but also virtual slicing and volume–rendering reconstructions (Alba–Tercedor, 2014). No stain was used. Data–set images of each case were reoriented with DataViewer, providing complete horizontal/vertical longitudinal sections, and fully transversal cross–section slices. Finally, a new dataset, corresponding to the selected transversal cross–section of the new volume of interest (VOI) was saved (fig. 3A). This new dataset was reopened with DataViewer to create a new shadow projection (these being the small figures on top of the regular shadow projections of figures 1 and 2). Afterwards, using CTAn software, each tubular case was virtually divided in two halves (external and internal; figs. 4B, 4D), and by running the 3D analysis plugin of CTAn, we calculated the total surface area (as well the total volume) of substrate grains for each half (fig. 3C). We selected the appropriate option of that plugin and calculated the thickness structure.

Finally, we made volume–rendering images using CTVox, representing the substrate grains with different colors according to their respective coarseness. As in previous papers (Alba–Tercedor et al., 2014), we followed the methodology detailed in Bruker–Micro– CT’s Method Notes (Bruker–Micro–CT, 2014a, 2014b). Statistical differences between grain volume and surface (of external and internal case halves) were tested using non–parametric Sign tests (StaSoft Inc, 2005). Results Three cases (#1, #2 and #6) were doubles, with an additional tube inside (figs. 1A, 1B, 2C), while the others (cases #3, #4 and #5) presented a single–tube architecture (figs. 1C, 2A, 2B). In all cases, conspicuous coarser rock grains appeared at both ends. Some of these grains were especially conspicuous: the large grain situated internally in between the external and internal tube (figs. 1A, 3A, 5D, 5F, 5G), the large grain fixed opposite to the external opening of the tube (case #2: fig. 1B), and in case #3, the external accumulation of visible coarser grains (fig. 1C). Cases #4 and #5 had accumulations of grains at both ends (figs. 2A, 2B). To explain the above observations, we propose a starting hypothesis as follows: the architecture of the pupal case should maintain a balanced weight of the two halves, the 'external' opening half (We), and the 'internal' half (Wi) (fig. 6A). On the contrary, either if Wi < We or if Wi > We, the case would have a high likelihood of lying on the substrate in a vertical or close to vertical position, but not a horizontal position (see figure 6B, and left case positions in fig. 6C). Then, if the water level decreases, cases not lying horizontally would have higher probabilities of being exposed to the air and drying up (compare the left and right situations in figure 6C: the case marked with an arrow would be exposed in case of a minor decrease in the water level). Figure 7 shows the small brooks where the pupal cases were collected and the detail of the shallow ditches. If the hypothesis were correct, we should find a similar weight in both halves of each case, regardless of whether or not they are doubles (a new tube inside an old one). Thus, the cases were indirectly weighed, measuring the total surface and total volume of the whole grains of substrate on each half (assuming the simplification that all grains have a similar density and considering that both volume and surface are directly related to weight). Table 1 summarizes the results for the total surface area (μ2) and total volume (μ3) of the substrate grains from the external (with the opening) and internal halves. Figure 4 shows the comparisons of the total surface areas and total volumes of the external and internal halves of the pupal case. After calculating the thickness structure of the substrate grains used to build case #1, we observed that the volume reconstructions by CTVox rendered as colored images permitted the grains of the case to be visually distinguished according to their coarseness. Thus, figure 5 clearly shows that the coarser grains are

Animal Biodiversity and Conservation 39.1 (2016)

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Fig. 1. Shadow projection (X–ray) images of the caddisfly pupal cases studied (A. Case #1; B. Case #2; C. Case #3). Above each X–ray image there are new shadow projections captured with DataViewer after the images were reoriented and reopened (see text for details): A. Source voltage = 56 kv, source current = 100 µA, pixel size = 13.06 µm; B. Source voltage = 64 kv, source current = 100 µA, pixel size = 14.15 µm; C. Source voltage = 64 kv, source current = 100 µA, pixel size = 13.97 µm. Fig. 1. Imágenes de rayos X de los estuches pupales de tricópteros estudiados (A. Estuche #1; B. Estuche #2; C. Estuche #3). Encima de cada imagen de rayos X se sitúan reconstrucciones adicionales, obtenidas con el programa informático DataViewer, tras reorientar su posición (véase el texto para obtener más detalles): A. Voltaje de la fuente de alimentación = 56 kv, intensidad de la fuente de alimentación = 100 µA, tamaño de vóxel = 13,06 µm; B. Voltaje de la fuente de alimentación = 64 kv, intensidad de la fuente de alimentación = 100 µA, tamaño de vóxel = 14,15 µm; C. Voltaje de la fuente de alimentación = 64 kv, intensidad de la fuente de alimentación = 100 µA, tamaño de vóxel = 13,97 µm.

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Fig. 2. Shadow projection (X–ray) images of caddisfly pupal cases studied (A. Case #4; B. Case #5; C. Case #6). At the top of each X–ray image there are new shadow projections images captured with DataViewer after the images were reoriented and reopened (see text for details): A, B, and C. Source voltage = 64 kv; source current = 100 µA; pixel size = 15.06 µm. Fig. 2. Imágenes de rayos X de los estuches pupales de tricópteros estudiados (A. Estuche #4; B. Estuche #5; C. E estuche #6). Encima de cada imagen de rayos X se sitúan reconstrucciones adicionales obtenidas con el programa informático DataViewer, tras reorientar su posición (véase el texto para obtener más detalles): A, B y C. Voltaje de la fuente de alimentación = 64 kv; intensidad de la fuente de alimentación = 100 µA; tamaño de vóxel= 15,06 µm.

Animal Biodiversity and Conservation 39.1 (2016)

Fig. 3. Data–set images of each case were reoriented with DataViewer, making it possible to obtain complete horizontal/vertical longitudinal sections, and fully transversal cross–section slices (A). The reoriented fully transversal cross–section (indicated with a red arrow in A) was saved as a new volume of interest (VOI) data set, and reopened with DataViewer to create a new shadow projection the one used when opened with CTAn for analysis (B). Each tubular case was virtually divided into two halves (B: external and D: internal), and with the CTAn’s 3D analysis plugin the total surface area (as well the total volume) of the substrate's grains for each half was calculated (C). Note that volume renderings of the external and internal halves represented in D, are only to facilitate an understanding of the process, but all the calculation process of total volume and total surface area of the grains from each half was calculated directly with CTAn. Fig. 3. El conjunto de imágenes de cada estuche se reorientó mediante DataViewer para poder obtener secciones horizontales y verticales completas y cortes completamente transversales (A). La sesión transversal perfectamente reorientada (indicada con una flecha roja en A) se guardó como una serie de imágenes que representan un nuevo volumen de interés (VOI) que con DataViewer permitió crear nuevas imágenes y que fue usado con CTAn para el análisis (B). Cada estuche tubular se dividió virtualmente en dos mitades (B: externa y D: interna) y, mediante el complemento para análisis 3D de CTAn, se calcularon la superficie total y el volumen de los granos de substrato de cada mitad (C). Las reconstrucciones volumétricas de las mitades externas e internas, representadas en D, son simplemente para ayudar a comprender el proceso, pero todo el proceso para calcular el volumen total y la superficie total de los granos de substrato de cada mitad se realizó directamente con CTAn.

Alba–Tercedor et al.

5E7

Total surface (µ2)

4E7

Mean Mean ± SD Mean ± 1.96*SD

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Total volumen (µ3)

4E6

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IntS

Mean Mean ± SD Mean ± 1.96*SD

3E6 3E6 2E6 2E6 1E6 5E6

ExtV

IntV

Fig. 4. Box and whisker plots comparison of the total surfaces (A) and total volumes (B) of the external (with the opening) and internal halves of the pupal case of Annitella amelia as indirect measures of weight. No statistical significance was found between the two halves (p > 0.2 and p > 0.6). However, the internal halves clearly tended to be slightly heavier (with higher values of total surfaces and total volumes). This is because in the external halves the pupa itself and some extra grains to seal the case were not included in the scans (see text for details). Fig. 4. Comparación mediante diagramas de cajas y ''whisker plot'' de la superficie total (A) y el volumen total (B) de las mitades externas (con la abertura del estuche) e internas del estuche pupal de Annitella amelia como medidas indirectas de peso. No se encontraron diferencias estadísticas significativas entre ambas mitades (p > 0,2 y p > 0,6). Sin embargo, se observó una clara tendencia a que la mitad interna fuera ligeramente más pesada (con mayores valores de superficie total y volumen total). Esto es debido a que en la mitad externa tanto la pupa como los granos de sustrato adicionales para cerrar el estuche no se incluyeron en los escaneos (véase el texto para obtener más detalles).

Animal Biodiversity and Conservation 39.1 (2016)

min. <- thickness -> max.

A > 1 mm <

Fig. 5. CTVox volume renderings of case #1. Colors represent the thickness structure (see bar scale): A. External view, F. Internal longitudinal section; G. The same as F but the rendering was made in regular gray–value images. Figures B, C, D and E, respectively, represent cut portions of the case corresponding to different segments (note that they are slightly rotated to the left to show the inside content): A. Anterior (external); B, D. Middle; E. Posterior (internal). Fig. 5. Reconstrucciones volumétricas del estuche #1, obtenidas con CTVox. Los colores representan el grosor de las estructuras (véase la escala): A. Vista externa; F. Sección longitudinal interna; G. Igual que F pero la reconstrucción volumétrica de la imagen se hizo tonos grises. En las figuras B, C, D y E se representan, respectivamente, los cortes del estuche a distintos niveles (obsérvese que están ligeramente rotados a la izquierda para poder ver el contenido interior): A. Anterior (exterior); B, D. Media; E. Posterior (interna).

Alba–Tercedor et al.

Wi (weight of the internal half)

Wi < We

We (weight of the external half)

Wi > We

Wi We

water level

Fig. 6. The starting hypothesis: the architecture of the pupal case should maintain the weight of both halves balanced (A): the 'external' opening half (We), and 'internal' half (Wi). On the contrary (B), either if Wi < We or if Wi > We, there would be a high probability that the case on the substrate would take a vertical or close to vertical position, but not horizontal (see left case positions on C). Thereafter, if the water level descends, cases not lying horizontal would have high probabilities of exposure to the air and drying (compare left and right situations on C: the case indicated with an arrow would be exposed in case of a slight descent in the water level). Fig. 6. La hipótesis de partida: la arquitectura del estuche pupal debería estar dirigida a mantener equilibrado el peso de las dos mitades (A): la mitad ''externa'' de la abertura (We) y la mitad ''interna'' (Wi). Por el contrario (B): tanto si Wi < We como si Wi > We, existiría una elevada probabilidad de que el estuche permaneciera en el sustrato en posición vertical o casi vertical, pero no en posición horizontal (véase la posición de los estuches a la izquierda en C). Así, si el nivel del agua desciende, los estuches que no estén en posición horizontal tendrían una gran probabilidad de quedar expuestos al aire y secarse (compárense las situaciones izquierda y derecha en C: el estuche señalado con una flecha quedaría expuesto en caso de que se produjera un leve descenso del nivel del agua).

Animal Biodiversity and Conservation 39.1 (2016)

Pupae in the remaining stream ditches 1 cm

Fig. 7. General aspect of the small brooks from where the pupal cases were collected and detail of the small and shallow ditch. Fig. 7. Aspecto general de los pequeños arroyos donde se colectaron los estuches pupales y detalle del cauce reducido y poco profundo.

concentrated at each end (figs. 5A, 5B, 5D, 5E), while the central part is constructed with finer elements. The elements used for the new inner tube were constructed with finer (≈ lighter) grains than those surrounding the external tubular case (fig. 5F). Discussion When comparing the total surface area of the grains (both from the external parts and those from the internal parts of the pupal cases), the values were similar (no statistical significance, p > 0.2; although the internal half tended to be slightly heavier (with higher values of total surface area) than the external half (table 1, fig. 4). Similarly, for total volumes and external/internal halves, no statistically significant differences were found (p > 0.6). Moreover, the internal halves tended to be slightly heavier (with higher values of total volume) than the external halves. This can be explained taking into account that once the last instar larva finishes building the pupation case, the larva uses silk to fix additional grains to close the external opening. The weight of the

new grains, even when small, must be heavy enough to balance the weight of the external half. Moreover, the equilibrium should also be established with the weight of the pupa itself, which although small is not negligible. The clear architectural behavior of the last instar larva is striking because it adds the appropriate heavier or lighter element to avoid any weight bias of either half of the pupal case, as shown in figure 5. It is important to point out that the observed equilibrium, ensuring that the weight of the case is similar in both halves, applies regardless of whether or not cases are double. Typically, case–carrying caddisflies pupate in the larval case after they have fixed it to coarser material from the stream bottom and sealed off the anterior opening with a silk, perforated cover (Wiggins, 2004). This is a significant behavioral distinction of the suborder Integripalpia (most of the case–carrying caddisflies), and therefore species departing from the normal behavior are noteworthy (Wiggins, 2001). A few species of limnephilids, brachycentrids, and phrygaenids can build new cases before pupation (Malicky, 2000); several papers have discussed the phylogenetic significance of

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Table 1. Total surface (µ2) and total volume (µ3) of the substrate grains from the external (with the opening) and internal halves, determined with CTAn’s 3D plugin: ExtS. External surface; IntS. Internal surface; ExtV. External volume; IntV. Internal volum; * 'Double' cases (see figure 3 and text for details). Tabla 1. Superficie total (µ2) and volumen total (µ3) de los granos de sustrato de las mitades externas (con abertura) e internas, obtenidos mediante el complemento 3D del programa informático CTAn: ExtS. Superficie externa; IntS. Superficie interna; ExtV. Volumen externo; IntV. Volumen interno; * Estuches dobles (véase la figura 3 y el texto para obtener más detalles). Cases

#1*

#2*

#6*

Means

ExtS

35323199

24801167 27063499

23048370 21258677

32091636 27264424.667

IntS

36720348

32742492 26040551

29254573 30881087

38343592 32330440.500

ExtS/IntS

0.96

0.76

1.04

0.79

0.69

0.84

0.85

IntS/ExtS

1.04

1.32

0.96

1.27

1.45

1.19

1.21

ExtV

1966790

2234408

1972342

1488350

1405858

2565488

1938872.667

IntV

3443146

2158977

1949663

2780136

3050464

2866918

2708217.333

ExtV/IntV

0.57

1.03

1.01

0.54

0.46

0.89

0.75

IntV/ExtV

1.75

0.97

0.99

1.87

2.17

1.12

1.48

building a new case for pupation (Malicky, 2000; Wiggins, 2001; Bohle, 2004). Nevertheless, this behaviour is not a generalization, and intraspecific variability has been recorded (Statzner, 2011). Even if a new case is not built for pupation, the pupal case of case–carrying caddisflies may have some mineral fragments that are lacking in the larval case (Wiggins, 2004), which the larvae presumably has to find near the location where they pupate. This applies to certain goerids and odontocerids in which their larvae close the tube openings with small pieces of gravel prior to pupation. However, this behaviour has not been recorded before for limnephilids. Thus, the presence of double cases in A. amelia is a new finding in the literature available. This finding raises the question as to whether the external tube of these double cases represents the reuse of an abandoned empty cases from another species, or whether it is an addition for pupation inside the existing tube. The answer to this question requires additional experiments with live larvae. Conclusions The micro–CT study of the pupal cases of the caddisfly species Annitella amelia indicates that before pupation, the last–instar larvae either search actively for an abandoned tubular case where they build a new tube inside or use only their own case for pupation. In both situations, they need to seal the opening with new grains. This would imply an increase in weight at that end, biasing the overall weight (this is more apparent when a new tube inside an existing case is built). Therefore, the larva must manipulate the architecture by adding new grains to the opposite half (either outside or inside the case) to balance the weight of

the two halves. Once the pupal case is closed, it has more likelihood of lying horizontally on the bottom of the brook, thus avoiding air exposure in the event of a fall in the water level. Pupal cases were located on the shore of a narrow brook in early autumn (Sáinz– Bariáin & Zamora–Muñoz, 2012). During pupation (in most caddisfly species lasting ca. three weeks) there is a high probability of fluctuations in water level (this applies especially to the shore sites where the pupal cases were located), and hence the advantage of the observed architectural behaviour of adding elements to balance the weight of the case favors its horizontal position on the bottom of the brook. This survival strategy increases the probability that the insect will remain submerged in the water during development and until the adult emerges and flies. Acknowledgments We thank Bruker–Skyscan staff for fast and effective support, their patience and effectiveness, and for their constant improvements to the software and in implementing new options we requested. Also for their kindness in providing the senior author fast and effective suggestions and answers to queries. In this respect, we are especially indebted to: Alexander Sasov, Stephan Boons, Xuan Liu, Phil Salmon, Jeroen Hostens, and Vladimir Kharitonov. An advance of this work was presented during the 2015 Bruker–micro–CT users meeting, supported by NIFA grant 'Developing an Infrastructure and Product Test Pipeline to Deliver Novel Therapies for Citrus Greening Disease', 2015. Lead Dr. S. Brown, Kansas State University & USDA. We are very grateful to Modesto Berbel for his field assistance, to Jesús Martínez–Menéndez for his help

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in the sampling logistic and to Professor János Oláh for financial support. This research was also funded by the OAPN of the Ministerio de Medio Ambiente y Medio Rural y Marino de España (project ref: 039/2007). Marta Sáinz–Bariáin was supported by a PhD grant from the Gobierno de Navarra. We also thank Marcos González for constructive comments on the manuscript and David Nesbitt for checking the English. References Alba–Tercedor, J., 2014. From the sample preparation to the volume rendering images of small animals: A step by step example of a procedure to carry out the micro–CT study of the leafhopper insect Homalodisca vitripennis (Hemiptera, Cicadellidae). Bruker Micro–CT Users Meeting 2014: 260–288. Available at: http://www.skyscan.be/company/ UM2014/000_AbstractBook2014.pdf. Alba–Tercedor, J., Ascaso, C. & Wierzchos, J., 2014. Using micro–CT to explore pore contents in the ignimbrite, a volcanic rock in the Atacama Desert with endolithic microbial communities: the microhabitat potentially expected on Mars. In Bruker Micro–CT Users Meeting 2014: 47–55. Alba–Tercedor, J., Sáinz–Bariáin, M. & Zamora–Muñoz, C., 2015b. Using Micro–CT to elucidate the pupal case architecture as a survival strategy of a caddisfly. In: Bruker Micro–CT Users Meeting 2015: 163–172.

Bohle, H. W., 2004. Larval and pupal case building in Trichoptera: a comment to articles of G. B. Wiggins and H. Malicky in Braueria 27 and 28. Braueria, 31: 9–10. Bruker–Micro–CT, 2014a. How to make color–coded 3D models for structure thickness in CTVox Method note. Bruker–Skyscan Method Notes, 25: 1–10. – 2014b. How to make color–coded size distributions in CTVol Method note. Bruker–Skyscan Method Notes: 1–16. Malicky, H., 2000. Which caddis larvae construct a new case for pupation? Braueria, 27: 19–20. Sáinz–Bariáin, M. & Zamora–Muñoz, C., 2012. New record of Annitella amelia Sipahiler, 1998 (Trichoptera, Limnephilidae) in the Iberian Peninsula. Boletín de la Asociación española de Entomologia, 36(1–2): 203–205. StaSoft Inc, 2005. StatSoft. Statistica Data analysis software system, version 7. Available at: http:// www.statsoft.com/. Statzner, B., 2011. Mineral grains in caddisfly pupal cases and streambed sediments: assesing resource use and its limitation across various river types. Annales de Limnologie – International Journal of Limnology, 47: 103–118. Wiggins, G. B., 2001. Construction behavior for new pupal cases by case– making caddis larvae: Further comment. (Trichoptera: Integripalpia). Braueria (Lunz am See, Austria), 28: 7–9. – 2004. Caddisflies: the underwater architects. University of Toronto Press, Toronto, Bufalo, London.

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Environmental determinants and spatial mismatch of mammal diversity measures in Colombia J. F. González–Maya, A. Arias–Alzate, R. Granados–Peña, N. J. Mancera–Rodríguez & G. Ceballos

González–Maya, J. F., Arias–Alzate, A., Granados–Peña, R., Mancera–Rodríguez, N. J. & Ceballos, G., 2016. Environmental determinants and spatial mismatch of mammal diversity measures in Colombia. Animal Biodiversity and Conservation, 39.1: 77–87. Abstract Environmental determinants and spatial mismatch of mammal diversity measures in Colombia.— Including complementary diversity measures into ecological and conservation studies should improve our ability to link species assemblages to ecosystems. Recent measures such as phylogenetic and functional diversity have furthered our understanding of assemblage patterns of ecosystems and species, allowing improved inference of ecosystem function and conservation. We evaluated spatial patterns of taxonomic, phylogenetic and functional diversity of mammals in Colombia and identified their main environmental determinants, as well as interrelationships and spatial mismatch between the three measures. We found significant effects of elevation and precipitation on species richness, slope and species richness on phylogenetic diversity, and slope and phylogenetic diversity on functional diversity. We also identified a spatial mismatch of the three measures in some areas of the country: 12% of the country for species richness and 14% for phylogenetic and functional diversity. Our results highlight the importance of including species relationships within environmental drivers with biogeographical and distribution analyses and could facilitate selection of priority areas for conservation, especially when mismatch occurs between measures. Key words: Environmental filtering, Functional diversity, Phylogenetic diversity, Species richness Resumen Factores ambientales y discrepancia espacial de las medidas de diversidad de mamíferos en Colombia.— La inclusión de medidas complementarias de diversidad en los estudios de ecología y conservación debería mejorar nuestra capacidad de establecer vínculos entre los ensamblajes de especies y los ecosistemas. Medidas recientes como la diversidad filogenética y la funcional han mejorado nuestra comprensión de los patrones de ensamblaje de las especies y los ecosistemas, lo que ha permitido mejorar las inferencias sobre el funcionamiento y la conservación de los ecosistemas. Hemos evaluado la distribución espacial de la diversidad taxonómica, filogenética y funcional de mamíferos en Colombia, y hemos identificado los principales factores ambientales que la determinan, así como las relaciones y la discrepancia espacial entre las tres medidas. Hemos observado que la elevación y la precipitación ejercen un efecto significativo en la riqueza de especies; la pendiente y la riqueza de especies, en la diversidad filogenética; y la pendiente y la diversidad filogenética, en la diversidad funcional. Asimismo, hemos observado una discrepancia espacial entre las tres medidas en ciertas regiones del país: en el 12% del país para la riqueza de especies y en el 14% para la diversidad filogenética y funcional. Los resultados ponen de manifiesto la importancia de incluir las relaciones existentes entre las especies y los factores determinantes ambientales en los análisis biogeográficos y de distribución, y pueden facilitar la selección de áreas prioritarias para la conservación, en especial cuando existen discrepancias entre las medidas. Palabras clave: Filtrado ambiental, Diversidad funcional, Diversidad filogenética, Riqueza de especies

ISSN: 1578–665 X eISSN: 2014–928 X

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Received: 06 II 15; Conditional acceptance: 31 VIII 15; Final acceptance: 20 I 16 José F. González–Maya & Gerardo Ceballos, Inst. de Ecología, Univ. Nacional Autónoma de México, Apdo. postal 70–275, México DF, 04510 México.– José F. González–Maya, Proyecto de Conservación de Aguas y Tierras, ProCAT Colombia/Internacional, Bogotá, Colombia.– Andrés Arias–Alzate, Lab. de Análisis Espaciales, Inst. de Biología, Univ. Nacional Autónoma de México, México DF, 04510 México.– Ramón Granados–Peña & Néstor Javier Mancera–Rodríguez, Depto. de Ciencias Forestales, Fac. de Ciencias Agropecuarias, Univ. Nacional de Colombia, Medellín, Colombia. Corresponding author: J. F. González–Maya. E–mail: jfgonzalezmaya@gmail.com

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Introduction Measuring biological diversity has become a major research challenge in the increasingly interdisciplinary fields of ecology and conservation biology (Cardillo et al., 2008; DeFries et al., 2010). Traditional measures have emphasized species richness and evenness (Purvis & Hector, 2000), but more sophisticated measures including evolutionary history and species function within ecosystems have recently been used (Buckley et al., 2010; Cadotte et al., 2011). These new measures purportedly allow more precise and comprehensive assessments of ecological and conservation issues related to biodiversity across spatial and temporal scales (Rosenzweig, 1995; Hadly & Maurer, 2001; Cadotte et al., 2011). However, interpreting the results of phylogenetic and functional diversity remains a challenge, particularly in understanding mechanisms potentially responsible for observed patterns (Calba et al., 2014; González–Maya et al., 2016). This situation hinders what could otherwise be considered a substantive advance in comprehensive conservation planning (Devictor et al., 2010; Dalerum, 2013; Dehling et al., 2014). Phylogenetic diversity is a measure of evolutionary history, such as the diversity within an assemblage (Collen et al., 2011). It provides insights into the evolutionary distinctiveness of an assemblage and can be used to estimate the evolutionary potential for future ecosystem performance (Dalerum, 2013). In contrast, functional diversity incorporates elements of biodiversity that represent how ecosystems function (Dıa ́ z & Cabido, 2001) and is important for understanding current ecosystem dynamics, resilience and services (Tilman et al., 1997; Díaz et al., 2013). Continued environmental degradation places growing pressure on the world´s biodiversity (Flynn et al., 2009), leading some authors to suggest we are facing the sixth mass extinction (Barnosky et al., 2011; Pimm et al., 2014; Ceballos et al., 2015). As the complexities of ecosystems and species interactions are unraveled, comprehensive and interdisciplinary conservation schemes are needed to account for the dynamic and interwoven patterns in the tapestry of the world´s natural capital (Dalerum et al., 2009; Devictor et al., 2010; Dalerum, 2013; Zupan et al., 2014). Incorporating multiple measures of species diversity including species richness, but more importantly evolutionary history and ecosystems functioning into planning, would be a major advance in conservation (Dalerum, 2013). The Neotropical region has high biodiversity (Mora et al., 2011), but is one of the least biologically known regions of the world (Myers et al., 2000; Cardillo et al., 2006). This knowledge gap is a constraint for comprehensive conservation planning (Boitani et al., 2011; Visconti et al., 2011), exacerbated by our limited knowledge of how environmental drivers influence species diversity (Kerr, 1997; Colwell et al., 2008; Rondinini et al., 2011b; González–Maya et al., 2016). Most previous assessments of priority setting for the Neotropical region have focused on classic measures such as species richness (Gerardo Ceballos, 2007; Jenkins & Giri, 2008; Forero–Medina & Joppa, 2010;

González–Maya et al., 2015), but few analyses have explored multi–measure approaches to account for evolutionary history and ecosystem function, and most analyses have been at global scales (Safi et al., 2011). As a first step to further our understanding of biodiversity patterns, we provide the first nation– wide assessment of terrestrial mammal diversity in the mega–diverse country of Colombia using a new generation of measurement tools. Specifically, we assessed i) spatial patterns of species richness, functional and phylogenetic diversity, ii) the influence of environmental factors on these patterns, and iii) the spatial mismatch of the three measures. Material and methods We first developed a grid of 127 points located in the centroid of 1 x 1 degree cells over the country, defining these cell centroids as our sampling unit. We selected this coarse resolution to match the scale of global distribution maps for mammal species developed for the IUCN Red List of Threatened Species (IUCN, 2012; Schipper et al., 2008) since the country lacks information for finer resolution. As these species distribution maps were developed for the global scale, we used this spatial resolution to reduce potential bias from overestimated distribution polygons and with illustrative purposes (González–Maya et al., 2015); nevertheless, we acknowledge potential limitations of using such a coarse resolution (Rondinini et al., 2011a). Therefore, our approach is based on centroids, namely sampling points, and regardless of the cell size, the data come from specific localities not related with resolution. Cells are used only for illustrative purposes, since points (e.g., random) do not allow to illustrate spatial patterns. Based on these distribution polygons, we extracted those species present or potentially present in the country (González–Maya et al., 2012, 2015, 2016). We calculated the centroid of each cell (i.e., cell geographic center) and extracted all species overlapping each centroid as a proxy of the species assemblage present in each cell (Safi et al., 2011). Given there is no other detailed information for the country regarding species distributions (Solari et al., 2013) and as these polygons were corrected by national experts (Schipper et al., 2008), we believe this was the best available approach for country–wide mammal analyses (González–Maya et al., 2015, 2016). For cells overlapping the edge of the country, we estimated the centroid after clipping the perimeter of the country over the grid. For each cell assemblage we calculated species richness and phylogenetic and functional diversity. phylogenetic diversity (PD) was estimated using the Meredith et al. (2011) phylogenetic tree and Faiths phylogenetic diversity index (Faith, 1992), which is based on the sum of the branches connecting all species in phylogenetic space for a given species assemblage. Functional diversity (FD) was calculated using the Petchey and Gaston FD index (Petchey & Gaston, 2002b; Safi et al., 2011; González–Maya et al., 2016), where the FD index is defined as the sum

