ABC vol 39.2 (2016) by Museu Ciències Naturals de Barcelona MCNB

Editor en cap / Editor responsable / Editor in Chief Joan 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 Miquel Arnedo Univ. de Barcelona, Barcelona, Spain 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 Ben J. Hatchwell Univ. of Sheffield, UK Joaquín Hortal Museo Nacional de Ciencias Naturales-CSIC, Madrid, Spain Jacob Höglund Uppsala Univ., Uppsala, Sweden 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 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 39.2, 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: Artipapel 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: Cucujus cinnaberinus (Scopoli, 1763) (Jordi Domènech)

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Factors affecting fledgling output of great tits, Parus major, in the long term S. Rodríguez, E. Álvarez & E. Barba

Rodríguez, S., Álvarez, E. & Barba, E., 2016. Factors affecting fledgling output of great tits, Parus major, in the long term. Animal Biodiversity and Conservation, 39.2: 147–154. Abstract Factors affecting fledgling output of great tits, Parus major, in the long term.— Fledgling production has often been used as an estimator of avian reproductive success, and it is conditioned by factors affecting offspring development and/or survival during the nesting period. We aimed to determine which predictors influenced fledgling output among a set of basic breeding parameters and local temperature data collected over 25 years in a Mediterranean great tit, Parus major, population, using an information–theoretic approach for model selection. Of the studied variables, the number of hatchlings per nest was the single–most important predictor influencing fledgling production, with larger broods eventually yielding more fledglings, although mass prior to fledging may have been compromised. This result suggests an overall good adjustment between brood size and resource availability in the studied population. Key words: Fledgling production, Nestling survival, Brood size, Long–term study Resumen Factores que afectan a la producción de volantones en el carbonero común, Parus major, a largo plazo.— La producción de volantones ha sido frecuentemente utilizada para estimar el éxito reproductor de las aves y está condicionada por factores que afectan al desarrollo de los pollos, a la supervivencia o a ambos durante su estancia en el nido. Nuestro objetivo en este trabajo fue determinar los factores predictores que influyen en la producción de volantones a partir de un conjunto de parámetros reproductivos básicos y temperaturas locales recopilados durante 25 años en una población mediterránea de carbonero común, Parus major, haciendo uso de criterios de información para la selección de modelos. De las variables estudiadas, el número de huevos eclosionados por nido resultó ser el factor predictor con mayor influencia en la producción de volantones, de tal forma que las puestas más grandes originaron más volantones, si bien el peso de los pollos antes de abandonar el nido podría haberse visto comprometido. Este resultado sugiere que hay un buen ajuste general entre el tamaño de puesta y la disponibilidad de recursos en la población estudiada. Palabras clave: Producción de volantones, Supervivencia en el nido, Tamaño de puesta, Estudio a largo plazo Received: 11 I 16; Conditional acceptance: 23 II 16; Final acceptance: 10 III 16 Samuel Rodríguez, Elena Álvarez & Emilio Barba, Cavanilles Inst. of Biodiversity and Evolutionary Biology, Univ. of Valencia, 46980 Paterna, c/ Catedrático José Beltran Martínez 2, 46980 Paterna, Valencia, Spain.– Elena Álvarez, Dept. de Ecología Evolutiva, Museo Nacional de Ciencias Naturales–CSIC, c/ José Gutiérrez Abascal 2, 28006 Madrid, Spain. Corresponding author: Samuel Rodríguez. E-mail: samuel.rodriguez@uv.es

ISSN: 1578–665 X eISSN: 2014–928 X

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Introduction Avian reproductive success is a recurrent topic in ornithological research. It depends on the number of breeding attempts, with predation being the main cause of complete nest failure (see Martin, 1995), and on the number of individuals surviving to become breeding adults per successful attempt. Among successful nests (i.e., those with at least one young fledged), the number of fledglings has often been used as a reliable estimator of the number of recruited young (Weatherhead & Dufour, 2000; Wiens & Reynolds, 2005) and is conditioned by factors influencing offspring development and/or survival during the nesting period. Among the factors potentially affecting fledgling output, breeding date has proven to influence offspring fitness, with nestlings raised earlier in the season usually benefitting from higher resource availability (Catry et al., 1998), although in certain years, breeding too early could also be disadvantageous (Monrós et al., 2002). In this sense, hatching date could be a more accurate parameter than laying date when analyzing the optimal timing of reproduction in birds (Tomás, 2015). Egg size, in turn, may affect nestling immune function and/or growth (Williams, 1994; Hipfner, 2000), as larger eggs provide the embryo access to higher quantities of energy (Birkhead & Nettleship, 1982). The aforementioned factors (i.e., egg size and bird phenology), together with clutch size, may be indicators of the quality of the parents and their ability to raise the brood, which would have direct consequences on chick survival to fledging (Pettifor et al., 2001). Moreover, if parents optimize their clutch size based on resource availability (Cresswell & McCleery, 2003; Naef–Daenzer et al., 2004), and some of these eggs fail to hatch, the remaining young may receive greater care and thus improve their survival prospects. As a result, not only the absolute number of hatchlings, but also the number of unhatched eggs could affect fledgling production. Temperature is one of the main abiotic factors influencing nesting conditions and eventual fledgling production. Nestlings have limited thermoregulatory abilities during their first days of life, which makes them especially vulnerable to suboptimal thermal conditions (Murphy, 1985; McCarty & Winkler, 1999; Takagi, 2001; Bradbury et al., 2003). When exposed to high temperatures, nestlings lose appetite, and their growth rate and musculature decrease (Belda et al., 1995; Geraert et al., 1996). On the other hand, low temperatures also limit nestling condition (Krijgsveld et al., 2003), as colder nest microclimates require a higher investment in thermoregulation, at the expense of processes such as growth or development of the immune system (Dawson et al., 2005; Rodríguez & Barba, in press). Although many factors have been shown to affect fledgling production, they have seldom been studied simultaneously to determine their relative importance (Coulter & Bryan, 1995; Martín–Vivaldi et al., 1999; Knight & Rogers, 2004; Gullet et al., 2015; Herman & Colwell, 2015). Moreover, their relative weight may vary from year to year, so that long–time series are

needed to elucidate each factor’s net effect on long temporal scales. Using reproductive and local temperature data collected over 25 years in a Mediterranean great tit, Parus major, population, we here aimed to determine the predictors with the greatest influence on the number of fledglings. We also assessed the relationships between the relevant predictors and condition at fledging (i.e., mass and size at fledging). Material and methods Fieldwork Data used for the present study were obtained during a long–term research project on a Mediterranean great tit population breeding near Sagunto (Valencia, eastern Spain 39º 42' N, 0º 15' W, 30 m a.s.l.). The study area was located within a homogeneous, extensive orange plantation (Andreu & Barba, 2006). We used reproductive and thermal data collected from 1986 to 2010. Mean laying date of the first egg (given as April dates) for the studied population during this period was 15.92 ± 5.20. Each year, we placed wooden nest boxes (see Lambrechts et al., 2010, for dimensions) by the end of February. They were removed after each breeding season. Nest boxes were visited with the periodicity necessary (daily at some stages) to accurately determine the following reproductive parameters: clutch size, hatching date (date of hatching of the first egg), number of hatchlings and number of fledglings (e.g., Greño et al., 2008). We measured the length and width of every egg of most clutches once it was considered to be complete (at least three days without the appearance of new eggs), using a caliper (± 0.1 mm). We determined the volume of each egg using the equation: 2

V = (0.4673 x L x B ) + 0.042 3

V being the egg volume in mm , 0.4673 the shape parameter, L the egg length in mm and B the egg width in mm (Ojanen et al., 1978). When nestlings were 15 days old, they were ringed with individually numbered metal rings and weighed (digital balance, ± 0.01 g), and their tarsus length was measured (caliper, ± 0.01 mm). We visited the nest boxes at least five days later to determine the number of fledglings. Within–nest mean egg volume, mean nestling body mass and mean nestling tarsus length were used in analyses to avoid pseudoreplication (Hurlbert, 1984). We only have data of nestling biometry since 1993. We used data from first clutches, of non–manipulated nests. As we were only interested in successful nests, we also excluded those nests where no nestlings fledged, and those for which data from any of the recorded reproductive parameters was missing. This led us to eventually discard data from three years (i.e., 1989, 2004 and 2005), either because of absence of a reasonable number of successful nests (i.e., less than five nests in 2004), or absence of data on egg size (1989 and 2005). Overall, we used data from 644 successful nests in the analyses.

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Daily ambient temperatures were obtained from the Meteorological Station 'El Pontazgo', close to the study area. For each nest, we calculated average mean ambient temperatures during the first five and 15 days after hatching. We chose these periods so as to (1) encompass a period of high vulnerability to changes in ambient temperature (during their first five days of age, great tit nestlings lack the capacity to regulate their internal body temperature; see experiments in Shilov 1973), and (2) to account for overall temperatures experienced during nestling development. Statistical analyses We conducted Generalized Linear Models (GLMs) with a Poisson error distribution and log link function to determine which factors explained nestling survival, taking an information–theoretic approach to model selection (Johnson & Omland, 2004; Whittingham et al., 2006). As dependent variable, we considered the absolute number of fledglings. As explanatory variables, we considered mean egg size, clutch size, hatching date, number of hatchlings, number of unhatched eggs (i.e., the difference between clutch size and the number of hatchlings), and mean ambient temperatures during the first five and 15 days after hatching. To simplify interpretation and limit the set of models considered, we did not include interaction terms. We also analyzed the relationship between the number of fledglings per nest and the number of hatchlings (see results for explanation) by fitting different regression curves and choosing the simplest model from among the significant ones. Additionally, we performed simple linear regressions to examine the relationship between the number of hatchlings per nest (see results for explanation) and mean nestling mass, and mean nestling tarsus length. We assessed the relevance of incorporating the year as a factor by performing a Likelihood Ratio Test with the fully–parameterized model. As its addition did not result in a statistically significant improvement in model fit (x2 = 18.903, P = 0.5914) we rejected its inclusion in the models. We tested the validity of this general model by visually inspecting its residuals. Previous studies have shown that all of the analyzed predictors can affect nestling survival when considered individually, so we had no reason to select certain combinations of variables over others. Therefore, we generated 128 models considering all possible non–redundant combinations of predictive variables, ranking them using the small sample sizes' corrected Akaike Information Criterion (AICc, Burnham & Anderson, 1998). We relied on model averaging to obtain a weighted average of predictor estimates from a subset of equally–plausible models (i.e., models with AICc value differing less than two units from the higher–ranked model), and determined each predictor’s relative importance in this subset by adding the Akaike weights of those models where it appeared. To further contrast the influence of each parameter in the model subset, we examined their model–averaged weighted effect sizes or β estimates. When the 95% confidence intervals (CIs) of a

149

model–averaged β estimate for a particular parameter overlapped zero, we considered it unlikely that the parameter had much influence on the response variable. Analyses were performed using the lmtest, MuMIn, and glmulti packages in R (R Development Core Team, 2010; Zeileis & Hothorn, 2002; Barton, 2013; Calcagno, 2013), as well as SPSS v. 22. Results We found that 89% of the eggs laid in the 644 nests included in this study produced live hatchlings, and 86% of these hatchlings eventually fledged. Moreover, in 48% of the nests, all the hatchlings eventually fledged and among the remaining nests (i.e., with at least one nestling lost prior to fledging), an average of 73% of the hatchlings left the nest. Mean annual number of fledglings per nest during the study period was 6.14 ± 0.88 (mean of yearly means; range: 4.25–7.71; n = 22 years). Considering the initial model set (128 models), two predictor variables showed a higher probability of inclusion in the best approximating model of the number of fledglings, as given by the sum of Akaike weights of the models in which they appear: number of hatchlings (ƩWi = 0.784) and clutch size (ƩWi = 0.648). Egg size (ƩWi = 0.545) had intermediate importance, whereas number of unhatched eggs (ƩWi = 0.432), hatching date (ƩWi = 0.320), and mean ambient temperatures during the first 15 days after hatching (ƩWi = 0.278) and during the first five days after hatching (ƩWi = 0.273) had lower importance. Four models fitted the data equally well, as given by their AICc scores. This set of best–fitting models included clutch size, egg size, number of hatchlings and number of unhatched eggs as explanatory variables (table 1, models 1, 2, 3, and 4). Overall, a total of 22 additional models had AICc values within two units of the best–ranked models. They generally explained 46–48% of the deviance of the null model. The combined Akaike weight of this subset of best–fitting models was 0.625. According to the model–averaged coefficients of the predictor variables (table 2), the number of fledglings decreased with hatching date and number of unhatched eggs, and increased with egg size, number of hatchlings, temperatures during the first five and 15 days after hatching. The relative importance of the predictor variables in the model– averaged subset, calculated by the sum of the Akaike weights over all the models in which they appear, was high for number of hatchlings (ƩWi = 0.77), clutch size (ƩWi = 0.69), number of unhatched eggs (ƩWi = 0.69), and egg size (ƩWi = 0.63). Of these parameters, only the number of hatchlings had a strong effect size (i.e., β estimate), with CIs ranging from 0.105 to 0.184, whereas clutch size, number of unhatched eggs and egg size had CIs overlapping zero (table 2). The remaining variables were of low importance and their 95% CIs overlapped zero (table 2): hatching date (ƩWi = 0.22), mean ambient temperatures during the first five and 15 days after hatching (both ƩWi = 0.10). The simplest best–fitting

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Table 1. Top–ranked models (i.e., with ∆AICc < 2) and last ranked model used to test the effect of temperature and reproductive parameters on the number of fledglings: CS. Clutch size; ES. Egg size; NH. Number of hatchlings; NUE. Number of unhatched eggs; T5. Mean ambient temperatures during the first five days after hatching; T15. Mean ambient temperatures during the first 15 days after hatching; AICc. Corrected Akaike Information Criterion for small sample sizes; ∆AICc. Difference in AICc values in relation to model 1. Tabla 1. Los modelos mejor puntuados (es decir, con ∆AICc < 2) y el último modelo empleados para analizar el efecto de la temperatura y los parámetros reproductivos en el número de volantones: CS. Tamaño de puesta; ES. Tamaño de huevo; NH. Número de huevos eclosionados; NUE. Número de huevos sin eclosionar; T5. Promedio de la temperatura ambiental durante los primeros cinco días después de la eclosión; T15. Promedio de la temperatura ambiental durante los primeros 15 días después de la eclosión; AICc. Criterio de Información de Akaike corregido para muestras pequeñas; ∆AICc. Diferencia de los valores de AICc en relación con el modelo 1. Model

Parameters included

AICc

∆AICc

Akaike weight

CS, ES, NH

2562.307

0.04166

CS, ES, NUE

2562.307

0.04166

ES, NH, NUE

2562.307

0.04166

CS, ES, NH, NUE

2562.307

0.04166

NH, NUE

2562.543

0.236

0.03702

CS, NH

2562.543

0.236

0.03702

CS, NUE

2562.543

0.236

0.03702

CS, NH, NUE

2562.543

0.236

0.03702

ES, NH

2563.106

0.799

0.02794

2563.867

1.560

0.01770

CS, HD, ES, NH

2563.969

1.662

0.01814

CS, HD, ES, NUE

2563.969

1.662

0.01814

HD, ES, NH, NUE

2563.969

1.662

0.01814

CS, HD, ES, NH, NUE

2563.969

1.662

0.01814

CS, HD, NH

2564.200

1.893

0.01617

CS, HD, NUE

2564.200

1.893

0.01617

HD, NH, NUE

2564.200

1.893

0.01617

CS, HD, NH, NUE

2564.200

1.893

0.01617

T5, CS, ES, NH

2564.236

1.929

0.01588

T5, ES, NH, NUE

2564.236

1.929

0.01588

T5, CS, ES, NH, NUE

2564.236

1.929

0.01588

T5, CS, ES, NUE

2564.236

1.929

0.01588

T15, CS, ES, NH

2564.259

1.952

0.01569

T15, CS, ES, NUE

2564.259

1.952

0.01569

T15, ES, NH, NUE

2564.259

1.952

0.01569

T15, CS, ES, NH, NUE

2564.259

1.952

0.01569

128

T5, HD

2776.394

214.1

1.3527E–48

function explaining the relationship between the number of fledglings (NF) and the number of hatchlings (NH) was linear (NF = 0.8891 NH – 0.1359, r = 0.983, P < 0.001; fig. 1).

There was a significant, negative relationship between mean nestling mass (M) and the number of hatchlings (NH) per nest (M = –0.2318 NH + 18.349, r = 0.282, P < 0.001; fig. 2). We also found

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Table 2. Model–averaged coefficients of the predictor variables from the subset of best–fitting models. (For abbreviations, see table 1.) Tabla 2. Coeficientes promediados de los factores predictores incluidos en el subconjunto de modelos con mejor ajuste. (Para las abreviaturas, véase la tabla 1.) Parameter

Estimate

95% CI

Adjusted SE

Lower

Upper

Z value

P(>|Z|)

T15

0.003135

0.01118

0.01120

–0.01882

0.02509

0.280

0.780

–0.001254

0.002065

0.002069

–0.005309

0.002802

0.606

0.545

0.0002104

0.0001381

0.0001384

–0.00006084 0.0004816

1.520

0.128

0.1448

0.02010

0.02012

0.1054

0.1843

7.197

<2E–16

0.002941

0.009218

0.009235

–0.01516

0.02104

0.319

0.750

0.02048

0.07555

0.07556

–0.1276

0.1686

0.271

0.786

NUE

–0.09400

0.06468

0.06469

–0.2208

0.03279

1.453

0.146

a non–significant trend for mean nestling tarsus length (T) to decrease with the number of nestlings (T = –0.0269 NH + 19.582, r = 0.074, P = 0.077). Discussion

Number of fledglings

The number of hatchlings had a significant, positive effect on fledgling production, so that larger broods eventually yielded more fledglings. In this long–term approach, we did not find other significant predictors of the number of fledglings produced per nest in the

13 12 11 10 9 8 7 6 5 4 3 2 1 0

studied population, although other predictors are likely relevant in certain years, depending on environmental conditions. Several studies have analyzed the importance of brood size for nestling growth and survival (Groves, 1984; Coulson & Porter, 1985; Burness et al., 2000; Benharzallah et al., 2015), although its effect, either positive or negative, is dependent on parental quality and resource availability (Gebhardt–Henrich & Richner, 1998). Taking care of large broods is energetically demanding, forcing parents to adjust clutch sizes based on their ability to rear the resulting chicks

2 1

4 5 6 7 8 9 10 Number of hatchlings

152

154

Fig. 1. Average number of fledglings (± SE) produced per nest in relation to the number of hatchlings. Sample sizes above error bars refer to the number of nests. Fig. 1. Promedio de volantones producido por nido (± EE) en relación con el número de eclosiones. Los tamaños muestrales indicados sobre las barras de error se refieren al número de nidos.

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Mean nestling mass (g)

131 137

16 14 12 10

4 5 6 7 8 Number of hatchlings

Fig. 2. Relationship between mean nestling mass at day 15 (± SE) and the number of hatchlings per nest. Sample sizes above error bars refer to the number of nests. Fig. 2. Relación entre el peso medio de los pollos en el día 15 (± EE) y el número de eclosiones por nido. Los tamaños muestrales indicados sobre las barras de error se refieren al número de nidos.

efficiently (Lack, 1947; Murphy & Haukioja, 1986; Wellicome et al., 2013). Parental age has been positively correlated with chick growth, either as a result of increased experience (Coulson & Porter, 1985) or reproductive effort (Pugesek, 1995). Moreover, parental breeding performance is necessarily linked to the ability to provide food to the developing chicks, so that limitations in food supply under resource–poor scenarios may carry over restrictions in nestling growth and/or survival inside the nest (Gebhardt–Henrich & Richner, 1998; Wellicome et al., 2013). In our study, most chicks hatched per nest survived to leave the nest, suggesting a good adjustment between brood size and resource availability in the studied population in the long term. In addition, the mean annual number of fledglings was comparable to that of other areas within the same latitudinal range (Sanz, 2002; Atiénzar et al., 2012). The demands of raising large broods may have limited nestling growth, as revealed by the negative relationship between number of hatchlings and mean mass at fledging. In this study, nestling quality appeared to be compromised by nestling quantity. This result agrees with previous observational studies, where mean nestling mass has been shown to decline with increasing brood size (Perrins, 1965 reviewed in Klomp, 1970). Moreover, experimentally–enlarged broods produced lighter fledglings in several manipulative experiments (Smith et al., 1989; Tinbergen & Daan, 1990; Pettifor et al., 2001; Hõrak, 2003). In this population, previous studies revealed that adults reduced the number of feeding visits per nestling as brood size increased (Barba et al., 2009), and nestling growth rate decreased as clutch size increased (Barba et al., 1993). None of the other predictors considered in this study had a significant effect on the number of fledglings

in the long term. Therefore, nestling survival during the analyzed period seems to have been determined by brood size, regardless of the importance that, to a greater or lesser extent, other factors may have during certain years depending on particular environmental conditions. Adverse weather events prior to incubation, for instance, may negatively affect egg volume and clutch size, or bring about delays in hatching dates (Monrós et al., 1998). These breeding alterations may eventually affect nestling development and/or survival to fledging (Monrós et al., 1998; Krist, 2011; Etezadifar & Barati, 2015). Additionally, suboptimal nest temperatures during the nestling stage as a result of episodic hot or cold spells may directly handicap chick fitness and ultimately increase mortality (Belda et al., 1995; Takagi, 2001). Based on our results, the weak predictive power of these factors could be explained by the annual variability in the intensity of their effects on fledging production. In conclusion, brood size emerged as the best predictor of the number of fledglings produced per nest in our Mediterranean great tit population. Larger broods produced more fledglings, although mass prior to fledging may have been compromised. The relatively weak effect sizes of the remaining potential predictors of fledging output could be a consequence, at least in part, of their dependence on environmental variation between years. Acknowledgments We wish to thank all the people who helped with the fieldwork over the study period, the Spanish Ministry of Agriculture, Food and Environment for providing nest boxes, and the State Meteorological

Animal Biodiversity and Conservation 39.2 (2016)

Agency (AEMET) for providing temperature records of our study site. This work was supported by project CGL2013–48001–C2–1–P (Spanish Ministry of Science and Innovation). Samuel Rodríguez received a FPU grant (AP2010–5723) from the Spanish Ministry of Education, Culture and Sports. References Andreu, J. & Barba, E., 2006. Breeding dispersal of great tits Parus major in a homogeneous habitat: effects of sex, age and mating status. Ardea, 94: 45–58. Atiénzar, F., Álvarez, E. & Barba, E., 2012. Carbonero común – Parus major. In: Enciclopedia Virtual de los Vertebrados Terrestres: 1–43 (A. Salvador & M. B. Morales, Eds.). Museo Nacional de Ciencias Naturales, Madrid. Barba, E., Atiénzar, F., Marín, M., Monrós, J. S. & Gil–Delgado, J. A., 2009. Patterns of nestling provisioning by a single–prey loader bird, great tit Parus major. Bird Study, 56: 187–197. Barba, E., Gil–Delgado, J. A. & Monrós, J. S., 1993. Factors affecting nestling growth in the great tit (Parus major). Ardeola, 40: 121–131. Barton, K., 2013. MuMIn: Multi–Model Inference. R package version 1.9.13. Url: http://CRAN.R–project.org/package=MuMIn Belda, E. J., Ferrandis, P. & Gil–Delgado, J. A., 1995. Clutch size variation and nest failure of the serin Serinus serinus in orange groves. Ardeola, 42: 1–10. Benharzallah, N., Si Bachir, A., Taleb, F. & Barbraud, C., 2015. Factors affecting growth parameters of white stork nestlings in eastern Algeria. Journal of Ornithology, 156: 601–612. Birkhead, T. R. & Nettleship, D. N., 1982. The adaptative significance of egg size and laying date in thick–billed murres (Uria lomvia L.). Ecology, 63: 300–306. Bradbury, R. B., Wilson, J. D., Moorcraft, D., Morris, A. J. & Perkins, A. J., 2003. Habitat and weather are weak correlates of nestling condition and growth rates of four UK farmland passerines. Ibis, 145: 295–306. Burness, G. P., McClelland, G. B., Wardrop, S. L. & Hochachka, P. W., 2000. Effect of brood size manipulation on offspring physiology: an experiment with passerine birds. Journal of Experimental Biology, 203: 3513–3520. Burnham, K. P. & Anderson, D. R., 1998. Multimodel inference: understanding AIC and BIC in model selection. Sociological Methods & Research, 33: 261–304. Calcagno, V., 2013. glmulti: Model selection and multimodel inference made easy. R package version 1.0.7. Url: http://CRAN.R–project.org/ package=glmulti Catry, P., Ratcliffe, N. & Furness, R. W., 1998. The influence of hatching date on different life–history stages of great skuas Catharacta skua. Journal of Avian Biology, 29: 299–304. Coulson, J. C. & Porter, J. M., 1985. Reproductive

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Aspectos ecológicos de la anidación de Caiman crocodilus chiapasius (Bocourt, 1876) en la reserva de la biosfera La Encrucijada, México G. A. González–Desales, O. Monroy–Vilchis, P. Charruau & M. M. Zarco–González González–Desales, G. A., Monroy–Vilchis, O., Charruau, P. & Zarco–González, M. M., 2016. Aspectos ecológicos de la anidación de Caiman crocodilus chiapasius (Bocourt, 1876) en la reserva de la biosfera La Encrucijada, México. Animal Biodiversity and Conservation, 39.2: 155–160. Abstract Ecological aspects of nesting in Caiman crocodilus chiapasius (Bocourt 1876) in La Encrucijada Biosphere Reserve, Mexico.— Studies on caiman, Caiman crocodilus chiapasius, in Mexico are scarce. The present study was conducted to evaluate the key characteristics regarding the reproductive ecology of caiman in Mexico. We conducted nest searches from April to September 2014. We observed that nests were built in June and that hatching occurred in September and October. The phase of the moon had an effect on nesting events. The height of the nest, the distance to the nearest tree, and the distance from the top of the nest to the first egg were related to hatching success and incubation temperature. Key words: Caiman, Nesting, Description of nests, Description of eggs Resumen Aspectos ecológicos de la anidación de Caiman crocodilus chiapasius (Bocourt, 1876) en la reserva de la biosfera La Encrucijada, México.— Existen pocos estudios sobre el caimán de anteojos, Caiman crocodilus chiapasius, realizados en México. En el presente estudio evaluamos las características clave de la ecología reproductiva del caimán en México. Se realizó una búsqueda de nidos entre abril y septiembre de 2014, y se observó que la construcción de los mismos tiene lugar en junio y las eclosiones, en septiembre y octubre. La fase lunar influye en la anidación. Asimismo, la altura del nido, la distancia al árbol más cercano y la distancia desde el borde superior del nido al primer huevo están relacionadas con el éxito de eclosión y la temperatura de incubación. Palabras clave: Caimán, Anidación, Descripción de nidos, Descripción de huevos Received: 8 IX 15; Conditional acceptance: 27 X 15; Final acceptance: 11 III 16 G. A. González–Desales, O. Monroy–Vilchis & M. M. Zarco–González, Centro de Investigación en Ciencias Biológicas Aplicadas, Univ. Autónoma del Estado de México, México.– P. Charruau, Centro del Cambio Global y la Sustentabilidad en el Sureste A.C., Tabasco, México. Corresponding author: O. Monroy–Viilchis. E–mail: tavomonroyvilchis@gmail.com

En América, Caiman crocodilus tiene una amplia distribución (Casas–Andreu, 1995). C. c. chiapasius es la subespecie con distribución en México, restringida al estado de Chiapas (Escobedo–Galván et al., 2015), cuyas poblaciones están amenazadas en este país por las actividades antropogénicas (Aguilar–Galindo, 2005). La determinación del sexo en C. crocodilus es por temperatura (Lang & Andrews, 1994), lo que anteriormente se conocía como periodo termosensible (PTS) y que aún no se ha determinado. Respecto a la anidación, solo existen datos

anecdóticos (Álvarez del Toro, 1974), por lo que nos propusimos caracterizar los parámetros clave de la anidación de C. c. chiapasius en la reserva de la biosfera La Encrucijada, en México, y determinar los factores que influyen en las etapas de anidación y el éxito de eclosión. La reserva de la biosfera La Encrucijada se ubica en la región costera de Chiapas, ocupa 144.868 hectáreas de superficie divididas en dos zonas núcleo, El Palmarcito y La Encrucijada (INE–SEMARNAP, 1999; fig. 1); la búsqueda de nidos se llevó a cabo en esta última.

González–Desales et al.

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Nidos de caimán Zona de amortiguamiento La Encrucijada 4

12 km

Fig. 1. Ubicación de la reserva de la biosfera La Encrucijada, México, y localización de los nidos de Caiman crocodilus chiapasius. Fig. 1. Outline of La Encrucijada Biosphere Reserve, Mexico, and location of the nests of Caiman crocodilus chiapasius.

Se buscaron nidos dos o tres días por semana entre los meses de abril y julio y en septiembre de 2014. Se identificaron los montículos antes de que se terminara su construcción, lo que permitió estimar el tiempo de construcción y la fecha de oviposición. Se registró la fase lunar de las etapas de anidación. Al confirmar la presencia de huevos, se midió la distancia del centro del montículo al cuerpo de agua y al árbol más cercanos. La identificación del material de construcción se realizó por comparación de las plantas encontradas en los nidos con la vegetación circundante, considerando las especies de la zona (INE–SEMARNAP, 1999). Posteriormente, se abrió el nido para medir la cámara de incubación. Se obtuvieron el peso y las dimensiones de los huevos. Se utilizaron registradores de datos (HOBO Pendant© Temperature/Alarm UA–001–08) colocados a la mitad de la cámara en siete nidos para medir la temperatura de incubación cada media hora. Al final de la temporada de anidación se contaron los huevos no eclosionados para calcular el éxito de eclosión y de anidación. Para determinar la relación entre las características de los nidos, el éxito de eclosión, la temperatura de incubación y el tiempo de anidación, se realizó una correlación de Spearman, primero con los nidos encontrados en islotes menores de 3 m de diámetro y, posteriormente, con los mayores de 3 m. Se realizó un análisis de la varianza de las características de los huevos para evaluar las diferencias entre nidos y una correlación de Pearson entre estas características. Se

realizó una x2 para evaluar el efecto de la luna en las etapas de anidación, primero por etapa y posteriormente en conjunto. La evaluación de las diferencias en la temperatura de incubación entre nidos se realizó mediante un análisis de la varianza. Para comparar las temperaturas de incubación y las del PTS sugerido para C. latirsotris (Piña et al., 2007), realizamos una t de Student. Se localizaron 19 nidos en 11 zonas de anidación, dejando una separación de 150 m entre nidos (Charruau et al., 2010). Nueve de los nidos fueron depredados y 10, eclosionaron. Se contabilizaron 323 huevos de 14 nidos. Los nidos se encontraron a 2,2 ± 1,37 m de algún cuerpo de agua y a 0,74 ± 1,05 m de algún árbol (tabla 1). La construcción de los nidos inició en junio, principalmente en cuarto menguante (73,68%), y las oviposiciones se realizaron en junio y julio, generalmente en luna nueva (42,11%). La incubación duró 80,4 ± 9,8 días (n = 10) y las eclosiones ocurrieron en septiembre y octubre, principalmente en luna nueva (50%). La fase lunar es importante en las etapas de anidación (x2 = 31,26; gl = 6; p < 0,001), especialmente en la construcción (x2 = 27,52; gl = 3; p < 0,001) y la oviposición (x2 = 8,15; gl = 3; p < 0,05). Todos los nidos fueron de tipo montículo y se identificaron 25 especies de plantas utilizadas como material de construcción (tabla 2). La temperatura de incubación varía entre 30,57 y 32,54ºC de media, y difiere significativamente entre nidos (F = 880,80; gl = 6,25382; p < 0,01), a diferen-

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Tabla 1. Caracterización de los nidos y atributos de las nidadas de Caiman crocodilus chiapasius. Table 1. Characterization of the nests and features of clutches of Caiman crocodilus chiapasius.

Promedio

Características externas de los nidos

Distancia del nido al árbol más cercano (cm)

± DE

Intervalo

74,69

105,73

13–430

Distancia del nido al cuerpo de agua más cercano (cm) 228,28

137,86

42–580

Altura nido (cm)

39,72

10,84

23–59

Largo mayor del nido (cm)

159,46

40,04

126–291

Largo menor del nido (cm)

106,82

18,56

73,1–132

Profundidad del tope del nido al primer huevo (cm)

10,67

3,85

5,6–19,4

Características internas de los nidos Largo mayor cámara (cm)

21,29

3,18

14,9–25,9

Largo menor cámara (cm)

2,96

12,1–23,6

Altura cámara (cm)

12,04

2,88

7,1–16,3

Temperatura de incubación (ºC)

31,5

1,94

27,07–35,9

36–67

323

Características de los huevos Peso del huevo (g)

48,93

6,59

Largo mayor del huevo (mm)

60,3

3,73

49,9–74,2 323

Largo menor del huevo (mm)

36,91

1,74

31,2–40,8 323

Proporción largo/ancho del huevo

1,63

0,06

1,57–1,79

Número de huevos por nido

23,78

3,35

17–28

Número de huevos no eclosionados

3,2

2,48

0–8

Número de huevos eclosionados

21,6

2,45

18–26

Éxito de eclosión (%)

87,6

8,88

70,37–100

Éxito de anidación (%)

47,4

45,25

0–100

Tiempo de incubación

80,4

9,86

63–93

cia de las temperaturas promedio del PTS sugerido (tabla 3; t = 0,555; gl =12; p > 0,05). Teniendo en cuenta el patrón de DST (determinación sexual por temperatura) de C. crocodilus (Lang & Andrews, 1994), las temperaturas del PTS sugieren que en cuatro nidos se favoreció la producción de hembras; en dos, de machos; y en uno, de ambos sexos (fig. 2). En los nidos de islotes menores de 3 m de diámetro, las variables que presentaron una correlación significativa fueron la altura del montículo y su distancia al árbol más cercano (r = –0,90, p < 0,01). En los nidos de islotes mayores de 3 m de diámetro, se observó una correlación entre la temperatura de incubación y las variables siguientes: (a) la altura del montículo: la temperatura es más elevada cuando el montículo es bajo (r = –1, p < 0,01); (b) el ancho de la cámara: la temperatura es mayor cuanto más pequeña es la cámara (r = –1; p < 0,01); (c) la distancia al árbol más cercano: la temperatura es mayor cuanto más lejos esté el nido del árbol (r = –1; p < 0,01); y (d) los días de incubación: son más días cuando la temperatura de la cámara es alta (r = 1, p < 0,01). También se observó una correlación entre la distancia

del primer huevo al borde superior del montículo con (a) la altura del nido: cuando el nido es alto la cantidad de material de construcción depositado sobre la primera fila de huevos es menor (r = –0,94, p = 0,03); y (b) el éxito de eclosión, que aumenta cuando hay más material de construcción (r = 0,92, p = 0,03). El peso de los huevos difirió significativamente entre nidos (F = 158,89; gl = 13,309; p < 0,01), así como su longitud (F = 38,95; gl = 13,309; p < 0,01) y anchura (F = 89,54; gl = 13,309; p < 0,01). Existe una correlación entre el peso y la longitud (r = 0,75; p < 0,01) y entre el peso y la anchura (r = 0,86; p < 0,01), así como entre la longitud y la anchura del huevo (r = 0,49; p < 0,01). Los nidos eclosionados y depredados no presentaron diferencias significativas en ninguna de las variables evaluadas. Se presentan los primeros datos sobre ecología de anidación para la subespecie C. c. chiapasius. Se observó que el caimán construye el nido en junio, a diferencia de lo observado para C. c. fuscus en Venezuela y Costa Rica (Staton & Dixon, 1977; Allsteadt, 1994). No existe información sobre el material de construcción del nido de C. c. chiapasius, aunque sí la hay

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Tabla 2. Especies vegetales identificadas como material de construcción en los nidos de caimán de anteojos en la reserva de la biosfera La Encrucijada, México. Table 2. Plant species identified as construction material in nests of spectacled caiman in La Encrucijada Biosphere Reserve, Mexico.

Familia

Especie

Nombre local

Acanthaceae

Avicennia germinans

Madre sal o mangle negro

Amaryllidaceae

Crinum erubescens

Lirio

Araceae

Pistia stratiotes

Oreja

Arecaceae

Attalea rostrata

Palma manaca

Sabal mexicana

Palma real

Acrocomia aculeata

Coyol

Cocos nucifera

Palma de coco

Bombacaceae

Pachira acuatica

Zapoton

Bromeliaceae

Bromelia plumieri

Piñuela

Burseraceae

Bursera simaruba

Chocohuite

Combretaceae

Conocarpus erectus

Botoncillo o mangle negro

Laguncularia racemosa

Mangle blanco

Fabaceae

Machaerium seemannii

Tamarindillo

Gramineae

Paspalum sp.

Pasto

Lemnaceae

Lemna aequinoctialis

Chichicastle

Spirodela polyrrhiza

Lenteja de agua

Meliaceae

Cedrela odorata

Cedro

Trichilia havanensis

Limoncillo

Moraceae

Ficus involuta

Matapalo o amate

Polygonaceae

Coccoloba barbadensis

Papaturro

Pteridaceae

Acrostichum aureum

Helecho

Rhizophoraceae

Rizophora mangle

Mangle rojo

Sapotaceae

Manilkara zapota

Chicozapote

Sterculiaceae

Sterculia apetala

Castaño

Vitaceae

Vitis bourgaeana

Bejuco de agua

para C. c. fuscus (Staton & Dixon, 1977). Es probable que las hembras utilicen plantas específicas, ya que donde se han observado depredadores potenciales, los nidos presentaban plantas con espinas (Bromelia plumieri); asimismo, se ha observado que los nidos de aves con material espinoso son menos depredados (Lindell, 1996). El tiempo de incubación (63–93 días) es similar al registrado en Venezuela (70–75 días; Staton & Dixon, 1977), en Costa Rica (73–100 días; Allsteadt, 1994) y en México (75–110 días; Álvarez del Toro, 1974); aunque algunos nidos eclosionaron entre 63 y 69 días. La distancia de los nidos al cuerpo de agua más cercano es menor a la registrada para C. c. fuscus (3 m; Cintra, 1988), C. yacare (2,9 m; Allsteadt, 1994) y Melanosuchus niger (17,1–58,5 m; Villamarín–Jurado & Suárez, 2007). El tamaño de la cámara de incubación

es similar al observado por Allsteadt (1994), pero la altura entre el borde superior del montículo y el primer huevo es menor. Las hembras pueden elegir los sitios de anidación, lo que influye en la temperatura y la humedad de incubación, y repercute en la sobrevivencia de los embriones (Charruau, 2012). El número de huevos es similar a lo observado para la especie, pero son más pequeños (Staton & Dixon, 1977; Cintra, 1988; Allsteadt, 1994; tabla 1), lo que puede estar relacionado con la productividad primaria (González–Desales, 2015) o el tamaño de las hembras (Thorbjarnarson, 1996). No existe información para C. crocodilus sobre el efecto de la fase lunar en la construcción del nido, la oviposición ni la eclosión, y para otros cocodrilos son pocos los estudios sobre el tema (Casas–Andreu, 2003; Seijas & Acosta, 2014). Nuestros resultados

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Tabla 3. Temperaturas de incubación y del PTS (periodo termosensible) sugerido: PSE. Proporción sexual estimada. Table 3. Temperatures of incubation and suggested PTS (thermosensitive period): PSE. Estimated Sex ratio. Nido 1 2 3 4 5 6 7

Tª incubación (ºC) 30,73 30,93 32,54 32,11 30,57 32,38 30,83

DE 1,56 1,54 2,11 1,76 1,23 2,20 1,49

Tª PTS (ºC) 30,78 30,66 32,29 31,50 30,42 32,05 30,33

indican que las etapas de anidación no se producen al azar (x2 = 31,26; gl = 6; p < 0,001). Cuando las crías tardan más tiempo en eclosionar, la temperatura dentro de la cámara también es mayor, a diferencia de lo observado para la especie en un medio artificial (Lang & Andrews, 1994). Cuando el montículo es alto (> 39,72 cm), la distancia entre el primer huevo y el borde superior del montículo es menor, esto podría sugerir que las hembras procuran hacer más alto el montículo para disminuir el riesgo de inundación o colocar material sobre la cámara para disminuir la

DE 1,72 1,61 2,33 1,58 1,36 2,17 1,11

PSE Cerca de 100% de hembras Cerca de 100% de hembras Cerca de 100% de machos 50% de ambos sexos Cerca de 100% de hembras Cerca de 100% de machos Cerca de 100% de hembras

depredación. En otros caimanes, la depredación e inundación son los factores principales en la pérdida de nidos (Cintra, 1988; Allstead, 1994; Villamarín–Jurado & Suárez, 2007; Campos & Mourão, 2014). El éxito de anidación (47,4%) se ve afectado por la depredación de huevos, que depende de la abundancia de depredadores y del cuidado que dedica la hembra, como se ha observado en C. yacare (Campos & Mourão, 2014). Las temperaturas obtenidas para el PTS estimado sugieren que la producción de sexos en el área de estudio está sesgado hacia las hembras.