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of the branches necessary to connect all species in trait space. To do this, we first estimated a matrix of distances based on the Gower distance (because we used both qualitative and quantitative traits) and built a dendrogram with this distance matrix. We then summed the distance of all branches within the tree for each assemblage (Petchey & Gaston, 2002b). High FD values indicate high complementarity of species functions, therefore low redundancy based on the traits used and low values indicate lower diversity of species functions, thus higher redundancy (Safi et al., 2011). We used Pearson’s correlation to assess the degree of lineal relationships of the three measures. Even although new measures have improved Faiths phylogenetic diversity index (Chao et al., 2015), we still used this approach because it is the most similar approach to FD and because our analyses is not based on sampling data. We determined functional traits for each species using the PanTHERIA database (Jones et al., 2009), updates by Davidson et al. (2009), and our own revision, including activity (i.e., diurnal, nocturnal, crepuscular, or cathemeral), diet (i.e., insectivore, frugivore, herbivore or carnivore), habits (i.e., terrestrial, arboreal, aquatic, fossorial or scansorial) and body mass (g). All traits are available in other sources, and we note that not all species had complete data, especially those known only from a few localities or those with no distribution information available through the IUCN database. We therefore used approximations to trait values based on the closest species relative within the same genus. To assess the effects of environmental variables on diversity measures, we estimated mean cell annual precipitation and temperature, elevation and slope. Precipitation and temperature (i.e., annual precipitation (BIO12) and annual mean temperature (BIO1)) were calculated from the WorldClim database (Hijmans et al., 2005) based on representative estimates from 1950–2000 at 30 arc–seconds, while elevation and slope were derived from the Hydro1k Digital Elevation Model for South America, also at 30 arc–seconds (US Geological Survey, 2012). We used ordinary least squares regression to assess the influence of environmental variables on species richness (González–Maya et al., 2016), the influence of the environmental drivers and species richness on phylogenetic diversity, and the influence of environmental variables, species richness and phylogenetic diversity on functional diversity. For each measure, we generated all possible variable combinations without interaction of model terms, including 15 models for species richness, 31 for phylogenetic diversity and 63 for functional diversity (supporting information). We identified the best performing models using Akaike Information Criteria corrected for small samples (AICc) and Akaike weights (Wagenmakers & Farrell, 2004), selecting those models with Δ > 2 as significantly best–performing models (Burnham & Anderson, 1998; Burnham et al., 2011). We used adjusted R2 values to estimate the proportion of variation in the dependent variable explained by the model variables. After selecting the best models

according to AICc, we identified the variables of the best performing models and we calculated the variable coefficients and the Variance Inflation Factor (VIF) to assess correlation among them; models containing variables with scores > 7.5 were considered correlated (O’Brien, 2007). As we ran all main effect model combinations, when this occurred we discarded those models and selected the model with the next lowest AICc value (O’Brien, 2007). We estimated the Koenker studentized Breusch– Pagan statistic, K(BP), to assess the reliability of standard errors when heteroscedasticity was present. If the K(BP) was significant, we used the robust probability instead of the raw probability estimation (Breusch & Pagan, 1979; Koenker, 1981). Heteroscedasticity and non–stationarity indicate that the relationship between the dependent variable and the drivers would not change with changes in the magnitude of the drivers, and the relationship is not equal across geographic space, respectively. Moran´s I tests were used to test for residual clustering; clustered residuals indicate some variables or terms were missing from the model (Li et al., 2007). To explore where spatial mismatching occurred and where selected models did not perform adequately (i.e., indicating at least one important variable was missing from the model), we performed a hot–spots analyses using the residuals of the selected models based on the Getis–Ord Gi* statistic, estimating z–scores and p–values for each cell (Getis & Ord, 1992; Ord & Getis, 1995). Hot spots are those where z–cores are significant (p > 0.05), therefore indicating where high clustering occurs. P–values are considered significant when z–scores estimated with the cell and its neighbors differ from expected when compared proportionally to the sum of all features. Significant z–scores in a cell (p > 0.05) indicates clustered residual patterns and suggests one or more explanatory variables are missing in the model for that cell, in turn indicating spatial mismatch of the measures, overall model and the explanatory variables (Getis & Ord, 1992; Ord & Getis, 1995). We mapped cells with high levels of residual clustering that were significant (p > 0.05), therefore the spots of significant spatial mismatch of the terms of the model. All geographic and statistical analyses were performed using ArcGIS 10.2 (Environmental Systems Research Institute, 2013) and Spatrial Analyst extensions, and R software (R Team Development Core, 2008) and VIF package. Results We found a heterogeneous distribution of the three diversity measures of mammals in Colombia. We observed that species richness was concentrated near the center of the country, specifically towards the Andes piedmont, while the lowest values were concentrated in the Northern Llanos region (Eastern Colombia) and the northernmost portion of the country (i.e., Guajira Peninsula; fig. 1A). Phylogenetic and functional diversity were similarly distributed with greater values towards the southern Andes (FD)

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Fig. 1. Distribution of mammal species richness (A), phylogenetic diversity (B) and functional diversity (C) in Colombia: 1. Caribbean; 2. Pacific; 3. Andes; 4. Llanos (Orinoquia); 5. Amazon. Fig. 1. Distribución de la riqueza de especies (A), diversidad filogenética (B) y funcional (C) de mamíferos en Colombia: 1. Caribe; 2. Pacífico; 3. Andes; 4. Llanos (Orinoquía); 5. Amazonía.

and the Eastern and Western Andes cordilleras in the north (FD); lowest values were found for Eastern Colombia (i.e., Llanos) and an apparent homogenous distribution of both PD and FD was also found for Eastern Colombia, with homogeneous PD for the Llanos and homogenenous FD for the Amazon regions (fig. 1B, 1C). The three measures were highly related; species richness and phylogenetic diversity were highly correlated (Pearson = 0.96, p < 0.001), as were phylogenetic and functional diversity (Pearson = 0.95, p < 0.001), and species richness and functional diversity (Pearson = 0.90, p < 0.001). For species richness, the best model (table 1) included elevation and precipitation as the most important influencing variables. Nevertheless, Moran´s I test was positive for clustering of the residuals (Moran´s Index = 0.37, p < 0.001) and the overall proportion of variation in the dependent variable explained was low (R2 = 0.45). As the K(BP) indicated non–stationarity of the model (K[BP] = 2.36, p = 0.0381), we used robust probabilities (table 1). For phylogenetic diversity, the best model included species richness and slope,

with a high proportion of the variability explained (adjR2 = 0.94). Moran´s I (Moran´s Index = 0.005, p = 0.15) and K(BP) tests were not significant, indicating the change in relationship between the dependent variable and the determinants would not change when the magnitude of determinants change and that this relationship was constant across geographic space (table 1). Stationarity and heteroscedasticity were also found for the selected model. For functional diversity, the best model included phylogenetic diversity and slope, with a high proportion of variability explained by the model (adjR2 = 0.94), and indicated non–clustering of the residuals (Moran´s Index = –0.032, p = 0.09; table 1). The variable slope in both cases had less influence on phylogenetic and functional diversity than did species richness and phylogenetic diversity (i.e., species richness explained 61.56% of PD and PD explained 62.66% of functional diversity). Spatial mismatch for the three models identified areas where the models failed to explain the different diversity measures. For species richness, model mismatches occurred in the southern Andean region

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Table 1. Best performing candidate models (M; s. Selected model) testing the influence for environmental drivers on mammal species richness, phylogenetic diversity and functional diversity in Colombia: R(SE). Robust standard error; R(P). Robust p–value; VIF. Variance Inflation Factor; AICc. Corrected Akaike Information Criterion; K(BP). Koenker's studentized Breusch–Pagan Statistic and p–value. Tabla 1. Posibles modelos (M, s. Model seleccionado) más eficaces para comprobar la influencia de los factores ambientales en la riqueza de especies, la diversidad filogenética y la diversidad funcional de mamíferos en Colombia: R(SE). Error estándar robusto; R(P). Valor de p robusto; VIF. Factor de inflación de la varianza; AICc. Criterio de información de Akaike corregido; K(BP). Estadístico de Breusch–Pagan estudentizado por Koenker y valor de p. Variable M Variable Species richness M–1 Intercept Elevation Slope Precipitation M–2s Intercept Elevation Slope Temperature Precipitation M–3 Intercept Elevation Precipitation Phylogenetic diversity M–1 Intercept Richness Elevation Slope Temperature Precipitation M–2s Intercept Richness Slope Functional diversity M–1 Intercept PD Richness Elevation Slope Temperature M–2 Intercept PD Richness Elevation Slope Precipitation M–3s Intercept PD Slope

Coef.

R(SE)

R(P)

51.38 0.02 –0.02 0.00 60.10 0.02 –0.02 –0.36 0.00 50.82 0.02 0.002

3.19 0.00 0.01 0.00 11.09 0.00 0.01 0.42 0.00 3.19 0.00 0.001

0.00 0.45 972.8 0.00 7.09 0.17 7.17 0.03 1.10 0.00 0.45 973.28 0.00 7.80 0.16 7.23 0.40 1.98 0.02 1.19 0.00 0.44 973.4 0.00 1.08 0.02 1.07

1,159.58 20.92 –0.04 0.33 –4.05 0.02 1,099.12 21.27 0.23

74.42 0.75 0.04 0.09 2.25 0.01 42.69 0.71 0.05

0.00 0.95 1494.0 0.00 1.99 0.26 9.40 0.00 7.65 0.07 2.03 0.00 1.28 0.00 0.94 1495.4 0.00 1.47 0.00 1.47

0.09544 0.00019 0.00018 –0.00003 0.00012 –0.00007 0.09259 0.00020 0.00017 –0.00003 0.00012 0.00000 0.11085 0.00019 0.00004

0.03618 0.00002 0.00046 0.00001 0.00003 0.00029 0.03556 0.00003 0.00049 0.00001 0.00003 0.00000 0.02776 0.00001 0.00001

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2.36 p = 0.0381

6.54 p = 0.307

0.00943 0.91 –594.6 0.00000 18.44 0.69110 16.74 0.00125 9.50 0.00001 8.10 0.80018 1.89 0.01036 0.91 –594.6 0.00000 19.92 0.73322 17.30 0.00133 8.99 0.00001 8.29 0.91176 1.28 0.00012 0.91 –587.3 3.48 p = 0.175 0.00000 1.69 0.00139 1.69

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and Guajira peninsula in the northernmost part of the country, covering ~12% of the country (fig. 2A). A clear mismatch between environmental determinants and phylogenetic diversity occurred along the southern Pacific coast and to a lesser extent in a portion of the Amazon basin (~14%; fig. 2B). Greatest clustering and mismatch for functional diversity occurred in the Sierra Nevada de Santa Marta, Paramillo Complex and Guajira peninsula of the Caribbean region (~14%; fig. 2C). Discussion We provide the first quantification of phylogenetic and functional diversity of terrestrial mammals in Colombia. Our results show a high degree of relatedness between biodiversity measures, including high similarity in spatial patterns, similar to large scale analyses in other latitudes (Pavoine & Bonsall, 2011; Barnagaud et al., 2014; González–Maya et al., 2016). The evaluation of these complementary measures demonstrates how different attributes of biodiversity can be used simultaneously to better understand the assembly of species communities (Pavoine & Bonsall, 2011). Furthermore, previous works have identified how both phylogenetic and

functional characteristics can explain species co–occurrence at regional and global scales (Barnagaud et al., 2014). Our results highlight that even when the taxonomic, phylogenetic and functional diversity significantly overlap, some areas will differ between the three measures (i.e., spatial mismatch), suggesting other factors affect assemblage composition and species co–occurrence. The three diversity measures were strongly correlated, supporting how taxonomic richness drives phylogenetic diversity (Safi et al., 2011; Dalerum, 2013), which in turn is a key driver of functional diversity (Safi et al., 2011). Assemblages with larger or shorter evolutionary histories can markedly affect functional diversity and stability of those assemblages (Safi et al., 2011). However, for global analyses of these measures on mammals (Safi et al., 2011), spatial mismatches occur at different scales and geographic localities where additional factors or distinctive evolutionary histories have an unidentified effect on both measures (Devictor et al., 2010; Zupan et al., 2014). This is clear for areas previously found to have high endemisms and singularity like Sierra Nevada de Santa Marta and Southern Andes (Le Saout et al., 2013; Solari et al., 2013). Our results further indicate that selecting the areas with species–rich

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assemblages for conservation priorities will typically directly affect other biodiversity measures (Dalerum, 2013), and that areas identified as mismatches require further assessment and stronger consideration for conservation. Environmental determinants, or environmental filtering, determines a substantial proportion of the basic diversity measure, namely species richness (Messier et al., 2010; Pavoine & Bonsall, 2011), while the effect of these variables on other measures was less influential in our study than expected (González–Maya et al., 2016). Previous studies of trait– and phylogenetic–based diversity measures have proposed environmental filtering as the most likely driver of these measures (Messier et al., 2010; Pavoine & Bonsall, 2011; Safi et al., 2011; Swenson et al., 2012). However, in our study these drivers were not sufficient to fully explain variation in species richness. Safi et al. (2011) evaluated these three measures of diversity at a global scale and found they have a significant degree of surrogacy. Nevertheless, there appears to be considerable spatial mismatch across geographic scales, suggesting greater support for local and environmental factors influencing species assembly at taxonomic, functional and evolutionary levels. Local drivers, such as assemblage time, environmental constraints and biogeographic scale, have been proposed to explain phylogenetic and functional diversity patterns (Kraft & Ackerly, 2010; Spasojevic et al., 2014), which in our study seems to be a key aspect. Environmental constraints significantly affect species richness, slope, as a locally–defined variable affects functional and phylogenetic diversity, and assemblage evolutionary distinctiveness affects functional diversity. Our identification of slope as an important determinant of phylogenetic and functional diversity has been previously identified for substantially different systems and taxonomic groups (Cardoso et al., 2011; Punchi–Manage et al., 2013). In this study, as a locally–constrained variable, it is likely representative of locally–defined conditions of species assemblage. Our results can certainly be refined since both phylogenetic and functional diversity measures are highly influenced by the phylogeny and traits used, respectively, and the method used to estimate both measures (Dalerum, 2013). Our selection of both measures was based on using similar dendrogram– based measures, so the comparison and simultaneous evaluation of both measures was congruent (Faith, 1992; Petchey & Gaston, 2002b; Dalerum, 2013). As previously stated for concepts such as redundancy (Naheem, 1998; Bueno et al., 2013; Mouillot et al., 2013), as more information becomes available and we further understand evolutionary and ecological aspects of a group, analyses on diversity measures can be further refined. Nevertheless, as the first effort to map phylogenetic and functional diversity for Colombia, our results could be incorporated into conservation schemes and facilitate further exploration of these topics not only in Colombia but also in other Neotropical countries. Furthermore, we acknowledge that one degree cell size in a topographically complicated region such as the Andes surely average environmental diversity data, blurring the fine–grained

ecological mechanisms that might be responsible for the observed patterns. Thus, new studies along elevational or aridity gradients are needed in this area, probably one of the world’s richest in mammal species. Including complementary diversity measures helps us to further understand species assemblages by incorporating not only species richness but also species evolutionary history, function and patterns (Cadotte et al., 2011; Belmaker & Jetz, 2013; Monnet et al., 2014). Furthermore, it allows to explore mechanisms linking species to environment, ecosystem processes and vulnerability (Petchey & Gaston, 2002a, 2002b; Biswas & Mallik, 2010; Kraft & Ackerly, 2010; González–Maya et al., 2016), thus providing valuable information for more effective conservation planning (Barnagaud et al., 2014). Our results help to understand diversity patterns in Colombia, and our preliminary mapping could help define priorities for complementarity and singularity (Devictor et al., 2010; Zupan et al., 2014). Despite the potential surrogacy of diversity measures, identifying areas with high values of any of these would likely result in more comprehensive and integral conservation planning, integrating singularities at taxonomic, evolutionary and ecosystem function levels (González–Maya et al., 2016). The variation in three important biodiversity measures, and the fact that one measure cannot represent the entire reality of species assemblages, suggests species assemblages are best represented using multiple metrics. This approach could increase the likelihood that areas for conservation are adequately identified and provide a basis for integral conservation planning. Acknowledgements This paper constituted a partial fulfillment of the Graduate Doctoral Degree Program in Biomedical Sciences (Programa de Doctorado en Ciencias Biomédicas) of the National Autonomous University of México (UNAM) of the first author. J. F. González–Maya acknowledges the scholarship and financial support provided by the National Council of Science and Technology (CONACyT), and UNAM (scholarship 255983). The authors would like to thank R. Medellin, E. Martínez–Meyer, J. Belant, J. Schipper and L. Víquez–R. for constant support through the development of this project. Partial support was provided by ProCAT Colombia/ Internacional. References Barnagaud, J. Y., Daniel Kissling, W., Sandel, B., Eiserhardt, W. L., Sekercioglu, C. H., Enquist, B. J., Tsirogiannis, C. & Svenning, J. C., 2014. Ecological traits influence the phylogenetic structure of bird species co–occurrences worldwide. Ecology Letters, 17: 811–820. Barnosky, A. D., Matzke, N., Tomiya, S., Wogan, G. O. U., Swartz, B., Quental, T. B., Marshall, C., McGuire, J. L., Lindsey, E. L., Maguire, K. C., Mersey, B. & Ferrer, E. A., 2011. Has the Earth’s sixth mass

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Breeding ecology of the southern shrike, Lanius meridionalis, in an agrosystem of south–eastern Spain: the surprisingly excellent breeding success in a declining population G. Moreno–Rueda, I. Abril–Colón, A. López–Orta, I. Álvarez–Benito, C. Castillo–Gómez, M. Comas & J. M. Rivas Moreno–Rueda, G., Abril–Colón, I., López–Orta, A., Álvarez–Benito, I., Castillo–Gómez, C., Comas, M. & Rivas, J. M., 2016. Breeding ecology of the southern shrike, Lanius meridionalis, in an agrosystem of south– eastern Spain: the surprisingly excellent breeding success in a declining population. Animal Biodiversity and Conservation, 39.1: 89–98. Abstract Breeding ecology of the southern shrike, Lanius meridionalis, in an agrosystem of south–eastern Spain: the surprisingly excellent breeding success in a declining population.— The southern shrike, Lanius meridionalis, is declining at the Spanish and European level. One cause of this decline could be low reproductive success due to low availability of prey in agricultural environments. To investigate this possibility we analysed the breeding ecology of a population of southern shrike in an agrosystem in Lomas de Padul (SE Spain). Our results suggest the population is declining in this area. However, contrary to expectations, the population showed the highest reproductive success (% nests in which at least one egg produces a fledgling) reported for this species to date (83.3%), with a productivity of 4.04 fledglings per nest. Reproductive success varied throughout the years, ranging from 75% in the worst year to 92.9% in the best year. Similarly, productivity ranged from 3.25 to 5.0 fledglings per nest depending on the year. Other aspects of reproductive biology, such as clutch size, brood size, and nestling diet, were similar to those reported in other studies. Based on these results, we hypothesise that the determinant of population decline acts on the juvenile fraction, drastically reducing the recruitment rate, or affecting the dispersion of adults and recruits. Nevertheless, the exact factor or factors are unknown. This study shows that a high reproductive success does not guarantee good health status of the population. Key words: Agrosystems, Breeding success, Reproductive ecology, Southern shrike, Clutch size, Nestling diet Resumen Ecología reproductora del alcaudón meridional, Lanius meridionalis, en un agrosistema del sudeste de España: el desconcertante excelente éxito reproductivo en una población en decrecimiento.— La población de alcaudón meridional, Lanius meridionalis, está disminuyendo a escalas europea y española. Una posible causa de este decrecimiento podría ser la disminución del éxito reproductor debido a la escasa disponibilidad de presas en medios agrarios. En este estudio se analiza la ecología reproductora de una población de alcaudón meridional en un agrosistema situado en las Lomas de Padul (SE de España). Los resultados sugieren que la población de Padul se encuentra en decrecimiento; no obstante, en contra de lo esperado, la población mostró el mayor éxito reproductivo (% de nidos en los que al menos un huevo termina convirtiéndose en volantón) encontrado en esta especie (83,3%), con una productividad de 4,04 volantones por nido. El éxito reproductor osciló notablemente entre años, entre el 75% en el peor año y el 92,9% en el mejor año. De igual forma, la productividad osciló entre 3,25 y 5,00 volantones por nido según el año. Otros aspectos de la biología reproductiva de la población, como el tamaño de puesta o de nidada o la alimentación de los pollos, fueron similares a lo observado en otros estudios. Sobre la base de estos resultados, se sugiere que el factor determinante del decrecimiento de la población está actuando sobre la fracción juvenil, lo que reduce de forma drástica la tasa de reclutamiento, o bien afecta a la dispersión de adultos y reclutas. No obstante, se desconocen cuáles son los factores exactos. En cualquier caso, este estudio demuestra que un elevado éxito reproductor no garantiza el buen estado de salud de la población. Palabras clave: Agrosistemas, Éxito reproductor, Ecología reproductora, Alcaudón meridional, Tamaño de puesta, Alimentación de los pollos ISSN: 1578–665 X eISSN: 2014–928 X

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Received: 2 XI 15; Conditional acceptance: 22 XII 15; Final acceptance: 21 I 16 Gregorio Moreno–Rueda, Inmaculada Abril–Colón, Antonio López–Orta, Inés Álvarez–Benito & Carlos Castillo–Gómez, Depto. de Zoología, Fac. de Ciencias, Univ. de Granada, E–18071 Granada, Spain.– Mar Comas, Estación Biológica de Doñana (EBD–CSIC), c/ Américo Vespucio s/n., E–41092 Sevilla, Spain.– José M. Rivas, Estación Ornitológica de Padul (EOP), carretera de Bailén km 143, E–18640 Padul, Granada, Spain. Corresponding author: Gregorio Moreno–Rueda. E–mail: gmr@ugr.es

Animal Biodiversity and Conservation 39.1 (2016)

Introduction

Material and methods

Humans are causing many changes in landscapes, with direct consequences for species conservation (McKinney & Lockwood, 1999). Shifts in land use are mainly due to agriculture intensification (Matson et al., 1997; see also Stoate et al., 2009), which diminishes bird biodiversity and abundance (Siriwardena et al., 1998) as a consequence of habitat alteration, fragmentation or simplification, and pesticide use. In Spain, for example, approximately 50% of the surface area is occupied by farmland (Moreno–Rueda & Pizarro, 2009), illustrating the vast scale of the impact of agriculture on nature and the importance of its study for conservation. The southern shrike, Lanius meridionalis, like other shrikes, is a predatory passerine species that lives and nests in open habitats with shrubs or trees (Hernández, 1994), allowing it to inhabit mixed agricultural/natural landscapes. Nevertheless, Laniidae populations in general show a worldwide decline (Yosef, 2008). In Spain, for example, the southern shrike population is shrinking notably (Hernández & Infante, 2004; SEO/BirdLife, 2015), a decrease attributed mainly to agriculture–related changes in land use and pesticide applications (Hernández & Infante, 2004). Other shrike species (e.g., the great grey shrike, Lanis excubitor), however, are declining even in zones where they do not inhabit farmland (e.g., Kuczynski et al., 2010). The exact causes of the decline of the southern shrike are unknown. Campos et al. (2011) found that breeding success (% nests in which at least one egg produces a fledgling) for this species in Toro was low (37.9%), and suggested that this was the cause of their decline. Given that shrike nestlings are fed mainly arthropods (Hernández, 1993b; Campos et al., 2010), nestling survival may be reduced in agrosystems as a consequence of pesticides. Moreover, cereal farmlands (frequently used for foraging in the Toro population) constitute a habitat where shrike foraging is constrained, and this may in turn depress the breeding success (Campos et al., 2006). Most studies on the breeding biology of the southern shrike in Spain have been conducted in Extremadura (de la Cruz & de Lope, 1985), León (Hernández, 1993a), Zamora (Campos et al., 2011), and Navarra (Campos et al., 2006, 2007). Information concerning the biology of the southern shrike in the southern Iberian peninsula is lacking. In effect, in their review of the population trends of the species in Spain, Hernández & Infante (2004) did not refer to Andalusia because of the lack of data. We here provide information concerning the population trend of the southern shrike in an agrosystem located in Lomas de Padul (Granada, SE Spain), and present basic data concerning the reproductive biology of this population, including information on nestling diet. The main goal of our study was to examine whether the decline of this population is related to low breeding success.

The study was conducted from 2009 to 2011 and in 2014 in a population of southern shrikes in Lomas de Padul (SE Spain: 37º 01' 13'' N, 03º 41' 30'' W; fig. 1). The study area consists of a typical Mediterranean agrosystem, with a mix of almond and cereal farming interspersed with natural steppe meadows, plus isolated holm oaks, Quercus ilex, and scattered kermes oaks, Q. coccifera, where shrikes mainly nest. To locate nests, we exhaustively searched inside the oaks starting in mid–March. The sampling effort progressively increased over the years. The exact position of each nest found was recorded using a GPS device. For each nest located, we checked the presence and number of eggs. If nests were found during laying, considering that shrikes lay one egg per day (Yosef, 1992), we used the number of eggs to estimate the day that the first egg was laid (laying date). On subsequent visits, one week later, we recorded clutch size (number of eggs laid). At that time, we estimated the day of hatching of the first egg (hatching date) according to the normal time of incubation (15 days; Harrison, 1991), given that southern shrikes start incubation with the last egg (Hernández, 1993a). Meanwhile, we did not visit the nest to avoid any disturbance that could affect breeding (Antczak et al., 2005; see also Tryjanowski & Kuźniak, 1999). Around the estimated hatching date, we visited the nest to determine the correct hatching date. We estimated the incubation period as the number of days between the laying of the last egg and the hatching of the first egg. We recorded the brood size (number of nestlings per nest) at hatching, and estimated the hatching success (number of nests in which at least one egg hatched) and the average percentage of eggs hatched per nest with hatching success. The cause of hatching failure was recorded considering three options: (1) embryo mortality or unfertilized egg (the egg simply did not hatch), (2) predation (normally the complete clutch disappeared), or (3) abandonment (the clutch was found cold). Some nestlings were used in begging experiments in 2010 and 2011 (Moreno–Rueda & Redondo, 2011, 2012). These nestlings were removed from the nest in the afternoon when they were 6 days old (hatching day = 0), and returned to the nest during the morning when 8 days old. Nestlings used in experiments and their siblings left in the nest during the experiments did not differ in behaviour, survival, or body size from those in unused nests. When nestlings were 12–days old, we recorded the number of surviving fledglings per nest. With these data, we further determined the productivity of the population, such as the number of fledglings produced per nest (for which we considered both successful and unsuccessful nests). We also estimated fledging success (percentage of nests in which at least one hatchling fledged), breeding success (percentage of nests in which at the least one egg produced a fledgling), and the average percentage of nestlings and eggs fledged per nest. The cause of fledging failure was recorded. The potential causes were:

Moreno–Rueda et al.

abandonment (nestlings in good condition found dead or cold), predation (nestlings in prime body condition that disappeared), and starvation (nestlings found in poor condition before death). Moreover, to ascertain parental feeding behaviour (feeding rate and food delivered to nestlings), we made a one–hour recording (following Pagani–Núñez & Senar, 2013) of 12 nests in 2009 when nestlings were 10–days old, with a Sony® Handycam HDR–XR155B. Parent birds quickly accepted the videocamera and usually resumed feeding in less than 5 min (sometimes as soon as one minute after the researchers had left the proximity of the nest). None of the nests were abandoned because of the camera. We later analysed filming, identifying the prey delivered to the nestlings, to the taxonomic level of order as a minimum. In addition to describing the reproductive parameters of southern shrike in our study population, we compared whether breeding parameters varied from year to year. To do so, we used the Kruskal–Wallis ANOVA test to examine differences in the mean of variables such as clutch size, brood size, and productivity. We used non–parametric statistics given that most of these variables did not fulfil the assumptions of normality and homoscedasticity (Quinn & Keough, 2002), and non–parametric statistic estimations are less affected by the violation of these assumptions (Siegel & Castellan, 1988). To compare frequencies (for variables based upon percentages), we used the Chi–square test. The means are given with their corresponding standard error. Moreover, for a better comprehension of inter–annual variation in breeding parameters, we compiled meteorological data (mean temperature and total precipitation) during the breeding season (March, April, and May) for the complete study, from the weather station of Padul. Results Population trend in Lomas de Padul Over the study years, we gradually found fewer southern shrike nests in the study area. The number of nests decreased from 17 nests in 2009 to 11 in 2014 (table 1) even though the study area was gradually expanded over the years (fig. 1). The average distance between nests over the 4 years of the study was 1.67 ± 0.013 km (n = 54 nests). Breeding phenology The average laying date was 5 IV (± 8.98 days, n = 54 nests); nesting began between 23 III and 29 IV. We found no significant differences in average laying date across years (table 1). The incubation period averaged 14.94 ± 1.01 days (median = 15 days; n = 51 nests, in which hatching occurred), ranging from 13 to 18 days. The average hatching date was 26 IV (± 11.55 days; n = 51), ranging between 12 IV and 16 V. We found no significant differences in average hatching date over the years (table 1).

Reproductive parameters The average clutch size was 5.64 ± 0.09 eggs (range 4–7, but with 90.2% of nests containing 5–6 eggs; n = 53 nests; one nest from 2009 was depredated during laying and was not considered). No significant differences were found in clutch size over the years (table 1), but the variance differed depending on the year (Levene’s test, F3, 49 = 5.81, P = 0.001). Coefficients of variation were higher in 2009 (16.3) and 2011 (12.3) than in 2010 (7.4) or 2014 (7.0). Average hatching success was 94.4% (n = 54), a percentage that did not differ significantly between years (table 1). The percentage of nests in which all eggs hatched was 64.1% (33 out of 54). The average percentage of hatched eggs per successful nest was 91.2 ± 2.0% (n = 51). No significant differences were found in average percentage of hatching with years (table 1). Hatching failure reached 11.0% of the eggs (n = 304), 3.5% due to abandonment, and 7.5% due to embryo mortality or to the egg not being fertilized. Only one nest was depredated before hatching (during laying). Two nests were abandoned during incubation. The average brood size was 4.87 ± 0.21 chicks (n = 51 nests). Neither average brood size nor variance in brood size fluctuated between years (table 1). Of the total of 263 chicks, 47 (17.9%) did not survive to fledging. Five nests were depredated during the nestling period (9.6% of nests). Only in one nest did the whole brood die as a consequence of starvation (in 2010). Feeding rate and nestling diet We recorded the ingestion of 85 prey by nestlings (table 2); 87% were arthropods, mainly Coleoptera (22%) and insect larvae (14%). Furthermore, we recorded the intake of small vertebrates (12%). The average feeding rate was 11.08 ± 0.59 feeds/hours (n = 12 nests). The feeding rate was not correlated with clutch size (r = 0.06, P = 0.88; n = 12 nests), brood size (r = 0.10, P = 0.75), or number of fledglings produced (r = 0.32, P = 0.30). Productivity Fledging success occurred in 88.2% of nests with hatchlings (n = 51). In successful nests with at least one fledgling, 92.7% of nestlings fledged (n = 45 nests), with no significant differences between years (table 1), suggesting a low rate of brood reduction. Thus, the total breeding success was 83.3% of nests (n = 54 nests). In fact, in 21 of 54 nests, all eggs produced a fledgling. The percentage of eggs that produced fledglings tended to vary, almost significantly, between years (table 1). Shrikes lost fewer eggs in 2010 and 2014 (80–85% of the eggs produced fledglings) than in 2009 and 2011 (about 60% of eggs fledged; table 1). Finally, the average productivity was 4.04 fledglings per nest (n = 54 nests). Productivity differed significantly between years (table 1), the highest being recorded in 2010 and 2014. Productivity in 2009 was significantly lower than in 2010 and 2014 (Kruskal–Wallis; H > 3.95; P < 0.05

Animal Biodiversity and Conservation 39.1 (2016)

Spain Padul

1 km

Fig. 1. Map showing the location of Lomas de Padul (SE Spain), and the situation of each nest in the study area: u Nests in 2009; n Nests in 2010; p Nests in 2011; l Nests in 2014. Given that shrikes reused some nests (or nested in the same tree) between years, some symbols are superimposed. (Lines indicate level curves, 1,000-1,100 m a.s.l.). Fig. 1. Mapa de la localización de las Lomas de Padul (SE de España) y la situación de cada nido en la zona de estudio: u Nidos de 2009; n Nidos de 2010; p Nidos de 2011; l Nidos de 2014. Dado que los alcaudones reutilizaron algunos nidos (o nidificaron en el mismo árbol) en diferentes años, algunos símbolos están superpuestos. (Las líneas indican las curvas de nivel, 1.000-1.100 m s.n.m.).

in both cases). In 2011 it was lower than in 2010 (H = 5.43; P = 0.02) and showed a trend to be lower than in 2014 (H = 2.77; P = 0.096). Meanwhile, there were no significant differences in productivity between 2009 and 2011 (H = 0.02; P = 0.89) or between 2010 and 2014 (H = 0.34; P = 0.56). Moreover, variance in productivity also varied statistically between years (Levene’s test: F3, 50 = 2.95, P = 0.04). Coefficients of variation in fledglings per nest were higher —about double— in 2009 and 2011 (64.2 and 70.8, respectively) than in 2010 and 2014 (31.4 and 38.9, respectively). Productivity showed no detectable relationship with meteorological variables (summarized in fig. 2). Discussion Findings in the present study suggest that the southern shrike population of Lomas de Padul is declining. This trend is in accordance with the situation of the southern shrike in the rest of Spain (Hernández & Infante, 2004) and in Europe (Tucker & Heath, 1994). The results also show that this decline in Lomas de Padul is not due to reproductive failure, as breeding success and productivity were notably

high in the population studied. On average, 83% of the nests fledged at least one nestling, and 71% of eggs successfully developed to produce a fledgling. These values of breeding success are higher than those reported for several other populations: 63% in Extremadura (Spain, de la Cruz & de Lope, 1985), 67–71% in León (NW Spain, Hernández, 1993a), 64% en Olite (N Spain, Campos et al., 2006), 38% en Toro (approx. Central Spain, Campos et al., 2011); 63% in Sede Boqer (Israel, Yosef, 1992), and 68% en Hazeva (Israel, Budden & Wright, 2000). It is of note that breeding success was similar in the aforementioned populations (about 63–71%), with the exception of that in Toro (38%, the lowest) and that in Lomas de Padul (83%, the highest). On the other hand, Budden & Wright (2000) reported that only 31% of nestlings fledged, while Hernández (1993a) reported that 62–64% of nestlings fledged. In Padul, however, almost 93% of nestlings fledged, the highest fledging success reported for this species to date. Regarding productivity, this was higher in Padul (four fledglings per nest) than in Israel (1.1; Budden & Wright, 2000) or in southern France (1.54; Lepley et al., 2000), but similar to that reported for NW Spain (3.6; Hernández, 1993a).

Moreno–Rueda et al.

Table 1. Values (± SE) of reproductive parameters measured or estimated in the population of southern shrike of Lomas de Padul (SE Spain), separated by year, and overall. For dates, SE indicates days. The statistical (H. Kruskal–Wallis ANOVA, x2. Chi–square) comparison between years is also included: * P < 0.05; § P = 0.06; ns. Not significant P > 0.10). The definition of each parameter measured is also included. For some estimates (laying date, hatching success, breeding success) we used all nests found (n = 17, 14, 12 and 11 according to year). Other estimations require data on clutch size (average clutch size and % eggs fledged), and therefore one nest in 2009 could not be used (n = 16 for 2009). Other estimations were based on number of hatchlings (hatching date, % eggs hatched, brood size or fledging success). Thus, sample sizes per year were: 15, 14, 12 and 10. Lastly, in the case of % of nestlings fledged, we considered only nests that produced at least one fledgling (n = 13, 13, 9 and 10). Tabla 1. Valores (± EE) de los parámetros reproductivos medidos o estimados en la población de alcaudón meridional de Lomas de Padul (SE de España), separados por cada año y en total. Para las fechas, el error estándar se expresa en días. También se indica la comparativa estadística (H. Kruskal–Wallis ANOVA, x2. Chi–cuadrado) entre años: * P < 0,05; § P = 0,06; ns. No significativa P > 0,10. Asimismo se incluye la definición de cada parámetro medido. Para algunas estimaciones (fecha de puesta, éxito de eclosión y éxito reproductor) se usaron todos los nidos encontrados (n = 17, 14, 12 y 11 según el año). Para otras, era necesario conocer el tamaño de puesta (tamaño de puesta medio y % de huevos que se convierten en volantones), por lo que uno de los nidos de 2009 no pudo usarse (n = 16 en 2009). Para otras estimaciones se partía del número de pollos eclosionados en el nido (fecha de eclosión, % de huevos eclosionados, tamaño de nidada o éxito de vuelo). Los tamaños de muestra de los distintos años fueron: 15, 14, 12 y 10. Por último, en el caso del % de pollos que vuelan, se consideraron solo los nidos que habían producido al menos un volantón (n = 13, 13, 9 y 10).

Parameter (definition)

2009

2010

2011

2014

Test

All years

Nests (number of nests found )

54 (total)

Laying date (average date of the first egg laid)

08/04 ± 10.0

03/04 ± 8.4

05/04 ± 6.4

03/04 ± 10.4

H = 2.29 ns

05/04 ± 9.0

27/04 ± 17.0

H = 1.26 ns

26/04 ± 11.6

5.82 ± 0.20

H = 2.24 ns

5.64 ± 0.09

Hatching date (average date of the first egg hatched)

28/04 ± 9.5

26/04 ± 13.8

25/04 ± 5.4

Clutch size (average number of eggs laid)

5.50 ± 0.16

5.79 ± 0.17

5.50 ± 0.19

Hatching success (% nests in which at least one egg hatched)

88.2

100

90.9

x23 = 2.25 ns

94.4

% Eggs hatched (average % of eggs hatched per successful nest)

90.9 ± 3.7

93.6 ± 3.9

90.0 ± 4.2

90.0 ± 4.6

H = 3.13 ns

91.2 ± 2.0

4.73 ± 0.47

H = 3.09 ns

4.87 ± 0.21

x23 = 3.83 ns

88.2

Brood size (average number of hatchlings per nest)

4.47 ± 0.37

5.43 ± 0.42

4.92 ± 0.45

Fledging success (% nests in which at least one chick fledges)

86.7

92.9

100

% Nestlings fledged (average % of chicks fledged per successful nest)

85.7 ± 4.2

96.2 ± 4.2

92.6 ± 5.0

97.5 ± 4.8

H = 4.73 ns

92.7 ± 2.3

Breeding success (% nests in which at least one egg produced a fledgling)

76.5

92.9

90.9

x23 = 3.18 ns

83.3

% Eggs fledged (average % of eggs become in fledglings)

59.5 ± 8.5

85.7 ± 9.4

60.8 ± 10.2

80.3 ± 10.6

H = 7.36§

70.8 ± 4.9

4.64 ± 0.59

H = 10.74*

4.0 ± 0.28

Productivity (average fledglings produced per nest)

3.29 ± 0.48

5.00 ± 0.53

3.25 ± 0.57

Animal Biodiversity and Conservation 39.1 (2016)

Therefore, the population decline in Lomas de Padul clearly cannot be ascribed to low reproductive success, given that it is probably one of the highest reported for this species. Other causes should be examined in the future. We can rule out habitat loss due to changes in land use as a possible cause of the decline because the only change of note in land use between 2009 and 2014 was the erection of wind turbines in a corner of the study area, and southern shrikes near the turbines did not abandon their territories as a result of this change. Therefore, given the high productivity of nestlings, the decline might be due to high mortality of fledglings or juveniles, depressing recruitment. Otherwise, even if adult mortality were high, recruitment should be sufficient to maintain the population size. The causes of such hypothetical juvenile mortality are unknown as it is difficult to ascertain what might provoke such a heavy loss of juveniles when nestling survival is so high. A high density of potential predators of juveniles or adults was not observed during the study (though not formally analysed), while potential nest predators were frequently detected (Montpellier snake Malpolon monspessulanus, dormouse Elyomis quercinus, red fox Vulpes vulpes, and magpie Pica pica). Nest predation, in effect, is one of the main causes of reproductive failure in southern shrike. In fact, Lepley et al. (2000) reported a nest–predation rate of 44%, while Hernández (1993a) reported a rate of 20%. In our population, 11% of the nests were depredated. In view of the information gathered, other unstudied possibility is that mortality is provoked by parasites or pathogens for which the transmission rate is higher in juveniles or adults than in nestlings (Valera et al., 2006; see also Casanueva et al., 2012). Another possibility is that fledglings produced in the Padul population are recruiting in other populations (Padul would be a source population). It is striking that shrikes (adults and yearlings) show very low philopatry (Giralt & Valera, 2007; Krištín et al., 2007; Tryjanowski et al., 2007). However, if the site is so good for reproduction, it is strange that territories are being lost and no new shrikes occupy them. Breeding success, nevertheless, varied between years (although not significantly), from 75% in 2009 and 2011 to more than 90% in 2010 and 2014. Overall productivity was also higher in 2010 and 2014 than in 2009 and 2011. Therefore, it seems that 2009 and 2011 were bad years for shrike reproduction in Padul. Indeed, our findings in these poorer years were a slightly (non–significantly) smaller clutch size, lower fledging success, and a lower percentage of fledged nestlings. Moreover, clutch size, and also number of fledglings produced, showed higher variance in the bad years. Higher variance in reproduction in the bad years suggests that low–quality parents suffered more than did high–quality parents those years, this situation leading to increased variance. Campos et al. (2007) also found similar inter–annual variation in breeding success in a population in northern Spain. In their study, however, breeding success in the bad years was below 60% (while in Padul was around 75%), and in the good years it was 70–84%

Table 2. Number and percentage of each type of prey delivered to southern shrike nestlings in Lomas de Padul (SE Spain) (N = 12 nests, when nestlings were 10 days old): * Three Coleoptera found were identified as the red–striped oil beetle, Berberomeloe majalis. Tabla 2. Número y porcentaje de cada tipo de presa entregada por los padres a los pollos de alcaudón meridional en las Lomas de Padul (SE de España) (N = 12 nidos, cuando los pollos tenían 10 días): * Tres Coleoptera se identificaron como aceiteras, Berberomeloe majalis. Prey type

Number

Percentage

Coleoptera

19*

22.35

Insect larvae

14.12

Lepidoptera

9.41

Miriapoda

5.88

Orthoptera

5.89

Unidentified insects

29.41

Total arthropods

87.05

Lizard tail

1.18

Vertebrates (rodents)

11.77

Total Individuals

(in Padul, more than 90%). That is to say, shrike breeding success during the bad years in southern Spain was similar to that recorded during the good years in northern Spain. However, the causes of such inter–annual variation are unknown, and neither Campos et al. (2007) nor ourselves found a relationship between breeding success and weather conditions. This should be taken with caution, however, given the low sample size (four years), and the fact that meteorological conditions might act in a subtle way that is difficult to detect. Indeed, other studies did find an effect of weather on shrike reproduction. For example, Keynan & Yosef (2010) reported an effect of weather on reproduction in Israel, and Moreno–Rueda et al. (2014) reported a possible relationship between weather and reproductive parameters such as clutch size and brood sex ratio in N Spain. Other reproductive parameters, such as clutch and brood size, were similar in Lomas de Padul to those reported in other populations (Yosef, 1992; Hernández, 1993a; Campos et al., 2007). Clutch size, for example, seems highly conservative, being around 5.7 in all populations (Yosef, 1992; Hernández, 1993a; Campos et al., 2007; this study), although Budden & Wright (2000) reported a clutch size of only 3.9 in Israel.

Moreno–Rueda et al.

Precipitation

180

14.6

Precipitation (mm) Mean temperature (ºC)

14.4

160

14.2

140

120

13.8

100

13.6

13.4

13.2

12.8

2009

2010

2011

2014

Average temperature

200

12.6

Fig. 2. Total precipitation and average temperature in Lomas de Padul (SE Spain) during the breeding period of the southern shrike, for each year of study. Fig. 2. Precipitación total y temperatura media en las Lomas de Padul (SE de España) durante el periodo de cría del alcaudón meridional, para cada año de estudio.

Regarding nestling diet, arthropods were the main food (87%), especially Coleoptera (22%), which matches most previous studies on southern shrike nestling diet, indicating that the diet consists primarily of arthropods (Hernández, 1993b; Budden & Wright, 2000; Padilla et al., 2009; Campos et al., 2010). Nevertheless, Orthoptera were the main prey consumed by nestlings in Valladolid (Central Spain, Campos et al. 2010). In fact, Campos et al. (2010) reported that, in Valladolid, shrikes feed on Coleoptera less than expected by chance according to their availability; however, Coleoptera constitute the main prey of shrikes in the population studied here (Padul) and in León (near Valladolid; Hernández, 1993b). In general, the nestling diet matches well with the adult diet, i.e. mainly arthropods and occasionally small vertebrates (Hódar, 2006; see also Hernández et al., 1993; Lepley et al., 2004; Padilla et al., 2009). However, the portion of vertebrates in the diet should not be understated; although the frequency of items is low, they may represent a major portion of the biomass (which we failed to measure). For example, Hódar (2006) reported similar frequencies of vertebrates in the adult diet of a population near ours, and this represented more than 50% of the biomass. In conclusion, this study suggests that the population of southern shrike in Lomas de Padul (SE Spain) is declining despite one of the highest rates of breeding success reported for this species. This decline therefore indicates that some unknown factor hampers recruitment in the population. Finally, our results highlight the need to exercise caution in

ecological management, given that a high breeding success should not be immediately interpreted as a healthy population, and breeding success, without additional information, should not be used as a surrogate of the population trend. Acknowledgements Álvaro Rivas, David Ochoa and José Miguel Pascual collaborated during nest searching. The complete study was carried out with the permission of the Andalusian government. We are in debt to the shrikes for their infinite patience. David Nesbitt improved the English, and comments by Piotr Tryjanowski and two anonymous referees improved the manuscript. References Antczak, M., Hromada, M. & Tryjanowski, P., 2005. Research activity induces change in nest position of the Great Grey Shrike Lanius excubitor. Ornis Fennica, 39: 9–14. Budden, A. E. & Wright, J., 2000. Nestling diet, chick growth and breeding success in the Southern Grey Shrike (Lanius meridionalis). The Ring, 22: 165–172. Campos, F., Gutiérrez–Corchero, F. & Hernández, M. Á., 2006. Nidificación del alcaudón real Lanius meridionalis en agrosistemas del norte de España. Ecología, 20: 225–232.

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Kuczynski, L., Antczak, M., Czechowski, P., Grzybek, J., Jerzak, L., Zablocki, P. & Tryjanowski, P., 2010. A large scale survey of the great grey shrike Lanius excubitor in Poland: Breeding densities, habitat use and population trends. Annales Zoologici Fennici, 47: 67–78. Lepley, M., Guillaume, C. L. P., Newton, A. & Thévenot, M., 2000. Biologie de reproduction de la pie–grièche méridionale Lanius meridionalis en crau sèche (Bouches–du–Rhône–France). Alauda, 68: 35–43. Lepley, M., Thevenot, M., Guillaume C.–P., Ponel, P. & Bayle, P., 2004. Diet of the nominate Southern Grey Shrike Lanius meridionalis in the north of its range (Mediterranean France): capsule in this region the diet is mainly cold–blooded prey, mostly insects such as beetles. Bird Study, 51: 156–162. Matson, P. A., Parton, W. J., Power, A. G. & Swift, M. J., 1997. Agricultural intensification and ecosystem properties. Science, 277: 504–509. McKinney, M. L. & Lockwood, J. L., 1999. Biotic homogenization: a few winners replacing many losers in the next mass extinction. Trends in Ecology and Evolution, 14: 450–453. Moreno–Rueda, G., Campos, F., Gutiérrez–Corchero, F. & Hernández, M. Á., 2014. Costs of rearing and sex–ratio variation in southern grey shrike Lanius meridionalis broods. Journal of Avian Biology, 45: 424–430. Moreno–Rueda, G. & Pizarro, M., 2009. Relative influence of habitat heterogeneity, climate, human disturbance, and spatial structure on vertebrate species richness in Spain. Ecological Research, 24: 335–344. Moreno–Rueda, G. & Redondo T., 2011. Begging at high level simultaneously impairs growth and immune response in southern shrike (Lanius meridionalis) nestlings. Journal of Evolutionary Biology, 24: 1091–1098. – 2012. Benefits of extra begging fail to compensate for immunological costs in southern shrike (Lanius meridionalis) nestlings. PLoS ONE, 7: e44647. Padilla, D. P., González–Castro, A., Nieves, C. & Nogales, M., 2009. Trophic ecology of the Southern Grey Shrike (Lanius meridionalis) in insular environments: the influence of altitude and seasonality. Journal of Ornithology, 150: 557–568. Pagani–Núñez, E. & Senar, J. C., 2013. One hour of sampling is enough: Great Tit Parus major parents feed their nestlings consistently across time. Acta Ornithologica, 48: 194–200. Quinn, G. P. & Keough, M. J., 2002. Experimental design and data analysis for biologists. Cambridge University Press, Cambridge. SEO/BirdLife, 2015. Programas de seguimiento de SEO/BirdLife 2014. SEO/BirdLife, Madrid. Siegel, S. & Castellan Jr., N. J., 1988. Non–parametric Statistics for the Behavioral Sciences, 2nd ed. McGraw–Hill, Singapore. Siriwardena, G. M., Baillie, S. R., Buckland, S. T., Fewster, R. M., Marchant, J. H. & Wilson, J. D., 1998. Trends in the abundance of farmland birds: a quantitative comparison of smoothed Common

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Animal Biodiversity and Conservation 39.1 (2016)

Testing the efficacy of downscaling in species distribution modelling: a comparison between MaxEnt and favourability function models J. Olivero, A. G. Toxopeus, A. K. Skidmore & R. Real

Olivero, J., Toxopeus, A. G., Skidmore, A. K. & Real, R., 2016. Testing the efficacy of downscaling in species distribution modelling: a comparison between MaxEnt and favourability function models. Animal Biodiversity and Conservation, 39.1: 99–114. Abstract Testing the efficacy of downscaling in species distribution modelling: a comparison between MaxEnt and favourability function models.— Statistical downscaling is used to improve the knowledge of spatial distributions from broad–scale to fine–scale maps with higher potential for conservation planning. We assessed the effective� ness of downscaling in two commonly used species distribution models: Maximum Entropy (MaxEnt) and the favourability function (FF). We used atlas data (10 x 10 km) of the fire salamander, Salamandra salamandra, distribution in southern Spain to derive models at a 1 x 1 km resolution. Downscaled models were assessed using an independent dataset of the species' distribution at 1 x 1 km. The FF model showed better downscaling performance than MaxEnt, and the models that were based on linear combinations of environmental variables performed better than models allowing higher flexibility. The FF model minimized model overfitting compared to the MaxEnt. Key words: Atlas distribution data, Model transferability, Favourability function model, Maximum Entropy model, Overfitting, Salamandra salamandra Resumen Eficacia del aumento de resolución espacial en modelos de distribución de especies: comparación entre el modelo MaxEnt y el de la función de favorabilidad.— El aumento estadístico de la resolución espacial se utiliza para mejorar el conocimiento de las distribuciones espaciales, transformando mapas de resolución gruesa en mapas de resolución fina, que son más adecuados para planificar la conservación. Se ha evaluado la eficacia de este aumento de la resolución en dos modelos muy utilizados de distribución de especies: el de máxima entropía (MaxEnt) y la función de favorabilidad (FF). Se han obtenido modelos con resolución de 1 x 1 km a partir de datos de atlas (10 x 10 km) de la distribución de la salamandra común Salamandra salamandra en el sur de España. Para evaluar estos modelos con mayor resolución, se ha utilizado un conjunto de datos inde� pendientes sobre la distribución de la especie a 1 x 1 km. Se ha observado que el modelo de favorabilidad es más eficaz para aumentar la resolución espacial que el de MaxEnt y los modelos basados en combinaciones lineales de variables ambientales son más eficaces que los modelos que permiten una mayor flexibilidad. Comparado con MaxEnt, el modelo de favorabilidad minimizó el sobreajuste del modelo. Palabras clave: Datos de atlas de distribución, Transferibilidad de modelos, Modelo de favorabilidad, Modelo de máxima entropía, Sobreajuste, Salamandra salamandra Received: 10 IX 15; Conditional acceptane: 24 XI 15; Final acceptance: 22 II 16 Jesús Olivero & Raimundo Real, Grupo de Biogeografía, Diversidad y Conservación, Depto. de Biología Animal, Fac. de Ciencias, Univ. de Málaga, Campus de Teatinos s/n., 29071 Malaga, Spain.– Albertus G. Toxopeus & Andrew K. Skidmore, Dept. of Natural Resources, Geo–information Science and Earth Observation (ITC), Univ. of Twente, P. O. Box 217, Hengelosestraat 99, 7500 AE, Enschede, The Netherlands.

ISSN: 1578–665 X eISSN: 2014–928 X

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Introduction

Material and methods

Atlases are available for a large variety of taxa world� wide and represent species occurrence in the form of maps (Harrison, 1989). These maps often cover extensive geographic regions and their production usually involved large numbers of volunteers collecting data. Finer–scale maps of the distribution of species, required for conservation planning, can be derived from atlas maps by using statistical downscaling techniques (Kunin et al., 2000; Araújo et al., 2005; Barbosa et al., 2010). Such finer resolution maps have been valuable to understand how environmen� tal variables and different spatial resolutions affect species distributions (Barbosa et al., 2010) and to determine the impact of climate change on species ranges (Araújo & Rahbek, 2006) and the links between human nutrition and biodiversity protection (Fa et al., 2014, 2015). Downscaling assumes that a property within larger units is the arithmetic average of the property within smaller units (Bierkens et al., 2000). The ability of a model to produce fine–scale species distributions from a coarser resolution has been described as model generality or model transferability (Vanreusel et al., 2007; Gray et al., 2008). Comparisons of model transferability using different Species Distribution Models (SDMs) have been undertaken by several authors (Peterson et al., 2007; Gray et al., 2008). In this paper, we test for the first time the performance of the favourabil� ity function (FF) model and the Maximum Entropy (MaxEnt) model. The FF model was designed to derive species distribution maps by obtaining, from logistic regression, an environmental favourability function from a species occurrence whose results are not affected by an uneven proportion of pres� ences and absences (Real et al., 2006; Acevedo & Real, 2012); this property permits direct comparison between models when different species are involved in the analysis, and allows for model combinations (e.g., Fa et al., 2014). MaxEnt �� is a presence–back� ground profile method that has been successfully applied in a number of fields (Phillips et al., 2006). Considered consistently competitive with the highest performing methods (Elith et al., 2006, 2010), this is the most widely used SDM algorithm (Fourcade et al., 2014).�� MaxEnt uses input from a set of lay� ers or environmental variables as well as a set of georeferenced occurrence locations, to produce a model of relative suitability across the study area. Here, we evaluate the performance of MaxEnt and FF in downscaling (from a spatial resolution of 10 x 10 km squares to 1 x 1 km squares) by using the known distribution of a terrestrial species, the fire sa� lamander, Salamandra salamandra (Linnaeus, 1758) (Urodela, Salamandridae) in Andalusia (southern Spain). We test how well each model performs by assessing whether it: (1) displays sufficient discrimi� nation power at finer spatial resolutions; (2) accurately predicts observed distributions at finer resolutions; and (3) significantly resembles predictions obtained with models trained using independent data at a finer resolution.

Species and study area The fire salamander, Salamandra salamandra, occurs throughout most of the western Palaearctic region. This species is not included in the worldwide IUCN Red List, but is considered vulnerable in Spain (Pleguezuelos et al., 2004). The Andalusian region (fig. 1A) harbours three of the nine subspecies present in the Iberian pe� ninsula: the entire distribution of S. s. longirostris in the south, most of the range of S. s. morenica in the north, and some populations of S. s. crespoi in the west. The presence of S. salamandra is closely related to spe� cific environments: wet and shaded zones with high rainfall located on medium to high mountainous areas; forests with ponds or streams; and wet grasslands surrounded by hedges or stone walls (García–París et al., 2004; Pleguezuelos et al., 2004). The specific habitat requirements of the selected species result in a clear environmentally–defined distribution that makes it suitable for model evaluation. To test the downscaling performance of the various models we first used presence–absence atlas data (10 x 10 km UTM square grids) of S. salamandra in Andalusia (f�� igs. 1A, 1B�� ). Data from the species dis� tribution map published in Pleguezuelos et al. (2004) were used. The species was present in 328 (37%) 10 x 10 km UTM squares. Additionally, we used an independent dataset of 1,090 presences of the spe� cies (1 x 1 km resolution) to evaluate the results of the downscaled models. These records were direct observations of the species throughout Andalusia, obtained from field surveys undertaken between 1980 and 2003 (Tejedo et al., 2003; fig. 1C). Environmental variables We considered a total of 34 environmental varia� bles for our modelling procedures (table 1). These variables included climate, topography, land cover, and human activities. Climate may affect the distri� bution of species, mainly at global and meso–scales, whereas topography and land cover act at meso– and micro–scales (Mackey & Lindenmayer, 2001). A set of climatic variables was selected to provide information about average annual values, average seasonal values, and intra–annual variation. To� pographical variables were selected because they represent a level of strong integration between multiple factors that are biogeographically important for species (Hof et al., 2012), for example, tempera� ture, air pressure, humidity, precipitation, availability of area with certain environmental conditions, soil erosion, risk of extinction, and refuges for Pleisto� cene species. Vegetation cover could be a suitable descriptor for the distribution of S. salamandra since the most favourable areas for the species in southern Spain are ecosystems associated with forests but not with pastures and crops (Miñano et al., 2003; Romero et al., 2012); the Normalized Difference Vegetation Index (NDVI; Tucker, 1979) was used as a descriptor of vegetation because it

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0 205 500

1,000 1,500 2,000 km

Fig. 1. Geographical context of the study area and distribution of the fire salamander, Salamandra salamandra, in Andalusia: A. Spain is coloured grey, with Andalusia (southern Spain) shaded dark grey; B. Distribution in 10 x 10 km UTM squares according to Pleguezuelos et al. (2004); C. Location of 1 x 1 km grids with presence according to Tejedo et al. (2003). Fig. 1. Contexto geográfico del área de estudio y distribución de la salamandra común, Salamandra sala� mandra, en Andalucía: A. Se ha sombreado España en gris, con Andalucía (sur de España) en gris oscuro; B. Distribución en cuadrículas de UTM de 10 x 10 km según Pleguezuelos et al. (2004); C. Localización de las cuadrículas de 1 x 1 km con presencia según Tejedo et al. (2003).

is considered a good indicator of photosynthetically active biomass (Sellers, 1985; Khan et al., 2010). Distance to inland waters was selected because S. salamandra uses river courses and water bodies for reproduction (Miñano et al., 2003). Finally, anthro� pogenic factors (or human activities), such as roads or settlements, as well as land cover change due to agricultural activities, may have serious impacts on the habitats of S. salamandra in southern Spain (Pleguezuelos et al., 2004). All variables were available at a 1 x 1 km resolution, or were resampled at this resolution from finer ones. We computed the means of all variables within each 10 x 10 km square. Before inclusion in the modelling procedure, all variables were tested for multi–col� linearity. Variables with high multi–collinearity were removed until all remaining variables had a variance inflation factor (VIF) of < 10 (Marquardt, 1970; Mont� gomery & Peck, 1982). The remaining variables were included in the modelling routines, so that all models operated with the same variable set. Figure 2 shows a schematic description of the subsequent method� ological procedure.

Modelling techniques The FF model assesses variation in the probability of occurrence of a species, under certain conditions, with respect to the overall prevalence of the event (Real et al., 2006; Acevedo & Real, 2012). Favourability values are, thus, independent from the species prevalence. This property enables direct comparison between models when several species are involved in the analytical design, and allows for model combinations through fuzzy logic (Barbosa & Real, 2012). For this model, we used a forward–backward stepwise logistic regression to obtain a linear combination of variables (y). Favourability values were then computed using the following equation: F = ey / [(n1 / n0) + ey]

(equation 1)

where e is the basis of the natural logarithm, and n1 and n0 are the number of presences (= 328) and of absences (= 638), respectively. Absences were considered to be those squares not included in the presences subset. The use of a large number of

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Table 1. List of variables considered for the environmental models of Salamandra salamandra in Andalusia. The relative importance of each variable entered in the models was measured with the Wald parameter for the favourability function (FF), and with the percentage contribution for the two MaxEnt models: AMx. Auto– feature model; LMx. Linear–feature model; a WorldClim (Hijmans et al., 2005); b Mu et al. (2007); c Kumar et al. (1997); d Greif & Scharmer (2000); e GlobDEM50 (Farr & Kobrick, 2000); f Decadal NDVI images at 1 x 1 km spatial resolution collected by the VGT1 sensor onboard the System Probatoire d’Observation de la Terre 4 (SPOT4) platform (Oindo & Skidmore, 2002); g NIMA (1997); h IGN (1999); i Dobson et al. (2000). Tabla 1. Lista de variables ambientales consideradas en los modelos de distribución de Salamandra salamandra en Andalucía. La importancia relativa de las variables introducidas en los modelos se ha estimado mediante el parámetro de Wald para la función de favorabilidad (FF) y mediante el porcentaje de contribución en el caso de dos modelos de MaxEnt: AMx. Modelo con ajuste automático entre presencias y variables; LMx. Modelo con ajuste lineal. (Para las otras abreviaturas, véase arriba.)