34 33 Nido Nido Nido Nido Nido Nido Nido

32 31 30

1 2 3 4 5 6 7

25 IX 2014

18 IX 2014

11 IX 2014

4 IX 2014

28 VIII 2014

21 VIII 2014

14 VIII 2014

7 VIII 2014

31 VII 2014

24 VII 2014

17 VII 2014

10 VII 2014

29 3 VII 2014

Temperatura de incubación (ºC)

Fig. 2. Temperaturas de incubación de siete nidos de Caiman crocodilus chiapasius en la reserva de la biosfera La Encrucijada, México. Fig. 2. Incubation temperatures of seven Caiman crocodilus chiapasius nests in La Encrucijada Biosphere Reserve, Mexico.

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Agradecimientos Al pueblo mexicano que financió a través del Consejo Nacional de Ciencia y Tecnología (beca 360827) y de la Universidad Autónoma del Estado de México (3841/2014/CIA). Al Crocodile Specialist Group–IUCN por la beca otorgada. A 'Tío Abel', Humberto Yee y familia por prestar sus instalaciones para realizar este trabajo. Referencias Aguilar–Galindo, A., 2005. Evaluación del estado de conservación del Caiman crocodilus fuscus (Mertens, 1943) durante el año 2003–2004, en el sistema lagunar de Chantuto, reserva de la biosfera La Encrucijada, Chiapas, México. Tesis de Licenciatura, Universidad Autónoma Metropolitana, Xochimilco, México. Allsteadt, J., 1994. Nesting ecology of Caiman crocodilus in Caño Negro, Costa Rica. Journal of Herpetology, 28(1): 12–19. Álvarez del Toro, M., 1974. Los Crocodylia de México (Estudio Comparativo). Eds. Instituto Mexicano de Recursos Naturales Renovables, A.C. México. Campos, Z. & Mourão, G., 2014. Camera traps capture images of predators of Caiman crocodilus yacare eggs (Reptilia: Crocodylia) in Brazil´s Pantanal wetlands. Journal of Natural History, 49(15–16): 977–982. Doi: 10.1080/00222933.2014.930757. Casas–Andreu, G., 1995. Los cocodrilos de México como recurso natural. Presente, pasado y futuro. Revista de la Sociedad Mexicana de Historia Natural, 46: 153–162. – 2003. Ecología de la anidación de Crocodylus acutus (Reptilia: Crocodylidae) en la desembocadura del río Cuitzmala, Jalisco, México. Acta Zoológica Mexicana (n.s.), 89: 111–128. Charruau, P., 2012. Microclimate of American crocodile nests in Banco Chinchorro biosphere reserve, Mexico: Effect on incubation length, embryos survival and hatchlings sex. Journal of Thermal Biology, 37: 6–14. Charruau, P., Thorbjarnarson, J. B. & Hénaut, Y.,

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2010. Tropical cyclones and reproductive ecology of Crocodylus acutus Cuvier, 1807 (Reptilia: Crocodilia: Crocodylidae) on a Caribbean atoll in Mexico. Journal of Natural History, 44(11–12): 741–761. Doi: 10.1080/00222930903490993 Cintra, R., 1988. Nesting ecology of the Paraguayan caiman (Caiman yacare) in the Brazilian Pantanal. Journal of Herpetology, 22(2): 219–222. Escobedo–Galván, A. H., Casas–Andreu, G. & Barrios–Quiroz, G., 2015. On the occurrence of Caiman crocodilus in Oaxaca, Mexico: a misunderstanding for over 140 years. Mesoamerican Herpetology, 2(2): 220–223. González–Desales, G. A., 2015. Ecología de anidación de cocodrilianos en la reserva de la biosfera La Encrucijada, México. Tesis de Maestría, Universidad Autónoma del Estado de México. INE–SEMARNAP, 1999. Programa de manejo Reserva de la Biosfera La Encrucijada, México. Secretaria de Medio Ambiente, Recursos Naturales y Pesca, Instituto Nacional de Ecología. Lang, J. W. & Andrews, H. V., 1994. Temperature– dependent sex determination in crocodilians. The Journal of Experimental Zoology, 270: 28–44. Lindell, C., 1996. Benefits and costs to Plain–fronted Thornbirds (Phacellodomus rufifrons) of interactions with avian nest associates. Auk, 113: 565–577. Piña, C., Larriera, A., Siroski, P. & Verdade, L. M., 2007. Cranial sexual discrimination in hatchling broad–snouted caiman (Caiman latirostris). Iheringia, Série Zoologia, 97(1): 17–20. Seijas, A. & Acosta, J. G., 2014. Cronología de anidación de caimán de Orinoco (Crocodylus intermedius). Boletín de la Academia de Ciencias Físicas, Matemáticas y Naturales, 74(2): 39–52. Staton, M. & Dixon, J. R., 1977. Breeding biology of the spectacled caiman, Caiman crocodilus crocodilus, in the Venezuelan Llanos. U. S. Fish and Wildlife Service. Wildlife Research, Report 5. Thorbjarnarson, J. B., 1996. Reproductive characteristics of the Order Crocodylia. Herpetologica, 52: 8–24. Villamarín–Jurado, F. & Suárez, E., 2007. Nesting of the black caiman (Melanosuchus niger) in Northeastern Ecuador. Journal of Herpetology, 41(1): 164–167.

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On the road of dung: hypothetical dispersal routes of dung beetles in the circum–Sicilian volcanic islands M. Tonelli, R. Agoglitta, H. Dawson & M. Zunino

Tonelli, M., Agoglitta, R., Dawson, H. & Zunino, M., 2016. On the road of dung: hypothetical dispersal routes of dung beetles in the circum–Sicilian volcanic islands. Animal Biodiversity and Conservation, 39.2: 161–171. Abstract On the road of dung: hypothetical dispersal routes of dung beetles in the circum–Sicilian volcanic islands.— We analysed dung beetle communities on ten volcanic islands located around Sicily (Italy) to identify the most probable dispersal routes in the colonization of these islands. Assuming two scenarios, we analysed the dung beetle com� munities through the coefficient of dispersal direction DD2. Our results suggest that dispersal fluxes do not strictly follow the 'stepping stone' dynamic. Lipari and Vulcano are the likely core source areas for the north–of–Sicily area. In the Sicily Channel, Linosa appears to have been the main target area with three equivalent fluxes from Tunisia, Sicily, and Malta, while the fauna of Pantelleria resulted from their interchange and proximity to Tunisian fauna. In light of the congruence of our results with the known history of human movements and colonization, we propose a likely human contribution to the genesis of the dung beetle fauna of the circum–Sicilian volcanic islands. Key words: Dung beetles, Island biogeography, Thorectes intermedius, Stepping stone dispersal Resumen En el camino del estiércol: rutas de dispersión hipotéticas de los escarabajos coprófagos de las islas volcánicas circumsicilianas.— Se han analizado las comunidades de escarabajos del estiércol que habitan diez islas vol� cánicas localizadas alrededor de Sicilia (Italia), con el propósito de determinar las posibles rutas de dispersión que se siguieron en la colonización de estas islas. Utilizando dos supuestos diferentes, hemos analizado las comunidades de escarabajos coprófagos mediante el coeficiente de dirección de la dispersión DD2. Los resultados obtenidos sugieren que los flujos de dispersión no han seguido estrictamente una dinámica de 'stepping stone' (puntos de paso). Lípari y Vulcano habrían sido las principales fuentes de colonización de las zonas del norte de Sicilia. En el canal de Sicilia, Linosa habría sido la principal zona de destino con tres flujos equivalentes pro� cedentes de Túnez, Sicilia y Malta, mientras que la fauna de Pantelaría se explicaría por la conexión y cercanía de la isla con Túnez. Debido a la fuerte congruencia de nuestros resultados con la historia de los movimientos y colonizaciones humanas en estas zonas, proponemos que probablemente el factor antrópico haya contribuido a la génesis de la fauna de escarabajos del estiércol de las islas volcánicas circumsicilianas. Palabras clave: Escarabajos coprófagos, Biogeografía insular, Thorectes intermedius, Dispersión por puntos de paso Received: 29 X 15; Conditional acceptance: 25 XI 15; Final acceptance: 17 III 16 Mattia Tonelli, Dipto. di Scienze Pure e Applicate: DiSPeA (Previously DiSTeVA), Univ. degli Studi di Urbino 'Carlo Bo', Urbino (PU), Italy.– Rossana Agoglitta, via R. Caravaglios, 13, Castelvetrano (TP), Italy.– Helen Dawson, Cluster of Excellence TOPOI, Freie Univ. Berlin, Berlin, Germany.– Mario Zunino, Polo Universitario Asti Studi Superiori, Scuola di Biodiversità, Asti, Italy. Corresponding author: Mattia Tonelli. E–mail: m.tonelli3@campus.uniurb.it

ISSN: 1578–665 X eISSN: 2014–928 X

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Introduction Islands are among the areas of the world that have most aroused the curiosity of naturalists, long attracted by their peculiarities such as geographical isolation, small size and, at least for volcanic islands, recent age (Whittaker & Fernández�� –�� Palacios, 2007). Be� cause of the relative simplicity of studying an island (Vitousek, 2002), many studies of these environments have become paradigmatic (MacArthur & Wilson, 1967; Simberloff, 1974). Islands are ideal contexts to conduct a natural historical experiment (Diamond & Robinson, 2010). In biogeographical terms, we can distinguish two major categories of islands: continental and oceanic. The former are located on the continental shelf and may have been linked to the mainland in the past, while the latter have never been connected to the mainland (Whittaker & Fernández–Palacios, 2007). This distinction has conceptual implications of great importance. Since the beginning of the modern debate 'dispersal versus vicariance' (Croizat et al., 1974; Heads, 2014), the dispersalist approaches have undergone considerable criticism (Morrone & Crisci, 1995 and references cited therein). The non–refut� ability of dispersalist explanations, defined ad hoc (for review: Morrone & Crisci, 1995; Bueno Hernández & Llorente–Bousquets, 2000; Zunino & Zullini, 2004), has shifted focus towards vicariantist arguments. This paradigm shift has consequently led to a lack of interest in respect to oceanic islands due to the non–falsifiability of hypotheses (Cowie & Holland, 2006). However, in recent years, the importance of dispersal as a key mechanism in determining species distribution has been emphasized (De Queiroz, 2005; Cowie & Holland, 2006) and oceanic islands have attracted attention because their biodiversity pattern must necessarily be explained in dispersal terms (Cowie & Holland, 2006). In this context, the value of biodiversity analysis methods should be stressed (Magurran & McGill, 2011), especially regarding the beta diversity that Whittaker (1960, 1972) has defined as “the extent of change in community composition”. In recent years, studies concerning the beta diversity have proliferated (Anderson et al., 2011). This inter� est in the study of beta diversity is linked to a basic question of community ecology —what makes a set of species more or less similar to another in different times and spaces (Vellend, 2010)?. Several studies on different taxa and scales have addressed the issue of the distribution, composition and species richness of organisms from an eco–bio� geographical perspective, aiming to identify the key variables that could explain these patterns (Freestone & Inouye, 2006; Veech & Crist, 2007; Qian, 2009; Bin et al., 2010; Jiménez–Valverde et al., 2010; Vellend, 2010; Baselga et al., 2012; Dexter et al., 2012). These studies have also focused on island environments and multiple studies have analysed the factors controlling the spatial patterns of biodiversity among many taxa (Kadmon & Pulliam, 1993; Legakis & Kypriotakis, 1994; Palmer, 1998; Palmer et al., 1999; Garcia–Barros et al., 2002; Guerrero et al., 2005; Hausdorf & Hennig, 2005;

Dapporto & Cini, 2007; Fattorini, 2009a, 2009b, 2010; Sfenthourakis, 1996; Dennis et al., 2000). Fattorini (2010), for example, investigated the importance of island areas, distance from the continent, inter–island distance and island age of the Aeolian archipelago (southern Italy) in determining patterns of spatial variation in beta diversity for several taxa, including dung beetles. In this research, Fattorini concluded that the dung beetle fauna originated quite recently and that the species were established on the islands by a 'stepping stone' dispersive process: species dis� persed from one island to the nearest (MacArthur & Wilson, 1967). However, in an attempt to reconstruct the dispersal patterns of coprophagous fauna, Fattorini (2010) identified conflicting results. Specifically, his analysis of similarity (with Jaccard and Kulczynski 2 indices) produced three different clusters, which cannot provide an unambiguous explanation. Furthermore, these indices are not appropriate for the exploration of dispersal fluxes because they cannot identify the direction of dispersal. Using an expanded database (in terms of areas and dung beetle species) and inspired by Fattorini’s (2010) paper, we attempted in this exploratory research to reconstruct the possible dispersal routes of dung beetle fauna in the coloni� zation of circum–Sicilian volcanic islands in order to formulate a posteriori hypothesis about the probable mechanisms involved in the conformation of these island assemblages. Material and methods Study area The survey focused on 10 volcanic islands: eight loca� ted north of Sicily (Ustica and the Aeolian archipelago: Lipari, Salina, Vulcano, Stromboli, Filicudi, Alicudi, Panarea) and two in the Sicily Channel (Pantelleria and Linosa) (fig. 1). At no point in the past were these islands connected to continental areas, allowing us to exclude vicariance events. The oldest islands are Linosa and Ustica (about 1,000 Kyr). Their age excludes any involvement in the Messinian salinity crisis, which ended about 5.3 million years ago (Krijgsman et al., 1999). This period had a tremendous impact on the biogeography of the Medi� terranean fauna (Sanmartín, 2003; Marra, 2005). The estimate of the most severe sea–level drops over the last 5.3 million years is –120 m (Rohling et al., 2014). The Aeolian archipelago is separated from Sicily by a channel between 1,000 and 2,000 m deep, while the interisland depth varies from 400 to 1,400 m. Only Lipari and Vulcano, divided by water depths < 50 m, were connected to each other but they were always separated from Sicily during glacial periods of sea– level lowering. Ustica is the summit of a large volcanic edifice resting on the seabed at depths of the order of 2,000 m (Ruggieri, 1973; Marani et al., 2004). Pan� telleria and Linosa were also isolated during glacial phases (Shackleton et al., 1984). Although the hypothetical dispersal routes were in� vestigated only for volcanic islands, we also examined

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Italy

Tunisia

Aeolian Archipelago

Ustica

Egadi Archipelago

Pantelleria

Malta

Linosa Tunisia

Lampedusa

Fig. 1. Study area. Fig. 1. Zona de estudio.

the Scarabaeoidea fauna of other possible source areas: Sicily, Calabria, Tunisia, Malta, Lampedusa and the Egadi archipelago (Favignana, Marettimo and Levanzo). These possible source areas, which include the nearest mainland areas and other non–volcanic islands in the region, were examined in two different scenarios (see 'Analysis and interpretation' heading). The main climatic and vegetation factors are reaso� nably homogeneous among the considered volcanic islands (Agnesi & Federico, 1995; Cicala, 1997; Pasta & La Mantia, 2003; Nesos, 2013). The climate of the volcanic islands is typically Mediterranean (Agnesi & Federico, 1995; Pasta & La Mantia, 2003; Blasi et al., 2005; Nesos, 2013). The vegetation, despite being altered to some extent by a long human presence,

is distinctly Mediterranean and the main natural environments are maquis and garrigue landscapes (Ronsisvalle, 1973; Baccetti et al., 1995; Pasta & La Mantia, 2003; Lo Cascio & Pasta, 2004; Nesos, 2013). Given the relative environmental homogeneity of the considered islands, it is assumed that the simi� larity in richness and composition should be mainly related with the role played by dispersal processes (Cadotte, 2006). Data source and systematic group The presence–absence data (see annex) were drawn from Arnone et al. (1995, 2001), Carpaneto et al. (2005), Agoglitta et al. (2006), Dellacasa & Dellaca�

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sa (2006), Lo Cascio et al. (2006), Arnone, (2010), Fattorini (2010). The Tunisian data were taken from Baraud (1985) and Errouissi et al. (2009) and reviewed by Imen Labidi (pers. com., 2015) on the basis of comparisons with the collections Henry Normand and Muséum National d'Histoire Naturelle (Paris). Some data from the Egadi archipelago: Euoniticellus fulvus (Goeze, 1777), Cheironitis irroratus (Rossi, 1790), Onthophagus taurus (Schreber, 1759), Calamosternus granarius (Linnaeus, 1767), and Calamosternus mayeri (Pilleri, 1953) were provided by Marco Dellacasa (pers. com., 2014). The data for Malta were drawn from Pivotti et al. (2011). Analysis and interpretation There are several methods for reconstructing dispersal fluxes (Nathan et al., 2003). Some are complex and financially expensive but very informative (i.e., phylo� geography), while others are simple and inexpensive but less accurate (i.e., pairwise comparisons derived from a presence/absence matrix in homogeneous areas; Legendre, 1986). In this study, we adopted the latter as a preliminary and exploratory strategy to evaluate the existence of any noteworthy patterns. Data were analysed using the coefficient of disper� sal direction DD2 (Legendre & Legendre, 1984). This coefficient, rarely used in biogeographical analyses (but see: Legendre & Legendre, 1984; Bachraty et al., 2009; Borcard et al., 1995), measures the likeli� hood of species dispersal between two areas using species presence–absence data. The formula of the DD2 is:

DD2 (x1àx2) =

2a 2a + b + c

(b – c) a+b+c

where a is the number of species that two regions have in common; b is the number of species found in x1 but not in x2; c is the number of species found in x2 but not in x1. The first portion of the DD2 coefficient is the Sørensen index of similarity, while the second portion measures the asymmetry in taxonomic com� position. As Legendre & Legendre (1984) assert, 'the first portion states that unless two adjacent regions possess species in common, it would be difficult to think of these two faunas as deriving one from the other. The second portion creates the pictures of a fauna waiting at the border to invade an adjacent region; namely, the greater the number of species that inhabit an area, the greater the likelihood that this area acts as a source for neighbouring areas. Thus, DD2 measures the likelihood that species have dispersed form x1 to x2 (b larger than c). A negative value (c larger than b) indicates that, if dispersal occurred, species might have migrated from x2 to x1 (Legendre & Legendre, 1984). In summary, the quan� tity (b – c) would indicate the direction of dispersal flux, while the DD2 value, which reacts to both the similarity and the asymmetry between areas, would estimate flux intensity (Bachraty et al., 2009). We chose to use the DD2 index because, in analysing the possible dispersal fluxes, we think that presence is more important than supposed absence, and then we

decided to give double weight to the common species. This choice also allowed us to limit the biases and inconveniences caused by possible local extinctions. To evaluate the dispersal fluxes, we divided the circum–Sicilian volcanic islands into two groups: north of Sicily (Aeolian Islands + Ustica) and south of Sicily (Pantelleria and Linosa). Then we hypoth� esized two colonization scenarios: the first excluding any continental islands as possible sources, and the second including continental islands as possible source areas (table 1). Of all the possible source areas (significant values of DD2), we considered only those with the highest value of DD2 as being likely source areas, since this value indicates a greater intensity of flux. When two or more possible source areas had a relative difference in the DD2 value of less than 5%, they were both discussed as possible equivalent source areas. The McNemar test was used to test the null hypoth� esis that there is no asymmetry between two areas (H0: b = c). We used a two–tailed test of significance setting the probability of a type I error at α = 0.05. The coefficients were calculated for each pair of areas. The coefficients DD2 were calculated using the func� tion bgdispersal of the Vegan Package (Oksanen et al., 2012) for the software R (R Development Core Team, 2011). In order to identify the possible dispersal routes by the use of DD2 coefficient, four assumptions were made. First, the volcanic islands were originally empty. The fauna and flora now present in these areas are necessarily dispersed from other source areas. This assumption is consistent with the geological history of the concerned islands. Indeed, they have originated from volcanic events in the period between 1,000 and 90 Kyr and it is impossible that they had an ab origine fauna. Second, the past dispersal events have necessarily left marks on the present communities (Legendre & Legendre, 1984; Borcard et al., 1995; Bachraty et al., 2009). Third, dispersal comes from areas of high to low taxonomic richness (Legendre & Legendre, 1984; Borcard et al., 1995; Bachraty et al., 2009). And fourth, given the strong homogeneity of the environmental parameters of the islands, the similarity in the biodiversity pattern and fauna between islands should be mainly related to dispersal processes. Results In total, through the literature review, we identified 176 dung beetle species as being present in the study area: 18 Geotrupidae, 53 Scarabaeidae, and 105 Aphodiidae. On the volcanic islands alone, 48 species are reported: 3 Geotrupidae, 24 Scara� baeidae, and 21 Aphodiidae. The species richness of the volcanic islands ranges from 35 (Vulcano island) to one (Panarea island). The species with the high� est frequency in the volcanic islands is Thorectes intermedius (eight islands; see annex). Tables 2 and 3 show the results of DD2 fluxes with their McNemar and probability values. Figures 2 and 3 show these results graphically. The dispersal

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Table 1. Context and scenario (S) in evaluating hypothetical dispersal fluxes to the volcanic islands: * Continental islands. Tabla 1. Contexto y supuestos utilizados (S) en la evaluación de los hipotéticos flujos de dispersión hacia las islas volcánicas: * Islas continentales.

Context

Target islands

Possible source areas

North of Sicily 1 Lipari, Salina, Vulcano, Stromboli, Filicudi, Alicudi, Panarea, Ustica

Sicily, Calabria, Lipari, Salina, Vulcano, Stromboli, Filicudi, Alicudi, Panarea, Ustica

North of Sicily 2

Lipari, Salina, Vulcano, Stromboli, Filicudi, Alicudi, Panarea, Ustica

As above + Egadi islands (Favignana*, Levanzo*, Marettimo*)

South of Sicily

Pantelleria, Linosa

Sicily, Tunisia, Pantelleria, Linosa

South of Sicily 2 Pantelleria, Linosa

patterns in the north of Sicily are equivalent in both scenarios with both Lipari and Vulcano acting as major source areas (three fluxes each) followed by Sicily (two fluxes) and Salina (one flux) (tables 2, 3; figs. 2, 3). Both scenarios show two equivalent fluxes towards Alicudi (Lipari and Vulcano). Results in the Sicily Channel (south of Sicily) differ depending on the scenario. In the first scenario, Tuni� sia acts as a major source area (two fluxes), followed by Sicily (one flux). Linosa has two equivalent fluxes starting from Tunisia and Sicily, while the flux into Pantelleria indicates that it was probably colonized by Tunisian fauna. In the second scenario, Malta acts as a major source area (two fluxes) followed by Tunisia (one flux). Pantelleria shows two equivalent fluxes starting from Malta and Tunisia. Linosa was colonized by Maltese fauna (one flux). Discussion This study focused on the hypothetical dispersal routes of dung beetles in the circum–Sicilian volca� nic islands. The survey was conducted applying the DD2 coefficient of dispersal direction (Legendre & Legendre, 1984), a method that highlights the most probable routes of colonization considering the entire assemblages of each area. It is interesting to note that the distribution of dung beetles on the circum–Sicilian volcanic islands could be the result of a coherent dispersal process rather than due to chance. This is corroborated by the fact that all DD2 major fluxes had a significant value according to the McNemar test. In the north of Sicily, the dispersal fluxes led towards Vulcano and Lipari. These two islands thus acted as core source areas for the other islands (except Panarea,

As above + Egadi Islands (Favignana*, Levanzo*, Marettimo*), Malta*, Lampedusa*

which was colonized from Salina). The flow linking Ustica to Lipari suggests that the former was most likely colonized from the latter, noteworthy results since these islands are 150 km apart and Ustica is just 54 km away from Sicily. A chromosomal study (Colomba et al., 1995) about Thorectes intermedius populations of the mainland Sicily, Marettimo (Egadi Islands), Caprera (Sardinia) and Ustica revealed, as one would expect, that the populations of Ustica seem to be related to those of mainland Sicily. However, this study did not take into account the population of intervening areas, such as the Aeolian archipelago, as we did. The same is true for Alicudi, Filicudi, and Stromboli, all of which would have been colonized from Vulcano and Lipari, again acting as core source areas, as opposed to being targeted from their nearest neighbour in a stepping–stone fashion. Although the cluster analysis used by Fattorini (2010) to examine the similarity of island assemblages does not allow to determine the direction of disper� sal, our results are in agreement with some of those established by this author: Salina and Panarea are grouped together (see figure 3 in Fattorini, 2010), and in our work Salina is the source for Panarea. In the alternative solution of Kulczynski 2 (Fattorini, 2010: 1066), Salina was grouped with Lipari and Vulcano, and Lipari appears as the source of dung beetles for Salina. In Fattorini’s Jaccard results, Alicudi is related to the Vulcano and Lipari group, and our re� sults confirm this pattern with Alicudi displaying two equivalent fluxes departing from Lipari and Vulcano. In the Sicily Channel, Linosa has three equivalent fluxes, two in the first scenario and one in the sec� ond, with three possible source areas (Malta, Sicily, and Tunisia). Pantelleria has two equivalent fluxes (Tunisia in the first and second scenarios, and Malta in the second). Linosa is centrally located in the Sicily

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Table 2. Results of coefficient of dispersal direction DD2 (scenario 1): DD2. DD2 value; M. McNemar value; P. McNemar probability (* P < 0.05; ** P < 0.01; *** P < 0.001; **** P < 0.0001).

Table 3. Results of coefficient of dispersal direction DD2 (scenario 2): DD2. DD2 value; M. McNemar value; P. McNemar probability (* P < 0.05; ** P < 0.01; *** P < 0.001; **** P < 0.0001).

Tabla 2. Resultados del coeficiente de dirección de la dispersión DD2 (supuesto 1): DD2. Valor DD 2; M. Valor McNemar; P. Probabilidad McNemar (* P < 0,05; ** P < 0,01; *** P < 0,001; **** P < 0,0001).

Tabla 3. Resultados del coeficiente de dirección de la dispersión DD2 (supuesto 2): DD2. Valor DD 2; M. Valor McNemar; P. Probabilidad McNemar (* P < 0,05; ** P < 0,01; *** P < 0,001; **** P < 0,0001).

Dispersal flux

DD2

Dispersal flux

DD2

Lipari Ustica

0.21

14.36

***

Lipari Ustica

0.21

14.36

***

Vulcano Alicudi

0.24

30.97

****

Vulcano Alicudi

0.24

30.97

****

Lipari Alicudi

0.23

13.21

***

Lipari Alicudi

0.23

13.21

***

Vulcano Filicudi

0.21

22.89

****

Vulcano Filicudi

0.21

22.89

****

Sicily Lipari

0.29

85.94

****

Sicily Lipari

0.29

85.94

****

Salina Panarea

0.27

4.93

Salina Panarea

0.27

4.93

Lipari Salina

0.28

24.28

****

Lipari Salina

0.28

24.28

****

Vulcano Stromboli

0.27

38.14

****

Vulcano Stromboli

0.27

38.14

****

Sicily Vulcano

0.33

69.70

****

Sicily Vulcano

0.33

69.70

****

Sicily Linosa

0.14

104.97

****

Malta Linosa

0.28

24.45

****

Tunisia Linosa

0.14

143.49

****

Tunisia Pantelleria

0.18 137.94 ****

Tunisia Pantelleria

0.18

137.94

****

Malta Pantelleria

0.18

Channel, lying 120 km from Malta, 160 km from Sicily, and 165 km from Tunisia. Our results seem to reflect this geographical centrality, with no specific source area with major importance. Pantelleria seems to be more related with Tunisia, 70 km away. However, Malta (distance 200 km to Pantelleria) also seems to have played a role as source area. The importance of North Africa for Pantelleria is corroborated by studies carried out on other taxa. Magnano & Osella (1973), for example, reported that the curculionido–fauna of Pantelleria have the highest number of species with North African affinities compared to all other circum– Sicilian islands. Our results do not strictly support the stepping– stone model which supports dispersal from one island to its nearest neighbour. Rather, north of Sicily, Lipari and Vulcano islands might have acted as core source areas; while in the Sicily Channel, Linosa would have been the favourite target area and Pantelleria would have had two source areas (Tunisia and Malta) that are very far apart. Furthermore, the most frequent spe� cies in the volcanic islands is Thorectes intermedius, a flightless species unable to survive for long periods in contact with sea water (Zunino, unpublished raw data; Colomba et al., 1995). Thus, the maintenance of a viable dung beetle population on far–away islands was necessarily linked to the presence of humans and

12.32

***

domestic mammals from which to draw the manure necessary to feed and nest. Indeed, although some species are polyphagous, they need dung for nesting and larvae development (Palestrini & Zunino, 1985; Verdú et al., 2007). In view of these results, we propose that human movement was the principal factor accountable for dung beetle dispersal resulting in the colonization of the circum–Sicilian islands. Human activity and move� ment have played an important role as a medium for animal and plant dispersal (Pimentel, 2001; Forcina et al., 2015). Pimentel (2001) estimates that since the origin of farming (10,000 years ago), humans moved more than 400,000 species from one region of Earth to another. This phenomenon was particularly intense in the Mediterranean basin and its islands and increased as farming spread into this region (starting ca. 7,500 years ago) (Blondel & Vigne, 1993; Masseti, 1998; Blondel, 2006; Masseti & De Marinis, 2008, Vigne, 2014). The dispersal fluxes we have identified are in broad agreement with the ancient human colo� nization of the islands. In general, the circum–Sicilian islands were colonized directly from Sicily but, in the case of the Aeolian Islands, Lipari has played a role as main source area in the human colonization of the archipelago since the Neolithic Age (ca. 5,000 BC). There is limited evidence of settlement on Vulcano

Animal Biodiversity and Conservation 39.2 (2016)

167

10 7

8 5

4 3

12 100 km

Tunisia

Fig. 2. Potential dispersal fluxes ( ) for each volcanic island (scenario 1): 1. Sicily; 2. Calabria; 3. Vulcano; 4. Lipari; 5. Salina; 6. Filicudi; 7. Alicudi; 8. Panarea; 9. Stromboli; 10. Ustica; 11. Pantelleria; 12. Linosa. Fig. 2. Posibles flujos de dispersión ( ) para cada isla volcánica (supuesto 1): 1. Sicilia; 2. Calabria; 3. Vulcano; 4. Lípari; 5. Salina; 6. Filicudi; 7. Alicudi; 8. Panarea; 9. Estrómboli; 10. Ústica; 11. Pantelaría; 12. Linosa.

10 7

8 5

4 3

11 12

13 1

16 17 Tunisia

100 km

Fig. 3. Potential dispersal fluxes ( ) for each volcanic island (scenario 2): 1. Sicily; 2. Calabria; 3. Vulcano; 4. Lipari; 5. Salina; 6. Filicudi; 7. Alicudi; 8. Panarea; 9. Stromboli; 10. Ustica; 11. Levanzo; 12. Marettimo; 13. Favignana; 14. Malta; 15. Lampedusa; 16. Linosa; 17. Pantelleria. Fig. 3. Posibles flujos de dispersión ( ) para cada isla volcánica (supuesto 2): 1. Sicilia; 2. Calabria; 3. Vulcano; 4. Lípari; 5. Salina; 6. Filicudi; 7. Alicudi; 8. Panarea; 9. Estrómboli; 10. Ústica; 11. Levanzo; 12. Marettimo; 13. Favignana; 14. Malta; 15. Lampedusa; 16. Linosa; 17. Pantelaría.

Tonelli et al.

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during the prehistoric period until the classical period, although sulphur and alum were probably extracted during the Bronze Age, and animals were possibly kept on the island by Lipari’s earliest inhabitants, which would account for the similarities observed between the beetle fauna of the two islands. Owing to its agricultural potential and availability of desirable mineral resources (volcanic glass or obsidian), Lipari has been the only constantly occupied island in the Aeolian archipelago, with populations expanding and contracting on nearby islands, which underwent frequent episodes of abandonment (Bernabo Brea, 1958; Castagnino–Berlinghieri, 2011; Dawson, 2014). Contacts between the island of Ustica, first colonized by communities from Sicily in the Early Neolithic (6th– 5th millennium BC) (Mannino, 1998), and the Aeolian Islands are already attested in the Early Bronze Age (early 2nd millennium BC) and become more frequent in the Middle Bronze Age (mid–2nd millennium BC), as seen from parallel developments in pottery styles (Spatafora, 2009, 2012). Obsidian from Pantelleria has been found in Neolithic contexts in Tunisia (Mulazzani et al., 2010: 57), in Malta, Linosa, and Lampedusa (Tykot, 1996), demonstrating links between coastal and island communities of the southern Mediterranean as early as the 7th and 6th millennia BC. The dung beetle data in this context support a flux from south to north in the Sicily Channel, a scenario which warrants further archaeological investigation and highlights the mutually beneficial nature of such an interdisciplinary study. Given the distribution of Pantelleria obsidian on nearby Linosa, Malta, and the coastal areas of Tunisia (Tykot, 1996; Mulazzani et al., 2010), we can envisage a stop–over role for Pantelleria and nearby Linosa in the Sicily Channel, which would account for the distribution patterns observed for the dung beetles. On the basis of archaeological data, the current coprophagous beetle faunas may have originated by dispersal mediated by the first island human settle� ments, through the movements of mammals, domestic and otherwise, that they were carrying. It is plausible that the first island communities also made frequent movements of animals between the islands, to take advantage of shifting local resources. The patterns detected would be the result of the distribution since the prehistoric period of human settlers with animals as well as of subsequent transfers between the islands. Arguably, the initial human exploration of the islands followed simple distance criteria. Instead, the decision to establish permanent settlements must have been influenced by other factors, such as the presence of mineral resources (flint and obsidian), in favour of land� ings, water resources, areas of pasture and arable land (the latter often a function of the size of the islands) as well as demographic, social and cultural factors (as was clearly the case in the Aeolian islands), with the establishment of preferential contacts between different communities, such as between Ustica and Lipari and Malta and Pantelleria (Dawson, 2011, 2014). We should stress that our analysis considers the entire community of each island. It is therefore pos� sible that some single species may have colonized a particular island following different routes from those

identified. Furthermore, these dispersal lines should not be considered as synchronous, but rather as the result of various events occurring over time. Howe� ver, such events in different places and times must have left a trace in the present–day communities (Legendre & Legendre, 1984), decipherable accor� ding to our dispersal models in figures 2 and 3. This implicates that further investigation is indispensable to corroborate or refute our hypothesis. We suggest that phylogeographic studies may help describe with precision the spatial and temporal connections of dung beetle fauna in these volcanic islands, especially for the flightless species Thorectes intermedius. Conclusion According to our study, the dung beetle communities of the circum–Sicilian volcanic islands display dispersal fluxes that do not strictly underlie the stepping–stone dynamics. This is especially true for the islands to the north of Sicily, where Lipari and Vulcano act as core source areas for dispersal routes. In the Sicily Channel, small and faraway Linosa was colonized from Tunisia, Malta and Sicily, while Pantelleria was principally co� lonized by fauna from Tunisia and to a lesser extent from Malta. These results, together with the fact that a flightless species, Thorectes intermedius, is most frequently found on these islands, are supported by archaeological patterns in the islands’ human coloni� zation, suggesting a strong human contribution to the genesis of the dung beetle fauna of the circum–Sicilian volcanic islands. Acknowledgments We wish to thank Imen Labidi for checking the Tu� nisian dung beetle data, Marco Dellacasa for the data from the Egadi Archipelago, and Vito Ailara and Francesca Spatafora for their helpful comments on the significance of the archaeological and biological data from Ustica. We also thank the Editor (Jorge M. Lobo) and an anonymous referee for their helpful and constructive suggestions. References Agnesi, V. & Federico, C., 1995. Aspetti geografi� co–fisici e geologici di Pantelleria e delle Isole Pelagie (Canale di Sicilia). Naturalista Siciliano, 19 (suppl.): 1–22. Agoglitta, R., Barbero, E., Ragusa, E. & Zunino, M., 2006. Catalogo sistematico e topografico dei Geotrupidae e Scarabaeidae degradatori della Sicilia e delle isole circumsiciliane (Coleoptera: Scarabaeoidea). Boletín Sociedad Entomológica Aragonesa, 39: 181–204. Anderson, M. J., Crist, T. O., Chase, J. M., Vellend, M., Inouye, B. D., Freestone, A. L., Sanders, N. J., Cornell, H. V., Comita, L. S., Davies, K. F., Harrison, S. P., Kraft, N. J. B., Stegen, J. C. & Swenson, N.