Predictor variables

Relative importance

AMx

LMx

31.6

Climatic variables Average annual temperature (ºC)a Average temperature in January (ºC)a Average temperature in July (ºC)a

5.4

3.3

1.6

1.8

Average monthly spring rainfall (mm)a

1.3

1.0

15.5

1.6

< 0.1

53.9

7.3

6.7

24.6

0.9

3.8

5.5

2.2

4.1

Exposure to south (º)

< 0.1

0.2

Exposure to west (º)

0.1

< 0.1

6.9

6.7

Annual temperature range (ºC) Annual rainfall (mm)

Average monthly summer rainfall (mm)a Average monthly autumn rainfall (mm)a Average monthly winter rainfall (mm)a Annual rainfall coefficient of variationa Average annual evapotranspiration (mm)b Average spring evapotranspiration (mm)b Average summer evapotranspiration (mm)b Average autumn evapotranspiration (mm)b Average winter evapotranspiration (mm)b Average annual solar radiation (Wh/m2)c,d Average spring solar radiation (Wh/m2)c,d Average summer solar radiation (Wh/m2)c,d Average autumn solar radiation (Wh/m2)c,d Average winter solar radiation (Wh/m2)c,d Topographic variables Elevation (m)e Slope (º)e e

Land–cover variables Average annual NDVIf Average spring NDVIf Average summer NDVIf Average autumn NDVIf

8.6

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Table 1. (Cont.) Predictor variables

Relative importance

AMx

LMx

55.6

68.1

74.3

Annual NDVI coefficient of variance

0.3

< 0.1

Distance from inland waters (km)

0.8

0.9

Distance to nearest large city (km)h

0.9

< 0.1

Distance to nearest highway (km)

1.9

3.5

Population density in 2000 (pop/m )

0.5

0.1

Average winter NDVIf f

8.2

Anthropogenic variables h

2 i

variables in the model building process could cause type–I error. To avoid this, we controlled the false discovery rate (FDR) due to multiple tests using the procedure proposed by Benjamini & Hochberg (1995). To estimate the weight of variables in the model, we used the estimated Wald test (Hosmer & Lemeshow, 2000, p. 16). MaxEnt estimates the most uniform probability distribution (i.e., maximum entropy) of each environ� mental variable within the study area with the cons� traint that the expected value of each variable under this estimated distribution matches the mean values for the set of occurrence data (Phillips et al., 2006). MaxEnt is based on distinguishing known occurrence sites for a species from the 'background', that is the sum of presences and absences. For the occurren� ce of a given species, MaxEnt defines a probability distribution ql(x) according to this equation: ql(x) = [exp(Snj=1lj×fj(x))]/Zl

(equation 2)

where fj(x) is the value of a set of features (f1,…,fn), which are derived from environmental variables, at each x site, l = (l1,...,ln) is a vector of feature weights, and Zl is a normalizing constant which ensures that ql(x) sum to 1 over the study area. The results of the analyses were presented in a logistic output format (Q) so that large differences in output values better matched large differences in suitability: Q = [eH ql(x(z))] / [1 + eH ql(x(z))] (equation 3) where z is a vector of environmental variables, ql(x(z)) is the probability distribution in sites x with environmen� tal conditions z, and H is the entropy of ql. We ran 500 iterations using the Maximum Entropy Species Distribution Modelling v3.3.3 software. Two alternative procedures were considered for feature classes and they determined two degrees of flexibility for the model fit: (1) auto features —where linear, quadratic, product, threshold, and hinge features were combined— with the application's auto–option for datasets having more than 80 training samples

(Phillips & Dudík, 2008); and (2) linear features, where only linear features are permitted —as performed in the FF model. We used the regularization parameter settings (aimed at minimizing overfitting) proposed by Phillips & Dudík (2008) for more than 100 occurrence records, but we did not apply regularization multipliers (Radosavljevic & Anderson, 2014). Through the choice of these options in MaxEnt, we aimed to analyse the performance of downscaling at the edges of a whole range of degrees in model flexibility. Maps resulting from SDMs were downscaled from a 10 x 10 km resolution to 1 x 1 km squares. The models were thus projected to a 1 x 1 km resolution grid across the study area by applying the model equations (i.e., equation 1 for the FF model, and equation 3 for the MaxEnt models�� ) to predictor variables at this resolu� tion (see examples in Araújo et al., 2005; Barbosa et al., 2010). This method was chosen for simplicity. It is known as the direct downscaling approach (Bombi & d’Amen, 2012), and classified by Bierkens et al. (2000) as 'downscaling based on mechanistic models through a deterministic function (i.e., either equation 1 or equation 3)'. Comparison of model transferability We assessed the capacity of the models to discrimi� nate between presence and absence the receiving operating characteristic (ROC) plot. The area under the ROC curve (AUC) provides a single–number discrimination measure across all possible thresholds (Fielding & Bell, 1997). For the initial models, the ROC was assessed for the 10 x 10 km training data, and re–calculated after downscaling to the 1 x 1 km dataset. A higher AUC can indicate better perform� ance on condition that models are compared for the same species in the same study area (Lobo et al., 2008), because AUC can be influenced by the spe� cies prevalence or relative occurrence area (Chefaoui et al., 2011; Khaoruba et al., 2013). Sensitivity and specificity were also calculated before and after downscaling, considering thresholds throughout the whole suitability range.

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Suitability values predicted for the study species in presence grids were analysed for the FF and MaxEnt models. We used the Mann–Whitney U–test to eva� luate changes in suitability resulting from downscaling to a finer spatial resolution. We performed a threshold–dependent assessment to evaluate the model’s capacity to describe and predict. A threshold defining 'highly suitable' areas is needed to classify the distribution of a species. Suitability values obtained with the FF model were divided into three classes: highly suitable, i.e. = > 0.8; intermediate, 0.2–0.8; and 'highly unsuitable', = < 0.2. This is equivalent to defining a prediction with odds higher than 4:1 for 'highly suitable' and 'highly unsuita� ble' sites (Muñoz & Real, 2006). For the MaxEnt mo� dels, we used the ‘equalized predicted area' criterion for model comparison, which selects a threshold so that the compared models have the same predicted area (Phillips et al., 2006). Thus, for every MaxEnt model, thresholds were chosen in such a way that the sum of the grids in the results map —classified as 'highly suitable' and 'highly unsuitable'— equated those in the FF model. Thresholds calculated for the 10 x 10 km resolution outputs were also used in the 1 x 1 km outputs. We determined the descriptive capacity of the models before downscaling (at 10 x 10 km) by com� puting the percentage of presence grids in the 'highly suitable' and 'highly unsuitable' areas. To assess the models' predictive capacity after downscaling, we used presences at a 1 x 1 km resolution from Tejedo et al. (2003) as independent data (see also Araújo et al., 2005; Barbosa et al., 2010). To calculate if the differences between percentage presences were significant we used the arcsine test of equality of percentages (Sokal & Rohlf, 1979, p. 663). Finally, we also compared the downscaled models with alternative models trained using the 1 x 1 km dataset derived from Tejedo et al. (2003). Absences of S. salamandra were recorded if the species was not cited within the grid. The Pearson correlation coefficient was used for model comparison. Results Model description Only 16 of the original 34 variables were retained after the multicollinearity analysis. The set of varia� bles related to actual evapotranspiration was deleted, because these variables were strongly correlated with the NDVI (correlations were often higher than 0.8) and with temperature, radiation, and rainfall (correlations were sometimes higher than 0.7). All the average annual variables were also deleted because of their high VIF. If the values were reasonable, we preserved the variables that provided information on mean seasonal values and intra–annual variations of temperature, rainfall, and NDVI. Therefore, the annual temperature range and the average monthly spring rainfall were retained, despite the VIF being higher than 10 in the MaxEnt models (12.8 and 11.3, res�

pectively). The 16 remaining variables were included in the three modelling routines, although only eight of these variables were selected by the stepwise procedure for the FF model (table 1). Both the 'linear–feature' and 'auto–feature' MaxEnt models showed great similarities in ranking the impor� tance of the variables (table 1). The FF model also selected variables with high relevance in the MaxEnt models; average winter NDVI and average summer solar radiation were the most important variables in the three models. In general, suitability for S. salamandra was defined by mountain areas close to inland water, with high vegetation cover and climatically conditioned by variables describing energy and water availability throughout the year (see table 1), in agreement with the known habitat requirements for the species. Model discrimination, sensitivity, and specificity The FF and MaxEnt models produced visually similar geographical outputs and predictions (fig. 3A). Higher suitability values were obtained for areas where S. salamandra was present (compare with fig. 1). The discriminatory capacity of the three models at the lower resolution was > 0.9 for the AUC, i.e., 'outs� tanding' (Hosmer & Lemeshow, 2000, p. 162), and around 3% higher when comparing the 'auto–feature' MaxEnt model with the models combining variables linearly (see table 2). After downscaling, the capacity of the three models to discriminate between 1 x 1 km squares with and without presences was between 0.8 and 0.9 i.e., 'excellent'; the AUC was around 2.5% higher for the FF model. For all three models, the minimised difference bet� ween sensitivity and specificity was close to the 0.4 suitability value for the higher spatial resolution (fig. 4A). The sensitivity of the FF model was significantly higher than for the MaxEnt models where suitability was > 0.4. After downscaling (fig. 4B), the minimised differen� ce between sensitivity and specificity was at the 0.8 suitability value for the FF model, but remained close to the 0.4 suitability value using MaxEnt. Sensitivity increased considerably after downscaling in the FF model, whereas it decreased minimally in MaxEnt; the specificity decreased in all three models, though more strongly in the FF. Suitability values Average suitability for presence grids increased signifi� cantly after downscaling in the FF and 'linear–feature' MaxEnt models (Mann–Whitney U–test, p < 0.001); the increase was steeper in the FF model (see table 3, fig. 5), but suitability values remained stable in the 'auto–feature' MaxEnt model (p > 0.1). Threshold–dependent evaluation After downscaling, the percentage of 'highly suitable' squares increased (almost doubling) and the percen� tage of 'highly unsuitable' grids decreased slightly when using the FF model. Both percentages remained almost stable when using MaxEnt (fig. 3B; table 2).

Animal Biodiversity and Conservation 39.1 (2016)

Input

105

Species Variables

Presence/absence in 10 x 10 km UTM squares

Performance evaluation

1 x 1 km rasters

Modelling 10 x 10 km predictions

Discrimination AUC with input data at 10 x 10 km

Comparison of suitability values: Mann–Whitney U

Capacity to predict % of 10 x 10 km presence in each suitability class

1 x 1 km predictions (downscaling)

Average values within 10 x 10 km UTM squares

Performance evaluation Discrimination AUC with 1 x 1 km independent data

Output Suitability values in 10 x 10 km squares

Suitability values in 1 x 1 km squares*

Suitability classes at 10 x 10 km based on thresholds

Suitability classes at 1 x 1 km based on thresholds

Comparison of suitability values: Mann–Whitney U

Capacity to predict % of 1 x 1 km observations in each suitability class

Fig. 2. Schematic description of the methodological procedure: * Downscaled suitability values in 1 x 1 km squares are also compared to suitability values predicted by models trained with 1 x 1 km data. Fig. 2. Descripción esquemática del procedimiento metodológico: * Los valores de idoneidad al aumentar la resolución en cuadrículas de 1 x 1 km también se compararon con los valores de idoneidad predichos por los modelos calibrados con datos de 1 x 1 km.

Compared to the results of the MaxEnt models, the FF model showed significantly more presence grids in the 'highly suitable' area after downscaling (arcsine test of equality of percentages, p < 0.01) and significantly fewer presence grids in the 'highly unsuitable' area (p < 0.01). The results computed using the 'linear– feature' MaxEnt showed significantly more presence grids in the 'highly suitable' area than the results computed using 'auto–feature' MaxEnt (p < 0.01). The percentage of recorded presence grids in 'highly suitable' areas significantly increased after downscaling when using the FF model and also when using 'linear–feature' MaxEnt (arcsine test of equality of percentages, p < 0.01; the increase was steeper in the former case, see table 2, fig. 5). Within the 'highly unsuitable' areas, this percentage of presence grids increased significantly using 'auto–feature' MaxEnt (p < 0.01), and decreased significantly using the FF model (p < 0.01).

ver modelling technique was used; this was only slightly higher than the corresponding downscaled models. Correlation coefficients between models derived from downscaling and models trained with 1 x 1 km data performed using the same algorithm (main diagonal in table 4) were significant (p < 0.01), being higher than 0.7 using 'auto–feature' MaxEnt, higher than 0.8 using 'linear–feature' MaxEnt, and higher than 0.9 using the FF model. The three downscaled models had their highest correlation with the model trained with 1 x 1 km data using the FF model (left column in table 4), and correlations with the downscaled FF model (upper line in table 4) equalled the intra–technique correlation with the models trained at 1 x 1 km (main diagonal).

Downscaled models vs. models trained with high resolution data

Species distribution maps from biological atlases are often too coarse for real–world conservation planning (Kunin et al., 2000; Araújo et al., 2005; Barbosa et al., 2010; Bombi & D’Amen, 2012). National atlases, such as those for mammals in Spain, are at best at resolutions no

The AUC of the models trained with independent 1 x 1 km data (fig. 3C) were higher than 0.8 (table 2) whiche�

Discussion Model downscaling: valuable for conservation planning?

Olivero et al.

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Downscaling

10 x 10 km ----------------> 1 x 1 km

10 x 10 km --------------> 1 x 1 km 1

0.5

Suitable areas

Suitability

C 1 x 1 km

Unsuitable areas

Intermediate suitability

0.5

Suitability

Fig. 3. Geographical representation of the three distribution models performed for the fire salamander, Salamandra salamandra, in Andalusia: A. Suitability based on the models performed with 10 x 10 km resolution data, before and after downscaling to a 1 x 1 km resolution; B. Subdivision of Andalusia in highly suitable, intermediate and highly unsuitable areas (the threshold criterion for the FF model was defining a prediction with odds higher than 4:1 for 'highly suitable' grids, and lower than 1:4 for 'highly unsuitable' grids; the equalized predicted area criterion was chosen with MaxEnt, i.e., equating the 'highly suitable' and the 'highly unsuitable' surface areas to those in the FF); C. Suitability based on the models performed with 1 x 1 km resolution data; 1. Favourability; 2. Linear–feature MaxEnt; 3. Auto–feature MaxEnt. Fig. 3. Representación geográfica de los tres modelos de distribución realizados para la salamandra común, Salamandra salamandra, en Andalucía: A. Idoneidad basada en los modelos realizados con datos con resolución de 10 x 10 km, antes y después del aumento de resolución a 1 x 1 km; B. Subdivisión de Andalucía en áreas altamente idóneas, de idoneidad intermedia y altamente inadecuadas (el criterio para establecer umbrales en la función de favorabilidad consistió en definir como "altamente idóneas" las cuadrículas con un pronóstico de presencia mayor que 4:1, y como "altamente inadecuadas" las cuadrículas con un pronóstico de presencia menor que 1:4; con MaxEnt se ha utilizado el criterio de área predicha igualada, que consiste en igualar la superficie de las áreas "altamente idóneas" y "altamente inadecuadas" a las observadas con la función de favorabilidad); C. Idoneidad basada en los modelos realizados con datos con resolución de 1 x 1 km; 1. Favorabilidad; 2. Ajuste lineal de MaxEnt; 3. Ajuste automático de MaxEnt.

less than 10 x 10 km (Palomo & Gisbert, 2008), but those for larger areas, such as those for continental European mammals, can be coarser (50 x 50 km) (Mitchell–Jones et al., 1999). For management purposes, downscaling to finer resolutions is useful. Although some authors argue

that it is not possible to achieve a higher level of detail beyond that contained in the initial coarser–resolution maps (Stockwell & Peterson, 2003), others suggest that the properties that define a species distribution are the same at whatever resolution (Kunin, 1998).

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Table 2. Model assessment: FF. Favourability function; LMx. Maxent using only linear features; AMx. MaxEnt using the auto–feature option; a State variables were based on the distribution of S. salamandra according to Pleguezuelos et al. (2004) (10 x 10 km resolution) and to Tejedo et al. (2003) (1 x 1 km resolution); b Models performed with 10 x 10 km resolution data; c Models downscaled to a 1 x 1 km resolution; d Models performed with 1 x 1 km resolution data; e Asterisks indicate significant differences between percentages (arcsine test of equality of percentages; p < 0.01) compared to FF; f Asterisks indicate significant differences between percentages (arcsine test of equality of percentages; p < 0.01) compared to those before downscaling. Tabla 2. Evaluación del modelo: FF. Función de favorabilidad; LMx. MaxEnt utilizando solo el ajuste lineal; AMx. MaxEnt utilizando el ajuste automático; a Las variables se basaron en la distribución de S. salamandra según Pleguezuelos et al. (2004) (resolución de 10 x 10 km) y Tejedo et al. (2003) (resolución de 1 x 1 km); b Modelos realizados con datos con resolución de 10 x 10 km; c Modelos con resolución aumentada a 1 x 1 km; d Modelos realizados con datos con resolución de 1 x 1 km; e Los asteriscos indican diferencias significativas entre porcentajes (transformación arcoseno de igualdad de porcentajes; p < 0,01) en comparación con FF; f Los asteriscos indican diferencias significativas entre porcentajes (transformación arcoseno de igualdad de porcentajes; p < 0,01) en comparación con los porcentajes antes del aumento de resolución.

Parameter

LMx

AMx

Area under the ROC curvea AUC

10 x 10 kmb

0.920

0.925

0.948

10 x 10 –> 1 x 1 kmc

0.828

0.807

0.810

1 x 1 km

0.841

0.842

0.879

14.9

27.0

16.3*

11.2*

Percentage of gridse Highly suitable for Salamandra salamandra

10 x 10 kmb

10 x 10 –> 1 x 1 km c

Highly unsuitable for S. salamandra

10 x 10 kmb

51.9

10 x 10 –> 1 x 1 kmc

43.2

51.5*

54.6*

Percentage of presence gridsf In areas highly suitable for S. salamandra

10 x 10 kmb

40.7

38.2

42.5

10 x 10 –> 1 x 1 kmc

76.0*

52.8*

41.0

8.3

7.3

4.6

3.1*

7.0

7.3*

In areas highly unsuitable for S. salamandra

10 x 10 kmb

10 x 10 –> 1 x 1 km c

In our study, we showed that downscaling from 10 x 10 km maps to a 1 x 1 km resolution caused only a slight loss of discriminatory capacity. Overall, both methods had outstanding discriminatory capacities at the coarser resolution, even though the species’ prevalence in Andalusia (37%) was not remarkably low; these capacities remained excellent after downscaling. Some loss of discriminatory capacity after downscal� ing is not surprising. As spatial resolution becomes finer, local effects become more important (Hewitson & Crane, 1996). Thus, a reduction in accuracy is ex� pected because the importance of climate in influencing species distributions decreases at more local scales, whereas the influence of micro–environmental factors such as topography increases (Pearson et al., 2002;

Trivedi et al., 2008). Araújo et al. (2005) suggested that interpolation is possible if governing processes affecting species' distributions at coarser resolutions are also important in driving distributions at finer resolutions. In our case study, a combination of environmental fac� tors that could affect the distribution of S. salamandra at different spatial resolutions was used to prevent excessive loss in the biological meaning of the model. According to Guisan et al. (2007) and Bombi & D'Amen (2012), a 10–fold shortening of the grain size —referring to pixel side length— as is our case, should not severely affect predictions of species distributions. However, this meant that the number of finer–scale observations and predictions was roughly 100 times higher, and that the proportion between observed pres�

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Specificity (ascending lines) Sensitivity (desdending lines)

108

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1

A 10 x 10 km

Favourability Linear–feature in MaxEnt Auto–feature in MaxEnt

1.0 0.9 B 0.8 10 x 10 –> 1 x 1 km 0.7 0.6 0.5 0.4 0.3 Favourability 0.2 Linear–feature in MaxEnt Auto–feature in MaxEnt 0.1 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6

0.7

0.8

0.9

1.0

Suitability value Fig. 4. Sensitivity and specificity of the three models before (A) and after (B) their interpolation to a finer resolution. The fire salamander, Salamandra salamandra, distribution data provided by Pleguezuelos et al. (2004) were used at a 10 x 10 km resolution, and by Tejedo et al. (2003) at a 1 x 1 km resolution (see fig. 1). Fig. 4. Sensibilidad y especificidad de los tres modelos antes (A) y después (B) de su interpolación para aumentar la resolución espacial. Se han utilizado los datos sobre la distribución de la salamandra común, Salamandra salamandra, proporcionados por Pleguezuelos et al. (2004) con resolución de 10 x 10 km y por Tejedo et al. (2003) con resolución de 1 x 1 km (véase la fig. 1).

ence and absence was much lower than that at the coarser–scale. Consequently, in many suitable 1x1 km sites, the species was not observed, reducing the discriminative capacity of the model. In this situation, the downscaled model cannot —and should not— be very specific, and sensitivity should be considered as a better measurement of performance than specificity. This is why AUC, which weighs sensitivity and specifi� city equally, is expected to be lower after downscaling as a result of a much lower presence/absence ratio in the 1 x 1 km resolution dataset than in the training data. Bombi & D’Amen (2012) also observed that a more general effect of downscaling is a reduction of specificity. Our finding that our downscaled models had excellent discriminatory capacity, with a high capacity to predict species occurrences, suggests that this approach can be valuable for decision–making in conservation. None� theless, model downscaling will be more successful for wide–ranging taxa than for taxa with smaller home ranges that often have especially aggregated distribu� tions, and low dispersal (Kaliontzopoulou et al., 2008; Barbosa et al., 2010). This is because the former are more dependent on macro–environmental factors than spatially restricted species.

Threshold independent comparison Using a visual inspection of the geographic output, Araújo et al. (2005) found that downscaled maps were not only able to recover original spatial patterns of rich� ness observed at the coarser resolution, but were also able to identify finer gradients that were invisible in the original resolution. In our study, the 'auto–feature' MaxEnt model produced a more fragmented 1 x 1 km geographi� cal pattern than the other models (fig. 3A); this could be related to the degree of flexibility of this model being higher than the other two. The 'hinge' feature class in the auto–features option makes MaxEnt resemble the procedure for generalized additive models (GAMs) that find a flexible geographical relationship between species and the environment (Elith et al., 2010). This leads to a high model fit to observed species distributions (see fig. 6), which in our case provided a clear match between predicted highly suitable areas for S. salamandra and mountain rivers (see fig. 3A). Barbosa et al. (2010) also observed that the courses of rivers emerged as suitable areas for Lutra lutra and for Galemys pyrenaicus in Spain after downscaling from a 10 x 10 km resolution model, despite the fact that river locations were not explicitly included as predictor variables in their models.

Animal Biodiversity and Conservation 39.1 (2016)

At a more quantitative level, AUC comparisons suggested that model flexibility may have enhanced the discrimination capacity of the original output, at the cost of hindering its capacity to discriminate after downscaling. This is demonstrated by the fact that the 'auto–feature' MaxEnt model was the best discrimina� tor before downscaling, whereas the FF model was the best discriminator after downscaling (table 2). As observed in our results, previous MaxEnt–GLM com� parisons showed AUC values that were on average 2%–3% higher in �� MaxEnt models than in logistic–re� gression models (e.g., Elith et al., 2006 [n = 10]; Gibson et al., 2007 [n = 1]; Marini et al., 2010 [n = 12]). Here, this only happened with the 'auto–feature' MaxEnt model, which permitted the highest flexibility, and also yielded the lowest AUC values when downscaled at the 1 x 1 km resolution. Threshold–dependent comparison The FF model was more sensitive to both 10 x 10 km and 1 x 1 km presence observations of S. salamandra than the MaxEnt models, especially when the suitability threshold was high (fig. 4). Once a threshold for 'highly suitable' areas was defined, the FF model produced the highest proportion of presence observations in 'highly suitable' areas at the 1 x 1 km resolution (table 2). However, below the threshold for very low unsuitability, the FF model had the lowest proportion of presences, that is, the lowest over–prediction rate at this threshold (Barbosa et al., 2013). In contrast, the lowest proportion of presence grids in 'highly suitable' areas was obtained in the 'auto–feature' MaxEnt model (table 2). A possible explanation for this is that the detailed definition of water courses in the downscaled 'auto–feature' MaxEnt model

1 0.9 0.8 0.7 0.6 0.5 0.4 0.3

Favourability

109

Table 3. Mann–Whitney U–test to compare the rank of suitability values for Salamandra salamandra before and after downscaling: R10. Rank (10 x 10 km); R1. Rank (1 x 1 km) FF. Favourability function; LMx. MaxEnt using only linear features; AMx. MaxEnt using the auto–feature option; a Models performed with 10 x 10 km resolution data; b Models downscaled to a 1 x 1 km resolution. Tabla 3. Prueba de U de Mann–Whitney para comparar el rango de valores de idoneidad para Salamandra salamandra antes y después del aumento de resolución espacial: R10. Rango (10 x 10 km); R1. Rango (1 x 1 km); FF. Función de favorabilidad; LMx. MaxEnt utilizando solo el ajuste lineal; AMx. MaxEnt utilizando el ajuste automático; a Modelos con datos con resolución de 10 x 10 km; b Modelos con resolución aumentada a 1 x 1 km. FF

R10a

R1b

455.19 783.40 1,412 95,218 < 0.001

LMx 620.12 732.53 1,412 149,151 < 0.001 AMx 729.50 699.57 1,412 184,917 0.245

(see fig. 3B and discussion of the threshold–independent comparison) may be an artefact; it excluded locations, often far from water courses, in which individuals of this species are generally found outside the breeding season.

MaxEnt

10 x 10 1 x 1 Linear

Average suitability value

Auto

Presence proportion in highly suitable areas

Fig. 5. Average of suitability: F for favourability function (equation 1), and Q for MaxEnt (equation 3) in fire salamander, Salamandra salamandra, presence grids, and the proportion of presence grids in areas considered environmentally highly suitable by the models, before and after downscaling. MaxEnt values are represented according to both the 'linear–feature' and the 'auto–feature' options for the relationship between presences and environmental variables. Fig. 5. Promedio de la idoneidad: de F para la función de favorabilidad (ecuación 1), y de Q para MaxEnt (ecuación 3) en las cuadrículas con presencia de salamandra común (Salamandra salamandra), y proporción de cuadrículas con presencia en áreas consideradas muy idóneas desde el punto de vista ambiental según los modelos, antes y después del aumento de resolución espacial. Los valores de MaxEnt se han representado de acuerdo con ambas opciones de ajuste, "lineal" y "automático", entre presencias y variables ambientales.

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Table 4. Pearson coefficients for pairwise correlations between model outputs. All correlations were significant (p < 0.01): 1 x 1 km. Models performed with 1 x 1 km resolution data; 10 x 10 –> 1 x 1 km. Models downscaled to a 1 x 1 km resolution; FF. Favourability function; LMx. MaxEnt using only linear features; AMx. MaxEnt using the auto–feature option. Tabla 4. Coeficientes de Pearson para las correlaciones entre modelos. Todas las correlaciones fueron significativas (p < 0,01): 1 x 1 km. Modelos realizados con datos con resolución de 1 x 1 km; 10 x 10 –> 1 x 1 km. Modelos con resolución aumentada a 1 x 1 km; FF. Función de favorabilidad; LMx. MaxEnt utilizando solo el ajuste lineal; AMX. MaxEnt utilizando el ajuste automático. 1 x 1 km

LMx

AMx

0.912

0.872

0.776

LMx

0.886

0.876

0.761

AMx

0.833

0.817

0.770

10 x 10 –> 1 x 1 km

Downscaled models vs. models trained with high resolution data The comparison between the downscaled models and those trained with 1 x 1 km data, either based on prediction map visualization (figs. 3A, 3C), on correlation (table 4), or on discriminatory capacity (ta� ble 2), demonstrates that transferring the model from 10 x 10 km squares to 1 x 1 km squares worked well with all three methods. However, some noteworthy differences between models were found (table 4): the FF model not only had the highest correlation with the downscaled Favourability model, but also showed the highest correlations with any other downscaled model; at the opposite extreme was 'auto–feature' MaxEnt model, for which the lowest correlations with the downscaled models were obtained. Thus, the equivalence between downscaled models and models trained with fine–resolution data was higher with the FF model than with the MaxEnt models, though the ‘linear–feature’ model provided closer equivalences than when making the model as flexible as possible (as recommended by Phillip & Dudík, 2008). The two 1 x 1 km resolution maps created by the 'auto–feature' MaxEnt model produced a similar pat� tern of strips classified as ‘highly suitable’ areas for S. salamandra (compare figs. 3A, 3C). However, whe� reas these land strips corresponded to river courses in the downscaled model, in the model trained with the 1 x 1 km data they corresponded to secondary roads denoting sampling bias (compare figs. 1, 3C). Even though regularization parameters were set in MaxEnt

models as proposed by Phillips & Dudík (2008), a certain degree of overfitting is the most probable cause for the spatial coincidence between occurrences and roads in the 1 x 1 km model prediction. Conclusions Three main conclusions can be drawn from our results: (1) both MaxEnt and the FF model performed correctly when transferring models to a finer spatial resolution; (2) the FF model transferred better to a finer resolution compared to MaxEnt (i.e., the downscaled FF model got higher discrimination capacity and more accurate predictions); (3) the models that were based on linear combinations of environmental variables provided more accurate and less overfitted predictions after they were downscaled than the model that combined variables using a highly flexible function. Model accuracy and generality are characteristics that may compete with each other (Araújo & Rahbek, 2006; Elith et al., 2010), i.e., highly accurate models, in terms of the training data, might not be transfer� able. The main difference between a very flexible model and other models based on more restricted adjustments is exemplified in the response curves representing how each environmental variable affects the predictions of the three models in this study (fig. 6). The 'auto–feature' MaxEnt model seems to maximize the fit between the model and the training distribution data, whereas the other models adjusted the environmental response of S. salamandra to a logistic curve. The way MaxEnt models tried to fit the geographical relationship between species and the environment using auto–features resembles the procedure in generalized additive models (GAM, see Elith et al., 2010). The latter has been considered less robust regarding transferability than generalized linear models (GLM) because of overfitting (Randin et al., 2006). The use of regularization parameters for the control of overfitting has been recently revised (e.g., �� Radosavljevic & Anderson, 2014�� ), and conclu� sions point to the need to increase the regularization values proposed by Phillips & Dudík (2008). In our case study, the 'auto–feature' option in MaxEnt would clearly need regularization multipliers in order to avoid overfitting; however, our results did not suggest the existence of overfitting in the 'linear–feature' Max� Ent model. Alternatively, GLMs may produce models flexible enough to detect non–linear responses of the species to the environment but also constrained enough to avoid modelling stochastic variation in the species distributions. Our results contradict Gastón & García–Viñas (2011)' suggestion that the lower AUC values in GLMs, compared to MaxEnt models, are due to GLM overfitting. Low transferability has been described for MaxEnt when models are extrapolated beyond the study area (Peterson et al., 2007), though such criticism has been countered by Phillips (2008) as based on confusion between transferability and the problem of sample selection bias. Because MaxEnt is based on distinguishing known occurrence sites for a species

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1.00

0.80

0.60

0.40

0.20

0.00

16 18 20 22 24 26 28 Average temperature in July (ºC)

0.00

1.00

0.80

0.60

0.40

0.20

30 35 40 45 50 55 60 65 70 75 80 Average rainfall coefficient of variance (%)

0.00 0.00 5900 6000 6100 6200 6300 6400 6500 6600 3700 3750 3800 3850 3900 3950 4000 4050 Average sun radiation in summer Average sun radiation in winter 1.00

1.00

0.80

0.60

0.40

0.20

0.00

–2 0 2 4 6 8 10 12 14 16 18 20 22 24 Slope (degrees)

0.00

1.00

0.80

0.60

0.40

0.20

0.00

20 40 60 80 100 120 140 160 180 200 Average summer NDVI Favourability function

0 5000 10000 15000 20000 25000 Distance from inland waters (m)

20 40 60 80 100 120 140 160 180 200 Average winter NDVI Linear feature Auto feature in MaxEnt in MaxEnt

Fig. 6. Response curves showing how four environmental variables (x–axes) affected the model predictions (i.e., suitability for the fire salamander, Salamandra salamandra, in the y–axes, that is either the favourability function value F in equation 1 or the MaxEnt output Q in equation 3) while keeping all other variables constant in their average sample value: Black. Favourability function; Dark grey. Linear feature in MaxEnt; Light grey. Auto feature in MaxEnt. Fig. 6. Representación gráfica de la influencia de cuatro variables ambientales (eje de las X) en las predicciones de los modelos (es decir, la idoneidad para la salamandra común, Salamandra salaman� dra, en los ejes de las Y, que en la función de favorabilidad representa el valor F de la ecuación 1 o en MaxEnt, el valor Q en la ecuación 3) cuando las demás variables se mantienen constantes en su valor medio observado: Negro. Función de favorabilidad; Gris oscuro. MaxEnt con ajuste lineal; Gris claro. MaxEnt con ajuste automático.

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from the 'background', selecting 'wrong' backgrounds may cause erroneous outputs that could be incorrectly interpreted as failures of transferability. In this study, the two MaxEnt models used the same ‘background’ for comparisons, i.e., the entire set of 10 x 10 km squares in the study area. When a very flexible combination of variables was accepted, our results suggested the same relationship between overfitting and transferability cost in MaxEnt as that described in Peterson et al. (2007). Constraining MaxEnt to linear combinations of variables largely solved the problem of overfitting, but the transferred Favourability model still showed a better fit to the finer–resolution data than the MaxEnt models. Acknowledgements This work was supported by the Spanish Ministry of Agriculture, Food and Environment, Spanish National Park Network, project 1098/2014, by the FORAGES Research Program at the ITC (Faculty of Geo–Infor� mation Science and Earth Observation, University of Twente), and by the Program 'José Castillejo' (Ref. JC2007–00260). We also thank C. A. J. M. de Bie and V. Venus for their help in deriving key variables for this paper, Dr. J. E. Fa for his useful comments and suggestions, and Mr. S. Coxon for his help in revising the language used in this article. References Acevedo, P. & Real, R., 2012. Favourability: concept, distinctive characteristics and potential usefulness. Naturwissenschaften, 99: 515–522. Araújo, M. B. & Rahbek, C., 2006. How �� does cli� mate change affect biodiversity? Science, 313: 1396–1397. Araújo, M. B., Thuiller, W., Williams, P. H. & Reg� isnster, I., 2005. Downscaling European species atlas distributions to a finer resolution: implications for conservation planning. Global Ecology and Biogeography, 14: 17–30. Barbosa, A. M. & Real, R., 2012. Applying fuzzy logic to comparative distribution modelling: A case study with two sympatric amphibians. ScientificWorldJournal 10.1100/2012/428206. Barbosa, A. M., Real, R., Muñoz, A. R. & Brown, J. A., 2013. New measures for assessing model equilibrium and prediction mismatch in species distribution models. Diversity and Distributions, 29: 1333–1338. Barbosa, A. M., Real, R. & Vargas, J. M., 2010. Use of coarse–resolution models of species’ distributions to guide local conservation inferences. Conservation Biology, 24: 1378–1387. Benjamini, Y. & Hochberg, D., 1995. Controlling the false discovery rate: a practical and powerful ap� proach to multiple testing. Journal of the Royal Statistical Society: Series B, 57: 289–300. Bierkens, M. F. P., Finke, P. A. & de Willigen, P., 2000. Upscaling and downscaling methods for

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Effects of climate change on three species of Cupido (Lepidoptera, Lycaenidae) with different biogeographic distribution in Andalusia, southern Spain

R. Obregón, J. Fernández Haeger & D. Jordano

Obregón, R., Fernández Haeger, J. & Jordano, D., 2016. Effects of climate change on three species of Cupido (Lepidoptera, Lycaenidae) with different biogeographic distribution in Andalusia, southern Spain. Animal Biodiversity and Conservation, 39.1: 115–128. Abstract Effects of climate change on three species of Cupido (Lepidoptera, Lycaenidae) with different biogeographic distribution in Andalusia, southern Spain.— Knowledge of the spatial distribution of rare or endangered species is of key importance to assess conservation status at different geographic scales and to develop conservation and recovery programs. In this paper we review and update the distribution of three species of Lycaenid butterflies in Andalusia (southern Spain): Cupido carswelli, C. lorquinii, and C. osiris. Cupido carswelli is endemic in south east Spain and is considered a vulnerable species in the Red Book of Invertebrates of Andalusia. Cupido lorquinii is an Iberian–Maghrebian endemism, found in the southern half of the Iberian peninsula. Cupido osiris, widely distributed in Europe and Central Asia, has its southern limit of distribution in Andalusia. We modeled the potential current distribution of these species in Andalusia, using Maxent. Their potential distribution was mainly conditioned by the presence of their host plants and, to a lesser extent, by climatic variables: rainfall during the warmest and coldest quarters of the year and annual mean temperature. AUC test values, sensitivity, and specificity for the three models were high, confirming the accuracy of the models and their high predictive values. We also modeled the potential future distributions of the three species under the climate change scenario A2a. Our results predict a significant reduction in the potential distribution for C. lorquinii —which has a wider distribution in Andalusia than the other two species— and for the more localized species, C. osiris and C. carswelli. This expected decline in the south of the Iberian peninsula highlights the pressing need to design and implement specific conservation plans for these species. Key words: Modeling, Global Change, Cupido, Lepidoptera, Iberian peninsula Resumen Efectos del cambio climático en tres especies del género Cupido (Lepidoptera, Lycaenidae) con diferente distribución biogeográfica en Andalucía (sur de España).— El conocimiento de la distribución espacial de especies raras o amenazadas es un elemento clave para evaluar su estado de conservación a diferentes escalas geográficas y para elaborar programas de conservación y recuperación. En este trabajo se revisa y actualiza la distribución en Andalucía (sur de España) de tres especies de licénidos: Cupido carswelli, C. lorquinii y C. osiris. C. carswelli es endémica del SE de España y se considera una especie vulnerable en el Libro Rojo de los invertebrados de Andalucía. C. lorquinii es un endemismo iberomagrebí encontrado en la mitad meridional de la península ibérica. Por el contrario, C. osiris está ampliamente distribuida por Europa central y Asia, y tiene su límite meridional de distribución en Andalucía. Utilizando Maxent, se han elaborado modelos de la actual distribución potencial de estas especies en Andalucía, que resultó estar condicionada principalmente por la presencia de sus plantas nutricias y, en menor medida, por ciertas variables climáticas: la precipitación durante el trimestre más cálido, la precipitación durante el trimestre más frío y la temperatura media anual. Los valores obtenidos de AUC, sensibilidad y especificidad para los tres modelos fueron altos, lo que confirma la exactitud y el elevado valor predictivo de los modelos. Además, se ha elaborado un modelo de la distribución potencial futura de las tres especies en un contexto de cambio climático A2a. Los resultados obtenidos muestran una reducción significativa de la distribución potencial tanto para C. lorquinii, cuya distribución en Andalucía es más amplia que la de las otras dos especies, como para las especies más localizadas, C. osiris y C. carswelli. Esta disminución prevista en el sur de la península ibérica pone de manifiesto la inminente necesidad de elaborar y poner en práctica planes de conservación específicos para estas especies. ISSN: 1578–665 X eISSN: 2014–928 X

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Palabras clave: Elaboración de modelos, Cambio global, Cupido, Lepidoptera, Península ibérica Received: 30 IX 15; Conditional acceptance: 11 XII 15; Final acceptance: 23 II 16

Rafael Obregón, Juan Fernández Haeger & Diego Jordano, Dept. of Botany, Ecology and Plant Physiology, Univ. of Córdoba, E–14071, Córdoba, Spain. Corresponding author: Rafael Obregón. E–mail: rafaobregonr@gmail.com

Animal Biodiversity and Conservation 39.1 (2016)

Introduction In the current scenario of biodiversity decline conditioned by habitat loss and climate change, the populations of an increasing number of species have shown a marked decline in recent years (Asher et al., 2001; Fox et al., 2011; PECBMS, 2013; Balmer et al., 2013; Inger et al., 2015). There is therefore a pressing need to prioritize conservation to mitigate the anticipated effects of global change (Balmford & Bond, 2005) and to elaborate recovery plans. To do so requires the detailed assessment of the state of populations of many species amongst which the geographical distribution is a key aspect. The limits of the area of occupancy are important quantitative criteria to assess the status of species included in any of the categories of the Red List (IUCN, 2012). Current knowledge of the distribution of many species remains vague and incomplete, and is usually based on data that have not been collected following standardized sampling procedures. Data is therefore spatially biased to areas that have been prospected more intensively (Soberón et al., 1996; Hortal et al., 2008; Fernández & Nakamura, 2015) according to their accessibility or attractiveness to researchers (Romo et al., 2006). In this sense, as inland Andalusia is one of the least prospected area in Spain it has the lowest number of records of butterflies in the country (Romo & García–Barros, 2005). Species distribution models (SDMs) are a powerful tool to assess population status because, when properly used (Kramer–Schadt et al., 2013; Merrow et al., 2013), they allow estimation of the main environmental requirements of the species and their geographic projection, from which, maps of the potential or real distribution of the species can be obtained (Guisan et al., 2006; Drake & Bossenbroek, 2009). SDMs have also been used to predict the potential future distribution of species under the influence of climate change (Thuiller, 2003; Parmesan, 2006), thereby helping to detect sensitive areas and to mitigate possible effects (Balmford & Bond, 2005). However, the results of this type of application should be treated with caution (Merrow et al., 2013). In this paper we analysed the current distribution and potential distributions (southern Spain) of the three species of the genus Cupido (Schrank, 1801) in Andalusia (C. lorquinii, C. osiris, and C. carswelli) using Maxent (Phillips et al., 2006; Phillips & Dudik, 2008). Modeling of their potential distributions is particularly useful as it predicts the location of sites that provide the conditions and resources necessary for their presence, and thus indicates priority areas for conservation action. In Andalusia, the three species are distributed as local, isolated, small populations as would be expected given that C. osiris and C. lorquinii are at the limits of their respective ranges, while C. carswelli is an endemic species with highly limited distribution. These factors, combined with their short flight periods and poor ability for dispersal, makes them difficult to locate. Their distributions on a continental scale are very different. Cupido osiris has a wide, but fragmented distribution from southern and central Europe to central Asia

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(López–Vaamonde et al., 1994; García–Barros et al., 2013), with Andalusia being the southern limit of its range on the continent. This southern distribution of taxa of Eurosiberian origin is the result of north–south migrations during glacial–interglacial periods and their postglacial shelter in mountain ranges of the southeastern Iberian peninsula (Martín & Gurrea, 1990; Romo & García–Barros, 2010; Obregón & Gil–T., 2015). In contrast, C. lorquinii is an Ibero–Maghrebi endemism common in the Rif Mountains in northern Morocco and Algeria, while in Europe it is distributed only in the southern half of the Iberian peninsula (García– Barros et al., 2013). The third species included in this study, C. carswelli, has the narrowest geographic range because it is endemic to the Bético systems of northeastern Andalusia and Murcia. Cupido carswelli is considered as a species by some authors (Kudrna, 2002; Gil–T., 1998, 2003, 2006, 2008) but as a subspecies of C. minimus by other authors such as García–Barros et al. (2013). In this paper we consider C. carswelli as a species, in agreement with Kudrna (2002), Gil–T. (2003, 2006), Cuvelier & Tarrier (2002), Obregón (2011), and studies of DNA barcoding (COI) (Dincă et al., 2015). Cupido carswelli is listed as vulnerable in the Andalusian region according to the Red Book of the Invertebrates of Andalusia (Gil–T., 2008). This level of protection is not extended to the national level due to its consideration by some authors (García–Barros et al., 2013) as a subspecies of the widely distributed in Europe C. minimus. Climate change is a matter of record and its effects on the distribution of organisms and particularly butterflies have already been demonstrated (Parmesan & Yohe, 2003; Gutiérrez–Illán et al., 2010). According to the models of the IPCC (2014), rises in temperature will affect the dynamics of rainfall and, as a direct consequence, affect the spatial distribution of ecosystems and their functioning (De Groot et al., 2009). Climate change will affect all species, but especially those with very limited dispersal ability (Hoyle & James, 2005). The genus Cupido, like many other species of Lycaenid, is one such species. Several studies on the effects of global warming on butterflies predict shifts to areas of higher latitude and/or altitude (De Groot et al., 2009; Gutiérrez–Illán et al., 2010). However, the latitudinal displacement of butterflies found at medium and high altitude could be prevented by the presence of barriers —such as vast agricultural areas at low altitude that would be impassable for species of low mobility— and a lack of equivalent displacement of their host plants (Romo et al., 2014). This work aims to provide a predictive view of how the distribution of these three rare Lycaenids in Andalusia could change under a climate change scenario. Material and methods Maps of the current distribution in Andalusia Andalusia (southern Spain) covers an area of 87,000 km2. It includes the continuous mountain range of Sierra Morena to the north and the discontinuous

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system formed by the Béticas ranges (Subbética and Penibética mountains) in the south, separated by the extensive fluvial valley of the river Guadalquivir. The transformation of the landscape for agricultural uses over centuries has eliminated many species of fauna that depended on the natural vegetation. In some cases, such species have been reduced to small, fragmented populations within the agricultural matrix or confined to mountainous areas with a very thin soil cover. In addition, certain species of central European distribution maintain local populations in some areas of the Andalusian mountains (the southernmost limit of their distribution) where they find microclimates and conditions appropriate for their persistence, as in the case of C. osiris. Our analysis of the current distribution of these three species is based on chorological information published in the form of articles and short notes in scientific journals (Gil–T., 1998, 2002, 2003, 2006, 2008; Lara Ruiz, 2009; Obregón, 2011) and in atlases (García–Barros et al., 2004; Moreno–Benítez, 2015), on records available in different museums and institutions, on online databases (GBIF, 2013), and on data from specimens in the collections of the authors and Felipe Gil–T. In addition, given that Andalusia has areas that have been subjected to little or no prospection, between 2004 and 2015 a series of field surveys were carried out to confirm the presence of these three species at previously–surveyed sites and to locate new populations in Andalusia. The presence data collected by these two means, initially with a resolution of 1 x 1 km, were processed with ArcGIS 10.2 (ESRI, 2010) to map the distribution of the three species in UTM projection with a resolution of 10 x 10 km, to safeguard, as far as possible, the local populations. Ecology of the species studied Cupido lorquinii is a univoltine species (March to June) that can have a partial second generation in some years (Gil–T., 2002). Its presence is strongly conditioned by the presence of its host plant Anthyllis vulneraria. Cupido osiris is a univoltine Lycaenid (May–June) that has a a close relationship with its host plants of the genus Onobrychis (Munguira et al., 1997; Settele et al., 2008). Cupido carswelli is a univoltine Lycaenid (April and May) distributed in colonies very localized in habitats preferably located in ravines and forest clearings where A. vulneraria grows (Gil–T., 2008; Obregón, 2011). For all three species of Cupido, the diapause may last over 300 days and includes both summer and winter. It is, therefore, the most vulnerable stage because of the risks of dehydration, freezing, and attack by parasitoids, predators, or diseases. Current potential distribution To produce the potential distribution models, we used Maxent v. 3.3.3 (Phillips et al., 2006; Elith et al., 2011). In a defined geographic area, Maxent uses data for the presence of the species (the localities where it has been recorded) as the dependent variable and a set

Obregón et al.

of environmental variables: bioclimatic, topographic, and lithological, and also in our case, the probability of the presence of host plants, as predictors (Anderson et al., 2003). The presence data used in the models are georeferenced in UTM squares of 1 km2. Table 1 shows the details of the environmental variables used as predictors. Climatic variables (resolution: 1 km2) extracted from the national data bases of the AEMET (Spanish Meteorological Agency) and topographic altitude variables extracted from a digital model of terrain (250 m resolution) were included in the model. The species of Cupido studied appears to form local colonies associated with stands of their host plants. We therefore considered the presence of these plants should be included as an additional predictor. For this purpose, we modeled the current potential distribution of Anthyllis vulneraria and of the genus Onobrychis in Andalusia using data collected from the GBIF and our own data recorded in surveys relating to the following taxa: (1) A. vulneraria, including the subspecies reuteri, maura, gandogeri, microcephala, and arundana, but not pseudoarundana – a strict acidophile growing on shale soils in Sierra Nevada (Granada); (2) in the case of the genus Onobrychis, the distribution in Andalusia was modeled for the following species: O. caput–galli, O. argentea, O. humilis, O. saxatilis, O. spartaea, O. stenorhiza, and O. viciifolia together. The variables used for the modeling of host plants were annual average temperature, annual precipitation, and pH in the first 30 centimeters of soil (Harmonized World Soil Database; FAO, 2009). The soil pH on a 5 x 5 km scale was extrapolated to a cell size of 1 km2 using ArcGis. The resulting predicted distributions were subsequently used as independent variables (table 1) in the models of the current potential distribution of the three species of butterfly. For the modeling, Maxent used a number of presences for 'training' and others for the test. For C. carswelli: six for training and one for the test; C. lorquinii (65 and 8); C. osiris (8 and 1); the host plants Onobrychis (195 and 22) and A. vulneraria (661 and 74). To avoid problems of co–linearity, non–parametric correlation analysis (Spearman r) was used to detect and eliminate environmental variables that were highly correlated with each other (r ≥ 0.80) and therefore redundant (Elith et al., 2006, 2011; Merrow et al., 2013). Also discounted were variables whose contribution to the model was negligible. Thus, the number of predictor variables included in the models was reduced, thereby avoiding 'overfitting' (Kramer– Schadt et al., 2013; Fernández et al., 2015). The models were replicated 10 times for each species. To assess the predictive ability of the model, we used the AUC (area under the receiver–operator curve) and the sensitivity (proportion of presences predicted correctly) and specificity (proportion of absences predicted correctly) (Pearce & Ferrier, 2000; Romo et al., 2013; Merrow et al., 2013; Obregón et al., 2014, in press; Fernández et al., 2015). An AUC value greater than 0.8 is considered to indicate a model with sufficient accuracy and reliability (Newbold et al., 2009).

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Table 1. Environmental and ecological variables analyzed, references and units. Tabla 1. Variables ambientales y ecológicas analizadas, referencias y unidades.

Abbreviation

Source/Reference

Units

Environmental variables Mean temperature in warmest quarter

TWQ

AEMET

ºC

Precipitation in warmest quarter

PWQ

AEMET

Precipitation in coldest quarter

PCQ

AEMET

Altitude

ALT

Digital Elevation Model (DEM)

Occurrence probability of A. vulneraria

AVU

GBIF + unpublished own data

0–1

Occurrence probability of Onobrychis

ONO

GBIF + unpublished own data

0–1

Ecological variable

Distribution in a climate change scenario To investigate the possible effects of climate change on the distribution of the three species of Cupido, and given the high dependence of the three species of butterflies on their host plants, we constructed two separate models of the distribution of the host plants. We used the variables annual average temperature and annual precipitation, employing the values expected in a hypothetical scenario of climate change for Andalusia, as predicted by the IPCC (IPCC, 2014; scenario A2a), with a spatial resolution of 1 km2. The IPCC (2014) estimates an increase in temperature of 0.2°C for each period of 10 years, with a maximum increase of 1.5–4.5ºC by the end of the 21st century. The continuous logistical outputs of the Maxent models were converted into binary outputs according to the ETSS (Equal Training Sensitivity and Specificity) threshold, to represent the loss of potential habitat with respect to the model of current distribution. In the bitmap, the 1 km2 squares with a probability below the ETSS threshold will have a value of 0 while those equal to or above the threshold will have a value of 1. Each model has a different ETSS threshold value. Results Map of the current distribution in Andalusia The data published on the distribution of these three species of butterflies showed their presence in a total of 78 UTM squares of 100 km2 (C. lorquinii = 65, C. osiris = 5, C. carswelli = 6). The data from new locations collected during 10 years of fieldwork provided a total of 33 new squares (C. lorquinii = 30, C. osiris = 2, C. carswelli = 1) in which their presence was recorded, representing an increase of 42.3%. Figure 1 shows the locations where the presence of each of the species was confirmed.

In the distribution of the known locations of C. osiris according to precipitation and annual average temperature, two locations were clear 'outliers' (red circles); these corresponded to the sites in the province of Cadiz cited by Ocete et al. (1985a, 1985b), which we consider erroneous identifications. In terms of potential niche, the optimum annual average temperature and annual precipitation for C. osiris and C. carswelli were very similar, with C. lorquinii being the most eurioic of the three species (fig. 2). Because of the high specificity of the three species in terms of their use of host plants, we also updated the distribution in Andalusia of A. vulneraria (all subspecies together) and seven species of the genus Onobrychis (O. caput–galli, O. argentea, O. humilis, O. saxatilis, O. stenorhiza, and O. viciifolia). Figure 3 shows the known distribution maps of the species of the genus Onobrychis and of A. vulneraria, as well as the distribution of the host plants in Andalusia according to the model. Models of the current potential distribution and under a future scenario of climate change The logistical analysis with Maxent showed the contribution of the variables and the results of the AUC, sensitivity, and specificity tests to evaluate the models of the current potential distribution and future potential distribution (table 2). As can be seen, the three species are closely dependent on the distribution of their host plants, and on the precipitation of the coldest or warmest quarters of the year. Figure 1 shows the logistical outputs of the maps of the current potential distribution of the species. Figure 4 shows the response curves of the two variables with the greatest weight in the respective models of the current distribution (excluding host plant variables), in relation to the probability of occurrence of the species. The most stenoic species were C. osiris and C. carswelli, which showed similar responses to

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C. lorquinii

110

220 km

C. osiris

110

C. carswelli

110

220 km

C. osiris

220 km

C. lorquinii

110

C. carswelli

220 km

110

220 km

110

220 km

Fig. 1. Distribution map and current distribution model of species of the genus Cupido in Andalusia (southern Spain). Distribution maps: new UTM squares are in blue and squares obtained from the bibliography are in red (UTM 10 km). Distribution model: from green to red: low probability (LP) to high probability (HP) of occurrence (resolution of the squares: 1 km2). Fig. 1. Mapa de distribución y actual modelo de distribución de las especies del género Cupido en Andalucía (sur de España). Mapas de distribución: en azul se muestran las nuevas cuadrículas UTM y en rojo, las bibliográficas (UTM 10 km). Modelo de distribución: de verde a rojo: de menor probabilidad (LP) a mayor probabilidad (HP) de presencia (resolución de cuadrícula: 1 km2).

the variables PWQ and PCQ. The probability of presence increased with the precipitation accumulated in the warmest quarter and with decreasing precipitation in the coldest quarter —that, being mid–mountain areas, is usually in the form of snow. For C. lorquinii, an Ibero–North African species with greater environmental tolerance and more habitats in Andalusia, the probability of its presence rose with increasing ALT. In contrast, with decreasing TWQ, the probability of occurrence of C. lorquinii decreased significantly. A comparative analysis of the model predictions of the current potential distribution and future potential distribution highlights significant differences, regarding the increase or decrease in potential habitat in the future climate change scenario (fig. 5). Resultant maps show a decrease in potential habitat in a global change scenario for the three Cupido species (blue). This loss is remarkable in the most restricted distribution in Andalusia: C. osiris and C. carswelli. Table 3 shows the number of 1 km2 squares considered by the model as optimal habitat (p ≥ ETSS

threshold) under current conditions and those predicted for the future climate change scenario according to the IPCC (2014), thus providing an estimate of the hypothetical loss of habitat that the latter would cause. Discussion Assessment of the status of populations of animals and plants is essential to prioritize the conservation of species and the habitats on which they depend, and is therefore crucial in the current biodiversity crisis. To carry out such assessment, key elements are a sufficiently detailed knowledge of their geographical distribution and, if necessary, the prediction of changes that may occur over time (Bartel & Sexton, 2009). Unfortunately, despite the efforts being made, substantial knowledge gaps in this field are impractical to solve by conducting systematic inventories due to constraints concerning time and resources (financial, human, logistic). For these reasons, species distribution

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Annual precipitation (mm)

1,400

C. carswelli C. osiris C. lorquinii

1,200 1,000 800 600 400 200 0

8 10 12 14 16 18 Annual mean temperature (ºC)

Fig. 2. Average annual temperature and rainfall recorded in the localities where Cupido species are present in Andalusia. C. lorquinii has a higher tolerance to both parameters than the other two species. The sites marked with a red circle (C. osiris) correspond to citations in the province of Cadiz that we consider erroneous (spatial resolution: 1 km2). Fig. 2. Temperatura media anual y precipitación anual registradas en las localidades en las que las especies del género Cupido están presentes en Andalucía. C. lorquinii tiene una mayor tolerancia a ambos parámetros que las otras dos especies. Las localidades marcadas con un círculo rojo (C. osiris) corresponden a citas bibliográficas de la provincia de Cádiz que consideramos erróneas (resolución espacial: 1 km2).

models are becoming more and more useful (Heikkinen et al., 2007a; Gutiérrez–Illán et al., 2010). As a result of our intensive field work over 10 consecutive years (2004–2014) and using unpublished data provided by other Andalusian entomologists we have significantly increased the number of known loca-

tions of the genus Cupido in Andalusia. Specifically, the number of 10 km2 UTM squares occupied has been augmented by 30 for C. lorquinii (46%), by two for C. osiris (40%), and by one for C. carswelli (17%). When combined, this represents an increase of 42% in the number of grids occupied by these species.

Anthyllis

110

220 km

110

Onobrychis

220 km

110

220 km

110

220 km

Fig. 3. Distribution map and current distribution model of Anthyllis vulneraria and species of the genus Onobrychis. Fig. 3. Mapa de distribución y actual modelo de distribución de Anthyllis vulneraria y las especies del género Onobrychis.

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Table 2. Predictive variable contributions (%) analyzed in the current and future distribution models, AUC, Sensitivity and Specificity tests, and equal training sensitivity and specificity (ETSS) threshold: Clr. C. lorquinii; Ccr. C. carswelli; Cos. C. osiris. Tabla 2. Contribución (%) de las variables predictoras analizadas en los modelos de distribución actual y futuro, AUC, pruebas de sensibilidad y especificidad y umbral de igualdad de sensibilidad y especificidad en la calibración (ETSS en su sigla en inglés). (Para las abreviaturas, véase arriba.)

Current model

Future model

Environmental variable

Clr

Ccr

Cos

Clr

Ccr

Cos

Mean temperature in warmest quarter

2.9

10.0

2.1

82.1

0.6

Precipitation in warmest quarter

2.1

21.2

4.4

1.5

53.2

74.8

Precipitation in coldest quarter

2.1

10.2

2.3

16.5

46.2

25.2

Altitude

4.8

–

91.2

–

Occurrence probability of A. vulneraria Occurrence probability of Onobrychis

88.1

58.6

–

ETSS threshold

0.351

0.484

0.357

0.509

0.614

0.459

AUC–scores

0.888

0.976

0.908

0.798

0.917

0.980

Sensitivity test

0.911

0.832

0.939

0.921

0.896

0.871

Specificity test

0.038

0.109

0.201

0.021

0.111

0.098

The three species of Cupido are distributed non– uniformly over Andalusia, as shown on the updated distribution maps, with a preference for mountainous areas of the Béticas ranges (the Subbéticos and Penibéticos Systems). The current distribution of the three species and their host plants in Andalusia is conditioned by previous sheltering from glaciers and the glacial–interglacial climatic variation. It is also largely a reflection of the landscape fragmentation that has occurred for centuries due to intensification of agriculture. Today, the distribution of these Lycaenid species is restricted to mountainous areas with steep slopes, where farming is not viable. The dominance of calcareous soils in these mountains determines the probability of the presence of the host plants on which these species depend. In addition, significant differences in rainfall and temperature between the mountainous areas occupied by butterflies and the coastal areas, river valleys, and plains make these areas optimal locations for these Lycaenids. Based on these findings and on prior knowledge of the ecological requirements of these butterflies, we developed predictive models of their distribution and analyzed the contributions to the models of the variables used as predictors. The ecological niche and distribution models are the initial step in the ecological study of a species (Khanum et al., 2013). They constitute an efficient tool that is widely used to gain insight into the set of conditions most suitable for the presence of the species tested, and hence indicate the locations where the probability of occurrence of the species is highest (Guisan & Zimmer-

mann, 2000; Khanum et al., 2013). These models are valuable for planning and implementing conservation action and management. However, they often include only bio–climatic and, in some cases, topographical variables (Guisan et al., 1999; Gutiérrez–Illán et al., 2010), although anthropic factors —such as the types and intensity of land use (livestock, agriculture, urban development, reforestation, fire,...)— can significantly affect the distribution of species (Obregón et al., 2014; Bubová et al., 2015). These variables are difficult to quantify, so the models generated are credible only for those habitats where there is no significant, negative human disturbance. In our case, the robustness of the models was increased by the incorporation, as a predictor, of the distribution of host plants —a key component of the habitat of these butterflies which, in turn, responds to the effects of the anthropic factors mentioned above. Nevertheless, distribution models tend to overestimate the potential distribution areas, not taking into account other essential ecological interactions, including mutualism, competition, parasitism, etc. (Heikkinen et al., 2007b). In myrmecophilous lycaenid species, the presence of mutualistic ants is also of great importance, especially in obligate interactions (Filz & Schmitt, 2015). In our models, the most important variables that had most weight were the presence of host plants, together with altitude and climatic variables: seasonal rainfall and temperature during the summer. The presence of their host plants, which show optimum growth in soils of pH 6.5–7.8, also conditions the occurrence of Cupido species. This ecological variable makes a strong contribution to the models: up to 91.2% for

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Logistic output (occurrence probability)

C. lorquinii 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0

-250 0 250 500 750 1000 1250 1500 1750 ALT

20 22 TWQ

C. osiris 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0 20 40 60 80 100 120 140 160 180 200 PWQ

100

150

200

250 PCQ

300

350

400 450

100

150

200

250 PCQ

300

350

400 450

C. carswelli 1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1

0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0 20 40 60 80 100 120 140 160 180 200 PWQ

Fig. 4. Response curves (current model) showing the relationships between the probability of the presence of a species and the two top predictors (excluding the host–plant variable), for C. lorquinii, C. osiris and C. carswelli. Values shown are the averages of 10 replicate runs; blue margins show the standard deviation (SD) for 10 replicates: ALT. Altitude; TWQ. Temperature of the warmest quarter; PWQ. Precipitation of the warmest quarter; PCQ. Precipitation of the coldest quarter. Fig. 4. Curvas de respuesta (modelo actual) que muestran la relación entre la probabilidad de presencia de una especie y las dos variables predictoras que más contribuyen al modelo (con exclusión de la variable de planta nutricia) de C. lorquinii, C. osiris y C. carswelli. Los valores mostrados representan la media de las 10 réplicas del modelo; los márgenes en azul reflejan la desviación estándar (DE) de las 10 réplicas: Alt. Altitud; TWQ. Temperatura del trimestre más cálido; PWQ. Precipitación del trimestre más cálido; PCQ. Precipitación del trimestre más frío.