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Pine seed predation by mice: an experimental assessment of preference R. Flores–Peredo & B. S. Bolívar Cimé

Flores–Peredo, R. & Bolívar Cimé, B. S., 2016. Pine seed predation by mice: an experimental assessment of preference. Animal Biodiversity and Conservation, 39.2: 173–184. Abstract Pine seed predation by mice: an experimental assessment of preference.— Seed traits are considered an essential factor influencing rodents' foraging preferences. We evaluated the mouse's preferences for seeds of four pine species, Pinus patula, P. pseudostrobus, P. teocote and P. montezumae, that differ in length, width, nutritional content, and concentrated tannins. In 'cafeteria experiments' in the laboratory, we tested six of the nine mice species commonly found in the temperate forest of Southern Mexico. Longer and wider seeds were those of P. teocote and P. montezumae. P. teocote seeds had the highest protein content, P. patula were highest in lipids, and P. montezumae seeds were highest in carbohydrates. In concentrated tannins, gallic acid content was highest in P. patula seeds and tannic acid content was highest in P. teocote seeds. Mice preferred small pine seeds with a high lipid and gallic acid content, a low tannic acid content, and an intermediate protein and carbohydrate content. The foraging behavior of rodents, their energy optimization, and the likely effects on seed fate and plant composition would thus be mediated by combinations of seed traits rather than by single seed traits such as size or tannin contents. Key words: Bromatological analysis, Concentrated tannins, Energy optimization, Temperate forest, Seed size, Small rodents Resumen Depredación de semillas de pino por roedores: una evaluación experimental de las preferencias.— Se considera que las características de las semillas son un factor esencial que influye en las preferencias de forrajeo de los roedores. Evaluamos en laboratorio, mediante experimentos tipo cafetería, las preferencias alimentarias de seis de las nueve especies de roedores que se observan con frecuencia en el bosque templado del sur de México por las semillas de cuatro especies de pinos: Pinus patula, P. pseudostrobus, P. teocote y P. montezumae, que difieren entre sí en el largo, el ancho, el contenido nutricional y la concentración de taninos. Las semillas más largas y anchas fueron las de P. teocote y P. montezumae. Las de P. teocote tuvieron el mayor contenido de proteína, las de P. patula fueron las más ricas en lípidos y las de P. montezumae fueron las más ricas en carbohidratos. En cuanto a la concentración de taninos, el mayor contenido de ácido gálico se encontró en las semillas de P. patula y el de ácido tánico, en las de P. teocote. Los roedores prefirieron semillas pequeñas con un alto contenido de lípidos y ácido gálico, un bajo contenido de ácido tánico y un contenido intermedio de proteína y carbohidratos. En consecuencia, el comportamiento de forrajeo de los roedores, su optimización energética y los posibles efectos en el destino de las semillas y la composición de la vegetación estarían determinados por una combinación de características de las semillas más que por una única característica como el tamaño o el contenido de taninos. Palabras clave: Análisis bromatológico, Concentración de taninos, Optimización energética, Bosque templado, Tamaño de las semillas, Pequeños roedores Received: 18 XII 14; Conditional acceptance: 4 II 15; Final acceptance: 26 III 16 Rafael Flores–Peredo & Beatriz del Socorro Bolívar Cimé, Inst. de Investigaciones Forestales (INIFOR), Parque Ecológico El Haya, Antigua Carretera Xalapa–Coatepec, Univ. Veracruzana, Xalapa, Veracruz, México. Corresponding author: Rafael Flores–Peredo. E–mail: peredofr@gmail.com ISSN: 1578–665 X eISSN: 2014–928 X

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Introduction Seed production is a fundamental process in forest ecosystem dynamics as seeds are the template of forest regeneration. Seeds are the most nutritious part of plants because of the concentration of carbohydrates, fats and proteins necessary for early seedling development. For this reason, seeds are important food items for small vertebrates, such as rodents and birds, and invertebrates such as insects (Janzen, 1971). Among rodents, squirrels and mice are responsible for the loss of most tree seeds in northern temperate and boreal forests because they are efficient predators and seed dispersers (Yi et al., 2015). In pine forest, they remove and consume 24 to 99% of seeds (Steele et al., 2005; Vander Wall, 2010; Flores–Peredo et al., 2011, Wang et al., 2012), while birds and arthropods usually play a smaller role (Hulme, 2002). As a result, rodents regulate seedling establishment, influencing the dynamics and distribution of plant communities and also the evolution of their reproductive strategies (Hulme & Kollmann, 2005; Wang et al., 2014). Seed traits such as size, nutrient content (proteins, lipids, carbohydrates) and secondary compounds (alkaloids and tannins) are considered one of the most essential factors influencing foraging preferences of granivores (e.g., Janzen, 1971; Díaz, 1996), which in turn may regulate seed fate and plant structure (Hoshizaki & Miguchi, 2005; Wang & Chen, 2009). Regarding seed size, it has been documented that large seeds are consumed more because of their nutritional value (Xiao et al., 2004; Wang & Chen, 2012). However, as larger seeds take longer to consume that smaller seeds, rodents can be at greater risk from predators during consumption. Large seeds are thus more likely to be removed and cached than eaten in situ by scatter–hoarding rodents (Boman & Casper, 1995; Jansen et al., 2004; Hulme & Kollmann, 2005; Sivy et al., 2011). Rodents are also known to select seeds of high nutritional value by smell, avoiding in situ those with secondary toxic compounds such as tannins and terpenes (Wang & Chen, 2009; Zong et al., 2010; Rubino et al., 2012). Tannins (naturally astringent compounds) and terpenes (mainly hydrocarbons found in volatile oils and resins) reduce the digestibility of seeds because of their high affinity for proteins (Wang & Chen, 2012). This can lead to body weight loss and even death (Vander Wall, 2001; Shimada & Saitoh, 2003). Nevertheless, rodents may choose seeds with tannins in periods of low food availability (Xiao et al., 2008; Vander Wall, 2010), attenuating their effects by consuming seeds that are high in protein and fat content (Wang & Chen, 2012; see also Díaz, 1996). Identifying which seeds rodents prefer in forest ecosystems may help to understand their influence on plant community dynamics (Hulme, 2002), their foraging strategies, energy optimization (Kasparian & Millar, 2004; Hoshizaki & Miguchi, 2005) and the way in which these resources are used by granivore species in their habitats (Millar et al., 1985). In temperate forests in central Veracruz, Mexico, the feeding preferences of rodents seems to involve

several factors that favor the dominance of Pinus teocote, together with the regenerative strategies of the species, herbivory and light intensity, because seeds of this species and those of P. montezumae are removed little (Flores–Peredo et al., 2011). It has been reported that wood, needles and bark from P. teocote contain two of the principal concentrated tannins, tannic and gallic acids (Rosales–Castro & González–Laredo, 2003; Rosales–Castro et al., 2009; Sáenz–Esqueda et al., 2010), and those from P. montezumae have high levels of tannic acid and turpentine (Rodriguez–Franco, 1997; Bernabé–Santiago et al., 2013), but tannic and gallic acid levels in seeds are unknown. Reported seed sizes for these species are 4.0 ± 0.42 (SE) mm length and 2.4 ± 0.21 mm width for P. teocote (Ramírez–García, 2000), and 8.0 ± 0.27 mm length and 4.0 ± 0.32 mm width for P. montezumae (Perry, 2009). Both species are dispersed by wind, rodents and insects. Studies with rodents using artificial seeds (Wang & Chen, 2008, 2012), acorns (Smallwood et al., 2001; Shimada & Saitoh, 2003; Steele et al., 2005; Takahashi & Shimada, 2008), pine seeds (Chen & Chen, 2011; Zong et al., 2010) and seeds from other plant species (Downs et al., 2003) would suggest rodents have clear preferences for seeds from among these pine species in relation to size and nutrient contents. In an in situ laboratory, we evaluated the feeding preferences for seeds of pines species among six out of the nine species of small mice captured in the temperate forest in the central area of Veracruz state (those captured in sufficient numbers to be tested), in relation to seed size, nutrient content and secondary compounds. The purpose of this study was to address: 1) whether there are size differences among the pine seeds considered; 2) whether there are differences among these seeds in their nutritional content and concentrated tannins such as gallic acid and tannic acid; and 3) whether different rodent species select and consume different pine seed species according to traits such as seed size, nutritional content and concentrated tannins. We hypothesized that (1) species of pine seeds differ in traits such as nutritional content and size, (2) seeds with a negative selection in field experiments (P. teocote and P. montezumae) will be chosen and consumed less in a laboratory setting because of high concentrated tannin contents and the low lipid contents, and 3) seed traits might influence rodents' foraging behavior, thereby influencing seed fate and plant community composition. Material and methods Study area The study was conducted in the central region of the state of Veracruz, in the San Juan del Monte Ecological Reserve in Mexico (19º 39' 00'', 19º 35' 0'' N, 97º 05' 00'', 97º 07' 30'' W, between 2,327 and 3,100 m a.s.l.), which has an area of 609 ha. The vegetation mosaic is comprised of three types of vegetation: 1) pine forest, with Pinus teocote as the dominant species (ca. 69% of the forest cover in the

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area, followed by Pinus patula, P. pseudostrobus and P. montezumae (GEV & CEMA, 2002). These trees are 15 to 25 m high, and 6 to 8 m apart; 2) oak–alder forest consisting mainly of Quercus crassifolia Humb et Bonpl and Alnus jorullensis HBK that are 6 to 12 m high; and 3) subalpine grassland, consisting mainly of patches of Brachypodium mexicanum Roem et. Schult and Muhlenbergia macroura Muhly, fairly close together (1 m apart) or, sometimes packed together with tillers that are up to 1 m high, in association with occasional shrubs such as Baccharis conferta Kunth that are 1 to 3 m high (GEV & CEMA, 2002). Seed collection, measurement and site selection For each species of pine, ten trees were randomly selected during the seeding season (November–January) and 800 mature cones (200 per species) were collected. The cones were dried in the sun and the seeds were removed. The dispersal wing was removed before laboratory experiments. To assess intra– and inter–specific variation in seed size, three samples of 50 seeds were selected from a total of 350 g per pine species. Each seed of each sample was measured (length and width) with a digital caliper to the nearest 0.01 mm (Rodriguez–Laguna et al., 2012). Nutrient analysis The bromatological analyses were made on 300 g of seeds from each pine species, using three subsamples of 100 g according to standardized methods (AOAC, 2005). In order to determine moisture, ash, protein, lipid, fiber and carbohydrate content, the seeds were pulverized in a mortar. The Soxhlet method (AOAC, 2005) was used to determine crude fat content. For moisture content, samples were over–dried at 70°C for 72 h. Ash was determined by incineration and crude fiber was determined by acid and alkaline digestion of the samples. Protein analysis was automated, using micro Kjeldahl equipment (Brand: Buchi Labortechnik, Type: B–339) and the conversion method for total protein nitrogen (N x 6.25) was used as recommended by FAO/OMS (1973). Total carbohydrate was obtained from the additive difference in the percentages of moisture, ash, protein and lipids. We determined two of the most common concentrated tannins, gallic acid and tannic acid (Alasalvar & Shahidi, 2009; Rosales–Castro et al., 2009; Sáenz– Esqueda et al., 2010). Gallic acid was determined using 400 g of seeds per species in four subsamples of 100 g, and 300 g of seeds per species in three subsamples of 100 g were used for tannic acid determination. To extract gallic acid, about 150 mg of the extract was dissolved in 10 mL of methanol, and 2 mL of this solution was filled up with 0.3% HCl to 5 mL. A 100 µL aliquot of the resulting solution was added to 2 mL of 2% Na2CO3 and after 2 min 100 µL of Folin–Ciocalteau reagent (Merck, Darmstadt, Germany) (diluted with methanol 1:1) was added. After a further 30 minutes, the absorbance was measured at 750 nm using a spectrophotometer. The concentration was calculated using gallic acid as standard,

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and the results were expressed as milligrams gallic acid equivalents (GAE) per gram extract (Matthaus, 2002). To extract tannic acid, we took into account amendments to the ISO–1988 International standard for the determination of tannins number 9648.5 (ISO Norm 9648, 1988). Rodent capture Between February 2006 and January 2007, rodents were captured within the three vegetation types (pine forest, oak–alder forest and subalpine grassland) with two replicate sampling plots (1.7 hectares approximately, 130 m x 130 m), separated by 3 km on average. We sampled each replicate twice a month over 12 months, with a 1–week break between visits. The sampling effort was 144 trap–nights per vegetation type, and 7,200 trap–nights overall. In each replicate, we established four random linear transects (two of 130 m and two of 120 m) with a width of 5 m, where we set 13 and 12 Sherman traps, respectively (1 trap/10 m, 50 traps in total) baited with oats, vanilla and peanut butter. Traps remained active for 12 h (6.00 p.m.–6.00 a.m.). When it was necessary to identify the individuals captured, we euthanized by asphyxia an adult male and female of each recognizable rodent species following the American Society of Mammalogists guidelines and procedures on animal ethical care and use (Sikes et al., 2011) and authorized by the Mexican federal authority (SEMARNAT). Taxonomical identification of species was based on cranial morphology according to Wilson & Reeder (2005). Feeding preference experiments were done with the animals and species that were recorded throughout the year until we obtained data from 20 individuals for each mouse species. Feeding preferences The feeding preference experiments were performed using a wood box (60 x 30 x 30 cm) divided into two areas (isolation and feeding). The feeding area was covered with black plastic to facilitate cleaning and reduce animal stress (Moberg & Mench, 2000). For each test, we used a plastic Petri dish with 20 seeds (five of each species of pine) to be eaten ad libitum. For each run of the experiment, one mouse from each captured species, which had fasted during the previous 6 h, was placed in the isolation area for about 10 minutes. The connecting door was then opened and the mouse was allowed to enter the feeding area. We evaluated the choice of seeds by pine species, identifying in the feeding area in each trial (five times for each mouse) (Heroldova et al., 2008) the first seed chosen by olfaction among 20 seeds of four pine species. After identifying the seed chosen, we allowed the mouse to eat freely for 5 minutes before it was removed from the box at the end of the experiment. At the end of each trial, we added together the number of times a certain seed was chosen for each pine species and counted the number of seeds consumed. This was repeated five times with the same mouse every 40 min. After the experiment, the mouse was released at the place where it was captured.

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Statistical analyses Intra–specific variation in the length and width of the seeds for each pine species was evaluated using Barlett´s test, considering three groups of 50 seeds as replicates after evaluation of data normality with Shapiro–Wilk´s tests (Crawley, 2007). If variances were homogeneous for each pine species, we then used an analysis of variance to assess inter–specific differences in seed size. For significant differences, we used a multiple–comparison Tukey test to contrast seed size among pairwise pine species (Crawley, 2007). To assess differences in the protein, lipid and carbohydrate contents of seeds among the four pine species, we applied a one–way ANOVA. Because these data departed from normality (according to Shapiro–Wilk’s tests), we performed square–root transformations (Crawley, 2007). For significant differences, we used multiple–comparison Tukey tests. To assess differences in the gallic and tannic acid content in seeds among the four pine species, we applied a Kruskal–Wallis nonparametric test (Crawley, 2007). We used the values obtained in percentage for each component as response variable and the pine species as explanatory variable. Differences in pine seed species chosen for the first time in the experiment were evaluated using a general linear mixed model (GLMM; Wang et al., 2012), since our data involved repeated measurements from the same individual (five repetitions) and both random (each mouse tested) and fixed (pine seed species) effects (Crawley, 2007). The pine seed species was the single categorical explanatory variable in the model, which had four levels corresponding to each pine species tested. For this analysis, the response variable was binary: pine seed species chosen or not chosen, thus the family was binomial and the link function used was logit (Crawley, 2007). The same analysis was performed to evaluate differences in the number of seeds consumed among pine species; in this case, we used a Poisson distribution (response variables were counts) and log as link function in the

model. When the tests were significant, differences between levels of the explanatory variable were evaluated using the multcomp package version 1.3–5 (Bretz et al., 2010). These analyzes were performed separately for each rodent species with more than 12 individuals tested using the R software version 2.13.2 (R Development Core Team, 2008). Results For each pine species, seed length and width values were normal. We found no intra–specific variation in seed length and width for the pine species evaluated (table 1). However, length of seeds showed inter–specific significant differences (F3,8 = 271.48, P < 0.001). Longer seeds were those of Pinus teocote (6.26 ± 0.04 mm) and P. montezumae (5.69 ± 0.04 mm) compared with P. patula (5.13 ± 0.04 mm) and P. pseudostrobus (4.56 ± 0.04 mm) (fig. 1A). Similarly, the width of the seeds differed among pine species (F3,8 = 1639.00, P < 0.001). Wider seeds were those of Pinus montezumae (4.23 ± 0.02 mm) and P. teocote (4.04 ± 0.02 mm) compared with P. patula (2.62 ± 0.02 mm) and P. pseudostrobus (2.55 ± 0.02 mm) (fig. 1B). Protein (F3,8 = 13291, P = < 0.001), lipids (F3,8 = 25.95, P = < 0.001) and carbohydrate content (F3,8 = 11745, P = < 0.001) of seeds were significantly different among the four pine species (fig. 2). Generally, the protein content of the seeds was relatively low and Pinus teocote seeds contained significantly more protein (13.29%). Lipid content was slightly higher than protein content and the seeds of P. patula had the highest lipid content (38.48%). Carbohydrate content was the predominant nutrient type in the seeds, and P. montezumae had the highest carbohydrate content (75.23%). Seed fiber content did not differ among pine species (F3,8 = 0.44, P = 0.729): P. patula 8.60%, P. pseudostrobus 8.13%, P. teocote 8.53% and P. montezumae 11.56%.

Table 1. Values obtained using the Shapiro Wilk test for length and width values of four pine seed species: normality according to Shapiro–Wilk and homoscedasticity according to Barlett. The n value corresponds to three groups of 50 seeds for each species of pine. Tabla 1. Valores obtenidos usando la prueba de Shapiro Wilk para los valores de largo y ancho de las semillas de cuatro especies de pino: la normalidad según Shapiro–Wilk y la homocedasticidad según Bartlett. El valor de n corresponde a tres grupos de 50 semillas para cada especie de pino.

Species

Length (mm) n

Normality

Homoscedasticity

Width (mm) Normality

Homoscedasticity

150

P > 0.065

F2 = 1.26, P = 0.533

P > 0.100 F2 = 0.10, P = 0.953

Pinus pseudostrobus 150

P > 0.100

F2 = 4.30, P = 0.117

P > 0.100 F2 = 1.52, P = 0.468

Pinus montezumae

150

P > 0.100

F2 = 2.07, P = 0.355

P > 0.100 F2 = 0.16, P = 0.924

Pinus teocote

150

P > 0.100

F2 = 4.37, P = 0.112

P > 0.100 F2 = 4.37, P = 0.112

Pinus patula

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6.6 6.4 6.2 6.0 5.8 5.6 5.4 5.2 5.0 4.8 4.6 4.4 4.2

d c

Width (mm)

Length (mm)

177

a b

4.6 4.4 4.2 4.0 3.8 3.6 3.4 3.2 3.0 2.8 2.6 2.4 2.2

Pps Pm Pt Pine species

a Pps Pm Pine species

Fig. 1. Differences between length (A) and width (B) of seeds of four pine species from the central area of Veracruz State, Mexico: Pp. Pinus patula; Pps. Pinus pseudostrobus; Pm. Pinus montezumae; Pt. Pinus teocote. Letters a, b, c and d indicate significant differences at P < 0.05; mean ± SE. Fig. 1. Diferencias entre el largo (A) y el ancho (B) de las semillas de cuatro especies de pino de una zona central del estado de Veracruz, México. Las letras a,b,c y d indican diferencias significativas con P < 0,05; media ± EE. (Para las abreviaturas de las especies, véase arriba.)

100

Nutritional content (%)

70 b

60 50

30 b

20 10

a Pp

c d

Pps Pt Pm Pp Protein

Pps Pt Pm Lipids Pine species

Pp Pps Pt Pm Carbohydrates

Fig. 2. Protein, lipid and carbohydrate content of the seeds from four temperate forest pine species from the central area of Veracruz State, Mexico: Pp. Pinus patula; Pps. Pinus pseudostrobus; Pt. Pinus teocote; Pm. Pinus montezumae. In each nutritional block, protein, lipids, and carbohydrates. Letters a, b, c, and d indicate significant differences, P < 0.05; mean ± SE. Fig. 2. Contenido de proteínas, lípidos y carbohidratos en las semillas de cuatro especies de pino de un bosque templado del centro del estado de Veracruz, México. En cada grupo nutricional, proteínas, lípidos y carbohidratos. Las letras a, b, c y d indican diferencias significativas con P < 0,05; media ± EE. (Para las abreviaturas de las especies, véase arriba.)

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0.40 0.38 0.36 0.34 0.32 0.30 0.28 0.26 0.24 0.22 0.20 0.18 0.16 0.14 0.12

B a

c b d Pp

0.9

0.8 Tannic acid (%)

Gallic acid (%)

Pps Pt Pm Pine seed species

0.7 0.6 0.5 0.4 0.3

0.2

0.1 0.0

Pps Pt Pm Pine seed species

Fig. 3. Concentrated tannins: percentage of galllic acid (A) and tannic acid (B) found in 100 g of seeds from four pine species in temperate forest in the central area of Veracruz State, Mexico: Pp. Pinus patula; Pps. Pinus pseudostrobus; Pt. Pinus teocote; Pm. Pinus montezumae. Letters a, b, c, and d indicate significant differences at P < 0.05; mean ± SE. Fig. 3. Concentración de taninos: porcentaje de ácido gálico (A) y ácido tánico (B) registrado en 100 g de semillas de cuatro especies de pino en un bosque templado del centro del estado de Veracruz, México. Las letras a, b, c y d indican diferencias significativas con P < 0,05; media ± SE. (Para las abreviaturas de las especies, véase arriba.)

Total content of gallic acid among seed species was significantly different (H = 14.15, df = 3, P = 0.0027), with seeds of P. patula showing the highest percentages (0.364 ± 1.2) (fig. 3A). Among species of seeds, the total amount of tannic acid was also significantly different (H = 10.42, df = 3, P = 0.0153), with seeds of P. teocote showing the highest levels (0.795 ± 0.5) (fig. 3B). We caught a total of 248 animals belonging to nine species of mice from five genera and one family (Muridae). Five species were granivores, and four were omnivores; all are potential seed predators. We used 124 of these mice for the preference experiments, but only six species reached more than 12 individuals captured and were included in statistical analysis (table 2). The majority of rodents (five species) chose P. patula and P. pseudostrobus seeds more often than P. montezumae (table 3, fig. 4); and all these species consumed more P. patula and P. pseudostrobus seeds (table 3, fig. 5). Discussion We identified interspecific variation among the length and width of pine seed species. P. teocote and P. montezumae seeds were longer and wider than the other species studied. The nutritional contents of seeds also differed significantly among pine species. P. teocote seeds had the highest content of protein and tannic acid, P. patula seeds were highest in lipids and carbohydrates, and P. montezumae seeds had the lowest percentages of gallic and tannic acid. The

Table 2. Nine mouse species recorded in a temperate forest in central Veracruz, Mexico. The total number of individuals (N), the number of individuals per species used in the experiments (NE) and food guild (FG: O. Omnivore; G. Granivore) are given. Tabla 2. Nueve especies de roedores registradas en un bosque templado del centro de Veracruz, México. Se proporcionan el número total de individuos (N), el número de individuos por especie usados en los experimentos (NE) y el gremio alimentario (FG: O. Omnívoro; G. Granívoro). Mouse species

Peromyscus melanotis

Peromyscus maniculatus

Reithrodontomys mexicanus 41

Reithrodontomys fulvescens

Reithrodontomys megalotis

Reithrodontomys sumichrasti 12

Mus musculus

Microtus mexicanus

Neotomodon alstoni Total

248 124

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Table 3. Summary of the general linear mixed model test evaluating feeding preferences of six rodent species: Z. Z–score; P. P–value; Pm. Pinus montezumae; Pp. Pinus patula; Pps. Pinus pseudostrobus; Pt. Pinus teocote. Bold numbers indicate Z values with significant differences at P < 0.05. Tabla 3. Resumen del modelo lineal generalizado mixto para evaluar las preferencias alimentarias de seis especies de roedores. Los números en negritas indican diferencias significativas con P < 0,05 para los valores Z. (Para las abreviaturas, véase arriba.)

P. maniculatus

Z;P

P. melanotis R. mexicanus R. fulvescens Z;P

Z;P

R. megalotis R. sumichrasti Z;P

Z;P

Chosen seed Pp vs. Pm

2.920;0.018

1.494;0.438 5.288;<0.001 5.641;<0.001 4.657;<0.001 4.027;<0.001

Pps vs. Pm

2.646;0.039

3.331;0.005

4.015;<0.001

3.238;0.006

3.106;0.009

Pt vs. Pm

–1.638;0.353 –1.357;0.523 2.927;0.017

3.705;<0.001

0.769;0.866 2.134;0.136

Pps vs. Pp

–0.295;0.991 1.925;0.215 –1.902;0.220 –3.651;0.001

–2.001;0.184 –0.750;0.872

3.571;0.002

Pp vs. Pt

–4.243;<0.001 –2.759;0.029 –3.281;0.006 –3.050;0.012 –4.229;<0.001 –2.729;0.029

Pps vs. Pt

–4.008;<0.001 –4.415;<0.001 –1.454;0.457 0.662;0.908 –2.502;0.058 –2.036;0.167

Number of seeds consumed Pp vs. Pm 10.190;<0.001 7.883;<0.001 11.850;<0.001 10.431;<0.001 9.237;<0.001 9.042;<0.001 Pps vs. Pm 9.644;<0.001 10.342;<0.001 9.874;<0.001 8.752;<0.001 7.790;<0.001 7.786;<0.001 Pt vs. Pm

0.626;0.921 –1.490;0.4323 2.527;0.054

Pps vs. Pp

–0.723;0.884

Pp vs. Pt

–9.789;<0.001 –8.932;<0.001 –9.927;<0.001 –9.386;<0.001 –9.135;<0.001 –8.603;<0.001

Pps vs. Pt

–9.223;<0.001 –11.164;<0.001 –7.762;<0.001 –7.639;<0.001 –7.679;<0.001 –7.307;<0.001

3.102;0.010

1.282;0.570

–2.438;0.068 –1.947;0.205

majority of rodents (five species) chose P. patula and P. pseudostrobus seeds and all rodents consumed more small seeds from P. patula that were rich in lipids and gallic acid and from P. pseudostrobus with an intermediate content of protein, carbohydrates and gallic acid. The pine seeds studied show variation in characteristics such as length and width (Perry, 2009), as related to the particular biology of each species and environmental conditions (Eguiluz, 1982). Several studies have reported that seed size is a decisive factor for scatter–hoarding rodents in the choice between seed predation and dispersal (Wang & Chen, 2009; Wang et al., 2013) because seed size is frequently correlated with handling time and energy payback (Brewer, 2001), which in turn had a bearing on the efficiency of foraging (Waite & Ydenberg, 1994) and predation risk (Lima et al., 1985; Sivy et al., 2011). The general consensus is that larger seeds are more likely to be removed rather than eaten in situ (Jansen et al., 2004); in our case, this gives a certain advantage to species such as P. montezumae and P. teocote for their dispersal and establishment, and is associated with other factors such as the particular regeneration strategies of each species. P. montezumae, for example, grows slowly and has a cespitose habit during its early years, although its root development is substantial (Vera et al., 1988). This confers an advantage to P. teocote, whose longer seeds are

0.134;0.999

0.610;0.927

–1.711;0.312 –1.547;0.402

related to higher seedling growth rates and production of more vigorous seedlings (Ramírez–García, 2000), and adaptability to impoverished soils, where they are capable of becoming established and emerging as the dominant species (Perry, 2009). Many tree species that depend on scatter–hoarding animals for seed dispersal also produce massive crops of large seeds at irregular intervals; in pines, this process is known as seedbed years (Perry, 2009). Mast seeding and large seed size in these species have been explained as adaptations to increase animal dispersal and reduce predation (Jansen et al., 2004). Hereby, the comparison between seeds eaten in situ and removed by rodents is important because they have different consequences for the reproductive success and composition of plant species, i.e., seeds removed indicate some probabilities of success of seed dispersal and seedling establishment, while seeds eaten in situ mean total seed predation (Stiles, 2000; Morán–López et al. 2015; Wang & Yang, 2015). Seed size, however, is not the only determining factor in seed removal and dispersal (Wang & Chen, 2012). Other factors such as the nutritional quality and defensive secondary compounds particularly tannic acids are also involved in the plant–animal interactions (Vander Wall, 1990; Yi et al., 2015). Several studies have documented that large seeds of Quercus, Lithocarpus, Cyclobalanopsis, Castanopsis

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a 0.4

0.4 0.3

0.4

0.3 d

0.2

0.0 Pp Pps Pt Pm Pp Pps Pt Pm Peromyscus melanotis Peromyscus maniculatus a a 0.5 0.5

0.0

0.4

0.3

0.4 b

0.1 0.0

0.3

0.2

Pp Pps Pt Pm Reithrodontomys fulvescens

0.1 0.0

0.5

Pp Pps Pt Pm Reithrodontomys mexicanus a b

0.3

0.2 c

0.1

0.0

0.4

0.2

0.1

0.3

Seeds chosen (%)

0.2 0.1

Pp Pps Pt Pm Reithrodontomys megalotis

0.0

c d

Pp Pps Pt Pm Reithrodontomys sumichrasti

Fig. 4. Proportion of seeds chosen from four pine species by six species of rodents, captured over a one–year period in the temperate forest in the central area of Veracruz State, Mexico: Pp. Pinus patula; Pps. Pinus pseudostrobus; Pt. Pinus teocote; Pm. Pinus montezumae. Letters a, b, c, and d indicate significant differences at P < 0.05; mean ± SE. Fig. 4. Proporción de semillas elegidas de cuatro especies de pino por seis especies de roedores capturados en el periodo de un año en el bosque templado del centro del estado de Veracruz, México. Las letras a, b, c y d indican diferencias significativas con P < 0,05; media ± SE. (Para las abreviaturas de las especies, véase arriba.)

and Carapa genus in a subtropical forest of Southwest China are more often selected by rodents possibly because of their high nutritional quality (Jansen et al., 2004; Xiao et al., 2004, 2006), as larger food size often maximizes energy payback for seed consumers (Brewer, 2001). Similarly, some studies have suggested that rodents prefer to cache seeds with high tannin levels and consume seeds with low tannin levels (Smallwood et al., 2001; Shimada & Saitoh, 2003). In other studies, rodents have been shown to eat low–tannin acorns in situ and hoard high–tannin acorns (Barthelmess, 2001; Smallwood et al., 2001; Xiao et al., 2008), whereas other studies have found different, even opposite results (Xiao et al., 2006; Wang & Chen, 2009, 2011). Rodents not only feed on readily available resources, but also select foods high in certain chemical components and low in others, thus regulating their needs and energy expenditure (Bozinovic et al., 1997). Understanding seed preference in scatter–hoarding rodents is thus

complicated because selection involves a complex decision–making process (Wang & Chen, 2012). Fat and protein are key nutrients that determine the nutritional quality of a food item in mammalian diets, and hence play an important role in rodent foraging processes (Xiao et al., 2006; Takahashi & Shimada, 2008); on the other hand, concentrated tannins also affect rodent foraging behavior and in turn, seed fate (Vander Wall, 2010). Our results contrast with these assumptions, however, if we consider the individual effect of size, nutritional quality and tannin presence. Seeds of P. patula, considered small, had a high fat content and concentrated tannins such as gallic acid and P. teocote seeds (big seeds) had a high protein content but also the highest amounts of tannic acid. Fat is an important energy source that directly affects survival and reproduction in animals. Rodents appear to prefer seeds with high quantities of fat (Xiao et al., 2006) because these provide an energy resource in winter (Steele, 2008). Rodents from the

No seeds consumed

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2 b

No seeds consumed

4 3 2

5 b

4 c

5 a

Pp Pps Pt Pm Reithrodontomys fulvescens

Pps Pt Pm Reithrodontomys mexicanus

3 b

3 c

0 0 Pp Pps Pt Pm Pp Pps Pt Pm Peromyscus melanotis Peromyscus maniculatus

3 b

1 Pp Pps Pt Pm Reithrodontomys megalotis

Pp Pps Pt Pm Reithrodontomys sumichrasti

Fig. 5. Number of seeds from four species of pine tree consumed by six rodent species in a temperate forest from the central area of Veracruz State, Mexico: Pp. Pinus patula; Pps. Pinus pseudostrobus; Pt. Pinus teocote; Pm. Pinus montezumae. Letters a, b, c, and d indicate significant differences at P < 0.05; mean ± SE. Fig. 5. Número de semillas consumidas de cuatro especies de pino por seis especies de roedores en un bosque templado del centro del estado de Veracruz, México. Las letras a, b, c y d indican diferencias significativas con P < 0,05; media ± SE. (Para las abreviaturas de las especies, véase arriba.)

genus Peromyscus, for example, have an affinity for seeds with a high lipid content, such as those from Pinus cembroides (piñon or pinyon pine), rather than those from P. discolor (Martinez–Delgado et al., 1996). In our study, the majority of rodents chose and consumed small seeds of P. patula and P. pseudostrobus, high in fat and gallic acid content, low in tannic acid content, and an intermediate level of protein and carbohydrate content. These results indicated that rodents commonly performed energy balances based on their digestive capacity. Similarly, desert rodents prefer diets with specific combinations of proteins, lipids and carbohydrates, which also prevent metabolic water loss (Chad et al., 2001). According to Wang & Chen (2012), rodents choose and remove seeds with a high fat and protein content because these elements can mitigate the negative effects of foods with high concentrations of tannins. In our case, the high consumption of P. patula seeds —those with the highest fat amounts— can mitigate

the negative effects of gallic acid. In contrast, P. teocote seeds, that had the highest amount of proteins and tannic acid, were consumed less. In laboratory experiments with rats, gallic acid has been considered an excellent antioxidant with protective effects against toxic elements (Vijaya–Padma et al., 2011). Furthermore, it is a polyphenol involved in the metabolism of carbohydrate assimilation, preventing its antioxidant properties from being converted into fat (Hanhineva et al., 2010), which may explain the consumption of P. pseudostrobus seeds with an intermediate carbohydrate content. It is possible that rodents consume seeds with high amounts of this compound because it allows them to regulate their metabolism and energy optimization because of their beneficial anti–inflammatory, anti–allergenic and cardiovascular properties (Martin & Appel, 2009). Regarding protein content, in a cafeteria experiment, when offered natural and artificial food, Peromyscus leucopus selected those foods with 15% protein over

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those that had 5%, 25% and 35% (intermediate content), demonstrating that selection is not only based on nutritional needs, but also on metabolic capacity and digestibility (Chad et al., 2001). Similarly, a study of the food preferences of the rodent Clethrionomys gapperi using natural and commercial foods revealed similar results, a preference for food with 14% protein over those with 20 and 30% (Kasparian & Millar, 2004). Protein levels are also important for the growth and reproduction of rodents (Cameron & Eshelman, 1996), which they select depending on their physical requirements (Bensaid et al., 2002). This is due to the fact that in rodents there are critical levels for assimilation of protein that relate to normal growth and maintenance of healthy animals (Shenk et al., 1970). Our results clearly support the comments of Vander Wall (2010) and Wang & Chen (2012) showing that set traits of certain pine seeds, such as size, nutritional content and chemical defenses, are indicators of seed quality, affect rodent foraging decisions in a temperate forest, and are involved with the plant species composition of the site. Seed traits influence rodent foraging preferences because all seed traits are combined, and it is difficult to distinguish individual trait effects on rodents foraging behavior or the interactions among them. A large number of plants, such as pines (Perry, 2009; Zong et al., 2010; Nopp–Mayr et al., 2011; Lobo, 2013; Yi et al., 2015), show differences in seed traits (Díaz, 1996; Wang & Chen, 2008, 2012), and are a key element for understanding the foraging behavior of rodents and also their physiological condition and energy optimization (Blate et al., 1998; Wang & Chen, 2009; Sivy et al., 2011). However, other aspects, such as regenerative strategies of species, are also involved (Hulme & Kollmann, 2005). Detailed studies of these processes and foraging strategies among rodents are essential to understand the dynamics involved in the establishment and persistence of plant communities. Acknowledgments The Mexican Science Council (CONACYT) awarded a doctoral studies scholarship (175058) to R. Flores Peredo. The 'Instituto de Biotecnología y Ecología Aplicada' (INBIOTECA) of the 'Universidad Veracruzana' provided the installations for the indoor research and laboratory access. The 'Facultad de Nutrición of the Universidad Veracruzana' provided the equipment for the bromatological analyses. The Food Laboratory in the Chemistry Faculty of the UNAM provided equipment for the analysis of secondary compounds. Lorena López Lozada contributed valuable suggestions and comments with reference to the statistical analyses. References Alasalvar, C. & Shahidi, F., 2009. Tree nuts: Composition, Phytochemicals, and Health effects. CRC Press. Boca Raton, FL, USA. AOAC, 2005. Official Methods of Analysis of AOAC International. 18th ed. AOAC Int, Gaithersburg, MD.

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Éxito reproductivo de los pájaros bobos patas azul, Sula nebouxii, y los pájaros bobos café, Sula leucogaster, como indicador de perturbación por uso turístico en las Islas Marietas, México

J. L. Cornejo–Ortega, R. M. Chávez–Dagostino & F. G. Cupul–Magaña Cornejo–Ortega, J. L., Chávez–Dagostino, R. M. & Cupul–Magaña, F. G., 2016. Éxito reproductivo de los pájaros bobos patas azul, Sula nebouxii, y los pájaros bobos café, Sula leucogaster, como indicador de perturbación por uso turístico en las Islas Marietas, México. Animal Biodiversity and Conservation, 39.2: 185–193. Abstract Breeding success of the blue–footed booby, Sula nebouxii, and the brown booby, Sula leucogaster, as an indicator of touristic disturbance in the Islas Marietas, Mexico.— We studied the breeding success of two seabird species, the blue–footed booby, Sula nebouxii, and the brown booby, Sula leucogaster, in relation to touristic disturbance in order to focus conservation management strategies in the protected area of the Marietas Islands in Bahía de Banderas, Mexico. Data were collected throughout the breeding season of 2013 at Isla Larga. We considered three sites under different conditions of simulated disturbance within the colonies: 'medium', visits constrained to a single path; 'high', visits without spatial restrictions, and 'low', no visits. The total numbers of nests, eggs and chicks for each species were recorded weekly at the three sites. On the basis of these data, we determined the viability of eggs (hatching success) and chicks. A generalized linear mixed model (GLIMMIX) showed that breeding success (eggs–to–fledglings rate) had no relationship to the conditions of the area and but was significantly lower in the blue–footed booby. The presence of tourists, as measured in this study, was not the cause of nesting failure. Other, non–evaluated factors likely play a role in limiting the breeding success of the two species of booby studied here. Key words: Fertility, Hatching, Booby birds, Nests Resumen Éxito reproductivo de los pájaros bobos patas azul, Sula nebouxii, y los pájaros bobos café, Sula leucogaster, como indicador de perturbación por uso turístico en las Islas Marietas, México.— Se analizó de forma experimental el posible efecto de las visitas turísticas en el éxito reproductivo de dos especies de pájaro bobo, el de patas azules, Sula nebouxii, y el café, Sula leucogaster, a fin de proponer estrategias de gestión para su conservación en el área natural protegida Islas Marietas en Bahía de Banderas, en México. Los datos se recopilaron durante la temporada de anidación de 2013 en Isla Larga. Se escogieron tres sitios con distintas condiciones de perturbación simulada en las colonias: ''medio'', con visitas limitadas a un único sendero; ''alto'', con visitas sin ningún tipo de regulación en el espacio; y ''bajo'', sin visitas. A través de la observación de nidos durante toda la crianza, se determinó en cada momento el número total de huevos y pollos de cada especie, así como la viabilidad de los huevos (éxito de eclosión) y los pollos, desde el nacimiento hasta el vuelo. Un procedimiento de elaboración de modelos (GLIMMIX) mostró que la relación entre las condiciones de las tres zonas y las tasas de éxito de reproducción de ambas especies (huevos que dieron lugar o no a pollos volantones) no fue significativa, si bien el éxito reproductor del pájaro bobo de patas azules fue significativamente inferior. Concluimos que la presencia de visitas simuladas no influyó en la probabilidad de malogro de los nidos, por lo que probablemente existen otros factores limitantes del éxito reproductor que se desconocen y que afectan por igual a las poblaciones objeto de estudio. Palabras clave: Fertilidad, Eclosión, Pájaros bobos, Nidos Received: 11 IV 14; Conditional acceptance: 21 X 14; Final acceptance: 8 IV 16 José Luis Cornejo–Ortega, Rosa María Chávez–Dagostino & Fabio Germán Cupul�� –�� Magaña, Centro Universi� tario de la Costa de la Universidad de Guadalajara, 48280 Puerto Vallarta, Jalisco, México. Correspondencia: J. L. Cornejo. E–mail: jose.luiscornejo@hotmail.com ISSN: 1578–665 X eISSN: 2014–928 X

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Introducción

Material y métodos

La transformación acelerada a la que son sometidos los ecosistemas repercute en la biodiversidad tanto a escala global (Mensing et al., 1998; MEA, 2005; Fu et al., 2003) como local (Angermeier & Schlosser, 1995). El turismo se ha convertido en una de las actividades económicas más importantes del mundo; su rápido crecimiento ha creado una gran demanda de recursos en los ambientes locales que ha perjudicado la biodiversidad, debido en gran parte a la falta de planificación y de medidas preventivas (Palacio–Núñez et al., 2007). Se estima que el ecoturismo por sí solo contribuye al 9% del PIB mundial, lo que representó un mercado de 6.000 mil millones de USD en 2011 (INTOSAI–WGEA, 2013). Sin embargo, recientemente se ha reconocido que las actividades recreativas en la naturaleza representan una nueva y grave amenaza para los ecosistemas (Taylor & Knight, 2003; Sutherland, 2007) cuyos efectos más frecuentes se producen en el rendimiento reproductivo (Watson & Moss, 2004; Langston et al., 2007) y la supervivencia (Müllner et al., 2004). Debido a estos problemas, es deseable que las estrategias ecoturísticas contemplen el uso responsable de los recursos naturales, que haya una participación de la población local y que se informe al visitante (Boo, 1992; Ross & Wall, 1999; Burger, 2000). Por ello, estas estrategias deben planificarse y adaptarse a cada espacio y proyecto. El estado de conservación de una zona puede evaluarse sobre la base de bioindicadores (Randall, 1992); sin embargo, en los ecosistemas protegidos se utilizan la presencia, distribución o abundancia de especies amenazadas o endémicas como indicadores de cambios en los ecosistemas (Heino et al., 2005; Rubinoff & Powell, 2004). Determinadas especies de aves son un magnífico grupo indicador (Pyrovetsi & Papastergiadou, 1992; Browder et al., 2002) y algunas de ellas, en razón de su estrategia de vida, pueden utilizarse para elaborar predicciones de respuesta a la presencia humana (por ejemplo, Tershy et al., 1997; Higginbottom et al., 2003; Newsome et al., 2004). En caso de que una población de aves sea intolerante a la presencia humana, ello proporcionaría una ''alerta temprana'' que permitiría modificar las estrategias de uso turístico a corto plazo en caso necesario. Este trabajo tiene como objetivo analizar el éxito reproductivo de los pájaros bobos café, S. leuco� gaster, y los pájaros bobos de patas azules, Sula nebouxii, en tres zonas del Parque Nacional Islas Marietas (costa pacífica mexicana) en distintas condiciones de estrés provocado con el fin de establecer si existe dependencia entre el éxito reproductivo y la presencia de turistas. Nuestra hipótesis de partida establece que el éxito reproductivo será sensible a diferentes grados de molestias. Específicamente, predecimos que el fracaso reproductor será mayor en condiciones de visitas no reguladas (sin senderos) en comparación con visitas reguladas (en senderos balizados) y en ausencia de visitas. A partir de los resultados obtenidos se pretende obtener directrices para elaborar estrategias de gestión encaminadas a disminuir los efectos negativos del turismo.