C. osiris. For C. carswelli, the contribution of this variable is lower (58.6%), while climatic variables, such as precipitation in summer, are more important. Regarding the remaining variables, the precipitation during the summer or winter, when the preimaginal phases of Cupido are in diapause, may modify the survival of caterpillars. Altitude, as a variable, made

no contribution to the models for the more stenoic species of Cupido (C. osiris and C. carswelli), while it was the variable with the second–greatest weight in the C. lorquinii model —a result of the broad altitudinal range of the localities where the presence of this species has been confirmed (7–1,885 m; mean = 923.8; SD = 486.9).

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Current model C. lorquinii

110

220 km

Future model

110

C. osiris

110

220 km

110

C. carswelli

110

220 km

110

220 km

Unsuitable Loss Gain Suitable

Fig. 5. Modeled current (suitable and unsuitable) and future (suitable, lost, gained and unsuitable) distribution for Cupido species. Current predictions are shown as a binarian map (red ≥ equal training sensitivity and specificity threshold). Future predictions are based on an A2a emission scenario for 2050. Fig. 5. Modelo de la distribución actual (óptimo y subóptimo) y futura (óptimo, pérdida de hábitat, ganancia de hábitat y subóptimo) de las especies del género Cupido. Las predicciones actuales se muestran en un mapa binario (color rojo ≥ umbral de igualdad de sensibilidad y especificidad en la calibración). Las predicciones futuras se basan en un escenario de cambio climático A2a para 2050.

Using Maxent, we also modeled, the potential future distribution of the three species under the climate change scenario A2a (IPCC, 2014). In the model for C. lorquinii, the mean temperature of the warmest quarter was the variable with most weight. However, C. carswelli and C. osiris responded in a similar way to seasonal rainfall. In a climate scenario where the temperature increase at the end of the present century would range between 1.5 and 4.5°C (IPCC, 2014) and where the dynamics of rainfall would be affected, the models show a potential loss of habitat of up to 88.1% for C. osiris. In this future scenario, the areas with environmental features similar to those of the areas that the species inhabit currently would probably be found at higher altitudes, as has been observed with other species of similar mountain ranges (Gutiérrez– Illán et al., 2010 ), and at more northern latitudes. In the case of C. osiris, habitat loss in Andalusia is easily interpretable because this species is widespread in Central Europe and because Andalusia

represents the southernmost limit of its distribution (García–Barros et al., 2013). Within the northern Iberian peninsula, this species is mainly concentrated in mountainous areas with more xerophilous conditions in the northern third (the Cantabrian and Iberian mountains and the Pre–Pyrenees). That is why C. osiris populations in Andalusia are confined to mountain ranges with wet microclimates and mean summer maximum temperatures below 28°C, such as the La Sagra, Cazorla, Segura, and Orce Guillimona ranges. If we extended the predictive model to the whole of the Iberian peninsula, the trend of the loss of habitat with optimal conditions would be even more marked (our own data). In the Climatic Risk Atlas of European Butterflies (Settele et al., 2008), the predictions at the European level for C. osiris are for a loss of up to 95% of its potential habitat, which is why it has been included in the category HHHR (extremely high risk climate change). The C. carswelli model shows that its current endemic distribution, restricted to the NE

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Table 3. UTM squares (1 km2) with a probability of occurrence higher than the equal training sensitivity and specificity (ETSS) threshold, with respect to the total number of squares in Andalusia in the current and future models. Tabla 3. Cuadrículas UTM (1 km2) con probabilidad de presencia superior al umbral de igualdad de sensibilidad y especificidad en la calibración (ETSS en su sigla en inglés), respecto al total de cuadrículas de Andalucía para los modelos actual y futuro.

UTM squares (1 km2)

C. lorquinii

C. osiris

C. carswelli

Probability > ETSS (future model)

10,902 (11.8%)

498 (0.5%)

649 (0.7%)

Probability > ETSS (current model)

28,338 (30.7%)

3,953 (4.2%)

4,696 (5.0%)

Percentage of change (end of the XXI century)

–61.6%

–88.1%

–86.0%

∑ (total squares)

92,174

of Andalusia and Murcia, is a result of the probable extinction of the taxon in nearby mountains, although it is still possible to find it in similar enclaves near to the known populations. However, its restricted distribution and the barcoding data (Dincă et al., 2015) suggest a recent speciation process, starting from C. lorquinii. At present, no sympatric populations of C. lorquinii and C. carswelli have been detected, the Euclidean distance between their closest populations being 53 km. Alternatively, the intermediate morphology of their imagos and preimaginal stages suggests a hybrid between C. mininus and C. lorquinii as the possible origin of C. carswelli. This prediction, of a drastic reduction in terms of potential habitat, is of particular concern for C. carswelli because it is the most vulnerable of these three species since it is endemic to the southeast of the Iberian peninsula. In contrast, C. lorquinii is an Ibero–Maghreb species with a high environmental and ecological tolerance (Gil–T., 2002). This breadth of environmental niche is reflected in the results of the future model for Andalusia, its habitat loss (61.6%) being significantly lower than those of the other two species of Cupido. In addition, the decline in butterfly species may be related strongly to the loss of potential habitat for their host plants, on which they depend closely. Currently, the possibility that these three species could expand their distribution is very limited due to the ongoing loss of natural habitats with optimal conditions. Fragmentation and management in the Andalusian mountain ranges and their surroundings inhibit the establishment of new populations, as for species of the genus Pseudophilotes (Obregón et al., 2014). This can be extrapolated to the sparse populations of C. lorquinii, which are isolated in mountains in the north of Huelva province, where the intense agrosilvopastoral management could accelerate their decline. The maps and distribution models generated in this study should be used in the development of

management and conservation plans for both the species concerned and their habitat; otherwise, their numbers could decrease and even disappear. This is the case for the Betic endemism C. carswelli and the relict populations of C. osiris from glacial refuges, for which stochastic phenomena, such as fires or changing land use in their ranges, could have irreversible consequences. According to the results generated by the future distribution models, we consider it necessary to extend the regional protection of C. carswelli to the European level. In the case of C. osiris, its scarce populations in Andalusia and their high vulnerability require a plan of conservation and protection at the regional level to safeguard the last relict populations in southern Europe. Acknowledgments The authors thank Felipe Gil–T. (Granada) for generously providing occurrence data, Javier López–Tirado (Univ. Huelva), Salvador Arenas (Univ. Córdoba) and Pilar Fernández (Univ. Córdoba) for their valuable comments on an earlier version of the manuscript, and Roger Vila and Vlad Dincă (Instituto de Biología Evolutiva; CSIC–Universitat Pompeu–Fabra, Barcelona) for their helpful comments concerning DNA bar–coding. We also wish to express our gratitude to the Editor and two anonymous reviewers for their valuable comments and suggestions to improve this paper. References Anderson, R. P., Lew, D., & Peterson, A. T., 2003. Evaluating predictive models of species’ distributions: criteria for selecting optimal models. Ecological Modelling, 162(3): 211–232. Asher, J., Warren, M., Fox, R., Harding, P., Jeffcoat, G. & Jeffcoat, S., 2001. The Millennium Atlas of

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Comparing prey composition and prey size delivered to nestlings by great tit, Parus major, and blue tit, Cyanistes caeruleus, in a Mediterranean sclerophyllous mixed forest H. Navalpotro, E. Pagani–Núñez, S. Hernández–Gómez & J. C. Senar Navalpotro, H., Pagani–Núñez, E., Hernández–Gómez, S. & Senar, J. C., 2016. Comparing prey composition and prey size delivered to nestlings by great tit, Parus major, and blue tit, Cyanistes caeruleus, in a Mediterranean sclerophyllous mixed forest. Animal Biodiversity and Conservation, 39.1: 129–139. Abstract Comparing prey composition and prey size delivered to nestlings by great tit, Parus major, and blue tit, Cyanistes caeruleus, in a Mediterranean sclerophyllous mixed forest.— Resource partitioning is a central issue in ecology be� cause it can establish to which point similar species can coexist in the same habitat. Great tits and blue tits have been classical model species in studies of trophic competence. However, most studies on the topic have been conducted at localities where caterpillars are by far the most relevant prey brought to the nestlings. In Mediterranean mixed forests, nevertheless, the abundance of caterpillars is relatively low and it is spiders that play a key role in the diet of great tits, at least for nestlings. The aim of this paper was to study nest food provisioning to establish the degree of diet overlap of these two tit species in a Mediterranean forest. Our results showed that blue tit feeding rates were higher than those of great tits, probably to compensate for the smaller prey delivered to nestlings by blue tits. Blue tits brought more spiders than great tits, while grey tits brought larger prey and more caterpillars. This may be because larger great tits can prey upon larger prey items than blue tits. As a main result, this study supports the view of resource partitioning by great and blue tits in sclerophyllous Mediterranean forest ecosystem. Key words: Parus major, Cyanistes caeruleus, Diet composition, Prey size, Spiders, Mediterranean Resumen Comparación de la composición y el tamaño de las presas que el carbonero común, Parus major, y el herrerillo común, Cyanistes caeruleus, aportan a sus pollos en un bosque mediterráneo mixto esclerófilo.— La división de los recursos es un aspecto esencial en ecología porque puede determinar hasta qué punto pueden coexistir especies parecidas en un mismo hábitat. El carbonero común y el herrerillo común son especies que se utilizan tradicionalmente como modelo en los estudios sobre competencia trófica. No obstante, la mayoría de los estudios sobre este tema se han llevado a cabo en localidades en las que las orugas son, con diferencia, la presa que más se aporta a los pollos. Sin embargo, en los bosques mixtos mediterráneos la abundancia de orugas es relativamente escasa y son las arañas el elemento fundamental de la alimentación del carbonero común, al menos para los pollos. El objetivo del presente artículo es es� tudiar el aporte de alimentos al nido para establecer el grado de solapamiento de la dieta entre estas dos especies de paros en un bosque mediterráneo. Nuestros resultados mostraron que la tasa de alimentación del herrerillo común es superior a la del carbonero común, probablemente para compensar el hecho de que las presas que el herrerillo lleva a los pollos son de menor tamaño. El herrerillo común aportó más arañas que el carbonero, pese a que el carbonero gris llevó presas de mayor tamaño y más cantidad de orugas. Ello se debe a que el carbonero común puede cazar presas más grandes que el herrerillo. El principal resultado de este estudio respalda la hipótesis de la división de recursos entre el carbonero común y el herrerillo común en un ecosistema forestal mediterráneo esclerófilo. Palabras clave: Parus major, Cyanistes caeruleus, Composición alimentaria, Tamaño de presa, Arañas, Mediterráneo Received: 11 XI 15; Conditional acceptance: 8 I 16; Final acceptance: 15 III 16 H. Navalpotro, E. Pagani–Núñez, S. Hernández–Gómez & J. C. Senar, Evolutionary Ecology Unit, Natural Sciences Museum of Barcelona, Psg. Picasso s/n., 08003 Barcelona, Spain.– E. Pagani–Núñez, Behavioral and Community Ecology, Conservation Biology Group, College of Forestry, Guangxi Univ., 100 Daxue Road, Nanning 530005, Guangxi, People’s Republic of China. Corresponding author: J. C. Senar. E–mail: jcsenar@bcn.cat ISSN: 1578–665 X eISSN: 2014–928 X

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Introduction Competition is an interaction between species or populations for the same limited resource, such as space, food, or nest sites. This interaction reduces fitness of both parts (Dhondt, 2012). Studies about competition are necessary to understand the func� tion of ecosystems (Stenseth et al., 2015). One of the main sources of competition is food because it is a major factor in determining reproductive success and individual survival (Nour et al., 1998). In such a competitive scenario, related species coexisting in the same habitat may shift their prey types (or prey size) to avoid competition (Dhondt, 1989). Species of the family Paridae have been widely used as models to evaluate interspecific competi� tion (Dhondt, 2012; Atiénzar et al., 2013). Two of the most commonly studied species are great tits, Parus major L. and blue tits, Cyanistes caeruleus L. These two insectivorous passerines mainly share the same habitat everywhere in Europe (Perrins, 1979). Early studies on the topic examined the diet of tits in depth and compared it between different species during the breeding season (Gibb & Betts, 1963; Török, 1986) and in winter (Betts, 1955). Conclusions were limited, however, because the sample size was small and the observation time was short (García–Navas et al., 2013). More recently, García–Navas et al. (2013) concluded that great tits brought a higher proportion of caterpillars than blue tits, while blue tits brought a higher proportion of spiders than great tits. They also found that great tits and blue tits differed in their preference for specific caterpillar species (see also Török & Tóth, 1999). Prey size also appears to be an important factor in food niche differentiation (Török, 1986; Nour et al., 1998; Massa et al., 2004), with blue tits eating smaller caterpillars than great tits. According to Dhondt (1977), this consumption of smaller caterpillars would reduce the future availability of larger caterpillars for the great tit (see however García–Navas et al., 2013). These findings indicate interspecific competition for food between these two species. Supporting this view, it has been observed that when blue tits were removed from the breeding area, the nestling weight of great tits increased (Minot, 1981; Török & Tóth, 1999). Most studies on the topic to date, however, have been conducted in deciduous forests, where caterpillars are the main food resource (see, however, Massa et al., 2004). The abundance of caterpillars and other insects varies considerable between habitats, across seasons, and between years (Bańbura et al., 1999; Tremblay et al.,�� 2003, 2005; Arnold�� et al.,�� 2010)�� . Because caterpil� lars are superabundant in central Europe, all studies on diet from these areas mention this prey. However, it has been observed that 'suboptimal habitats' have a relatively low proportion of caterpillars. This is the case of coniferous forests (Gibb & Betts, 1963; van Balen, 1973), suburban gardens (Cowie & Hinsley, 1988), orange groves (Barba & Gil–Delgado, 1990) and sclerophyllous forests (Blondel et al., 1991; Bańbura et al., 1994). Mediterranean sclerophyllous habitats are especially relevant due to their relatively high diver�

sity of arthropods and the limited abundance of prey compared to deciduous forests (Blondel et al., 1991; García–Navas & Sanz, 2010). This compels species living in this habitat, where the proportion of caterpillars is lower and the proportion of spiders is higher than in deciduous forest, to feed on a greater variety of food (Pagani–Núñez et al., 2011). Indeed, recent research has highlighted the importance of spiders for nestling development (Török & Tóth, 1999; Ramsay & Houston, 2003; García–Navas et al., 2013; Pagani–Núñez & Senar, 2014), reflecting their suitability as alternative prey to caterpillars. Studies about food competition in sclerophyllous habitats are therefore needed to understand, in a broader sense, the degree of diet overlap of these two species (Cholewa & Wesolowski, 2011). The main aim of the present study was to determine whether blue tit and great tit use the same food resources, or whether there is a difference in composition of size of prey that allows them to coexist in this habitat. We compared the food composition of nestling diet of great tits and blue tits in a Mediterranean predominant sclerophyllous mixed forest using video trapping. A secondary aim of this paper was to analyse whether spiders are an important food resource for the blue tit in sclerophyllous forests, as previously found for great tit (Pagani–Núñez et al., 2011). Material and methods Area of study We carried out fieldwork during the breeding season in 2012 by filming the parental investment of great tit (GT) and blue tit (BT), two hole–nester passerines. The study area was a Mediterranean forest located in the field station of 'Can Catà', within the Parc Natural de Collserola (Cerdanyola, Barcelona, NE of the Iberian Peninsula, 45º 27' N, 2º 8' E). The area is composed of sclerophyllous forest dominated by holm oaks, Quercus ilex, 67% and, to a lesser extent, oaks, Quercus cerrioides, 17% and aleppo pines, Pinus halepensis, 16% at the bottom of the valley, with a highly developed understory. Aleppo pine was the predominant species on most of the hills (54%), surrounded by shrubs and the recruitment of oak species (holm oaks: 31%, oaks: 14%). The proportion of oaks, Quercus spp., in relation to pines ranged from 5 to 95% and correlated negatively with the altitude above sea level. We used altitude and the percentage of Quercus spp. in relation to aleppo pines (Pagani–Núñez et al., 2014b) as the most simple but most accurate habitat variables to characterize the structure of the forest. Altitude ranged from 80 to 225 m above sea level (see Pagani–Núñez et al., 2011, 2014b for more information about this area and the method used). The 'Can Catà' field station had 182 nest boxes distributed throughout the area (80 ha). Nest boxes were located on the trunks of the trees at an approximate height of 1.30 m. The size of the nest boxes was 21 cm x 32 cm, with a cylindri� cal tube of 10 cm in length and 5 cm (in diameter)

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designed to protect the entrance from predators (such as mustelids). The diameter of the hole was designed for titmice (30 mm). Reproduction and diet recording Tit reproduction in 'Can Catà' occurred from the end of April to mid–June. Nest–boxes were revised twice a week to determine nest–building state, laying date, hatching date (considering day 0 as the hatching date) and brood size. We used differences in nest structure to determine the breeding species: blue tits used more feathers (normally grey and white) and lighter materials to build the nest, while great tit nests were darker and had more moss and fur. Moreover, great tit eggs were slightly larger. To obtain information about nestling diet and paren� tal provisioning effort, nest boxes from both species were recorded when chicks were around 11–12 days old (average 11.72, SD = 1.93 days after hatching), when food demand is highest (Perrins, 1991). A digital micro–camera (Mini Colour Sony IR Camera SK– C170IR) attached to the nest–box roof was located and focused on the entrance, so that delivered prey could be observed. These cameras had an infrared view and motion sensor and when movement was detected, the camera started filming until the action stopped. To minimize the possible effects produced by the in� stallation of the camera, two days before recording, a replica of the devices used with the camera (electric cables and a fake battery container) was installed (and camouflaged) to accustom the birds to this apparatus. The camera was installed and activated at midday and removed 24 h later. Normally, parents continued their usual behaviour after the cameras were placed. To avoid biases, however, we used only full clock hours from 7 a.m. to 2 p.m. from the second day. Once all boxes were recorded, the videos were analysed (n = 58). Sex of the parent, prey type, prey size and exact time were determined for each feeding action using Micro D Player software. To differentiate males from females, most great tits were captured us� ing funnel traps during the previous winter (Senar et al., 1997). Individuals were marked with a numbered PVC ring that was could be read in the recordings, allowing easier recognition of each individual. For birds with no ring, the shininess of the black cap was used, the male having a glossier crown. This sexual dichromatism is ac� centuated under infrared light conditions (Pagani–Núñez & Senar, 2014). Blue tits were also ringed during winter, using a white PVC ring for females, and a blue PVC ring for males. Females without a ring were caught at the nest box during the incubation period (on the 10th day) and were marked, allowed sexing in the recordings. The shininess of the blue cap and the width of the blue col� lar could also be used to differentiate sexes (personal observation). All adults were measured (body mass, wing–length, tarsus length, plumage colouration) and aged according to Svensson (1992). We classified prey into three categories: caterpil� lars, spiders, and others. The 'others' group included Coleoptera, Orthoptera, Phasmida, Diptera, fruits and other unidentified prey. For a more detailed descrip�

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tion of the most common prey at the generic level, see Pagani–Núñez et al. (2011). Although not all prey could be clearly identified, around 90% of the prey were categorized. Prey size was estimated in relation to the length of the bill of the great tit (which had the average of 9 mm) and according to a semi– quantitative scale: small (less than 9 mm), medium (9.1 mm–12 mm) and large (longer than 12.1 mm) (Pagani–Núñez et al., 2011; see also García–Navas & Sanz, 2010). We ringed nestlings of both species at 14–17 days old (around five days before fledging). Occupation rate in the study year was 29.3% and 11.0% (53 and 20 nests), for great tits and blue tits respectively. The fact that not all the nest boxes were occupied suggests that nest sites were not a limiting factor in this area. Statistical analyses We computed the absolute number of total feeding actions brought by each parent in every nest box. In most of the feeding actions, parents brought a single prey. Feeding rate (number of prey per hour) was used instead of total number of prey, because a few recordings had less than five hours due to a technical failure (battery). To approximate normality, all the proportions were arcsine–root transformed. The feeding rate was analysed using a general linear model (GLM), comparing differences between species. Each mentioned variable was included as the depend� ent variable, while sex and species were categorical factors. Percentage of Quercus tree species and date of recording were fitted as continuous variables to control for habitat and for phenology, respectively. Brood size was square root transformed and used as a covariate in the model. When the interaction between categorical variables, species and sex was statistically significant, a post–hoc planned comparison analysis was performed. All two–way interactions between spe� cies and covariates (date and percentage of Quercus spp.) were tested and removed manually from the analyses when no effect was detected. We also computed the proportion of different prey items brought by each parent in every nest box. Prey composition was also analysed through a general linear model (GLM), comparing differences between species in a similar way as for the analysis of feeding rates. Since Pagani–Núñez & Senar (2014)�� found sig� nificant effects of daily temperature and rainy weather on the proportion of different prey types delivered to the nest, these variables were also included in the analyses. However, no effect of rain and temperature was observed in our dependent variables, so these covariate variables were finally removed to simplify the analyses. Meteorological data was provided by the Observatori Fabra (Barcelona). Differences in diet between the two tit species could potentially be a by–product of differences in the use of the habitat or in reproduction time. We therefore first tested for differences between the two species in habitat structure around 25 m of the nest–boxes, measured as the percentage of Quercus in elation to Pinus, and for differences in the location of the nest

Navalpotro et al.

132

box along the altitudinal gradient of our study area (m a.s.l.). Additionally, we tested for differences in laying date measured as days from 1st April. When only one parent was present during the recording, we excluded such nests from the analyses (n = 5 for GT and n = 1 for BT). Thus, the final sample size was 32 GT and 16 BT. We conducted these analyses using STATISTICA 8.0 (StatSoft, 2007). Results Habitat structure and breeding phenology No differences were observed between blue and great tits in percentage of Quercus species around the nest box (GLM: F1, 52 = 0.09, p = 0.76) or in altitude of the location of the nest (GLM: F1, 52 = 1.02; p = 0.32). Laying date did not differ between the two species (GLM: F1, 52 = 1.20; p = 0.28). Feeding rates Blue tits brought more prey items per unit of time than great tits (fig. 1, table 1). The interaction between spe� cies and sex was significant (table 1), indicating that although no significant differences were observed in feeding rate between sexes in great tits, these diffe� rences were significant in blue tits, with males bringing more food per hour than females (fig. 1, table 1). Even though blue tits had larger broods (GT: 4.90 ± 0.22; BT: 5.62 ± 0.29; GLM: F1, 52 = 6.22, p = 0.016, number of nestlings the day of recording) which might explain their higher feeding rate, no correlation was found between the number of prey provided per hour and brood size (table 1). The feeding rate did not correlate with the date or with the percentage of Quercus trees surrounding the nest–boxes. Prey composition and size Caterpillars were the main prey provided to nestlings for both species (GT: 48% ± 0.03, BT: 40% ± 0.04). However, great tits brought a higher proportion of caterpillars than blue tits (fig. 2, table 2). The inte� raction between species and sex was significant, so that although blue tit females and males brought the same proportion of caterpillars to their nestlings, great tit males fed their nestlings with a higher proportion of this prey than females (fig. 2, table 2). Great tits brought larger caterpillars than blue tits (fig. 3, table 3), but no significant differences between sexes were obtained (table 3). The proportion of caterpillars provided by parents decreased across the season (fig. 4, table 2). Although the �� graphs showed a peak in the abundance of cat� erpillars in the middle of the season, no significant correlation was found when we tested the quadratic relation between caterpillars and date. Regarding �� en� vironmental variables, the proportion of caterpillars increased with the number of oaks surrounding the nest boxes (table 2).

Spiders were the second main prey brought to nest� lings by both species (GT: 0.15 ± 0.01, BT: 0.26 ± 0.02). Blue tits brought a significantly higher proportion of spiders than great tits (fig. 2, table 2). Females of both species brought a higher proportion of spiders than males (fig. 2, table 2). No interaction was found between sex and tit species in percentage of spiders, so that differences between sexes were consistent for the two bird species (table 2). Great tits brought bigger spiders than blue tits (fig. 3, table 3). No sex effect was detected (table 3). In relation to environmental variables, no correlation was found between proportion of spiders provided to nestlings and date or proportion of oaks surrounding the nest boxes. In addition to caterpillars and spiders, both great tits and blue tits brought a wide variety of insects and other food items to their nestlings (GT: 37% ± 0.02, BT: 34% ± 0.03), namely, butterflies, moths, grassho� ppers, spider egg bags, stick insects, and fruits. We observed no significant differences between blue tits and great tits or between sexes regarding these 'other' prey items (fig. 2, table 2). However, the percentage of other prey interacted with sex and species, so that female great tits and male blue tits brought a higher proportion of other prey items than great tit males and blue tit females respectively (table 2). Great tits brought larger items of this 'other' prey than blue tits, especially in relation to grasshoppers, moths and stick insects (fig. 3, table 3). The proportion of 'other' prey types increased across the season (table 2). Regarding total prey size, pooling all the prey items, great tits foraged on larger prey than blue tits. Males of both species tended to bring larger prey than females, but the difference was only marginally significant. The interaction between sex and species on total prey size was not significant (table 4). Total prey size significantly increased with brood size. Total prey size correlated negatively with total feeding rates. The number of prey per hour was therefore lower for parents that brought larger prey (fig. 5, table 4). Discussion Feeding rates Great tits and blue tits differed in their feeding rates. blue tits showed higher provisioning rates than great tits. Our results are in line with previous research carried out in British gardens and in a Belgium oak forest (Cowie & Hinsley, 1988; Nour et al., 1998). These differences in feeding rates could be due to the fact that blue tits have larger clutches than great tits (Cramp & Perrins, 1994). Experimental studies have shown that increasing the number of chicks in great tit nests increases feeding rates (García–Navas & Sanz, 2010; Pagani–Núñez et al., 2015). However, we did not find an effect of brood size on feeding rates in our study year in either species. Alternatively, the higher feeding rates of blue tits when compared to great tits could be due to the fact that prey brought by blue tits were smaller than those brought by great tits, so that blue tits would need to bring a higher proportions of

Animal Biodiversity and Conservation 39.1 (2016)

Number of prey/h

Female Male

Table 1. Results from the general linear model (GLM) comparing the feeding rates between great tit and blue tit, and between sexes. The model relates the variable to the proportion of oaks surrounding the nest (% Quercus spp.), the date of recording, and brood size: ß. Effect size.

20 18 16 14

Tabla 1. Resultados obtenidos con el modelo lineal general al comparar la tasa de alimentación entre el carbonero común y el herrerillo común y entre sexos. El modelo relaciona la variable con la proporción de robles y encinas cercanos al nido (% Quercus spp.), la fecha de observación y el tamaño de la nidada: ß. Magnitud del efecto.

12 10 8 6 4

133

Great tit

Blue tit

Fig. 1. Differences in number of prey per hour provided to nestlings between male and female great tit and blue tit during the breeding season in 2012 (see table 1). Fig. 1. Diferencias en el número de presas por hora entregadas a los pollos entre machos y hembras de carbonero común y de herrerillo común durante la temporada de cría de 2012 (véase la tabla 1).

smaller prey to compensate for the brood’s nutritional requirements. The negative correlation we found be� tween feeding rate and size of the prey supports this view (see also Grieco, 2001, 2002). Great tit males and females did not differ in the number of prey provided to nestlings per hour. This is consistent with previous work (García–Navas et al., 2013; Pagani–Núñez & Senar, 2014). However, we found that blue tit males brought more food to their chicks than females, which contrasts with data from Bańbura et al. (2001), who found the reverse. On the other hand, García–Navas et al. (2013) did not find any differences. This stresses that the provisioning rate between sexes may differ greatly from one habitat to another, although we do not yet know the reason for these differences. The number of visits per hour in this study was lower than the numbers found in other related studies (Cowie & Hinsley, 1988; Nour et al., 1998; García–Navas et al., 2013). That may be due to the brood size of central and northern European tit populations being larger than southern popula� tions (Cramp & Perrins, 1994). Larger–brood nests have a higher nutrition demand, requiring parents to provide more food per time unit (Naef–Daenzer & Keller, 1999; García–Navas & Sanz, 2010)�� . Addi� tionally, caterpillars are far more abundant in central and northern Europe during the breeding season (van Balen, 1973) than in southern mixed forests dominated by holm oaks, where prey abundance is

F1, 89

Species

–0.57

46.1

< 0.001

Sex

–0.22

7.1

0.01

Species*Sex

0.21

6.5

0.01

% Quercus spp.

–0.10

1.4

0.24

Date of recording –0.12

2.2

0.14

Brood size

0.1

0.72

0.03

in general lower (Blondel et al., 1991; Bańbura et al., 1994; Pagani–Núñez et al., 2014b). This higher abundance of readily available prey in central and northern forests is likely reflected in the higher feed� ing rates in these populations. Prey composition and size Regarding food composition, caterpillars were the main prey for both species (GT: 48.1%; BT: 40.1%). Spiders were the second prey for both species. In northern populations, the abundance of spiders does not exceed 10% of food composition, when nestlings are 10–12 days old (van Balen, 1973; Török, 1985; Cowie & Hinsley, 1988; Naef–Daenzer et al., 2000). The proportion of spiders we found (great tit: 14.8% and blue tit: 25.8% on average, reaching in some pairs 52.4% and 54.7%, respectively) was therefore higher than in other regions. However, we should point out that 2012 was not outstanding in numbers of this prey (great tits in the same area have been observed to consume 25–40% of spiders depending on the year; Pagani–Núñez et al., 2011; Pagani– Núñez & Senar, 2014), so that spider numbers could be even higher for blue tits. In any case, our results reflect the great variation between years (Bańbura et al., 1994) and habitats (van Balen, 1973; Blondel et al., 1991; Tremblay et al., 2005) regarding the consumption of spiders. More importantly, our data show that in sclerophyllous habitats, spiders are a very important food resource not only for great tits (Pagani–Núñez et al., 2011; Pagani–Núñez & Senar, 2014) but also for blue tits.

Navalpotro et al.

134

70%

Caterpillars Spiders Other prey

60%

% of prey

50% 40% 30% 20% 10% 0%

Female Male Great tit

Female Male Blue tit

Fig. 2. Mean percentage of caterpillars, spiders and other prey brought to nestlings by males and females, comparing great tit and blue tit species during the 2012 breeding season (see table 2). Fig. 2. Comparación entre el carbonero común y el herrerillo común del porcentaje medio de orugas, arañas y otras presas entregadas a los pollos por machos y hembras, durante la temporada de cría de 2012 (véase la tabla 2).