Zona de estudio Las Islas Marietas se sitúan en la costa meridional del estado de Nayarit (México), en el municipio de Bahía de Banderas (fig. 1). Ocupan una superficie total de 1.383 ha y fueron declaradas área protegida con categoría de Parque Nacional en el año 2005. Lo integran dos islas principales: Isla Larga e Isla Redonda, además de algunos islotes menores. El archipiélago posee un gran valor científico y educativo por su riqueza faunística. Las islas son fundamentales para los procesos reproductivos de poblaciones de especies protegidas por el gobierno mexicano y se consideran de gran belleza escénica (DOF, 2010). Asimismo, constituyen una importante zona de refugio y tránsito para 92 especies de aves (CONANP, 2007), aunque solo nidifican ocho, entre ellas el pájaro bobo café, S. leucogaster, y el pájaro bobo de patas azules, S. nebouxii, cuyas poblaciones se calcula ascienden a 112.626 y 7.435 individuos, respectivamente (Rebón–Gallardo, 2000); además, son el lugar donde se concentra la mayor población mundial de la primera especie. A pesar de que en Isla Larga predominan las aves reproductoras residentes de verano y en Isla Redonda existe una mayor proporción de residentes permanentes, es posible observar comportamientos reproductivos de alguna especie de ave en ambas islas, en las que los bobos comparten hábitat, durante todo el año. Las dos especies objeto de estudio no se encuentran amenazadas a escala global, son de amplia distribución y muestran un fuerte gregarismo tanto durante la reproducción como en la alimentación. Asimismo, anidan sobre el suelo, generalmente en zonas planas entre la vegetación o las rocas, ponen de uno a tres huevos y los nidos de ambas pueden encontrarse poco distantes entre sí y mezclados. Sin embargo, el bobo café de las Islas Marietas reúne pasto para hacer el nido, que generalmente se observa en suelo más pronunciado, mientras que el bobo pata azul prescinde del pasto o hace el nido sobre él. El ciclo reproductor de las dos especies es muy similar: ponen de uno a tres huevos que incuban por cerca de 41 días. Las crías tardan poco más de tres meses en alcanzar la edad de volar y los padres aún las cuidan y alimentan durante 56 días más. Comienzan a reproducirse entre los dos y tres años de edad. Su temporada de anidación va de enero a agosto (Carboneras, 1992). Antiguamente, las islas estuvieron ocupadas de forma temporal por campamentos de pescadores que en diversas épocas capturaban diferentes especies, como tiburones, madreperlas, moluscos y pepinos de mar. También la recogida de guano fue una actividad importante. Antes del decreto que declaró las islas zona natural protegida, las visitas de lugareños y turistas prácticamente no tenían restricciones e incluso se podían organizar fiestas y campamentos en el lugar. Sin embargo, no existía una oferta turística organizada para visitar la zona terrestre de la zona. A raíz de dos incendios ocurridos en Isla Redonda

20º 42' 30'' N

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Océano Pacífico

Isla Redonda

20º 42' 0'' N

Isla Larga

B A México Islas Marietas

105º 35' 0'' W

105º 34' 30'' W

100

200 m

105º 34' 0'' W

Fig. 1. Localización de Islas Marietas y zonas de observación de nidos con diferentes grados de estrés potencial derivado de visitas: A. Alto; B. Medio; C. Bajo (modificado de CONANP, 2007). Fig. 1. Location of the Marietas Islands and the observation zones subjected to different intensities of potential stress by visitors: A. High; B. Medium; C. Low (modified from CONANP, 2007).

en 1996 y en 1997 en Isla Larga (Rebón–Gallardo, 2000), ambos aparentemente provocados, se restringieron las visitas a las islas. Según el plan de ordenación (CONANP, 2007), en la actualidad se pueden realizar actividades turísticas en Isla Larga, por lo cual es necesario llevar a cabo estudios que generen información sobre los posibles efectos que ello tendría en algunos grupos como las aves, a fin de minimizarlos. Procedimientos de campo Las observaciones se realizaron en Isla Larga. Se establecieron tres zonas de muestreo (fig. 1): Zona A, esta zona y la adyacente forman parte de la zona central de uso restringido, donde se permite realizar actividades de educación ambiental y ecoturismo. En ella se encuentra ubicado un proyecto de sendero interpretativo de aproximadamente 180 m de longitud, al que se accede desde la playa, que sube por una zona rocosa y continúa por una zona plana de poca pendiente con pastizales, hasta una cueva. Durante el estudio, el sendero estuvo cerrado, pero se prevé que se abra al uso público a partir de 2017 y que puedan utilizarlo un máximo de 36 visitantes al día (Cornejo et al., 2011). Zona B, se encuentra detrás de la cueva en la zona oriental de la isla, en una zona protegida donde se permite la monitorización biológica y la investigación científica, previa autorización de las autoridades del parque, pero donde no se prevé permitir el uso turístico. Zona C, localizada sobre la cueva en la parte centrooriental de la isla (fig. 1), fuera del área de uso público y de difícil acceso, se considera una zona ''control''.

Los registros dirigidos a identificar, caracterizar y monitorizar los nidos de pájaros bobos se realizaron mediante visitas semanales entre enero y julio de 2013, es decir, 28 visitas en total a cada zona. Para ello se constituyeron grupos de entre dos y seis visitantes a los que previamente se instruyó sobre la forma en que habían de comportarse durante el recorrido. En cada una de las visitas, el mismo número de visitantes acudió a las zonas A y B. En el primer caso (grado ''medio'' de molestias), los visitantes siguieron solamente el sendero, observaron y hablaron en voz baja teniendo cuidado de no acercarse a menos de 5 m de los nidos, tomaron fotografías y escucharon una explicación. En los nidos de la zona B (grado ''alto''), el grupo de visitantes no siguió un sendero, se acercó a una distancia de 1–5 m de los nidos, no observó las reglas estipuladas para el sendero y habló en voz alta durante el recorrido. La zona C solamente fue visitada por un investigador que realizó las observaciones con binoculares con la menor perturbación posible (grado ''bajo''). En cada una de las tres zonas, A, B y C, se estableció un transecto lineal de 180 m que corresponde a la longitud total del sendero establecido para uso público de la zona A. Además, se estableció una zona de observación, de 5 m a cada lado, a lo largo de cada transecto. Durante cada recorrido se identificaron los nidos y la especie, y se contabilizó el número de huevos y de polluelos. Cada nido se identificó con un número y se le dio seguimiento registrando los cambios que se produjeron durante el periodo de observación. Se consideró que un nido tenía éxito si al menos un pollo llegaba a volar (Beale & Monaghan, 2005).

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Análisis de datos Para cada especie se representaron gráficamente las fechas de máxima abundancia de nidos, huevos y pollos. A través de las observaciones realizadas en cada uno de los nidos y huevos se determinó la viabilidad, la fertilidad, el éxito de eclosión y el éxito del pollo de acuerdo con Mayfield (1975) y con Erwin & Custer (1982), donde la viabilidad (V) corresponde a la proporción de huevos que permanecieron en el nido (Hv) por lo menos durante el periodo de incubación (Ht) sin sufrir daño aparente, en relación con el total de huevos puestos. La fertilidad (F) se consideró como la proporción de huevos que eclosionaron (He) en relación con el número de huevos viables (Hv). El éxito de eclosión es la proporción de huevos que eclosionan respecto del total de huevos puestos y el éxito del pollo se consideró como la proporción de pollos que llegaron a la edad de volantón respecto al número de huevos eclosionados. Hemos utilizado modelos mixtos lineales generalizados (GLIMMIX) para analizar la relación entre la variable respuesta ''éxito reproductor'' (vuelan o no pollos: 1/0, distribución binomial con función de enlace logit) y tres variables explicativas: la ''zona de anidamiento'' (A, B y C), la ''especie'' (pájaros bobos de patas azules, Sula nebouxii, y bobos café, Sula leucogaster) y la interacción entre ellas. Ambas variables explicativas se consideraron variables categóricas. Además, para evitar la no independencia de los datos, todos los modelos incluyeron el ''huevo'' anidado en el ''nido'' como término aleatorio. Todos los análisis se realizaron en R 3.1.3 (R Studio Team, 2015) y se seleccionó el mejor modelo de acuerdo con el criterio de Akaike (AIC) y la corrección para muestras pequeñas (AICc). Resultados En total, se registraron y monitorizaron 52 nidos de ambas especies (34 de S. nebouxii y 18 de S. leucogaster), y se distribuyeron de la siguiente forma: zona A: 13 y 3; zona B: 11 y 4; y zona C: 10 y 11. La temporada reproductiva de S. nebouxii se prolongó desde febrero hasta julio (figs. 2A, 2B). Teniendo en cuenta que aparecieron nidos activos en julio, es probable que la nidificación continuara de forma esporádica en los meses subsecuentes. Hubo una pauta similar en la cronología de puesta y eclosión de S. leucogaster, aunque algo desfasada en el tiempo, ya que comenzó en marzo y finalizó en julio. Sin embargo, en otras zonas de la isla fuera del área de los recorridos experimentales, se observó anidación activa después del mes de julio y, por ello, la temporada reproductiva de esta especie es más amplia que la de S. nebouxii. El tamaño medio de la puesta fue respectivamente de 1,8 para S. nebouxii (9 nidos con un huevo; 22 con 2, y 3 con 3) y de 1,5 para S. leucogaster (respectivamente 8, 10 y 0). En conjunto y para las tres zonas de estudio, las variables que evaluaron el éxito reproductor mostraron que la viabilidad de los huevos de S. leucogaster resultó mucho menor que

la de los de S. nebouxii, mientras que la fertilidad fue mayor (fig. 3). Los valores de éxito de la eclosión y del pollo mostraron valores similares. No obstante, es obvio que estas frecuencias están muy influenciadas por el tamaño de las muestras, que es relativamente bajo para S. leucogaster (tabla 1). Los análisis estadísticos realizados mediante GLIMMIX revelaron que no hubo diferencias significativas en el éxito reproductor entre las distintas zonas. Sin embargo, sí se produjo una variación significativa al considerar la especie, de modo que el éxito reproductor fue significativamente más bajo para el pájaro bobo de patas azules (valor de Z = –2,937; P = 0,0033), lo que corrobora lo anteriormente señalado. La interacción entre la zona y la especie tampoco arrojó resultados significativos en el éxito reproductor. Discusión Nuestros resultados parecen indicar que el éxito reproductor de los pájaros bobos varía en función del grado de molestias a que se ve sometida la zona de muestreo (S. leucogaster: el 9% en la zona B ''alto'' en comparación con el 50% en la zona C ''bajo''; S. nebouxii: el 75% en comparación con el 82%). De hecho, Schreiber (2002) menciona que los valores bajos del éxito de eclosión de los huevos pueden estar relacionados con la alteración del desarrollo embrionario causada por la sobreexposición al sol o por la falta de calor, algo que ocurriría si el ave que incuba es molestada por los visitantes. Sin embargo, la elaboración de modelos revela que estas diferencias no son achacables al tratamiento por zona, sino que solamente la variable ''especie'' resultó incluida significativamente. En consecuencia, puede concluirse que el éxito reproductivo de las especies objeto de estudio es independiente de la presencia de visitantes. Estos resultados concuerdan con los encontrados por Beale & Monaghan (2005) en Escocia para dos especies de aves marinas: Rissa tridactyla y Uria aalge. Estos autores no encontraron una relación significativa entre la tasa de malogro de los nidos y el número de visitantes. Ambas especies de pájaros bobos registraron un éxito de eclosión muy bajo (15,8%) en 2013 en comparación con los registros en otros lugares dentro del área de distribución de las especies (fig. 4). Ceyca & Mellink (2009) analizaron el éxito de los bobos café de Morros El Potosí, en México, y obtuvieron un éxito de eclosión del 61% en la temporada 2006, similar a los registros de San Pedro Mártir, en México (63,6%; Tershy et al., 2000), las islas Kure (61,2%, Woodward, 1972), el atolón de Johnston (63%) y la isla de Navidad (51%, Nelson, 1978). Por el contrario, en las colonias del golfo de California el éxito de eclosión en 2003 fue muy bajo (el 23,7% en la isla San Jorge y el 16,4% en el farallón de San Ignacio), lo que se atribuyó a la presencia del fenómeno El Niño (Suazo–Guillén, 2004). Aunque el éxito de eclosión fuera bajo, el éxito reproductivo de las crías de los pájaros bobos en nuestra zona de estudio fue de casi el 100%, lo que nos indica que una vez que

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Sula nebouxii

40 35 30 N

Nidos

Huevos

Pollos

10 5 0 B

Enero Febrero Marzo Abril

Mayo Junio

Julio

Sula leucogaster

20 Nidos

Huevos 10

Pollos

5 0

Enero Febrero Marzo Abril Mayo Junio Periodo de estudio

Julio

Fig. 2. Número mensual de nidos, huevos y pollos de: A. S. nebouxii; B. S. leucogaster. Fig. 2. Monthly number of nests, eggs and chicks of: A. S. nebouxii; B. S. leucogaster.

el huevo eclosiona las posibilidades de que el pollo sobreviva y llegue a volantón son muy altas. Por otra parte, en cuanto a otros parámetros reproductores, las cifras obtenidas fueron aparentemente normales en comparación con otras colonias estudiadas. Así, la cronología de anidación de los bobos de patas azules y los bobos café fue muy similar, si bien el primero comenzó más temprano (febrero) su anidación, en comparación con el segundo (marzo), con un máximo entre marzo, abril y mayo para ambas especies que coincide con lo observado por Hernández (2005) para el bobo café. También los tamaños de puesta encontrados en la zona de estudio se ajustan a lo descrito para las especies en otras colonias de su área de distribución. Aunque en algunas colonias los

bobos café pueden tener nidadas de tres huevos (por ejemplo en las islas de Cabo Verde, las islas del Swain Reefs y la isla San Jorge; Hazevoet, 1995; Schreiber & Norton, 2002; Suazo–Guillén, 2004), lo común es que sean de dos (Schreiber & Norton, 2002). En casi todas las colonias el porcentaje de nidos con dos huevos ha sido superior al 58% (Woodward, 1972; Hazevoet, 1995; Schreiber & Norton, 2002), igual que en Morros El Potosí (el 59% de nidos con dos huevos, el 41% de nidos con un huevo) (Ceyca & Mellink, 2009). De todo lo anteriormente expuesto se deduce que las colonias de pájaro bobo de la zona de estudio mostraron un éxito reproductor muy bajo debido a que los huevos no llegaron a eclosionar y que ello

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Tabla 1. Éxito de la eclosión (Ee, huevos que dan lugar a pollos) por especie en cada zona de estudio. Table 1. Hatching success (Ee, eggs that produced chicks) of the two species in each study zone. Zona

Especie

Uso público (A) S. nebouxii

30,8% 13

S. leucogaster

33,3% 3

Estrés (B)

S. nebouxii

9,1% 11

S. leucogaster

75%

Control (C)

S. nebouxii

50%

S. leucogaster

81,8% 11

no puede atribuirse a la intervención humana realizada en este estudio. Determinar otros factores que puedan influir requerirá realizar posteriores aproxima-

ciones de investigación. El éxito reproductivo puede estar influenciado por numerosos factores bióticos y abióticos (Rotenberry & Wiens, 1991) y aunque, en general, en las aves marinas se puede utilizar como un indicador de la calidad del ambiente —pues refleja la disponibilidad de alimento en el mar (Cairns, 1992; Furness, 2003) o la contaminación que afecta, entre otros aspectos, al grosor de la cáscara del huevo (Blus et al., 1997; Giesy et al., 2003)—, no existen indicios de escasez de alimento o contaminación actual en la zona. Además, debe mencionarse que en las muestras recogidas en 2006 de huevos de bobos café en el Pacífico mexicano y el Golfo de California, incluidas las islas Marietas, se determinó un nivel bajo de compuestos de metabolitos de organoclorados (diclorodifenildicloroetileno o DDE), lo que se consideró un signo de ecosistema marino costero saludable. Las concentraciones encontradas no están relacionadas con el adelgazamiento de la cáscara del huevo y, por tanto, no ponían en riesgo la eclosión ni el éxito reproductivo (Mellink et al., 2009). Los compuestos organoclorados en las Marietas se relacionaron entonces con los insumos utilizados para el control de mosquitos tanto en Puerto Vallarta como en la Riviera Nayarit. Hoy en día, las concentraciones de organoclorados podrían ser superiores a las encontradas

100%

% Éxito reproductivo

100%

85,7% 84,9%

90% 80% 70% 60% 50% 40%

50% 36,8% 27,4%

30%

18,4%

20%

23,3%

10% 0%

S. leucogaster (n = 76) S. nebouxii (n = 73) Variables de estudio Fig. 3. Éxito reproductivo de las dos especies objeto de estudio. La viabilidad (V) correspondió a la proporción de huevos que permanecieron en el nido durante el periodo de incubación sin sufrir daños aparentes, en relación con el total de huevos puestos. La fertilidad (F) se consideró como la proporción de huevos que eclosionaron en relación con el número de huevos viables. El éxito de eclosión (Ee) fue la proporción de huevos que eclosionaron respecto del total de los huevos puestos y el éxito del pollo (Ep) se consideró como la proporción de pollos que llegaron a la edad de volantón respecto al número de huevos eclosionados. Fig. 3. Reproductive success of the two study species. Viability (V) corresponded to the proportion of eggs remaining in the nest during the incubation period without apparent damage in relation to the total number of eggs. Fertility (F) was the proportion of eggs that hatched in relation to the number of viable eggs. Hatching success (Ee) was the proportion of eggs that hatched in relation to the total number of eggs laid, and success of the young (Ep) was the proportion of chicks reaching fledging stage regarding the number of hatched eggs.

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% Éxito reproductivo

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

86%

191

92%

92% 78%

71%

62% 50%

48%

39%

37%

27%

18%

Islas Marietas

Isla Pajarera Área de estudio

Isla Cocina

Fig. 4. Comparación del éxito reproductivo del género Sula entre tres sistemas insulares. Fig. 4. Comparison of the reproductive success of Sula genus between three island systems.

debido a la intensificación de las campañas para controlar a los mosquitos transmisores de dengue y chikungunya, además de la proliferación de campos de golf en la zona (hay uno muy cerca de la zona de estudio), que utilizan insumos con compuestos organoclorados para mantener los pastos. Otro factor que podría influir en el bajo éxito de eclosión es la depredación directa por otras aves marinas. En Isla Larga hemos observado en varias ocasiones la depredación y destrucción de los huevos de bobos por parte de la gaviota ploma, Larus heermanni. La presencia humana provocaría además el abandono del nido por parte de los bobos y daría a las gaviotas la oportunidad de depredar huevos y crías tal como se ha observado en varias de las islas del Golfo de California con la gaviota pata amarilla, Larus livens (Anderson et al., 1976; Carboneras, 1992; Burger & Gochfeld, 1993; Velarde–González, & Anderson, 1993). Así pues, cabe la posibilidad de que el bajo éxito reproductivo de ambas especies objeto de estudio en nuestra zona esté condicionado por la presencia y depredación de la gaviota ploma, si bien este factor, de existir, no se habría acentuado a causa de las visitas realizadas durante el experimento. Implicaciones para la gestión A partir de los resultados obtenidos podría concluirse que no es previsible que las visitas a las zonas de nidificación de los pájaros bobos café y de patas azules de las islas Marietas, tal como aparecen en el experimento, repercutan gravemente en el éxito reproductor de las aves. De todos modos, no hay que perder de vista que nuestros resultados se basan en tamaños de muestra relativamente bajos, por lo que no cabe excluir que haya pequeños efectos de las molestias que no se hayan detectado estadísticamente. Es posible,

por ejemplo, que la presencia de los depredadores de nidos sea más alta en los días con buen tiempo o que las aves puedan ser más propensas a abandonar los nidos cuando las condiciones climáticas son benévolas, de igual forma los turistas visitan las islas cuando hay buen tiempo (Cadiou & Monnat, 1996). Limitar de modo absoluto el acceso de personas puede eliminar los riesgos asociados a las visitas, pero puede tener importantes costes sociales que deben tenerse en cuenta, especialmente en lo relativo a la educación pública y la sensibilización en materia de conservación de espacios y especies amenazadas. Cornejo–Ortega et al. (2011) sugieren que el límite máximo de visitantes diarios al sendero de uso público de las Marietas sea de 36, lo que acarrearía unos costos ambientales relativamente bajos. De este modo, este instrumento de ordenación y conservación puede ser valioso para minimizar la perturbación humana y hacerla compatible con la gestión de avistamiento de vida silvestre, tal como sugiere Fernández–Juricic et al. (2004). En cualquier caso, parece recomendable mantener una ordenación adaptativa del régimen de visitas a las colonias de aves marinas de modo que sea posible modificarlo en función de los resultados que proporcione un seguimiento de las especies objeto de estudio (Possingham et al., 2001; McCarthey & Possingham, 2007). Agradecimientos Los autores, en particular J. L. C.–O., agradecen al CONACyT la beca de estudios doctorales. De igual manera se agradece a la CONANP por el apoyo recibido para la recopilación de datos en el campo. El Dr. José Antonio Donázar, la Dra. Ainara Cortés–Avizanda y Lorenzo Quaglietta hicieron valiosas aportaciones a este trabajo.

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Animal Biodiversity and Conservation 39.2 (2016)

Brief communication

Effects of the North Atlantic Oscillation on Spanish catches of albacore, Thunnus alalunga, and yellowfin tuna, Thunnus albacares, in the North–east Atlantic Ocean C. J. Rubio, D. Macías, J. A. Camiñas, I. L. Fernández & J. C. Báez Rubio, C. J., Macías, D., Camiñas, J. A., Fernández, I. L. & Báez, J. C., 2016. Effects of the North Atlantic Oscillation on Spanish catches of albacore, Thunnus alalunga, and yellowfin tuna, Thunnus albacares, in the North–east Atlantic Ocean. Animal Biodiversity and Conservation, 39.2: 195–198. Abstract Effects of the North Atlantic Oscillation on Spanish catches of albacore, Thunnus alalunga, and yellowfin tuna, Thunnus albacares, in the North–east Atlantic Ocean.— Tuna are highly migratory pelagic species (HMPS) with great importance in commercial fishing. Several authors have highlighted the effect of climatic oscillations such as the North Atlantic Oscillation (NAO) on HMPS. This paper analyzes the effects of the NAO on two HMPS: albacore, Thunnus alalunga, and yellowfin tuna, Thunnus albacares. Fishing data from the Spanish fleet operating in the North Atlantic area were obtained from the International Commission for the Conservation of Atlantic Tunas (ICCAT) database. The results show a positive correlation between the NAO index and the Catch per Unit Effort (CPUE) for both albacore and yellowfin tuna, depicting a potential effect on their capturability. Key words: Climate oscillation, Pelagic migratory species, Fisheries, North Atlantic Resumen Efectos de la Oscilación del Atlántico Norte en las capturas españolas de atún blanco, Thunnus alalunga, y de rabil, Thunnus albacares, en el océano Atlántico nororiental.— Los túnidos son considerados grandes migrantes pelágicos (GMP) y tienen un elevado interés en la pesca comercial. Varios autores han puesto de relieve el efecto de las oscilaciones climáticas como el índice Oscilación del Atlántico Norte (NAO) en los GMP. En este trabajo se analizan los efectos de la NAO en dos especies de GMP: el atún blanco, Thunnus alalunga, y el atún de aleta amarilla o rabil, Thunnus albacares. Los datos sobre pesca de la flota española que faena en la zona del Atlántico Norte se obtuvieron de la base de datos de la Comisión Internacional para la Conservación del Atún Atlántico (CICAA). Los resultados muestran una relación positiva entre el índice NAO y la captura por unidad de esfuerzo (CPUE) tanto para el atún blanco como para el rabil, lo que refleja un efecto potencial sobre su capturabilidad. Palabras clave: Oscilación climática, Especies migrantes pelágicas, Pesquerías, Atlántico Norte Received: 3 III 16; Conditional acceptance: 1 IV 16; Final acceptance: 13 IV 16 C. J. Rubio & I. L. Fernández, Depto. de Biología Animal, Univ. de Málaga, Málaga, Spain.– C. J. Rubio, D. Macías, J. A. Camiñas & J. C. Báez, Inst. Español de Oceanografía, Centro Oceanográfico de Málaga, 29640 Fuengirola, Málaga, Spain.– J. C. Báez, Investigador Asociado, Fac. de Ciencias de la Salud, Univ. Autónoma de Chile, Chile. Corresponding author: J. C. Báez. E–mail: granbaez_29@hotmail.com

Introduction Tuna species are an important fishing and commercial resource and have been exploited since antiquity. Their migratory and gregarious behavior makes them especially susceptible to some fishing gear. Two tuna ISSN: 1578–665 X eISSN: 2014–928 X

species, skipjack tuna, Katsuwonus pelamis, and yellowfin tuna, Thunnus albacores, are currently among the top 10 fish catches in the world (FAO, 2010). The International Commission for the Conservation of Atlantic Tunas (ICCAT) is responsible for the conservation and management of tuna and tuna–like © 2016 Museu de Ciències Naturals de Barcelona

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fishes in the Atlantic Ocean and contiguous waters. ICCAT promotes the collection of biological and fishery data concerning tuna and tuna–like species and the analysis of statistical information related to the state of conservation and trends in abundance of these fishery resources exploited in the ICCAT competence area. According to available ICCAT data, albacore, Thunnus alalunga, and yellowfin tuna, Thunnus albacares, constitute the major part of tuna catches by the North Atlantic Spanish fleet. Several authors have discussed the effect of climatic oscillations on migratory species (Robinson et al., 2009), particularly on various tuna species, such as the Atlantic bluefin tuna, Thunnus thynnus (Macías et al., 2012; Báez et al., 2013). For this reason, some authors propose modeling the response of migratory species to large–scale climatic phenomena integrating weather conditions in large areas, such as the North Atlantic Oscillation (NAO), rather than studying the effect of local conditions (Forchammer et al., 2002; Robison et al., 2009). The NAO is considered the largest source of variability —both seasonal and interannual— affecting the climate of the North Atlantic area: Europe, North Africa and North America (Hurrell, 1995). The NAO refers to an oscillation between the anticyclone of the Azores and a low–pressure area near Iceland, which redistributes air mass from the Arctic to the subtropical Atlantic (Hurrell, 1995). Part of the Atlantic and adjacent seas (particularly the Mediterranean Sea) respond quickly and locally to the NAO by varying the surface sea temperature, the depth of the ocean mixed layer, the ocean heat content, the thickness of the ocean ice shelf, surface current circulation, and the intensity and direction of the prevailing winds (Visbeck et al., 2001). We hypothesized that the NAO could have an effect on tuna catches. The aim of the present study was to analyze the effect of the NAO on Spanish albacore and yellowfin fishery captures in the North Atlantic.

Material and methods ICCAT compiles capture data reported by member states by fishing gear and area (called task I); fishing effort data are also sorted by fishing gear and area (called task II). These data are freely downloadable from the ICCAT website. Fishing gear used to catch tuna in the ICCAT area mainly consists of baitboat, purse–seine and surface longline. Cases with available historical data series of more than ten years according to type of fishing gear (baitboat, purse seine, troll and longline) and species were albacore caught using purse seine and baitboat, and yellowfin tuna caught using purse seine and baitboat. Albacore is a medium size tuna. The ICCAT recognizes two stocks of albacore in the North Atlantic region, one in the Atlantic sensu stricto and another in the Mediterranean Sea. The present study includes only data from the Atlantic stock because only Spanish Atlantic fleet catches were taken into consideration. Yellowfin tuna is a cosmopolitan species distributed in open waters of tropical and subtropical areas of the three oceans, not being present in the Mediterranean. It is assumed that there is a single yellowfin tuna stock for the whole Atlantic Ocean. NAO data were collected from the National Oceanic and Atmospheric Administration (NOAA) website: http://www.cpc.ncep.noaa.gov. We used the NAO average data per year for the analyses. However, as many authors (e.g., Hurrell, 1995) emphasize that the NAO has its maximum effect between November and April, we also used the NAO average of these months. This variable was called winter NAO (NAOw). We performed linear and non–linear regression between the CPUE (Catch Per Unit Effort by species, fishing gear and year, retrieved from the ICCAT task II data) as the dependent variable, and climate indexes

Table 1. Results of the significant linear and non–linear relationships between NAO and albacore and yellowfin CPUE: R2. Determination coefficient; F. F–Fisher; df. Degrees of freedom; Cte. Constant; b. Slope. Tabla 1. Resultados de las relaciones significativas lineales y no lineales entre la NAO y CPUE del atún blanco y la del rabil: R2. Coeficiente de determinación; F. F de Fisher; df. Grados de libertad; Cte. Constante; b. Pendiente.

Function

R 2

Cte

Linear

0.214

5.718

0.026

1.604

2.683

Quadratic

0.418

7.188

0.004

0.998

4.282

4.375

Cubic

0.606

12.074

P < 0.0001

0.276

0.755

12.734 10.431

Linear

0.275

7.948

0.01

35.221

34.236

Quadratic

0.401

6.695

0.006

29.845

48.414

38.786

Cubic

0.493

6.152

0.004

24.795

23.734

97.288 72.997

Exponential 0.281

8.194

0.009

28.642

0.856

Albacore

Yellowfin tuna

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12 10 8

y = 10.43x3 + 12.735x2 + 0.7559x + 0.2771 R2 = 0.6561

6 4 2

–1.4

–1.2

–1

–0.8 – –0.6 –0.4 –0.2

0 -2

y = 2.6827x + 1.6052 R2 = 0.214

0.2

0.4

0.6

0.8

-4 B

140 120 100 y = 72.997x3 + 97.287x2 + 23.735x + 24.796 R2 = 0.4927

80 60 40 20

–1.4

1.2

–1

0 –0.8 –0.6 –0.4 –0.2 0 NAO –20

y = 34.238x + 35.222 R2 = 0.2746

0.2

0.4

0.6

0.8

Fig. 1. CPUE of albacore (A) and yellowfin tuna (B) plotted for the Atlantic Spanish purse seine fishery, and NAO as independent variable. A positive trend towards the positive NAO values is observed. The most significant linear and non–linear relationship (together with its function) is showed. Continuous line represent the linear trend (function shown on right), dashed line represent the non–linear trend (function shown on left). Fig. 1. La CPUE del atún blanco (A) y del rabil (B) para la pesca con redes de cerco en la costa atlántica de España representada gráficamente y la NAO como variable independiente. Se observa una tendencia positiva con respecto a los valores positivos de la NAO. Se muestra la relación lineal y no lineal más significativa (junto con su función). La línea continua representa la tendencia lineal (la función se muestra aen la derecha) y la línea discontinua representa la tendencia no lineal (la función se muestra en la izquierda).

(NAO and NAOw) as independent or explanatory variables. In all cases, the normality of the data was verified using the Kolmogorov–Smirnov test. Results and discussion We obtained a positive significant linear and non–linear regression between the CPUE (the unit of effort being hours at sea) for the Atlantic albacore and NAO (table 1, fig. 1A) and between the CPUE of the North Atlantic Spanish baitboat fishery and NAO (table 1, fig. 1B). Atmospheric oscillations modify the intensity of several meteorological phenomena, such as wind, rain and storms. They increase the run–off and nutrient input to the sea, changing response to the

trophic levels of marine ecosystems (Drinkwater et al., 2003) and exploited resources. These meteorological phenomena may, in turn, affect fishery resources in at least two aspects: i) the fishing effort value, and ii) the variability of the pelagic ecosystem. When referring to fishing effort, climatic oscillations at sea, such as a severe storm, might reduce the fishing effort. Likewise, occurrences promoting favorable weather conditions (e.g., a period of stability and calm sea) might increase the fishing effort in a certain area. However, we did not observe a significant correlation between NAO and fisheries effort either in albacore fisheries (r = 0.408, P = 0.053) or in yellowfin tuna fisheries (r = –0.367, P = 0.085). Moreover, meteorological phenomena could affect the biology and behavior of large migratory species of commercial interest such as those considered

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here, either affecting the trophic resources available, their migration period, or their distribution and/ or local abundance. Changes in the depth of the thermocline could also affect the availability of fish (i.e., catchability) (Lehodoy, 2000). Our analyses of Spanish catches of purse seine albacore catches and baitboat yellowfin tuna catches in the North Atlantic showed a positive, significant regression of CPUE with the NAO as an independent variable. However, we did not find a significant correlation between fishing effort and atmospheric oscillations in any of the fisheries studied. These results suggest that the NAO effects on the variable CPUE mainly occur through effects on the pelagic ecosystem, affecting the abundance of individuals (or their catchability) of the Spanish fishery target species, albacore and yellowfin tuna, in a given area. The relation between CPUE and NAO was positive in both species. This can be explained by the fact that, during positive NAO phases, western winds that could shift the species shoals eastward towards European and African coasts —the area where the Spanish fleet operatesl— increase. Furthermore, during positive NAO phases, the number and intensity of North Atlantic storms increase, contributing to the occurrence of phytoplankton blooms (Martínez–García et al., 2010; Baez et al., 2014), which in turn may attract potential prey of tuna species. According to Consoli et al. (2008), albacore tuna can be considered a top carnivore, and small pelagic fish (e.g., Aulopiformes and Clupeiformes) and cephalopods are its potential prey. In this line of reasoning, Báez & Real (2011) found a significant relationship between monthly landings of anchovy, Engraulis encrasicolus, and the NAO around the Gulf of Cádiz. It is therefore possible that favorable conditions for small pelagic fishes also attract the top predators in certain areas. Our findings suggest it would be desirable to incorporate NAO predictive models into current models used by ICCAT experts for fisheries management so as to enable more efficient management of large migratory pelagic fisheries. Acknowledgments This study was supported by projects from the IEO based in Malaga: GPM–4 (IEO), GPM12–13 (IEO), GPM16 (IEO) and the Programa Nacional de Datos Básicos del Sector Pesquero Español (PNDB project, EU–IEO). JCB was supported by the PNDB project. References Báez, J. C., Macías, D., De Castro, M., Gómez–Gesteira, M., Gimeno, L. & Real, R., 2013. Analysis of the effect of atmospheric oscillations on physical condition of pre–reproductive bluefin tuna from the Strait of Gibraltar. Animal Biodiversity and

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Conservation, 36: 225–233. Báez, J. C. & Real, R., 2011. The North Atlantic Oscillation affects landings of anchovy Engraulis encrasicolus in the Gulf of Cádiz (south of Spain). Journal of Applied Ichthyology, 27(5): 1232–1235. Báez, J. C., Real, R., López–Rodas, V., Costas, E., Salvo, A. E., García–Soto, C. & Flores–Moya, A., 2014. The North Atlantic Oscillation and the Arctic Oscillation favour harmful algal blooms in SW Europe. Harmful Algae, 39: 121–126. Consoli, P., Romeo, T., Battaglia, P., Castriota, L., Esposito, V. & Andaloro, F., 2008. Feeding habits of the albacore tuna Thunnus alalunga (Peciformis, Scombridae) from central Mediterranean Sea. Marine Biology, 155: 113–120. Drinkwater, K. F., Belgrano, A., Borja, A., Conversi, A., Edwards, M., Greene, C. H. & Walker, H., 2003. The response of marine ecosystems to climate variability associated with the North Atlantic Oscillation. Geophysical Monograph–American Geophysical Union, 134: 211–234. FAO, 2010. The State of World Fisheries and Aquaculture 2010. Rome, FAO. Forchammer, M., Post, E. & Stenseth, N.–C., 2002. North Atlantic Oscillation timing of long–and short– distance migration. Journal of Animal Ecology, 71: 1002–1014. Hurrell, J. W., 1995. Decadal trends in the North Atlantic Oscillation: Regional temperatures and precipitation. Science, 269: 676–679. Lehodey, P., 2000. Impacts of the El Niño Southern Oscillation on tuna populations and fisheries in the tropical Pacific Ocean. Technical report, 13th meeting of Standing Committee on tuna and billfishes. Noumea, New Caledonia. Macias, D., Báez, J. C., Alot, E., Rioja, P., Gómez– Vives, M. J., Ortiz de Urbina, J. M. & Real, R., 2012. Factores de condición del atún rojo prereproductor capturado en el estrecho de Gibraltar y su correlación con las oscilaciones atmosféricas. Collective Volume of Scientific Papers, ICCAT, 68(1): 267–275. Martínez–García, S., Fernández, E., Alvarez–Salgado, X.–A. González, J., Lønborg, C., Marañó, E., Morán, X.–A. G. & Teira, E., 2010. Differential responses of phytoplankton and heterotrophic bacteria to organic and inorganic nutrient additions in coastal waters off the NW Iberian Peninsula. Marine Ecology Progress Series, 416: 17–33. Robinson, R. A., Crick, H. Q. P., Learmonth, J. A., Maclean, I. M. D., Thomas, C. D., Bairlein, F., Forchhammer, M. C., Francis, C. M., Gill, J. A., Godley, B. J., Harwood, J., Hays, G. C., Huntley, B., Hutson, A. M., Pierce, G. J., Rehfisch, M. M., Sims, D. W., Santos, M. B., Sparks, T. H., Stroud, D. A. & Visser, M. E., 2009. Travelling through a warming world: climate change and migratory species. Endangered species research, 7(2): 87–99. Visbeck, M. H., Hurrell, J. W. Polvani, L. & Cullen, H. M., 2001. The North Atlantic Oscillation: Past, present, and future. Proceedings of the National Academy of Sciences, 98: 12876–12877.

Animal Biodiversity and Conservation 39.2 (2016)

Forum

Questioning current practice in brown bear, Ursus arctos, conservation in Europe that undervalues taxonomy S. Gippoliti

Gippoliti, S., 2016. Questioning current practice in brown bear, Ursus arctos, conservation in Europe that undervalues taxonomy. Animal Biodiversity and Conservation, 39.2: 199–205. Abstract Questioning current practice in brown bear, Ursus arctos, conservation in Europe that undervalues taxonomy.— The present paper highlights problems associated with the currently–accepted taxonomy of brown bear, Ursus arctos, and their consequences for conservation at the European level. The enormous morphological variability within Ursus arctos is not acknowledged in current taxonomy and conservation practice. Seven major clades are recognized in Ursus arctos by molecular researchers, and although Western Europe maintains most of the populations belonging to the relict Clade 1 brown bear lineage, no reference to this is made in current conservation policy. Furthermore, the tiny population of Apennine brown bears, characterized by unique skull morphology, is not even recognized as a distinct Evolutionari Significant Unit (ESU) by current European legisla� tion, nor is it included in the IUCN Red List. This may have serious consequences as brown bear conservation in Western Europe has been mainly based on restocking and reintroduction programs. Key words: Ursus arctos marsicanus, Italy, Species concepts, Conservation, Semen banking, ESU Resumen Cuestionamiento de la actual estrategia de conservación del oso pardo, Ursus arctos, en Europa, que infravalora la taxonomía.— En este trabajo se ponen de relieve los problemas relacionados con la taxonomía actualmente aceptada del oso pardo, Ursus arctos, y sus consecuencias para la conservación en el ámbito europeo. En la actualidad, ni la taxonomía ni las prácticas de conservación reconocen la enorme variabilidad morfológica existente dentro de la especie Ursus arctos. Los investigadores moleculares reconocen la existencia de siete clados principa� les en Ursus arctos y, a pesar de que en Europa occidental la mayoría de las poblaciones pertenecen al primitivo Clado 1 del linaje de oso pardo, en las políticas vigentes de conservación no se hace referencia a ello. Además, la diminuta población de osos pardos de los Apeninos, caracterizada por una morfología craneal particular, ni siquiera es reconocida como una unidad evolutiva significativa (UES) por la legislación europea vigente ni tampoco está incluida en la Lista Roja de la UICN. Ello puede tener graves consecuencias, puesto que la conservación del oso pardo en Europa occidental se ha basado principalmente en programas de repoblación y reintroducción. Palabras clave: Ursus arctos marsicanus, Italia, Conceptos de especie, Conservación, Banco de semen, UES Received: 23 I 16; Conditional acceptance: 18 III 16; Final acceptance: 21 IV 16 Spartaco Gippoliti, Società Italiana per la Storia della Fauna 'G. Altobello', Viale Liegi 48, 00198 Roma (Italy). E–mail: spartacolobus@hotmail.com

ISSN: 1578–665 X eISSN: 2014–928 X

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Introduction More than 150 years since the publication of Darwin’s 'Origin of Species' (Darwin, 1859), philosophical and biological issues regarding speciation and species boundaries are still debated (Hey, 2006; Naomi, 2011). In effect, conservation assessments usually include a review of what is deemed 'currently accepted taxo� nomy', with little understanding that taxonomy is in fact a specialist discipline, and that 'currently accepted' carries little or no scientific weight if not supported by updated taxonomic revisions (Gutierrez & Helgen, 2013). The conservation of biodiversity ultimately de� pends upon the work of taxonomists (McNeely, 2002). While it is clear that our knowledge is still limited for most tropical regions, it is often overlooked that, even in Europe, new assessments of the taxonomy of particular groups often lead to species descriptions (Fontaine et al., 2012). Occasional conflicts between mammal taxonomists and conservationists have been observed in recent years (i.e., Isaac et al., 2004; Groves & Robovský, 2011; Shetty & Vidya, 2011; Cotterill et al., 2014). The case of the brown bear, Ursus arctos Linnaeus, 1758, represents a notable example of the neglect of taxonomic issues in the current approaches for the conservation of large mammals. It is well established that the polar bear, Ursus maritimus, Phipps, 1774 is closely allied to Ursus arctos Linnaeus, 1758. However, patterns of mitochondrial DNA have failed to confirm the reciprocal monophyly of the two taxa (Talbot & Shields, 1996). The species status of the polar bear has never been seriously questioned, and new data with other molecular markers appear to have reestablished the 'true relationship' between the two species (Cronin et al., 2013). Yet the hypothesis that polar bears originated from an island brown bear population, so that these brown bears are phylogenetically closer to polar bears than, for example, Gobi Desert brown bears, seems perfectly credible and merits further examination. It is of interest that no studies to date have yet used molecular data to provide an alternative to the now classic 'one species' approach to Ursus arctos taxonomy, despite evidence of several deeply di� vergent mtDNA monophyletic clades within 'arctos' (Galbreath et al., 2007). Furthermore, current awareness of the historical occurrence of hybridization and introgression between polar and brown bears (Edwards et al., 2011; Bidon et al., 2014) seems to support the need to adopt a different approach to species delimitation in the U. arctos complex away from the interbreeding criteria adopted as the fundamental pillar by the biological species concept. In the present paper we contend that the time is ripe for a taxonomic revision of the whole U. arctos complex, adopting an integrative coherent approach. In the meantime, we here review available evidence with the aim of integrating the present conservation strategy for brown bear conservation within the Eu� ropean Union.

Gippoliti

What are the consequences for brown bear conservation? The taxonomic history of brown bears has been complicated owing to the great deal of phenotypic variation found both locally and regionally (Kitchener, 2010). Most modern researchers therefore simply choose to ignore the issue. Despite the availability of a wealth of genetic data in recent years (Swenson et al., 2011), its taxonomic significance has not been investigated (Kitchener, 2010; see below), or only ra� rely (Galbreath et al., 2007). In the specific IUCN/SSC Action Plan, the presence of possible taxonomically divergent populations in such a widespread species is simply overlooked (Servheen et al., 1998) with the consequence that the whole species is not considered as threatened (Least Concern; McLellan et al., 2008). Such treatment is prone to type 2 and 3 taxonomic errors (Cotterill et al., 2014), and one or more cryptic lineages may be at unnoticed risk of becoming extinct (Calvignac et al., 2009). In Europe, the species is included in Annex II of the Habitat Directive, but no attention is given to conservation below the species level. A major finding of genetic research, never fully translated into taxonomy and conservation strategy, is that the U. arctos complex can be separated into seven major geographically structured mitochondrial DNA clades and a small number of subclades (Hi� rata et al., 2013; Ashrafzadeh et al., 2016). Current EU bear conservation strategies (i.e., Boitani et al., 2015) seem to completely overlook that some of the Western European populations belong to the relict mtDNA lineage Clade 1, mainly restricted to the Iberian, Italian, Balkan and Southern Scandinavian Peninsulas (Davison et al., 2011; Hirata et al., 2013; fig. 1), and recently discovered in Western Turkey (fig. 1; Çilingir et al., 2015). The value of recognized clades as conservation management units has been challenged in Europe by Valdiosera et al. (2007), who found Clade 3 mtDNA in ancient bear samples from within the current Clade 1 range in Northern Spain. These results have been interpreted as suggesting that present brown bear lineages are more the result of range fragmentation by humans than of evolutionary significant units (Valdiosera et al., 2008). The issue deserves further study as it is highly probable that with changing environmental conditions (i.e., glacials), Europe was colonized by mammal lineages of Eastern origin that retreated during interglacial periods, while Mediterranean lineages survived in southern refugia. For instance, during the Late Glacial, both Lynx lynx (Linnaeus, 1758) and L. pardinus (Temminck, 1827) occurred on the Iberian peninsula (Sommer & Benec� ke, 2006) and even in the northern Italian peninsula (Rodríguez–Varela et al., 2015), confirming their evo� lutionary species status. The size of the populations belonging to U. arctos Clade 1, wholly restricted to Europe, is difficult to estimate from available data because some of the 'populations' considered by EU experts (Scandinavian, Carpathian) are centered in the contact area where Clade 1 meets the worldwide Clade 3 (Zachos et al., 2008; Xenikoudarkis et al., 2015). It seems that so far no study has addressed

Animal Biodiversity and Conservation 39.2 (2016)

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Clade 3a Clade 1

Fig. 1. Approximate distribution of Ursus arctos Clade 1 and Clade 3a in Western Europe. Fig. 1. Distribución aproximada de los clados 1 y 3a de Ursus arctos en Europa occidental.

the question of whether the two clades are also dis� tinguishable morphologically, as has been attempted elsewhere (e.g., Baryshnikov et al., 2004). Bear conservation in the EU and the overlooked demise of the Apennine bear Large carnivore populations, including brown bears, have recently been described as flourishing in EU sta� tes (Chapron et al., 2014). Attempts have been made to reestablish almost extinct brown bear populations (Alps, Pyrenees) through the translocation of bears from viable populations elsewhere. As in the rest of the world, no intraspecific taxonomic units have been accepted by bear experts in Europe (Swenson et al., 2000; Swenson et al., 2011). Accordingly, it has been emphasized that the Croatian bear population would appear to satisfy all criteria to serve as a source po� pulation for future reintroduction projects in Western Europe (Kocijan et al., 2011). This approach to brown bear conservation in Europe has been challenged with specific reference to the small, isolated Apennine brown bear population whose only breeding nucleus is found in the National Park of Abruzzo, Lazio and Molise, in Italy (Guacci et al., 2013). The original description of U. arctos marsicanus Altobello, 1921, based on limited materials, was rightly dismissed by Pocock (1932) who was aware of the considerable

morphological variability found in U. arctos. Yet this view has been shared without any further study of new materials throughout the 20th Century, a period of taxonomic inertia for European mammalogy (Gippoliti & Groves, 2013). According to early genetic studies (Randi et al., 1994; Taberlet & Buvet, 1994), this population, to� gether with the Balkan populations, is considered to belong to the western brown bear clade 1b and shows negligible differentiation. But more recently, both Randi (2003) and Lorenzini et al. (2004) have indicated that differences in mitochondrial DNA and microsatellites suggest a distinct management unit. Furthermore, evidence is mounting that Apennine brown bears have a considerable phenotypic distincti� veness —specifically regarding the skull (Conti, 1954; Loy et al., 2008; Colangelo et al., 2012), to the extent that all these authors accepted U. arctos marsicanus as a valid taxon. Capasso Barbato et al. (1993), while discussing the cranial characters of extant U. arctos populations and U spelaeus Rosenmuller, 1784, confirmed that U. arctos marsicanus share some peculiarities with U. spelaeus, as previously evidenced by Conti (1954). This unusual situation can hardly be explained simply as the result of 'genetic drift' due to isolation from the main continental bear population in the last 400–700 years (cfr. Ministry of the Environment, 2011; Colangelo et al., 2012). The stability of a suture zone in Scandinavia in the last

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150 years, with the two clades only a few kilometers apart (Xenikoudarkis et al., 2015), demands that historical connectivity between the Apennine and Alps populations be verified and not merely automatically inferred. It seems reasonable at this stage to consider the Apennine brown bear as a southern endemic survivor, like the Apennine chamois Rupicapra ornata Neumann, 1899 (Vigna–Taglianti, 2003). At this point, one would surely have expected a revision of conservation policies both nationally and at the EU level. Nothing of the kind happened. Guacci et al. (2013) called for a more pressing conservation strategy for this endemic Italian taxon, including, if necessary, captive breeding and a bank of biomate� rials —an aspect that is not considered in the Natio� nal Action Plan (Ministry of the Environment, 2011), but is pursued elsewhere through semen collection from live individuals or post–mortem recovery of epididymal spermatozoa (Fickel et al., 2007; Anel et al., 2011). At present, it seems that conservation au� thorities and bear researchers continue to emphasize ecological connectivity between Apennine protected areas to create new breeding nuclei and reduction of human–induced mortality. If such an approach does not lead to positive results (for instance, due to female brown bear philopatry and thus dispersal avoidance outside their natal range), no alternative strategy seems to exist —or, better, the only availa� ble way to maintain genetic variability and increase range size in the future would be to bolster this population with individuals from the closest viable wild population, as done elsewhere (Chapron et al., 2009). Even if this intervention vigorously followed the IUCN Guidelines for reintroductions and other conservation translocations, given the unique status of U. arctos marsicanus among brown bears, it is clear that no candidate population exists. In 2008 it was stated that: 'The reconsideration and acceptance of the Apennine population as a distinct taxon will have a strong effect on any action to be undertaken for the conservation of the species in Italy' (Loy et al., 2008). As Randi (2003) also stressed: 'there should be distinct conservation managements for the Alpine and Apennine brown bear populations, and Apennine brown bears should be managed as an evolutionary significant unit (ESU)' (Loy et al., 2008). It should be emphasized that although the small population size (about 50 individuals, including circa 13 breeding females; cfr. Ciucci et al., 2015) is obviously a cause for concern, so far, no obvious effects of inbreeding have been reported. Although captive–breeding is not generally considered a viable option for brown bear conservation (Huber, 2010), Guacci et al. (2013) stressed that release of orphan bears is a common practice in several parts of the world (cfr. Beecham et al., 2015). Thus, if it is necessary to save a threatened taxon, captive–bred cubs could be released adopting a similar approach. Although starting a captive breeding program is a considerable risk with this current population status, since the 1990s, four Apennine brown bears have been kept in captivity (roughly 10% of the wild adult population). No serious attempts have been

Gippoliti

made to breed these bears, however, because it is assumed that captive–bred bears would not be successfully released back to the wild. Apart from captive breeding, however, it is time to recognize that our goal in Central Italy is the conservation of U. arctos marsicanus —an endemic taxon— and not simply that of the Apennine brown bear population. Moving ahead in the conservation of brown bear diversity Only today are we beginning to appreciate how deca� des of game management and wildlife translocations, without adequate backup from zoology and especially from taxonomy, has led us to overlook the fate of native Italian endemic taxa of ungulates (such as wild boars, Sus scrofa majori De Beaux & Festa, 1927 and roe deer, Capreolus capreolus italicus Festa, 1925), to the point where their re–establishment is near impossible given the presence of introduced alien stocks (Gippoliti & Amori, 2002; Champagnon et al., 2012). Even with carnivores such as the Eurasian otter Lutra lutra, aware� ness of the presence of a distinctive ESU in southern Italy (Panzacchi et al., 2010) came just in time to block some reintroduction programs. The Southern European Peninsulas of Iberia, Italy and the Balkans are known today to maintain a number of endemic lineages that make them a conservation priority; these lineages inclu� de the most threatened cat species in the world, Lynx pardina, considered a subspecies of Lynx lynx until 20 years ago (Beltrán et al., 1996). The European Union needs to re–evaluate its conservation policy. A premium must be assigned to the conservation of populations that have not been altered by human–assisted genetic introgression. Only in this way can we effectively increase awareness of European biodiversity heritage. As regards the conservation of brown bear in Europe, it has been suggested that an integrative approach to taxonomic research should be adopted. In the meantime, no measure should be proposed to encourage gene flow in the contact zone between Clade 1 and Clade 3. In the case of relict Clade 1 populations, such as the Apennine marsicanus, im� mediate action, as recognized by current conservation plans (Boitani et al., 2015; Ministry of the Environment, 2011), must be integrated by a long–term approach to secure genetic materials for future use, as has been done for the Cantabrian population (Nicolas et al., 2010). The precautionary principle and avai� lable scientific evidence demand that we manage U. arctos marsicanus as a distinct ESU. As such, future re–stocking with individuals from other populations is clearly not recommended. Augmentation of the Apennine bear population has never been officially proposed. Any such project would raise serious safety concerns among local communi� ties, who have never reported incidents with Apennine bears. Furthermore, such a project would lead to a hybrid swarm or substitution of a unique brown bear taxon before we fully understand the origin, history and significance of U. arctos marsicanus.

Animal Biodiversity and Conservation 39.2 (2016)

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Use of wild–caught individuals as a key factor for success in vertebrate translocations L. Rummel, A. Martínez–Abraín, J. Mayol, J. Ruiz–Olmo, F. Mañas, J. Jiménez, J. A. Gómez & D. Oro

Rummel, L., Martínez–Abraín, A., Mayol, J., Ruiz–Olmo, J., Mañas, F., Jiménez, J., Gómez, J. A. & Oro, D., 2016. Use of wild–caught individuals as a key factor for success in vertebrate translocations. Animal Biodiversity and Conservation, 39.2: 207–219. Abstract Use of wild–caught individuals as a key factor for success in vertebrate translocations.— Success of verte� brate translocations is crucial to improve efficacy and efficiency of conservation actions but it is often difficult to assess because negative results (failed translocations) are seldom published. We developed surveys and sent them to heads of conservation services in three major Spanish Mediterranean regions. The purpose of our surveys was to determine which methodological factor that could easily be implemented in practice was more influential for translocation success. These factors included the origin of translocated individuals (captive or wild) and translocation effort (propagule size and program duration). After analyzing 83 programs, corre� sponding to 34 vertebrate species, by means of generalized linear mixed modelling, we found that 'origin' was more relevant for translocation success than 'effort', although we could not rule out some role of translocation effort. Variance in success of translocation programs involving individuals from wild sources was smaller and consequently results more predictable. Origin interacted with taxa so that success was higher when using wild birds and especially wild fish and mammals, but not when releasing reptiles. Hence, we suggest that, for any given effort, translocation results will be better for most vertebrate taxa if individuals from wild sources are used. When this is not feasible, managers should release captive–reared individuals for a long number of years rather than a short number of years. Key words: Translocation success, Vertebrates, Origin of individuals, Reintroduction effort, Captive–breeding, Cost of release Resumen La utilización de individuos capturados en el medio natural como factor fundamental del éxito en las translocaciones de vertebrados.— Resulta fundamental que las translocaciones de vertebrados den buenos resultados para mejorar la eficacia y la eficiencia de las medidas de conservación, si bien a menudo es difícil de evaluar debido a que los resultados negativos (translocaciones fallidas) raramente se publican. Elaboramos encuestas y las remitimos a los jefes de los servicios de conservación de tres importantes regiones mediterráneas de España. La finalidad de nuestras encuestas era determinar el factor metodológico, que pudiera ponerse en práctica con facilidad, más influyente en el éxito de las translocaciones. Entre estos factores figuraban la procedencia de los individuos translocados (cautividad o medio natural) y el esfuerzo de translocación (tamaño del propágulo y duración del programa). Tras analizar 83 programas, correspondientes a 34 especies de vertebrados, por medio de modelos mixtos lineales generalizados, observamos que la procedencia era más importante para el éxito de la translocación que el esfuerzo, si bien no pudimos descartar que este último tuviera alguna influencia. La varianza en el éxito de los programas de translocación que utilizan individuos procedentes del medio natural fue inferior y, en consecuencia, los resultados, más predecibles. La procedencia interaccionó con los taxones de forma que el éxito fue mayor cuando se utilizaron aves silvestres y, en especial, peces y mamíferos silves� tres, pero no sucedió lo mismo cuando se liberaron reptiles. Por consiguiente, sugerimos que, para un esfuerzo dado, los resultados de la translocación serán mejores para la mayoría de taxones de vertebrados si se utilizan individuos procedentes del medio natural. Cuando esto no sea posible, los gestores deberían liberar durante muchos años individuos criados en cautividad. ISSN: 1578–665 X eISSN: 2014–928 X

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Palabras clave: Éxito de translocación, Vertebrados, Procedencia de los individuos, Esfuerzo de reintroducción, Cría en cautividad, Coste de liberación Received: 17 II 16; Conditional acceptance: 13 IV 16; Final acceptance: 29 IV 16 Lisa Rummel, Fakultät �� für Umwelt und Natürliche Ressourcen, Albert–Ludwigs–Universität Freiburg, Tennenba� cher Straße 4, 79106 Freiburg im Breisgau, Germany.– Alejandro Martínez–Abraín, Evolutionary Biology Group (GIBE), Fac. de Ciencias, Univ. da Coruña, Campus da Zapateira, 15071 A Coruña, Spain.– Lisa Rummel, Alejandro Martínez–Abraín & Daniel Oro, Population Ecology Group, IMEDEA (CSIC–UIB), c/ Miquel Marquès 21, 07190 Esporles, Mallorca, Spain.– Joan Mayol, Servei de Protecció d’Èspècies, Govern Balear, c/ Gremi Corredors 10, 07009 Palma de Mallorca, Spain.– Jordi Ruiz–Olmo & Francesc Mañas, Dept. d’Agricultura, Ramaderia, Pesca, Alimentació i Medi Natural, Dirección General del Medio Natural y Biodiversidad (DAAM), c/ Dr. Roux 80, 08017 Barcelona, Spain.– Juan Jiménez & Juan Antonio Gómez, Wildlife Service, Conselleria d’Agricutura, Medi Ambient, Canvi Climàtic i Desenvolupament Rural, Generalitat Valenciana, Ciutat Adminis� trativa 9 d’Octubre, Torre 1, 46018 Valencia, Spain. Corresponding author: A. Martínez–Abraín

Animal Biodiversity and Conservation 39.2 (2016)

Introduction Wildlife managers have at their disposal in situ and ex situ measures to prevent decline or extinction of threatened species or populations or to revert them to their original state. Ex situ conservation, defined as conservation of components of biological diver� sity outside their natural habitats (Secretariat of the Convention on Biological Diversity, 2005) involves removal of the threatened species from its wild ha� bitat to promote breeding in captivity. However, ex situ conservation programs should include release of individuals into the wild to comply with the ultimate goal of species conservation, defined as recovery of self–sustainable populations in their natural environ� ments. Translocation programs are hence a specific type of ex situ conservation actions. IUCN (1987) defined translocation as 'the move� ment of living organisms from one area, with sub� sequent free release in a second area, involving organisms coming either from wild or captive sources'. Here we follow the original definitions established by the IUCN, distinguishing between three major types of translocations: 'introduction', as movement of living organisms by humankind outside their indigenous distribution, 'reintroduction', as intentional movement of organisms by humankind into a part of the native range from which the species has disappeared or become extirpated, and 'reinforcement', as movement of individuals by humankind within their original habitat with the intention of building up number of individuals of an existing population (IUCN/SSC, 2013). Direct persecution and increasing habitat loss due to human impact has resulted in translocation programs becoming a widespread tool to protect and enhance wildlife (Griffith et al., 1989; IUCN, 1998; Seddon et al., 2007). For example, while at the be� ginning of the 1990s the number of animal species involved in reintroduction programs worldwide was 126, by the year 2005 it had risen to 489 (Seddon et al., 2007). The prospect of fast results and the high–publicity character, supported by numerous success stories, explain the general popularity and acceptance of translocation programs (Wolf et al., 1996; Seddon et al., 2007) despite success rates being relatively low. These rates, assessed in several studies, vary between 11% (Beck et al., 1994) and 67% (Wolf et al., 1996), and are likely overestimated because successful programs are more likely to be published than failed programs or programs with an uncertain outcome (Reading et al., 1997; Fischer & Lindenmayer, 2000; Miller et al., 2014). The Reintroduction Specialist Group of the IUCN’s Species Survival Commission published a first set of guidelines for reintroductions (IUCN, 1998) with the aim of increasing the success rate of translocations. These guidelines have been updated recently (IUCN/ SSC, 2013), and ideally every practitioner should use them before planning and implementing a translocation program. This document points out that reintroduction is only reasonable when the previous causes of extinc� tion, such as over–harvest, habitat loss or predation, have been removed or sufficiently reduced to guar�

209

antee long–term survival of the reintroduced species. Detailed feasibility studies and risk assessments must be conducted to check whether the release site is suit� able for the reintroduced population. In addition, every translocation program should include monitoring and continued management so that the outcome of the program can be assessed and reported, independently of whether translocation has been successful. Despite these IUCN suggestions, there is a lack of well–documented post–release monitoring assess� ments that can provide information on consequences of particular conservation actions, and improve future decision–making regarding design and implementation of translocation programs (Sutherland et al., 2004; Armstrong & Seddon, 2008; Pérez et al., 2012). The success of translocation programs has been evalu� ated in detail in only a few cases, to some extent due to the difficulty in providing a generally applicable definition of 'success' (Seddon, 1999; Fischer & Lin� denmayer 2000; Robert et al., 2015). Consequently, some factors which might determine the outcome of conservation–oriented translocations have yet to be identified by studies analyzing the methodological, environmental, species–specific and social or eco� nomic factors involved (Griffith et al., 1989; Wolf et al., 1996; Fischer & Lindenmayer, 2000). For this study, we focused only on the methodologi� cal factors that are important in the success of vertebra� te translocations, to provide conservation practitioners with applied guidance for improving success of their translocations programs in relation to variables that they can implement in practice (see table 1 for a review of factors identified in past literature that may determine outcome of conservation–oriented translocations). Specifically, we focused on two major methodological factors whose influence on success of translocation programs has been well documented in the literature: (1) the origin (wild or captive) of released individuals and (2) reintroduction effort, measured as number of released individuals and as duration of the program (i.e., defined as the period when releases occurred). We were interested in evaluating whether the origin of released individuals and the effort involved in translo� cation were equally relevant. Our a priori expectation was that the origin of released individuals would be a more relevant factor than effort in our modelling of translocation success, because a cost in terms of high mortality following release from captivity (i.e., incapacity to find food or escape from predators) is emerging as a usual property of translocation programs involving captive–bred individuals (see Tavecchia et al., 2009). Material and methods Data collection Data on the success of translocation programs (i.e., re–introductions/introductions and reinforcements) with conservation goals were obtained by surveying managers of wildlife conservation services in the au� tonomous regions of Catalonia, the Balearic Islands, and Valencia (fig. 1). These three regions cover a

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Table 1. Review of factors identified in past literature that may determine outcome of conservation– oriented translocations. Tabla 1. Examen de los factores que, según los datos publicados, pueden determinar el resultado de las translocaciones orientadas a la conservación. Factor

Citations

Environmental Habitat quality

Griffith et al. (1989), Wolf et al. (1996, 1998), Burgman et al. (1998),

Sheean et al. (2012), White et al. (2012), Cochran–Biederman et al. (2015)

Habitat improvement/

Griffith et al. (1989), Wolf et al. (1996, 1998),

removal of initial cause

Fischer & Lindenmayer (2000), White et al. (2012),

of decline

Cochran–Biederman et al. (2015)

Habitat range

Griffith et al. (1989), Wolf et al. (1996, 1998), White et al. (2012)

Predation

Short et al. (1992), Fischer & Lindenmayer (2000), Matson (2004),

Shier (2006), Bertolero et al. (2007), Aaltonen et al. (2009),

Grey–Ross et al. (2009), Moseby et al. (2011), Sheean et al. (2012),

White et al. (2012)

Competition

Griffith et al. (1989), Burgman et al. (1998), Bertolero et al. (2007),

Sheean et al. (2012)

Species–specific Reproductive potential

Griffith et al. (1989), Wolf et al. (1996)

Migratory tendency

Wolf et al. (1996, 1998), Cochran–Biederman et al. (2015)

Diet

Griffith et al. (1989), Wolf et al. (1996, 1998)

Methodological Origin of released

Griffith et al. (1989), Bright & Morris (1994), Wolf et al. (1996, 1998),

individuals

Fischer & Lindenmayer (2000), Stoinski et al. (2003),

Nicoll et al. (2004), Brown et al. (2006), Jule et al. (2008),

Aaltonen et al. (2009), Roe et al. (2010), Champagnon et al. (2012)

Number of released

Griffith et al. (1989), Short et al. (1992), Wolf et al. (1996, 1998),

individuals

Green (1997), Fischer & Lindenmayer (2000), Matson (2004),

Moulton et al. (2012), White et al. (2012), Cochran–Biederman et al. (2015)

Program duration

Griffith et al. (1989), Wolf et al. (1998), Cochran–Biederman et al. (2015)

Release method

Griffith et al. (1989), Bright & Morris (1994), Wolf et al. (1996, 1998)

(hard vs. soft)

Richardson et al. (2013)

Age at release

Sarrazin & Legendre (2000), Shier (2006), Aaltonen et al. (2009),

Martínez–Abraín et al. (2011), White et al. (2012)

Others Public relations / attitude

Reading & Kellert (1993), Reading et al. (1997)

Management

Clark & Westrum (1989), Reading et al. (1997), Sheean et al. (2012)

and organization Long –term commitment

Short et al. (1992)

to the project Funding

Reading et al. (1997), Cochran–Biederman et al. (2015)

Animal Biodiversity and Conservation 39.2 (2016)

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120

240

360 km

Fig. 1. Spanish Mediterranean regions whose vertebrate translocation programs were analyzed in this study, shown within the context of the western Mediterranean. Fig. 1. Regiones mediterráneas de España cuyos programas de translocación de vertebrados se analizaron en este estudio, mostrados en el contexto del Mediterráneo occidental.

major part of the western Mediterranean, and are linked by close cooperation in implementing translo� cation programs. Data collection was a long process of exchanging information between managers and researchers to guarantee comparability of information available from the three regions. Program managers listed, independently, all the translocation programs that involved vertebrate species since the existence of regional governments in Spain (i.e., approximately since the early 1980’s). The final dataset contained information on 83 translocation programs, involving 34 vertebrate species (table 2, appendix 1). The duration of programs that were still in progress at the time of data collection was calculated as the number of years of implementation up until 2013. Managers were as� ked to provide information on the following variables: species translocated, number of animals released, origin of animals (i.e., captive–bred or from the wild), year of initiation and ending of the program, type of translocation (i.e., re–introduction/introduction or rein� forcement), and program success. Researchers asked managers to evaluate, according to their personal ex� perience, the success of their translocation programs. They were asked to evaluate success on a subjective scale from 0 to 10, where 0 was a complete failure and 10 a complete success (i.e., establishment and reproduction in the wild of the species translocated). Intermediate scores meant that establishment and/or reproduction had not been permanent. The process assumes that managers have similar knowledge and backgrounds to judge program success, which we feel is a reasonable assumption given the geogra� phical proximity of their regions, and the knowledge

of managers from any of the regions about programs from the other regions. A more objective criterion of success based on demographic parameters (e.g., a positive population growth rate or a low probability of quasi–extinction) would be preferred, but it requires detailed monitoring of the study species, which is not always done. Our dataset In some cases, the number of fish or reptiles/amphi� bians released was one or two orders of magnitude higher than the maximum number of mammals and birds released (i.e., which was 2,350). Thus we used the log10 of 'number' for statistical analyses, preventing convergence problems. Also, AIC had to be corrected for small sample size by means of AICc (Burnham & Anderson, 2008). Secondly, variance in the variable 'success' ex� ceeded its mean, suggesting overdispersion, and hence making a Poisson distribution of errors probably inappropriate. In fact, the ĉ value (i.e., residual devi� ance/residual degrees of freedom) of the saturated model was 6.15. We dealt with overdispersion by us� ing a negative binomial distribution (with the package glmmADMB), but reduced it minimally. Furthermore, the use of QAICc rather than AIC, for model selection did not improve our modelling. Thus, we reduced the variance of the variable 'success' by merging success scores into four categories with arbitrary cut–off points, and analyzing it as an ordinal variable (1 = from 0 to 3, 2 = from 4 to 6, 3 = from 7 to 8, and 4 = from 9 to 10). This new scale follows the same idea of

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Table 2. Summary of the main features of translocation programs examined in this study by taxa: * For statistical analyses the log10– transformed variable 'number' was used; B. Birds; M. Mammals; F. Fish; H. Herpetofauna. Tabla 2. Resumen de las principales características de los programas de translocación examinados en este estudio por taxón: * Para los análisis estadísticos, se usó la transformación logarítmica de la variable ''número'': B. Aves; M. Mamíferos; F. Peces; H. Herpetofauna.

Number of programs Total

Reinforcements 4

–

Reintroductions/ introductions

Number of programs per region Balearic Islands 11

–

Number of species 16

Catalonia C. Valenciana

Origin From the wild 12

Captive–bred 16

Number of individuals released per program (*) Median

58.5 48.5

Minimum

Maximum

2,350

1,058 1,124.5 12

63 260,000 5,300

Duration (years) Median

4.5

Minimum

Maximum

the original survey procedures, but it reduces the complexity of the analysis. Statistical analysis Translocation success was analyzed using Probit Logistic Regression models. '�� Success' was the re� sponse variable and 'origin', 'number' and 'taxa' were introduced as fixed effects. We intended to control for 'species' and 'region' as random effects to account for the fact that programs dealing with related species or programs coming from the same region can be more similar in their success than programs dealing

with unrelated species or those coming from different regions. However, this was not possible due to the use of Probit Logistic Regression Models. Our fixed effects are the most relevant effects among methodological factors, and importantly the most suitable variables to be modified by conservation practitioners: translocation effort, measured as number of released individuals and as duration of the program in years, plus origin, considering whether individuals were captive–breeding or from the wild. We set up 12 models corresponding to an equal number of biologically–sound hypotheses, with either one single fixed effect or the addition or interaction of two fixed effects. We contrasted multiple hypotheses (i.e., model comparison and selection) using theoreti� cal information criteria (AIC). Models with a ∆i < 2 were considered statistically equivalent, whereas ∆i values between three and seven were considered to indicate a considerably lesser relative–fit of the model (Burnham & Anderson, 2008). All analyses were performed using R (Version 3.1.0) software in� cluding the packages MASS and AICcmodavg (http:// www.r–project.org/). The relationship between success and duration and success and number, in relation to the use of wild or captive individuals, was analyzed using ANCOVA. Results When analyzing the success of translocation programs using multiple hypotheses testing, the models with the least AICc value (i.e., the most parsimonious models among our set of candidate models) were models 1, 2 and 3. All three models included the variable 'origin', either as the only fixed effect, as an additive effect of origin and duration, or as an interaction of origin with taxa (table 3). Taken altogether, the first three models accounted for ca. 70% of wi, suggest� ing that the origin of released individuals was the most important determinant of success in relation to translocation programs. Model 2 included dura� tion of translocation programs, as an additive effect to origin but, when duration was taken individually, as a fixed effect, the model had very little support, suggesting that origin was more influential than dura� tion (table 3). The same happened with the variable number. In summary, translocation success seemed to be considerably more affected by 'origin' than by 'number' or 'duration', the two variables measuring translocation effort. The fact that one of the best models included taxa as an interaction with origin suggests that the effect of success on origin differed depending on the taxa considered (i.e., fish, reptiles, birds and mammals). According to figure 2, success was greater for most taxa when using wild animals, especially for fish and mammals and, to a lower extent, for birds. However, success was lower when using wild herpetofauna. For translocation programs using individuals from wild sources, the median success score was 8, with the upper limit of the boxplot (the 3rd quartile) reaching 10, meaning that one quarter of all programs using indivi�

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Table 3. Model comparison testing effect of explanatory variables (origin of individuals, duration of translocation programs and number of individuals released) on success scores taken as an ordinal variable. See Material and methods for further modelling details: K. Number of identifiable parameters; NL. Natural logarithm of the likelihood function. (Best models shown in bold.) Tabla 3. Comparación entre modelos para probar el efecto de las variables explicativas (procedencia de los individuos, duración de los programas de translocación y número de individuos liberados) en las puntuaciones de éxito tomadas como variable ordinal. Véase el apartado Material and methods para encontrar información detallada de los modelos: K. Número de parámetros identificables; NL. Logaritmo neperiano de la función de probabilidad. (Los mejores modelos se señalan en negrita.)

Model

AICc

∆i

success ~ origin

–107.65

success ~ origin + duration

–106.64

223.43

0.26

223.47

0.04

0.25

success ~ taxa * origin

success ~ origin * duration

–105.82

223.90

0.47

0.20

–106.55

225.36

1.93

0.10

success ~ origin * number

success ~ origin + number

–107.64

225.46

2.03

0.09

–107.64

225.46

2.03

0.09

success ~ duration + number

success ~ number

–111.14

232.46

9.03

–112.70

233.52

10.10

9 10

success ~ taxa

–112.79

233.71

10.28

success ~ taxa * number

–110.77

233.80

10.37

success ~ duration * number

–111.11

234.48

11.06

success ~ duration

–113.60

235.32

11.89

duals from the wild were evaluated with the greatest success score (fig. 3). However, the median success score for translocations using individuals from captive sources was only 5.5, and one out of four programs was evaluated with a success score of 0. Both types of programs were able to achieve high success sco� res, but use of individuals from wild sources seldom led to low success scores, whereas programs using individuals from captive sources frequently failed. Va� riance of the median success was hence greater for programs dealing with captive–bred individuals, and as a consequence, the predictability of results was greater for programs dealing with individuals from a wild origin (fig. 3). Figure 4 shows the influence of the variables 'dura� tion' and 'number' on translocation success depending on the use of wild or captive individuals. Success increased with program duration (with a greater ef� fect when dealing with wild individuals) and the vari� ance in success decreased with increasing program duration: programs lasting five years or less were evaluated with almost every possible success score from 0 to 10, whereas success scores of long–lasting programs had mostly high values (fig. 4A). Surpris� ingly, (because one would expect that long–lasting programs were associated with the release of greater numbers of individuals) success decreased with the number of released individuals (fig. 4B). This puzzling result is explained by exploring origin of individuals,

because programs using greater numbers were those releasing more captive–reared individuals for which the relationship success/number was lower than for individuals from wild sources (fig. 4B). Furthermore, the correlation between 'duration' and 'number' (log10– transformed) was positive and statistically significant but weak (r = 0.28; 95% CI of Rho 0.07–0.47). Discussion Our results indicate that success of vertebrate trans� locations increases when using wild individuals. This effect was clear for all major taxa considered, except for herpetofauna that seemed to benefit from captivity. This exception could be related to a higher physiologi� cal and/or behavioral plasticity of terrestrial ectotherms than terrestrial homeotherms and aquatic ectotherms. Anyhow, success translocating captive–reared reptiles and amphibians should be more common than when releasing other vertebrate groups. Although 'origin' was the main determinant of suc� cess, we cannot exclude an effect of program duration, given that one of the best models included 'duration' as an additive fixed effect. The optimal situation would then be a program releasing wild individuals for a long period of time. Programs using individuals from wild sources achieved greater median success scores than pro�

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Success

8 6 4 2

Capt_mamm

Wild_mamm

Capt_herp

Wild_herp

Capt_fish

Wild_fish

Capt_bird

Wild_bird

Fig. 2. Boxplot showing the interaction of translocation success and taxa (birds, fish, herpetofauna, and mammals) when using wild individuals (wild) or individuals from captivity (capt). Fig. 2. Diagrama de caja en el que se muestra la interacción del éxito de la translocación y los taxones (aves, peces, herpetofauna y mamíferos) cuando se utilizan individuos silvestres (wild) o individuos en cautividad (capt).

grams using individuals from captive sources. Similar results were obtained by past studies which have shown that animal translocations are more likely to succeed when individuals from wild sources are re� leased (Griffith et al., 1989; Wolf et al., 1996; Fischer &

Lindenmayer, 2000). For example, Brown et al. (2006) conducted a reintroduction program with wild–born and hacked Aplomado falcons, Falco femoralis, and found that captive–born falcons survived at lower rates than wild–born falcons, possibly because they did not

Success

8 6 4 2 0 Wild

Origin

Captivity

Fig. 3. Boxplot comparing median success scores assigned by wildlife managers to translocation programs dealing with captive–bred individuals or individuals from wild sources. Fig. 3. Diagrama de caja en el que se comparan las medianas de las puntuaciones de éxito asignadas por los gestores de fauna silvestre con los programas de translocación en que se utilizan individuos criados en cautividad o individuos procedentes del medio natural.