2013). Differences could not be due to differences between the two species in habitat use or breed� ing phenology. These differences have been partly explained by the greater diet breadth of great tits than that of blue tits (Török, 1985; García–Navas et al., 2013; Wiebe & Slagsvold, 2015). The question,

We observed that great tits, especially males, included a higher proportion of caterpillars in the diet of nestlings than blue tits. In contrast, blue tits preyed on a higher proportion of spiders than great tits. This supports the results of other authors studying other habitats (Török & Tóth, 1999; García–Navas et al.,

Table 2. Results from the general linear model (GLM) comparing the proportion of prey (caterpillars, spiders, other prey type) between great tit and blue tit and between sexes. The model includes the analyses relating to proportion of oaks surrounding the nest (% Quercus spp.), date of recording, and brood size. Tabla 2. Resultados obtenidos con el modelo lineal general (GLM) al comparar la proporción de presas (orugas, arañas y otro tipo de presas) entre el carbonero común y el herrerillo común y entre sexos. El modelo incluye los análisis sobre la proporción de robles y encinas cercanos al nido (% Quercus spp.), la fecha de observación y el tamaño de la nidada.

Caterpillars ß

F1, 89

Spiders ß

F1, 89

Other prey ß

F1, 89

Species

0.27

9.0 < 0.001

–0.45 22.9 < 0.001

0.00

0.0

0.97

Sex

–0.13

1.9

0.17

0.32

11.8 < 0.001

–0.06

0.4

0.52

Species*Sex

–0.18

4.1

0.05

0.3

0.57

0.20

4.7

0.03

% Quercus spp.

0.31

11.8 < 0.001

–0.10

1.1

0.31

–0.28

9.3 < 0.001

Date of recording

–0.47

26.9

0.00*

–0.01

0.0

0.94

0.52

33.0 < 0.001

Brood size

–0.01

0.0

0.88

–0.16

2.8

0.10

0.14

2.4

0.13

Animal Biodiversity and Conservation 39.1 (2016)

135

3.0

Great tit Blue tit

2.8 2.6

Prey size

2.4 2.3 2.0 1.8 1.6 1.4 1.2 1.0

Caterpillars

Spiders

Other prey

Fig. 3. Mean size of caterpillars, spiders and other prey type fed to nestlings by great tit and blue tit parents during the 2012 breeding season (see table 3). Fig. 3. Tamaño medio de orugas, arañas y otro tipo de presas entregadas a los pollos por los progenitores de carbonero común y de herrerillo común durante la temporada de cría de 2012 (véase la tabla 3).

however, is why great tits widen their diet breadth com� pared to that of blue tits. In the past, caterpillars had been considered the best food resource for nestlings (Perrins, 1991) as they require shorter handling time and are easier to ingest. However, recent work has reported that while spiders have nutritional contents

that are similar to caterpillars, spiders have a higher level of taurine, an amino acid which is important for the development of the nestlings' feathers (Gosler, 1993) and their central nervous system (Ramsay & Houston, 2003; Arnold et al., 2007; see also García– Navas & Sanz, 2010). Accordingly, nestlings of both

Table 3. Results from the general linear model (GLM) comparing the size of the different prey (caterpillars, spiders, others) between great tit and blue tit and between sexes. The model includes the analyses relating to proportion of oaks surrounding the nest (% Quercus spp.), date of recording, and brood size. Tabla 3. Resultados obtenidos con el modelo lineal general (GLM) al comparar el tamaño de las distintas presas (orugas, arañas y otro tipo de presas) entre el carbonero común y el herrerillo común y entre sexos. El modelo incluye los análisis sobre la proporción de robles y encinas cercanos al nido (% Quercus spp.), la fecha de observación y el tamaño de la nidada. Species

Caterpillars ß

F1, 89

Spiders ß 0.41

F1, 89

16.5 < 0,001

Other prey ß 0.38

F1, 89

0.61

44.3 < 0.001

15.4 < 0.001

Sex

0.09

0.9

0.35

0.11

1.2

0,27

0.05

0.2

0.64

Species*Sex

–0.05

0.3

0.60

0.13

1.6

0,21

–0.01

0.0

0.92

% Quercus spp.

0.13

2.1

0.15

–0.01

0,0

0,90

0.08

0.8

0.38

Date of recording

–0.13

2.2

0.14

0.15

2,3

0,13

0.33

12.0 < 0.001

Brood size

0.13

1.9

0.17

0.11

1,2

0,29

0.20

4.0

0.05

Navalpotro et al.

136

100%

Great tit Blue tit

% Caterpillars

80%

60%

40%

20%

0% 65

85 90 95 100 Days from March 1st

105

110

115

Fig. 4. Relationship between percentage of caterpillars brought by great tit and blue tit and date during the 2012 breeding season (time is measured by days from 1st of March) (see table 2). Fig. 4. Relación entre el porcentaje de orugas entregadas por el carbonero común y por el herrerillo común y la fecha durante la temporada de cría de 2012 (el tiempo se mide en días a partir del 1 de marzo) (véase la tabla 2).

species receiving a higher percentage of spiders in their diet showed a better growth rate (García–Navas et al., 2013; Pagani–Núñez & Senar, 2014). Spiders should therefore be a preferred food resource also for great tits (Török & Tóth, 1999). In effect, experiments with captive birds have shown that great tits, given the choice, prefer to feed on spiders than caterpillars (Pagani–Núñez�� et al.,�� 2014a)�� . Perhaps the explana� tion for this is related to the fact that, because of their larger size, great tits can prey on larger prey items than blue tits (Wiebe & Slagsvold, 2015). Great tits in our area typically prey on Zoropsis spiders (which are far larger than spiders captured by blue tits) and contain over 50% more taurine and 5% more proteins than small spiders (Ramsay & Houston, 2003)�� . Therefore, great tits could easily attain bet� ter levels of micronutrients than blue tits who would need to bring a large proportion of small spiders to reach the same nutritional levels as those obtained by great tits. In consequence, great tits could take advantage of the seasonal appearance of caterpillars without compromising the health and growth of their nestlings, and this would result in a higher proportion of caterpillars in their diet. Regarding intersexual differences in parental invest� ment, great tit males fed their nestlings with a higher percentage of caterpillars than did the females, which is in line with data from other studies (Pagani–Núñez et al., 2011; García–Navas et al., 2013). However, we did not find any intersexual differences in blue tits. This

Table 4. Results from the general linear model (GLM) comparing the total size of all prey between great tit and blue tit and between sexes. The model includes the analyses relating to proportion of oaks surrounding the nest (% Quercus spp.), date of recording, brood size and number of prey/h. Tabla 4. Resultados obtenidos con el modelo lineal general (GLM) al comparar el tamaño total de todas las presas entre el carbonero común y el herrerillo común y entre sexos. El modelo incluye los análisis sobre la proporción de robles y encinas cercanos al nido (% Quercus spp.), la fecha de observación, el tamaño de la nidada y el número de presas/h.

F1, 88

Species

0.351

17.4

< 0.001

Sex

–0.126

3.2

0.08

Species*Sex

0.033

0.2

0.64

% Quercus spp.

0.106

2.4

0.12

Date of recording –0.129

3.6

0.06

Brood size

0.214

9.5

< 0.001

Nº prey/h

–0.598

47.9

< 0.001

Animal Biodiversity and Conservation 39.1 (2016)

137

3.0 Great tit Blue tit

Total prey size

2.6 2.2 1.8 1.6 1.4 1.0

15 20 25 Number of prey/h

Fig. 5. Scatterplot showing the relationship between total prey size and feeding rates of great tit and blue tit during the 2012 breeding season (see table 4). Fig. 5. Diagrama de dispersión en el que se muestra la relación existente entre el tamaño total de las presas y la tasa de alimentación del carbonero común y el herrerillo común durante la temporada de cría de 2012 (véase la tabla 4).

is also in line with previous studies (García–Navas & Sanz, 2010; García–Navas et al., 2013), but contrasts with data from Bańbura et al. (2001) who found that blue tit males brought a higher proportion of caterpil� lars than females did. Regarding spiders, females of both species brought a significantly higher proportion of this prey than males, which agrees with previous results (Pagani–Núñez et al., 2011). The reason for this difference is uncertain. However, as females appear to invest more in reproduction (Bańbura et al., 2001), they perhaps select spiders as more profitable prey. Alternatively, it could be a consequence of vertical transmission of diet preferences at early stages at the nest (Wiebe �� & Slagsvold, 2015)�� , or simply a conse� quence of differences in personality traits (Costantini et al., 2005). We did not find any significant differences in prey size between males and females, most likely because dimorphism between males and females is negligible in both species (Przybylo, 1995; Przybylo & Merilä, 2000). Food selection does not seem therefore to be related to morphological traits related to bird size (García–Navas et al., 2013). Finally, the question arises as to whether great tits and blue tits compete for food during the breeding season in mixed sclerophyllous forests. Studies in central Europe focusing only on caterpillars observed the two species competed for caterpillars during the breeding season. Dhondt (1977) remarked that blue tits foraging on the smaller caterpillars would reduce the availability of larger caterpillars later in the sea�

son, which would negatively affect great tits. Török (1986) observed that food composition was the same between great and blue tits and that the difference was in prey size. In this work, we found for first time a difference between the two tit species in relation to the selection of spiders according to size, with great tits capturing larger spiders than blue tits. However, the case of blue tits reducing the availability of larger prey by preying upon small individuals would not be the case of spiders because the many species of spiders vary greatly in size. Also, juveniles of Zoropsis spiders appear just at the very end of the tit breeding season (Monterosso, 1937), eroding the possibility of blue tits eliminating future large spiders. Therefore, given that prey composition and size differ among Mediterranean great tits and blue tits, competition between the two species in this habitat seems to be minor. However, whether differences in diet are due to interspecific competition or food preference is difficult to ascertain with these data. As in other systems, to confirm competition between these two species, it would be necessary to conduct manipula� tive field experiments, alternatively removing the two species from experimental areas and ascertaining whether the birds expand their niche and exploit larger or smaller prey types (Török, 1986; Török & Tóth, 1999). For the time being, our results support the view of a clear resource partitioning by great and blue tits in sclerophyllous forest ecosystem, allowing for their coexistence.

138

Conclusions Our study showed that diets of great tits and blue tits in a Mediterranean mixed forest differed both in prey composition and in prey size delivered to nestlings. Blue tits brought a higher proportion of spiders than great tits while great tits brought relatively high quantities of caterpillars. This finding highlights the important role of spiders in the diet of blue tits in Mediterranean mixed forests. Blue tits brought smaller prey than great tits for all prey types, but worked at higher rates. Altogether, our results support the view of clear resource partitioning by great tits and blue tits in sclerophyllous forest ecosys� tems, a mechanism that facilitates their coexistence. Acknowledgements This work was supported by Research Project CGL2012–38262, Ministry of Economy and Competitiv� ity, Spanish Research Council. We are grateful to Ll. Arroyo for help in the lab and in the field. We thank the Gil family, owners of 'Can Catà', for allowing us to work on their property. Alfons Puertas kindly provided meteorological data, from Secció de Meteorologia of Observatory Fabra. Birds were handled with the permis� sion of the Departament de Medi Ambient, Generalitat de Catalunya. The Catalan Institute of Ornithology (ICO) provided the rings. References Arnold, K. E., Ramsay, S. L., Donaldson, C. & Adam, A., 2007. Parental prey selection affects risk–taking behaviour and spatial learning in avian offspring. Proceedings of the Royal Society B–Biological Sciences, 274: 2563–2569. Arnold, K. E., Ramsay, S. L., Henderson, D. L. & Larcombe, S., 2010. Seasonal variation in diet quality: antioxidants, invertebrates and Blue Tits Cyanistes caeruleus. Biological Journal of the Linnean Society, 99: 708–717. Atiénzar, F., Belda, E. J. & Barba, E., 2013. Coex� istence of Mediterranean tits: A multidimensional approach. Ecoscience, 20: 40–47. Bańbura, J., Blondel, J., Dewildelambrechts, H., Galan, M. J. & Maistre, M., 1994. Nestling diet variation in an insular Mediterranean population of Blue Tits Parus caeruleus: Effects of years, ter� ritories and individuals. Oecologia, 100: 413–420. Bańbura, J., Lambrechts, M. M., Blondel, J., Perret, P. & Cartan–Son, M., 1999. Food handling time of Blue Tit chicks: constraints and adaptation to different prey types. Journal of Avian Biology, 30: 263–270. Bańbura, J., Perret, P., Blondel, J., Sauvages, A., Galan, M. J. & Lambrechts, M. M., 2001. Sex differences in parental care in a Corsican Blue Tit Parus caeruleus population. Ardea, 89: 517–526. Barba, E. & Gil–Delgado, J. A., 1990. Seasonal– variation in nestling diet of the Great tit Parus major in orange groves in eastern Spain. Ornis

Navalpotro et al.

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Ruiz–García & Ferreras–Romero

Animal Biodiversity and Conservation 39.1 (2016)

Brief Communication

An evaluation of monk parakeet damage to crops in the metropolitan area of Barcelona J. C. Senar, J. Domènech, L. Arroyo, I. Torre & O. Gordo Senar, J. C., Domènech, J., Arroyo, L., Torre, I. & Gordo, O., 2016. An evaluation of monk parakeet damage to crops in the metropolitan area of Barcelona. Animal Biodiversity and Conservation, 39.1: 141–145. Abstract An evaluation of monk parakeet damage to crops in the metropolitan area of Barcelona.— We evaluated damage to commercial crops caused by the monk parakeet, Myiopsitta monachus, in the Baix Llobregat agricultural area (1,024 ha) bordering the city of Barcelona, Spain. Average crop loss was 0.4% for tomatoes, 28% for corn, 9% for red plums, 36% for round plums, 37% for pears, 17% for persimmons, and 7% for quinces. Our data show that the potential damage to crops by monk parakeets in this invaded area is now a reality. As a wait–and–see approach is likely to be a more costly strategy in the long–term, policy makers should assess issues such as the extent of damage, feasibility/cost benefit analysis, and public opinion so as to avoid greater damage and loss in the future. Key words: Monk parakeet, Myiopsitta monachus, Damage to crops, Invasive species Resumen Evaluación de los daños producidos por la cotorra de pecho gris en los cultivos del área metropolitana de Barcelona.— En este trabajo evaluamos los daños producidos por la cotorra de pecho gris, Myiopsitta monachus, en los cultivos comerciales del área agrícola del Baix Llobregat (1.024 ha), adyacente a la ciudad de Barcelona (España). En promedio, las cotorras causaron pérdidas en los cultivos del orden del 0,4% en el tomate, el 28% en el maíz, el 9% en la ciruela claudia ovalada, el 36% en la ciruela claudia redonda, el 37% en la pera, el 17% en el caqui y el 7% en el membrillo. Nuestro trabajo confirma de forma objetiva que los daños potenciales producidos por la cotorra de pecho gris en esta zona invadida son ya una realidad. La pasividad en la gestión ante las especies invasoras a la larga siempre acarrea graves consecuencias. Por lo tanto, los sistemas de detección de daños y la rápida intervención en este tipo de conflictos son herramientas básicas en la gestión para evitar problemas a medio largo plazo. Palabras clave: Cotorra de pecho gris, Myiopsitta monachus, Daños en cultivos, Especies invasoras Received: 25 II 16; Conditional acceptance: 26 III 16; Final acceptance: 29 III 16 J. C. Senar, J. Domènech, L. Arroyo, I. Torre & O. Gordo, Museu de Ciències Naturals de Barcelona, Psg. Picasso s/n., 08003 Barcelona, Spain.– I. Torre, Museu de Ciències Naturals de Granollers, 08402 Granollers, Barcelona, Spain.– O. Gordo, Dept. Biología de la Conservación. Estación Biológica de Doñana (CSIC), Sevilla, Spain.

Introduction The monk parakeet, Myiopsitta monachus, native to South America, has invaded several areas in North America and Western Europe in recent decades (Strubbe & Matthysen, 2009). Although the species has long been considered a potential threat to agriculture (Davis, 1974; Bruggers et al., 1998), damage to crops by this species has only been evaluated in countries where the species is native (Mott, 1973; Canavelli et al., 2012, 2014) and in the United States (Tillman et ISSN: 1578–665 X eISSN: 2014–928 X

al., 2000). No data are available for Europe (Menchetti & Mori, 2014). Accurately assessing crop loss by birds is key to developing methods to reduce such damage and to delineate management policies (Bruggers et al., 1998; Strubbe et al., 2011). The metropolitan area of Barcelona holds one of the largest densities of monk parakeets in Europe, with the species invading agricultural areas close to the inner city (Domènech et al., 2003). Our aim was to evaluate crop damage by monk parakeets in the agricultural park of Baix Llobregat. © 2016 Museu de Ciències Naturals de Barcelona

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Material and methods We evaluated damage in the Baix Llobregat region, an agricultural area bordering Barcelona city (fig. 1). We focused on the municipalities of El Prat de Llo� bregat, Viladecans, Gavà and Sant Boi de Llobregat, where vegetable gardens and orchards occupy 10% (1,024 ha) of the area (fig. 1) and where preliminary observations identified monk parakeet activity and crop damage (Domènech et al., 2003). Surveys were carried out in 2001, from June to September when many of the main crops ripen. Furthermore, it is the end of the breeding period and juveniles are also foraging around (Carrillo–Ortiz, 2009), so potential damage can increase. We focused on the most com� mon crops in the area, namely tomatoes and corn, and orchards. The study area included 146 tomato fields, with an estimated total of 458,751 plants (table 1). Since plants in the fields were perfectly aligned, we esti� mated the number of plants by counting the number of plants along the perimeter and extrapolating this to the total area. We randomly sampled 26 fields (18% of total fields) for damage. We used a cluster sample approach, dividing the whole study area into various equally sized areas and obtaining a simple random sample from all the clusters. This ensured that the whole area was sampled. Fields were visited when tomatoes were, in general, of good size (> 5 cm) and sufficiently ripe to be palatable. We sampled 15% of the total plants within each of the 26 fields, randomly sampling lines of five plants and surveying all the tomatoes within each line (table 1). We defined lines as contiguous plants parallel to the same furrow. We also estimated the number of tomatoes per plant in each field, by randomly sampling 20 plants within each field and averaging the number of tomatoes among them. Total damage was then estimated by extrapo� lating the average number of tomatoes per plant to the total of plants and computing on that value the percentage of damage recorded in the sampled units. The percentage of damage was computed within each field and then averaged for all the fields. The study area contained 17 fields of corn, used for livestock. All these fields were sampled. The estimated number of plants, counting the number of plants along the perimeter and extrapolating it to the total area, was 34,700, of which we sampled 18% (table 1). The area also included fields of popcorn. However, these fields were small (< 20 plants) and were only for farmers' personal use; no damage was recorded on these plants (pers. comm. by farmers), and we did not include them in the analyses. Most plants contained only one cob. Plants were sampled at random in lines of 20 or 50 plants, depending on the size of the field (see below). We sampled an aver� age of five lines of plants per field, this figure varying from two to 10 according to the size of fields and thus, to the length of lines. Fields varied from 120 to 12,000 plants, large fields containing > 1,000 plants and small fields having < 800 plants. No field was available at intermediate values. We considered the size of a field with respect to number of plants rather

St Boi de Ll.

Barcelona

Viladecans

Gavà

El Prat de Ll.

1 km

Fig. 1. Location of the Baix Llobregat region, within Catalonia (NE Spain), and the four municipalities surveyed. We focused on vegetable gardens (935 ha) and orchards (89 ha), marked in colour on the map, from the map provided at Agroterritori web page. (Detailed data on the use and composition of fields Idescat web page.) Fig. 1. Localización de la región del Baix Llobregat, en Cataluña (NE de España) y los cuatro municipios estudiados. Nos centramos en los huertos (935 ha) y las huertas (89 ha), marcados en color, obtenidos del mapa disponible en la página web Agroterritori. (Los datos detallados sobre la utilización y la composición de los campos se pueden encontrar en la página web Idescat.)

than to the geometric size because potential damage is proportional to the number of plants rather than to the true size. In the 5 largest fields (> 1,200 plants up to 12,000), we distinguished between exterior (from the fourth line outwards) and interior (from the fourth line inwards) parts. We performed repeated measures ANOVA (RMANOVA) with the % of damage (arcs in square root transformed) as variable response to test whether border and inner plants within each field dif� fered in the degree of damage. Regarding orchards, the study area contained a total of 191 trees made up of five species (table 1). We randomly sampled 13% of these trees (table 1). For each tree, we randomly sampled two high bran� ches (> 2 m above ground) and two low branches, counting the total number of fruits present and the total number damaged by parakeets. Damage by parakeets was, in general, very conspicuous and unmistakable because of the triangular marks they typically exert on the fruits and vegetables (fig. 2). We considered that a fruit was damaged if it had one or more bites, as any damage at all makes the fruit unsuitable for commercialization. We did not examine damage to fruit on the ground because of sampling difficulties.

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Table 1. Description of fields and plants sampled to estimate damage to crops caused by monk parakeets in the metropolitan area of Barcelona: Total. Total number of plants/trees; P/t. Plants/tree sampled; Av. Average damage (%); SE. Standard error damage (%); Min. Minimum damage (%); Max. Maximum damage (%); Est. Estimated number of fruits demaged. As for tomatoes and corn, we estimated the total production of the fields in the study area, and additionally provide an estimation of the total damage. Tabla 1. Descripción de los campos y las plantas muestreados para estimar los daños producidos en los cultivos por la cotorra de pecho gris en el área metropolitana de Barcelona. Calculamos la producción total de tomate y maíz en los campos de la zona de estudio, y proporcionamos también una estimación de los daños totales. (Para las abreviaturas, véase arriba.) Crop

Total

P/t

Min

Max

Est

Tomato (Solanum lycopersicum)

458,751

4,348

0.42

0.22

36,931

Corn (Zea mays)

34,700

6,310

28.1

6.4

9,748

Red plum (Prunus domestica)

150

8.8

4.0

–

Round plum (Prunus domestica)

35.8

29.0

–

Pear (Pyrus communis)

36.6

7.1

–

Persimmon (Diospyros kaki)

17.1

3.3

–

Quince (Cydonia oblonga)

6.5

0.2

6.3

6.7

–

Results The average percentage of tomatoes damaged per field was 0.4% (table 1). Tomato plants produced on average of 19.2 tomatoes (SE = 3.1; N = 26 fields; 520 plants). Given the total number of plants in the study area (see table 1), this resulted in an esti� mated total damage of 36,931 tomatoes. However, the percentage of damaged plants per field was not evenly distributed (fig. 3), and the percentage of fields attacked was 38%. When considering only attacked fields, damage rose to 1.1% of tomatoes. The average percentage of corn cobs damaged per field was 28% (table 1). This resulted in total damage of 9,748 corn cobs (table 1). Damage, however, was not homogeneous. Using paired data, we found that damage was greater in the outer edges of the fields than in the interior areas (exterior: 0.41% (SE = 0.10); interior: 0.19% (SE = 0.08); RMANOVA (F1,4 = 15.4, p = 0.02). The percentage of fields attacked was 75%. Damage to fruit trees varied depending on species, ranging from 6% of quinces to 37% of pears (table 1). Within the same fruit species, damage also varied according to the tree variety, so that while damage to red plums was only 9%, it increased to 36% for round plums (table 1, fig. 2). Discussion The monk parakeet is generally considered a pests to crops (Mott, 1973; Canavelli et al., 2012, 2013). However, as estimates of monk parakeet damage to crops in Europe are non–existent, it is difficult to

objectively evaluate conflict with farmers (Canavelli et al., 2012). Our data recorded in agricultural areas around Barcelona showed that crop damage by the monk parakeet is not negligible. Damage ranged from mean values of 0.4% to 37%, depending on crop type, with maximum values above 70% in some fields and for some crops. More studies are needed to understand the causes of this variability, such as the possible role of ripening status of the fruits, the presence of deterrent systems for birds, and the distance to breeding colonies (Canavelli et al., 2012). We should emphasize that the breeding population of monk parakeets in the study area was only 120 individuals (Domènech et al., 2003), while the crop area covered 1,024 Ha (fig. 1). Our results therefore support the view that even small populations can affect large areas. Foraging trips from the nearby parakeet population in Barcelona city (estimated around 1,500 individuals in 2001, Domènech et al., 2003) also seem plausible. In effect, in recent years we recorded two individuals originally ringed in Barcelona city centre (Parc Ciutadella) in the Baix Llobregat area (move� ments of > 10 km) (J. Oliver, pers. comm.). Currently, the local populations in Barcelona city and southern metropolitan areas have risen to > 5,000 birds �� (Mo� lina et al., 2016), so damage to crops has probably increased. Similar to findings in previous work (Canavelli et al., 2012), we found damage was more severe in the outer edges of corn fields than in the interior parts of the fields. We also found that some varieties of crops were more badly affected than others: round plums were targeted more than red plums, for example, and popcorn was not attacked at all while other corn varie�

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Fig. 2. Examples of crops damaged by monk parakeets in the metropolitan area of Barcelona. The damage by parakeets was in general unmistakable because of the triangular marks they typically exert on the fruit and vegetables. In the case of corn, the monk parakeet is the only bird species able to break through the husk to extract grains: A. Red plums; B. Round plums; C. Pears; D. Quince; E: Tomato; and F. Corn. Fig. 2. Ejemplos de cultivos dañados por la cotorra de pecho gris en el área metropolitana de Barcelona. En general, los daños producidos por la cotorra eran inconfundibles debido a las marcas triangulares que quedan en las frutas y verduras. En el caso del maíz, la cotorra de pecho gris es la única especie de ave capaz de romper la cáscara para extraer los granos: A. Ciruela claudia ovalada; B. Ciruela claudia redonda; C. Pera; D. Membrillo; E. Tomate; F. Maíz.

24 22 20 18 16 14 12 10 8 6 4 2 0

The economic consequences of damage are also crop–dependent. While in fruits and tomatoes any damaged piece must be discarded, independently of the degree of attack, the severity of the attack on

8 7

Nº of corn fields

Nº of tomato fields

ties underwent heavy damage. These observations suggest changes in management principles may be a useful option to reduce parakeet damage, as sug� gested by Canavelli et al. (2012, 2013).

6 5 4 3 2 1

0.5 1.0 1.5 2.0 2.5 3.0 3.5 4.0 4.5 5.0 5.5

Percentage of damage

Fig. 3. Frequency distribution of damage to tomato and corn fields in the metropolitan area of Barcelona. Fig. 3. Distribución de frecuencias de los daños producidos en los campos de tomate y de maíz en el área metropolitana de Barcelona.

Animal Biodiversity and Conservation 39.1 (2016)

corn is determined by the amount of grain left on the cob. Therefore, although corn showed some of the highest frequencies of damage, the economic losses could be lower than for other crops. Our data show that monk parakeet damage to crops in invaded areas is no longer just 'potential' (Davis, 1974) but has become a real threat. This species is included on a 'black list' of invasive species whose eradication is recommended in particular situations (Capdevila et al., 2006). Our evaluation of crop dam� age thus contributes to understanding the role of this invasive species in agricultural ecosystems, providing data for future management policies for these popula� tions. As findings suggest a wait–and–see approach is not the solution in such a situation (Conroy & Senar, 2009) policy makers should address issues related to the extent of damage, control feasibility and cost– benefit analysis, and public opinion (Strubbe et al., 2011) in order to control populations of this species and to avoid greater loss and damage. Acknowledgements The study was supported by funds from the Departa� ment de Medi Ambient of Generalitat de Catalunya, el Departament de Salut Pública of the Diputació de Barcelona, and the Agencia de Salut Pública de Barcelona (ASPB) of Ajuntament de Barcelona. We thank all those who facilitated access to their fields. This paper is dedicated to the memory of Josep Ballús, from the Generalitat de Catalunya, for his unwavering support to the study of invasive species. We also wish to acknowledge the support provided by COST Euro� pean Cooperation in Science and Technology Actions ES1304 'ParrotNet' for the development of this manu� script. The contents of this manuscript are the authors' responsibility and neither COST nor any person acting on its behalf is responsible for the use which might be made of the information contained herein. References Bruggers, R. L., Rodriguez, E. & Zaccagnini, M. E., 1998. Planning for bird pest problem resolution: a case study. International Biodeterioration & Biodegradation, 42: 173–184. Canavelli, S. B., Aramburú, R. & Zaccagnini, M. E., 2012. Aspectos a considerar para disminuir los conflictos originados por los daños de la cotorra (Myiopsitta monachus) en cultivos agrícolas. Hornero, 27: 89–101. Canavelli, S. B., Branch, L. C., Cavallero, P., Gon� zález, C. & Zaccagnini, M. E., 2014. Multi–level

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analysis of bird abundance and damage to crop fields. Agriculture, Ecosystems & Environment, 197: 128–136. Canavelli, S. B., Swisher, M. E. & Branch, L. C., 2013. Factors related to farmers’ preferences to decrease Monk Parakeet damage to crops. Human Dimensions of Wildlife, 18: 124–137. Capdevila, L., Iglesias, A., Orueta, J. F. & Zilletti, B., 2006. Especies exóticas invasoras: diagnóstico y bases para la prevención y el manejo. Organis� mo Autónomo Parques Nacionales, Ministerio de Medio Ambiente, Madrid. Carrillo–Ortiz, J., 2009. Dinámica de poblaciones de la cotorra de pecho gris (Myiopsitta monachus) en la ciudad de Barcelona. PhD Thesis, University of Barcelona. Conroy, M. J. & Senar, J. C., 2009. Integration of de� mographic analyses and decision modelling in su� pport of management of invasive Monk Parakeets, and urban and agricultural pest. Environmental and Ecological Statistics, 3: 491–510. Davis, L. R., 1974. The Monk Parakeet: A potential threat to agriculture. In: Proceedings of the 6th Vertebrate Pest Conference: 253–256. University of Nebraska, Lincoln. Domènech, J., Carrillo–Ortiz, J. & Senar, J. C., 2003. Population size of the Monk Parakeet Myiopsitta monachus in Catalonia. Revista Catalana d’Ornitologia, 20: 1–9. Menchetti, M. & Mori, E., 2014. Worldwide impact of alien parrots (Aves Psittaciformes) on native biodiversity and environment: a review. Ethology Ecology & Evolution, 26: 172–194. Molina, B., Postigo, J. C., Román–Muñoz, A. & Del Moral, J. C., 2016. La cotorra argentina en España: población reproductora en 2015 y método de censo. SEO/BirdLife, Madrid. Mott, D. F., 1973. Monk Parakeet damage to crops in Uruguay and its control. Bird Control Seminars Proceedings, 102. Ref Type, Conference Procee� ding, University of Nebraska, Lincoln. Strubbe, D. & Matthysen, E., 2009. Establishment success of invasive ring–necked and monk pa� rakeets in Europe. Journal of Biogeography, 36, 2264–2278. Strubbe, D., Shwartz, A. & Chiron, F., 2011. Concerns regarding the scientific evidence informing impact risk assessment and management recommenda� tions for invasive birds. Biological Conservation, 144: 2112–2118. Tillman, E. A., Van Doom, A. & Avery, M. L., 2000. Bird damage to tropical fruit in south Florida. In: The Ninth Wildlife Damage Management Conference Proceedings, October 5–8 (M. C. Brittingham, J. Kays & R. McPeake, Eds.). State College, PA, USA.