Animal Biodiversity and Conservation 39.2 (2016)

10 Success score

215

8 6 4 Wild Captive

2 0 0

15 Duration

Success score

Wild Captive

0 1

3 Lognumber

Fig. 4. A. Linear relationship between translocation success scores and duration of translocation programs for wild and captive individuals from an ANCOVA model. B. Linear relationship between success scores and number of individuals released in translocation programs for wild and captive individuals from an ANCOVA model. Fig. 4. A. Relación lineal entre las puntuaciones de éxito de la translocación y la duración de los progra� mas de translocación para individuos silvestres y en cautividad, obtenida mediante un modelo ANCOVA. B. Relación lineal entre las puntuaciones de éxito y el número de individuos liberados en programas de translocación para individuos silvestres y en cautividad, obtenida mediante un modelo ANCOVA.

develop foraging skills or learn to recognize and avoid predators during their time spent in captivity (Brown et al., 2006; Jule et al., 2008; Schetini de Azevedo et al., 2012; Gil et al., 2014). Many captive–born

individuals die immediately after release due to their inability to adapt to their new environments regarding predators or to find food. In fact, this immediate 'cost of release' (a high mortality rate among captive–reared

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individuals during the first weeks after release) seems to be an emergent property of animal translocations, especially when individuals from captive sources are involved. In this context, Tavecchia et al. (2009) found that approximately one third of the post–release mortality of reintroduced crested coots, Fulica cristata, which were raised in captivity, occurred within the first month post–release. As the survival rate increased with time spent in the wild, the authors concluded that it is probably the lack of experience of captive–born individuals that caused a high post–release mortality until released individuals became familiar with their new wild environment. Cabezas et al. (2013) provided a physiological explanation (i.e., differences in acute stress response) for greater establishment success of individuals from wild origins. Some authors failed to find differences between programs based on wild or captive–reared individuals. However, these results can be due to artifacts occurring for other reasons. For example, the negative results by White et al. (2012) in a long–lived parrot species could be related to both the definition of reintroduction success (first year survival > 0.5) and to low statisti� cal power. In addition, programs dealing with individuals from wild sources had smaller variances in success, mean� ing that prediction of results is greater when using wild–caught individuals, a property that is desirable in any translocation program. The importance of the origin of released individu� als for translocation success is supported indirectly by recent findings in invasion biology, where the determinants of establishment success of introduced birds were examined. Conclusions drawn from animal introductions may be used to interpret the results of analyses with animal translocations as it has been shown that introduced and reintroduced species show comparable properties (Blackburn & Cassey, 2004). Specifically, Carrete & Tella (2008) found that the key factor for success in establishing exotic pet bird species that escaped into the wild was their origin and the number of escaped birds. Surprisingly, the most successful invaders were those birds that were caught in the wild and then traded at the pet market, and not the most common pet bird species, which provide the most cases of escaped birds, that is, the greatest introduction effort. One of the reasons behind that success seems to be that wild–caught individuals have higher antipredatory responses and escape abilities than captive–bred individuals (Carrete & Tella, 2005) and also that international trade acts as a selection agent of the most resistant individuals (Carrete et al., 2012). Although there has been a substantial increase in number of animal translocations for conservation during the last 20 years, only a few include detailed evidence–based evaluations of program outcomes, making it difficult for practitioners to learn from previous failures, and to improve their methods to maximize probability of success. Therefore, conclu� sions drawn from our results (along the same line identified previously by other authors) can be useful guidelines to conservation practitioners when desig�

ning a translocation program involving vertebrate species. We recommend, for any given translocation effort, to use individuals from wild sources whenever possible, to increase the probability of achieving a successful establishment of the translocated species and a greater predictability of the outcome. This point is especially relevant in times of economic hardship because scarce available resources should be used optimally when considering costs and benefits. When it is not feasible to obtain individuals from wild sour� ces, either because they are extinct in the wild or the species is threatened with extinction, the best alternative is to implement the program for a long number of years (10–30 years), rather than releasing many captive–reared individuals for a short period of time. Perseverance also pays in translocation. Acknowledgments We are most grateful to all the tecnicians, wardens and field assistants involved in the progress of the translocation projects analyzed. Without their con� tribution this work would not have been possible. We are also most grateful to Dirección General del Medio Natural y Biodiversidad (DAAM), B. Minobis, P. Josep Jiménez, J. Sargatal, N. Valls, O. Comas, J. M. Queralt and N. Franch. A. M. A. was supported by a postdoctoral contract by Xunta de Galicia. L. R. received an ERASMUS scholarship during her stay at IMEDEA. We are also grateful to 'Programa de Investigación Competitiva del Sistema Universitario Gallego' reference GRC2014/050 from Xunta de Ga� licia for financing our project 'Grupo de Investigación en Biología Evolutiva (GIBE) de la Universidade da Coruña'. Catherine Andrés built figure 1. References Aaltonen, K., Bryant, A. A., Hostetler, J. A. & Oli, M. K., 2009. Reintroducing endangered Vancouver Island marmots: survival and cause–specific mor� tality rates of captive–born versus wild–born indi� viduals. Biological Conservation, 142: 2181–2190. Url: http://dx.doi.org:10.1016/j.biocon.2009.04.019. Armstrong, D. & Seddon, P., 2008. Directions in reintroduction biology. Trends in Ecology & Evo� lution, 23: 20–25. Url: http://dx.doi.org/10.1016/j. tree.2007.10.003. Beck, B. B., Rapaport, L. G., Price, M. R. S. & Wil� son, A. C., 1994. Reintroduction of captive–born animals. In: Creative Conservation: 265–286 (P. J. S. Olney, G. M. Mace & A. T. C. Feistner, Eds.). Springer, Netherlands. Bertolero, A., Oro, D. & Besnard, A., 2007. Assessing the efficacy of reintroduction programmes by mod� elling adult survival: the example of Hermann’s tor� toise. Animal Conservation, 10: 360–368. Url: http:// dx.doi.org/10.1111/j.1469–1795.2007.00121.x. Blackburn, T. M. & Cassey, P., 2004. Are introduced and re–introduced species comparable? A case study of birds. Animal Conservation, 7: 427–433.

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Appendix. List of species considered in our study (in alphabetic order) including the number of translocation programs (#Prg) for each species and the percentage of programs (%Prg) with the maximum success score. Apéndice. Lista de especies examinadas en nuestro estudio (por orden alfabético), que comprende el número de programas de translocación (#Prg) para cada especie y el porcentaje de programas (%Prg) con la máxima puntuación de éxito. Species

#Prg %Prg

Species

#Prg

%Prg

Fish

Birds Aegypius monachus

Bubulcus ibis

100

Aphanius iberus

Barbus meridionalis

100

Ciconia ciconia

Gasterosteus aculeatus

Circus pygargus

Gasterosteus gymnurus

Egretta garzetta

100

Salaria fluviatilis

Falco naumanni

Alytes muletensis

Valencia hispanica Herpetofauna

Fulica cristata

Hieraetus fasciatus

100

Larus audouinii

Bufo viridis

Marmaronetta angustirostris

Calotriton arnoldi

Netta rufina

100

Emys orbicularis

Nycticorax nycticorax

100

Mauremys leprosa

Oxyura leucocephala

Testudo graeca

Pandion haliaetus

Testudo hermanni

Capra hispanica

100

Capreolus capreolus

100

Porphyrio porphyrio

Tetrao urogallus

Mammals

Felis sylvestris

Lutra lutra

100

Ursus arctus

Ruiz–García & Ferreras–Romero

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The influence of vegetation structure on spider species richness, diversity and community organization in the Apšuciems calcareous fen, Latvia M. Štokmane & V. Spuņģis

Štokmane, M. & Spuņģis, V., 2016. The influence of vegetation structure on spider species richness, diversity and community organization in the Apšuciems calcareous fen, Latvia. Animal Biodiversity and Conservation, 39.2: 221–236. Abstract The influence of vegetation structure on spider species richness, diversity and community organization in the Apšuciems calcareous fen, Latvia.— Calcareous fens are considered to be among the most threatened ecosystems of Europe. They are also one of the most diverse habitats as they support an incredibly rich and diverse range of plant and animal species. However, in spite of their diversity, calcareous fens are still poorly investigated, especially when referring to fen invertebrates, such as spiders. Because spiders are good bioin� dicators, knowledge of their ecology in rare and threatened habitats is of interest. The aim of this study was to document the composition and diversity of spider species, families and foraging guilds in the ground– and grass–layers of the Apšuciems calcareous fen, and to evaluate the influence of vegetation structure on spider community organization. In summer 2012, we collected ground–dwelling spiders using pitfall traps and grass– dwelling spiders using sweep–netting. A total of 2,937 spider individuals belonging to 19 families and 80 species was collected in the Apšuciems fen. Our results indicate that spider species and families tend to be stratified across the vertical structure of the habitat; the spider composition in the ground stratum differed from that in the grass stratum. On the contrary, however, the spider foraging guild structure between the ground–layer and the grass–layer was similar. Each of the two studied strata presented similar guilds in similar proportions. Our results also showed that spider composition differed considerably between fen parts and that much of this variability could be explained by the architectural properties of the habitat. More diverse vegetation generally supported a higher number of spider species. Key words: Araneae, Community structure, Vertical stratification, Foraging guilds, Habitat heterogeneity Resumen La influencia de la estructura de la vegetación en la riqueza de especies, la diversidad y la organización de las comunidades de arañas en el pantano en terreno calcáreo de Apšuciems, en Letonia.— Se considera que los pantanos en terrenos calcáreos son uno de los ecosistemas más amenazados de Europa. Asimismo, son uno de los hábitats con mayor diversidad, puesto que albergan una variedad de especies de plantas y animales increíblemente rica y diversa. No obstante, a pesar de su diversidad, los pantanos en terrenos cal� cáreos se han estudiado poco, especialmente por lo que hace a los invertebrados, como las arañas. Debido a que son buenos indicadores, es interesante conocer su ecología en hábitats singulares y amenazados. Este estudio tiene como finalidad documentar la composición y diversidad de las especies, familias y gremios de alimentación de arañas en los estratos edáfico y herbáceo del pantano calcáreo de Apšuciems, y evaluar la influencia de la estructura de la vegetación en la organización de las comunidades de arañas. En verano de 2012, recogimos arañas que habitan en el suelo utilizando trampas de caída y arañas que habitan en la hierba con redes entomológicas. En total, en el pantano de Apšuciems se recogieron 2.937 arañas pertenecientes a 19 familias y 80 especies. Nuestros resultados indican que las especies y familias de arañas tienden a estra� tificarse a lo largo de la estructura vertical del hábitat; la composición de arañas en el estrato edáfico difería de la del estrato herbáceo. Por el contrario, la estructura de los gremios de alimentación era parecida en el estrato edáfico y el estrato herbáceo. Cada uno de los dos estratos estudiados presentaba gremios parecidos en proporciones similares. Nuestros resultados también pusieron de manifiesto que la composición de arañas ISSN: 1578–665 X eISSN: 2014–928 X

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difería considerablemente entre distintas partes del gremio y que gran parte de esta variabilidad se podía explicar por las propiedades arquitectónicas del hábitat. En general, cuanto más diversa era la vegetación, mayor era el número de arañas. Palabras clave: Araneae, Estructura de comunidades, Estratificación vertical, Gremios de alimentación, Heterogeneidad del hábitat Received: 9 X 15; Conditional acceptance: 23 XI 15; Final acceptance: 10 V 16 Maija Štokmane & Voldemārs Spuņģis, Dept. of Zoology and Animal Ecology, Fac. of Biology, Univ. of Latvia, Kronvalda Boulevard 4, LV–1586, Riga, Latvia Corresponding author: M. Štokmane. E–mail: hidra4@inbox.lv

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Introduction

Material and methods

Calcareous fen habitats have a high conservation value because they support an incredibly rich and diverse range of plants and animals, including many endangered species (Moore et al., 1989; Schmidt et al., 2008; McBride et al., 2011). Despite their ecological relevance, however, calcareous fens have been subjected to various destructive land use practices, such as drainage, peat harvesting, and neglect (Johnson, 2000; McBride et al., 2011). As a result, calcareous fens are now less common than they were 40 to 50 years ago (McBride et al., 2011) and are among the most threatened ecosystems in Europe (�� Seer & Schrautzer, 2014�� ). In Latvia, cal� careous fens are also one of the rarest habitats but their exact size is unknown; approximate estimates indicate they cover only 0.01% of the total area of Latvia (Auniņš et al., 2013). Spiders are among the most dominant insecti� vores in terrestrial ecosystems, and they inhabit a wide array of spatial and temporal niches (Kremen et al., 1993; Wise, 1995). As predators, spiders are important components of natural ecosystems, playing a vital role in structuring arthropod communities and thus having a significant role in the balance of nature (Gertsch, 1979; Uetz, 1991; Nyffeler et al., 1994; Marc et al., 1999). As spiders have a great potential as good bioindicators (Marc et al., 1999; Pearce & Venier, 2006), by studying them it is possible to assess the conservation value of a particular habitat (Churchill, 1997; Mas et al., 2009). To date, however, the ecology of spider assemblages has been poorly studied in fen ecosystems, especially calcareous fens. Spiders have been widely recommended as good indicator organisms for several reasons: (1) they are widely distributed in high numbers and therefore provide data that are appropriate for statistical analy� ses (Foelix, 2011); (2) they can be easily collected using standardised sampling methods (Wise, 1995); (3) they are taxonomically well known compared to other invertebrate groups, and �� can be identified wit� hout expensive equipment or techniques (Oxbrough et al., 2005; Cardoso, 2009); and (4) they are good predictors of overall invertebrate biodiversity since they appear to be linked to herbivore and detrivore food webs (Uetz, 1991; Wise, 1995; Willett, 2001). In previous studies, we investigated several cal� careous fens in the Coastal Lowland and focused on either ground–dwelling (Štokmane et al., 2013) or grass–dwelling spider assemblages (Štokmane & Spuņģis, 2014). In the present study, we focused on a single calcareous fen (the Apšuciems fen) and performed a more detailed study of both spider groups (ground– and grass–dwellers). The aims of this study were: (1) to document and compare the species rich� ness, diversity and guild composition of spiders in the ground and in grass layers of �� the Apšuciems calcare� ous fen; and (2) to evaluate the potential influence of several vegetation parameters (namely, plant species richness, plant diversity and vegetation height) on the diversity and community organization of ground– and grass–dwelling spider in this fen.

Study area and sampling design Samples were collected in the Apšuciems calcareous fen, in Lapmežciems parish, Engure district, Latvia. The Apšuciems fen is located in the Coastal Lowland of the Baltic Sea and the Gulf of Riga. The fen covers an area of about 15 ha, and it is situated in the territory of a unique hydrological regime —it is a periodically flooded dune slack. The Apšuciems fen is a nature reserve and a 'Natura 2000' site. We used a systematic sampling grid in the study (fig. 1). We randomly selected a point in the central part of the fen, and from this point we set up a 50 × 50 m grid in the fen. We then set a 9 × 9 m plot on the northwest corner of each grid cell, for a total of 61 plots. Four of the plots were later discarded because they were located in forested habitats. We therefore used a total of 57 sampling plots. To characterize the vegetation structure in each plot, we recorded the number of plant species and visually estimated their percent cover. Before data analysis, all vegetation cover values were transformed according to the Braun–Blanquet scale which gives numerical rankings to a range of percentages: (+) < 1% percent cover; (1) 1–5%; (2) 6–25%; (3) 26–50%; (4) 51–75%; (5) 76–100% (Braun–Blanquet, 1964). Vascular plants were identified to species level when possible, otherwise to genus. Bryophytes were considered as a group and were not identified to any taxonomic level. Vascular plant identification followed Pētersone & Brikmane (1980) and Mossberg & Stenberg (2003). Vegetation height (cm) was also recorded in each plot; it was measured as the height of the tallest plant. Spider sampling and identification Two collection methods were used to sample either ground–dwelling or grass–dwelling spiders. The ground–dwelling spiders were collected using pitfall traps, consisting of plastic cups with a diameter of 7.5 cm and a volume of 250 mL. Each trap was filled with 100 mL of a solution of 90 mL of 10% formaline, 10 mL ethylene glycol, and some detergent. Traps were placed in the ground with the rim leveled to the surface. Six pitfall traps were installed in each plot; traps were placed in two lines of three traps and spaced 1 m apart. Trapping was continuous, with traps being kept open from 27 VII until 22 VIII 2012. The grass–dwelling spiders were collected using a sweep net with a rim diameter of 30 cm. A sample consisted of 50 strokes of the sweep net taken in a circular manner within ca. 5 m from the plot center. The sweep–netting was carried out on 26 and 27 VII 2012. After collection, spiders were immediately preserved in 70% ethanol for later examination. In the laboratory, all spiders were sorted, counted and identified using appropriate literature. Mature spider individuals were identified to species when possible; unidentified adult specimens were recorded as morphospecies. Most immatures were identified to family only. We used the identification keys of Locket & Millidge (1953), Roberts

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(1996) and Nentwig et al. (2012), and followed the World Spider Catalog version 17.0 (Platnick, 2016) for the nomenclature and taxonomy of spiders. Voucher specimens were stored in 70% ethanol and deposited in the Department of Zoology and Animal Ecology, Faculty of Biology, University of Latvia, Riga. Statistical analyses To evaluate plant and spider species richness and diversity in the fen, we used three indices: the number of observed species (S) as the primary indicator of plant/spider species richness, as well as the Shannon– Wiener index (H), and the Pielou’s evenness index (J) as a measure of species diversity. We chose these indices because they are among the most popular and most frequently used diversity indices in ecology. Mathematical formulae to calculate the Shannon index and the evenness index can be found in Magurran (2004). The calculations were performed for each of the 57 sample plots and then averaged for the whole fen. All diversity indices were calculated using the PC–ORD 5.0 (McCune & Mefford, 2006). Spider dominance structure was analyzed at family and species levels, as well as by foraging guilds. The dominance level for each spider species was calculated according to the logarithmic dominance classification proposed by Engelmann (1978) in which eudominant species comprise > 32% of the total abundance, while dominant, subdominant, recedent, subrecedent, and sporadic species comprise 10–32%, 3.2–10%, 1–3.2%, 0.32–1%, and less than 0.32%, respectively. On the basis of prey capture method, spider families can be grouped into two or more foraging guilds of differing mobility. In this study, we used the following guild clas� sification (modified from Uetz, 1977; Wise, 1995): (1) web spinners; (2) sit–and–wait ambushers; and (3) active hunters. We used a simple linear regression analysis to test for relationships between spider diversity parameters (spider abundance, species richness and diversity) and vegetation characteristics: the number of plant species (species richness), plant diversity (Shannon index) and vegetation height. Before testing, data were checked for normality of distribution (using Kolmogorov–Smirnov test) and, if necessary, log–transformed prior to analy� ses. Regression analysis was conducted using the R software (R Development Core Team, 2011). The data were also interpreted using an ecological ordination technique —a redundancy analysis (RDA) that is the canonical version of principal component analysis (PCA) (Legendre & Legendre, 1998). RDA is one of the most prominent methods of direct gradient analysis (Lepš & Šmilauer, 2003). This analysis was used to detect patterns in spider community organi� zation in relation to vegetation structure. The RDA was based on the spider species and the number of specimens within each species found in each sample plot. Juvenile spiders and species with fewer than four individuals were excluded from the analysis. The species data were Hellinger–transformed prior to analysis, since the Hellinger distance is supposedly a better ecological distance than the Euclidean distance

(Legendre & Gallagher, 2001). The scaling method 2 (= the covariance biplot) was used. We tested the statistical significance of the RDA by means of per� mutations (number of permutations: 999). The RDA was run by the R (R Development Core Team, 2011) with the VEGAN package (Oksanen et al., 2009). Results Habitat characteristics of the studied fen A total of 50 species of vascular plants were found in the Apšuciems fen. The dominant plant species with the highest mean percent cover were Cladium mariscus with 27.81% cover (± 4.69 SE), Myrica gale with 21.06% (± 1.79), Molinia caerulea with 19.88% (± 3.50), Phragmites australis with 13.91% (± 2.03), Schoenus ferrugineus with 8.89% (± 1.95), Frangula alnus with 5.07% (± 1.68) and Carex lasiocarpa with 2.55% (± 0.65). The mean Shannon index for vascular plants was 1.44 (± 0.05) and it ranged from 0.49 to 2.10, while the mean evenness was 0.62 (± 0.02) and ranged from 0.23 to 0.85. The vegetation height also differed considerably between different parts of the Apšuciems fen —the mean vegetation height for the whole fen was 150 cm (± 14.55), but it ranged between 40 and 900 cm. Spider diversity A total of 2,937 spiders was collected, representing 80 species in 19 families. All spider species were sorted into two groups: ground–dwellers and grass–dwellers. Since we could not find any strict classification in the literature concerning which spider species are conside� red ground–dwellers and which are grass–dwellers, we classified all the collected spider species according to the method by which they were caught, i.e., if the par� ticular species was collected by pitfall trapping, it was considered to be a ground–dweller, but if the species was collected by sweep netting, it was considered to be a grass–dweller. Of all 80 spider species collected, only eight were obtained using both methods. In this case, a species was �� put in one or the other group tak� ing into account in which samples there was a greater number of individuals of the particular species. Thereby, Pardosa fulvipes (89% of all individuals found in pitfall traps) and Episinus angulatus (two of three individuals found in pitfall �� traps�� ) were �� classified as ground–dwell� ing spider species, whereas Dolomedes fimbriatus (89% of all individuals found in a sweep net), Pisaura mirabilis (86%), Evarcha arcuata (87%), Xysticus ulmi (85%), Oxyopes ramosus (98%) and Cheiracanthium punctorium (two of three individuals found in a sweep net) were considered grass–dwelling species. Fifty– five of the collected spider species were classified as ground–dwellers and 25 as grass–dwellers. The mean Shannon index was 1.69 (± 0.06 SE; range: 0.50 to 2.25) for ground–dwelling spiders and 0.85 (± 0.07 SE; range: 0.14 to 1.86) for grass–dwell� ing spiders. Species evenness was 0.87 (± 0.02) for the ground–dwelling spiders and 0.68 (± 0.04) for the grass–dwelling spiders.

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41 x

60 x

61 x

50 m

58 x

6323200 6323250 6323300 6323350 6323400 6323450 6323500 6323550 6323600 6323650 6323700

6323250 6323300 6323350 6323400 6323450 6323500 6323550 6323600 6323650 6323700

458250 458300 458350 458400 458450 458500 458550 458600 458650 458700 458750 458800 458850 458900 458950 459000 459050

Fig. 1. The study area and the arrangement of the sampling plots in the Apšuciems calcareous fen. In total, 57 out of 61 sample plots were used in the study (the four discarded plots are crossed out). Fig. 1. Área de estudio y localización de las parcelas de muestreo en el pantano en terreno calcáreo de Apšuciems. En total, en el estudio se utilizaron 57 de las 61 parcelas de muestreo (las cuatro que se descartaron están tachadas).

Spider dominance structure Spider dominance structure in the Apšuciems fen was analyzed both by taxonomic groups (i.e., spe� cies and families) and by ecological groups (i.e., foraging guilds). The most dominant species in the ground–layer were Trochosa terricola, Antistea elegans, Piratula hygrophilus, Zora spinimana, and Hygrolycosa rubrofasciata while in the grass–layer were Dolomedes fimbriatus and Evarcha arcuata (table 1). No eudominant species were detected among the ground–dwelling spiders, but the number of dominant and subdominant species was relatively large. Findings in the grass–layer differed somewhat as the numbers of spiders among the three most dominant classes were more evenly distributed, i.e., there were one eudominant, one dominant and two subdominant grass–dwelling spider species. Thus, species composition and dominance structure were evidently distinct in each of the two strata. A large number of sporadic spider species was also observed in the fen; 35 ground–dwelling spiders (63% of all ground–dwellers) and seven grass–dwellers (28% of all grass–dwellers) could be considered sporadic. We observed large differences in dominance at the family level between the ground and the grass layers (figs. 2A–2B). The most abundant family in the

ground–layer was Lycosidae, representing 60.8% of all the ground–dwelling spiders, while in the grass–layer the most abundant family was Pisauridae, represent� ing 59.9% of all the grass–dwelling spiders. These two families clearly dominated numerically, despite the fact that the family Pisauridae was represented almost solely by Dolomedes fimbriatus, while the family Lyco� sidae was represented by 13 different species. In turn, the most speciose spider families in the ground–layer were Linyphiidae (34.5% of all ground–dwellers) and Lycosidae (23.6%) while in the grass–layer they were Araneidae (28.0% of all grass–dwellers). Spiders were grouped into three foraging guilds based on the spider foraging technique: (1) web spinners (detected spider families: Theridiidae, Ara� neidae, Agelenidae, Linyphiidae, Tetragnathidae and Hahniidae); (2) sit–and–wait ambushers (Lycosidae, Thomisidae and Pisauridae); and (3) active hunters (Gnaphosidae, Clubionidae, Miturgidae, Philodromi� dae, Salticidae, Oxyopidae, Zoridae, Liocranidae and Corinnidae). The exception was the family Cybaeidae which was not included in any of the mentioned guilds because the single species that we collected from this family (the water spider, Argyroneta aquatica) shows different foraging strategies depending on the sex of an individual, i.e., males of A. aquatica wander around and catch their prey mainly by active hunting, while

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Table 1. The most abundant spider species collected in the ground–layer and in the grass–layer of the Apšuciems fen in 2012. The Engelmann’s scale of dominance is used (Engelmann, 1978). Tabla 1. Las especies de arañas más abundantes recogidas en el estrato edáfico y en el estrato herbáceo del pantano de Apšuciems en 2012. Se ha utilizado la escala de dominancia de Engelmann (Engelmann, 1978).

Dominance class Ground–layer

Grass–layer

Eudominant species (> 32%) –

Dolomedes fimbriatus (Pisauridae)

Dominant species (10–32%) Trochosa terricola (Lycosidae), Antistea

Evarcha arcuata (Salticidae)

elegans (Hahniidae), Piratula hygrophilus (Lycosidae), Zora spinimana (Zoridae), Hygrolycosa rubrofasciata (Lycosidae) Subdominant species (3.2–10%) Pirata tenuitarsis (Lycosidae), Piratula knorri

Oxyopes ramosus (Oxyopidae),

(Lycosidae), Pardosa sphagnicola (Lycosidae),

Heliophanus cupreus (Salticidae)

Pardosa fulvipes (Lycosidae) Recedent species (1–3.2%) Pirata uliginosus (Lycosidae), Allomengea vidua Pisaura mirabilis (Pisauridae), Synageles venator (Linyphiidae), Phrurolithus festivus (Corinnidae), (Salticidae), Xysticus ulmi (Thomisidae), Bathyphantes gracilis (Linyphiidae), Pardosa lugubris Singa hamata (Araneidae), (Lycosidae), Bathyphantes parvulus (Linyphiidae), Neoscona adianta (Araneidae) Euryopis flavomaculata (Theridiidae) Subrecedent species (0.32–1%) Walckenaeria alticeps (Linyphiidae), Leptorchestes berolinensis (Salticidae),

Tibellus maritimus (Philodromidae), Tetragnatha

Oedothorax sp. (Linyphiidae),

nigrita (Tetragnathidae), Clubiona germanica (Clubionidae), Tibellus oblongus (Philodromidae),

Erigone arctica (Linyphiidae)

Marpissa radiata (Salticidae), Araneus diadematus

(Araneidae), Araniella cucurbitina (Araneidae),

Araneus quadratus (Araneidae), Cheiracanthium

punctorium (Miturgidae)

Sporadic species (< 0.32%) The remaining 35 species

females spend most of their time inside a diving bell and are sit–and–wait ambushers (Schütz & Taborsky, 2003). The exclusion of Cybaeidae from the guild analysis did not affect the results because we caught only two A. aquatica individuals. Overall, the analysis of guild composition showed that the spider guild struc� ture in both layers was similar, with the sit–and–wait ambushers being the most numerically dominant guild in both strata, and the web spinners being the most species–rich guild in both strata (figs. 2C–2D).

The remaining seven species

Effects of vegetation structure The regression analysis showed that spider abundance, species richness and diversity were significantly affec� ted by plant species richness and plant diversity in the fen (table 2). Overall, the structural parameters of the vegetation were more influential in the grass–dwelling spiders. For example, the analyses showed that plant species richness accounted for 21.7% and 18.1% of the total variation in grass–dwelling spider species rich�

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A B 100% 100% 90% 90% 80% 80% 70% 70% 60% 60% 50% 50% 40% 40% 30% 30% 20% 20% 10% 10% 0% 0% Ground–layer Grass–layer

Grass–layer

Araneidae

Pisauridae

Hahniidae

Araneidae

Philodromidae

Salticidae

Gnaphosidae

Pisauridae

Linyphiidae

Zoridae

Linyphiidae

Salticidae

Lycosidae

Other families

Liocranidae

Theridiidae

Lycosidae

Other families

Oxyopidae

C 100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Ground–layer

Ground–layer Web spinners

Grass–layer

100% 90% 80% 70% 60% 50% 40% 30% 20% 10% 0%

Sit–and–wait ambushers

Ground–layer

Grass–layer

Active hunters

Fig. 2. The dominance structure of spider families and foraging guilds by the number of individuals and by the number of species in the ground–layer and in the grass–layer of the Apšuciems fen: A. The most abundant spider families; B. The most species–rich spider families; C. The most abundant spider foraging guilds; D. The most species–rich spider foraging guilds. Fig. 2. La estructura de la dominancia de las familias y gremios de alimentación de las arañas según el número de individuos y según el número de especies en el estrato edáfico y en el estrato herbáceo del pantano de Apšuciems: A. Las familias de arañas más abundantes; B. Las familias de arañas con mayor riqueza de especies; C. Los gremios de alimentación de arañas más abundantes; D. Los gremios de alimentación de arañas con mayor riqueza de especies.

ness and abundance, respectively. Meanwhile, a small fraction of the total variance of the ground–dwelling spiders was explained by the vegetation characteristics. In contrast to the positive relation between spi� ders and plant diversity, vegetation height negatively affected spider numbers (table 2). The total species

richness and diversity of grass–dwellers decreased significantly with increasing height of the vegetation. A correlation analysis between vegetation height and different plant species showed that higher vegeta� tion was positively associated with the presence of Phragmites australis (rS = 0.354; p–value < 0.01).

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Table 2. Linear regression analysis describing the relationships between the ground–dwelling and the grass–dwelling spiders and the studied vegetation characteristics (N = 57). Statistical significance: * p < 0.05; ** p < 0.01; *** p < 0.001. Tabla 2. Análisis de regresión lineal que describe las relaciones existentes entre las arañas que habitan en el suelo y las que habitan en la hierba y las características estudiadas de la vegetación (N = 57). Significación estadística: * p < 0,05; ** p < 0,01; *** p < 0,001. Predictor (x) Response (y)

p–value

Regression equation

Spider abundance

0.07438

0.04012*

y = 8.7995 + 0.8041x

Species richness

0.08362

0.02914*

y = 4.5857 + 0.2632x

Species diversity

0.1376

0.004497**

y = 1.09513 + 0.05695x

Ground–dwelling spiders Plant species richness

Plant diversity Spider abundance

0.02047

0.2884

y = 13.035 + 2.895x

Species richness

0.03291

0.1769

y = 5.7055 + 1.1333x

Species diversity

0.08383

0.02892*

y = 1.2514 + 0.3051x

Vegetation height Spider abundance

0.001644

0.7646

y = 17.179 + 0.714x

Species richness

0.01304

0.3976

y = 7.3452 – 0.6209x

Species diversity

0.04632

0.1079

y = 1.69339 – 0.19733x

Spider abundance

0.1812

0.0009618***

y = –3.5705 + 1.5505x

Species richness

0.2168

0.0002627***

y = 0.60042 + 0.07585x

Species diversity

0.1216

0.007852**

y = 0.14846 + 0.06674x

0.06134

0.06323

y = 3.721 + 6.191x

Species richness

0.1331

0.005258**

y = 0.8061 + 0.4080x

Species diversity

0.06776

0.05051*

y = 0.354 + 0.342x

Grass–dwelling spiders Plant species richness

Plant diversity Spider abundance

Vegetation height Spider abundance

0.01234

0.4108

y = 12.660 – 2.416x

Species richness

0.07256

0.04273*

y = 1.39722 – 0.26212x

Species diversity

0.06756

0.05086*

y = 0.85085 – 0.29715x

Spider community patterns The redundancy analysis (RDA) of the ground– dwelling spider assemblages produced a significant ordination (p = 0.001 after 999 permutations; fig. 3A). The numerical output of the RDA showed that the first two canonical axes together accounted for 33.8% of the total variance of the data; the first axis explained 19.8%. Axis 1 correlated strongly with a plant species

richness gradient, where plots rich in different plant species were plotted on the left while those with a low number of plant species and a large cover of Cladium mariscus were plotted on the right. Axis 2 was associated with the presence/absence of Scirpus tabernaemontani and bryophytes, where plots with high coverage of S. tabernaemontani and mosses were situated in the lower part of the graph and those with low coverage, in the upper part.

Animal Biodiversity and Conservation 39.2 (2016)

37 38

RDA2

0.5

0.0

56 51 50 27 24 56 39 54 22 15 48 41 5 Plants_H1 10 16 9

36 28

46 53 45

–0.5

52 20

6 21 2

Scir_tab

42 24 23 26 19 40 18

Bryophyta

–0.5

0.5 0.0

2 13 30 36 11 28 37 24 46

Myr_gale

–1.0

–0.5

Plants_H

43 31

31 52

1.0

Clad_mar

Plants_S 8

Mol_caer

1.5

RDA2

229

45 50

Veg_heig

39 26

42 41 17

10 3

22 56

Clad_mar

0.0 0.5 –1.5 –1.0 –0.5 0.0 0.5 RDA1 RDA1

1.0

1.5

Fig. 3. RDA ordination diagrams showing spider community organization according to vegetation structure, scaling 2. Circles represent sampling plots. Only species with ≥ 4 individuals were included in the analysis, and only the most significant vegetation variables (displayed as arrows) are shown: A. Ordination plot for the ground–dwelling spider assemblages; B. Ordination plot for the grass–dwelling spider assemblages. Abbreviations: Bryophyta. Bryophytes; Clad_mar. Cladium mariscus; Mol_caer. Molinia caerulea; Myr_gale. Myrica gale; Scir_tab. Scirpus tabernaemontani; Plants_H. Plant diversity (Shannon index); Plants_S. Plant species richness; Veg_heig. Vegetation height. Fig. 3. Diagramas de ordenación mediante el análisis de la redundancia (RDA en su sigla en inglés) en los que se muestra la organización de las comunidades de arañas en función de la estructura de la vegetación, escalamiento 2. Los círculos representan las parcelas de muestreo. Solo se incluyeron en el análisis las especies con más de 4 individuos y únicamente se muestran las variables de vegetación más significativas (mostradas como flechas): A. Gráfico de ordenación para los ensamblajes de arañas que habitan en el suelo; B. Gráfico de ordenación para los ensamblajes de arañas que viven en la hierba. Abreviaciones: Bryophyta. Briófitos; Clad_mar. Cladium mariscus; Mol_caer. Molinia caerulea; Myr_gale. Myrica gale; Scir_tab. Scirpus tabernaemontani; Plantas_H. Diversidad vegetal (índice de Shannon); Plantas_S. Riqueza de especies de plantas; Veg_heig. Altura de la vegetación.

RDA for the grass–dwelling spider assemblages also produced a significant ordination (p = 0.003 after 999 permutations; fig. 3B). The first two axes together explained 42.6% of the total variance, with the first axis alone explaining 39.0%. Similarly, the first axis separated the different plots along a plant diversity gradient. In addition, the vegetation height was a factor that displayed a very long arrow, showing its high importance in structuring grass–dwelling spider assemblages. Discussion Spider diversity in the fen The Shannon index values indicated that spider diver� sity varied greatly from one fen spot to the other for both the ground–dwelling and the grass–dwelling spiders. The reason for this variability could be related to the fact that the plant species diversity also varied considerably

between different parts of the fen. Apšuciems fen is visually a highly heterogeneous habitat that consists of a mosaic of different microhabitats where extremely poor vegetation patches (mainly consisting of Cladium mariscus) are scattered within very rich vegetation. Numerous studies have demonstrated that greater structural complexity of vegetation usually results in a higher diversity of spiders (Uetz, 1991; Jeanneret et al., 2003; Langellotto & Denno, 2004; Tews et al., 2004). The Shannon index also indicated that the ground–dwelling spider diversity in the Apšuciems fen was much higher than that of the grass–dwellers. As the Shannon diversity index combines evaluations of both species richness and evenness, such a low value of the Shannon index for the grass–dwelling spiders could be due to the considerably lower species richness of this group of spiders than that of ground–dwellers (only 25 species out of 80 were grass–dwellers), as well as the lower value of the evenness index (J = 0.68 for the grass–dwellers and J = 0.87 for the ground–dwellers). The evenness of the grass–dwelling spiders was low

230

because of the absolute dominance of a single spe� cies in the grass–layer —Dolomedes fimbriatus (family Pisauridae). Swampy areas are a typical habitat for D. fimbriatus (Roberts, 1996), and since it is a large spider (body length of a female can reach 20 mm), it may have a competitive advantage over other spiders that inhabit the same habitat stratum (Harwood et al., 2001). Besides, the differences in body size promote intraguild predation with the larger spider species of� ten being the intraguild predator (Samu et al., 1999; Patrick et al., 2012). Thus, the large body size of D. fimbriatus and the suitable conditions for this pisaurid in the fen could be the main reasons why this species has such a high abundance in the studied habitat. On the contrary, in the ground stratum the individuals were more evenly distributed among the different species (table 1). Most of the dominant ground–dwelling species belonged to the family Lycosidae�� , with �� the top–scor� ers being Trochosa terricola, Piratula hygrophilus and Hygrolycosa rubrofasciata. Other researchers that have studied spiders in wetland habitats have also observed that the Lycosidae family usually dominates in this type of habitat (Bultman, 1992; Koponen, 2003; Cummins, 2007). This might be explained by the fact that lycosids, similarly to pisaurids, are also often associated with water (Gertsch, 1979; Foelix, 2011). However, it has been argued that the prevalence of lycosids in the samples is probably because of the collecting method (pitfall traps) used. Pitfall traps are expected to differentially capture spiders with different activity, with the highly active groups (e.g., lycosids) being caught disproportionately more than the others (Bultman, 1992; Mallis & Hurd, 2005; Cummins, 2007). It has been shown that lycosids almost always dominate in the studies where pitfall trapping has been used, and no matter what kind of habitat the study has been carried out in (e.g., Corey et al., 1998; Mallis & Hurd, 2005; Fetykó, 2008; Kowal & Cartar, 2012). We also found many sporadic spider species in the Apšuciems fen. About 28% of all collected grass–dwelling spiders were represented by less than three individuals, while among the ground–dwelling spiders this number was considerably higher —63% of all ground–dwellers. This phenomenon has two possible, though not mutually exclusive, explanati� ons. The first explanation could be that our results simply confirm the widely observed pattern of spider community organization because many researchers have observed �� that spider communities characteris� tically contain comparatively few abundant species, and comparatively many rare species (Sørensen et al., 2002; Hsieh et al., 2003; Pinzon et al., 2012). An alternative explanation for such a large number of rare spider species in the Apšuciems fen might be related to the �� edge effect�� . �� The edge effect is remark� able in the Apšuciems fen because this fen occupies a relatively small area and also because of its close proximity to other habitat types (personal observation). It is known that edge effects in small habitats can alter the spider assemblage dramatically because spiders are known to be relatively effective dispersers. They can easily immigrate in the focal habitat by walking or ballooning (Gertsch, 1979; Bonte et al., 2011).

Štokmane & Spuņģis

For this reason, it would be valuable to sample the surrounding habitats in the future. We need to emphasize, however, that any compari� sons between the studied strata should be made with caution because we used two different methods to sample spiders —pitfall traps and a sweep net. These methods differ considerably in the overall sampling effort, i.e., pitfall trapping includes continuous sam� pling, while the duration of sweep–netting is usually much shorter. In the present study, the pitfall traps were operated approximately for a month, whereas the sweep–netting session was performed only once in that period. As local species richness may vary over time (Coddington et al., 1996), sweep netting may not represent the true species richness in the studied habitat. Besides, since the sweep netting in our study was carried out only during the daytime, it was restricted to diurnal spiders only (for example, families Pisauridae, Salticidae and Oxyopidae), while the pitfall traps collected both diurnally active spiders (Lycosidae and Zoridae) as well as nocturnally active ones (Gnaphosidae, Clubionidae and Liocranidae). It is well known that spiders exhibit both diurnal and nocturnal behavior (Canard, 1990; Roberts, 1996) because such differences in diel activity patterns decrease competition (Southwood, 1978; Otronen & Hanski, 1983). In fact, some authors have shown that spiders are generally more active by night than by day (Green, 1999; Cardoso et al., 2008) because predation pressure is lower at night (Coddington et al., 1991, 1996; Mestre et al., 2013), while in daytime, spiders are threatened by many visually hunting predators, especially birds, lizards, wasps and diurnal spiders (Foelix, 2011; Spiller & Schoener, 1998; Jones et al., 2011). This means it would be �� desirable�� to collect spi� ders in both periods, with the night collection perhaps being even more important than daytime collection. Vertical distribution patterns of spiders We compared the family, species and guild compo� sition of spiders in two different habitat strata —the ground–layer and the grass–layer. We found that spiders composition in each strata differed taxono� mically. There was a low species and even family (table 1; figs. 2A, 2B) overlap between the ground stratum and the grass stratum. In total, the ground– and the grass–layers shared only eight of 80 spider species. These results are in line with the findings of many other authors who have studied the vertical distribution of spiders and also observed that spiders tend to be stratified in the habitat (e.g., Turnbull, 1960; Culin & Rust, 1980; Stenchly et al., 2012; Pinzon et al., 2013). Moreover, studies indicate that spiders show species–level stratification not only in forested habitats (Brown, 2008; Pinzon et al., 2013) but also in open habitats (Kim et al., 1989; Pekár, 2005) even though these habitat types differ considerably in their vertical stratification. While forest habitats offer many different vertical strata for spiders (i.e., the litter layer, understory, upper canopy, overstory), non–forest ha� bitats exhibit little vertical stratification (Basset et al., 2003). Apparently, different spider species/families

Animal Biodiversity and Conservation 39.2 (2016)

are well adapted to living in a particular habitat layer. Horváth et al. (2009), for example, discovered that the large majority of diurnal spiders that hunt on flowers and other upper parts of the plant cannot survive in the lower strata. In contrast, most small spiders (e.g., linyphiids) usually live close to the ground (Balfour & Rypstra, 1998; Foelix, 2011). Such preferences for a certain stratum, however, are not surprising because different strata can provide very different microhabitats for spiders, i.e., each habitat stratum has its charac� teristic microclimatic conditions, different availability of appropriate substrate for foraging or web–building, and a different spectrum of prey animals (Turnbull, 1960; Abraham, 1983; Foelix, 2011). Studies have shown that spiders are extremely sensitive to the aforementioned factors, possibly explaining why �� dis� tinctive spider assemblages can establish between vertical strata (Oguri et al., 2014). Considering how spiders catch their prey, we di� vided our spider families into three functional groups or guilds: web spinners, sit–and–wait ambushers and active hunters. Our results showed that in spite of the great differences in family and species composition between the ground– and the grass–layer, the propor� tions of spider functional groups in both habitat layers were similar. In both strata, the sit–and–wait ambushers were the dominant spider guild regarding the number of individuals, while the web spinners dominated in both layers regarding the number of species (figs. 2C, 2D). We should stress, however, that these results could have differed if we had used a different spider guild classification. Spiders can generally be grouped into specific functional groups in many ways. For example, the division can be based on spider foraging strategy, habitat preferences, circadian activity, or prey range (�� Post & Riechert, 1977;�� Bultman et al., 1982; Whit� �� more et al., 2002; Cardoso et al., 2011). As a result, the number of recognized guilds varies. While some authors distinguish only two (Uetz, 1977) or three (Nyffeler, 1982) spider foraging guilds, others subdivide spiders into five (Gertsch, 1979; Young & Edwards, 1990), seven (Canard, 1990), eight (Riechert & Lockley, 1984; Uetz et al., 1999) and even 11 (Post & Riechert, 1977) different foraging guilds. The clearest distinction, however, is between web builders and wandering spi� ders (Uetz, 1977; Wise, 1995). These two spider guilds are ecologically different. Web builders are sedentary spiders that construct webs and thus feed mainly on moving prey, whereas wandering spiders are non–web– building predators that display a more mobile foraging strategy and thus feed on both moving and motionless prey (Nyffeler, 1999; Cobbold & MacMahon, 2012). We also used this basic and most stable division of spider guilds in the present study, however, we divided the wandering spiders into sit–and–wait ambushers and active hunters. This decision was based on the fact that the foraging strategy of sit–and–wait ambushers lies somewhere in the middle of the two basic guilds. Like active hunters, the sit–and–wait ambushers hunt without using webs, whereas like web builders, they do not actively pursue prey but wait for it to come to them (Wise, 1995). In any case, the results show that each habitat stratum is inhabited by several different guilds

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and not by a single guild. Such behavior is likely an adaptation to avoid competitive interactions, because since the 'foraging guild' is defined as a group of spe� cies using the same class of resources in a similar way, species belonging to the same guild are most likely to be competitors (Polis & McCormick, 1986; Uetz et al., 1999). This hypothesis was supported by Spiller (1984) and Herberstein (1998) who observed that mutually competing web builders construct their webs at different heights when occurring syntopically, but do not do so when one of the competititors is removed. Similarly, Enders (1974) stated that different orb–weaving spiders can co–exist in the same habitat only if they build their webs at different heights. The same can probably be applied to other (non–web–building) spider foraging guilds (Marc & Canard, 1997; Cardoso et al., 2011). Spider response to differences in vegetation structure In our study, spider abundance and species richness was positively associated with the plant species richness and plant diversity in the fen. Many other researchers have also observed that greater habitat complexity results in a higher abundance and diversity of spiders, because structurally more diverse habitats allow a greater niche diversification and coexistence of more spider species (Greenstone, 1984; Ryps� tra, 1986; Uetz, 1991; Langellotto & Denno, 2004). Overall, complex vegetation is beneficial for spiders in many ways. For example, one of the factors that explains spider distribution in the habitat is micro� climate (Turnbull, 1973; Tolbert, 1979), and since it is known that microclimate often correlates with the architecture of plants (Geiger, 1965; Hore & Uniyal, 2008), then there will be a greater variety of different microclimates if the habitat is more complex (Buch� holz, 2009). Moreover, the structural complexity within the habitat also provides a greater diversity of sites which can be used by spiders for resting, basking, sexual display, finding food, ovipositon or overwin� tering, and as an additional refuge from intraguild predation (Lawton, 1983; Halaj et al., 1998). And finally, the structural heterogeneity may also influence spider community structure indirectly via its influence on prey abundance and diversity, because typical prey species (such as herbivorous invertebrates) benefit from the greater variety of food resources available in more structurally diverse habitats (Nentwig, 1980; Siira–Pietikäinen et al., 2003). In contrast, vegetation height negatively influenced spider species richness and diversity. We also ob� served this in our previous research where we studied grass–dwelling spiders in several calcareous fens of the Coastal Lowland and concluded that higher vegetation has a significant negative effect on this group of spiders (Štokmane & Spuņģis, 2014). Again, we should emphasize that this is inconsistent with the findings of other authors who have shown that the number of spider species, as well as spider diversity, usually increase in accordance with the height of the herbaceous vegetation because higher vegetation is usually also more structured vertically (Greenstone, 1984; Mrzljak & Wiegleb, 2000; Harris et al., 2003).

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We think that one reason for this discrepancy could be related to the structural features of our studied fen habitats —the correlation analysis showed that fen places which were associated with taller vegetation were also associated with Phragmites australis (Štokmane & Spuņģis, 2014 and this study). P. australis is a typical expansive plant species which spreads very rapidly and forms monodominant stands, thereby simplifying the vegetation structure of the habitat (Auniņš et al., 2013). As a result, due to the lack of architectural diversity, spider species richness and diversity might also be low. Besides, P. australis creates shading, and thus the propor� tion of the photophilous spider species (e.g., Pirata uliginosus, Bathyphantes parvulus) can decrease (Štambuk & Erben, 2002). In their study, Buchholz & Schröder (2013) also found that spider assemblages of P. australis belts were less diverse than those of all other habitat types. They wrote that these outcomes can be related to fewer available niches (as a result of homogeneous reed belts) or to temporal flooding (which is common in reed belts). Our results showed that grass–dwelling spiders were generally more affected by the vegetation characteristics than ground–dwellers. We think that this could be explained by the fact that grass–dwell� ing spiders depend on vegetation to a larger degree than the ground–dwellers do. This is especially true when speaking about grass–dwellers that build webs (or so–called aerial web spinners, e.g., Araneidae, Theridiidae) because vegetation is their main sub� strate for web building (Whitmore et al., 2002), and a richly structured vegetation often ensures that a greater range of sizes and types of webs can be built (Greenstone, 1984; Uetz, 1991; Rypstra et al., 1999). Meanwhile, in contrast to aerial web spinners, web– spiders that generally live close to the ground (the so–called ground level web builders, e.g., Agelenidae, Linyphiidae, Hahniidae) use not only the vegetation as the web support structure but also several other structural aspects of the habitat, such as ground lit� ter, dirt or stones (Roberts, 1996; Balfour & Rypstra, 1998; Oxbrough et al., 2005). Distribution patterns of spider assemblages We described the patterns in spider species composi� tion across the fen using a redundancy analysis (RDA). The RDA showed that spider assemblages have a tendency to arrange in the ordination space according to habitat type. The differentiation of both the ground– and the grass–layer spider assemblage structure was determined mainly by the plant diversity gradient. Spider composition was highly dissimilar between the fen places with low plant species diversity and those places with high plant diversity. This corroborates the findings of many other authors who have also found that the type of vegetation has a great influence on the composition of spider assemblages, with different plant communities harbouring different associations of spiders (Muma, 1973; Gertsch & Riechert, 1976; Uetz, 1991; Buchholz, 2010; Torma et al., 2014). Thus, these results indicate that it is very important to maintain a

variety of habitat types within the focal habitat in order to enhance the spider biodiversity. The ordination analysis also revealed that while plant species richness and diversity appear to be a very important influencing factor for both ground– dwelling and grass–dwelling spider assemblages, some vegetation variables affected exclusively one or the other spider group. For instance, the variation in the ground–dwelling spider assemblage structure also seemed to be determined by the presence (or absence) of Scirpus tabernaemontani and the cover of mosses. These two factors were highly correlated with each other. It is therefore hard to say which of the two is more important for the ground–dwelling spiders in this study. However, the literature emphasizes the importance of mosses for some spider groups of the ground–layer, because m�� osses might serve as �� a re� fuge for particular ground–dwellers and they are also an important web attachment substrate for small web builders (e.g., Linyphiidae, Hahniidae) (Roberts, 1996; Harvey et al., 2002a; Jonsson, 2005). Meanwhile, an important factor that determined the structure of the grass–dwelling spider assemblages was vegetation height. We think that this outcome may be related to the �� differing biology of spider species, since dif� ferent species need specific vegetation heights. For instance, many of our collected grass–dwelling spiders (Evarcha arcuata, Oxyopes ramosus, Pachygnatha clercki, Sibianor aurocinctus) are usually associated with low vegetation (Locket & Millidge, 1951, 1953; Roberts, 1996; Harvey et al., 2002a, 2002b), while, for example, Araneus diadematus, which spins large orb webs, needs tall vegetation (Harvey et al., 2002b). Thereby, our results suggest that it would be advisable to maintain a mosaic of different vegetation heights in a habitat to ensure that the ecological needs of certain species are met and thus that the overall diversity of spiders is maximized. The main conclusions In conclusion, our findings show that �� the habitat sepa� ration of spiders in the Apšuciems fen seems to occur both vertically and horizontally. In our study, the spider assemblages of the ground–layer and the grass–layer were characterized by little similarity in species (and even family) composition. Apparently, most spider species are well adapted for a specific habitat stra� tum. In addition, our study showed that an important determinant of spider species richness and diversity in the fen was habitat diversity. The data indicated that structurally more diverse vegetation supports a higher number of spider species, which could be explained by a greater variety of available niches within a more complex vegetation. Overall, our results showed that since vegetation differed from one fen spot to the other, the spider composition was also highly dissimilar in different fen parts. Our results thus emphasize the importance of maintaining a mosaic–like pattern in the habitat, because different vegetation patches (e.g., a rich/poor vegetation, a tall/short vegetation) can provide habitat for very different spider assemblages and thus enhance the overall spider diversity.

Animal Biodiversity and Conservation 39.2 (2016)

Acknowledgments We would like to thank Andris Ziemelis and Agnese Žukova for their help in the field and Inese Cera for the verification of doubtful spider species. We also thank an anonymous referee for many valuable comments that improved an earlier version of the manuscript. The present study was supported by the project No. 09.1589 funded by the Latvian Council of Science 'Factors limiting diversity of animals in terrestrial ecosystems: interaction of natural and anthropogenic factors' and by the European Social Fund project (agreement No. 2009/0162/1DP/1.1.2.1.1/09/IPIA/ VIAA/004) 'Support for the implementation of master studies at the University of Latvia'. References Abraham, B. J., 1983. Spatial and temporal patterns in a sagebrush steppe spider community (Arach� nida: Araneae). Journal of Arachnology, 11: 31–50. Auniņš, A., Auniņa, L., Bambe, B., Eņģele, L., Ikau� niece, S., Kabucis, I., Laime, B., Lārmanis, V., Rēriha, I., Rove, I., Rūsiņa, S., Kretalova, R. S. & Strāķe, S., 2013. European Union protected habitats in Latvia: Interpretation manual. Latvian Fund for Nature, Riga. Balfour, R. A. & Rypstra, A. L., 1998. The influence of habitat structure on spider density in a no–till soybean agroecosystem. Journal of Arachnology, 26: 221–226. Basset, Y., Hammond, P. M., Barrios, H., Holloway, J. D. & Miller, S. E., 2003. Vertical stratification of arthropod assemblages. In: Arthropods of Tropical Forests: Spatio–Temporal Dynamics and Resource Use in the Canopy: 17–27 (Y. Basset, R. L. Kitch� ing, S. E. Miller & V. Novotny, Eds.). Cambridge University Press, Cambridge. Bonte, D., De Meester, N. & Matthysen, E., 2011. Selective integration advantages when transience is costly: immigration behaviour in an agrobiont spider. Animal Behaviour, 81: 837–841. Braun–Blanquet, J., 1964. Pflanzensoziologie: Grundzüge der Vegetationskunde. Springer–Verlag, Vienna. Brown, E., 2008. Vertical Distribution of Spiders (Araneae) on a Tropical Island. Independent Study Project (ISP) Collection, Paper 562: 1–30. Buchholz, S., 2009. Community structure of spiders in coastal habitats of a Mediterranean delta region (Nestos Delta, NE Greece). Animal Biodiversity and Conservation, 32.2: 101–115. – 2010. Ground spider assemblages as indicators for habitat structure in inland sand ecosystems. Biodiversity and Conservation, 19: 2565–2595. Buchholz, S. & Schröder, M., 2013. Diversity and ecology of spider assemblages of a Mediterra� nean wetland complex. Journal of Arachnology, 41: 364–373. Bultman, T. L., 1992. Abundance and Association of Cursorial Spiders from Calcareous fens in Southern Missouri. Journal of Arachnology, 20: 165–172.

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Animal Biodiversity and Conservation 39.2 (2016)

Brief communication

Comparison of the effectiveness of phalanges vs. humeri and femurs to estimate lizard age with skeletochronology M. Comas, S. Reguera, F. J. Zamora–Camacho, H. Salvadó & G. Moreno–Rueda Comas, M., Reguera, S., Zamora–Camacho, F. J., Salvadó, H. & Moreno–Rueda, G., 2016. Comparison of the effectiveness of phalanges vs. humeri and femurs to estimate lizard age with skeletochronology. Animal Biodiversity and Conservation, 39.2: 237–240. Abstract Comparison of the effectiveness of phalanges vs. humeri and femurs to estimate lizard age with skeletochronology.— Skeletochronology allows estimation of lizard age with a single capture (from a bone), making long–term monitoring unnecessary. Nevertheless, this method often involves the death of the animal to obtain the bone. We tested the reliability of skeletochronology of phalanges (which may be obtained without killing) by comparing the estimated age from femurs and humeri with the age estimated from phalanges. Our results show skeletochronology of phalanges is a reliable method to estimate age in lizards as cross–section readings from all bones studied presented a high correlation and repeatability regardless of the bone chosen. This approach provides an alternative to the killing of lizards for skeletochronology studies. Key words: Conservation, Demography, Growth, Population structure Resumen Comparación de la eficacia de las falanges respecto húmeros y fémures para la estimación de la edad en lagartijas mediante esqueletocronología.— La esqueletocronología permite estimar la edad de las lagartijas a partir de una sola captura (tomando una muestra de hueso), lo que hace innecesario un seguimiento a largo plazo. No obstante, los estudios esqueletocronológicos suelen implicar la muerte del animal para obtener el hueso. Nosotros probamos la fiabilidad de la esqueletocronología a partir de falanges (que pueden obtenerse sin matar al animal), comparando la edad estimada a partir de fémures y húmeros con la estimada a partir de falanges. Nuestros resultados muestran que la esqueletocronología de falanges es un método fiable para estimar la edad en lagartijas, ya que las lecturas de las secciones de todos los huesos estudiados presentaron una alta correlación y repetibilidad, independientemente del hueso escogido. Este método es una alternativa a la muerte del animal en estudios de esqueletocronología. Palabras clave: Conservación, Demografía, Crecimiento, Estructura poblacional Received: 3 IV 16; Conditional acceptance: 4 V 16; Final acceptance: 11 V 16 Mar Comas, Ecología Integrativa, Estación Biológica de Doñana (EBD–CSIC), Avda. Américo Vespucio s/n., Sevilla 41092, Spain.– Senda Reguera, Francisco J. Zamora–Camacho & Gregorio Moreno–Rueda, Depto. de Zoología, Fac. de Ciencias, Univ. de Granada, 18071 Granada, Spain.– Francisco J. Zamora–Camacho, Dept. of Biological Sciences, Dartmouth College, Hanover, New Hampshire, USA.– Humbert Salvadó, Lab. of Protistology, Depto. de Biologia Animal, Fac. de Biologia, Univ. de Barcelona, Avda. Diagonal 643, 08028 Barcelona, Spain. Corresponding author: Mar Comas. E–mail: mar.comas@ebd.csic.es

Introduction Demography studies, which require determination of the age of the animals studied, are fundamental in population ecology, in conservation biology and ISSN: 1578–665 X eISSN: 2014–928 X

in wildlife management. However, knowing the age of animals usually requires longitudinal studies, in which animals are captured and marked for long–term monitoring (Sutherland, 1997). Mark–recapture is a useful and precise method but it is time–consuming © 2016 Museu de Ciències Naturals de Barcelona

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and may be difficult in elusive species or those with high rates of movement. Moreover, marks may have negative consequences on individuals (Murray & Fuller, 2000). Alternative methods for mark–recapture are few. Nevertheless, some ectotherms with indeterminate growth may present a cyclic growth pattern in hard body structures, corresponding to alternate periods of growth and resting. In this way, age can be estimated by examining cyclic growth patterns in bones (Castanet, 1994). Femur and humerus are the most commonly used bones in reptile skeletochronology studies (Castanet, 1994). Their use, however, has the disadvantage that individuals must be dead or even specifically killed to obtain the bones, which, besides ethical concerns, precludes future studies or experiments with these specimens for which age has been estimated. Alternatively, researchers could use phalanges (easily obtained by toe clipping) to estimate age (e.g., Dubey et al., 2013). Clipping of one or two toes does not significantly reduce survival (Perry et al., 2011) and has no significant effects on key traits of animal behaviour, such as sprint speed (Husak, 2006). Therefore, estimating individual age with skeletochronology of phalanges would allow experimentation or future studies with animals of known age. In the present study, we examined the usefulness of phalanges to estimate age in reptiles in comparison with the use of the femurs and humeri. We used a collection of preserved individuals of the lizard Psammodromus algirus at the University of Granada (Spain). We estimated the age of these lizards using phalanges, humeri, and femurs, and compared the estimates made by the three types of bones. Material and methods Fourteen Psammodromus algirus from the scientific collection at the University of Granada were used for the skeletochronological analysis. No lizard was killed for this study. These lizards had died from natural causes while in captivity or by accident while handling during a longstanding study on this species (less than 1% of the lizards handled during the study died). Bodies were preserved in 70% ethanol. Later, long bones (femurs, humeri, and phalanges) were removed and age was estimated by means skeletochronology (Castanet & Smirina, 1990). We performed several trials to estimate the time needed for decalcification. Finally, the samples were decalcified in 3% nitric acid for at least three hours and 30 minutes. Although we used only one phalanx per lizard, the phalanx number was assigned at random in order to examine whether different phalanges are more or less suitable to estimate age. The basal and middle phalanges of each finger provide better resolution than does the most distal phalanx (Castanet & Smirina, 1990). Decalcified samples were conserved in PBS (phosphate–buffered saline) solution with sucrose (for cryoprotection) for at least 48 h at 4ºC, after which they were sectioned with the freezing microtome.

Comas et al.

Glass–slides were treated (prior to use) with a solution of glycerol (5 gr/L) and chromium (III) potassium sulphate (0.5 gr/L). Glycerol was used to improve the placing of the cross–sections on glass–slides. Chromium (III) potassium sulphate was used to improve sample conservation before applying the staining and fixation protocol. Glass slides were submerged for at least 5 minutes in glycerol–chromium (III) potassium sulphate solution and then oven dried for 24 h. The treated slides were then refrigerated until use. For cross–sections, samples were embedded in gel OCT (optimum cutting temperature) and then sectioned at 10–12 μm for phalanges and 14–30 μm for the longer bones, using a freezing microtome (CM1850 Leica) at the Centre of Scientific Instrumentation of the University of Granada. Cross–sections were stained with Harris hematoxylin for 20 minutes. The excess stain was then rinsed by washing the slides in tap water for 5 minutes. Later, stained sections were dehydrated with an alcohol series (70%, 96%, 100%; 5 min each), washed in xylol for 15 min, fixed with DPX (mounting medium for histology), and mounted on slides. Cross–sections were made and examined for the presence of LAGs using a light microscope (Leitz Dialux20) at magnifications from 50 to 125x. With a ProgresC3 camera, we took several photographs (a mean of 33.67 per individual) of various representative cross–sections, discarding those in which cuts were unsuitable for examining the LAGs. We selected diaphysis sections in which the size of the medullar cavity was at its minimum and that of the periosteal bone at its maximum (Castanet & Smirina, 1990). Because inferring age from the number of LAGs requires knowing the annual number of periods of arrested growth for each year, we compared our age estimates with juveniles, whose age was known to be less than a year. Multiple LAGs were found in juveniles in their first period of growth —which were counted as a single year—, while adults usually showed a single additional LAG per year. When various LAGs were found closely together, they were considered as a single LAG in order to avoid overestimation of age. A different LAG pattern depending on age may be explained by juvenile lizards usually being more active and showing more intermittent activity periods than adults (Carretero & Llorente, 1995). The number of LAGs detected in the periosteal bone was independently counted three times by the same person but on different occasions, always blindly regarding specimen identification (Sagor et al., 1998). Lizards were collected in summer. Therefore, LAGs deposited during previous winter hibernation were discernible from the outer edge of the bone. Consequently, the outer edge of the bone was not counted as a LAG. A Pearson’s correlation matrix was applied for the three age estimates and for each bone type. Repeatability (ri) was estimated using the formula ri = B / (B+W), where B is the variance between individuals and W is the variance within individuals, estimated from a one–way ANOVA (Senar, 1999).

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Table 1. Number of LAGs (age estimates) recorded from three readings (1, 2, and 3) of different limb bones: phalanx, femur, and humerus, of 14 individuals of Psammodromus algirus: ID. Identification code of each lizard. Tabla 1. Número de LAGs (líneas de detención del crecimiento; indicador de la edad estimada) a partir de tres lecturas (1, 2 y 3) de diferentes huesos de las extremidades: falange, fémur y húmero de 14 individuos de Psammodromus algirus: ID. Código de identificación de cada lagartija.

Phalanx

Femur

1 2 3

Humerus 1 2 3

Phalanx

Femur

4 4 4

ID 13104

1 2 3 5 5 5

1 2 3 – – –

10041

4 4 4

10032

3 3 3

Humerus 1 2 3 5 5 5

3 3 3

13151

3 3 3

– – –

3 3 3

1 1 1

10112

4 4 3

4 3 4

13155

10113

3 3 4

3 3 3

3 3 4

13156

1 1 1

– – –

1 1 1

2 2 2

10144

3 3 3

13158

10055

5 5 5

13119

2 2 2

– – –

2 2 2

5 5 5

12132

3 3 3

– – –

3 3 3

10051

5 5 5

Results

phalanx: ri = 0.982, F13, 28 = 112.8, P < 0.001; humerus: ri = 0.982, F13, 27 = 108.7, P < 0.001; femur: ri = 0.984, F9, 18 = 123.1, P < 0.001; all Pearson’s r > 0.93; table 1). In 12 lizards, age estimations were identical for all three readings and all bones studied (table 1; fig. 1).

In all lizards the number of LAGs remained almost identical for all limb bones analysed and between the three independent readings of the sections, independently of the phalanx number used (for

50 µm

Fig. 1. Cross–sections of the three long bones of the same individual: A. Femur; B. Humerus; and C. Phalanx, where five LAGs can be observed (ID number 10055). First LAGs near the marrow cavity correspond to first year of growth. (Photos: Mar Comas.) Fig. 1. Secciones transversales de los tres huesos largos del mismo individuo: A. Fémur; B. Húmero; C. Falange, donde pueden observarse cinco LAG (código de identificación: 10055). Las primeras LAG cerca de la cavidad de la médula ósea corresponden al primer año de crecimiento. (Fotografías: Mar Comas.)

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Discussion

References

Age estimated from the number of LAGs in all bones was identical in 85.7% of the lizards. Section readings from different bones presented a high correlation and repeatability, similar to that found in a previous study in Lacerta schreiberi (Luís et al., 2003). These findings confirm that skeletochronology of phalanges is a reliable method to estimate age in reptiles. Sections from humeri and phalanges were better than those from femurs; furthermore, in some individuals we were unable to obtain good sections from femurs because they were more difficult to cut. The fact that age was equally well estimated with any phalanx implies that the toe used is irrelevant. Nonetheless, we suggest avoiding clipping toes with special importance for animal movements, such as the longest toe. These results imply that killing lizards is unnecessary to perform skeletochronology, and support the use of phalanges for skeletochronology rather than bones that require the death of the animal, especially in the case of endangered species. The applications of this non–lethal approach in skeletochronology of phalanges in ecology and conservation biology are numerous and exceed those from skeletochronology implying the death of the specimen. For example, this method allows demographic studies with only one visit to the study area, making long–term studies unnecessary. This may fuel research programmes in areas of difficult access, where mark–recapture method would be ineffective. Skeletochronology of phalanges using this approach is a simple, economical, and ethical way to monitor herpetofauna. The application of skeletochronology of phalanges could also aid studies on age–related physiology, reproduction, and survival in reptiles, reducing disturbance to animals and providing an efficient and cheaper alternative to the mark–recapture approach with less impact on animals (Langkilde & Shine, 2006).

Carretero, M. A. & Llorente, G. A., 1995. Thermal and temporal patterns of two Mediterranean Lacertidae. In: Scientia herpetologica (Proceedings of the Seventh Ordinary General Meeting of the Societas Europaea Herpetologica): 213–223 (G. A. LLorente, A. Montori, X. Santos & M. A. Carretero, Eds.). Asociación Herpetológica Española, Barcelona. Castanet, J., 1994. Age estimation and longevity in reptiles. Gerontology, 40: 174–192. Castanet, J. & Smirina, E. M., 1990. Introduction to the skeletochronological method in amphibians and reptiles. Annales des Sciences Naturelles – Zoologie et Biologie Animale, 11: 191–196. Dubey, S., Sinsch, U., Dehling, M. J., Chevalley, M. & Shine, R., 2013. Population demography of an endangered lizard, the Blue Mountains Water Skink. BMC Ecology, 13: 4. Husak, J. F., 2006. Does survival depend on how fast you can run or how fast you do run? Functional Ecology, 20: 1080–1086. Langkilde, T. & Shine, R., 2006. How much stress do researchers inflict on their study animals? A case study using a scincid lizard, Eulamprus heatwolei. Journal of Experimental Biology, 209: 1035–1043. Luís, C., Rebelo, R., Brito, J. C., Godinho, R., Paulo, O. S. & Crespo, E. G., 2003. Age structure in Lacerta schreiberi from Portugal. Amphibia–Reptilia, 25: 336–343. Murray, D. L. & Fuller, R., 2000. A critical review of the effects of marking on the biology of vertebrates. In: Research Techniques in Animal Ecology: 15–64 (L. Boitani & T. K. Fuller, Eds.). Columbia University Press, New York. Perry, G., Wallace, M. C., Perry, D., Curzer, H. & Muhlberger, P., 2011. Toe clipping of amphibians and reptiles: science, ethics and the law. Journal of Herpetology 45: 547–555. Sagor, E. S., Ouellet, M., Barten, E. & Green, D. M., 1998. Skeletochronology and geographic variation in age structure in the wood frog, Rana sylvatica. Journal of Herpetology, 32: 469–474. Senar, J. C., 1999. La medición de la repetibilidad y el error de medida. Etologuía, 17: 53–64. Sutherland, W. J., 1997. Ecological Census Techniques. Cambridge University Press, Cambridge.

Acknowledgments We are grateful to Concepción Hernández, from the Centre of Scientific Instrumentation of the University of Granada, for her help with the freezing microtome. David Nesbitt improved the English. Comments by Rodrigo Megía and two anonymous referees improved the manuscript.

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Management reference for nature reserve networks based on MaxEnt modeling and gap analysis: a case study of the brown–eared pheasant in China

Y. Li, B. Cui, X. Qiu, C. Ding & I. Batool

Li, Y., Cui, B., Qiu, X., Ding, C. & Batool, I., 2016. Management reference for nature reserve networks based on MaxEnt modeling and gap analysis: a case study of the brown–eared pheasant in China. Animal Biodiversity and Conservation, 39.2: 241–252. Abstract Management reference for nature reserve networks based on MaxEnt modeling and gap analysis: a case study of the brown–eared pheasant in China.— Nature reserve designs and networks are important for wildlife and habitat conservation. Gap analyses are efficient and reliable tools for prioritizing habitat conservation efforts, especially when considering endangered species. We propose a conservation plan for the brown–eared pheasant, Crossoptilon mantchuricum, by identifying protection gap areas based on 14 existing nature reserves. A total of 45 locality sites and 11 environmental variables were selected according to the characteristics of habitat use of the brown–eared pheasant and applied to a maximum entropy (MaxEnt) model to obtain the species distribution. The MaxEnt model results showed a high prediction accuracy. The gap analysis results revealed that the Luliang Mountains in Shanxi and the Xiaowutai Mountains in Hebei had protection gaps. We found 458 km2 of optimum habitat and 1,390 km2 of moderately suitable habitat within the national nature reserve range. However, almost 1,861 km2 of the optimum habitat and 17,035 km2 of the moderately suitable habitat were unprotected, equivalent to 9.0% and 82.1%, respectively, of the total suitable habitat. Most of the unprotected area comprised moderately suitable habitat for brown–eared pheasant and should be prioritized in future conservation efforts. There are nine nature reserves along a north–to–south range in the Luliang Mountains that form a wildlife habitat corridor. To maintain the integrity, originality, and continuity of these habitats and thus protect brown–eared pheasants, local conservation departments should be strengthened to improve provincial nature reserve management and successfully carry out conservation efforts. Key words: Brown eared pheasant, GAP analysis, MaxEnt model, Nature reserves, Suitable habitat Resumen Referencia para la gestión de las redes de reservas naturales basada en la creación de modelos MaxEnt y el análisis de deficiencias: un estudio del faisán orejudo pardo en China.— La planificación de reservas naturales y la creación de redes son importantes para la conservación de los hábitats y la fauna silvestre. Los análisis de las deficiencias son instrumentos eficientes y fiables para establecer un orden de prioridad entre las iniciativas de conservación de hábitats, en especial por lo que respecta a las especies en peligro de extinción. Proponemos un plan de conservación para el faisán orejudo pardo, Crossoptilon mantchuricum, mediante la determinación de las zonas con una protección insuficiente en las 14 reservas naturales existentes. En total, se seleccionaron 45 localidades y 11 variables ambientales en función de las características del uso del hábitat del faisán orejudo pardo, y se utilizó un modelo de máxima entropía (MaxEnt) para obtener la distribución de la especie. Los resultados del modelo MaxEnt mostraron una elevada precisión de predicción. Los resultados del análisis de las deficiencias revelaron que en las montañas Luliang, en Shanxi, y las montañas Xiaowutai, en Hebei, la protección era insuficiente. Encontramos 458 km2 de hábitat óptimo y 1.390 km2 de hábitat moderadamente adecuado dentro de los límites de la reserva natural nacional. No obstante, casi 1.861 km2 del hábitat óptimo y 17.035 km2 del hábitat moderadamente adecuado no estaban protegidos, lo que equivale al 9,0% y el 82,1%, respectivamente, del hábitat adecuado total. La mayor parte de la superficie sin protección estaba formada por hábitat moderadamente adecuado para el faisán orejudo pardo y debería considerarse prioritaria en las iniciativas futuras de conservación. Hay nueve reservas naturales a lo largo ISSN: 1578–665 X eISSN: 2014–928 X

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de un eje norte–sur en las montañas Luliang que forma un pasillo ecológico. Para mantener la integridad, originalidad y continuidad de estos hábitats y, por tanto, proteger el faisán orejudo pardo, deberían reforzarse los departamentos locales de conservación con miras a mejorar la gestión de la reserva natural a escala provincial y poner en práctica eficazmente las iniciativas de conservación. Palabras clave: Faisán orejudo pardo, Análisis de deficiencias, Modelo MaxEnt, Reservas Naturales, Hábitat adecuado Reeceived: 11 IV 16; Conditional acceptance: 25 V 16; Final acceptance: 2 VI 16 Yilin Li, Xinyi Qiu, Changqing Ding, School of Nature Conservation, Beijing Forestry Univ., No. 35 Qinghua East Road, Haidian District, Beijing 100083, P. R. China.– Binbin Cui, Dept. of Biochemistry, Baoding Univ., No. 3027 Qiyi East Road, Lianchi District, Baoding, Hebei 071000, P. R. China.– Itrat Batool, Dept. of Biological Sciences, Beijing Forestry Univ., No. 35 Qinghua East Road, Haidian District, Beijing 100083, P. R.China. Corresponding author: Changqing Ding. E–mail: cqding@bjfu.edu.cn

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Introduction Nature reserves are used to protect populations and habitats of endangered species, such as the brown–eared pheasant, Crossoptilon mantchuricum. However, the home range of a species should not be restricted by reserve borders because nature reserves cannot encompass all suitable habitats. For example, Shota (2015) studied suitable habitats of the crested ibis, Nipponia nippon, which overlapped minimally with a conservation area on Sado Island. Moreover, some designated reserves cannot fully protect endangered species, although reserves should be accurate, efficient, and cost–effective (Prendergast et al., 1999). Therefore, habitat suitability should be evaluated before release because it is vital to planning more effective reserves (Shota et al., 2015). In addition, forecasting range shifts and suitable habitats for a species using various environmental factors can provide an invaluable reference for selecting protected areas and planning conservation (Hole et al., 2009). Species distribution models, such as maximum entropy (MaxEnt), random forest, and genetic algorithms for rule–set production models, are widely used to study conservation reserves. MaxEnt modeling uses presence–only occurrence and environmental data to predict suitable habitat of a particular species after assessing combinations of environmental variables and their interactions based on the maximum entropy principle (Phillips et al., 2006). MaxEnt modeling is currently one of the most commonly used models for probability–based predictions of suitable habitat distributions. Comparative studies have found that MaxEnt modeling is relatively good at predicting the potential distribution of a species and mapping areas that meet the environmental requirements (Elith et al., 2006). It has excellent performance and consistently outperforms many other methods, including GARP (genetic algorithm for rule–set production modeling), particularly when using sample sizes (Peterson, 2003). Gap analysis is relatively popular for evaluating reserves and biodiversity. It is useful for identifying sites that should be protected but that currently fall outside existing conservation networks (Burley, 1988). The ability to identify gaps in an existing reserve network is a simple and appealing concept in conservation management (Prendergast et al., 1999), and gap analysis provides a fast and comprehensive coarse–filtered approach to the protection and conservation of biodiversity (Scott et al., 1993). It uses geographic information system (GIS) technology to identify protection gaps in reserves and offers a powerful and efficient approach to managing reserves and practically guiding reserve selection (Prendergast et al., 1999). GIS is used for its ability to store thematic data layers and can perform complicated spatial analyses and overlap layers such as vegetation, elevation, and climate maps, which can be superimposed to conduct various spatial analyses (Scott et al., 1993). Therefore, areas of importance identified by gap analyses must be examined carefully for their biological qualities and management needs. Gap analysis also provides a quick assessment of vegetation that has already disappeared and associated

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species to provide focus for further biodiversity maintenance (Scott et al., 1993). GIS gap analysis models have been widely used to plan and evaluate animal diversity conservation and management (Edwards et al., 1996). Their rationale follows a conventional approach of selecting and reconfiguring reserves that can easily be adopted and used by conservation managers (Prendergast et al., 1999). The brown–eared pheasant is an endangered, mountain–dwelling pheasant endemic to China (Liu et al., 1991). It is listed as a vulnerable globally threatened species (IUCN, 2015). It is a typical mountain bird (Johnsgard, 1999) that inhabits coniferous and mixed coniferous–broadleaf forests (Li et al., 2010) at an altitude of 800 to 2,600 m (Xu et al., 1998; Pang et al., 2009; Zheng, 2015). Due to limited flight ability, wild pheasant populations depend on local areas for appropriate habitat. The brown–eared pheasant is found in three isolated populations: the western population in the Huanglong Mountains of Shaanxi, the central population in the Luliang Mountains of Shanxi, and the eastern population in the Xiaowutai Mountains of Hebei and Beijing (Zheng, 2015). Most endangered wildlife conservation is achieved via networks of protected areas in the form of reserves (Prendergast et al., 1999). Eight national nature reserves [Huanglong Shan (HLS), Hancheng (HC), Luya Shan (LYS), Pangquanguo (PQG), Wulu Shan (WLS), Heicha Shan (HCS), Xiaowutai Shan (XWTS), and Baihua Shan (BHS)] and six provincial nature reserves [Weifenhe (WFH), Lingjinggou (LJG), Fenheshangyou (FHSY), Yunding Shan (YDS), Xuegongling (XGL), and Jinhua Shan–Heng Lingzi (JHS–HLZ)] were instituted to protect the brown–eared pheasant and its suitable habitat. In this study, we used a MaxEnt model and GIS gap analysis of the existing reserve networks to assess conservation success, identify protection gaps, and provide advice to improve the protection of this rare and endangered species. Proper management of nature reserve design and networks is pivotal in population rehabilitation and habitat restoration. We addressed two important questions: (1) what are the current conservation achievements and are there protection gaps? and (2) how can protection gaps be addressed in future management plans for nature reserves? Material and methods Study area According to the Site Record Database for Chinese Galliformes (Zhang & Ding, 2007), the current distribution area of the wild brown–eared pheasant population was calculated using the minimum convex polygon method in ArcGIS ver. 10.0 (Esri, Redlands, CA, USA). This population is divided into three areas: the Huanglong Mountains in Shaanxi, the Luliang Mountains in Shanxi, and the joint region of the Xiaowutai Mountains in Hebei and Beijing. The brown–eared pheasant is non–migratory and has a dispersal distance of 5.7 km (Wang et al., 2006).

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The study area mapped out was 20 km and included its current distribution area (fig. 1). The reliability and accuracy of the model predictions should be improved when the model is extrapolated to a larger study area (Phillips, 2008; Phillips et al., 2009). We selected this research area to cover the potential range capacity and help identify potential habitats of this species. Distribution data sources The localities and distribution data of the brown–eared pheasant were obtained from the Site Record Database for Chinese Galliformes. We compared the geographic coordinates of these sites with modern occurrences in ArcGIS 10.0 (Xi’an 80 coordinate system). Long–term studies have been conducted on the brown–eared pheasant, and there is relatively sufficient information on its life history and biological needs (Li et al., 1990; Liu et al., 1991; Zhang et al., 2000). We selected 45 locality sites based on ecological and biogeographical features, including the vegetation and geomorphic preferences of this species, with the aim of predicting areas of suitable habitat similar to its actual niche. Environmental variable selection Biotic and abiotic factors, such as satellite–derived vegetation, geomorphic type, climate, and presence of roads and rivers, have been used in ecological models of species spatial distributions. In addition, researchers have investigated the effects of climate change on the suitable habitats of endangered species to develop a predictive distribution model using species distribution modeling (Li et al., 2010). We selected 11 environmental variables (vegetation, elevation, aspect, slope, maximum temperature of the warmest month, minimum temperature of the coldest month, annual mean temperature, annual precipitation, distance to the nearest river, distance to the nearest road, and distance to the nearest residential area) that influence the distribution of the brown–eared pheasant as the MaxEnt model environmental predictors of model habitat suitability (table 1). These environmental variables have been used to analyze the habitat choice of brown–eared pheasants in several studies (Li et al., 2009, 2012). The brown–eared pheasant is highly sensitive and vulnerable to climate change (Liu et al., 1991; Li et al., 2010). Climatic variables were presumed to effectively characterize the habitat suitability of the brown–eared pheasant across a large spatial scale. All environmental variables were recorded directly as quantitative data at a resolution of 2.5 arc/min. We extracted the attribute data of the environmental factors using ArcGIS 10.0 from 11 environmental layers. We used Student's t–test to evaluate significant differences among the 11 environmental factors in SPSS ver. 19.0 (IBM, Armonk, NY, USA). In addition, we used a recently developed modeling technique, TreeNet, in SPSS ver. 19.0 to assess major environmental preferences and authenticate the veracity of the suitable habitat predicted in MaxEnt Model ver. 3.3.

MaxEnt model Species distribution modeling can provide a measure of determining potential suitable habitats for species in study areas not covered by biological surveys (Corsi et al., 2000). MaxEnt modeling is a machine learning process that uses presence–only data (Rebelo & Jones, 2010) and environmental variables (Phillips et al., 2006), and it has become a convenient tool for conservation planning. Sample data should cover the ecological conditions throughout the range of a species (Wisz et al., 2008), but MaxEnt modeling has excellent predictive abilities with good accuracy using low sample sizes (Wisz et al., 2008). We used 45 sites for the presence data and 11 environmental variables for the predicted background in the MaxEnt model. In this experiment, we used 15 replicates. For each replicate we calibrated the model using a random sample of 75% of the modern distribution data for model training (n = 75); these data were evaluated against the remaining 25% for testing (n = 25) 10,000 randomly generated background points within the local range with a maximum of 5,000 iterations. We used two statistical analyses to quantify different aspects of the model’s performance (Elith & Graham, 2009). Omission and receiver operating characteristic plots with their respective areas under the curve (AUCs) are commonly used to measure the predictive performance of models (Pearce & Ferrier, 2000). The omission range is from 0 to 1, where lower omission values are indicative of higher prediction accuracies (Kang, 2010). As a threshold–independent method, the AUC ranges from 0 to 1, where 0.5 indicates randomness, 1 indicates perfect discrimination and 1.0 > AUC > 0.9 indicates very good predictive performance (Swets, 1988; Fielding & Bell, 1997). MaxEnt models produce a continuous raster with suitability values from 0 to 1 representing habitat suitability within the study area. Gap analysis The choice of threshold is important for ultimately determining protection gaps. The threshold should be defined based on the objectives of the model (Hernandez et al., 2006), while accounting for the precision and quality of the data (Rebelo & Jones, 2010). We required two threshold values to define the optimal, moderately suitable, and unsuitable habitat categories. MaxEnt modeling provides threshold values based on a variety of statistical measures. We plotted the logistic suitability output to place the limit for moderate suitability as the limit between the geometric and arithmetic increases. This threshold was used to define the minimum probability of suitable habitats and reclassify our model. We determined the limit for optimum suitability as the point at which suitability stabilized along the logistic curve. The suitability values were based on recent occurrence data. Using the species habits and characteristics, the purpose of the map was to differentiate between optimum habitat and moderately suitable habitat from total suitable habitat. From this,

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China

XWT–M Beijing

Shanxi TH–M

Shaanxi

Hebei LL–M

HL–M

TH–M

20 km buffer 100 km

Yellow River Mountains Study area Current distribution Provincial boundaries

High: 3,594 Low: 184

Fig. 1. Map of study area in China. Background data were based on the Spatial Distribution Map of Geomorphic Types in China (1:100,000) (Data Center for Resources and Environmental Sciences, Chinese Academy of Sciences–RESDC). The total study area comprised three areas: the Huanglong Mountains (HL–M) in Shaanxi, the Luliang Mountains (LL–M) in Shanxi, and the Xiaowutai Mountains (XWT–M) in Hebei and Beijing. TH–M indicates the Taihang Mountains. Fig. 1. Mapa de la zona de estudio en China. Los datos de referencia se basaron en el Mapa de distribución espacial de los tipos geomórficos en China (1:100.000) (Centro de datos para recursos y ciencias ambientales de la Academia China de Ciencias–RESDC). La superficie total de estudio estaba dividida en tres zonas: las montañas Huanglong (HL–M), en Shaanxi; las montañas Luliang (LL–M), en Shanxi; y las montañas Xiaowutai (XWT–M), en Hebei y Beijing. TH–M indica las montañas Taihang.

we defined three levels of habitat suitability: optimum habitat, moderately suitable habitat, and unsuitable habitat. We identified protection gaps by overlaying the habitat suitability and nature reserve layers in ArcGIS 10.0. Suitable habitats located outside the nature reserves were defined as protection gaps. The boundary map of the national nature reserves was obtained from the College of Nature Conservation at Beijing Forestry University, and detailed information was downloaded from the Ministry of Environmental Protection of the People's Republic of China (table 2). The locations of the six provincial nature reserves were labeled due to their unclear boundaries. The total size of these six provincial nature reserves was approximately 1,457.56 km2 based on information provided by Ministry of Environmental Protection of the People’s Republic of China. Results Model performance and evaluation The ecological niche of a species is determined by numerous biotic and abiotic factors. The t–test results showed that all 11 environmental variables differed significantly (P < 0.001) among the 45 sites

(table 3). The 45 sample sites represented different habitat conditions of the brown–eared pheasant. We gave full consideration to the 11 environmental backgrounds in the MaxEnt model, which allowed the model to acquire accurate suitable habitats to evaluate habitat preference. The suitable habitat distribution determined from this model therefore tended to be more complete than the TreeNet model. TreeNet and MaxEnt predicted that the habitat preference of the brown–eared pheasant was coniferous and mixed coniferous–broadleaf forests with gentle slopes on sunny south–facing aspects at high altitudes (table 4). The results of both models were similar, although they had levels of success in evaluating the range of suitable climate and distances differed. The TreeNet model yielded a conservative estimate of the optimum temperature of −15°C to 36°C independent of rainfall. In addition, the brown–eared pheasant preferred habitats far from residential areas and roads, and rarely depended on rivers. The MaxEnt model was robust in selecting the preference range, with a temperature range of −20°C to 35°C, and a closer distance to rivers, roads, and residential areas of > 0.5 km. These habitat preferences are in agreement with the known ecological characteristics of the brown–eared pheasant.

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Table 1. The sources of environmental variables used for modelling habitat suitability for the brown– eared pheasant. Aspect definition: 360 degrees divided into eight pieces, each 45 degrees: north, 0–22.5º and 337.5º–360º; northeast, 22.5º–67.5º; east, 67.5º–112.5º; southeast,112.5º–157.5º; south, 157.5–202.5º; southwest, 202.5º–247.5º; west, 247.5º–292.5º; northwest, 292.5º–337.5º, respectively. Tabla 1. Fuentes de variables ambientales utilizadas para establecer el modelo de idoneidad del hábitat para el faisán orejudo pardo. Definición de aspecto: 360 grados divididos en ocho partes, cada una de 45 grados: norte, 0º–22,5º y 337,5º–360º; noreste, 22,5º–67,5º; este, 67,5º–112,5º; sudeste,112,5º–157,5º; sur, 157,5º–202,5º; sudoeste, 202,5º–247,5º; oeste, 247,5º–292,5º; noroeste, 292,5º–337,5º, respectivamente.

Environmental variables Layer Website Unit Vegetation China vegetation type http://www.resdc.cn Dimensionless spatial distribution map Elevation Spatial distribution map m of geomorphic types in China Aspect º Slope gradient º Maximum temperature WorldClim (1950–2000) http:// www.worldclim.org ºC of the warmest month Minimum temperature ºC of the coldest month Annual means temperature ºC Annual precipitation mm Distance to nearest river China pyatyi river map http://www.webmap.cn/ km Distance to nearest road China road map km Distance to nearest China county level km residential area administrative region map

The MaxEnt model was accurate in predicting the ecological niche of the brown–eared pheasant even though we included only 45 samples. All of the training omission indexes were < 0.10, and all of the test omission indexes were < 0.35 (table 5). These values indicate that the MaxEnt model has very high prediction accuracy. The AUC results revealed a training average AUC of 0.9575, a test average AUC of 0.8985, and an AUC standard deviation of 0.0406, indicative of good model prediction performance (table 6).The MaxEnt model predicted a continuous raster from 0.00 to 0.94 that represented a suitable brown–eared pheasant habitat, shown as the green area in figure 2, which was mainly located in the Luliang Mountains in Shanxi and the Xiaowutai Mountains in Hebei. The results included a large area of suitable habitat that extended beyond its known distribution. Gap analysis of the protection area Considering that the evaluation index was dependent on the defined threshold, we selected a 10th percentile training presence logistic threshold (0.30) and habitat suitability probability (0.70) to divide the three habitat suitability grades: optimum habitat (0.94–0.70), moderately suitable habitat (0.70–0.30), and unsuitable habitat (0.30–0.00) (fig. 2).

Using ArcGIS 10.0, we found that the suitable habitat range of the brown–eared pheasant across the whole study area covered approximately 20,744 km2, with an optimum habitat area of 2,319 km2 and a moderately suitable habitat area of 18,425 km2. The optimum and moderately suitable habitats were mainly distributed throughout the Luliang Mountains in Shanxi and Xiaowutai Mountains in Hebei. These suitable habitats were continuously distributed throughout the study areas of Shanxi and Hebei–Beijing. While some of the suitable habitat area was protected by the eight national and six provincial nature reserves, large portions were not protected; we classified these as protection gaps. The gap analysis revealed large protection gap areas in the Luliang Mountains of Shanxi and the Xiaowutai Mountains of Hebei inside the study area. Furthermore, there were large areas of suitable habitat distributed in the north (Shuozhou), northeast (Wutai), and central (Qinyuan) areas of Shanxi outside the study area, as well as some suitable habitat scattered throughout Hebei. A network of eight national nature reserves was instituted to protect the brown–eared pheasant and its habitat in the total study area (2,640.45 km2), including four reserves in Shanxi, two reserves in Shaanxi, one reserve in Hebei, and one reserve in Beijing. From our analysis, this network contained

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Table 2. List detailing information for eight national nature reserves (the data source was the Ministry of Environmental Protection of the People’s Republic of China). Tabla 2. Lista con información detallada sobre ocho reservas naturales nacionales (la fuente de datos fue el Ministerio de Protección Ambiental de la República Popular de China).

Nature reserve

Area (km2)

Protection object

Huanglong Shan, HLS

817.53

Brown–eared pheasant and its habitats

Hancheng, HC

604.39

Brown–eared pheasant and its habitats

Luya Shan, LYS

214.53

Brown–eared pheasant, larch (Larix principis–rupprechtii Mayr.) and spruce (Picea asperata Mast.)

Pangquangou, PQG

104.66

Brown–eared pheasant, larch (Larix principis–rupprechtii Mayr.) and spruce (Picea asperata Mast.)

Wulu Shan, WLS

206.17

Brown–eared pheasant and its habitats

Heicha Shan, HCS

257.41

Forest ecosystems and brown–eared pheasant

Xiaowutai Shan, XWTS

218.33

Temperate zone forest ecosystems and brown–eared pheasant

Baihua Shan, BHS

217.43

Temperate zone secondary forest

approximately 458 km2 of optimum habitat and 1,390 km2 of moderately suitable habitat, equivalent to only 2.2% and 6.7% of the total suitable habitat area. There was an area of 1,861 km2 of optimum habitat and 17,035 km2 of moderately suitable habitat, equivalent to 9.0% and 82.1% of the total suitable habitat area, located outside the reserves, which should be considered for protection. Moderately suitable habitat should be the main target for protecting currently unprotected areas. Discussion Reserve networks There are 37 national nature reserves in Shaanxi, Shanxi, Hebei, and Beijing, including 16 reserves in Shaanxi, seven reserves in Shanxi, 12 reserves in Hebei, and two reserves in Beijing. These national nature reserves were instituted to protect different forest types and wildlife. Only eight of these national nature reserves were established to protect the brown–eared pheasant. Four national nature reserves (HLS, HC, XWTS, and BHS) are located in Shaanxi, Hebei and Beijing, and they have a total area of 1,857.68 km2. We found that HLS and HC covered the entire suitable habitat of the western brown–eared pheasant population in Shaanxi, while XWTS and BHS covered a large portion of the suitable habitat of the eastern population in Hebei–Beijing (fig. 2). Seven national nature reserves are located in Shanxi (LYS, PQG, HCS, WLS, Lishan Reserve [LS], Lingkong Shan Reserve [LKS], and Yangcheng Mang River Macaque Reserve [YCMR]), four of which (LYS, PQG, HCS, and WLS) were established to protect the brown–eared pheasant and

its habitat. In the study area, these reserves had an area of 782.77 km2, which covered a small fraction of the suitable habitat of the central population in Shanxi. The other three national nature reserves (LS, LKS, and YCMR) were established to protect other forests and wildlife outside the study area. A total of 101 provincial nature reserves have been created to protect forest ecosystems and wildlife, including 31 reserves in Shaanxi, 39 reserves in Shanxi, 19 reserves in Hebei, and 12 reserves in Beijing. Eleven of these are located in the study area: nine in Shanxi, one in Beijing, and one in Hebei. However, only six provincial nature reserves were developed to protect the brown–eared pheasant and its habitat in the study area. Except for JHS–HLZ in Hebei, the others (WFH, LJG, FHSY, YDS, and XGL) are located in Shanxi. Although these provincial nature reserves lack clear boundaries and ideal regulations, they contribute to protecting the habitat of the brown–eared pheasant. The impact of environmental variables on brown– eared pheasant distribution The brown–eared pheasant is a forest–dependent species. It mainly feeds on tender roots, stems, leaves, seeds, and fruits (Lu & Liu, 1983). It does not exist outside forests and it inhabits different forests at different elevations depending on the season (Liu et al., 1991). The breeding season lasts from March to July, when the it inhabits the slopes of mixed coniferous–broadleaf forest zones. When the temperature increases in summer, family flocks move to coniferous forests at higher elevations. In autumn and winter, they move to lower altitudes to inhabit sheltered slopes in broad–leaved forest belts. The life history of the brown–eared pheasant determines its choice of altitude and vegetation zone. Overall, this species

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Table 3. The t–tests of environmental variables. Eleven environmental variables showed high statistical significance (P < 0.001) between 45 sites. Tabla 3. Las pruebas de la t de las variables ambientales. Once variables ambientales mostraron una significación estadística elevada (P < 0,001) entre 45 sitios.

Environmental variables

Vegetation

32.931

0.000

Elevation

33.962

0.000

Aspect

12.534

0.000

Slope

10.205

0.000

Maximum temperature

118.775 0.000

Minimum temperature

–17.026 0.000

Annual means temperature

29.495

0.000

Annual precipitation

27.296

0.000

Distance to nearest river

10.226

0.000

Distance to nearest road

14.881

0.000

Distance to nearest residential area

12.384

0.000

prefers coniferous and mixed coniferous–broadleaf forests with gentle slopes and sunny south–facing aspects at high altitudes.

Nests and eggs in these forests are destroyed due to grazing by animals and mushroom foraging by local villagers. This directly reduces the reproductive success of the brown–eared pheasant (Zhang & Zhang, 2001). Residential areas with more roads and human interference have forced brown–eared pheasant populations to move to areas with less human interference (Zhang et al., 2004). Brown–eared pheasants usually avoid or cross roads very quickly when they are encountered. Roads do not hinder their movement, but reduce habitat connectivity and canopy density. The risk of becoming prey is higher around motorways (Zhang & Zhang, 2001); therefore, brown–eared pheasants primarily avoid residential areas and roads that are characterized by greater human disturbance. The brown–eared pheasant is sensitive and vulnerable to climate change (Liu et al., 1991, Li et al., 2010), and temperature and precipitation are important factors in habitat selection. Temperature directly affects its growth, development, reproduction, metabolism, and other life activities (Liu et al., 1991). Brown–eared pheasants choose suitable habitats, avoid adverse environments at different temperatures, and move up or down elevations and slopes with seasonal changes. The brown–eared pheasant lives in semi–arid areas. Precipitation indirectly affects the species’ life activities through its effects on vegetation. Excessive rainfall, snowfall, and low temperatures affect the species’ survival, especially influencing breeding and reducing its reproductive success (Liu et al., 1991). The brown–eared pheasant feeds more on fruits and leaves in the spring and summer, while it plucks snow off the ground in the winter and occasionally drinks stream water in the fall when passing mountain springs and streams. Habitats close to rivers offer relatively few refuge areas and have relatively high predation

Table 4. The habitat preference of brown–eared pheasant compared between MaxEnt and TreeNet models. Tabla 4. Comparación de la preferencia de hábitat del faisán orejudo pardo entre los modelos MaxEnt y TreeNet.

Environmental variables

MaxEnt

TreeNet

Vegetation

Coniferous and mixed

coniferous–broadleaf forests

Elevation

1,500–2,600 m

1,600–2,100 m

Aspect

Southwest

South–southwest

Slope

> 10º

6–16º

Maximum temperature

35ºC

35–36ºC

Minimum temperature

> –20ºC

>–15ºC

Annual means temperature

10–11ºC

6–9ºC

Annual precipitation

100–200 mm

100–300 mm

Distance to nearest river

> 0.7 km

1.5–1.7 km

Distance to nearest road

> 0.5 km

> 0.6 km

Distance to nearest residential area

> 0.65 km

> 0.4 km

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Table 5. Omission indexes of training and test of MaxEnt model.

Table 6. The AUC values of prediction by MaxEnt model repeated 15 times: SD. Standard deviation.

Tabla 5. Tasas de omisión de capacitación y prueba del modelo MaxEnt.

Tabla 6. Los valores del AUC (área bajo la curva) de la predicción realizada con el modelo MaxEnt se repitieron 15 veces: SD. Desviación estándar.

Indexes Minimum training presence

Training

Test

0.0000

0.1185

Training

Test

10% training presence

0.0741

0.3037

0.9571

0.877

0.0527

Equal training sensitivity

0.0963

0.3333

0.9475

0.9437

0.0147

0.9508

0.9404

0.0202

0.0592

0.1555

0.9574

0.9062

0.0299

0.9548

0.9304

0.0162

Maximum training sensitivity 0.0691

0.3259

0.96

0.8794

0.0595

0.9612

0.8802

0.0449

0.9589

0.9155

0.0434

0.9511

0.933

0.0177

0.9737

0.805

0.0618

0.9543

0.9144

0.0466

0.9585

0.8914

0.0549

0.9588

0.8755

0.055

0.9588

0.9176

0.0282

0.9601

0.868

0.0636

Averages

0.9575

0.8985

0.0406

and specificity Equal test sensitivity and specificity plus specificity Maximum test sensitivity

0.0617

0.0889

plus specificity

risks. Based on the habitat preference analysis, the brown–eared pheasant has little dependence on rivers. Pheasants tend to choose suitable habitats and avoid adverse environments to improve their chance of survival, and anthropogenic factors and natural conditions determine their distribution. Reserves have been instituted to protect endangered species and their habitats, but the conservation achievements of many of these reserves have been limited. Few reserves or networks have been designed or established using reserve selection and design techniques (Pressey, 1994) before allocating and protecting the land for conservation. This means that reserves designated for certain species may not fully overlap with the species’ distribution, resulting in protection gaps. Protection gaps and conservation implications The predicted results of the MaxEnt model were similar to the actual ecological niche of the brown–eared pheasant based on the studied environmental preferences. The results of the gap analysis indicated that only 8.9% of the suitable habitat of the brown–eared pheasant is protected by the current eight national nature reserves. The model identified 18,896 km2 of suitable habitat outside the protected reserves, of which 9.0% was optimum habitat and 82.1% was moderately suitable habitat. The geographical distribution of a species can be limited by factors that fall outside the scope of their optimum habitat, such as limited dispersal abilities, geographical barriers, and predators. Therefore, otherwise moderately suitable habitat may become necessary for the survival of a species. Since moderately suitable habitats constituted the majority of the protection gap areas in our study area, future conservation plans should consider this gap to improve brown–eared pheasant protection efforts.

The current distribution range of the brown–eared pheasant is segregated into three geographical populations: the western, central, and eastern populations. The western population in HLS in Shaanxi is located to the west of the Yellow River, while the central population in the Luliang Mountains in Shanxi is located to the east of the Yellow River. The eastern population in Hebei–Beijing is an isolated island on the east side of the Taihang Mountains (TH–M). The current distribution forms discontinuous islands (Zheng, 2015). Habitat continuity has been highlighted as a biodiversity conservation priority to improve the integrity and vulnerability of a species, which should be prioritized when planning nature reserves (Ginsberg, 1999; Prendergast et al., 1999). However, it is not feasible to connect the three isolated brown– eared pheasant populations. The most practicable conservation measure would be to identify areas of suitable habitat outside the existing nature reserves and improve conservation management by creating additional protected areas in these gaps to increase the integrity and consistency of conservation of each population. Based on our analysis, the optimum habitats of the brown–eared pheasant were located in the north and east of LYS, northeast of PQG, and north of WLS. The YDS Provincial Nature Reserve is east of the PQG National Nature Reserve (fig. 2). These two reserves

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Locality sites Provincial nature reserve National nature reserve Optimum habitat Moderate suitable habitat Unsuitable habitat

Shanxi

WFH

Shaanxi

LYS

HCS FHSY LJG YDS PQG XGL WLS

HLS

XWTS

Beijing

BHS JHS–HLZ

Hebei

LKS LS

YCMR 100 km

Fig. 2. Protection gap and grade distribution map of habitat suitability produced by the MaxEnt model and ArcGIS ver. 10.0. The green area represents the suitable habitat of the brown–eared pheasant, which covers most of its current distribution area. Large areas distributed in the north (Shuozhou), northeast (Wutai), and central (Qinyuan) areas of Shanxi fell outside the study area. The eight national nature reserves inside the study area were HLS, HC, LYS, PQG, WLS, HCS, XWTS, and BHS. The three national nature reserves outside the study area were LKS, LS, and YCMR. The six provincial nature reserves were WFH, LJG, FHSY, YDS, XGL, and JHS–HLZ. Fig. 2. Mapa de las zonas sin protección y la distribución de los grados de idoneidad del hábitat, producido por el modelo MaxEnt y ArcGIS ver. 10.0. La superficie verde representa el hábitat adecuado del faisán orejudo pardo, que abarca la mayor parte de su área de distribución actual. Las extensas zonas distribuidas en el norte (Shuozhou), el noreste (Wutai) y las áreas centrales de Shanxi (Qinyuan) estaban fuera de la zona de estudio. Las ocho reservas naturales nacionales dentro de la zona de estudio eran HLS, HC, LYS, PQG, WLS, HCS, XWTS y BHS. Las tres reservas naturales nacionales fuera de la zona de estudio eran LKS, LS y YCMR. Las seis reservas naturales provinciales eran WFH, LJG, FHSY, YDS, XGL y JHS–HLZ.

are roughly connected and cover a large area of suitable habitat. Reserve networks must be configured to optimize their conservation potential (Prendergast et al., 1999), and expanding the current reserves is both necessary and feasible. We suggest that the protected area should be extended to include suitable habitat within 15 km northeast of LYS and 16 km north of WLS to improve current conservation efforts for the brown–eared pheasant. Suitable habitat in the Luliang Mountains of Shanxi is almost continuously distributed (fig. 2). Five provincial nature reserves (WFH, LJG, FHSY, YDS, and XGL) are located among the four national nature reserves (LYS, PQG, WLS, and HCS). These provincial nature reserves are crucial to link protected habitats, especially FHSY and XGL, which are located in a narrow band of suitable habitat. The nine reserves are distributed from north to south in the Luliang Mountains, forming a wildlife habitat corridor that supports population dispersion and gene exchange within the central brown–eared pheasant population.

Well–designed boundaries and effective management systems are important for constructing provincial nature reserves. To maintain the integrity and continuity of suitable brown–eared pheasant habitat, local conservation departments should strengthen and improve their management of provincial nature reserves to optimize conservation effects. In addition, the organizational structure of provincial reserves should be clarified, including boundary confirmation, the institution of regular monitoring patrols, and implementation and improvement of habitat protection. In particular, it is essential to maintain local ecological wildlife corridors to sustainably develop the region. The Luliang Mountains are the main distribution area of the brown–eared pheasant. Although there are four national nature reserves and five provincial nature reserves in this area, a large area of suitable habitat remains unprotected. To ensure the stable development and continued growth of the brown–eared pheasant, protection measures against deforestation are urgently required to protect its suitable habitat, such as prohibiting logging in the Luliang mountains.

Animal Biodiversity and Conservation 39.2 (2016)

Furthermore, some suitable habitat is located in the north (Shuozhou) and central (Qinyuan) areas of Shanxi outside the study area. The brown–eared pheasant historically inhabited Qinyuan County (He & He, 1990; Liu et al., 1991), and this area should be considered for reintroduction to help rejuvenate the population of this endangered species. The protection gap area in the eastern population in Hebei–Beijing is continuous (fig. 2), with suitable habitat fragments in 10– to 24–km intervals. Two national nature reserves (XWTS and BHS) and one provincial nature reserve (JHS–HLZ) form a close triangle. This region has dense vegetation cover and little human disturbance due to bans on hunting, logging, and travel to maintain the integrity and connectivity of suitable habitat and ensure genetic exchange between the brown–eared pheasant populations in Hebei and Beijing. Implementing further protections in this area is feasible. Since the 1980s, the Chinese government has initiated large–scale tree planting, reforestation, and nature reserve programs to improve the survival rates of species that rely on forest landscapes, such as the brown–eared pheasant. In this study area, two counties (Laiyuan and Laishui) in Hebei Province and five counties (Yangqu, Loufan, Jixian, Xingxian, and Shilou) and two districts (Lishi and Xinfu) in Shanxi Province have provincial nature reserves to protect local forest and wetland ecosystems, as well as larch, Larix principis–rupprechtii Mayr., and pine, Pinus tabuliformis, forests and local wildlife. Ten provincial nature reserves [Tianlongshan (TLS, outside the study area), Yunzhongshan (YZS), Hejiashan (HJS), Renzushan (RZS), Tuanyuanshan (TYS), LJG, FHSY, YDS, XGL, and WFH] were created to protect the brown–eared pheasant and forest ecosystems in Shanxi. Only five of the provincial nature reserves (LJG, FHSY, YDS, XGL, and WFH) covered some of the suitable habitat in our study area, offering limited protection of suitable brown–eared pheasant habitat. We found that the western and eastern population habitats were better protected than the central population, and the suitable habitat of the central population in Shanxi urgently requires further protection. Brown–eared pheasant populations in nature reserves are stable and even increasing (Zheng, 2015). However, outside reserves, habitat loss and degradation due to urban development (Zheng, 2015) is the main cause of their decline. Therefore, it is crucial to strengthen the protection and management of suitable habitats outside nature reserves. Our models identified previously unknown protection gaps and determined good candidate areas for additional conservation. If conservation planners predict suitable habitat before designing reserves, give full consideration to the integrity and continuity of suitable habitat, and cover a relatively reasonable habitat range when planning nature reserves, then more suitable brown–eared pheasant habitat can be protected. In addition, the protection and management of provincial and other nature reserves are crucial for promoting steady brown–eared pheasant population growth. Our results may encourage conservation managers to use distribution modeling before beginning nature reserve construction projects (Hernandez et

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Animal Biodiversity and Conservation 39.2 (2016)

Animal Biodiversity and Conservation

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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.

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Animal Biodiversity and Conservation 39.2 (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.

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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 39.2 (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 39.2 (2016)

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Animal Biodiversity and Conservation 39.2 (2016)

Arxius de Miscel·lània Zoològica vol. 13 (2015) Museu de Ciències Naturals de Barcelona ISSN: 1698–0476 www.amz.museucienciesjournals.cat

Índex / Índice / Contents Gili, C., 2015. Revision of the Nassariidae (Gastropoda, Neogastropoda) of the malacological collection of the Museu de Ciències Naturals de Barcelona. Arxius de Miscel·lània Zoològica, 13: 1–24. Abstract Revision of the Nassariidae (Gastropoda, Neogastropoda) of the malacological collection of the Museu de Ciències Naturals de Barcelona.— The entire set of samples of the Nassariidae integrated in the malacological collection of the Museu de Ciències Naturals de Barcelona has been reviewed. For all the samples, the number of individuals has been counted, each shell has been revised individually, and the taxonomic determination has been corrected in those cases in which it seemed justified, updating the nomenclature. For those samples containing a mixture of different species, new samples have been created so that each sample contained a single species. Regardless of the annotated in the original labels, one biogeographical region has been assigned to each sample. Finally, the Nassariidae collection has been valuated as a whole regarding the number of samples, the number of species and its geographical distribution. Key words: Nassariidae, Taxonomic revision, Biogeography Martínez–Ortí, A., Bargues, M. D. & Mas–Coma, S., 2015. Dos nuevas localizaciones para España de Bulinus truncatus (Audouin, 1827) (Gastropoda, Planorbidae), hospedador intermediario de Schistosomiasis urinaria. Arxius de Miscel·lània Zoològica, 13: 25–31. Abstract Two new locations inSpain of Bulinus truncatus (Audouin, 1827) (Gastropoda, Planorbidae), intermediate host of urinary Schistosomiasis.— Two new populations of the planorbid snail species Bulinus truncatus were found in Spain in 2014. The first consisted only of shells in the lagoon of Villena (province of Alicante), which had dried up at the beginning of the 19th century. This finding is of important biogeographic interest because it links the presence of this species in northern Catalonia with its detection in southern Andalucia as this species has not been found previously either in Murcia or in the Valencian Community. The second population was found in El Ejido (province of Almeria), and thousands of living specimens were found here. This allowed a complete shell characterisation and molecular assessment by means of sequencing the cox1 gene of the mitochondrial DNA genome, which showed 100% homology with sequences of other populations of the same snail species available in the GenBank. The finding of B. truncatus in Almeria is of additional value given the applied importance of this planorbid species as a vector of urinary Schistosomiasis and hence representing a risk of disease introduction and autochthonous transmission in Spain, as has occurred in other southern European countries in the past and recently. Key words: Bulinus truncatus, Planorbidae, Urinary Schistosomiasis, cox1, Alicante, Almería, España Data paper Semprucci, F. & Balsamo, M., 2015. Checklist of free–living nematode species in the transitional environment of Lake Varano (Southern Italy). Arxius de Miscel·lània Zoològica, 13: 32–46. Abstract Checklist of free–living nematode species in the transitional environment of Lake Varano (Southern Italy).— This study documents for the first time the taxonomic composition of the nematode community and the number of free–living nematode species in Lake Varano, Southern Adriatic Sea, Italy. The nematode community was mainly composed of species typical of fine sediments that usually prevail in transitional environments (TEs). An overall ISSN: 1578–665 X eISSN: 2014–928 X

Animal Biodiversity and Conservation 39.2 (2016)

high number of nematode species was recorded (55), belonging to 36 genera in 17 families. These values are highly comparable to those reported for other Italian TEs, but appear lower than those recorded in other European brackish–water systems, probably in relation to the low salinity range of Lake Varano. Forty taxa were identified up to species level, thus increasing the number of the nematode marine species known for the Italian coasts from 443 to 463, for the Adriatic basin from 310 to 313, and for the Southern Adriatic sector from 37 to 77. Considering the importance of this phylum in the assessment of ecological quality and the great vulnerability of the Adriatic Sea ecosystems, an intensification of sampling efforts should be planned, especially in the Central–Southern part of the basin. Such a plan would provide new insights into the biogeography of one of the most important components of the benthic domain and potentially yield new information about the climate warming effects on the Adriatic Sea. Key words: Free–living nematodes, Biodiversity, Transitional environments, Southern Adriatic Sea Del Moral–Flores, L. F., Morrone, J. J., Alcocer Durand, J., Espinosa–Pérez, H. & Pérez–Ponce De León, G., 2015. Listado anotado de los tiburones, rayas y quimeras (Chondrichthyes, Elasmobranchii, Holocephali) de México. Arxius de Miscel·lània Zoològica, 13: 47–163. Abstract Checklist of sharks, rays and chimaeras (Chondrichthyes, Elasmobranchii, Holocephali) from Mexico.— We present an annotated checklist of the species of sharks, rays and chimaeras (chondrichthyan fishes) occurring in Mexican waters, based on a thorough review of the literature and electronic database searches, examination of museum collection specimens, and unpublished records obtained during fieldwork conducted in the last four years. The checklist contains information of at least 214 species of chondrichthyan fishes that occur in Mexican marine and brackish waters, assigned to 84 genera, 40 families and 14 orders. It includes eight species of chimaeras, 95 batoids and 111 sharks. Condrichthyan fauna in Mexico is one of the richest in the world, with almost 17.3% of the known species. An additional 16 species are included as their occurrence in Mexican marine waters is probable according to distributional patterns. Key words: Chondrichthyes, Elasmobranchs, Batoids, Chimaeras, Mexico III Encuentro Ibérico de Biología Subterránea Prieto, M., Agulló, J., Fadrique, F. & Masó, G., 2015. Coleópteros hipogeos protegidos o que requieren medidas de conservación en Cataluña. Arxius de Miscel·lània Zoològica, 13: 164–188. Abstract Hypogean beetles that are protected or that require conservation measures in Catalonia.— Hypogean species are characterized by their profound adaptations to the adverse conditions of their subterranean habitats. Such specialization, however, makes them particularly vulnerable to alterations in their habitat. In the Autonomous Community of Catalonia several legislative tools have been developed to protect threatened invertebrates, and most beetle species included in Decree 328/1992 protecting Areas of Natural Interest in Catalonia (PEIN) or considered in the future decree on the protection of Catalan invertebrates (CFAC) are linked to subterranean habitats. In the present revision we compile regulations and other documents relating to the protection of beetle hypogean fauna in Catalonia. We provide updated faunistic and biogeographic data as well as information on the conservation status of the species, most of which are endemisms confined to a small area. Some of these species have been monitored in recent years by the Arthropod Department of the Natural Sciences Museum of Barcelona (in collaboration with the Catalan Biospeleology Association) and the results of these studies are briefly discussed. Key words: Hypogean coleoptera, Biodiversity, Endemicity, Protected species, Conservation, Subterranean environment, Catalonia

ISSN: 1578–665 X eISSN: 2014–928 X

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 39.2 (2016) ISSN 1578–665 X eISSN 2014–928 X 147–154 Rodríguez, S., Álvarez, E. & Barba, E. Factors affecting fledgling output of great tits, Parus major, in the long term 155–160 Brief communication González–Desales, G. A., Monroy–Vilchis, O., Charruau, P. & Zarco–González, M. M. Aspectos ecológicos de la anidación de Caiman crocodilus chiapasius (Bocourt, 1876) en la reserva de la biosfera La Encrucijada, México 161–171 Tonelli, M., Agoglitta, R., Dawson, H. & Zunino, M. On the road of dung: hypothetical dispersal routes of dung beetles in the circum–Sicilian volcanic islands 173–184 Flores–Peredo, R. & Bolívar Cimé, B. S. Pine seed predation by mice: an experimental assessment of preference 185–193 Cornejo–Ortega, J. L., Chávez–Dagostino, R. M. & Cupul–Magaña, F. G. Éxito reproductivo de los pájaros bobos patas azul, Sula nebouxii, y los pájaros bobos café, Sula leucogaster, como indicador de perturbación por uso turístico en las Islas Marietas, México 195–198 Brief communication Rubio, C. J., Macías, D., Camiñas, J. A., Fernández, I. L. & Báez, J. C. Effects of the North Atlantic Oscillation on Spanish catches of albacore, Thunnus alalunga, and yellowfin tuna, Thunnus albacares, in the North–east Atlantic Ocean

199–205 Forum Gippoliti, S. Questioning current practice in brown bear, Ursus arctos, conservation in Europe that undervalues taxonomy 207–219 Rummel, L., Martínez–Abraín, A., Mayol, J., Ruiz– Olmo, J., Mañas, F., Jiménez, J., Gómez, J. A. & Oro, D. Use of wild–caught individuals as a key factor for success in vertebrate translocations 221–236 Štokmane, M. & Spuņģis, V. The influence of vegetation structure on spider species richness, diversity and community organization in the Apšuciems calcareous fen, Latvia 237–240 Brief communication Comas, M., Reguera, S., Zamora–Camacho, F. J., Salvadó, H. & Moreno–Rueda, G. Comparison of the effectiveness of phalanges vs. humeri and femurs to estimate lizard age with skeletochronology 241–252 Li, Y., Cui, B., Qiu, X., Ding, C. & Batool, I. Management reference for nature reserve networks based on MaxEnt modeling and gap analysis: a case study of the brown–eared pheasant in China IX–X Abstracts del volum 13 (2015) d'Arxius de Miscel·lània Zoològica Abstracts del volumen 13 (2015) de Arxius de Miscel·lània Zoològica Abstracts of volume 13 (2015) of Arxius de Miscel·lània Zoològica

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