Ruiz–García & Ferreras–Romero

Animal Biodiversity and Conservation 39.1 (2016)

Animal Biodiversity and Conservation

Manuscrits

Animal Biodiversity and Conservation és una revista interdisciplinària publicada, des de 1958, pel Museu de Ciències Naturals de Barcelona. Inclou articles d'investigació empírica i teòrica en totes les àrees de la zoologia (sistemàtica, taxonomia, morfologia, biogeografia, ecologia, etologia, fisiolo� gia i genètica) procedents de totes les regions del món amb especial énfasis als estudis que permetin compendre, desde un punt de vista pluridisciplinar i integrat, els patrons d'evolució de la biodiversitat en el seu sentit més ampli�� . La �� revista no publica com� pilacions bibliogràfiques, catàlegs, llistes d'espècies o cites puntuals. Els estudis realitzats amb espècies rares o protegides poden no ser acceptats tret que els autors disposin dels permisos corresponents. Cada volum anual consta de dos fascicles. Animal Biodiversity and Conservation es troba registrada en la majoria de les bases de dades més importants i està disponible gratuitament a internet a www.abc.museucienciesjournals.cat, de manera que permet una difusió mundial dels seus articles. Tots els manuscrits són revisats per l'editor execu� tiu, un editor i dos revisors independents, triats d'una llista internacional, a fi de garantir–ne la qualitat. El procés de revisió és ràpid i constructiu. La publicació dels treballs acceptats es fa normalment dintre dels 12 mesos posteriors a la recepció. Una vegada hagin estat acceptats passaran a ser propietat de la revista. Aquesta es reserva els drets d’autor, i cap part dels treballs no podrà ser reproduïda sense citar–ne la procedència.

Els treballs seran presentats en format DIN A–4 (30 línies de 70 espais cada una) a doble espai i amb totes les pàgines numerades. Els manuscrits han de ser complets, amb taules i figures. No s'han d'enviar les figures originals fins que l'article no hagi estat acceptat. El text es podrà redactar en anglès, castellà o català. Se suggereix als autors que enviïn els seus treballs en anglès. La revista els ofereix, sense cap càrrec, un servei de correcció per part d'una persona especialitzada en revistes científiques. En tots els casos, els textos hauran de ser redactats correctament i amb un llenguatge clar i concís. La redacció del text serà impersonal, i s'evitarà sempre la primera persona. Els caràcters cursius s’empraran per als noms científics de gèneres i d’espècies i per als neologis� mes intraduïbles; les cites textuals, independentment de la llengua, seran consignades en lletra rodona i entre cometes i els noms d’autor que segueixin un tàxon aniran en rodona. Quan se citi una espècie per primera vegada en el text, es ressenyarà, sempre que sigui possible, el seu nom comú. Els topònims s’escriuran o bé en la forma original o bé en la llengua en què estigui escrit el treball, seguint sempre el mateix criteri. Els nombres de l’u al nou, sempre que estiguin en el text, s’escriuran amb lletres, excepte quan precedeixin una unitat de mesura. Els nombres més grans s'escriuran amb xifres excepte quan comencin una frase. Les dates s’indicaran de la forma següent: 28 VI 99 (un únic dia); 28, 30 VI 99 (dies 28 i 30); 28–30 VI 99 (dies 28 a 30). S’evitaran sempre les notes a peu de pàgina.

Normes de publicació Els treballs s'enviaran preferentment de forma electrònica (abc@bcn.cat). El format preferit és un document Rich Text Format (RTF) o DOC que inclogui les figures i les taules. Les figures s'hauran d'enviar també en arxius apart en format TIFF, EPS o JPEG. Cal incloure, juntament amb l'article, una carta on es faci constar que el treball està basat en investigacions originals no publicades anterior ment i que està sotmès a Animal Biodiversity and Conservation en exclusiva. A la carta també ha de constar, per a aquells treballs en que calgui manipular animals, que els autors disposen dels permisos necessaris i que compleixen la normativa de protecció animal vigent. També es poden suggerir possibles assessors. Quan l'article sigui acceptat, els autors hauran d'enviar a la Redacció una còpia impresa de la versió final acompanyada d'un disquet indicant el progra� ma utilitzat (preferiblement en Word). Les proves d'impremta enviades a l'autor per a la correcció, seran retornades al Consell Editor en el termini de 10 dies. Aniran a càrrec dels autors les despeses degudes a modificacions substancials introduïdes per ells en el text original acceptat. El primer autor rebrà una còpia electrònica del treball en format PDF. ISSN: 1578–665X eISSN: 2014–928X

Format dels articles Títol. Serà concís, però suficientment indicador del contingut. Els títols amb designacions de sèries numèriques (I, II, III, etc.) seran acceptats previ acord amb l'editor. Nom de l’autor o els autors Abstract en anglès que no ultrapassi les 12 línies mecanografiades (860 espais) i que mostri l’essència del manuscrit (introducció, material, mètodes, resultats i discussió). S'evitaran les especulacions i les cites bibliogràfiques. Estarà encapçalat pel títol del treball en cursiva. Key words en anglès (sis com a màxim), que orientin sobre el contingut del treball en ordre d’importància. Resumen en castellà, traducció de l'Abstract. De la traducció se'n farà càrrec la revista per a aquells autors que no siguin castellanoparlants. Palabras clave en castellà. Adreça postal de l’autor o autors. (Títol, Nom, Abstract, Key words, Resumen, Pala� bras clave i Adreça postal, conformaran la primera pàgina.)

Introducción. S'hi donarà una idea dels antecedents del tema tractat, així com dels objectius del treball. Material y métodos. Inclourà la informació perti� nent de les espècies estudiades, aparells emprats, mètodes d’estudi i d’anàlisi de les dades i zona d’estudi. Resultados. En aquesta secció es presentaran úni� cament les dades obtingudes que no hagin estat publicades prèviament. Discusión. Es discutiran els resultats i es compa� raran amb treballs relacionats. Els suggeriments de recerques futures es podran incloure al final d’aquest apartat. Agradecimientos (optatiu). Referencias. Cada treball haurà d’anar acom� panyat de les referències bibliogràfiques citades en el text. Les referències han de presentar–se segons els models següents (mètode Harvard): * Articles de revista: Conroy, M. J. & Noon, B. R., 1996. Mapping of spe� cies richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773. * Llibres o altres publicacions no periòdiques: Seber, G. A. F., 1982. The estimation of animal abundance. C. Griffin & Company, London. * Treballs de contribució en llibres: Macdonald, D. W. & Johnson, D. P., 2001. Dispersal in theory and practice: consequences for conserva� tion biology. In: Dispersal: 358–372 (T. J. Clober, E. Danchin, A. A. Dhondt & J. D. Nichols, Eds.). Oxford University Press, Oxford. * Tesis doctorals: Merilä, J., 1996. Genetic and quantitative trait vari� ation in natural bird populations. Tesis doctoral, Uppsala University. * Els treballs en premsa només han d’ésser citats si han estat acceptats per a la publicació: Ripoll, M. (in press). The relevance of population studies to conservation biology: a review. Animal Biodiversity and Conservation. La relació de referències bibliogràfiques d’un tre� ball serà establerta i s’ordenarà alfabèticament per autors i cronològicament per a un mateix autor, afegint les lletres a, b, c,... als treballs del mateix any. En el text, s’indic aran en la forma usual: "... segons Wemmer (1998)...", "...ha estat definit per

Robinson & Redford (1991)...", "...les prospeccions realitzades (Begon et al., 1999)...". Taules. Es numeraran 1, 2, 3, etc. i han de ser sempre ressenyades en el text. Les taules grans seran més estretes i llargues que amples i curtes ja que s'han d'encaixar en l'amplada de la caixa de la revista. Figures. Tota classe d’il·lustracions (gràfics, figures o fotografies) entraran amb el nom de figura i es numeraran 1, 2, 3, etc. i han de ser sempre ressen� yades en el text. Es podran incloure fotografies si són imprescindibles. Si les fotografies són en color, el cost de la seva publicació anirà a càrrec dels au� tors. La mida màxima de les figures és de 15,5 cm d'amplada per 24 cm d'alçada. S'evitaran les figures tridimensionals. Tant els mapes com els dibuixos han d'incloure l'escala. Els ombreigs preferibles són blanc, negre o trama. S'evitaran els punteigs ja que no es reprodueixen bé. Peus de figura i capçaleres de taula. Seran clars, concisos i bilingües en la llengua de l’article i en anglès. Els títols dels apartats generals de l’article (Intro� ducción, Material y métodos, Resultados, Discusión, Conclusiones, Agradecimientos y Referencias) no aniran numerats. No es poden utilitzar més de tres nivells de títols. Els autors procuraran que els seus treballs originals no passin de 20 pàgines (incloent–hi figures i taules). Si a l'article es descriuen nous tàxons, caldrà que els tipus estiguin dipositats en una institució pública. Es recomana als autors la consulta de fascicles recents de la revista per tenir en compte les seves normes. Comunicacions breus Les comunicacions breus seguiran el mateix proce� diment que els articles y tindran el mateix procés de revisió. No excediran de 2.300 paraules incloent–hi títol, resum, capçaleres de taula, peus de figura, agraïments i referències. El resum no ha de passar de 100 paraules i el nombre de referències ha de ser de 15 com a màxim. Que el text tingui apartats és op� cional i el nombre de taules i/o figures admeses serà de dos de cada com a màxim. En qualsevol cas, el treball maquetat no podrà excedir de quatre pàgines.

Animal Biodiversity and Conservation 39.1 (2016)

Animal Biodiversity and Conservation Animal Biodiversity and Conservation es una revista interdisciplinar, publicada desde 1958 por el Museo Ciencias Naturales de Barcelona. Incluye artículos de investigación empírica y teórica en todas las áreas de la zoología (sistemática, taxonomía, morfología, biogeografía, ecología, etología, fisiología y genéti� ca) procedentes de todas las regiones del mundo, con especial énfasis en los estudios que permitan comprender, desde un punto de vista pluridisciplinar e integrado, los patrones de evolución de la biodi� versidad en su sentido más amplio. La revista no publica compilaciones bibliográficas, catálogos, listas de especies sin más o citas puntuales. Los estudios realizados con especies raras o protegidas pueden no ser aceptados a no ser que los autores dispongan de los permisos correspondientes. Cada volumen anual consta de dos fascículos. Animal Biodiversity and Conservation está re� gistrada en todas las bases de datos importantes y además está disponible gratuitamente en internet en www.abc.museucienciesjournals.cat, lo que permite una difusión mundial de sus artículos. Todos los manuscritos son revisados por el editor ejecutivo, un editor y dos revisores independientes, elegidos de una lista internacional, a fin de garan� tizar su calidad. El proceso de revisión es rápido y constructivo, y se realiza vía correo electrónico siempre que es posible. La publicación de los trabajos aceptados se realiza con la mayor rapidez posible, normalmente dentro de los 12 meses siguientes a la recepción del trabajo. Una vez aceptado, el trabajo pasará a ser propie� dad de la revista. Ésta se reserva los derechos de autor, y ninguna parte del trabajo podrá ser reprodu� cida sin citar su procedencia.

Normas de publicación Los trabajos se enviarán preferentemente de forma electrónica (abc@bcn.cat). El formato preferido es un documento Rich Text Format (RTF) o DOC, que incluya las figuras y las tablas. Las figuras deberán enviarse también en archivos separados en formato TIFF, EPS o JPEG. Debe incluirse, con el artículo, una carta donde conste que el trabajo versa sobre investigaciones originales no publicadas anterior mente y que se somete en exclusiva a Animal Biodiversity and Conservation. En dicha carta también debe constar, para trabajos donde sea necesaria la manipulación de animales, que los autores disponen de los permisos necesarios y que han cumplido la normativa de protección animal vigente. Los autores pueden enviar también sugerencias para asesores. Cuando el trabajo sea aceptado los autores de� berán enviar a la Redacción una copia impresa de la versión final junto con un disquete del manuscrito preparado con un procesador de textos e indicando el programa utilizado (preferiblemente Word). Las pruebas de imprenta enviadas a los autores deberán

ISSN: 1578–665X eISSN: 2014–928X

III

remitirse corregidas al Consejo Editor en el plazo máximo de 10 días. Los gastos debidos a modifica� ciones sustanciales en las pruebas de imprenta, intro� ducidas por los autores, irán a cargo de los mismos. El primer autor recibirá una copia electrónica del trabajo en formato PDF. Manuscritos Los trabajos se presentarán en formato DIN A–4 (30 lí� neas de 70 espacios cada una) a doble espacio y con las páginas numeradas. Los manuscritos deben estar completos, con tablas y figuras. No enviar las figuras originales hasta que el artículo haya sido aceptado. El texto podrá redactarse en inglés, castellano o catalán. Se sugiere a los autores que envíen sus trabajos en inglés. La revista ofrece, sin cargo ningu� no, un servicio de corrección por parte de una persona especializada en revistas científicas. En cualquier caso debe presentarse siempre de forma correcta y con un lenguaje claro y conciso. La redacción del texto deberá ser impersonal, evitándose siempre la primera persona. Los caracteres en cursiva se utilizarán para los nombres científicos de géneros y especies y para los neologismos que no tengan traducción; las citas textuales, independientemente de la lengua en que estén, irán en letra redonda y entre comillas; el nombre del autor que sigue a un taxón se escribirá también en redonda. Al citar por primera vez una especie en el trabajo, deberá especificarse siempre que sea posible su nombre común. Los topónimos se escribirán bien en su forma original o bien en la lengua en que esté redactado el trabajo, siguiendo el mismo criterio a lo largo de todo el artículo. Los números del uno al nueve se escribirán con letras, a excepción de cuando precedan una unidad de medida. Los números mayores de nueve se escribirán con cifras excepto al empezar una frase. Las fechas se indicarán de la siguiente forma: 28 VI 99 (un único día); 28, 30 VI 99 (días 28 y 30); 28–30 VI 99 (días 28 al 30). Se evitarán siempre las notas a pie de página. Formato de los artículos Título. Será conciso pero suficientemente explicativo del contenido del trabajo. Los títulos con designacio� nes de series numéricas (I, II, III, etc.) serán aceptados excepcionalmente previo consentimiento del editor. Nombre del autor o autores Abstract en inglés de 12 líneas mecanografiadas (860 espacios como máximo) y que exprese la esen� cia del manuscrito (introducción, material, métodos, resultados y discusión). Se evitarán las especulacio� nes y las citas bibliográficas. Irá encabezado por el título del trabajo en cursiva. Key words en inglés (un máximo de seis) que especifiquen el contenido del trabajo por orden de importancia.

Resumen en castellano, traducción del abstract. Su traducción puede ser solicitada a la revista en el caso de autores que no sean castellano hablantes. Palabras clave en castellano. Dirección postal del autor o autores. (Título, Nombre, Abstract, Key words, Resumen, Palabras clave y Dirección postal conformarán la primera página.) Introducción. En ella se dará una idea de los ante� cedentes del tema tratado, así como de los objetivos del trabajo. Material y métodos. Incluirá la información referente a las especies estudiadas, aparatos utilizados, me� todología de estudio y análisis de los datos y zona de estudio. Resultados. En esta sección se presentarán úni� camente los datos obtenidos que no hayan sido publicados previamente. Discusión. Se discutirán los resultados y se compara� rán con otros trabajos relacionados. Las sugerencias sobre investigaciones futuras se podrán incluir al final de este apartado. Agradecimientos (optativo). Referencias. Cada trabajo irá acompañado de una bibliografía que incluirá únicamente las publicaciones citadas en el texto. Las referencias deben presentarse según los modelos siguientes (método Harvard): * Artículos de revista: Conroy, M. J. & Noon, B. R., 1996. Mapping of spe� cies richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773. * Libros y otras publicaciones no periódicas: Seber, G. A. F., 1982. The estimation of animal abundance. C. Griffin & Company, London. * Trabajos de contribución en libros: Macdonald, D. W. & Johnson, D. P., 2001. Dispersal in theory and practice: consequences for conserva� tion biology. In: Dispersal: 358–372 (T. J. Clober, E. Danchin, A. A. Dhondt & J. D. Nichols, Eds.). Oxford University Press, Oxford. * Tesis doctorales: Merilä, J., 1996. Genetic and quantitative trait vari� ation in natural bird populations. Tesis doctoral, Uppsala University. * Los trabajos en prensa sólo se citarán si han sido aceptados para su publicación: Ripoll, M. (in press). The relevance of population studies to conservation biology: a review. Animal Biodiversity and Conservation.

Las referencias se ordenarán alfabéticamente por autores, cronológicamente para un mismo autor y con las letras a, b, c,... para los trabajos de un mismo autor y año. En el texto las referencias bibliográficas se indicarán en la forma usual: "... según Wemmer (1998)...", "...ha sido definido por Robinson & Redford (1991)...", "...las prospecciones realizadas (Begon et al., 1999)...". Tablas. Se numerarán 1, 2, 3, etc. y se reseñarán todas en el texto. Las tablas grandes deben ser más estrechas y largas que anchas y cortas ya que deben ajustarse a la caja de la revista. Figuras. Toda clase de ilustraciones (gráficas, figuras o fotografías) se considerarán figuras, se numerarán 1, 2, 3, etc. y se citarán todas en el texto. Pueden incluirse fotografías si son imprescindibles. Si las fotografías son en color, el coste de su publicación irá a cargo de los autores. El tamaño máximo de las figuras es de 15,5 cm de ancho y 24 cm de alto. Deben evitarse las figuras tridimensionales. Tanto los mapas como los dibujos deben incluir la escala. Los sombreados preferibles son blanco, negro o trama. Deben evitarse los punteados ya que no se reproducen bien. Pies de figura y cabeceras de tabla. Serán claros, concisos y bilingües en castellano e inglés. Los títulos de los apartados generales del artículo (Introducción, Material y métodos, Resultados, Discusión, Agradecimientos y Referencias) no se numerarán. No utilizar más de tres niveles de títulos. Los autores procurarán que sus trabajos originales no excedan las 20 páginas incluidas figuras y tablas. Si en el artículo se describen nuevos taxones, es imprescindible que los tipos estén depositados en alguna institución pública. Se recomienda a los autores la consulta de fascícu� los recientes de la revista para seguir sus directrices. Comunicaciones breves Las comunicaciones breves seguirán el mismo pro� cedimiento que los artículos y serán sometidas al mismo proceso de revisión. No excederán las 2.300 palabras, incluidos título, resumen, cabeceras de tabla, pies de figura, agradecimientos y referencias. El resumen no debe sobrepasar las 100 palabras y el número de referencias será de 15 como máximo. Que el texto tenga apartados es opcional y el número de tablas y/o figuras admitidas será de dos de cada como máximo. En cualquier caso, el trabajo maque� tado no podrá exceder las cuatro páginas.

Animal Biodiversity and Conservation 39.1 (2016)

Animal Biodiversity and Conservation

Manuscripts

Animal Biodiversity and Conservation is an inter� disciplinary journal published by the Natural Science Museum of Barcelona since 1958. It includes empiri� cal and theoretical research from around the world that examines any aspect of Zoology (Systematics, Taxonomy, Morphology, Biogeography, Ecology, Ethol� ogy, Physiology and Genetics). Special emphasis is given to integrative and multidisciplinary studies that help to understand the evolutionary patterns in biodiversity in the widest sense. The journal does not publish bibliographic compilations, listings, catalogues or collections of species, or isolated descriptions of a single specimen. Studies concerning rare or protected species will not be accepted unless the authors have been granted the relevant permits or authorisation. Each annual volume consists of two issues. Animal Biodiversity and Conservation is regis� tered in all principal data bases and is freely available online at www.abc.museucienciesjournals.cat assur� ing world–wide access to articles published therein. All manuscripts are screened by the Executive Editor, an Editor and two independent reviewers so as to guarantee the quality of the papers. The review process aims to be rapid and constructive. Once accepted, papers are published as soon as is practicable. This is usually within 12 months of initial submission. Upon acceptance, manuscripts become the pro� perty of the journal, which reserves copyright, and no published material may be reproduced or cited without acknowledging the source of information.

Manuscripts must be presented in DIN A–4 format, 30 lines, 70 keystrokes per page. Maintain double spacing throughout. Number all pages. Manuscripts should be complete with figures and tables. Do not send original figures until the paper has been accepted. The text may be written in English, Spanish or Catalan, though English is preferred. The journal provides linguistic revision by an author’s editor. Care must be taken to use correct wording and the text should be written concisely and clearly. Scientific names of genera and species as well as untrans� latable neologisms must be in italics. Quotations in whatever language used must be typed in ordinary print between quotation marks. The name of the author following a taxon should also be written in lower case letters. When referring to a species for the first time in the text, both common and scientific names should be given when possible. Do not capitalize common names of species unless they are proper nouns (e.g. Iberian rock lizard). Place names may appear either in their original form or in the language of the manuscript, but care should be taken to use the same criteria throughout the text. Numbers one to nine should be written in full within the text except when preceding a measure. Higher numbers should be written in numerals except at the beginning of a sentence. Specify dates as follows: 28 VI 99 (for a single day); 28, 30 VI 99 (referring to two days, e.g. 28th and 30th), 28–30 VI 99 (for more than two consecu� tive days, e.g. 28th to 30th). Footnotes should not be used.

Information for authors Electronic submission of papers is encouraged (abc@bcn.cat). The preferred format is DOC or RTF. All figures must be readable by Word, embedded at the end of the manuscript and submitted together in a separate attachment in a TIFF, EPS or JPEG file. Tables should be placed at the end of the document. A cover letter stating that the article reports original research that has not been published elsewhere and has been submitted exclusively for considera� tion in Animal Biodiversity and Conservation is also necessary. When animal manipulation has been necessary, the cover letter should also specify that the authors follow current norms on the protection of animal species and that they have obtained all relevant permits and authorisations. Authors may suggest referees for their papers. Once an article has been accepted, authors should send a paper copy and an electronic copy of the final version. Please identify software (preferably Word). Proofs sent to the authors for correction should be returned to the Editorial Board within 10 days. Expenses due to any substantial alterations of the proofs will be charged to the authors. The first author will receive electronic version of the article in PDF format.

ISSN: 1578–665X eISSN: 2014–928X

Formatting of articles Title. Must be concise but as informative as possible. Numbering of parts (I, II, III, etc.) should be avoided and will be subject to the Editor’s consent. Name of author or authors Abstract in English, no longer than 12 typewritten lines (840 spaces), covering the contents of the article (introduction, material, methods, results and discussion). Speculation and literature citation should be avoided. The abstract should begin with the title in italics. Key words in English (no more than six) should express the precise contents of the manuscript in order of relevance. Resumen in Spanish, translation of the Abstract. Summaries of articles by non–Spanish speaking authors will be translated by the journal on request. Palabras clave in Spanish. Address of the author or authors. (Title, Name, Abstract, Key words, Resumen, Pala� bras clave and Address should constitute the first page.) Introduction. Should include the historical back� ground of the subject as well as the aims of the paper.

Material and methods. This section should provide relevant information on the species studied, materi� als, methods for collecting and analysing data, and the study area. Results. Report only previously unpublished results from the present study. Discussion. The results and their comparison with related studies should be discussed. Suggestions for future research may be given at the end of this section. Acknowledgements (optional). References. All manuscripts must include a bibliog� raphy of the publications cited in the text. References should be presented as in the following examples (Harvard method): * Journal articles: Conroy, M. J. & Noon, B. R., 1996. Mapping of spe� cies richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773. * Books or other non–periodical publications: Seber, G. A. F., 1982. The estimation of animal abundance. C. Griffin & Company, London. * Contributions or chapters of books: Macdonald, D. W. & Johnson, D. P., 2001. Dispersal in theory and practice: consequences for conserva� tion biology. In: Dispersal: 358–372 (T. J. Clober, E. Danchin, A. A. Dhondt & J. D. Nichols, Eds.). Oxford University Press, Oxford. * Ph. D. Thesis: Merilä, J., 1996. Genetic and quantitative trait variation in natural bird populations. Ph. D. Thesis, Uppsala University. * Works in press should only be cited if they have been accepted for publication: Ripoll, M. (in press). The relevance of population studies to conservation biology: a review. Animal Biodiversity and Conservation. References must be set out in alphabetical and chrono� logical order for each author, adding the letters a, b, c,... to papers of the same year. Bibliographic citations in the text must appear in the usual way: "...according to Wemmer (1998)...", "...has been defined by Robinson & Redford (1991)...", "...the prospections that have been carried out (Begon et al., 1999)..."

Tables. Must be numbered in Arabic numerals with reference in the text. Large tables should be narrow (across the page) and long (down the page) rather than wide and short, so that they can be fitted into the column width of the journal. Figures. All illustrations (graphs, drawings, photo� graphs) should be termed as figures, and numbered consecutively in Arabic numerals (1, 2, 3, etc.) with reference in the text. Glossy print photographs, if essential, may be included. The Journal will publish colour photographs but the author will be charged for the cost. Figures have a maximum size of 15.5 cm wide by 24 cm long. Figures should not be tridimen� sional. Any maps or drawings should include a scale. Shadings should be kept to a minimum and preferably with black, white or bold hatching. Stippling should be avoided as it may be lost in reproduction. Legends of tables and figures. Legends of tables and figures should be clear, concise, and written both in English and Spanish. Main headings (Introduction, Material and methods, Results, Discussion, Acknowledgements and Referen� ces) should not be numbered. Do not use more than three levels of headings. Manuscripts should not exceed 20 pages including figures and tables. If the article describes new taxa, type material must be deposited in a public institution. Authors are advised to consult recent issues of the journal and follow its conventions. Brief communications Brief communications should follow the same proce� dure as other articles and they will undergo the same review process. They should not exceed 2,300 words including title, abstract, figure and table legends, ack� nowledgements and references. The abstract should not exceed 100 words, and the number of references should be limited to 15. Section headings within the text are optional. Brief communications may have up to two figures and/or two tables but the whole paper should not exceed four published pages.

Animal Biodiversity and Conservation 39.1 (2016)

VII

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99–114 Olivero, J., Toxopeus, A. G., Skidmore, A. K. & Real, R. Testing the efficacy of downscaling in species distribution modelling: a comparison between MaxEnt and favourability function models 115–128 Obregón, R., Fernández Haeger, J. & Jordano, D. Effects of climate change on three species of Cupido (Lepidoptera, Lycaenidae) with different biogeographic distribution in Andalusia, southern Spain

129–139 Navalpotro, H., Pagani–Núñez, E., Hernández–Gómez, S. & Senar, J. C. Comparing prey composition and prey size delivered to nestlings by great tit, Parus major, and blue tit, Cyanistes caeruleus, in a Mediterranean sclerophyllous mixed forest 141–145 Brief communication Senar, J. C., Domènech, J., Arroyo, L., Torre, I. & Gordo, O. An evaluation of monk parakeet damage to crops in the metropolitan area of Barcelona

Les cites o els abstracts dels articles d’Animal Biodiversity and Conservation es resenyen a / Las citas o los abstracts de los artículos de Animal Biodiversity and Conservation se mencionan en / Animal Biodiversity and Conservation is cited or abstracted in: Abstracts of Entomology, Agrindex, Animal Behaviour Abstracts, Anthropos, Aquatic Sciences and Fisheries Abstracts, Behavioural Biology Abstracts, Biological Abstracts, Biological and Agricultural Abstracts, BIOSIS Previews, CiteFactor, Current Primate References, Current Contents/Agriculture, Biology & Environmental Sciences, DIALNET, DOAJ, DULCINEA, Ecological Abstracts, Ecology Abstracts, Entomology Abstracts, Environmental Abstracts, Environmental Periodical Bibliography, FECYT, Genetic Abstracts, Geographical Abstracts, Índice Español de Ciencia y Tecnología, International Abstracts of Biological Sciences, International Bibliography of Periodical Literature, International Developmental Abstracts, Latindex, Marine Sciences Contents Tables, Oceanic Abstracts, RACO, Recent Ornithological Literature, REDIB, Referatirnyi Zhurnal, Science Abstracts, Science Citation Index Expanded, Scientific Commons, SCImago, SCOPUS, Serials Directory, SHERPA/ RoMEO, Ulrich’s International Periodical Directory, Zoological Records.

Consorci format per / Consorcio formado por / Consortium formed by:

Índex / Índice / Contents Animal Biodiversity and Conservation 39.1 (2016) ISSN 1578–665 X eISSN 2014–928 X

1–10 Acevedo, A. A., Franco, R. & Carrero, D. A. Diversity of Andean amphibians of the Tamá National Natural Park in Colombia: a survey for the presence of Batrachochytrium dendrobatidis 11–16 Feldman Turjeman, S., Centeno–Cuadros, A. & Nathan, R. Isolation and characterization of novel polymorphic microsatellite markers for the white stork, Ciconia ciconia: applications in individual–based and population genetics 17–27 Belenguer Barrionuevo, R., López–Iborra, G. M., Dies, J. I. & Castany i Alvaro, J. Dramatic decline of the bearded reedling, Panurus biarmicus, in Spanish Mediterranean wetlands 29–36 Farashi, A. & Naderi, M. & Parvian, N. Identifying a preservation zone using multi– criteria decision analysis 37–44 Cuadrado, M., Sánchez, Í., Barcell, M. & Armario, M. Reproductive data and analysis of recoveries in a population of white stork, Ciconia ciconia, in southern Spain: a 24–year study

45–63 Cordero–Rivera, A., Encalada, A. C., Sánchez– Guillén, R. A., Santolamazza–Carbone, S. & von Ellenrieder, N. The status of Rhionaeschna galapagoensis (Currie, 1901) with notes on its biology and a description of its ultimate instar larva (Odonata, Aeshnidae) 65–75 Alba–Tercedor, J., Sáinz–Bariáin, M. & Zamora– Muñoz, C. Changing the pupal case architecture as a survival strategy in the caddisfly, Annitella amelia Sipahiler, 1998 (Insecta, Trichoptera) 77–87 González–Maya, J. F., Arias–Alzate, A., Granados– Peña, R., Mancera–Rodríguez, N. J. & Ceballos, G. Environmental determinants and spatial mismatch of mammal diversity measures in Colombia 89–98 Moreno–Rueda, G., Abril–Colón, I., López–Orta, A., Álvarez–Benito, I., Castillo–Gómez, C., Comas, M. & Rivas, J. M. Breeding ecology of the southern shrike, Lanius meridionalis, in an agrosystem of south–eastern Spain: the surprisingly excellent breeding success in a declining population

Amb el suport de / Con el apoyo de / With the support of: