Animal Biodiversity and Conservation issue 33.1 (2010)

Formerly Miscel·lània Zoològica

2010

and

Animal Biodiversity Conservation 33.1

Dibuix de la coberta:

de Jordi Domènech.

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de redacció / Secretaría de redacción / Editorial Office

Secretària de redacció / Secretaria de redacción / Managing Editor Montserrat Ferrer

Museu de Ciències Naturals Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail abc@bcn.cat

Consell assessor / Consejo asesor / Advisory Board Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

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, Portugal Xavier Bellés Centre d' Investigació i Desenvolupament–CSIC, Barcelona, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Michael J. Conroy Univ. of Georgia, Athens, USA Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Ignacio Doadrio Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain José Antonio Donazar Estación Biológica de Doñana–CSIC, Sevilla, Spain Gary D. Grossman Univ. of Georgia, Athens, USA Damià Jaume IMEDEA–CSIC, Univ. de les Illes Balears, Spain Jordi Lleonart Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Jorge M. Lobo Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Pablo J. López–González Univ de Sevilla, Sevilla, Spain Juan José 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 Javier Perez–Barberia The Macaulay Institute, Scotland, United Kingdom 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 CSIC–UPF, Barcelona, Spain Pedro Rincón Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain Alfredo Salvador Museo Nacional de Ciencias Naturales–CSIC, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Ciències Naturals de Barcelona, Barcelona, Spain Carles Vilà Estación Biológica de Doñana–CSIC, Sevilla, Spain Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana–CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle–CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Jersey, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana–CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Barcelona, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 33.1, 2010 © 2010 Museu de Ciències Naturals, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: S. A. de Litografías ISSN: 1578–665X Dipòsit legal: B–16.278–58 The journal is freely available online at: http://w3.bcn.es/V62/Home/V62XMLHomeLinkPl/0,4388,418159056_418911616_1,00.html

Animal Biodiversity and Conservation 33.1 (2010)

1

Relative abundance of amphibians in forest canopy gaps of natural origin vs. timber harvest origin C. A. Strojny & M. L. Hunter, Jr.

Strojny, C. A. & Hunter, M. L., Jr., 2010. Relative abundance of amphibians in forest canopy gaps of natural origin vs. timber harvest origin. Animal Biodiversity and Conservation, 33.1: 1–13.

Abstract Relative abundance of amphibians in forest canopy gaps of natural origin vs. timber harvest origin.— Small–scale canopy gaps created by logging may retain adequate habitat structure to maintain amphibian abundance. We used pitfalls with drift fences to measure relative abundance of amphibians in 44 harvested gaps, 19 natural treefall gaps, and 36 closed–canopy forest plots. Metamorphs had relatively lower capture rates in large harvest gaps for Ambystoma maculatum, Lithobates catesbeianus, L. clamitans, and L. sylvaticus but we did not detect statistically significant (p < 0.1) differences among gap types for Lithobates palustris metamorphs. L. clamitans juveniles and L. sylvaticus juveniles and adults had relatively lower capture rates in large harvest gaps. For juvenile–adult A. maculatum, we caught relatively fewer individuals in all gap types than in closed–canopy areas. Some groups with overall lower capture rates (immature Plethodon cinereus, juvenile L. palustris) had mixed differences among gap types, and Notophthalmus viridescens (efts) and adult P. cinereus showed no differences among gap types. One species, L. clamitans, was captured more often at gap edges than gap centers. These results suggest that harvest gaps, especially small gaps, provided habitat similar to natural gaps for some, but not all, amphibian species or life–stages.

Key words: Amphibians, Forest management, Canopy gaps, Natural disturbance, Irregular group shelterwood.

Resumen Abundancia relativa de anfibios en los claros de origen natural del dosel forestal frente a las claros producidos por la explotación forestal.— Los claros a pequeña escala producidos en el dosel forestal por la industria maderera pueden conservar una estructura del hábitat apropiada para mantener la abundancia de anfibios. Utilizamos trampas con vallas de intercepción para medir la abundancia relativa de anfibios en 44 claros en que la madera había sido cortada, 19 claros naturales producidos por la caída de los árboles, y 36 zonas de dosel cerrado. Para Ambystoma maculatum, Lithobates catesbeianus L. clamitans y L. sylvaticus las tasas de captura son relativamente bajas en los claros de tala grandes para los metamorfos, pero no detectamos diferencias estadísticamente significativas (p < 0,1) entre los tipos de claros para los metamorfos de Lithobates palustris. Los juveniles de L. clamitans y los juveniles y adultos de L. sylvaticus dieron unas tasas de captura relativamente inferiores en los claros de tala grandes. Para los juveniles–adultos de A. maculatum, capturamos relativamente menos individuos en todos los tipos de claros que en las zonas boscosas cerradas. Algunos grupos con tasas de captura general inferiores (inmaduros de Plethodon cinereus, juveniles de L. palustris), presentaban diferencias mixtas entre los tipos de claros, y Notophthalmus viridescens (fase inmadura terrestre) y los adultos de P. cinereus no presentaban diferencias entre los distintos tipos de claros. Una especie, L. clamitans, fue capturada más a menudo en los bordes de los claros que en sus centros. Estos resultados sugieren que los claros producidos por la industria maderera, y especialmente los más pequeños, proporcionaban un hábitat similar a los claros naturales para algunas, pero no todas, las especies o las fases vitales de los anfibios.

Palabras clave: Anfibios, Gestión forestal, Claros del dosel, Perturbación natural, Clareo sucesivo uniforme de grupos irregulares.

(Received: 27 V 09; Conditional acceptance: 27 VII 09; Final acceptance: 30 XI 09) Carol A. Strojny & Malcolm L. Hunter, Jr., Dept. of Wildlife Ecology, 5755 Nutting Hall, Univ. of Maine, Orono, ME 04469, USA. ISSN: 1578–665X

© 2010 Museu de Ciències Naturals

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Introduction Timber harvests designed to emulate the structural changes that result from natural disturbances may facilitate meeting both biological conservation and timber production goals (Seymour & Hunter, 1999; Perera et al., 2004). This concept assumes that native species have adapted to natural disturbance patterns and therefore will be less adversely affected by human–induced disturbances if they are modeled after natural disturbance regimes. In the forests of northeastern North America, small–scale canopy gaps are a common form of natural disturbance (Lorimer, 1977; Runkle, 1991; Rogers, 1996; Seymour et al., 2002). The Acadian Forest Ecosystem Research Program of the University of Maine, USA implemented a harvesting regime designed to emulate natural canopy gaps in a mixed coniferous–deciduous forest.

Some harvesting methods, notably clearcuts, often negatively affect amphibian populations (Ash, 1997; DeMaynadier & Hunter, 1998; Harpole & Haas, 1999; Chan–McLeod, 2003; Renken et al., 2004; Semlitsch et al., 2009). In a review of 18 independent studies, DeMaynadier & Hunter (1995) found amphibian abundance to be 3.5 times greater in mature forest sites than in clearcut sites. Furthermore, research in an Appalachian hardwood forest showed that terrestrial salamander abundance decreased after group selection, shelterwood, and leave–tree harvests as well as clearcuts (Harpole & Haas, 1999; Knapp et al., 2003; Homyack & Haas, 2009). In contrast, some studies that examined effects of small–scale canopy gap disturbances did not detect differences in relative abundances of red–backed salamanders (Plethodon cinereus) (Messere & Ducey, 1998; McKenny et al., 2006) or frogs and salamanders (Greenberg, 2001).

To better understand the ecological effects of harvest origin gaps created to emulate natural disturbance, we investigated forest amphibians in harvest and natural canopy gaps in a mixed forest in central Maine, USA. Specifically, we: 1) compared relative abundance of forest amphibians within harvest–created gaps to determine if location (gap center, edge, north and south aspect) influenced amphibian distributions; and 2) compared relative amphibian abundance among harvest and natural canopy gaps, using adjacent closed–canopy forest as reference plots.

Material and methods Study area and experimental treatments We conducted our research at the Penobscot Experimental Forest (PEF) in Penobscot County, Maine, USA. The PEF encompasses 1,540 hectares of predominately mixed coniferous–deciduous forest. Dominant tree species are Tsuga canadensis, Acer rubrum, Pinus strobus, Thuja occidentalis, Abies balsamea, Betula papyrifera, Picea rubens, Populus tremuloides, P. grandidentata, and A. saccharum. We conducted our research within nine, approximately 10–ha, research

Strojny & Hunter

areas of mature forest in the PEF. The harvest origin gaps under study are in six research areas that were harvested between 1995 and 1997. Most harvests were completed by manual felling, delimbing, and topping with chainsaws at the stump. We sampled forest amphibians in the nine research areas, where each research area contained a certain type of canopy gap treatment: three research areas had a combined total of 22 large harvest gaps (1,328 ± 113 m2; mean ± 1 SE), three had a combined total of 22 small harvest gaps (674 ± 65 m2), and three had a combined total of 19 natural canopy gaps (249 ± 28 m2). Large gaps were created by removing approximately 20% of the canopy within the 10 ha stand, resulting in seven to eight gaps per research area (irregular group shelterwoods with reserves). Small gap harvests removed approximately 10% of the canopy within the stand, creating seven to eight gaps per research area (selection harvests). In the unharvested research areas, natural gaps were defined by any area where at least two tree falls or stem breaks of canopy trees ≥ 25 cm in diameter created a gap, exposing understory stems to the sky (Runkle, 1991). Basal area of reserve trees (unharvested trees within gaps) was lowest in large harvest gaps (11 m2/ha), and greater in small harvest gaps (14 m2/ha) and natural gaps (24 m2/ha) (Schofield, 2003). We also sampled forest amphibians in 36 closed–canopy plots (four plots per research area) located between the gaps. The basal area of closed–canopy areas averaged 32 m2/ha (Schofield, 2003). These plots were used to test for spatial independence and to control for some of the natural variability among the nine research areas.

Vegetative patterns among harvest gaps, natural gaps, and closed–canopy forest areas were described four years post–harvest by Schofield (2003).

Total cover for herbs, shrubs, seedlings, saplings, and ferns was highest (34.9%) in harvest gaps, 25.5% in natural gaps, and 10.6% in closed–canopy plots. In the larger harvest gaps (1,170–2,106 m2), gap centers had greater herbaceous and shrub cover than edges. Natural gaps tended to have more conifer regeneration, lichens, and mosses while harvest gaps had more hardwood regeneration, shrubs, and herbaceous cover. Coarse Woody Debris (CWD) characteristics were compared before and after harvests for each treatment at the stand level (Fraver et al., 2002). Research areas with large harvest gaps had the greatest increase in volume and abundance of small–diameter CWD, with less of an increase in small–gap research areas and the least increase in natural–gap research areas.

The proportion of well–decayed CWD to total CWD decreased following harvests because the harvests generated fresh, undecayed CWD. Amphibian sampling We sampled amphibians using pitfall traps with drift fences (pitfall arrays) from 10 V–26 VII and 4 IX–23 X in 2002, and 22 IV–25 X in 2003. Traps in all plots were monitored one to two times per week throughout these periods. The temporary closure in 2002 was

Animal Biodiversity and Conservation 33.1 (2010)

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A

B

Gap edge

North

Center

South

Drift fence Pitfall

Fig. 1. Diagram of the arrangement of pitfalls with drift fences (arrays) in harvested and natural gaps, where most gaps had 3 arrays (A) and a subset had arrays along the entire north–south transect to test for differences in capture rates within the gap (B).

Fig. 1. Diagrama de la disposición de las trampas de intercepción dotadas de valla de deriva en los claros de tala y naturales; en la mayoría de los claros existían 3 dispositivos (A) y cada subconjunto tenía dispositivos a lo largo de todo su transecto norte–sur, para estudiar las diferencias en las tasas de captura dentro del claro (B).

implemented due to hot and dry conditions in late July and August of 2002. Pitfall traps were constructed from two #10 aluminum cans taped end–to–end (36 cm deep), buried in the ground at each end of a 3–m long by 0.5–m high plastic fence buried into the ground. Moss placed in the bottom of the traps provided shelter to amphibians from dry conditions and predators (Enge, 2001). Plastic funnels in the pitfall traps were used to prevent the escape of amphibians that are able to climb the sides. The diameter of the base of these funnels was 12–14 cm. Sticks (< 1.5 cm diameter) were placed in pitfall traps to facilitate escape of shrews and mice as recommended

by Perkins & Hunter (2002).

To study how treatment differences influenced relative amphibian abundance, each canopy gap had three pitfall arrays: 5 m south of the plot center, at center, and 5 m north of the center (fig. 1a). Closed canopy plots also had three arrays. To study how location within a gap was correlated with relative amphibian abundance, a subsample of the gaps (11 large gaps, 12 small gaps, and seven natural gaps) were randomly selected to have pitfall arrays positioned every 5 m along the entire north–south transect of each gap (fig. 1b). All pitfall arrays were randomly oriented in one of the following directions: north–south, northeast–southwest, northwest–southeast, east–west.

Amphibians were captured, measured from snout to anterior end of the vent in length (SVL­), and released 6–10 m east or west of the trap. During 2002, we marked amphibians with a visible implant elastomer tag under the skin (Davis & Ovaska, 2001; Bailey, 2004); however, very low recapture rates (< 0.4%) did not warrant repeating this procedure in 2003.

Data analysis Amphibian abundance was measured by the number of captures per 100 trap nights (TN), with one trap night for every night an individual pitfall was open. Habitat selection of amphibians varies both interspecifically (Stebbins & Cohen, 1995; DeMaynadier & Hunter, 1998) and intraspecificallly (i.e. among life stages) (DeMaynadier & Hunter, 1999; Rothermel & Semlitch, 2002). Therefore, we calculated capture rates for each individual species, and for age–classes of spotted salamanders (Ambystoma maculatum), red–backed salamanders, bullfrogs (Lithobates catesbeianus), green frogs (L. clamitans), pickerel frogs (L. palustris), and wood frogs (L. sylvaticus) (Strojny, 2004). Data from 2002 and 2003 were analyzed independently because of different sampling periods.

Relative abundance within gaps To test for differences in capture rates between 1) northern and southern areas of the gaps, and 2) edges and center areas of the gaps, we calculated probabilities using BLOSSOM’S (Midcontinent Ecological Science Center, U. S. Geological Survey) multiple response permutation procedures (MRPP) for paired samples, with a probability value < 0.1 considered significant (Cade & Richards, 1999). We analyzed the 11 largest gaps because they represented the most extreme canopy removal conditions with the greatest likelihood of detecting differences in relative amphibian abundance.

We only analyzed species that occurred in all 11 gaps.

For comparisons between northern and southern areas within a gap, we measured capture rates for the three northern–most and three southern–most pitfall arrays.

For comparisons of edges and centers of gaps, we were

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concerned that aspect may obfuscate edge effects, so we combined captures for the northern–most and southern–most pitfall arrays to represent edge capture rates. Then we combined captures for the two middle pitfall arrays to derive gap–center capture rates. For each replicate, there was at least 10 m between center and edge pitfall arrays within the gap.

Relative abundance among gap types In comparing treatment types (large gap, small gap, natural gap), analyses were only conducted on species and age–classes of species that were detected in all nine research areas (table 1). We combined all captures to calculate rates for each plot type (gap or closed–canopy) based on each plot’s sampling effort.

In order to use individual gaps as the experimental units to compare gap types, we took two measures to guard against confounding factors such as spatial autocorrelation and natural variation among research areas. First we used an analysis of variance (ANOVA) to test for differences in amphibian abundance among the closed–canopy plots for each treatment, using the research areas as the units of replication.

A difference would indicate a potential site–related bias on all plots within one or more of the research areas. From this test, juvenile bullfrogs in 2003 were excluded from analyses due to a higher capture rate in closed–canopy plots of the large–gap treatment (F–ratio2,6 = 6.01; p = 0.04). Second, to account for natural variation, our response variable was calculated as follows: for each research area, the mean capture rate of the four closed–canopy plots was subtracted from each gap capture rate value (for gaps in that same research area) to derive a "difference value".

Therefore, all values reported for gap type are in reference to capture rates of the closed–canopy plots in the same research area, to decrease the likelihood of site–specific effects biasing results. This method is limited in precision because there were only four closed–canopy plots and the method does not account for the variability among them.

We used SYSTAT’s (ANOVA) tool to test for treatment effects on ranks of the difference values at the α = 0.1 level. All pairwise comparisons for treatment differences were made using Tukey’s multiple comparison procedure. We estimated 90% confidence intervals around the difference value medians of each treatment with a bootstrapping procedure, sampling 5,000 times with replacement (SYSTAT) to compare and contrast treatments. Sign tests were used to determine if capture rates in gaps were significantly (α < 0.1) less than zero. We also compared difference values of harvest gaps (n = 10) that occurred within the size range of natural gaps (n = 19). Because of unequal sample sizes and variation, this test was done with BLOSSOM’s MRPP as a nonparametric equivalent of the classical t–test (Cade & Richards, 1999).

Results Eleven species were caught in 2002, for a total of 2,930 captures in 98,457 TN (2.98 captures per 100 TN)

Strojny & Hunter

(table 1). In 2003, we captured 9,069 amphibians representing 12 species over 152,597 TN (5.94 captures per 100 TN).

Relative abundance within gaps Location within gaps (north vs. south or edge vs. center) had no effect on relative amphibian abundance, except for green frogs (appendix 1).

Mean green frog capture rates were higher at gap edges (2.52 captures/100 TN) than in gap centers (1.74 captures/100 TN) (p = 0.02 in 2003; n = 11).

Patterns in 2002 were consistent with those of 2003 although we did not analyze wood frogs and red–backed salamanders due to sample limitations.

In 2002, mean green frog capture rates were also higher at edges (1.05 captures/100 TN) than gap centers (0.61 captures/100 TN) (p = 0.05; n = 11).

Because of the within–gap patterns for green frogs, subsequent analyses of their distributions only used data from the center three pitfall arrays of these 11 large gaps.

Relative abundance among gap types For the following comparisons, when capture rates in gaps were less than the capture rate means of the associated closed–canopy sites (i.e., difference values were negative) we refer to this as lower abundance within gaps. Conversely, when capture rates in gaps were higher than the associated closed–canopy plot means (i.e., positive difference values), we refer to this as higher abundance.

In 2003, gap type had statistically significant effects on relative abundance in six of seven anuran groups: bullfrog metamorphs, juvenile pickerel frogs, and juvenile and metamorph groups of green frogs and wood frogs (table 2; appendix 2). Three metamorph groups (bullfrogs, green frogs, and wood frogs) showed the lowest relative abundance within large gaps. Bullfrog and green frog metamorph abundances were low in small gaps as well, and relatively high within natural gaps. Abundance values for small and natural gaps were similar for juvenile–adult and metamorph wood frogs, and juveniles of pickerel frogs and green frogs. Of five anuran groups tested in 2002, we detected treatment differences for green frog metamorphs (lowest abundance in the large gap treatment) and wood frog metamorphs (natural gap treatment showed reduced abundance and no change within harvested treatments) (table 3).

Two of five salamander groups showed treatment differences in 2003: spotted salamander metamorphs and immature red–backed salamanders (table 2; appendix 2). For spotted salamander metamorphs, both large and small harvest gaps showed low abundance while natural gaps showed similar abundance to closed–canopy plots. For immature red–backed salamanders, abundance was relatively high in small gaps and relatively low in large gaps, and natural gap treatment values overlapped with both large and small gap treatments. No differences among gap types were

Animal Biodiversity and Conservation 33.1 (2010)

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Table 1. Counts of amphibian species and their age–classes captured in the Penobscot Experimental Forest, Maine, in 2002 and 2003: a Numbers in parentheses did not occur in all nine research areas and were not included in analyses; b Sampling period in 2002: 10 V–26 VII and 4 IX–23 X; c Sampling period in 2003: 22 IV–25 X. Tabla 1. Recuento de las especies de anfibios y de sus clases de edad, capturados en el Bosque Experimental de Penobscot, Maine, en 2002 y 2003: ª Los números entre paréntesis no se dieron en la totalidad de las nueve áreas de investigación, y no se incluyeron en los análisis; b Período de muestreo en el 2002: 10 V–26 VII and 4 IX–23 X; c Período de muestreo en el 2003: 22 IV–25 X.

Countsa

Species

2002

Blue–spotted Salamander (Ambystoma laterale)

(21)

(75)

Spotted Salamander (A. maculatum)

712

2,252

b

2003c

Juveniles and adults

381

901

Metamorphs

331

1,350

Eastern Newt (efts only) (Notophthalmus viridescens)

501

1,363

Four–toed Salamander (Hemidactylium scutatum)

(0)

(2)

Eastern Red–backed Salamander (Plethodon cinereus)

163

687

116

522

Adults

46

162

American Toad (Anaxyrus americanus)

Immatures

(1)

(1)

American Bullfrog (Lithobates catesbeianus)

198

554

Adults

(2)

(6)

Juveniles

128

273

Metamorphs

68

273

Green Frog (Lithobates clamitans)

875

2,528

Adults

(0)

(8)

Juveniles

(64)

141

Metamorphs

804

2,359

Pickerel Frog (Lithobates palustris)

144

353

Adults

(4)

(4)

Juveniles

(21)

61

Metamorphs

(116)

281

Northern Leopard Frog (Lithobates pipiens)

(41)

(278)

Mink Frog (Lithobates septentrionalis)

(63)

(66)

Wood Frog (Lithobates sylvaticus)

209

910

Juveniles and adults

102

169

Metamorphs

106

741

Summary Total captures

2,930

9,069

Trap nights (tn)

98,457

152,597

Captures/100 tn

2.98

5.94

detected for red efts, adult red–backed salamanders, and juvenile–adult spotted salamanders. Although there were no differences among gap types for juvenile–adult spotted salamanders, all gaps had lower

relative abundance than closed–canopy sites in 2003 (large gaps p = 0.00; small gaps p = 0.00; natural gaps p = 0.06). In 2002, red efts showed lower abundance in large gaps than in small and natural gaps (table 3).

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Strojny & Hunter

Table 2. 2003 ANOVA results of ranked difference values and Tukey's pairwise comparisons among gap treatments (difference values —reported in captures per 100 trapnights— calculated by subtracting the mean closed–canopy capture rate of a 10–ha research area from the gap capture rate): Lhg. Large harvest gap; Shg. Small harvest gap; Ng. Natural gap; Lg. Large gap; Sg. Small gap; Lg–Sg. Large gap vs. Small gap; Lg–Ng. Large gap vs. Natural gap; Sg–Ng. Small gap vs. Natural gap; I. Immature; J. Juvenile; A. Adult; M. Metamorph; E. Efts.

Tabla 2. Resultados del ANOVA para el 2003 de los valores diferenciales ordenados y la comparación por pares de Tukey entre los tratamientos de los claros (los valores diferenciales —en capturas por cada 100 noches de trampeo— calculados restando la tasa media de captura de un área de investigación de 10 ha de dosel cerrado, de la tasa de captura en el claro): Lhg. Claro de tala grande; Shg. Claro de tala pequeño; Ng. Claro natural; Lg. Claro grande; Sg. Claro pequeño; Lg–Sg. Claro grande frente a claro pequeño; Lg–Ng. Claro grande frente a claro natural; Sg–Ng. Claro pequeño frente a claro natural; I. Inmaduro; J. Juvenil; A. Adulto; M. Metamorfo; E. Individuo inmaduro terrestre.

Mean (SE) difference values of gap type

Lhg (n = 22)

Shg (n = 22)

Ng (n = 19)

Pairwise comparisons p

Lg–Sg Lg–Ng Sg–Ng

Salamanders Spotted Salamander J & A

–0.25 (0.10)

–0.39 (0.09)

–0.20 (0.08)

0.18

M

–1.52 (0.54)

–1.96 (0.57)

0.33 (0.54)

0.00

–0.19 (0.09)

–0.26 (0.15)

0.20 (0.39)

0.42

0.95

0.00

0.00

Eastern Newt E

Eastern Red–backed Salamander A

0.00 (0.09)

0.00 (0.07)

–0.19 (0.06)

0.10

I

–0.06 (0.02)

0.03 (0.03)

–0.03 (0.04)

0.08

0.07

0.76

0.337

0.06

0.02

Anurans American Bullfrog M

–0.16 (0.03)

–0.07 (0.02)

0.13 (0.06)

0.00

0.00

Green Frog J

–0.09 (0.02)

0.01 (0.02)

0.03 (0.03)

0.00

0.00

0.01

0.88

M

–0.91 (0.14)

–0.13 (0.07)

0.30 (0.16)

0.00

0.00

0.00

0.05

0.05

0.16

Pickerel Frog J

0.00 (0.02)

0.06 (0.02)

0.01 (0.02)

0.05

M

0.06 (0.06)

0.24 (0.07)

0.59 (0.30)

0.19

0.88

Wood Frog J & A

–0.07 (0.02)

0.05 (0.04)

0.06 (0.02)

0.00

0.00

0.00

0.31

M

–0.65 (0.06)

0.10 (0.17)

–0.25 (0.13)

0.00

0.00

0.00

0.58

Immature red–backed salamander results were partially consistent with 2003 results, where large gaps exhibited lower abundance than natural gaps.

When we limited comparisons to harvest gaps that were similar in size (< 512 m2) to natural gaps, we still found low relative abundance within harvest gaps for four groups: bullfrog metamorphs, green frog juveniles and metamorphs, and juvenile–adult wood frogs (Strojny, 2004).

Discussion Relative abundance within gaps Overall, there was little evidence that location within a gap (north or south aspect, edges, center) influenced amphibian abundance. Only green frog capture rates (also the species with the highest number captured) were relatively high at the edges of large gaps in

Animal Biodiversity and Conservation 33.1 (2010)

7

Table 3. 2002 ANOVA results of ranked difference values and Tukey's pairwise comparisons among gap treatments (difference values —reported in captures per 100 trapnights— calculated by subtracting the mean closed–canopy capture rate of a 10–ha research area from the gap capture rate): I. Immature; J. Juvenile; A. Adult; M. Metamorph; E. Efts.

Tabla 3. Resultados del ANOVA para el 2002 de los valores diferenciales ordenados y la comparación por pares de Tukey entre los tratamientos de los claros (los valores diferenciales —en capturas por cada 100 noches de trampeo— calculados restando la tasa media de captura de un area de investigación de 10 ha de dosel cerrado, de la tasa de captura en el claro): I. Inmaduro; J. Juvenil; A. Adulto; M. Metamorfo; E. Individuo inmaduro terrestre.

Mean (SE) difference values of gap type

Lhg (n = 22)

Shg (n = 22)

Ng (n = 19)

Pairwise comparisons p

Lg–Sg

Lg–Ng Sg–Ng

Salamanders Spotted Salamander J & A

–0.38 (0.10)

–0.51 (0.07)

–0.07 ( 0.06)

0.00

0.06

0.82

0.00

M

0.08 (0.14)

–0.87 (0.27)

0.08 (0.14)

0.00

0.00

0.78

0.01

–0.35 (0.06)

–0.18 (0.11)

0.14 (0.10)

0.00

0.00

0.00

0.12

Eastern Newt E

Eastern Red–backed Salamander A

–0.05 (0.03)

0.02 (0.04)

–0.01 (0.02)

0.37

I

–0.04 (0.02)

0.01 (0.01)

0.01 (0.01)

0.08

0.16

0.10

0.95

Anurans American Bullfrog J

0.04 (0.04)

0.00 (0.03)

0.00 (0.02)

0.80

M

0.00 (0.02)

–0.01 (0.02)

0.00 (0.02)

0.97

Green Frog M

–0.30 (0.16)

0.57 (0.27)

0.14 (0.15)

0.00

0.00

0.00

0.99

Wood Frog J&A

0.00 (0.02)

–0.01 (0.04)

0.00 (0.03)

0.66

M

0.04 (0.05)

0.04 (0.07)

–0.09 (0.03)

0.00

both 2002 and 2003. In smaller gaps there was no indication of gap aspect or edge effects for any of the species. Location within small gaps also did not affect vegetation patterns (Schofield, 2003).

Relative abundance among gap types Pairwise comparisons among gap types illustrated how sensitivity to gap size or gap origin varied among species groups. Anurans are more mobile, and therefore thought to be comparatively less physiologically constrained in open habitats than salamanders (Stebbins & Cohen, 1995; DeMaynadier & Hunter, 1998). Nevertheless, in 2003, five of seven anuran groups showed relatively lower abundance for at least one of the harvest gap treatments. Abundances of

0.71

0.00

0.04

bullfrog and green frog metamorphs were lowest in large gaps, moderately low in small gaps, and highest in natural gaps (table 2; appendix 2). Furthermore, when we compared harvest and natural gaps of the same size, we observed lower abundance in gaps of harvested origin (Strojny, 2004), thus indicating both size of gap and gap origin were important. Chan– McLeod (2003) and Patrick et al. (2006) also found anurans, especially smaller individuals, to be limited by conditions created by timber harvesting. For three other anuran groups (green frog juveniles, wood frog juvenile–adults and metamorphs) large gaps exibited lower abundances —but small–gap and natural–gap treatments were similar (table 2; appendix 2). This suggests that small harvest gaps provided habitat similar to natural gaps even though they were, on

8

average, larger than natural gaps. Both metamorphs and juveniles of pickerel frogs, a species associated with open habitat (Hunter et al., 1999), showed either no differences among gaps or higher abundance within gaps (table 2, appendix 2).

Juvenile–adult spotted salamanders were the only group with lower abundance in all gap types, and they showed only limited differences among gap types (tables 2, 3). Spotted salamander metamorphs showed lower abundance in both large and small harvest gaps, but not in natural gaps (table 2; appendix 2). These results were consistent with previous research that detected lower capture rates of spotted salamander metamorphs in open–canopy areas such as clear–cuts (DeMaynadier & Hunter, 1998; Renken et al., 2004) and even partially cut stands (Patrick et al., 2006).

Gap type effects for our other two salamander species were less definitive or absent.

Red efts showed reduced abundance in large harvest gaps in 2002, but no statistical differences among gap types in 2003 —despite much larger sample sizes (tables 2, 3). For adult red–backed salamanders no differences among gap types were detected in 2002 or 2003. Inconsistent treatment effects were detected for immature red–backed salamanders, with relatively higher abundance in small gaps and lower abundance in large and natural gaps in 2003, while abundance in large gaps was lower relative to small and natural gaps in 2002.

Although red–backed salamanders have been widely described as sensitive to forest management (Ash, 1997; DeMaynadier & Hunter, 1998; Waldick et al., 1999; Welsh & Droege, 2001; Hicks & Pearson, 2003; Knapp et al., 2003; Homyack & Haas, 2009), they may be relatively insensitive to small–scale harvesting, at least as adults (Messere & Ducey, 1998; McKenny et al., 2006).

The divergence between large and small harvest gaps (observed for metamorphs of bullfrogs, green frogs, wood frogs, and juveniles of green frogs and wood frogs) may be associated with differences in both gap size and residual structure. Per unit area, more reserve trees were left in small gaps (14 m2/ha basal area) than in large gaps (11 m2/ha basal area).

Presence of residual structure such as reserve trees (Greenberg, 2001) and CWD (Moseley et al., 2004) may explain the continuation of observed amphibian activity in harvested areas. The strength of the effects in our study may be lower than in similar studies of canopy disturbance and amphibians undertaken in other regions because of the relatively cool, moist conditions found in Maine compared to forests in the southern U.S. (Semlitsch et al., 2009).

Also, when evaluating responses of amphibians to harvesting, time since harvest is important to consider (Knapp et al., 2003; Morneault et al., 2004; Homyack & Haas, 2009). In our gaps, most tree regeneration was under 0.5 m in height with tree abundance decreasing with increasing stem height (Schofield, 2003).

The regeneration that had occurred in our harvest gaps 6–8 years post harvest was limited and not as advanced as one would expect to find in a clear–cut where more light is available to stimulate growth.

Strojny & Hunter

Management implications To evaluate harvested and natural gaps, we focused on amphibians that inhabit upland forests, whether for foraging, dispersal, or reproduction. Disturbances that remove a greater proportion of the canopy tend to result in a greater reduction in amphibian abundance than less intense disturbances (Semlitsch et al., 2009).

More specifically, research on amphibian response to partial (50%) canopy removal and complete canopy removal in the same region as our study also found variable responses depending on the species and age–class (Patrick et al., 2006). The proportions of juvenile captures for all species in common to the two studies, with the exception of pickerel frogs, were progressively lower from uncut areas to partial canopy removal to complete canopy removal areas (Patrick et al., 2006). With the relatively limited canopy disturbance of our study, we found that harvest gaps, especially small gaps, can provide habitat comparable to natural gaps for some amphibian groups, but not all. It is important to note that the differences we did detect were at a "local" scale, using the gap as the experimental unit. At a landscape scale, the closed– canopy conditions surrounding the canopy gaps likely aid in maintaining species abundance, as found by Renken et al. (2004).

There is a general consensus that long–term forest management needs to incorporate biological and physical diversity into management goals (Franklin et al., 1997; Seymour & Hunter 1999). Since forest biota and processes are closely related to structural elements (Palik et al., 2002), studies such as ours that identify and quantify differences between artificial and natural disturbances can aid foresters in designing harvests that maintain ecological integrity (DeMaynadier & Hunter, 1995; Coates & Burton, 1997; Lindenmayer et al., 2006).

Acknowledgments We thank Fred Servello and Robert Wagner for initial reviews of this manuscript, as well as the helpful comments and insights provided by anonymous reviewers.

Bill Halteman provided invaluable statistical guidance for this project. H. Alcock, S. Barteaux, A. Easley, J. Everett, and student volunteers assisted with field data collection. This project was funded through the United States Department of Agriculture’s National Research Initiative Competitive Grants Program.

The University of Maine’s Association for Graduate Students provided additional funding for research and conference travel. Maine Forest and Agriculture Experiment Station Publication No. 3088.

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Appendix 1. Mean relative abundance (captures per 100 trap nights) of amphibians captured in 11 harvest–created gapsa, 2003, comparing capture rates between a) northern and southern edges of a gap, and b) edges and gap centers: a North–south transects of the gaps were between 35–61 m long; b Probabilities were calculated using a multiple response permutation procedure, α = 0.10.

Apéndice 1. Abundancia relativa media (capturas cada 100 noches de trampeo) de anfibios capturados en 11 claros creados por la industria madereraª, en el año 2003, comparando las tasas de captura a) de los bordes norte y sur del claro, y b) de los bordes y el centro de los claros: ª Los transectos norte– sur de los claros estaban entre 35 y 61 m de longitud; b Las probabilidades se calcularon utilizando un procedimiento de permutación de respuesta multiple, α = 0,10. a) Aspect (north vs. south)

Mean (± 1 SE)

Species (number captured)

North

South

Difference

pb

Spotted Salamander (382)

1.97 (0.80)

1.21 (0.41)

0.76 (0.45)

0.13

0.59 (0.19)

0.48 (0.09)

0.11 (0.14)

0.38

0.86 (0.31)

0.66 (0.11)

0.19 (0.28)

0.59

Juveniles and adults (129) Eastern Newt (efts) (183) Eastern red–backed salamander (79)

0.30 (0.06)

0.36 (0.09)

–0.06 (0.10)

0.64

Immatures (18)

0.05 (0.02)

0.10 (0.03)

–0.05 (0.03)

0.19

Adults (61)

0.25 (0.06)

0.26 (0.09)

–0.01 (0.09)

0.93

Bullfrog (101)

0.35 (0.10)

0.49 (0.12)

–0.14 (0.10)

0.13

Green Frog (506)

1.90 (0.52)

2.33 (0.57)

–0.43 (0.50)

0.33

Wood Frog (85)

0.32 (0.06)

0.39 (0.10)

–0.07 (0.09)

0.60

0.47 (0.11)

0.59 (0.18)

–0.11 (0.16)

0.40

Metamorphs (61)

b) Edge vs. gap center

Mean (± 1 SE)

Species (number captured)

Gap edge

Gap center

Difference

pb

Spotted Salamander (249)

1.43 (0.57)

1.69 (0.86)

–0.27 (0.66)

0.52

0.50 (0.11)

0.52 (0.22)

–0.02 (0.22)

0.80

Eastern Newt (efts) (103)

0.81 (0.31)

0.49 (0.08)

0.32 (0.28)

0.38

Eastern red–backed salamander (49)

0.30 (0.09)

0.32 (0.10)

–0.02 (0.14)

0.70

0.23 (0.10)

0.22 (0.07)

0.01 (0.13)

0.79

Bullfrog (72)

0.47 (0.11)

0.43 (0.08)

0.04 (0.09)

0.53

Green Frog (336)

2.52 (0.68)

1.74 (0.50)

0.78 (0.31)

0.02

Wood Frogs (57)

0.42 (0.10)

0.29 (0.09)

0.13 (0.11)

0.29

0.62 (0.19)

0.43 (0.14)

0.19 (0.13)

0.23

Juveniles and adults (81)

Adults (35)

Metamorphs (40)

12

Strojny & Hunter

Appendix 2. Median difference values with 90% confidence intervals for species/age groups of amphibians captured in the Penobscot Experimental Forest, 2003. Difference values were calculated by subtracting the mean capture rates of closed–canopy plots from gap capture rates for their respective research areas. The x–axis shows treatment type: large harvest gap (n = 22), small harvest gap (n = 22), and natural gap (n = 19). Letter values at the base of each plot show Tukey’s pairwise comparison results on the ranked difference values. Shared letters indicate no difference (α > 0.10): LG. Large Gap; SG. Small gap; NG. Natural Gap. Apéndice 2. Valores diferenciales de la mediana con un 90% de intervalos de confianza para los grupos de especie/edad de anfibios capturados en el Bosque Experimental de Penobscot, en el 2003. Los valores diferenciales se calcularon restando las tasas medias de captura de las zonas de dosel cerrado de las tasas de captura de los claros en sus áreas de investigación respectivas. El eje x corresponde al tipo de tratamiento: claro de tala grande (n = 22), claro de tala pequeño (n = 22), y claro natural (n = 19).

Las letras en la base de cada registro representan los resultados de la comparación por pares de Tukey de los valores diferenciales ordenados. Las letras compartidas indican que no existía diferencia alguna (α > 0,10): LG. Claro grande; SG. Claro pequeño; NG. Claro natural.

Mean difference values (captures per 100 TN)

Mean difference values (captures per 100 TN)

0.1

Spotted Salamander (juveniles and adults)

0.0 –0.1 –0.2 –0.3 –0.4 a SG

Mean difference values (captures per 100 TN)

0.8

0.0

–0.1 –0.2 –0.3 –0.4 –0.5

a

a

LG

SG

1 0 –1 –2 a LG

a SG

b NG

Eastern Newt (efts)

0.6 0.4 0.2 0.0 –0.2 –0.4 –0.6

Eastern Red–backed Salamander (adults) 0.2 0.1

2

a –3 NG

a LG

Mean difference values (captures per 100 TN)

a LG

Mean difference values (captures per 100 TN)

–0.5

Spotted Salamander (metamorphs)

a SG

a NG

Eastern Red–backed Salamander (immature) 0.10 0.05 0.00 –0.05 –0.10

a –0.15 NG

a

b

ab

LG

SG

NG

Animal Biodiversity and Conservation 33.1 (2010)

13

0.3 0.2 0.1 1 0.0 –0.1 –0.2 –0.3

0.10 0.05 0.00 –0.05

b SG

Green Frog (metamorphs) 1.0 0.5 0.0

b –1.5 NG

Pickerel Frog (juveniles)

0.00 –0.05 a LG

b SG

0.05 0.00 –0.05 –0.10 b

LG

SG

1.2

b

a LG

b SG

c NG

Pickerel Frog (metamorphs)

1.0 0.8 0.6 0.4 0.2 –0.2

–0.4 ab NG

Wood Frog (juveniles and adults)

a

Mean difference values (captures per 100 TN)

a LG

0.05

–0.15

c NG

–1.0

0.10

0.10

b SG

–0.5

–0.10

–0.10

a LG

Mean difference values (captures per 100 TN)

Green Frog (juveniles)

–0.15

American Bullfrog (metamorphs)

Mean difference values (captures per 100 TN)

Mean difference values (captures per 100 TN)

Mean difference values (captures per 100 TN)

Mean difference values (captures per 100 TN)

Mean difference values (captures per 100 TN)

Appendix 2. (Cont.)

a LG

a SG

a NG

Wood Frog (metamorphs) 0.4 0.2 0.0 –0.2 –0.4 –0.6 –0.8

–1.0 NG

a LG

b SG

b NG

"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

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Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

Animal Biodiversity and Conservation 33.1 (2010)

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Unusual behaviour of an immature loggerhead turtle released in the Alboran Sea J. J. Bellido, J. C. Báez, J. J. Castillo, J. J. Martín, J. L. Mons & R. Real

Bellido, J. J., Báez, J. C., Castillo, J. J., Martín, J. J., Mons, J. L. & Real, R., 2010. Unusual behaviour of an immature loggerhead turtle released in the Alboran Sea. Animal Biodiversity and Conservation, 33.1: 15–18.

Abstract Unusual behaviour of an immature loggerhead turtle released in the Alboran Sea.— A juvenile loggerhead turtle with buoyancy problems was captured in the Alboran Sea (Mediterranean Sea, south of Spain) and released 14 months later after healing. Six days after the release, the turtle was seen swimming 42 km from the point of release, displaying unusual behaviour. We re–captured and released it again, 95 nautical miles offshore, near the Alboran Island. Ten days later the turtle arrived at the beach close to where it had been maintained in captivity. We discuss these findings in the context of behavioural alteration and habituation in released sea turtles. Capture–mark–recapture studies of sea turtles should be approached with caution as manipulated animals may modify their usual behaviour.

Key words: Sea turtle, Captivity, Capture–mark–recapture, Post–release, Mediterranean Sea. Resumen Comportamiento inusual de un ejemplar de tortuga boba joven liberado en el Mar de Alborán.— Un individuo juvenil de tortuga boba con problemas de flotabilidad fue capturado en el Mar de Alborán (Mar Mediterráneo, sur de España). Fue liberado 14 meses después de su curación. Seis días después de la liberación, la tor� tuga fue vista nadando a 42 km del punto de liberación, con un comportamiento inusual. Por este motivo fue recapturada y liberada de nuevo, a 95 millas náuticas de la costa cerca de la Isla de Alborán. Diez días más tarde, la tortuga llegó a la playa, cerca de donde se la había mantenido en cautividad. En la presente nota se discuten estos hechos en el contexto de la alteración de la conducta y la habituación de las tortugas en libertad.

Los estudios centrados en la captura, marcaje y recaptura de las tortugas marinas, por ejemplo, deben de abordarse con cautela, ya que la manipulación de estos animales podría modificar su comportamiento habitual.

Palabras claves: Tortuga marina, Captura–marcado–recaptura, Posliberación, Mar Mediterráneo.

(Received: 17 VI 09; Conditional acceptance: 30 XI 09; Final acceptance: 7 I 10) J. J. Bellido,���������������������������������������������������������������������������������������������������� J. J. Castillo, J. J. Martín & J. L. Mons, Aula del Mar de Malaga. Avda. �������������������������������� M. Heredia 35, 29001 Mála� ga, España (Spain).– J. C. Báez, Inst. Español de Oceanografía, Centro Oceanográfico de Málaga, Puerto Pesquero de Fuengirola s/n, 29640 Fuengirola, Málaga, España (Spain).– J. J. Bellido, J. C. Báez & R. Real, Univ. de Málaga, Fac. de Ciencias, Depto. de Biología Animal, Campus de Teatinos, Boulevard Louis Pasteur, 29071 Málaga, España (Spain).

Corresponding author: J. C. Báez. E–mail: jcarlos.baez@ma.ieo.es

ISSN: 1578–665X

© 2010 Museu de Ciències Naturals

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Introduction In animal behaviour philopatry has been defined as a tendency to remain in, or return to, an individual’s birthplace (Parker, 2003). This phenomenon should be considered in any capture–mark–recapture study on wild migratory species, or when an individual is released back into its natural habitat after recovery from an injury because studies have indicated that such events may induce behavioral alterations (for example, Addison & Nelson 2000; Gauthier–Clerc et al., 2004; Dugger et al., 2006).

It is well known that sea turtles have a strong sense of orientation and return to their natal beaches after many years (������������������������������������ Lohmann et al., 1999; Putman & Lohm� ann, 2008). Swingle et al. (1994), however, found that released turtles exhibited alterations in behaviour, and Addison & Nelson (2000) also reported another case of habituation in a loggerhead sea turtle from Florida (Atlantic USA). Behavioural modifications, nevertheless were not been taken into account in recent studies of capture–mark–release in loggerhead sea turtle (e.g.

Casale et al., 2007; Hochscheid et al., 2007; Revelles et al., 2008; Cardona et al., 2005, 2009). Eckert et al. (2008) used wildlife animals in their study of cap� ture–mark–release in Loggerhead from the Western Mediterranean Sea, to avoid behavioural modifications.

We present the unusual behaviour of an imma� ture loggerhead turtle released in the Alboran Sea, and examine the possible consequences of such modifications in studies of marine migratory species.

Material and methods Study area The Alboran Sea connects the Western Mediterranean Sea with the Atlantic Ocean. It is an outstanding area for megafauna in the North Atlantic–Mediterranean region, providing an important corridor for migratory marine turtles (e.g. Camiñas, 1997).The loggerhead turtle Caretta caretta is the most abundant sea turtle (Bellido et al., 2010) in this region but little is known about its use of the Alboran coast. Recent studies have shown, however, that Atlantic turtles cross the Strait of Gibraltar, enter the Western Mediterranean basin looking for feeding grounds, and later return to the Atlantic, again crossing Alboran waters (Camiñas & De la Serna, 1995).

Threatened Marine Species Recovery Centre The "Consejería de Medio Ambiente de la Junta de Andalucía" (the Andalusia Environmental Advisory Board) supports a network of Recovery Centres for Threatened Marine Species and a volunteer stranding network with a strong presence in all the municipalities of the Andalusian coast. Other bodies, such as local police and scientific groups, collaborate closely in the detection and care of stranded individuals. Every year, many Loggerhead turtles strand in Andalusian waters and are transferred to a recovery centre.

Bellido et al.

The recovery centre in Aula del Mar of Malaga has indoor tanks of 2 x 2 m. The temperature of the water ranges between 23ºC in summer and 18ºC in winter. Sea turtles are fed small pelagic animals, such as mackerel or squid, that are rich in fat. When the veterinary team considers the animal is fit, it is released. On release, all turtles are tagged with an internal microchip and an external metal tag.

Results and discussion A loggerhead turtle with buoyancy problems was found on 19 V 2007 in waters of Almuñecar (36º 40' N, 3º 41' W). Its straight carapace length was 43 cm. It was captured and treated for lung infection. The reco� very process took 10 months, but the veterinary team decided to delay the turtle’s release until the summer season to increase its chances of acclimatization. It was released at Malaga Bay (36º 33' N, 4º 26' W) on 3 VII 2008, after 14 months in the Aquarium Aula del Mar at Benalmádena (36º 35' N, 4º 31' W).

Six days later, the turtle was seen swimming near the coast of Torrox (36º 43' N, 3º 56' W), 42 km from the point of release. People at the beach noticed that the turtle exhibited unusual swimming behaviour, insistently approaching people. For this reason, the turtle was re–captured and moved back to Aula del Mar of Benalmadena, where it spent 5 more weeks before going back to the sea. This time the turtle was released 95 nautical miles offshore, near the Alboran Island (35° 55' N, 03° 02' W). Ten days later the turtle was found on the coast of Benalmadena (36º 36' N, 4º 28' W), close to the site where it had lived for more than a year (fig. 1).

The present case exemplifies a loggerhead tur� tle’s change in behaviour after living in captivity, and is similar to the report of habituation cases observed by Swingle et al. (1994), and Addison & Nelson (2000).

Nowadays, the most accepted hypothesis for turtle philopatry is magnetic imprinting (Putman & Lohmann, 2008). However, in addition to magnetic imprinting, Putman & Lohmann (2008) believe that turtles could use local recognition cues such as female pheromones and chemicals from the beach.

Use of cues of this type would likely account for alterations in their natural behaviour and explain their ability to return to the place of captivity. Larger studies on behavioural alterations are needed so that reintroduction policies can incorporate ways of reducing habituation in turtles prior to release.

Acknowledgements We would like to thank Daniel Carrera–Martínez for his helpful comments. We are grateful to Consejería de Medio Ambiente de la Junta de Andalucía for pro� viding data of strandings. This study was supported by the Consejería de Innovación, Ciencia y Empre� sa of the Junta de Andalucía (research project no.

P05–RNM–00935).

Animal Biodiversity and Conservation 33.1 (2010)

–10º

–9º

–8º

–7º

–6º

–5º

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–4º

–3º

–2º

–1º

0º

1º

2º 40º

39º

38º

37º

Aula de Mar

Atlantic Ocean

3

a

2

1

Mediterranean Sea 36º b

35º Fig. 1. Study area (Andalusia Coast, Spain): 1. First detection (19 V 07); a. The turtle is released (3 VII 08); 2. It appears in Torrox (9 VII 08); b. Released again, Alboran Island (6 VIII 08); 3. It appears in Benalmadena. We used “maptool” (available on www.seaturtle.org) as mapping tool.

Fig. 1. Área de estudio (costa andaluza, España): 1. Primera detección (19 V 07); a. La tortuga es liberada (3 VII 08); 2. Aparece en Torrox (9 VII 08); b. Liberada de nuevo, isla de Alborán (6 VIII 08); 3. Aparece en Benalmádena. Utilizamos “maptool” (disponible en www.seaturtle.org) como herramienta de mapeo.

References Addison, D. S. & Nelson, K. A., 2000. Recapture of a tagged, captive reared juvenile Loggerhead turtle – An example of habituation? Marine turtle Newsletter, 89: 15–16.

Bellido, J. J., Castillo, J. J., Pinto, F., Martín, J. J., Mons, J. L., Báez, J. C. & Real, R., 2010. Diffe� rential geographical trends for Loggerhead turtles stranding dead or alive along the Andalusian coast, South Spain. Journal Marine Biological Association, U. K., 90(2): 225–231.

Camiñas, J. A., 1997. Capturas accidentales de tor� tuga boba Caretta caretta (Linnaeus, 1758) en el Mediterráneo occidental en la pesquería de palan� gre de superficie de pez espada (Xiphias gladius Linnaeus, 1758). Collective Volume of Scientific Papers ICCAT, 46: 446–455.

Camiñas, J. A. & De la Serna, J. M., 1995. The Loggerhead distribution in the Western Mediter� ranean Sea as deduced from the captures by the Spanish Long Line Fishery. Scientia Herpetologica, 316–323.

Cardona, L., Revelles, M., Carreras, C., San Félix, M., Gazo, M. & Aguilar, A., 2005. Western Mediterranean immature Loggerhead turtles: habitat use in spring and summer assessed through satellite tracking and aerial surveys. Marine Biology, 147: 583–591.

Cardona, L., Revelles, M., Parga, M. L., Tomas, J., Aguilar, A., Alegre, F., Raga, A. & Ferrer, X., 2009. Habitat use by Loggerhead sea turtles Caretta caretta off the coast of eastern Spain re� sults in a high vulnerability to neritic fishing gear.

Marine Biology, 156: 2621–2630.

Casale, P., Freggi, D., Basso, R., Vallini, C. & Argano, R., 2007. A model of area fidelity, nomadism, and distribution patterns of Loggerhead sea turtles (Caretta caretta) in the Mediterranean Sea. Marine Biology, 152: 1039–1049.

Dugger, K. M., Ballard, G., Ainley, D. G. & Barton, K. J., 2006. Effects of flipper bands on foraging be� havior and survaival of Adelie Penguins (Pygoscelis adeliae). The Auk, 123: 858–869.

Eckert, S., Moore, J. E., Dunn, D. C., Sagarminaga van Buiten, R., Eckert, K. L. & Halpin, P. N., 2008.

Modeling Loggerhead turtle movement in the Medi� terranean: importance of body size and oceanog� raphy. Ecological Application, 18: 290–308.

Gauthier–Clerc, M., Gendner, J. P., Ribic, C. A. Fra� ser, W. R., Woehler, E. J., Descamps, S., Gilly, C., Le Bohec, C. & Le Maho, Y., 2004. Long–term effects of flipper bands on penguins. Proceedings of the Royal Society B: Biological Sciences, 271: 423–426.

Hochscheid, S., Bentivegna, F., Bradai, M. N. & Hays, G. C., 2007. Overwintering behaviour in sea turtles:

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dormancy is optional. Marine Ecology Progess Series, 340: 287–298.

Lohmann, K. J., Hester, J. T. & Lohmann, C. M. F., 1999. Long–distance navigation in sea turtle. Ethol� ogy Ecology & Evolution, 11: 1–23.

Parker, S. B. (Ed.), 2003. Philopatry. McGraw–Hill Dictionary of Scientific and Technical Terms. Mc� Graw–Hill Companies, Inc., Answers.com., 2003.

Retrieved on 2009–01–27.

Putman, N. F. & Lohmann, K. J., 2008. Compatibility of magnetic imprinting and secular variation. Current Biology, 18(14): 596–597.

Revelles, M., Camiñas, J. A., Cardona, L., Parga, M.,

Bellido et al.

Tomás, J., Aguilar, A., Alegre, F., Raga, A., Berto� lero, A. & Oliver, G., 2008. Tagging reveals limited exchange of immature Loggerhead sea turtles (Caretta caretta) between regions in the western Mediterranean. Scientia Marina, 72: 511–518.

Swingle, W. M., Warmolts, D., Keinath, J. & Musick, J., 1994. Loggerhead sea turtle had–strat evaluation: captive growth rates and post release movements and beahavior. In: Fourteenth Annual Symposium on Sea Turtle Biology and Conservation: 289–292 (K. A. Bjorndal, A. B. Bolton, D. A. Johnson & P. J. Eliazar, Eds.). NOAA Technical Memorandum NMFS–SEFSC–351.

Animal Biodiversity and Conservation 33.1 (2010)

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Caracterización y selección del sitio de anidación de la grulla cubana (Grus canadensis nesiotes) en el herbazal del Refugio de Fauna El Venero, Cuba Y. Ferrer Sánchez, D. Denis Ávila & I. Ruiz Companioni Ferrer Sánchez, Y., Denis Ávila, D. & Ruiz Companioni, I., 2010. Caracterización y selección del sitio de anidación de la grulla cubana (Grus canadensis nesiotes) en el herbazal del Refugio de Fauna El Venero, Cuba.

Animal Biodiversity and Conservation, 33.1: 19–29.

Abstract Characterization and selection of nest sites by the Cuban sandhill crane (Grus canadensis nesiotes) in the grasslands of the El Venero Wildlife Refuge, Cuba.— Grus canadensis nesiotes is an endemic threatened subspecies of crane that inhabits freshwater wetlands. We characterized its nesting site and analyzed nest–site selection at three spatial scales in grasslands of El Venero Wildlife Refuge (Cuba), during the breeding seasons of 2005–2007. We monitored 26 nests until hatching. We also measured vegetation height, coverage at 30 and 100 cm, and distance between grass stems at nests. These values were compared with values measured at points 100 m away from nests. We used a GIS to obtain distances to channels, roads and forest patches, as well as to determine percentages of grass, water, palm–grass and casuarina–grass in circles of 100, 400, 700 and 1,000 m of radius around both nests and random points. Vegetation variables around nests (height: 78.9 ± 2.1; coverage at 30 cm: 97.8 ± 0.6; coverage at 100 cm: 64.7 ± 1.6) were lower than those at 18 m away. There were no differences in vegetation variables or distances to forests and water between nests and random points located farther. Percentage covers of grassland and forest influenced nest site selection. Average distance between simultaneous active nests was 1,305.8 ± 106 m, the smaller area of potential use was 30.3 km2 and the mean influence area was 2.13 ± 0.36 km2. Nest site selection by cranes, as well as nest site characteristics, depended of the presence of extensive areas of grassland.

Key words: Cuban crane, Selection, Nesting area, Spatial scales, Grassland.

Resumen Caracterización y selección del lugar de nidificación de la grulla cubana (Grus canadensis nesiotes) en los herbazales del Refugio de Fauna El Venero, Cuba.— Grus canadensis nesiotes es una subespecie endémica y amenazada de grulla cuyas poblaciones están asociadas a humedales de agua dulce. En este trabajo se caracterizó su lugar de nidificación y se determinó su selección a tres escalas espaciales en los herbazales del Refugio de Fauna El Venero, Cuba, durante los años 2005–2007. Se monitorizaron 26 nidos hasta la eclosión.

También se midió la altura de la vegetación, la cobertura a 30 y 100 cm, y la distancia entre los tallos de las hierbas en los lugares de nidificación (microhábitat). Estas variables se compararon entre nidos y puntos al azar situados a 100 m de los nidos (mesohábitat). Para el análisis a escala de macrohábitat se utilizó un SIG, obteniéndose las distancias a canales, caminos y superficies boscosas, y también los porcentaje de herbazales, lagunas, herbazales con casuarinas y herbazales con palmas en círculos de radios de 100, 400, 700 y 1.000 m centrados tanto en los nidos como en los puntos aleatorios. Las variables de la vegetación alrededor de los nidos (alturas: 78,9 ± 2,1; cobertura a 30 cm: 97,8 ± 0,6; cobertura a 100 cm: 64,7 ± 1,6) fueron menores que a distancias de 18 m. A una distancia mayor las diferencias entre las variables de vegetación o las distancias a los bosques o a las lagunas, en los nidos y en los puntos aleatorios no fueron estadísticamente significativas.

La elección del lugar de nidificación estaba influenciada por el porcentaje de cobertura de los herbazales y los bosques. La distancia promedio entre nidos activos simultáneos fue de 1.305,8 ± 106 m, el área de uso potencial de menor tamaño fue 30,3 km2 y el área promedio de influencia de cada nido fue de 2,13 ± 0,36 km2. La selección y características del lugar de nidificación dependieron pues de la presencia de áreas extensas de herbazal.

ISSN: 1578–665X

© 2010 Museu de Ciències Naturals

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Ferrer Sánchez et al.

Palabras clave: Grulla cubana, Selección, Área de nidificación, Escalas espaciales, Herbazal.

(Received: 12 VIII 09; Conditional acceptance: 11 XI 09; Final acceptance: 03 II 10) Yarelys Ferrer Sánchez & Idael Ruiz Companioni, Empresa Nacional para la Protección de la Flora y la Fauna.

Calle 42 esquina 7a, # 514, Playa, Ciudad de La Habana, Cuba.– Dennis Denis Ávila, Fac. de Biología, Univ. de la Habana. Calle 25 e/I y J, Plaza de la Revolución, Ciudad de La Habana, Cuba.

Corresponding author: Y. Ferrer Sánchez. E–mail: ffconservacion@enet.cu

Animal Biodiversity and Conservation 33.1 (2010)

Introducción Las grullas (Aves, Gruidae) son especies funcionalmente importantes dentro de los humedales naturales, los cuales constituyen hábitats primarios para este grupo (Bishop, 1988). La pérdida excesiva de estas áreas naturales ha sido la causa fundamental de la disminución del tamaño de las poblaciones de estas aves (Meine & Archibald, 1996a). En ese caso se encuentra la grulla cubana, Grus canadensis nesiotes (Gundlach, 1875), subespecie endémica del archipiélago cubano, que sufre amenazas por la pérdida y degradación de sus hábitats, las cuales han provocado que la subespecie esté en peligro de extinción (Meine & Archibald, 1996a, 1996b). El cambio en el régimen hídrico de los humedales, la expansión agrícola de cultivos de arroz (Oriza sativa) y caña (Saccharum officinarum) en los bordes y dentro de los humedales, el cambio en la comunidad de plantas herbáceas provocado por el pastoreo del ganado tradicional y del búfalo asiático (Bubalus bubalis), la sustitución de especies en los bosques naturales por variedades comerciales, entre otras amenazas, contribuyeron a la disminución de las poblaciones de G. c. nesiotes (Gálvez et al., 1999).

Actualmente existen localidades donde se practica la cacería furtiva sobre esta subespecie, y es posible también que las poblaciones tengan problemas genéticos y demográficos como consecuencia de su fragmentación y pequeño tamaño.

Con el creciente interés por la subespecie cubana y su delicado estado de conservación (Meine & Archibald, 1996a), se han realizado estudios descriptivos de la ecología reproductiva, el uso de hábitat y el ámbito hogareño en la población de la Isla de la Juventud (Gálvez, 2002), la más numerosa para Cuba (Gálvez et al., 1999). Los resultados de estos estudios aportaron información relevante para el manejo de esta subespecie en el ecosistema de arenas silíceas de dicha isla. Sin embargo, su alcance es limitado ya que las 12 poblaciones restantes de grullas se distribuyen por herbazales anegados que existen como reductos de las antiguas sabanas naturales.

Estos humedales tienen una composición florística y estructural diferente a las sabanas mencionadas y están sometidos a fuertes presiones humanas, afectando de esta forma varias poblaciones de aves, incluidas las grullas.

Para realizar un manejo de las poblaciones de grullas se necesita conocer sus requerimientos de hábitat, y a pesar del amplio estudio existente sobre la ecología reproductiva de la especie nominal (ej.: Bennett & Bennett, 1990; Depkin et al., 1994; Littlefield, 2003; Kreger et al., 2006), la interpretación que se ha hecho sobre la relación entre la especie y el ambiente no ha sido suficiente para conservar las áreas usadas por estas aves. Estas deficiencias son consecuencia de los estudios y comparaciones realizados a escalas simples. Sin embargo, un análisis a múltiples escalas en paisajes heterogéneos, podría incrementar el conocimiento sobre las necesidades de las especies (Wiens, 1989) y la interpretación necesaria para realizar un manejo adaptable de las mismas.

Esta aproximación provee una mejor resolución a los

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problemas de dominio y ayuda a incrementar el grado de generalidad de los patrones observados y de sus determinantes (Cueto, 2006).

Estas limitantes en los estudios también han afectado a G. c. nesiotes, restringiendo la realización de un manejo adaptable de la subespecie, fundamentalmente en los humedales. Este tipo de manejo incorpora el método científico a las acciones que se realicen, para aprender cuáles opciones funcionan y cuáles no, y adaptar las decisiones posteriores a esta nueva información (Holling, 1978). A partir de la problemática y los vacíos de información existentes con las poblaciones de grullas, el presente estudio tiene como objetivos caracterizar el sitio de anidación de G. c. nesiotes y determinar los patrones de su selección a tres escalas espaciales de análisis.

Material y métodos El presente estudio se llevó a cabo durante los años 2005 al 2007 en el Refugio de Fauna El Venero (22o 01' 31,38'' N – 78o 30' 44,82'' W), al norte de la provincia Ciego de Ávila, Cuba. Esta área protegida abarca parte de la cuenca hidrográfica La Yana, y las formaciones vegetales presentes son el bosque semideciduo mesófilo con humedad fluctuante, los bosques siempre verdes y los herbazales de ciénaga. Estos últimos son los hábitats que más usan las grullas y se caracterizan por especies como el macío (Thypha dominguensis), la cortadera (Eleocharris interstincta), la cortadera de dos filos (Cladium jamaicense), el junco (Cyperus spp.), el rabo de zorra (Erianthus giganteus) y el platanillo de río (Thalia geniculata) (Inguanzo et al., 2008). Estos herbazales sostienen a la tercera población de grullas más grande de Cuba, con alrededor de 102 individuos (Gálvez, 2002).

En el área de herbazales de ciénaga (5.695,9 ha) se localizaron 30 nidos y 26 de estos fueron monitoreados hasta la eclosión de los huevos. Se realizaron tres diseños de muestreo para el análisis de posibles patrones de selección del sitio de anidación. Estos diseños abarcaron la caracterización del hábitat de anidación a nivel de microhábitat, mesohábitat y macrohábitat y se emplearon puntos fijos y aleatorios sin presencia de nidos para comparar la estructura de la vegetación y la presencia, distancia y porcentaje de varios elementos del paisaje.

El muestreo a nivel de microhábitat de anidación se realizó luego de eclosionados los huevos. Alrededor de cada nido se delimitaron tres anillos concéntricos de 6 m, 12 m y 18 m de radio externo. Dentro de estas franjas se deslindaron y distribuyeron de forma aleatoria 4, 8 y 12 parcelas cuadradas de 1 m2, respectivamente. En las parcelas se midió la altura del estrato herbáceo y la distancia entre hierbas con una cinta métrica de 1 cm de precisión, y las coberturas vegetales a 30 cm y 100 cm del suelo con una pantalla de densidad. A partir de las distancias entre hierbas se determinó la distribución espacial por el índice de agregación y la densidad del estrato herbáceo por el método del vecino más cercano (Krebs, 1999). Los

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Ferrer Sánchez et al.

datos de estas variables medidas por parcela en cada nido fueron estandarizados calculando el valor medio general de cada variable por nido, para eliminar el efecto de la correlación espacial.

A nivel de mesohábitat se realizó un muestreo en ocho de los nidos monitoreados, alrededor de los cuales se delimitó un área de 15 m de radio. Dentro del área se distribuyeron aleatoriamente 16 parcelas de 1 m2 y en estas se registraron las mismas variables estructurales de la vegetación, mencionadas para el diseño anterior. El mismo procedimiento fue aplicado en cuatro puntos ubicados a 100 m de cada nido, en las cuatro direcciones cardinales.

En el análisis del macrohábitat se registraron las coordenadas geográficas de los 26 nidos con un GPS de 5 m de precisión. El área que potencialmente utilizan las grullas para anidar dentro de los límites del herbazal fue determinada por medio de una función kernel fija (Worton, 1989), con un parámetro de suavizado calculado ad hoc y se calculó el área definida por la isolínea del 90% de probabilidad. El área de influencia de cada nido fue determinada a partir de los polígonos de Dirichlet (Silverman, 1986). Ambos métodos fueron aplicados a partir de la extensión Animal Movement Analysis 1.1 para ArcView 3.2 y de las ubicaciones geográficas de los nidos activos simultáneos en cada año, entre los cuales también se calculó la distancia.

Esta distancia fue analizada entre nidos activos sin barreras físicas que limitaran su visibilidad.

El análisis del macrohábitat se realizó sobre un mapa temático digitalizado a partir de las hojas cartográficas del área (escala 1:25.000, proyección UTM, datum NAD27 para Cuba) del Instituto de Geodesia y Cartografía. Las áreas se corrigieron y actualizaron superponiendo una composición de falso color a partir de las bandas 4–2–1 del sensor ETM + del Landsat (fecha de adquisición: marzo, 2001) y escenas descargadas del servidor Google Earth Plus en diciembre del 2007. A partir del mapa obtenido se realizó una validación de los datos en el campo.

Con el programa ArcView 3.2 se ubicaron los nidos (n = 26) y puntos aleatorios (n = 26) y se

calculó el área de elementos del paisaje definidos como: herbazal, bosque, laguna, herbazal con casuarinas (Casuarina equisetifolia), herbazal con palmas (Sabal maritima) y cañaveral (cultivo de Saccharum officinarum). A partir de cada nido y punto aleatorio (sobre el sitio disponible para la anidación) se delimitaron círculos de 100, 400, 700 y 1.000 m de radio, que abarcaron áreas de 0,03 km2; 0,5 km2; 1,5 km2 y 3,1 km2, respectivamente. Para la selección de estos radios se tuvo en cuenta la distancia mínima entre nidos activos simultáneos, el ámbito hogareño de crías de grullas (Baker et al., 1995) y una aproximación a los movimientos que realizan las grullas en esta época (Watanabe, 2006). En estas áreas se calculó el porcentaje de cobertura de cada elemento del paisaje mencionado. También se registró la distancia más cercana desde nidos y puntos aleatorios a otros elementos del paisaje como: canales menores (de curso estrecho, pueden ser intermitentes), canales mayores (caudal regular y curso amplio), caminos y bosques.

A todos los datos obtenidos en el estudio se les realizaron las pruebas de normalidad (Kolmogorov–Smirnov) y de homogeneidad de varianzas (Scheffe–Box) para analizar el cumplimiento de los principios de las pruebas paramétricas. Las pruebas no paramétricas empleadas en los análisis son consecuencia del incumplimiento de las premisas mencionadas.

A cada variable se le calculó el valor medio, sus límites de confianza al 95% y el error estándar. Las comparaciones pareadas entre las características de la vegetación de nidos y puntos, los porcentajes de los diferentes elementos del paisaje, así como la distancia a estos en nidos y puntos aleatorios, se realizaron con pruebas U de Mann–Whitney.

La comparación de las características de la vegetación a diferentes distancias del nido (tres franjas), se realizó por una prueba de Kruskall–Wallis. Para identificar a posteriori los grupos con diferencias se graficaron los estadísticos descriptivos de las variables analizadas.

Tabla 1. Estadísticas de posición y dispersión de las variables medidas en la vegetación herbácea alrededor de los nidos de la grulla cubana (Grus canadensis nesiotes), a nivel de microhábitat, durante los años 2005 al 2007, Refugio de Fauna El Venero (Ciego de Ávila, Cuba, n = 104).

Table 1. Position and dispersion statistics of the variables measured in herbaceous vegetation around the nests of the Cuban crane (Grus canadensis nesiotes), at the microhabitat level, from 2005 to 2007, Wildlife Refuge El Venero (Ciego de Avila, Cuba, n = 104).

Variable

Media

ES

IC 95%

Min.

Máx.

Altura (cm)

78,9

2,1

74,8–83,0

24,6

150,0

Cobertura 30 cm (%)

97,8

0,6

96,6–98,9

53,3

100,0

Cobertura 100 cm (%)

64,7

1,6

61,5–68,0

0,0

100,0

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1,1 1,0

23

Media ± ES 1,96 x ES

Altura

1,0 0,9 0,9 0,8 0,8 0,7 0,7

1

2 Anillo

3

1,3

Cobertura a 100 cm

1,2

Media ± ES 1,96 x ES

1,1 1,0 0,9 0,8 0,7 0,6 0,5

1

2 Anillo

3

Fig. 1. Valor medio, error estándar y límites de confianza del 95% de la altura estandarizada de las hierbas y la cobertura vegetal estandarizada a 100 cm, a tres distancias: 1 (6 m), 2 (12 m) y 3 (18 m) de los nidos de Grus canadensis nesiotes, en el análisis a nivel de microhábitat, durante los años 2005 al 2007, Refugio de Fauna El Venero (Ciego de Ávila, Cuba).

Fig. 1. Mean value, standard error and 95% confidence intervals for standardized grass height and standardized plant cover at 100 cm, from three distances: 1 (6 m), 2 (12 m) and 3 (18 m) to Grus canadensis nesiotes nest, in the analysis at microhabitat level, from 2005 to 2007, Wildlife Refuge El Venero (Ciego de Avila, Cuba).

Se calculó el índice estandarizado de selección (Manly et al., 1993) para determinar si las proporciones en que aparecieron los elementos del paisaje alrededor de los nidos y en los puntos aleatorios fueron seleccionadas o evitadas por las grullas. El índice se comparó con una prueba de x2 (Atienza, 1994). Se empleó la prueba de la t de Student para comparar entre pares de años la distancia existente entre nidos activos simultáneamente. Todos los análisis se realizaron con un nivel de significación de 0,05, con el empleo del programa Statistica 6.0 (StatSoft Inc., 2003).

Resultados Las grullas construyeron sus nidos solamente en los herbazales de ciénaga. La altura promedio de la vegetación alrededor de estos (a nivel de microhábitat) fue de aproximadamente 80 cm, con valores máximos de hasta metro y medio (tabla 1). La cobertura de hierbas fue elevada, acorde a la densidad de vegetación, y a 30 cm del suelo se mantuvo casi sin variación con valores superiores al 95%.

La altura (Kruskal–Wallis H(2, N = 79) = 6,3; p = 0,04) y la cobertura a 100 cm (Kruskal–Wallis H(2, N = 79) = 6,3;

24

Ferrer Sánchez et al.

Tabla 2. Estadísticas de posición y dispersión de la distancia entre nidos simultáneamente activos y su área de influencia en el análisis a nivel de macrohábitat, para la grulla cubana (Grus canadensis nesiotes) durante los años 2005 al 2007, Refugio de Fauna El Venero (Ciego de Ávila, Cuba): Min. Mínimo; Max. Máximo.

Table 2. Position and dispersion statistics for the distances between active simultaneous nests and their area of influence in the analysis of macrohabitat level for the Cuban crane (Grus canadensis nesiotes) from 2005 to 2007, Wildlife Refuge El Venero (Ciego de Avila, Cuba): Min. Minimum; Max. Maximum.

Años

Distancia entre nidos (m) Media

n

ES

Mín.

Área de influencia (km2) Máx.

Media

n

ES

Mín.

Máx.

2005

1.433,7 18

153,5

332,7 2.661,9

1,28

10

0,23

0,55

3,02

2006

1.353,9

4

363,7

596,6 2.338,3

2,06

6

0,64

0,65

4,52

2007

1.159,2 17

162,6

333,4 2.812,6

2,94

10

0,72

0,49

8,13

Total

1.305,8 39

106,0

332,7 2.812,6

2,13

26

0,36

0,49

8,13

p = 0,04) del estrato herbáceo presentaron diferencias estadísticamente significativas, para el análisis de las tres franjas a diferentes radios de los nidos. En sustitución a una prueba a posteriori, la figura 1 mostró que las franjas 0–6 m y 12–18 m tienen una alta probabilidad de ser diferentes para las variables antes mencionadas. Sin embargo, las variaciones encontradas para la cobertura del estrato herbáceo a 30 cm no fueron significativas (Kruskal–Wallis H(2, N = 79) = 2,4; p = 0,3).

La distancia entre hierbas vecinas no mostró significación estadística (Kruskal–Wallis H(2, N = 79) = 0,9; p = 0,6), con valores entre 2,2 y 2,7 cm. Al calcular los índices de agregación se obtuvo una distribución agregada de las hierbas (0,48; 0,68 y 0,48, respectivamente) y las variaciones existentes tampoco fueron significativas.

La comparación de la estructura del estrato herbáceo en un radio de 15 m desde el nido y en puntos a 100 m, no mostró diferencias estadísticamente significativas. Tanto la altura promedio alrededor de los nidos (media = 77,5 ± 3,8; n = 26), la cobertura a 30 cm (media = 99,7 ± 0,2) y la cobertura a 100 cm (media = 67,5 ± 3,2), no tuvieron variaciones relevantes respecto a los puntos a 100 m (altura: media = 80,0 ± 2,4; n = 92; U = 1.099 p = 0,5. Cobertura a 30 cm: media = 99,5 ± 0,2; U = 1.143,5; p = 0,7. Cobertura a 100 cm: media = 72,1 ± 1,6; U = 998; p = 0,2).

En general, el área de uso potencial para la anidación, determinada a partir de la función kernel, alcanzó sus menores valores en los años 2005 (17,5 km2) y 2006 (16,7 km2), mientras que para el 2007 (30,3 km2) aumentó considerablemente. Los nidos de grullas que se encontraban activos simultáneamente se distribuyeron a distancias cercanas a los 1.300 m. La distancia mínima fue de 330 m aproximadamente, y los nidos vecinos más alejados entre sí se encontraron alrededor de los 2.800 m (tabla 2). El análisis comparativo de las distancias

entre nidos activos simultáneos entre los años 2005 y 2007 no arrojó diferencias estadísticamente significativas (t = 1,2; p = 0,2).

El área de influencia de los nidos fue diferente para cada año, extendiéndose como promedio hasta los 2 km2, con una variación desde los 0,5 km2 hasta los 8 km2 (tabla 2). Para el año 2005 se obtuvo la menor área, y representó alrededor del 43,5% del área estimada para el 2007.

Para el análisis del macrohábitat, en un radio de 100 m alrededor de los nidos y puntos aleatorios, la frecuencia de aparición del herbazal de ciénaga fue mayor que el resto de los elementos del paisaje. Los canales menores y mayores, así como los caminos, tuvieron una frecuencia de aparición semejante y son los otros elementos que aparecen a los 100 m. Sin embargo, en el contorno de los puntos aleatorios se incorporaron los bosques, las lagunas, el herbazal con casuarinas y con palmas y no aparecieron los caminos y los canales mayores (fig. 2). En los radios superiores a los 100 m apareció el cañaveral, el herbazal con palmas y con casuarinas, y disminuyó la frecuencia de aparición del herbazal notablemente. En los puntos aleatorios aparecieron los caminos y los canales mayores y la frecuencia del herbazal se comportó semejante a los nidos. A pesar de las ligeras diferencias, no se encontró significación estadística en cuanto a las frecuencias de los elementos del paisaje, analizados para nidos y puntos aleatorios tanto a 100 m como a mayores radios (p > 0,05).

Los resultados del análisis del porcentaje de área que ocupa cada elemento del paisaje hasta los 100 m del nido, mostraron solamente la ocupación por herbazal de ciénaga. Para los puntos aleatorios esta misma área estuvo representada por un porcentaje similar de herbazal, herbazal con casuarina y herbazal con palmas, y en menor proporción aparecieron los bosques (fig. 3). En la medida que aumentó la escala de

Animal Biodiversity and Conservation 33.1 (2010)

25

100% 90% 70% 60%

Nidos

Frecuencia

80%

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

100 m

400 m

Radios

700 m

1.000 m

100%

Herbazal

90%

Bosque Puntos aleatorios

Frecuencia

80% 70% 60% 50% 40% 30% 20%

Canal menor Canal mayor Caña Palmares Casuarinas

10% 0%

Laguna

100 m

400 m

Radios

700 m

1.000 m

Caminos

Fig. 2. Frecuencia de aparición de distintos elementos del paisaje en diferentes áreas alrededor de los nidos de Grus canadensis nesiotes y de puntos aleatorios, Refugio de Fauna El Venero (Ciego de Ávila, Cuba).

Fig. 2. Frequency of appearance of the distinct landscape elements in different areas around Grus canadensis nesiotes nests and random points, Wildlife Refuge El Venero (Ciego de Avila, Cuba).

muestreo se incorporaron los bosques, cañaverales, y los otros dos tipos de herbazales, pero siempre se mantuvo el porcentaje de herbazal por encima del resto de los elementos paisajísticos alrededor de los nidos. Para los puntos aleatorios el área de herbazal se mantuvo estable y menor que en los nidos, y hubo aumento del porcentaje de lagunas, bosques y cañaverales y disminución del porcentaje de herbazal con palmas. Para este estudio las mayores diferencias del área disponible para la anidación en el humedal entre nidos y puntos aleatorios, se encontraron a distancias radiales menores a los 400 m. Las diferencias estadísticamente significativas se encontraron entre el porcentaje de herbazal presente hasta los 100 m (mayor en nidos; z = 3,55; p = 0,0004) y de lagunas presentes hasta los 1.000 m (mayor en puntos aleatorios; z = –2,99; p = 0,003).

El análisis de la distancia desde los nidos a elementos del paisaje arrojó diferencias estadísticas solo para la distancia al bosque. El valor medio de esta distancia desde los nidos fue aproximadamente el doble de la distancia desde puntos aleatorios (tabla 3).

Los resultados del índice estandarizado de selección sugirieron una selección para el herbazal (tabla 4). Esta selección, estadísticamente significativa (x2 = 23,4; p = 0,0003), apoyó los resultados anteriores respecto a la composición del paisaje en el sitio de anidación.

Discusión Entre los parámetros de la estructura de la vegetación alrededor de los nidos, la altura y la cobertura a

26

Ferrer Sánchez et al.

100% 80% 70% 60%

Nidos

Porcentaje de área

90%

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

100 m

100%

400 m Radios

700 m

1.000 m

80%

Puntos aleatorios

Porcentaje de área

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

Herbazal Bosque Laguna Caña Palmares Casuarinas

100 m

400 m Radios

700 m

1.000 m

Fig. 3. Porcentaje del área que ocupan varios elementos del paisaje a diferentes escalas espaciales alrededor de nidos de Grus canadensis nesiotes y de puntos aleatorios, Refugio de Fauna El Venero (Ciego de Ávila, Cuba).

Fig. 3. Percentage of area that occupied landscape elements at different spatial scales around Grus canadensis nesiotes nests and random points, Wildlife Refuge El Venero (Ciego de Avila, Cuba).

100 cm tuvieron valores diferentes a varias distancias de estos, que sugieren la selección de un sitio de anidación dentro del herbazal. La vegetación circundante al sitio seleccionado para construir el nido puede proteger a las grullas de los depredadores y limita su visibilidad ante otras parejas (Littlefield, 2001), ya que la altura y densidad de esta vegetación aumenta en la medida que se aleja del nido, a nivel de microhábitat. Este punto, a la vez, debe facilitar la entrada del ave al nido y la visibilidad necesaria para detectar cualquier situación de peligro potencial (Walkinshaw, 1949). Bennett (1978) obtuvo resultados similares y apoya la idea de selección de sitios en los cuales la altura y la densidad de la vegetación permitan el movimiento de las grullas.

El análisis a una escala espacial mayor (100 m) no mostró ninguna tendencia notable entre el área usada para la anidación y las zonas disponibles. La aparente homogeneidad en el área puede indicar que

las grullas, a esta escala, no buscan sitios diferentes respecto a la estructura disponible de la vegetación.

Esta homogeneidad espacial en las áreas de anidación fue reportada también por Dwyer (1990) para G. c. pratensis, al comparar la estructura de la vegetación alrededor de los nidos con puntos aleatorios ubicados en sitios sin anidación. Sin embargo, Watanabe (2006) le atribuye importancia a la altura de la vegetación en las áreas de anidación de G. c. canadensis, al ser mayor el valor medio de esta variable y estadísticamente significativo respecto a los puntos aleatorios en las zonas sin anidación. Walkinshaw (1973) y Bennett (1988) concluyen que las especies de plantas son sólo un componente pequeño en la selección del área de anidación, comparado con la importancia de la estructura de la vegetación.

Los resultados obtenidos pueden sugerir también que la similitud estructural de la vegetación en las áreas no utilizadas contribuye a la disponibilidad de

Animal Biodiversity and Conservation 33.1 (2010)

27

Tabla 3. Distancia medida desde los nidos de Grus canadensis nesiotes y los puntos aleatorios a diferentes elementos del paisaje a nivel de macrohábitat, durante los años 2005 al 2007, Refugio de Fauna El Venero (Ciego de Ávila, Cuba).

Table 3. Distance measured from Grus canadensis nesiotes nests and random points to different landscape elements at a macrohabitat level, from 2005 to 2007, Wildlife Refuge El Venero (Ciego de Avila, Cuba).

Elementos del paisaje Distancias (m)

Nidos

Puntos aleatorios

U de Mann–Whitney

Media ± ES

n

Media ± ES

n

A caminos

523,7 ± 59,11

23

508,4 ± 47,71

24

0,17

0,86

A canales menores

313,1 ± 34,51

26

333,9 ± 42,90

21

-0,41

0,68

A canales mayores

502,1 ± 62,21

18

552,7 ± 80,99

11

-0,67

0,50

A bosques

461,9 ± 45,20

27

236,9 ± 26,38

27

3,59

0,0003

áreas óptimas para las parejas que conquistan nuevos territorios. Por lo tanto, si existe área disponible en el humedal con iguales características a los hábitats de anidación, entonces este ecosistema podría soportar una carga mayor de parejas reproductoras, y la población podría tender al crecimiento. Para este análisis también se debe tener en cuenta que esta población está sometida a presiones como la territorialidad y la experiencia de los adultos, que pueden limitar la utilización del hábitat disponible. A esto se suman algunos factores espaciales como la distancia entre nidos activos simultáneos y la dispersión de nidos dentro del humedal, que pueden influir en la selección del área de anidación.

La distribución de los nidos de G. c. nesiotes dentro del humedal estuvo condicionada, en parte, por la disponibilidad de hábitat de herbazal y la distancia entre nidos activos simultáneamente. Esta distancia entre nidos en áreas abiertas, como los herbazales, fue menor que la reportada por Gálvez et al. (2005) para la isla de la Juventud (2,9 a 6,0 km). Estas diferencias podráin relacionarse con las características de los ecosistemas, las cuales favorecen en cobertura y altura del estrato herbáceo para la población en estudio y en la frecuencia de aparición de arbustos para la población de la isla de la Juventud. Resultados similares fueron reportados por Dwyer (1990), con distancias mínimas sorprendentes de 72 m. Thompson (1970) informó sobre distancias mayores de 36,5 km, lo que puede estar enmascarado por factores como la calidad de los hábitats disponibles.

El área de influencia de los nidos de G. c. nesiotes estuvo relacionada a la distancia entre nidos activos simultáneos, y tuvo valores menores que los referidos para G. c. canadensis (21,9 km2) y G. leucogeranus (41,9 km2) (Watanabe, 2006). El área potencial para la anidación de esta subespecie incluye elementos del paisaje que no fueron utilizados por las grullas para la anidación. Sin embargo, la productividad no

z

p

sólo depende de la presencia de hábitats adecuados para anidar, sino de la proximidad de otros hábitats de alimentación con fuentes de agua disponible (Depkin et al., 1994).

La composición del paisaje en las áreas alrededor de los nidos mostró una mayor frecuencia y proporción de herbazal de ciénaga respecto a los puntos aleatorios. Este resultado apoya la idea de que la subespecie cubana, en el área de estudio, construye sus nidos en áreas con predominio de herbazal.

Tabla 4. Índice estandarizado de selección aplicado a la proporción de los diferentes elementos del paisaje en los nidos de Grus canadensis nesiotes y en puntos aleatorios, a nivel de macrohábitat, durante los años 2005 al 2007, Refugio de Fauna El Venero (Ciego de Ávila, Cuba).

Table 4. Standardized selection index applied to the proportion of the different landscape elements in Grus canadensis nesiotes nests and random points, at macrohabitat level, from 2005 to 2007, Wildlife Refuge El Venero (Ciego de Avila, Cuba).

Categoría

Índice

ES

LC 95%

Herbazal

0,29

0,27

0,9–2,3

Bosque

0,15

0,30

0,02–1,6

Laguna

0,12

0,32

0,0–1,49

Cañaveral

0,12

0,32

0,0–1,49

Herbaza–palma

0,20

0,16

0,2–1,05

Herbazal–casuarina 0,11

0,60

0,0–2,69

28

Según lo observado, estas aves no construyen los nidos en sitios próximos a lagunas y bosques. A partir de los 100 m es que se pueden encontrar estos elementos, los cuales pueden poner en riesgo la supervivencia de huevos, crías y adultos, por el riesgo de inundación y depredación de los huevos, además de que los bosques no les reportan recursos alimentarios (Urbaneck & Bookhout, 1992). Los herbazales deben ser considerados elementos prioritarios de conservación, por la importancia que conlleva su uso como sitio de anidación de G. c. nesiotes, en el Refugio de Fauna El Venero.

La selección del nido, al parecer, parte desde sitios completamente descubiertos de vegetación arbustiva y arbórea, en la medida que va aumentado la distancia a partir de este punto van apareciendo en mayor proporción combinaciones de herbazal con casuarinas, con palmas y el bosque. Después de estos, aparecen los cañaverales y áreas con otros sembrados que son fuentes de alimentación para los adultos, pero a la vez contienen depredadores que afectan potencialmente a los huevos y crías. Por lo tanto, las mayores diferencias entre nidos y puntos aleatorios se encuentran a distancias por debajo de los 400 m, y a partir de distancias mayores se hace más homogénea el área de los nidos respecto al resto del área analizada en el humedal. Watanabe (2006) obtuvo resultados semejantes para G. c. canadensis, y supone que la selección está determinada por la presencia de áreas moderadamente húmedas, fuentes de agua alrededor de los nidos con 5,5 cm de profundidad y una vegetación de 20 cm de altura.

El análisis general del paisaje mostró una relación inversa entre las escalas de estudio y las probabilidades de encontrar diferencias entre el área de nidos y el área de puntos aleatorios. Es posible que la superposición entre estas áreas a escalas espaciales grandes refleje la heterogeneidad del paisaje, al medir las mismas características en ambas áreas.

Es necesario recordar para esta investigación, que el aumento de la escala de estudio conlleva una disminución de la disponibilidad de hábitat, lo que trae confusiones en el análisis de los resultados (Baker et al., 1995).

Agradecimientos Se les agradece a los técnicos del área protegida El Venero por la ayuda brindada en la toma de los datos de campo. A la organización Platte River Whooping Crane Maintenance Trust, Inc. por el equipamiento donado para el trabajo en el humedal y el apoyo financiero para el entrenamiento en Sistemas de Información Geográfica. Al grupo de ordenamiento territorial del CIBNOR por el curso impartido sobre las herramientas de SIG. Referencias Atienza, J. C., 1994. La utilización de índices en el estudio de la selección de recursos. Ardeola, 41:

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173–175.

Baker, B. W., Cade, C., Mangus, W. L. & McMillen, J. L., 1995. Spatial analysis of Sandhill Crane nesting habitat. J. Wildl. Manage., 59: 752–758.

Bennett, A. J., 1978. Ecology and status of greater sandhill cranes in southeast Wisconsin. Tesis de Maestría, Universidad de Wisconsin.

– 1988. Habitat use by Florida sandhill cranes in the Okefenokee Swamp, Georgia. Proc. 1988 North Am. Crane Workshop: 121–129.

Bennett, A. J. & Bennett, L. A., 1990. Productivity of Florida sandhill cranes in the Okefenokee Swamp, Georgia. J. Field Ornith., 61(2): 224–231.

Bishop, M. A., 1988. Factors affecting productivity and habitat use of Florida sandhill cranes (Grus canadensis pratensis): an evaluation of three areas in Central Florida for a nonmigratory population of whooping cranes (Grus americana). Tesis doctoral, Universidad de la Florida.

Cueto, V. R., 2006. Escalas en Ecología: su importancia para el estudio de la selección de hábitat en aves. Hornero, 21(1):1–13.

Depkin, F. C., Brandt, L. A. & Mazzotti, F. J., 1994.

Nest sites of Florida sandhill cranes in Southwestern Florida. Fla. Field Nat., 22(2): 39–47 Dwyer, N. C., 1990. Nesting ecology and nest–site selection of Florida sandhill cranes. Tesis de Maestría, Universidad de La Florida.

Gálvez, X., 2002. Distribución y abundancia de Grus canadensis nesiotes en Cuba. Uso de hábitat y reproducción de una población de esta especie en la Reserva Ecológica Los Indios, Isla de la Juventud. Tesis doctoral, Universidad de la Habana.

Gálvez, X., Berovides, V. & Chávez–Ramírez, F., 2005. Nesting Ecology and Productivity of the Cuban Sandhill Crane on the Isle of Youth, Cuba.

Proc. North Am. Crane Workshop, 9: 225–236.

Gálvez, X., Berovides, V., Wiley, J. W. & Rivera, J., 1999. Population size of Cuban Parrots Amazona leucocephala and Sandhill Cranes Grus canadensis and community involvement in their conservation in northern Isla de la Juventud, Cuba. Bird Conservation International, 9: 97–112.

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"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

Animal Biodiversity and Conservation 33.1 (2010)

31

Evaluación de estimadores no paramétricos de la riqueza de especies.

Un ejemplo con aves en áreas verdes de la ciudad de Puebla, México J. A. González–Oreja, A. A. de la Fuente–Díaz–Ordaz, L. Hernández–Santín, D. Buzo–Franco & C. Bonache–Regidor González–Oreja, J. A., De la Fuente–Díaz–Ordaz, A. A., Hernández–Santín, L., Buzo–Franco, D. & Bonache– Regidor, C., 2010. Evaluación de estimadores no paramétricos de la riqueza de especies. Un ejemplo con aves en áreas verdes de la ciudad de Puebla, México. Animal Biodiversity and Conservation, 33.1: 31–45.

Abstract Assessing non–parametric estimators of species richness. A case study with birds in green areas of the city of Puebla, Mexico.― Our objective was to evaluate the performance of non–parametric estimators of species richness with real data. During the 2003 breeding season, bird communities were sampled in two green areas in the city of Puebla (Mexico), and the corresponding sample–based rarefaction curves were obtained. Mean data were adjusted to two non–asymptotic and seven asymptotic accumulation functions, and the best model was selected by means of reliability criteria in information theory. The cumulative Weibull and the Beta–P functions were the best–fit models. Bias, precision and accuracy of five non–parametric estimators of species richness (ICE, Chao 2, Jackknife 1, Jackknife 2, and Bootstrap) were then assessed for increasing sampling efforts (1–53 sampling units) against the asymptote of the selected accumulation functions. All the non–pa� rametric estimators here evaluated underestimated true richness most of the time, specially in one of the sites. However, after combining data from the two assemblages, only ICE, and Jackknife 1 and 2 exhibited bias below 10% with different sampling efforts, and only Jackknife 1 was globally accurate (scaled mean squared error x 100 < 5%, even with low sampling efforts, ca. 20% of the total). Therefore, we propose using the Jackknife 1 non–parametric estimator as a lower bound to measure bird species richness in urban sites similar to those in the present study.

Key words: Accuracy, Bias, Biodiversity, Birds, Inventories, Jackknife, Precision, Urbanization.

Resumen Evaluación de estimadores no paramétricos de la riqueza de especies. Un ejemplo con aves en áreas verdes de la ciudad de Puebla, México.― Nuestro objetivo fue evaluar el desarrollo de estimadores no paramétricos de la riqueza de especies con datos reales. Durante la temporada de cría de 2003 censamos las comu� nidades de aves en dos áreas verdes de la ciudad de Puebla (México), y obtuvimos las correspondientes curvas de rarefacción, que fueron ajustadas a dos funciones de acumulación de especies no asintóticas y siete asintóticas. Según criterios de la teoría de la información, la función de acumulación de Weibull o la Beta–P fueron las que mejor describieron estas curvas de acumulación, y asumimos que sus asíntotas estimaron la riqueza real en los dos sitios. Después evaluamos el sesgo, la precisión y la exactitud de cinco estimadores no paramétricos de la riqueza de especies (ICE, Chao 2, Jackknife 1, Jackknife 2 y Bootstrap) para esfuerzos de muestreo crecientes (1–53 unidades de censo). Todos los estimadores no paramétricos aquí evaluados subestimaron la riqueza asintótica la mayor parte del tiempo, en especial en una de las comunidades. Sin embargo, tras combinar los datos de los dos sitios, sólo ICE, Jackknife 1 y Jackknife 2 mostraron sesgos menores al 10% con algún esfuerzo de muestreo, aunque únicamente Jackknife 1 tuvo una exactitud global alta (error medio relativo al cuadrado x 100 < 5%), incluso con esfuerzos de muestreo bajos (cerca del 20% del total de las unidades de censo). En conclusión, proponemos que el estimador no paramétrico Jackknife 1 puede usarse como un límite inferior de la riqueza de especies de aves en áreas urbanas similares a las de nuestro estudio.

Palabras clave: Exactitud, Sesgo, Biodiversidad, Aves, Inventarios, Jackknife, Precisión, Urbanización.

ISSN: 1578–665X

© 2010 Museu de Ciències Naturals

32

González–Oreja et al.

(Received: 12 VIII 09; Conditional acceptance: 18 XII 09; Final acceptance: 1 III 10) José Antonio González–Oreja, Arturo Andrés de la Fuente–Díaz–Ordaz, Lorna Hernández–Santín, Daniela Buzo–Franco & Carolina Bonache–Regidor, Depto. de Ecosistemas. NEIKER–Tecnalia, Inst. Vasco de Investigación y Desarrollo Agrario, Parque Tecnológico Bizkaia, 48160 Derio, España (Spain).

Corresponding author: J. A. González–Oreja. E–mail: jgonzorj@hotmail.com

Animal Biodiversity and Conservation 33.1 (2010)

Introducción Las medidas de la biodiversidad cumplen una función primordial en la evaluación del impacto de las activida� des humanas sobre los sistemas ecológicos, y se han utilizado como un "barómetro" del estado general de los ecosistemas (Leitner & Turner, 2001). Teóricamente, la forma más directa e intuitiva de medir la biodiversi� dad es la riqueza (Sarkar, 2002; Magurran, 2004): el número de especies que habitan en una comunidad local, temporal y espacialmente homogénea. Ahora bien, en la práctica, la medida exacta y precisa de la riqueza no es una labor sencilla (Magurran, 2004), pues el número de especies observadas en una comunidad aumenta con el esfuerzo de muestreo invertido en la misma. Por ello, la riqueza debería determinarse sólo a partir de inventarios completos, lo que generalmente es poco práctico o muy difícil de lograr, si no imposible.

Entonces, la mejor opción consiste en estimar el número de especies a partir de un muestreo previo (la ventana a través de la cual observamos el mundo ecológico; Leitner & Turner, 2001), incluso para organismos relati� vamente bien conocidos (Colwell & Coddington, 1994), como las aves (Walther & Martin, 2001).

Se han propuesto muchos métodos que estiman la riqueza, pero las aproximaciones más utilizadas en ecología son las siguientes (Colwell & Coddington, 1994; Chazdon et al., 1998): (a) extrapolación de la curva de acumulación de especies como una función del esfuerzo de muestreo, donde se asume que la riqueza total es el número de especies que se encontrarían con un esfuerzo infinito (asíntota); (b) estimación del número de especies aún no observadas, después de ajustar las abundancias de las especies a modelos de distribución paramétrica (como los descritos por la serie logarítmica, la serie log–normal, o la de Poisson log–normal) y (c) uso de estimadores no paramétricos de la riqueza de especies, que se basan en el estudio de las especies raras y permiten estimar el número de nuevas especies a partir de las relaciones de abundancia o incidencia de las especies ya detectadas en el muestreo.

Algunos autores han considerado a los estimado� res no paramétricos como el avance más importante en la medida de la biodiversidad en los últimos tiempos (Magurran, 2004). Entre ellos están los estimadores desarrollados por Chao (1984) basados en la abundancia o en la incidencia de las especies (Colwell & Coddington, 1994; Leitner & Turner, 2001; Chao, 2005), y los métodos basados en el remues� treo, como los estimadores de tipo Jackknife y las técnicas Bootstrap (Palmer, 1990). Estas técnicas son adiciones valiosas al conjunto de herramientas con que cuentan los ecólogos para cuantificar la biodiversidad (Longino et al., 2002) y evaluar las consecuencias de las actividades humanas sobre los ecosistemas (Walther & Martin, 2001). Aunque se han realizado ya algunas valoraciones de su desem� peño (véase Walther & Moore, 2005), se necesitan nuevos estudios comparados de datos empíricos bajo la mayor diversidad posible de condiciones ambientales (Colwell & Coddington, 1994; Gotelli & Colwell, 2001; Leitner & Turner, 2001; Walther & Martin, 2001; Longino et al., 2002; Magurran, 2004).

33

El impacto de las actividades humanas sobre los sistemas ecológicos queda bien ejemplificado por los cambios en los usos del suelo derivados de la urba� nización, cuyas consecuencias representan una seria amenaza a la conservación de la biodiversidad en todo el mundo (McKinney, 2002), y podrían suponer la erradicación de un elevado número de especies de los hábitats afectados (Marzluff et al., 2001a; Chace & Walsh, 2006), en especial en los países en vías de desarrollo situados en latitudes tropica� les (Marzluff et al., 2001b). Ante esta situación, los ecólogos se enfrentan a las tareas de cuantificar el impacto de la urbanización sobre la biodiversidad, y de proponer medidas que permitan conservar la mayor biodiversidad posible en los ecosistemas urbanos (Marzluff et al., 2001a; Miller et al., 2001; Lim & Sodhi, 2004). En muchos casos, las áreas verdes urbanas representan los últimos espacios "naturales" en las grandes ciudades, y ofrecen un refugio potencial a una fracción de tamaño generalmente desconocido de la diversidad original (McDonnell & Pickett, 1990; Miller & Hobbs, 2002). Es el caso de las aves, que han sido consideradas como bioindicadores de los efectos de la urbanización (Savard et al., 2000). En este artículo, evaluamos el comportamiento de varios estimadores no paramétricos de la riqueza de espe� cies en comunidades de aves de áreas verdes en un país con una población creciente en asentamientos urbanos, México (CONABIO, 2006).

Materiales y métodos Área de estudio y muestreos de aves El estudio se realizó en dos áreas verdes de la ciudad de Puebla, capital del Estado de Puebla (México): el Parque Ecológico "Revolución Mexica� na" (Sitio 1; 56,5 ha), un área de esparcimiento de la población que cuenta con superficies arboladas dominadas por Cassuarina equisetifolia, Fraxinus udhei y Pinus sp. pl.; y el campus de la Universidad de las Américas Puebla (Sitio 2; 70,2 ha), un área verde rica en edificios dispersos en una matriz de jardines intervenidos y manchas arboladas, donde los árboles dominantes son C. equisetifolia, Pinus montezumae y Cupressus lindleyi. Para una mayor descripción de estos sitios, véase Barillas Gómez (2004) y González–Oreja et al. (en prensa).

Entre el comienzo de junio y principios de agosto de 2003, en cada uno de los dos sitios completamos 53 estaciones de escucha cualitativa (radio = 25 m; tiempo = 10 min; para detalles sobre el método, véase Fonderflick, 1998). Como máximo, cada día de trabajo de campo se realizaron nueve unidades de muestreo en un solo sitio, que estuvieron separadas por un mínimo de 250 m; todos los censos se iniciaron entre las 07:50 y las 10:50 am, registrando la presencia de todas las especies de aves vistas u oídas en cada una de las estaciones de escucha (Columbiformes, Cuculiformes, Piciformes y Passeriformes), sin incluir a las que sólo pasaban volando por encima del punto de muestreo. Para más información sobre la compo�

34

sición y estructura de las comunidades de aves en éstas y otras áreas verdes de la ciudad de Puebla, véase De la Fuente Díaz Ordaz (2003), Hernández Santín y Buzo Franco (2004) y González–Oreja et al. (2007, en prensa).

Estimas de la riqueza mediante extrapolación Para evaluar con datos empíricos el desarrollo de estimadores de riqueza es necesario tener una idea previa del número real de especies en la comunidad (Leitner & Turner, 2001; Walther & Moore, 2005).

Ahora bien, para determinar la riqueza real mediante el muestreo éste tiene que ser completo; en caso contrario, se puede ajustar la curva de riqueza acu� mulada a alguno de los modelos de acumulación de especies disponibles en la bibliografía, y extrapolar para un esfuerzo de muestreo infinito (Soberón & Llorente, 1993; Díaz–Francés & Soberón, 2005). En teoría, las funciones de acumulación de especies al� canzan una asíntota cuando la probabilidad de añadir una nueva especie al inventario alcanza finalmente el cero; entonces, se asume que la asíntota equivale a la riqueza real, sujeta al error de muestreo (incerti� dumbre) derivado del ajuste a los datos observados.

Sin embargo, son no asintóticas si dicha probabilidad nunca se hace nula (Soberón & Llorente, 1993).

Con los datos obtenidos en cada sitio construimos primero la curva suavizada de acumulación de espe� cies observadas (i.e., la curva de rarefacción basada en muestras, que representa la esperanza estadística del número de especies observado al remuestrear en el total de unidades de muestreo de cada sitio con esfuerzos crecientes; Gotelli & Colwell, 2001); así, obtuvimos el valor medio de especies observadas con 1, 2, 3… n unidades de muestreo (Sobs Mao Tao; Colwell et al., 2004). Después, ajustamos las curvas obtenidas a un conjunto de R = 9 modelos matemáticos, sin y con asíntota, ampliamente usados en estudios de ecología y biogeografía (Soberón & Llorente, 1993; Flather, 1996; Tjorve, 2003): los modelos potencial y exponencial (no asintóticos), y los modelos descritos por las funciones de Clench, exponencial negativa, logística, de Morgan–Mercer– Flodin, de Chapman–Richards, acumulada de Weibull y Beta–P (asintóticos; tabla 1).

Siguiendo una sugerencia de Walther & Moore (2005), utilizamos técnicas de selección de modelos basadas en la teoría de la información de Kullback– Leibler (K–L) y en métodos de máxima verosimilitud, que tienen en cuenta el principio de parsimonia, para obtener los modelos que mejor describen los datos (para una aproximación similar, véase Jiménez–Valverde et al., 2006; González–Oreja et al., 2010). Realizamos los ajustes de las curvas suavizadas de riqueza acumulada a los modelos antes citados usando técnicas de regresión no lineal implementadas en los programas Statistica vers. 7.0 (StatSoft, 2004) y GraphPad Prism vers. 5 (Motulsky & Christopoulos, 2003). En la mayoría de los casos, usamos los algoritmos "Simplex" o "Simplex & qua� si–Newton", pero en algunos modelos aplicamos los algoritmos "Hooke–Jeeves & quasi–Newton"

González–Oreja et al.

o "Rosenbrock & quasi–Newton". Para evaluar la idoneidad de cada modelo a los datos de cada si� tio calculamos el Criterio de Información de Akaike corregido para muestras pequeñas (AICc); AICc es una medida de la cantidad de información K–L que se pierde al sustituir una colección de datos reales por un modelo más sencillo que los describe: es más plausible el ajuste de los datos al modelo con la menor pérdida de información (el menor valor AICc). A partir de las diferencias de AICc entre cada modelo y el mejor evaluado (DAICc), calculamos la verosimilitud mediante el peso de Akaike; los pesos de Akaike son una medida de la evidencia a favor de que el modelo i sea el mejor del conjunto R, teniendo en cuenta la pérdida de información K–L. Finalmente, asumimos que la asíntota del modelo mejor evaluado es la estima más acertada de la riqueza real en cada sitio de estudio. Para una explicación detallada de las técnicas basadas en la teoría de la información, así como para las fórmulas matemáticas de los cálculos AIC y relacionados, véase Anderson et al. (2000), Burnham & Anderson (2001) y Hobbs & Hilborn (2006).

Estimadores no paramétricos Para esfuerzos de muestreo crecientes (de 1 a 53 unidades de muestreo), calculamos las curvas suavizadas de acumulación de especies estimadas según los siguientes estimadores no paramétricos (Chazdon et al., 1998; Colwell, 2006): el estimador de cobertura basado en la incidencia (ICE); el es� timador Chao 2; los estimadores de tipo Jackknife de primer y segundo orden (Jack 1 y Jack 2), y el estimador de tipo Bootsrap. ICE se basa en el nú� mero de especies raras (las observadas en menos de 10 unidades de muestreo), mientras que Chao 2 tiene en cuenta a las especies observadas en exac� tamente una y dos unidades de muestreo; Jack 1 es una función del número de especies presentes en sólo una unidad de muestreo, mientras que Jack 2 considera también a las especies presentes en dos unidades de muestreo. Eliminamos el posible efecto del orden en el que se añaden las muestras a la curva mediante remuestreo aleatorio en el conjunto de unidades de muestreo de cada sitio (Colwell & Coddington, 1994). Seguimos a Walther & Moore (2005) y Colwell (2006), y en todos los cálculos que implican múltiples reordenaciones de muestras usamos 100 aleatorizaciones, con reemplazamiento.

Realizamos todas las estimas mediante el programa EstimateS vers. 8.0 (Colwell, 2006), y exportamos los resultados de todas las reordenaciones aleatorias a un archivo de Microsoft ® Office Excel donde calcu� lamos el sesgo, la precisión y la exactitud de cada estimador para esfuerzos de muestreo crecientes.

Evaluación del desempeño de los estimadores no paramétricos Un estimador robusto y exacto no debería ser sensible al tamaño de la muestra, y por encima de cierto umbral de unidades de muestreo debería permanecer más

Animal Biodiversity and Conservation 33.1 (2010)

35

Tabla 1. Estructura de los modelos de acumulación de especies no asintóticos y asintóticos, ajustados a las curvas de rarefacción de cada área de estudio. En todos los casos la variable dependiente [S(x)] fue la riqueza observada a cumulada (Sobs Mao Tao; valor medio obtenido tras 100 remuestreos con reemplazamiento), mientras que la variable independiente (x) fue el esfuerzo de muestreo (1–53 unidades de censo); k es el número de parámetros de cada modelo (a–d).

Table 1. Structure of non–asymptotic and asymptotic species accumulation models, adjusted to the rarefaction curves for each study site. In all cases the dependent variable [S(x)] was the accumulated observed richness (Sobs Mao Tao: mean value obtained after resampling 100 times with replacement), whereas the independent variable (x) was sampling effort (1–53 sampling units); k is the number of parameters of each model (a–d).

Modelo

S(x)

k

Asíntota

No asintóticos Potencial

axb

2

–

Exp

a+blog(x)

2

–

Clench

Clench

ax/(1+bx)

2

a/b

Exponencial negativo

NegExp

a(1–exp(–bx))

2

a

a/(1+exp(–bx+c))

3

a

ax /(b+x )

3

a

Exponencial

Power

Asintóticos

Logístico Morgan–Mercer–Flodin

Log MMF

c

c

Chapman–Richards

CR

a(1–exp(–bx))

3

a

Weibull acumulado

CW

a(1–exp(–bx ))

3

a

Beta–P

a(1–(1+(x/c)d)–b)

4

a

Beta–P

o menos estable alrededor de un valor (la riqueza estimada por el estimador; Chazdon et al., 1998; Leitner & Turner, 2001). Además, un estimador ideal debería alcanzar su propia asíntota mucho antes que la curva de acumulación de especies observadas, y aproximarse a ella de un modo no sesgado (Chazdon et al., 1998; Gotelli & Colwell, 2001; véase también Hortal et al., 2006). Por un lado, seguimos a Colwell & Coddington (1994), Chazdon et al. (1998) y Lon� gino et al. (2002), y representamos gráficamente el valor de cada estimador a lo largo de esfuerzos de muestreo crecientes, inspeccionando su aproximación a la asíntota de la riqueza observada en cada sitio.

Por otro lado, y también para esfuerzos de muestreo crecientes, calculamos para cada sitio las siguientes medidas de desempeño de los estimadores (véase tabla 3 para las ecuaciones, y Walther & Moore, 2005 para una explicación más detallada): (a) sesgo, expresado como el porcentaje de la riqueza real de especies (PAR = 100 x SME + 100), donde SME es el error medio relativo de las estimas obtenidas me� diante el remuestreo con reemplazamiento; un valor PAR > 100% implica la sobreestima de la riqueza real, mientras que un valor PAR < 100% indica que el estimador subestima; (b) precisión, medida como el coeficiente de variación (CV) de todos los valores estimados en cada esfuerzo de muestreo; CV mide la repetibilidad de las estimas independientes, sin

c

c

tener en cuenta que el estimador sea sesgado o no y (c) exactitud, o la distancia global que separa al valor estimado del real, medido como el error medio relativo al cuadrado de las 100 estimas obtenidas en cada esfuerzo de muestreo (SMSE); un SMSE bajo indica que, en promedio, las estimas individuales están próximas al valor real, lo que se asocia a un sesgo bajo y una precisión alta; por lo tanto, la exactitud es generalmente la característica más deseable de las tres medidas consideradas (Hellmann & Fowler, 1999; Walther & Moore, 2005). Finalmente, evaluamos el desempeño global de los estimadores no paramétricos promediando los valores obtenidos en los Sitios 1 y 2.

Como el esfuerzo de muestreo fue el mismo en ambos sitios, para las medidas de sesgo (PAR) y exactitud (SMSE) calculamos la media aritmética (Walther & Moore, 2005), mientras que para la medida de preci� sión (CV) calculamos la media geométrica (una forma correcta de promediar variables que se expresan como porcentajes o proporciones; Zar, 1999).

Resultados Breve descripción de las avifaunas En total, en el Sitio 1 se observaron 15 especies de aves, de las que 8 estuvieron presentes en más del

36

González–Oreja et al.

Evaluación de los estimadores. Sitio 1 En el Sitio 1, la curva suavizada de riqueza acumulada perdió gradualmente pendiente al in� crementar el número de unidades de muestreo, tendiendo claramente hacia una asíntota próxima a 15 especies (fig. 1). El número medio de espe� cies registradas en sólo una unidad de muestreo descendió gradualmente desde un valor próximo a 4 con bajos esfuerzos de muestreo hasta un valor final cercano a 1, lo que sugiere la idoneidad de la labor de muestreo (fig. 2). Los nueve modelos de acumulación de especies se ajustaron de modo notable a los datos (coeficientes de determinación, R2, siempre mayores a 90%, que fue la bondad del ajuste del peor modelo: el potencial, no asintótico), y cinco se ajustaron excepcionalmente bien (todos ellos asintóticos: R2 > 99%; tabla 2). El que mejor describió el comportamiento de la riqueza en el Sitio 1 fue el acumulado de Weibull (CW: AICc = –429,8; wi = 0,845), seguido por el Beta–P (bP: AICc = –426,4; wi = 0,155); los demás tuvieron valores AICc claramente mayores, por lo que la evidencia a su favor fue mucho menor (en realidad, despre� ciable: wi < 10–22; tabla 2). Los dos modelos mejor

30 Riqueza (nº de especies)

10% de las unidades de muestreo; el zanate mexicano (Quiscalus mexicanus) fue la especie más frecuente (pues se localizó en el 94,4% de las unidades de muestreo), seguida por la tórtola colalarga (Columbina inca) y el tordo ojo rojo (Molothrus aeneus) (registra� das ambas en el 43,4% de las unidades de muestreo).

Tres especies se encontraron en sólo dos unidades de muestreo (el jilguero dominico, Carduelis psaltria; el gorrión casero, Passer domesticus, y el tordo dorso rufo, Turdus rufopalliatus), y no hubo ninguna especie que se observara en sólo una unidad de muestreo.

En el Sitio 2 se observaron 27 especies, de las que 18 se registraron en más del 10% de las unidades de muestreo; la especie más frecuente también fue el za� nate mexicano (79,3% de las unidades de muestreo), seguida por el mosquero cardenal (Pyrocephalus rubinus, 62,3%), el toquí pardo (Pipilo fuscus, 56,6%) y el cuitlacoche pico curvo (Toxostoma curvirostre; 50,9%). Una especie (el tirano tropical, Tyrannus melancholicus) se observó en sólo dos unidades de muestreo, y cinco más en una única unidad de mues� treo (el carpintero de pechera, Colaptes auratus; una especie de bolsero, Icterus sp.; el reyezuelo sencillo, Regulus calendula; el estornino pinto, Sturnus vulgaris y el chipe corona negra, Wilsonia pusilla).

Sitio 2

25 Sitio 1

20 15 10 5 0

0

10 20 30 40 Esfuerzo de muestreo (nº de censos)

50

Fig. 1. Curvas suavizadas de acumulación de la riqueza observada (curvas de rarefacción basadas en muestras) para las comunidades de aves en Sitio 1 y Sitio 2. En cada caso se muestra el valor medio (y la desviación están� dar, barras de error) del número de especies (Sobs Mao Tao, obtenido tras 100 remuestreos con reemplazamiento), según esfuerzos de muestreo crecientes (1–53 unidades de censo).

Fig. 1. Smooth richness accumulation curves (sample–based rarefaction curves) for bird assemblages in Site 1 and Site 2. In both cases the mean value (and the standard deviation, error bars) of the number of species (Sobs Mao Tao, obtained after resampling 100 times with replacement) are shown, for increasing sampling efforts (1–53 sampling units).

soportados por los datos tuvieron la misma asíntota (15,17; error estándar de la asíntota en el modelo CW = 0,006; intervalo de confianza al 95% para la asíntota en el modelo CW: 15,16–15,18). Asumimos que 15,17 fue la mejor estima disponible de la ri� queza en el Sitio 1; esto confirma la idoneidad del muestreo, pues habríamos observado a la práctica totalidad de las especies presentes (98,9%).

Fig. 2. Smooth richness accumulation curves for the non–parametric estimators ICE, Chao 2, Jack 1, Jack 2, and Bootstrap, for the bird assemblage in Site 1. In each panel the mean values, and the standard deviation (error bars), of the number of species estimated after resampling 100 times with replacement is shown, for increasing sampling efforts (1–53 sampling units). For comparative purposes, each panel also shows the asymptotic richness value estimated by means of the best species accumulation function (upper horizontal line; see table 2), and the value of Sobs Mao Tao (curve below the estimator line). The bottom right panel shows the evolution of the number of species in exactly one and two sampling units.

Animal Biodiversity and Conservation 33.1 (2010)

15

15

10

10

5

5

0

0 Jack 1 20

20

Riqueza (nº de especies)

ICE 20

20

37

15

15

10

10

5

5

0

0 Bootstrap

20

Chao 2

Jack 2

5 4

15

Una unidad de muestreo 3

10 2 5

0

1

0

10

20

30

Dos unidades de muestreo

0 40 50 0 10 20 30 Esfuerzo de muestreo (nº de censos)

40

50

Fig. 2. Curvas suavizadas de acumulación de la riqueza según los estimadores no paramétricos ICE, Chao 2, Jack 1, Jack 2 y Bootstrap, para la comunidad de aves del Sitio 1. En cada panel se muestra el valor medio, y la desviación estándar (barras de error), del número de especies estimado tras 100 remuestreos con reemplazamiento, según esfuerzos de muestreo crecientes (1–53 unidades de censo).

Con propósitos comparativos, en cada panel se muestra el valor de riqueza asintótica estimado según la mejor función de acumulación de especies (línea horizontal superior; véase tabla 2), y el valor de Sobs Mao Tao (curva por debajo de la curva del estimador). El panel inferior derecho muestra la evolución del número de especies presentes en exactamente una y dos unidades de censo.

38

González–Oreja et al.

Tabla 2. Resultados del ajuste de los modelos de acumulación de especies de la tabla 1 a las curvas de rarefacción del Sitio 1 y Sitio 2. Para cada modelo se muestra la suma de cuadrados (SS), el coeficiente de determinación (R2[%]), el valor Criterio de Información de Akaike corregido para muestras pequeñas (AICc), la diferencia de AICc entre cada modelo y el más plausible (DAICc), el peso de Akaike (wi), y la asíntota.

Los valores en cursiva muestran asíntotas por debajo de la riqueza total observada en cada sitio, mientras que los valores en negrita muestran la asíntota del modelo mejor evaluado.

Table 2. Results of the adjustment of the species accumulation models in table 1 to the rarefaction curves from Site 1 and Site 2. For each model, the sum–of–squares (SS), the coefficient of determination (R2[%]), the value of the Akaike Information Criterion corrected for small samples (AICc), the difference in AICc with the most plausible model (DAICc), the Akaike weight (wi), and the asymptote are shown.

Italic values show asymptotes below the total observed richness for each site, whereas bold face values show the asymptote of the best assessed model.

Modelo

SS

R2(%)

AICc

ΔAICc

wi

Asíntota

CW

0,01

99,99

–429,80

0,00

0,845

15,17

Beta–P

0,01

99,99

–426,41

3,39

0,155

15,17

CR

0,09

99,98

–330,22

99,58

15,04

MMF

1,05

99,74

–201,57

228,23

2,3 x 10–50

16,41

Clench

1,19

99,70

–197,19

232,61

2,6 x 10

16,66

NegExp

7,57

98,09

–98,88

330,92

1,2 x 10

14,72

Log

7,88

98,02

–94,56

335,24

1,3 x 10

14,73

Exp

15,29

96,15

–61,64

368,16

9,6 x 10–81

Power

39,56

90,03

–11,26

418,54

1,1 x 10–91

Sitio 1

2,0 x 10

–22

–51 –72 –73

Sitio 2

1

33,33

Beta–P

0,06

99,99

–355,31

0,00

MMF

0,47

99,95

–243,40

111,91

5,0 x 10–25

29,45

CW

2,49

99,72

–155,65

199,67

4,4 x 10–44

26,68

CR

5,65

99,37

–112,13

243,18

Clench

–53

1,6 x 10

25,95

–55

6,67

99,25

–105,61

249,70

5,9 x 10

27,21

Exp

13,13

98,53

–69,72

285,60

9,6 x 10–63

Log

39,81

95,53

–8,68

346,64

5,4 x 10–76

25,10

Pow

51,83

94,18

3,06

358,37

1,5 x 10

NegExp

72,60

91,84

20,92

376,23

2,0 x 10–82

En general, todos los estimadores no paramétricos evaluados estuvieron siempre por encima de los valo� res de riqueza observada en el Sitio 1 (Sobs Mao Tao; fig. 2). Con esfuerzos de muestreo de menos de 5 unidades de muestreo (ca. 10% del total), ICE sobreestimó la riqueza asintótica del Sitio 1 (fig. 2), pero después se mantuvo casi constante y muy próximo a la asíntota de los modelos CW y Beta–P, aunque mostró un ligero sesgo en general negativo (96% < PAR < 100,5; tabla 3). Los estimadores Chao 2, Jack 1, Jack 2 y Bootstrap se aproximaron suavemente a la riqueza asintótica con esfuerzos de muestreo crecientes, aunque Jack 1 y 2 mostraron

–78

24,62

un ligero sesgo positivo (PAR > 100%) a lo largo de gran parte del muestreo (fig. 2, tabla 3). En términos de precisión, ICE fue el peor estimador con esfuerzos de muestreo muy bajos (menos del 20% de las uni� dades de muestreo: CV > 30%), y Jack 2 fue el peor estimador con mayores esfuerzos de muestreo (más del 35% de las unidades de muestreo: CV > 15%, incluso con el 100% del esfuerzo de muestreo); el estimador Bootstrap fue siempre el más preciso, llegando a valores CV < 10% con 30 unidades de muestreo o más (fig. 2, tabla 3).

En el Sitio 1, Jack 1 fue el estimador que alcanzó una exactitud global mayor al 95% con un menor es�

Animal Biodiversity and Conservation 33.1 (2010)

39

Tabla 3. Medidas relativas del desempeño: sesgo, expresado como el porcentaje de la riqueza real estimado (PAR); precisión, expresada como el coeficiente de variación (CV) y exactitud, medida como el error medio relativo al cuadrado (SMSE) de cada estimador no paramétrico ICE, Chao 2, Jack 1, Jack 2 y Bootstrap, en el Sitio 1, Sitio 2 y en promedio. Los promedios de PAR y SMSE son medias aritméticas; los promedios de CV son medias geométricas (Zar, 1999). En todos los casos, se muestran los valores correspondientes para esfuerzos de muestreo crecientes (según unidades de censo (de 5 a 53) y porcentaje del total del muestreo del 9,4 al 100%). En negrita se muestran valores de PAR entre 90 y 110%, o CV < 10%, o SMSE x 100 < 10%. Ecuaciones: PAR = 100 x SME + 100; SME = (1/An)Si (Ei – A); y SMSE = (1/A2n)Si (Ei – A)2, donde A es el valor de la asíntota, n es el número de muestras, y Ei es el valor del estimador en la muestra i. Para más detalles, véase Walther & Moore (2005).

Table 3. Relative performance mesures: bias, expressed as the percent of actual richness (PAR); precision, expressed as the coefficient of variation (CV); and accuracy, expressed as the scaled mean squared error (SMSE) of the non–parametric estimators ICE, Chao 2, Jack 1, Jack 2, and Bootstrap, for Site 1, Site 2, and average. Averages for PAR and SMSE are arithmetic means, averages for CV are geometric means (Zar, 1999). In all cases, values are shown for increasing sampling efforts (from 5 to 53 sampling units, and from 9.4 to 100% of total sampling effort). In bold values of PAR between 90 and 110%, as are values of CV < 10%, and SMSE x 100 < 10%. Equations: PAR = 100 x SME + 100; SME = (1/An)Si (Ei – A); and SMSE = (1/A2n)Si(Ei – A)2, where A is the asymptotic or total species richness, n is the number of samples, and Ei is the estimated species richness for the i sample. For more details, see Walther & Moore (2005).

Nº censos % del total

PAR(%) 5

10

20

CV(%) 30

53

5

10 20 30 53

SMSE x 100 5

10 20 30 53

9,4 18,9 37,7 56,6 100

9,4 18,9 37,7 56,6 100

9,4 18,9 37,7 56,6 100

100,4 98,5 95,8 100,5 99,7

52,8 30,2 17,1 12,1 6,0

28,1 8,8 2,9 1,5 0,4

Chao

76,3 83,4 90,8 96,1 98,0

45,1 26,2 18,9 11,9 6,4

17,5 7,6 3,8 1,5 0,4

Jack 1

75,1 89,6 98,4 104,2 103,3

25,1 19,8 14,5 11,4 7,1

9,7 4,2 2,1 1,6 0,6

Jack 2

85,4 98,2 102,3 107,8 101,4

29,6 26,6 22,5 18,1 15,7

8,5 6,9 5,4 4,4 2,6

Bootstrap

63,6 78,6 90,3 97,1 100,4

22,5 16,7 11,6 9,0 4,8

15,3 6,3 2,0 0,9 0,2

ICE

63,7 67,4 71,8 75,5 80,6

29,1 19,1 2,6 13,1 9,2

16,6 12,3 8,8 7,0 4,3

Chao

256,8 66,3 71,2 74,7 79,3

32,5 27,3 14,8 17,0 11,5

22,1 14,7 9,4 8,0 5,1

Jack 1

58,7 68,8 75,4 78,3 82,9

19,7 16,8 11,8 12,3 8,9

18,4 11,1 6,8 5,6 3,5

Jack 2

63,8 73,8 79,5 80,8 84,5

24,1 22,1 15,8 17,8 14,5

15,5 9,5 5,8 5,7 3,9

Bootstrap

51,3 61,8 69,5 73,4 78,8

17,3 14,4 10,1 9,8 6,7

24,5 15,4 9,8 7,6 4,8

ICE

82,0 83,0 83,8 88,0 90,1

39,2 24,0 14,7 12,6 7,4

22,4 10,6 5,8 4,2 2,3

Chao 2

66,6 74,8 81,0 85,4 88,7

38,3 26,8 16,7 14,2 8,6

19,8 11,1 6,6 4,7 2,8

Jack 1

66,9 79,2 86,9 91,3 93,1

22,2 18,3 13,0 11,8 7,9

14,1 7,7 4,4 3,6 2,1

Jack 2

74,6 86,0 90,9 94,3 93,0

26,7 24,3 18,9 17,9 15,1

12,0 8,2 5,6 5,1 3,2

Bootstrap

57,5 70,2 79,9 85,2 89,6

19,7 15,5 10,8 9,4 5,7

19,9 10,9 5,9 4,2 2,5

Sitio 1 ICE

Sitio 2

Promedio

fuerzo de muestreo: con sólo 10 unidades de muestreo (prácticamente el 20% del total), SMSE x 100 = 4,2%, y descendió aún más hasta un valor final de 0,6% (ta� bla 3). Los demás estimadores tuvieron una exactitud

similar tan sólo con 20 unidades de muestreo o más, excepto Jack 2 (que sólo mostró tal exactitud con esfuerzos de muestreo aún mayores, de 30 unidades de muestreo o más; tabla 3).

40

González–Oreja et al.

Evaluación de los estimadores. Sitio 2 En el Sitio 2, la curva suavizada de riqueza acu� mulada perdió pendiente de modo menos marcado que en el Sitio 1, y la tendencia asintótica no fue tan clara (fig. 1). El número medio de especies observadas en una unidad de muestreo descendió desde cerca de 7 con bajos esfuerzos de muestreo a casi 2,8 al final; el número medio de especies observadas en dos unidades de muestreo no mostró tendencia a descender, y estuvo próximo a 2,5 a lo largo de todo el estudio (fig. 3). Ambas observacio� nes sugieren la presencia de más especies, aún no detectadas. Cinco funciones de acumulación de especies, todas ellas asintóticas, mostraron coeficientes de determinación R2 > 99%, pero sólo una estuvo bien soportada por los datos: el modelo Beta–P (AICc = –355,3; wi = 1); en los demás casos, la evidencia a su favor fue despreciable (tabla 2), lo que revela su poca adecuación a los datos; es más, la asíntota de cuatro modelos estuvo incluso por debajo de la riqueza total observada en el Si� tio 2. La asíntota del mejor modelo fue 33,3 (error estándar de la asíntota en el modelo Beta–P = 0,269; intervalo de confianza al 95% para la asíntota en el modelo Beta–P: 32,79–33,88). Asumimos que 33,3 fue la mejor estima disponible de la riqueza en el Sitio 2; esto refuerza la observación anterior sobre la menor calidad global del muestreo en el Sitio 2 que en el Sitio 1, pues habríamos observado al 81,8% de su riqueza total.

Con esfuerzos de muestreo muy pequeños, ICE tuvo valores PAR > 100% (fig. 3), pero después mostró un comportamiento similar a S obs Mao Tao, aunque siempre por encima (i.e., con menor sesgo). Los estimadores Jack 1, Jack 2 y Boots� trap mostraron un mismo comportamiento, pues crecieron gradualmente hacia su propia asíntota; sin embargo, Bootstrap describió una curva muy similar a Sobs Mao Tao, aunque ligeramente por encima (fig. 3). En el Sitio 2, Jack 2 fue siempre el estimador menos sesgado, aunque sus valores PAR estuvieron sólo entre el 63,8% y el 84,5% de la riqueza asintótica. Con esfuerzos de muestreo muy bajos, el peor estimador en términos de precisión fue ICE (con menos de 5 unidades de muestreo; tabla 3), y Jack 2 con cualquier número mayor de unidades de muestreos; el estimador más preciso fue siempre Bootstrap (17,3% < CV < 6,7%; fig. 3; tabla 3). Con esfuerzos de muestreo de 10 unidades de muestreo o más, el SMSE x 100 de Jack 2 estuvo

siempre por debajo del 10%, y bajó hasta un valor final del 3,9% (tabla 3). Los demás estimadores no paramétricos aquí evaluados tuvieron valores SMSE x 100 < 10% solamente con 20 unidades de muestreo o más (aunque Jack 1 fue un estimador ligeramente menos exacto que Jack 2 con sólo 10 unidades de muestreo: SMSE x 100 = 11,1%).

Evaluación global de los estimadores Tras combinar los datos de los Sitios 1 y 2, sólo tres estimadores mostraron un sesgo menor al 10% con algún esfuerzo de muestreo: ICE (pero sólo con el 100% del esfuerzo de muestreo), Jack 1 (con algo más del 50% de las unidades de muestreo) y Jack 2 (aún con esfuerzos de muestreo tan bajos como el 37,7% de las unidades de muestreo; tabla 3). En ge� neral, todos los estimadores subestimaron la riqueza asintótica, aunque este sesgo disminuyó con mayores esfuerzos de muestreo, y ningún otro mostró sesgos menores del 5%. En términos de sesgo, los peores estimadores fueron Bootstrap y Chao 2 (menores valores PAR; tabla 3).

En términos de exactitud global, el mejor esti� mador fue Jack 1: fue el único de los estimadores evaluados con valores promedio SMSE x 100 < 5% aún con esfuerzos de muestreo sólo ligeramente por encima del 20% del total; su exactitud global aumentó con esfuerzos mayores (por ejemplo, con cerca de la mitad de todas las unidades de muestreo: SMSE x 100 = 3,6%; tabla 3). Después de Jack 1, el siguiente mejor estimador fue Jack 2 (que fue el mejor estimador con esfuerzos de muestreo muy bajos, aunque SMSE x 100 > 10%; tabla 3).

Discusión A pesar de que la biodiversidad es un concepto que no se puede reducir a un único número (Sarkar, 2002; Magurran, 2004), hay razones que sustentan el uso de la riqueza de especies como un indicador ecológico del estado general de los ecosistemas (Hellmann & Fowler, 1999; Dale & Beyeler, 2001).

Pero, los métodos simples para medir la riqueza, como el número de especies observado, dependen de modo muy marcado del tamaño de la muestra, y exhiben generalmente un sesgo negativo (Colwell & Coddington, 1994; Gotelli & Colwell, 2001; Leitner & Turner, 2001). En términos de sesgo, en nuestro estudio la riqueza observada (Sobs Mao Tao) fue

Fig. 3. Smooth richness accumulation curves for the non–parametric estimators ICE, Chao 2, Jack 1, Jack 2, and Bootstrap, for the bird assemblage in Site 2. In each panel the mean value and the standard deviation (error bars), of the number of species estimated after resampling 100 times (with replacement) is shown, for increasing sampling efforts (1–53 sampling units). For comparative purposes, each panel also shows the asymptotic richness value estimated by means of the best species accumulation function (upper horizontal line; see table 2), and the value of Sobs Mao Tao (curve below the estimator line). The bottom right panel shows the evolution of the number of species in exactly one and two sampling units.

Animal Biodiversity and Conservation 33.1 (2010)

ICE 35

35

30

30

25

25

20

20

15

15

10

10

5

5

0

0 Jack 1 35

Riqueza (nº de especies)

35 30

30

25

25

20

20

15

15

10

10

5

5

0

41

Jack 2

0 Bootstrap

35

10 9

30

8

25

7

20

6 5

15

Una unidad de muestreo

4 3

10

2

5 0

Chao 2

Dos unidades de muestreo

1 0

10

20

30

0 40 50 0 10 20 30 Esfuerzo de muestreo (nº de censos)

40

50

Fig. 3. Curvas suavizadas de acumulación de la riqueza según los estimadores no paramétricos ICE, Chao 2, Jack 1, Jack 2 y Bootstrap, para la comunidad de aves del Sitio 2. En cada panel se muestra el valor medio y la desviación estándar (barras de error), del número de especies estimado tras 100 remuestreos con reemplazamiento, según esfuerzos de muestreo crecientes (1–53 unidades de censo).

Con propósitos comparativos, en cada panel se muestra el valor de riqueza asintótica estimado según la mejor función de acumulación de especies (línea horizontal superior; véase tabla 2), y el valor de Sobs Mao Tao (por debajo de la curva del estimador). El panel inferior derecho muestra la evolución del número de especies presentes en exactamente una y dos unidades de muestreo.

42

también la peor forma de medir el número real de especies (figs. 2, 3). ¿Pueden los estimadores no paramétricos de la riqueza de especies aquí eva� luados reducir este sesgo y aumentar la exactitud, incluso con un menor esfuerzo de muestreo?

Para valorar el comportamiento de los estimadores con datos reales es necesario conocer el número de especies de la comunidad (Walther & Moore, 2005), información que se puede obtener mediante otras aproximaciones. Los métodos usados para este fin incluyen la opinión bien informada de expertos locales (i.e., una guesstimate; Walther & Moore, 2005; para un ejemplo de su uso, véase Hortal et al., 2006), o la extrapolación a partir del ajuste de los datos a funciones matemáticas que describen el proceso de acumulación de especies (Soberón & Llorente, 1993; Colwell & Coddington, 1994; Gotelli & Colwell, 2001; Walther & Moore, 2005). A menos que la comunidad se haya muestreado de modo exhaustivo, estas curvas subestimarán también la riqueza real de un modo desconocido (Magurran, 2004), por lo que es importante que la función utilizada para modelar los datos empíricos presente un buen ajuste a los mismos (Jiménez–Valverde & Hortal, 2003; López–Gómez & Williams–Linera, 2006), aspecto al que no siempre se le ha prestado la debida atención en la literatura (O’Hara, 2005).

Soberón & Llorente (1993) presentaron tres modelos que han sido usados por muchos autores para estimar el número de especies en sus co� munidades de estudio (el modelo de dependencia lineal, el exponencial negativo, y la ecuación de Clench), y justificaron la elección a priori de un único modelo con base en criterios teóricos (véase, también, Moreno, 2001). Sin duda, reducir a tres el conjunto de los posibles modelos matemáticos que describen la acumulación de especies, o peor aún a un único modelo, aumenta la probabilidad de que la función que mejor los describe quede fuera del conjunto. Sin embargo, Colwell & Coddington (1994) defendieron una aproximación empírica, claramente diferente: el ajuste de los datos a todos los mode� los razonables disponibles, y su evaluación "por los medios más rigurosos disponibles" (sic; véase también Díaz–Francés & Soberón, 2005). Aunque la cantidad de funciones matemáticas que pueden describir las curvas de acumulación de especies es muy amplia (Flather, 1996; Thompson et al., 2003; Tjorve, 2003; Jiménez–Valverde et al., 2006), lo cierto es que muchos autores han asumido un único modelo en sus estudios: el modelo de Clench, también conocido como la función de Michaelis– Menten (Chazdon et al., 1998; Brose & Martinez, 2004; Canning–Clode et al., 2008; Williams, 2008), implementada igualmente en varios de los progra� mas disponibles, como EstimateS (Colwell, 2006).

Si el ajuste se realiza para calcular la asíntota, y asumir después que es la mejor estima de la riqueza del sitio de estudio, entonces ajustar los datos a un conjunto reducido de modelos puede llevar a resultados erróneos en la evaluación de los estimadores, errores que pasarán generalmente inadvertidos.

González–Oreja et al.

En este artículo ajustamos las curvas suavizadas de acumulación de especies a dos modelos no asin� tóticos y siete modelos asintóticos utilizados en estu� dios de ecología y biogeografía (Chazdon et al., 1998; Moreno & Halffter, 2000; Jiménez–Valverde & Hortal, 2003; Thompson et al., 2003; Jiménez–Valverde et al., 2006; Díaz–Francés & Soberón, 2005; O’Hara, 2005). En resumen, tras comparar la evidencia que soportaba a unos y otros modelos, mediante técnicas basadas en la teoría de la información que tienen en cuenta el principio de parsimonia, las curvas de acu� mulación de especies se ajustaron mejor a modelos asintóticos relativamente complejos en su estructura (en concreto, el modelo de Weibull acumulado y el Beta–P) que a modelos más sencillos que han sido más utilizados en ecología (como el de Clench).

Esta misma observación ha sido realizada ya por otros autores (Flather, 1996; Jiménez Valverde et al., 2006; González–Oreja et al., 2010), y sugiere que la aplicación indiscriminada de modelos tradicional� mente aceptados por la comunidad científica puede no resultar siempre acertada. Cuando el inventario está prácticamente completo, las diferencias en las estimas asintóticas de riqueza que ofrecen los distintos modelos pueden ser pequeñas; es el caso del Sitio 1 de nuestro estudio (rango: 14,7−16,7; tabla 2). Sin embargo, cuando el inventario es de peor calidad, pues quedan aún más especies por añadir a la lista, o hay especies transitorias (véase más abajo), las diferencias pueden ser notables; es el caso del Sitio 2 (rango: 24,6−33,3).

Tras asumir que la asíntota del mejor modelo en cada sitio es una estima confiable del número de especies de aves presentes, evaluamos el des� empeño de los diferentes estimadores no paramé� tricos de la riqueza. No hay un estimador que sea "el mejor" en todas las situaciones, o que resulte especialmente indicado para un grupo concreto de organismos (Walther & Morand, 1998; Walther & Moore, 2005). Por ello, autores diferentes, que han aplicado diversos criterios de evaluación, han repor� tado distintos comportamientos de los estimadores.

Como un primer resumen, Walther & Moore (2005) revisaron 14 estudios en los que se comparaba el desempeño de varios estimadores, y concluyeron que la riqueza observada es generalmente el peor, mientras que los estimadores de Chao y los de tipo Jackknife (como Jack 1 y Jack 2), son generalmente los que mejor se comportan (véase también Hortal et al., 2006; López–Gómez & Williams–Linera, 2006; Canning–Clode et al., 2008, o Williams, 2008). En este estudio utilizamos criterios gráficos "blandos", como los utilizados por Colwell & Coddington (1994), Chazdon et al. (1998) y Longino et al. (2002), y cri� terios estadísticos "duros", más rigurosos, como los utilizados por Walther & Moore (2005). Los criterios "blandos" tienen en cuenta la estabilidad–sensibilidad de los estimadores a los cambios en el esfuerzo de muestreo. Esta aproximación ha sido criticada por Walther & Morand (1998), pues un estimador más o menos estable, cuyos valores no cambian a lo largo de esfuerzos de muestreo crecientes, puede ser igualmente un estimador sesgado o impreciso.

Animal Biodiversity and Conservation 33.1 (2010)

Los criterios "duros" aplicados en nuestro estudio mostraron que los estimadores evaluados también subestimaron la riqueza asintótica. Ahora bien, este error fue mayor en el Sitio 2, en el que encontra� mos varias especies de aves que podemos califi� car de transitorias o "turistas" (literalmente, tourist species), que no forman parte de las comunidades estudiadas, y que pueden "inflar" los valores de las estimas (Magurran, 2007). Es el caso del carpintero de pechera, o de las observaciones muy tempranas (inicios de agosto) del reyezuelo sencillo y el chipe corona negra (datos propios inéditos). Con base en métodos tradicionalmente aplicados en estudios de captura y recaptura, otros autores han analizado los cambios espaciales en la riqueza y la composición de las comunidades de aves cuando la probabilidad de detección de las especies es heterogénea (véase, por ejemplo, Boulinier et al., 1998; Nichols et al., 1998).

Es posible que estos métodos ayuden a mejorar los estudios de biodiversidad en áreas urbanas.

En ciertos escenarios, unos estimadores pueden ser los mejor evaluados en términos de sesgo, y otros diferentes en términos de precisión, por lo que sería difícil recomendar unos u otros; en estos casos, el análisis global (i.e., exactitud) podría oscu� recer la evaluación. Aún así, el examen combinado de los resultados obtenidos en nuestros dos sitios de estudio, sitios que varían en la calidad de sus inventarios y en la importancia relativa de las espe� cies transitorias, revela que el mejor estimador (en términos de exactitud global) fue Jackknife 1. Fue el único de los cinco estimadores evaluados con una exactitud global por encima del 95%, incluso con esfuerzos de muestreo bajos (cerca del 20% de todas las unidades de muestreo; tabla 3). Por ello, a falta de análisis de evaluación en otros sitios de interés, y aunque es muy posible que los mejores estimadores sean específicos de cada caso (Walther & Morand, 1998), proponemos usar el estimador no paramétrico Jackknife 1 como un límite inferior de la riqueza real de especies de aves en áreas verdes y otros entornos urbanos comparables a los de este estudio.

Agradecimientos El trabajo de campo se realizó con cargo al Proyecto "Estudios de la avifauna de Puebla y su entorno", financiado por el Decanato de Investigación y Post� grado de la Universidad de las Américas Puebla (Puebla, México). Agradecemos a Robert K. Colwell, Eloísa Díaz Francés, Joaquín Hortal, Jorge Lobo y Claudia Moreno su ayuda con algunas dudas surgidas durante la realización de este estudio. Tres revisores anónimos, y el Editor de la revista, leyeron y criti� caron constructivamente dos versiones previas de este trabajo, aportando varias ideas para su mejora.

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"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

Animal Biodiversity and Conservation 33.1 (2010)

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Anthrenus (Florilinus) loebli n. sp.

(Coleoptera, Dermestidae, Anthrenini) from the Middle East M. Kadej & J. Háva

Kadej, M. & Háva, J., 2010. Anthrenus (Florilinus) loebli n. sp. (Coleoptera, Dermestidae, Anthrenini) from the Middle East. Animal Biodiversity and Conservation, 33.1: 47–51.

Abstract Anthrenus (Florilinus) loebli n. sp. (Coleoptera, Dermestidae, Anthrenini) from the Middle East.— A new species Anthrenus (Florilinus) loebli from Israel, Lebanon and Jordania is described, illustrated and compared with the similar species classified within the subgenus Florilinus Mulsant & Rey, 1868. The new species is characterized by oval eyes, eight–segmented antenna and subtriangular, occasionally triangular, scales on the dorsum. The yellowish/light brown scales are present on the anterior and terminal part of the elytra and create three irregular, transverse bands. Antennal segment eight are at least 4.8 to 5x longer than segment 7 in male, 2.1x longer in female. The new species is most similar to A. (F.) museorum (Linnaeus, 1761); A. (H.) fuscus Olivier, 1789 and A. (F.) flavidus Solsky, 1876. An identification key to externally similar species of the genus is given. The most distinctive taxonomic characteristics concern the male genitalia and antenna (in ratio of length of segments of antennal club) and are also described.

Key words: Taxonomy, New species, Coleoptera, Dermestidae, Anthrenus, Israel, Lebanon, Jordania.

Resumen Anthrenus (Florilinus) loebli sp. n. (Coleoptera, Dermestidae, Anthrenini) de Oriente Medio.— Se describe una nueva especie, Anthrenus (Florilinus) loebli, de Israel, el Líbano y Jordania. Se la describe, ilustra y compara con las especies similares clasificadas en el subgénero Florilinus Mulsant & Rey, 1868. La nueva especie se caracteriza por tener los ojos ovalados, antenas de ocho segmentos y escamas subtriangulares, ocasionalmente triangulares, en el dorso. Dichas escamas, marrón claro/amarillentas, se hallan en la parte anterior y terminal de los élitros, formando tres bandas transversals irregulares. El octavo segmento de la antena es al menos de 4,8 a 5 veces más largo que el séptimo en el macho, y 2,1 veces más largo en la hembra. Esta nueva especie es muy parecida a A. (F.) museorum (Linnaeus, 1761); A. (H.) fuscus Olivier, 1789 y A. (F.) flavidus Solsky, 1876. Se da una clave de identificación para especies del mismo género que se parecen externamente. Las características taxonómicas distintivas de la especie conciernen a los genitales masculinos y a las antenas (en la proporción de la longitud de la maza de la antena) y se describen detalladamente.

Palabras clave: Taxonomía, Especie nueva, Coleoptera, Dermestidae, Anthrenus, Israel, Líbano, Jordania.

(Received: 27 X 09; Conditional acceptance: 19 I 10; Final acceptance: 26 III 10) Marcin Kadej, Dept. of Biodiversity and Evolutionary Taxonomy, Zoological Inst., Univ. of Wrocław ul. Przybyszewskiego 63/77, 51–148 Wrocław, Poland.– Jiří Háva, Private Entomological Lab. and Collection, Únětice u Prahy 37, CZ–252 62 Praha–západ, Czech Republic.

Corresponding author: M. Kadej: E–mail:entomol@biol.uni.wroc.pl

ISSN: 1578–665X

© 2010 Museu de Ciències Naturals

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Introduction Anthrenus carpet beetles are small and round. Their body is covered with colourful scales of various brown, tan, red, whitish and grey hues. The scales create different patterns (spots, transversal bands), especially on the pronotum and elytrae. These patterns are usually specific to a particular species, making them very useful in the identification process.

The genus Anthrenus was initially divided into 8 subgenera (Mroczkowski, 1968). Zhantiev (1976), however, reduced this genus to only 2 subgenera but his postulate was ignored by other taxonomists who still recognized 8 subgenera (Beal, 1998; Burakowski et al., 1986). The ninth subgenus, Peacockia, was described in 1993 (Menier & Villemant, 1993), followed by another one –Setapeacockia, recognized by Háva (2008). The issue of Anthrenus classification remains unresolved, and both classifications prevail in the available publications. The classification by Zanthiev (2009) includes only two subgenera: Anthrenus s. str. and Florilinus, whereas the other classification adds to the nine subgenera: Anthrenodes, Anthrenops, Anthrenus s. str., Florilinus, Helocerus, Nathrenus, Peacockia, Ranthrenus, Solskinus (Háva, 2003), the tenth subgenus –Setapeacockia.

Subgenus Florilinus has 30 species and all of them are characterized by 8–segmented antennae with 2–segmented antennal club. Only two species within the subgenus Florilinus have been found in Israel–the cosmopolitan Anthrenus museorum (Linnaeus, 1761) and A. sordidulus Reitter, 1889 (Háva, 2010). This article follows up on the previous articles describing Dermestidae found in Israel (Háva, 2007; Háva et al., 2001, 2007).

Kadej & Háva

The morphological structures were examined under a Nikon Eclipse E 600 phase contrast microscope with a drawing table attached, and a Nikon SMZ–800 binocular microscope; the samples were immersed in glycerin and exposed to transmitted light. After study, all structures were put back into plastic micro vials filled with glycerin under the appropriate specimen.

Photos were taken with a Nikon Coolpix 4500 camera.

The terminology used in this paper follows that of Beal (1998).

Results Subfamily Megatominae Tribe Anthrenini Anthrenus (Florilinus) loebli n. sp. (figs. 1–6) Name derivation The name of the new species is dedicated to the Mr I. Löebl, MHNG, taxonomist of Scaphidiinae.

Material and methods

Type material Holotype: male, Israel, Galilee, Ginosar, 26 V 1973, I. Löbl lgt., MNHG. Paratypes: 4 males 7 females, the same data as holotype; 2 males 1 female, JHAC; 2 males 6 females, MHNG; 1 male 4 females, Israel, Galilee, au dessous Safad, 500 m, 14 VI 1973, I. Löbl lgt., MHNG; 1 male, Israel, Galilee, au dessous Safad, 500 m, 30 V 1973, I. Löbl Igt., MKCP; 3 females, Israel, Hagalil, Umg. Nahariyya Kabri, VI 1981, Kiener leg., MHNG; 4 males, N Lebanon, Nahrel–Bared, 20 km N.E. of Tripoli, 2 VI 2001, P. M. Pavett lgt., NMGW; 1 male 1 female, Jordan bor. occ., cca 20 km N of Amman, 32° 12´ N 35° 53´ E, 250 m, 19 V 2007, F. Kantner lgt., JHAC.

The size of beetles or their body parts can be useful in species recognition and thus, the following measurements were made: total length (TL, linear distance from anterior margin of pronotum to apex of elytra); pronotal length (PL, maximum length measured from anterior margin to posterior margin); pronotal width (PW, maximum linear transverse distance); elytral length (EL, linear distance from shoulder to apex of elytron); elytral width (EW, maximum linear transverse distance); F. Subgenus Florilinus; H. Subgenus Helocerus.

Moreover, the following abbreviations refer to the collections in which the examined material is deposited: JHAC. Private �������������������������������������������� Entomological Laboratory and Collection, Jiří Háva, Prague–west, Czech Republic; MHNG. Museum d´histoire naturelle, Genève, Switzerland; MKCP. Marcin Kadej, Institute of Zoology, Department of Biodiversity and Evolutionary Taxonomy collection, Wrocław, Poland; NMGW. National Museums and Galleries of Wales, Cardiff, United Kingdom.

Specimens of the species described here are provided with a red, printed label with text as follows: holotype (or paratype, respectively) Anthrenus (Florilinus) loebli n. sp. J. Háva & M. Kadej det. 2008.

Description Body measurements (mm): TL 2.07–2.15 PL 0.45– 0.57 PW 0.95–1.00 EL 1.62–1.70 EW 1.29–1.35.

Body convex, slightly elongate, covered by subtriangular, occasionally triangular, scales, mostly with 7–8, occasionally 5 more or less linear ribs; the apex of the scale body is truncate or concave and an apical lappet is present (fig. 6). Head distinctly convex and oval eyes. Frons with median ocellus, covered with grey scales. Antenna 8–segmented, with 2–segmented antennal club (fig. 3); antennal segments 1–6 light–brown, antennal club brown.

Antennal segment 8 at least 4.8 to 5x longer than segment 7 in male, 2.1x longer in female. Antenna occupies whole cavity of antennal fossa. Antennal club occupies less than half of the antenna length in male and female. Antennal fossa completely open along lateral margin of the pronotum. Dorsal and ventral surface of integument brown, slightly punctated, covered with scales (figs. 1, 2). Pronotum covered with mixed grey, yellowish/light brown (lateral margins, on the angles and central bottom apex) and dark brown scales (in the central part) scales.

Elytra covered with mixed yellowish/light brown and

Animal Biodiversity and Conservation 33.1 (2010)

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1

2

3

4

5

0.1 mm

0.1 mm

0.1 mm

6

0.01 mm

Figs. 1–6. Anthrenus (Florilinus) loebli n. sp.: 1. Habitus, dorsal aspect; 2. Habitus, ventral aspect; 3.

Male antenna; 4. Male genitalia; 5. Median lobe, lateral view; 6. Scales.

Figs. 1–6. Anthrenus (Florilinus) loebli sp. n.: 1. Hábito, vista dorsal; 2. Hábito, vista ventral; 3. Antena masculina; 4. Genitales masculinos; 5. Lóbulo medio, vista lateral; 6. Escamas.

dark brown scales. The yellowish/light brown scales are present on the anterior and terminal part of the elytra and create three irregular, transverse bands.

The areas between bands are covered with dark brown scales mixed with single yellowish scales.

Ventral surface grey except for visible sternites I–V covered with mixed grey and light brown scales; first abdominal sternite without stria. Legs brown, covered with grey scales on dorsal surface. Tarsus with two tarsal claws slightly curved. Male genitalia as in figure 4. Parameres U–shaped, covered with numerous short setae. Median lobe C–shaped, wide posteriorly, distal end of aedeagus strongly reflexed ventrally (figs. 3, 5). Pygidium lacking dark, subbasal,

transverse, carina–like line; setae limited to apical area, occasional and rather randomly placed.

Variability Occasionally, the dorsum of some specimens might be covered with grey scales only; in such cases, the dorsal patterns are absent.

Differential diagnosis The new species’ dorsal appearance resembles A. (F.) museorum (Linnaeus, 1761); A. (H.) fuscus Olivier, 1789 and A. (F.) flavidus Solsky, 1876. It can be easily identified from externally similar species and from A.

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Kadej & Háva

Identification key for species of genus Anthrenus (Florilinus) externally similar.

Clave de identificación para especies del género Anthrenus (Florilinus) parecidas externamente.

1 Antenna 5–segmented, antennal club 1–segmented A. (H.) fuscus Olivier, 1789 Antenna 8–segmented, antennal club 2–segmented 2 2 Elytra and pronotum covered only by unicolor yellow, sometimes grey scales A. (F.) sordidulus Reitter, 1889 Elytra and pronotum covered by tricolor scales 3 3 Disc of pronotum usually with distinct median pronotal line of pale scales; abdominal sterna 1–5 bicolor; covered with patch of dark scales at lateral margins of abdominal sterna 2–5 and in the middle of sterna 5 A. (F.) museorum (Linnaeus, 1761) Disc of pronotum without distinct median pronotal line of pale scales; abdominal sterna 1–5 unicolor; sometimes covered with mixed grey and light brown scales 4 4 Disc of pronotum consist of all dark brown scales in the central part A. (F.) loebli sp. n.

Disc of pronotum covered with light brown/grey/yellowish scales in the central part A. (F.) flavidus Solsky, 1876

sordidulus (also recorded from Israel) by characters mentioned in the identification key.

Some other important differences can be also found in the morphology of the male genitalia and antenna, especially in ratio of length of segments of antennal club.

Morfology of male genitalia Aedeagus (median lobe) (in lateral view): S–like shape, slightly reflexed ventral F–like shape (A. museorum); C–like shape, slightly reflexed ventral (A. flavidus and A. loebli), Apex of aedeagus (lateral view): rounded (A. museorum/A. sordidulus); acute (A. flavidus and A. loebli), but bridge between paramers is relatively wide in A. flavidus but thin in A. loebli. All the species of apex of aedeagus are conical in shape (in frontal view), except A. museorum which is bubble–shaped.

Morphology of antennae Male antennal segment 8 at least 5x longer than segment 7, in female 2.2x longer (A. museorum), 7–8x longer in male, 1.7–2x in female (A. flavidus), 2x longer in male and female (A. sordidulus), 4.8 to 5x longer in male, 2.1x longer in female (A. loebli).

Discussion Many of Florilinus’s species look similar externally thanks to the particular dorsal patterns. Main differences helpful in identification are found in morphology of male genitalia and form of antennae. For this reason the examination of the male genitalia and ratio of segment lengths of antennal club are crucial to confirm identification.

Acknowledgements We would like to thank to D. Tarnawski (Zoological Institute, Wrocław University, Poland) who provided helpful comments to improve this manuscript, J. Tarnawski (Institute of Computer Science, Wrocław University, Poland) for his help with the manuscript translation and I. Löbl (MHNG), B. Levey (NMGW) and F. Kantner (České Budějovice, Czech Republic) for loan of the material of interest.

This work was supported by funding (2020/IZ/2010) from the Institute of Zoology, University of Wrocław.

References Beal, R. S., 1998. Taxonomy and Biology of Nearctic Species of Anthrenus (Coleoptera: Dermestidae). Transactions of the American Entomological Society, 124: 271–332.

Burakowski, B., Mroczkowski, M., & Stefańska, J., 1986. Katalog fauny Polski, Cz. 23, Tom 11. Coleoptera (Dermestoidea, Bostrychoidea, Cleroidea i Lymexyloidea). Warszawa: PWN. (In Polish.)

Háva, J., 2003. World Catalogue of the Dermestidae (Coleoptera). Studie a Zprávy Oblastního Muzea Praha–východ v Brandýse nad Labem a Staré Boleslavi, Supplementum 1: 1–196.

– 2007. New or interesting Dermestidae (Coleoptera) from Jordan and Israel. Stuttgarter Beiträge zur Naturkunde, Serie A, 699: 1–6.

– 2008. Description of a New Subgenus Setapeacockia subgen. nov. of the genus Anthrenus Geoffroy, 1762 (Coleoptera: Dermestidae: Anthrenini) from Central Asia. Litvijas Entomologos, 45: 43–45.

– 2010. Dermestidae World (Coleoptera). World Wide

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Web electronic publication (open in 2004): http:// www.dermestidae.wz.cz Háva, J., Pavlíček, T., Chikatunov, V. & Nevo, E., 2001.

Dermestid beetles in "Evolution Canyon", Lower Nahal Oren, Mt. Carmel including new records for Israel. Phytoparasitica, 29: 97–101.

Háva, J., Pavlíček, T. & Chikatunov, V., 2007. Corrigenda and addenda of Dermestidae in the "Catalogue of the Beetles (Coleoptera) of Israel and Adjacent Areas". Mitteilungen des Internationalen Entomologischen Vereins, 32: 117–131.

Menier, J., J. & Villemant, C., 1993. Description et biologie de Anthrenus (Peacockia n. sgen.) vladimiri n. sp. prédateur des pontes de Porthetria

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dispar (L.) au Maroc (Coleoptera, Dermestidae; Lepidoptera, Lymantriidae). Revue France d´ Entomologique, 15: 61–66.

Mroczkowski, M., 1968. Distribution of the Dermestidae (Coleoptera) of the world with a catalogue of all nown species. Annales Zoologici, 26: 15–191.

Zhantiev, R., D., 1976. Zhuki kozheedy fauny SSSR. [The skin eaters family Dermestidae of fauna of the USSR.] Moskva: Izdatelstvo Moskovskogo Universiteta. (In Russian.)

– 2009. Ecology and Classification of Dermestid Beetles (Coleoptera, Dermestidae) of the Palearctic Fauna. Entomological Review, 89(2): 157–174.

"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

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Avian community responses to the establishment of small garden allotments within a Mediterranean habitat mosaic J. Quesada & I. MacGregor–Fors

Quesada, J. & MacGregor–Fors, I., 2010. Avian community responses to the establisment of small garden allotments within a Mediterranean habitat mosaic. Animal Biodiversity and Conservation, 33.1: 53–61.

Abstract Avian community responses to the establishment of small garden allotments within a Mediterranean habitat mosaic.— Ecological studies focused on small–scale habitat alterations have found positive, null, and negative effects on biodiversity. In this study, we describe the effects that establishing a relatively small area of garden allotments had on bird communities. To assess such effects, we analyzed avian community diversity (i.e., species richness and abundance) and behavioral traits (i.e., foraging, perching). Although land transformation was recent and on a small geographic–scale, our results showed that bird communities in the allotments were dominated by a few species, while in the almond plantation (former habitat) evenness was higher. When perching and foraging behavior was compared in the two study areas, we found a signifi� cantly higher proportion of foraging in the garden allotments, and a higher proportion of birds perching in the naturalized plantation. Although new habitats often enhance regional bird species richness in Mediterranean landscapes, we found no evidence of an increase in regional avian diversity related to the establishment of small garden allotments. We propose that future harvesting activities should consider the scale, intensity, and frequency of the generated perturbation in order to promote biodiversity.

Key words: Avian ecology, Biodiversity, Bird communities, Land–use transformation.

Resumen Respuestas de una comunidad de aves al establecimiento de un pequeño huerto dentro de un hábitat Mediterráneo en mosaico.— Estudios previos de ecología enfocados a los efectos que tienen las alteraciones de los hábitats a pequeña escala han hallado efectos positivos, nulos y negativos sobre la biodiversidad.

En este trabajo describimos los efectos que tiene el establecimiento de un pequeño huerto sobre la comu� nidad de aves. Para ello, analizamos los valores de diversidad (i.e., riqueza de especies y abundancia) y el comportamiento (i.e., forrajeo, uso de perchas) de las comunidades de aves. Los resultados de este trabajo muestran que, aunque el cambio de uso de suelo es reciente y a pequeña escala, las comunidades de aves observadas en el huerto están dominadas por unas pocas especies, mientras que mostraron ser mayormente equitativas en las plantaciones naturalizadas de almendros (hábitat previo al establecimiento de los huertos).

Cuando comparamos el comportamiento de las aves en ambos hábitats, encontramos una mayor proporción de aves en búsqueda activa de alimento en los huertos, mientras que el número de aves desarrollando otras actividades (descanso) fue mayor en las plantaciones naturalizadas. Aunque la presencia de nuevos hábitats puede elevar la riqueza regional de la avifauna en paisajes mediterráneos, nuestros resultados no muestran evidencia de un efecto positivo significativo en el aumento de la riqueza regional de aves debido al estable� cimiento de pequeños huertos. Proponemos que las futuras actividades agrícolas deban tener en cuenta la escala, intensidad y frecuencia de las perturbaciones generadas con la finalidad de lograr un efecto positivo sobre la biodiversidad.

Palabras clave: Ecología aviar, Biodiversidad, Comunidades de aves, Transformación del uso del suelo.

(Received: 21 IX 09; Conditional acceptance: 7 XII 09; Final acceptance: 26 III 10)

ISSN: 1578–665X

© 2010 Museu de Ciències Naturals

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Quesada & MacGregor–Fors

J. Quesada, Institut Català d’Ornitologia, Barcelona, España (Spain).– I. MacGregor–Fors, Lab. de Ecología Funcional, Centro de Investigaciones en Ecosistemas, Univ. Nacional Autónoma de México, Campus Morelia, Antigua Carretera a Pátzcuaro 8701, Morelia 58190, Michoacán, México.

Corresponding author: J. Quesada. E–mail: analisi@ornitologia.org

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Introduction

Methods

Agricultural activities generate increasing land–use change worldwide (Vitousek et al., 1997; Schroter et al., 2005). This phenomenon is closely related to changes in the nature and dynamics of biotic communities, leading to community ecology shifts such as the invasion and domination of wildlife communities by a few generalist and/or opportu� nistic species, and even to the extinction of those species sensitive to habitat alterations (Vitousek et al., 1997; Czech et al., 2000). Previous stu� dies have shown that habitat change can affect biodiversity positively or negatively (Burel et al., 1998; Benton et al., 2003; Sax & Gaines, 2003; Lepczyk et al., 2008), largely depending on the environmental heterogeneity generated by the anthropogenic modification of habitats (Mason & MacDonald, 2000; Benton et al., 2003; Herrando et al., 2003; Pons et al., 2003; Suárez–Seoane et al., 2002). However, differences in the effects that land–use change have on biodiversity are difficult to predict due to the magnitude of change and the differential response of species, with some of them being positively affected and others negati� vely affected by such modifications (Blair, 1996; Devictor et al., 2008).

Knowing the ecological effect of small–scale environmental alterations can aid local landscape management activities and wildlife conservation strategies (Pickett & Cadenassso, 1995; Gutzwiller, 2002). In this study we describe the response of bird communities to the establishment of a series of small garden allotments in an area that was modified ~50 years ago from Mediterranean ve� getation to almond plantations. These areas are now abandoned and are conceived as naturalized, creating a typical Mediterranean mosaic grid that includes both natural and/or naturalized vegetation, and crops. To assess the effect of such land–use transformation on bird communities, we compared bird species richness, abundance, and evenness in abandoned naturalized almond plantations (inclu� ding scattered Mediterranean vegetation patches) with an area of recently established small garden allotments. We also assessed the species turnover rate between these two habitats, and evaluated how birds used them. To do so, we recorded perching and feeding activities. We used birds as ecological models to evaluate the effect of habitat replacement because they are highly conspicuous, relatively easy to survey, and sensitive to habitat changes. Fur� thermore, they constitute complex communities in almost every natural and human–altered ecosystem (Furness & Greenwood, 1993; Gregory et al., 2009; MacGregor–Fors et al., 2009). We expected bird species richness to be higher in naturalized almond plantations due to their closed canopy, but predicted that bird abundances would be higher in the garden allotments due to the quantity and availability of a variety of human–produced food resources. We also predicted differences in the way in which birds use each of the studied habitats.

Study area This study was conducted in Abrera (Catalunya), north east Spain (41° 31' 07'' N, 1° 53' 55'' E; ~65 m a.s.l.). Main plant assemblages in this area include abandoned almond tree (Prunus spp.) plantations (50 years old) with scattered patches of Mediterra� nean vegetation (referred to as almond plantations hereafter). Thus, although the origin of this habitat is anthropogenic, it has become a naturalized habitat due to abandonment and its vegetation structure including open patches covered with an understory of herbaceous plants and native bushes (e.g., Quercus coccifera, Pistacia lentiscus, Erica arborea) with scattered Mediterranean trees dominated by Holm Oaks (Quercus ilex) and Aleppo Pine trees (Pinus halepensis). In 2002, an approximate area of 2.4 hectares of the naturalized almond plantation was transformed into 20 x 20 m garden allotments for recreational and non–commercial purposes. These allotments are basically comprised of herbaceous crops, such as corn, potatoes and legumes, and a few scattered almond trees.

Bird surveys To evaluate avian responses to the establishment of the garden allotments, we compared bird communi� ties therein with those in the adjacent former almond plantation. Birds were surveyed during winter, the breeding season, and post–breeding migration of 2005. We carried out bird surveys on seven separate days throughout the year in each habitat, starting one hour after dawn. We used the area search me� thod (Ralph et al., 1993) recording all birds present in the surveyed areas for 30 minutes. Because the allotment area was relatively small, the size of the naturalized almond plantation we studied was also small. Although the two habitats were contiguous, we selected survey sites that were located 300 m apart to assure survey independence (Bibby et al., 1992; Ralph et al., 1993).

Statistical analyses To assure a representative sample of bird communities within the garden allotments and almond plantations, we calculated the mean predicted species richness for both habitats using ACE, an abundance–based coverage estimator (SPADE; Chao & Shen, 2006).

ACE uses the coefficient of variance of a sub–sam� ple of rare species, determined by a cut–off point, to characterize the degree of heterogeneity for the pro� bability of species detection, to estimate the number of missing species in a given sample, and to calculate a statistical expectation of the predicted species based on a given sample (Chao & Lee, 1992).

Species rank/abundance plots were used to com� pare bird community evenness among both studied habitats (as recommended by Magurran, 2004).

Rank/abundance plots are often used to represent

56

distribution of species abundance in a community.

They highlight differences in dominance/evenness among communities; steep curves represent as� semblages with high dominance of a few species, and shallower slopes imply communities with higher evenness where species share similar abundances.

The steepness of the slope of rank/abundance plots allows to infer the processes determining the diver� sity of a community, and reflects the success of the implied species to compete for limited resources (Magurran, 2004). Because ranked abundances did not follow a normal distribution, data were transformed (log10). To test differences in the slopes of both rank/ abundance regression lines, we performed Ancova.

Bird abundances recorded in both surveyed habitats were also compared using a generalized linear model (one way GLZ Anova Model) considering a Poisson distribution. We contrasted the richness values of bird species recorded in the garden allotments and adjacent almond plantations using rarefaction curves (Sobs Mao Tao ± 95% confidence intervals; EstimateS platform; Colwell, 2005). Rarefaction curves are based on the repeated re–sampling of all pooled samples, representing the statistical expectation of species richness in sample (Gotelli & Colwell, 2001; Colwell, 2005). To determine if species richness values were statistically different between the studied habitats, we compared their 95% confidence intervals. When confidence intervals did not overlap, α < 0.01 was considered statistically significant (following Payton et al., 2003; M. Payton, pers. com.).

We assessed the species turnover rate between the two studied habitats using a recently proposed index (ßsim; Lennon et al., 2001). ßsim quantifies the relative magnitude of species gains and losses in relation to the sample with less unique species, allowing the identification of species loss or shift in relation to the sample with more unique species (Koleff et al., 2003; Gaston et al., 2007). Also, we analyzed differences in the proportion of species pertaining to recorded trophic guilds in both studied habitats using a contingency table chi–square test.

To evaluate differences in the way that birds used both study habitats, we recorded the activity carried out by every sight–recorded bird. Two activities were recorded in sample sizes sufficient to conduct robust statistical analyses: (1) foraging; and (2) perching. Be� havioral observations were recorded simultaneously with the area search surveys. To compare differences in the number of birds feeding and perching within the studied habitats, we performed a general linearized model (GLZ: two–way Anova Model), following a Poisson distribution, where bird abundance was the dependent variable, and the predictors were habitat and behavior (perching and foraging).

Results Analysis of species prediction revealed that our survey method was sufficient to record a representative sam� ple of the bird communities present in both habitats during the study period. The number of bird species

Quesada & MacGregor–Fors

recorded in naturalized almond plantations and garden allotments comprised 86.3 and 85.4% of their mean bird richness prediction respectively (ACE = 33.6 and 23.4 species, respectively).

We recorded a total of 34 bird species of 24 genera, six of which are considered regionally endangered (sensu Estrada et al., 2004). Of the total 34 species, 29 were recorded in naturalized almond plantations, pertaining to five main feeding groups: insectivores (31%), omnivores (31%), granivores (21%), frugivores (10%), and carnivores (7%). In contrast, we only re� corded 20 species in the garden allotments, of which 30% were granivores, 30% omnivores, 25% insecti� vores, 10% frugivores, and 5% carnivores (table 1).

Bird communities recorded in the allotment area were highly dominated by a small number of spe� cies, while communities in the almond plantations were fairly even (ANCOVA F1,45 = 13.36, p < 0.001; fig. 1). Bird abundances differed between the studied habitats, with higher values in the garden allotments (Wald = 4.15, df = 1, p < 0.05; table 2). We also found differences in the richness of bird species between the two habitats. When we compared the computed rarefaction curves from both communities, using an abundance cut–off point of 143 individuals (total abundance value for almond plantations, the least abundant community), almond plantations showed a significantly higher species richness (27.0 ± 5.7) than those in the garden allotments (14.8 ± 4.9; fig. 2).

Of the total recorded bird species, 15 were shared by both habitats, 14 were unique to almond planta� tions, and 5 were unique to the allotments, although two of the latter were probably accidental (i.e., Lanius meridionalis, Sylvia melanocephala) as they typica� lly belong to Mediterranean mosaic habitats. Thus, the species turnover analysis was low (ßsim = 0.25).

However, we did not find differences in the proportion of species pertaining to the recorded trophic guilds in the two habitats (c2 = 4.99, df = 4, p = 0.28).

Based on our bird behavioral measures (i.e., number of perching and foraging birds), avian activity differed between the two study habitats. We recorded a significantly higher number of birds perching in naturalized almond plantations, while a significantly higher number of foraging birds was found in the gar� den allotments (GLZ: habitat: Wald = 4.45, p < 0.05; activity: Wald = 5.25, p < 0.05: activity x habitat: Wald = 26.22, p < 0.001; fig. 3).

Discussion Results from this study showed that the bird commu� nities in the recently established garden allotments differed from those recorded in adjacent naturalized almond plantations. Bird communities in the newly created garden allotments had lower bird species richness but higher bird density, mainly comprised of three species (58% of the total recorded abun� dance): Eurasian Tree Sparrow (Passer montanus), Barn Swallow (Hirundo rustica), and European Serin (Serinus serinus). High abundance of these species was not surprising as they are typically associated

Animal Biodiversity and Conservation 33.1 (2010)

57

Table 1. Bird species recorded in the surveyed garden allotment area and naturalized almond plantations (Mediterranean mosaic). Total number of individuals recorded for each species is reported: Trophic guild (Tg): C. Carnivore; F. Frugivore; G. Granivore; I. Insectivore; O. Omnivore. Conservation status (Cs, sensu Estrada et al., 2004): LC. Least concern; NT. N. Near threatened; VU. Vulnerable; CR. Critical. Habitat: Ap. Naturalized almond plantations. Ga. Garden allotments.

Tabla 1. Especies de aves observadas en la zona de huertos y en plantaciones de almendros naturalizadas (mosaico mediterráneo). Se incluye el número total de individuos observados de cada especie registrados: Grupo trófico (Tg): C. Carnívoro; F. Frugívoro; G. Granívoro; I. Insectívoro; O. Omnívoro. Estado de conservación (Cs, sensu Estrada et al., 2004): LC. Preocupación menor; NT. Casi amenazada; VU. Vulnerable; CR. Critico. Hábitat: Ap. Plantaciones de almendros naturalizadas. Ga. Área de huertos.

Habitat

Family

Species

Tg

Cs

Ap

Ardeidae

Ardea cinerea

C

NT

1

Columbidae

Columba palumbus

G

LC

2

2

Meropidae

Merops apiaster

I

LC

4

1

Upupidae

Upupa epops

I

LC

3

Picidae

Picus viridis

I

LC

1

Hirundinidae

Hirundo rustica

I

LC

Turdidae

Erithacus rubecula

O

LC

2

Phoenicurus ochruros

I

LC

6

Phoenicurus phoenicurus

I

CR

2

2

Turdus merula

F

LC

1

1

Turdus philomelos

F

LC

2

18

Turdus viscivorus

F

LC

1

Syliviidae

Sylvia melanocephala

I

LC

2

Sylvia atricapilla

I

LC

6

2

Phylloscopus collybita

I

LC

2

Regulus ignicapilla

O

LC

5

Muscicapidae

Muscicapa striata

I

NT

1

Aeigthalidae

Aegithalos caudatus

O

LC

14

Paridae

Parus caeruleus

O

LC

1

Parus major

O

LC

9

Certhiidae

Certhia brachydactyla

I

LC

2

Laniidae

Lanius meridionalis

C

VU

Corvidae

Pica pica

O

LC

10

13

Sturnidae

Sturnus vulgaris

O

LC

23

1

Sturnus unicolor

O

LC

2

Passeridae

Passer domesticus

O

LC

11

16

Passer montanus

O

NT

19

45

Fringilidae

Coccothraustes coccothraustes

G

NT

10

Fringilla coelebs

G

LC

Serinus serinus

G

LC

Carduelis chloris

G

LC

4

4

Carduelis carduelis

G

LC

13

17

Carduelis spinus

G

NT

8

Carduelis cannabina

G

LC

7

Ga

44 2

3 1

1 35

2

58

Quesada & MacGregor–Fors

2.0

Table 2. Bird species richness and abundance recorded in the studied naturalized almond plantations and garden allotments. Abundance values represent averages (± SD) from the seven surveys: Ap. Naturalized almond plantations; Ga. Garden allotments.

Naturalized almond plantations f(x) = –0.05x + 1.33

1.5

Tabla 2. Riqueza de especies de aves y abundancia, registradas en las áreas estudiadas de plantaciones de almendros naturalizadas y la zona de huertos. Los valores de la abundancia representan promedios (± DE) de los siete muestreos. Ap. Plantaciones de almendros naturalizadas; Ga. Área de huertos.

Bird abundance (log)

1.0

0.5

0.0

2.0 Garden allotments f(x) = –0.01x + 1.64

1.5

Ap

Ga

Total species richness

29

20

Bird abundances

23 ± 16.5

30 ± 22.3

Perching birds

10.4 ± 9.6

3.6 ± 2.9

Foraging birds

6.8 ± 6.9 10.7 ± 19.2

1.0

0.5

0.0 0

5

10 15 20 Species rank

25

30

Fig. 1. Rank/abundance plots for the recorded bird communities in the studied naturalized almond plantations and garden allotments.

The equation of the regression line for each rank / abundance plot is displayed.

Fig. 1. Gráficas de rango/abundancia de las comunidades de aves de las zonas estudiadas de plantaciones de almendros naturalizadas y áreas de huertos. Se muestra la ecuación de la línea de regresión para cada curva de rango / abundancia.

with human–modified habitats. Barn swallows are well–adapted to nesting and breeding around human habitation in Catalonia (Estrada et al., 2004) and they are associated with feeding in open farmland areas (Cramp, 2000). Tree sparrows and European serins are granivorous species and are associated with farmland and gardens within the study area (Estrada et al., 2004).

Bird communities recorded in the naturalized almond plantation with scattered Mediterranean vegetation were species–rich, but observed in lower abundance and greater evenness than the commu� nities in the newly established allotments. These findings indicate that newly established allotments of this type provide resources that benefit a few particular species, while adjacent naturalized almond plantations hold a set of resources, mainly related to their vegetation structure (e.g., closed canopy, understory, forest edges, and open herbaceous pat� ches), that support a higher number of more evenly distributed bird species.

As the recently established garden in this study comprises a managed system with constant an� thropogenic input of resources it is not unusual that we found significantly higher bird abundance here.

These findings are consistent with previous studies that report higher bird abundances in human–altered systems when compared to those from pre–existing wildlands (e.g., forest edges, agro–ecosystem, urban areas; Farina, 1997; Clergeau et al., 1998; Sallabanks et al., 2000; Chace & Walsh, 2006; Ortega–Álvarez & MacGregor–Fors, 2009, in press.). Such increases in bird abundance in human–managed systems have been related to the constant availability of food due to the steady input of resources, but only those species able to exploit these resources benefit (Shochat, 2004; Robb et al., 2008).

The fact that we found a significantly higher number of birds perching in naturalized almond plantations could be related to higher predation risk in open areas (Whittingham & Evans, 2004), and/ or the fact that close–canopy habitats with native understory include more perching sites (Guevara et al., 1998). Conversely, we recorded a significantly

Animal Biodiversity and Conservation 33.1 (2010)

59

18 Naturalized almond plantations

30 25 20

Garden allotments

15 10

Foraging birds Perching birds

14 12 10 8 6 4

5 0

16 Bird abundance

Accumulated species richness (computed; mean ± 95% CI)

35

2 0

50 100 200 250 Accumulated abundance (computed)

Fig. 2. Rarefaction curves for the naturalized almond plantations and garden allotment area.

Bird species richness was significantly higher in naturalized almond plantations, with an average value almost two fold higher than that recorded for the garden allotments. Solid lines represent mean values of species richness and dashed lines 95% confidence intervals.

Fig. 2. Curvas de rarificación para las plantaciones de almendros naturalizadas y la zona de huertos. La riqueza de especies de aves fue significativamente mayor en las plantaciones naturalizadas de almendros, con un valor promedio de casi el doble que las observadas en la zona de huertos. Las líneas continuas representan los valores medios de la riqueza de especies y las líneas discontinuas los intervalos de confianza del 95%.

higher number of bird foraging in the garden allo� tments, reinforcing the idea that shifts in the surveyed bird communities are not related to the diversity of food resources present in the two habitats, but to their availability and/or abundance (Shochat, 2004; Robb et al., 2008).

Our results show that the establishment of garden allotments can dramatically shift the diversity and structure of bird communities in a small geographic area. Although our survey shows that bird species richness in the studied area was enhanced ~15% due to the establishment of the garden allotments, adding five new indigenous bird species, four of them (i.e., Sylvia melanocephala, Lanius meridionalis, Fringilla coelebs, Carduelis cannabina) were recorded in low numbers (0.15–0.30 individuals/survey) and are common in Mediterranean vegetation matrixes.

Thus, not recording a significant effect between the

0

Naturalized almond plantations

Garden allotments

Fig. 3. Habitat use of birds in the naturalized almond plantations and garden allotment area.

We found a significantly higher number of birds perching in naturalized almond plantations but a significantly higher number of birds foraging in the garden allotment area.

Fig. 3. Uso del hábitat por parte de las aves en las plantaciones de almendros naturalizadas y la zona de huertos. Encontramos un número de aves significativamente mayor de aves posadas en las plantaciones de almendros naturalizadas, pero un número significativamente más alto de aves forrajeando en la zona de huertos.

establishment of the studied gardens and regional bird species richness differs from previous studies that have found habitat heterogeneity to increase regional wildlife species richness (Benton et al., 2003; Brotons et al., 2003; Weibull et al., 2003). As the addressed land–use change was of a particularly local nature it is not representative of all possible anthropogenic land–use changes in the region. Further studies are needed to clarify the effects that different types of agricultural systems, developed at different scales and intensities, can have on wildlife communities.

Acknowledgments We specially thank Jordi Ballesta (SEO/Birdlife Ca� talunya) for suggesting this study and for allowing the use of field data. Sergi Herrando, Rubén Or� tega–Álvarez and two anonymous reviewers kindly improved our manuscript. This study was developed as a collaboration with members of the 2009 SGR 1467 research group.

60

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"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

Animal Biodiversity and Conservation 33.1 (2010)

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Faunal assemblages and multi–scale habitat patterns in headwater tributaries of the South Fork Trinity River – an unregulated river embedded within a multiple–use landscape H. H. Welsh, Jr., G. R. Hodgson, J. J. Duda & J. M. Emlen Welsh, H. H., Jr., Hodgson, G. R., Duda, J. J. & Emlen, J. M., 2010. Faunal assemblages and multi–scale habitat patterns in headwater tributaries of the South Fork Trinity River – an unregulated river embedded within a multi� ple–use landscape. Animal Biodiversity and Conservation, 33.1: 63–87.

Abstract Faunal assemblages and multi–scale habitat patterns in headwater tributaries of the South Fork Trinity River – an unregulated river embedded within a multiple–use landscape.— Headwaters can represent 80% of stream kilometers in a watershed, and they also have unique physical and biological properties that have only recently been recognized for their importance in sustaining healthy functioning stream networks and their ecological services.

We sampled 60 headwater tributaries in the South Fork Trinity River, a 2,430 km2, mostly forested, multiple–use watershed in northwestern California. Our objectives were: (1) to differentiate unique headwater types using 69 abiotic and vegetation variables measured at three spatial scales, and then to reduce these to informative subsets; (2) determine if distinct biota occupied the different tributary types; (3) determine the environmental attributes as� sociated with the presence and abundance of these biotic assemblages; and (4) using niche modeling, determine key attribute thresholds to illustrate how these biota could be employed as metrics of system integrity and ecologi� cal services. Several taxa were sufficiently abundant and widespread to use as bio–indicators: the presence and abundance of steelhead trout (Oncorhynchus mykiss), herpetofauna (reptile and amphibian) species richness, and signal crayfish (Pacifastacus leniusculus) represented different trophic positions, value as commercial resources (steelhead), sensitivity to environmental stress (amphibians), and indicators of biodiversity (herpetofauna species richness). Herpetofauna species richness did not differ, but abundances of steelhead trout, signal crayfish, and amphibian richness all differed significantly among tributary types. Niche models indicated that distribution and abun� dance patterns in both riparian and aquatic environments were associated with physical and structural attributes at multiple spatial scales, both within and around reaches. The bio–indicators responded to unique sets of attributes, reflecting the high environmental heterogeneity in headwater tributaries across this large watershed. These niche attributes represented a wide range of headwater environments, indicating responses to a number of natural and anthropogenic conditions, and demonstrated the value of using a suite of bio–indicators to elucidate watershed conditions, and to examine numerous disturbances that may influence ecological integrity.

Key words: Headwater tributaries, Bio–indicators, Multi–scale, Ecological integrity.

Resumen Comunidades faunísticas y patrones de hábitats multiescala en las cabeceras de los afluentes del río South Fork Trinity – un río de caudal no regulado encajado en un paisaje de usos múltiples.— Las cabeceras pueden representar el 80% de los kilómetros de recorrido en una cuenca fluvial y poseen unas propiedades físicas y biológicas únicas, cuya importancia hasta hace poco no se habían reconocido para el sostenimiento de un funcionamiento sano de las redes de cuencas y sus servicios ecológicos. Tomamos muestras de 60 cabeceras de los afluentes del río South Fork Trinity, una cuenca de 2.430 km2, boscosa en su mayor parte y de múltiples usos, situada en el noroeste de California. Nuestros objetivos eran: (1) diferenciar tipos de cabeceras únicos utilizando 69 variables abióticas y vegetales, medidas a tres escalas espaciales, y luego reducirlos a subcon� juntos informativos; (2) determinar si distintos biotas ocupaban los distintos tipos de afluentes; (3) determinar las características medioambientales asociadas con la presencia y abundancia de dichas comunidades bióticas; y (4) utilizando una modelización de nichos, determinar los umbrales de los atributos claves para ilustrar cómo estos biotas podrían emplearse para la medición de la integridad del sistema y los servicios ecológicos. Varios ISSN: 1578–665X

© 2010 Museu de Ciències Naturals

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Welsh et al.

taxones fueron suficientemente abundantes y extendidos para utilizarlos como bioindicadores; la presencia y abundancia de la trucha arco iris (Oncorhynchus mykiss), la riqueza en especies de la herpetofauna (reptiles y anfibios) y el cangrejo señal (Pacifastacus leniusculus) representaban diferentes posiciones tróficas, el valor como recursos comerciales (la trucha arco iris), la sensibilidad al estrés ambiental (anfibios), e indicadores de la biodiversidad (riqueza de especies de la herpetofauna). La riqueza de especies de la herpetofauna no difirió, pero la abundancia de la trucha arco iris, del cangrejo señal, la riqueza de anfibios, difirieron significativamente entre los tipos de afluentes. Los modelos de los nichos indicaron que los patrones de distribución y abundancia, tanto en los ambientes acuáticos como en los ribereños, estaban asociados con atributos físicos y estructura� les a multiples escalas espaciales, tanto dentro como alrededor de los tramos acuáticos. Los bioindicadores respondieron a series únicas de atributos, reflejando la elevada heterogeneidad ambiental en las cabeceras de los afluentes en toda esta gran cuenca. Dichos atributos de los nichos representaban una amplia gama de ambientes de cabeceras fluviales, indicando respuestas a una serie de condiciones naturales y antropogénicas.

Se demostró el valor de utilizar una serie de bioindicadores para elucidar las condiciones de las cabeceras y para examinar las numerosas perturbaciones que pueden influir sobre la integridad ecológica.

Palabras clave: Cabeceras de afluentes, Bioindicadores, Multiescala, Integridad ecológica.

(Received: 12 VIII 09; Conditional acceptance: 18 II 10; Final acceptance: 13 IV 10) Hartwell H. Welsh & Garth R. Hodgson, USDA Forest Service, Redwood Sciences Lab., 1700 Bayview Drive, Arcata, California 95521, USA.– Jeffrey J. Duda & John M. Emlen, Western Fisheries Research Center, US Geological Survey, 6505 NE 65th Street, Seattle, Washington 98115, USA. Corresponding author: H. H. Welsh. E–mail: hwelsh@fs.fed.us This article was written and prepared by U. S. Government employees on official time, and it is therefore in the public domain and not subject to copyright.

Animal Biodiversity and Conservation 33.1 (2010)

Introduction Understanding ecosystem dynamics and cross–scale interactions (Peters et al., 2007) are challenging in dendritic riverine ecosystems where geomorphology, hydrology, and landscape processes influence biotic communities at multiple spatial and temporal scales (Ward, 1989, 1998; Wiens, 2002; Allan, 2004; Lowe et al., 2006). Whole watersheds are logical units for examining these ecological processes because they are contained within distinct natural boundaries (i.e., Montgomery, 1999; Benda et al., 2004; Lowe et al., 2006). There is also a growing body of knowledge about watershed–scale processes and how they shape and influence ecosystem services (e.g., Naiman & Bilby, 1998; Fagan, 2002; Wiens, 2002; Allan, 2004). This knowledge can guide comparative studies and allows key principles of ecosystem processes to be uncovered (e.g., Grant et al., 2007). It can also promote the development of management strategies designed to enhance and protect the functionality of these systems (Lowe et al., 2006). By learning how far ecosystems can be perturbed without harming their integrity, resource managers can make informed decisions regarding natural resources. Ecological pro� cesses like stable food webs that provide abundant fish for harvest, or high and stable biodiversity that can facilitate ecosystem resilience, are essential to maintain sustainable riverine ecosystems. Only eco� systems that are managed sustainably will provide perpetual services without losing process elements and system integrity (Westra et al., 2000; Hooper et al., 2005; Karr, 2006).

First, 2nd and 3rd–order channels (Strahler, 1957) (hereafter headwaters) can comprise over 80% of channel length in a watershed (Dunne & Leopold, 1978). These small tributaries and their integral riparian environments are hotspots for watershed faunal diversity (e.g., Naiman & Decamps, 1997; Ward, 1998; Ward & Tochner, 2001; Fernandes et al., 2004; Sabo et al., 2005). The loss of this diversity can have negative consequences for entire ecosystems and their ability to function and provide sustainable services (e.g., Naeem, 1994; Loreau et al., 2002; Duffy, 2003; Dobson et al., 2006). Here, we focus on the ecological attributes of headwater tributar� ies and their unique aquatic and riparian animal assemblages (Lowe & Likens, 2005; Richardson et al., 2005). Headwater streams provide key functional links with terrestrial (Nakano & Murakami, 2001) and downstream environments (Wipfli et al., 2007; Freeman et al., 2007); they improve water quality, sort, clean, and deliver coarse organic substrates needed by stream organisms for cover and repro� duction, and provide nutrients for fish. Knowledge of how watershed level processes can potentially affect these functions is paramount for managing and maintaining the ecological integrity of riverine ecosystems (Meyer et al., 2007).

Our first objective was to describe unique low–or� der tributary types within the South Fork Trinity River (SFTR) watershed based on attributes representing a wide range of conditions, ecological processes, and

65

disturbance regimes. To do this we used a combination of upland, riparian, and aquatic attributes associated with 60 randomly selected tributaries from across the entire watershed. We initially considered 69 variables, representing three spatial scales and numerous eco� logical processes, in a cluster analysis to distinguish unique tributary types. We followed with a series of scale–specific discriminant analyses, which served to reduce the number of independent variables and to detect those most informative attributes within and across scales. Our second objective was to determine if the abundance, evenness and species richness of common species or species groups differed between reach types, seeking potential bio–indicators. Our third objective was to model the distribution patterns of the bio–indicators using refined sub–sets of those independent variables used to differentiate the reach types. Understanding the environmental gradients that influence these bio–indicators can reveal important thresholds and key relationships that enable their uses as indicators of ecosystem integrity.

Material and methods Study area and sampling The SFTR is a 2,430 km2 catchment in the Klam� ath–Siskiyou bioregion of northwestern California, USA. (fig. 1). This bioregion is a globally significant area of biodiversity due to its age, range of geo� morphologies, soil types and moisture gradients, conditions that have created high endemism and many relict species (Whittaker, 1960, 1961; Welsh, 1994; DellaSalla et al., 1999; Sawyer, 2006). The SFTR is dominated on the west side by Douglas–fir (Pseudotsuga menziesii) mixed conifer/hardwood forest, with lesser amounts of ponderosa pine (Pinus ponderosa), montane hardwood–conifer, montane hardwood, montane riparian, and blue oak (Quercus douglasii)–gray pine (Arceuthobium occidentale) for� ests (Mayer & Laudenslayer, 1988); drier forest types are more dominant on the east side. Ownership is a mixture of federal (US Forest Service) and private lands. Periodic fires constitute an important natural disturbance with the SFTR experiencing median fire intervals of 11.5–16.5 years (Taylor & Skinner, 2003).

The conservation strategy of the US Northwest Forest Plan (Thomas et al., 2006) lists the SFTR as a key watershed for the preservation of salmonid fishes.

A stratified random approach was used to distrib� ute 60 sample locations across the entire watershed in order to capture the full range of headwater aquatic and riparian conditions (fig. 1). Headwa� ters were located using a Geographic Information System (GIS; ESRI, Redlands, CA) grid (cell size 1 km2) overlaid on the watershed. Fifteen equally sized polygons were created from north to south, with four 1 km2 cells randomly selected in each one. The centers of these grid cells were used to locate the closest headwater tributary. GIS–derived locations were visited and searched for potential sample reaches within 2 km of each starting point.

Welsh et al.

66

The search criteria consisted of locating a ≥ 300 m stream reach of accessible perennial surface flow shallow enough to sample without diving. Reaches near abrupt changes in vegetation (i.e., edge) and those surrounded by highly heterogeneous forest types were avoided. Although the SFTR contains many small roads used for timber harvesting and private access, this network was not used to find locations; channel access at or near roads required locating reaches ≥ 50 m upstream.

Data collection We sampled sub–basins 14 to 1,900 ha in size and measured variables at three nested spatial scales that are not mutually exclusive.

The sub–basin scale Attributes at the sub–basin scale were coarse in resolution, including topographic features and vege� tation mosaic elements representative of the entire sub–basin. Features included relative amounts of the primary forest types, annual minimum and maximum air temperatures and solar illumination, and geogra� phic features including aspect and mean elevation.

Values for sub–basin attributes were determined in GIS to characterize the larger spatial context in which reaches were embedded (appendix 1; 22 sub–basin scale variables).

The reach scale Reach scale variables characterized the proximate tributary environment by measuring the structure and plant species composition immediately surrounding each reach (e.g., tree species composition by size class, ground cover vegetation). Variables were collec� ted in three circular plots centered on the reach and spaced equally at 50, 150, and 250 m. Each reach included 1/10th and 1/5th ha concentric circles, and one soil station per side, 25 m above the channel (appendix 1: 28 reach scale variables).

The habitat unit scale Habitat unit scale variables characterized conditions within each reach, including canopy cover and stream channel morphology. We deployed water temperature data–loggers from June to October at the bottom of each reach to measure summer water temperatures.

These data were used to calculate a mean weekly maximum water temperature (MWMT; Dunham et al., 2005). MWMT is derived by averaging the daily maximum water temperatures for the hottest week of the summer. At this latitude, greater daily extremes occur in summer and are more limiting than winter minimums for cool temperate–adapted fauna such as salmonids and many amphibians (Magnuson et al., 1979; Huey, 1991). We estimated fine sediments by calculating mean sediment depths from 10 pools in each reach (e.g., Welsh & Ollivier, 1998) (appendix 1: 19 variables).

Animal sampling Two teams collected fish, amphibian and reptile data during daylight hours in June through Sep� tember from 2000–2003. The herpetofauna team used a four–tiered aquatic/riparian/upland ap� proach consisting of: (1) a channel–focused visual encounter survey (VES; Crump & Scott, 1994) of each 300 m reach, (2) 10 area–constrained (ACS) cross–channel aquatic sampling belts, (3) one ½– hour seep–focused VES search, and (4) one upland (terrestrial) 4–hour VES search conducted on clear days between 10 am and 4 pm (Welsh & Hodgson, 1997). The channel–focused VES consisted of a single observer walking slowly upstream recording all observations. The observer walked three to four paces, stopped and scanned the wetted channel and bank–full width for animals. The 10 ACS consisted of one to two observers systematically searching a defined stream area, using acrylic view boxes to search underwater before, during, and after remov� ing all detachable channel substrates. A small dip net, held immediately downstream of the view box, captured dislodged animals. Locations of the ACS belts were determined by dividing the reach into five 60 m sub–sections and locating each belt us� ing random numbers. Within each sub–section, one "fast water" and one "slow water" habitat unit was selected based upon relative water velocity (e.g., Hawkins et al., 1993). Within each habitat unit, 1 m long cross–stream belts were situated in accessible habitat; areas that prohibited thorough searching (i.e., large downed logs) were avoided. The seep VES consisted of searches in seeps or springs detected during the channel VES. The upland VES occurred at least 10 m above riparian vegetation and was conducted for two–person hours on each side of a reach; data were collected at 40 reaches in 2003. The herpetological richness analysis included incidentals from 20 reaches re–sampled in 2001 and 2002.

Fish data were collected in 2001, but due to re� duced late–summer flows and equipment failure only 55 of 60 reaches were sampled. The two–person fish team used a Smith–Root backpack electrofisher to sample fish. While electrofishing, we minimized cur� rent and set voltage to reduce animal trauma while facilitating capture (Reynolds, 1996). Each 300 m reach was divided into three sections. Within each 100 m subsection, we used six random numbers to locate sample units (18 units sampled per reach).

When arriving at the first random distance from the bottom of each section, we electrofished the closest intact habitat unit (fast or slow) using a multiple–pass method. Block nets were not used because tributaries were small and water velocities low. Stunned animals were captured with nets and held in stream water.

Animals seen but not captured were counted and identified to species and size category. To ensure conservative estimates, the number of un–captured animals enumerated during the successive n + 1 passes could not exceed the number encountered during pass n, unless obvious differences in size were observed. After the first habitat unit, the next

Animal Biodiversity and Conservation 33.1 (2010)

67

random distance upstream was used to find the nearest opposite type (fast or slow water). The fish team sampled ≥ four days before or after the herpetofauna team.

Data analysis

* 40º 45'

Cluster analysis of environmental variables rk fo ay H C ek re rk Fo ity in Tr er iv R

N

h ut So

The clustering procedure established four unique reach groups, but it provided no information on the relative importance of the 69 variables. We employed discriminant analysis (DA) to determine which vari� ables differed among the four types and to rank their relative importance (Green & Vascotto, 1978; McCune & Grace, 2002). Ecological subsets were arranged by spatial scale and analyzed in a hierarchical series of DAs (SAS Institute Inc., 2003) to identify those variables that best determined group membership in each subset and at each scale. Variables at each scale were divided into subsets representing structural, compositional, or climatic attributes of the landscape, forest stand or stream environment (appendix 1) (e.g., Welsh & Lind, 1995). Four–group DAs were performed on each subset at each scale (appendix 1). The null hypothesis tested was that there were no differences between reach types for the variables within each subset. For model–building, variables were entered if the P value for the partial F statistic was ≤ 0.10 and removed it if it was > 0.05. A linear or quadratic discriminant function was calculated based on the variables selected. Bartlett’s modification of the likelihood ratio analysis was used to test the

n tai un Mo

Multi–scale discriminant analysis

rk Fo uth So

Our overall objective was to examine the full range of aquatic and riparian conditions that characteri� zed SFTR headwaters, and relate those conditions to particular faunal distributions. Therefore, we did not constrain our sampling to a specific set of attributes other than stream order. This enabled us to incorporate the considerable heterogeneity along multiple environmental gradients and across multiple spatial scales to characterize both reaches and the surrounding sub–basins in which they were embedded. However, we did assume that sufficient commonalities would exist among the 60 tributaries that would allow us to detect a reasonable number of unique sets based on their shared positions in the dendritic network and along environmental gradients.

This would enable us to both compare reach types and to discern possible reasons for differences in animal distributions and abundances. To this end, we used non–hierarchical K–Means cluster analysis (Hintze, 2000), which minimizes the within–cluster sums of squares. We eliminated one variable each from six highly correlated (r ≥ 0.70) pairs, resulting in 69 variables from three spatial scales (appendix 1), variables were used with a K–Means algorithm (with 100 random starts and 1000 iterations) to determine unique reach types and assign group membership for each of the 60 reaches.

E

W S

0 2 4 6 8 10 km

123º 20'

Fig. 1. The South Fork Trinity River Watershed, California, USA, with sampling locations of the 60 headwater reaches. Circles represent reach Group 1 (n = 13), triangles represent reach Group 2 (n = 16), squares represent reach Group 3 (n = 11), and diamonds represent reach Group 4 (n = 20).

See methods for details on the determination of group membership.

Fig. 1. La cuenca del río South Fork Trinity, California, USA, con las 60 localizaciones de muestreo cercanas a las cabeceras. Los círculos representan el Grupo 1 de localizaciones (n = 13), los triángulos el Grupo 2 (n = 16), los cuadrados el Grupo 3 (n = 11), y los diamantes el Grupo 4 (n = 20).

Para los detalles sobre la pertenencia a un grupo determinado, ver los métodos.

homogeneity of variance–covariance matrices (SAS Institute Inc., 2003).

We then combined the significant variables from the DAs of the ecological subsets and performed composite DAs at each spatial scale. Our objective was to derive a reduced set of variables that best distinguished the reach types at each scale. We then ran a final multi–scale DA with the reduced number of variables from each scale–specific DA. With this iterative approach we were able to find those variables that were best able to discriminate between the reach types at each scale, and across scales, and thus reduce the initial number of environmental variables from the cluster analysis to just those that provided both the greatest discriminatory power and the most

Welsh et al.

68

information on how the tributary types differed. We tested the ability of our DA models to accurately predict whether or not the data from a given reach fit a particu� lar reach type (i.e., classification success) using both a jackknife procedure and a re–substitution test (SAS Institute Inc., 2003). Cohen’s Kappa statistic (Titus et al., 1984) was computed for each model to indicate the classification success compared with chance. For this test, we equalized the prior probabilities of group membership because the true proportion of sites in each of the reach groups was unknown prior to the analysis (SAS Institute Inc., 2003).

Analysis of animal distributions We ran ANOVAs (SAS Institute Inc., 2003) to examine the abundances, richness and evenness of faunal assemblages and individual species among the reach types, testing the null hypothesis of no difference in abundance for each assemblage or species across the four types. Our approach was based on the assumption that differences in animals among the reach types could be directly or indirectly linked to the different ecological attributes of these types. An example of an indirect link is the occurrence of tailed frogs (Ascaphus truei), a cold–water–adapted species whose presence can represent the capacity of streams to support similarly adapted fauna such as coho salmon (Oncorhynchus kisutch; Welsh & Hodgson, 2008). For parametric ANOVA we used log or square root transformations to reduce skewness. The distribution of crayfish could not be normalized so we used a non–parametric Krus� kal–Wallis ANOVA. When ANOVAs were significant, we used the Student–Newman–Keuls (SNK) a posteriori multiple comparisons to test group differences. We set α ≤ 0.10, as this level reduces chances of type II errors and is more appropriate for detecting ecological trends (Shrader–Frechette & McCoy, 1993).

Predictive models To examine the relationships between the envi� ronmental attributes (appendix 1), and amphibian richness, and those individual species that varied by stream group based on ANOVA, we evaluated competing predictive models comprised of subsets of these attributes. Lizard diversity and western fence lizard (Sceloporus occidentalis) abundance varied significantly among stream groups based on ANOVA, but they are not riparian or aquatic obligates and their predictive models were weak so they were omitted in this final analysis. Using Spearman correlation analyses, we reduced the environmental attributes to those significantly correlated (α ≤ 0.1) with each of five bio–indicators. Relationships between these attributes and faunal metrics were assessed with non–parametric multiplicative regression analysis (NPMR) (McCune, 2006) using the software Hy� perNiche version 1.0 (McCune & Mefford, 2004).

NPMR, designed for multivariate niche modeling, seeks to optimize a fit of detection data along multiple environmental gradients (i.e., in multi–dimensional attribute space) rather than adhere to a specific

model form like linear or Poisson regression. NPMR considers interactions among all predictor variables in a given model (McCune, 2006). NPMR estimates a response at a given point in the predictor space by heavily weighting points that are near a target point, and giving less weight to distant points (using a minimum of three points); data points employed in the model comprise the ecological neighborhood. In model generation, we set the minimum neighborhood size to five percent of each sample. The term "tole� rance" is used to describe how broadly information is borrowed from nearby areas in predictor space while attempting to estimate the value of a particular attribute around a target point (McCune, 2006); it is thus akin to the niche breadth for that attribute.

Tolerance is then the bandwidth used in the multi� plicative kernel smoother, given in the units of the environmental attribute (McCune, 2006). A species that is broadly tolerant to a particular attribute uses information from a large neighborhood of data points (McCune, 2006). We used a local mean estimator and Gaussian weighting function in all–possible–sub� sets regression for each set of models. Models were assessed using a leave–one–out cross–validated R2 (xR2), which is equal to one minus the ratio of the residual sum of squares over the total sum of squares (Antoine & McCune, 2004). We used the HyperNiche exhaustive search mode to determine best models, with up to six predictor variables, based on xR2 (e.g., Giordani, 2007). Relationships between bio–indicators and variables are reported as positive (+), negative (–), or humped/U–shaped (^).

Results Cluster analysis The K–Means cluster analysis considered options from two to six groups, with the four group solution the most informative; variation in the data explained dropped from 76.1 to 71.7% beyond four groups, declining more steeply thereafter. The numbers of tributaries in these groups were 11, 13, 16, and 20.

We examined the Euclidean distance matrix values for the four group solution, and present scatter plots illustrating group separation (fig. 2).

Discriminant analyses Distinguishing tributary groups at the sub–basin scale We performed a DA of 22 sub–basin variables to detect differences in the landscape settings of the four tribu� tary groups (table 1). We found five geographic, three climatic, three disturbance, and one geologic attribute differed among the reach groups at the sub–basin scale (table 1). The best model was that of geographic relationships; the climate model was second, and the disturbance regime model third (table 1). When these 12 variables were combined in a sub–basin scale DA, seven contributed to the composite model; four geographic, two climatic, and one geologic (table 1).

Animal Biodiversity and Conservation 33.1 (2010)

69

14

Group 1

Group 2

12

Group 2

10

Group 3

8

Group 4

6 4 14

Group 3

12 10 8 6 4

Group 4

14 12 10 8 6 4 4

6

8 10 12 Group 1

14

4

6

8 10 Group 2

12

14

4

6

8 10 Group 3

12

14

Fig. 2. Scatter plots of Euclidian distances showing six views of the separation of the four group solution from the K–Means cluster analysis (R Development Core Team, 2009).

Fig. 2. Diagrama de dispersión de las distancias euclidianas, que muestra seis visiones de la separación de los cuatro grupos a partir del análisis de conglomerados K–Means (R Development Core Team, 2009).

Distinguishing tributary groups at the reach scale Twenty–eight variables were used to examine differen� ces in terrestrial environments adjacent to the tributary groups (table 2). The best model consisted of tree and log attributes, with five forest structure and tree composition variables differing (table 2). Other models indicated differences in understory and ground–level vegetation, ground cover, and the amount of upland forest canopy (table 2). The composite model deri� ved from the DA of these 13 variables contained six attributes, three showed differences in numbers of small and large conifers, and medium hardwoods, and three indicated differences in riparian forest width, and amounts of ferns and leaf litter (table 2).

Distinguishing tributary groups at the habitat unit scale Nineteen channel attributes were measured within the reaches (table 3). The aquatic conditions model was the best, indicating differences among groups in the amount of overhead channel canopy, per� cent of fine sediments (S–Star), and mean weekly maximum water temperature (MWMT) (table 3).

Differences in aquatic substrates were indicated for percent boulders, pebbles, gravels, and visually estimated fine sediments (table 3). The composite model at this scale consisted of overhead canopy, fine sediments (S–Star), MWMT, percent boulders, and visually estimated fines (table 3).

Welsh et al.

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Table 1. Results of discriminant analyses of 22 sub–basin variables. Variables were sub–set into four ecological components and analyzed separately: P. PRISM data; C. Count data; % Percent data; † Variable transformed for statistical analysis. Variables included that did not enter the models are: geographic relationships (basin aspect, † basin area); disturbance regimes († plantation [%], young conifers [%], late–seral trees [%], † grass and shrubs [%], † fire, stumps [C]); parent geology († HF geology); composite (road density, † road crossings, northing, mean temperature [P], hardwood trees [%]). CV. Canonical variable. (Means and standard deviations are for untransformed data.)

Tabla 1. Resultados de los análisis discriminantes de las 22 variables de las subcuencas. Las variables se clasificaron en cuatro componentes ecológicas y se analizaron por separado: P. Datos PRISM; C. Datos de recuento; % Porcentajes; † Variable transformada para el análisis estadístico. Las variables incluidas en los análisis pero que no entraron en los modelos son: relaciones geográficas (aspecto de la cuenca, † área de la cuenca); regímenes de perturbación († plantación [%], coníferas jóvenes [%], árboles seriales tardíos [%], † hierba y arbustos [%], † fuego, tocones [C]); geología original († geología HF, rocas metamórficas precretácicas); composición (densidad carreteras, † cruces carreteras, distancia hacia el norte, temperatura media [P], árboles leñosos [%]). CV. Variable canónica. (Las medias y las desviaciones estándar son de los datos no transformados).

K–Means cluster groupings

1 (n = 13)

Variables

Mean

SD

2 (n = 16) Mean

SD

3 (n = 11) Mean

SD

Pooled within–group 4 (n = 20)

standardized CV

Mean

CV1

SD

CV2

CV3

Geographic relationships Easting

31.28 15.39

14.44

5.54

Northing

46.53 19.10

53.97 12.37

50.95

8.91

9.49

0.85 0.71 –0.93

28.21 11.26

–0.01 1.11 –0.87

Elevation 1226.00 171.15 647.50 189.76 1190.91 445.72 989.70 273.30

0.24 0.76 0.33

26.29 19.22

38.72

Illumination in December

Slope (%)

135.33 26.32 0.18

0.07

96.05 24.67 0.19

0.08

86.48 31.86 0.12

0.08

98.26 23.88 0.06

0.04

–0.29 0.41 0.83 –0.57 0.52 –0.69

Wilks’ lambda = 0.072; F (df = 15,144) = 15.25; P < 0.0001

Jackknife success (%) = 75.0; Cohen's Kappa = 0.660; P < 0.0001

Climate Precipitation (P)

129.63 16.40 131.65 10.52

116.45 15.62 131.36 16.50

0.64 0.11 0.97

Mean temperature (P)

11.08

0.62

11.58

0.68

11.53

1.02

10.18

0.79

1.42 0.68 –0.13

Minimum temperature (P)

3.52

1.45

3.15

0.66

5.56

1.20

2.65

1.42

–1.25 0.44 0.50

Wilks’ lambda = 0.261; F (df = 9,132) = 10.76; P < 0.0001

Jackknife success (%) = 63.3; Cohen's Kappa = 0.507; P < 0.0001

Disturbance regimes Road density 0.01

0.01

0.01

0.01

0.01

0.01

0.01

0.00

0.62 –0.88 –0.04

† Road crossings

1.08

1.85

3.06

4.48

1.45

2.11

9.00 10.11

0.37 0.74 –0.70

Hardwood trees (%)

0.20

0.20

0.21

0.17

0.24

0.16

0.40

0.20

0.62 0.07 0.85

Wilks’ lambda = 0.433; F (df =12,141) = 4.36; P < 0.0001 Jackknife success (%) = 51.7; Cohen's Kappa = 0.355; P < 0.0001

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Table 1. (Cont.)

K–Means cluster groupings 1 (n = 13)

Variables

Mean

SD

2 (n = 16) Mean SD

3 (n = 11) Mean

SD

Pooled within–group

4 (n = 20) Mean

SD

standardized CV CV1

CV2

CV3

Parent geology † RCM geology (%)

0.33

0.47

0.84

0.34

0.00

0.00

0.78

0.36

1.00

Wilks’ lambda = 0.506; F (df = 3,56) = 18.20; P < 0.0001

Jackknife success (%) = 45.0; Cohen's Kappa = 0.280; P < 0.0001

Composite model Easting

31.28 15.39

14.44

5.54

50.95

8.91

38.72

9.49

0.98 –0.74 –0.02

Minimum temperature (P)

3.52

1.45

3.15

0.66

5.56

1.20

2.65

1.42

–0.37 0.91 –0.69

Illumination December

135.33 26.32

96.05 24.67

86.48 31.86

98.26 23.88

–0.18 –0.22 1.01

Elevation 1226.08 171.15 647.50 189.76 1190.91 445.72 989.70 273.30

0.15 0.75 0.56

† RCM geology (%)

Slope (%)

0.33

0.47

0.84

0.34

0.00

0.00

0.78

0.36

–0.38 –0.65 –0.12

18.08

7.24

18.87

7.96

12.09

8.17

6.50

3.68

–0.77 0.25 0.12

Precipitation (P)

129.63 16.40 131.65 10.52

116.45 15.62 131.36 16.50

0.27 –0.56 –0.25

Wilks’ lambda = 0.024; F (df = 24,143) = 15.63; P < 0.0001

Jackknife success (%) = 85.0; Cohen's Kappa = 0.797; P < 0.0001

Distinguishing tributary groups across spatial scales

Stream groups and animal distributions

Combining variables from the three scale–spe� cific composite models into a multi–scale model resulted in a final model comprised of 10 varia� bles —five from the sub–basin scale, three from land–surrounding–the–reaches, and two from within the reaches (table 4). This model indicated that tributaries in the SFTR watershed were best distinguished by easting, sub–basin slope, illumi� nation in December, annual minimum air tempe� rature, mafic volcanic rock and chert, numbers of conifers 28–60 cm DBH, numbers of hardwoods 28–60 cm DBH, riparian width, MWMT, and per� cent of fine sediments (S–Star) (table 4). Using canonical scores from the greatly reduced set of variables in this multi–scale model (10 vs. 69 in the cluster analysis) we plotted the relationships of the 60 tributaries in three dimensions (fig. 3).

The final multi–scale model improved group se� paration and provided useful information on the environmental gradients that separated the reach groups compared to the cluster analysis.

We found no differences in reptile or amphibian evenness, or in reptile richness among tributary groups. However, amphibian richness differed, with Group 2 having significantly greater richness than the other three groups (table 5). Several species including the southern torrent salamander (Rhyacotriton variegatus), the black salamander (Aneides flavipunctatus), the rough–skinned newt, and the Pacific chorus frog (Pseudacris regilla), were de� tected in numbers too low to test individually with ANOVA, but none–the–less contributed to differences in amphibian richness. Two anurans were sufficiently widespread and abundant for ANOVA. The foothill yellow–legged frog (Rana boylii) was more abundant in tributaries of Group 2 compared to the other types and the tailed frog was more abundant in tributaries of Group 1 compared with the other groups (table 5).

Lizards (all species combined) were more abundant along tributaries of Group 4 compared with those of Group 2, and the western fence lizard was more abundant along tributaries of Group 4 compared

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72

Table 2. Results of discriminant analyses of 28 attributes surrounding the reach. Variables were sub– set into four ecological components and analyzed separately: † Variables transformed for statistical analysis (see table 1 for variable codes). Variables included in the analyses that did not enter the models are: trees and logs († Hardwood 61–120 cm DBH [C], mean stand age, maximum stand age, conifer > 120 cm DBH [C]; † Hardwood 15–27 cm DBH [C], logs [C]); Understory vegetation (shrub, %); Ground level vegetation († herb, %); Ground cover († soil [%], rock [%], organic debris [%], litter depth [%]); Forest climate (upland canopy variation [%], soil temperature, air temperature); Composite (conifer 61–120vcm DBH [C], † conifer seedling [%], † hardwood seedling [%], † grass [%], moss [%], log [%], upland canopy closure [%]); CV. Canonical variable. (Means and standard deviations are for untransformed data.)

Tabla 2. Resultados de los análisis discriminantes de 28 atributos de los cursos. Las variables se subclasificaron en cuatro componentes ecológicas y se analizaron por separado: † Variable transformada para el análisis estadístico (véase la tabla 1 para los códigos de las variables). Las variables incluidas en los análisis pero que no entraron en los modelos son: árboles y troncos († madera dura 61–120 cm DAP [C], edad media de la madera en pie, edad máxima de la madera en pie, coníferas > 120 cm DAP [C]; † Madera dura 15–27 cm DAP [C], troncos [C]); Vegetación del sotobosque (arbustos, %); Vegetación a nivel del suelo († hierba, %); Superficie del suelo († suelo [%], roca [%], desechos orgánicos [%], profundidad del mantillo [%]); Clima forestal (variación del dosel en tierras altas [%], temperatura del suelo, temperatura del aire); Composición (coníferas 61–120 cm DAP [C], † brotes de coníferas [%], † brotes de madera dura [%], † hierba [%], musgo [%], troncos [%], cobertura del dosel en tierras altas [%]); CV. Variable canónica. (Las medias y las desviaciones estándar son de datos no transformados.)

K–Means cluster groupings 1 (n = 13)

Variables

Mean

SD

2 (n = 16) Mean SD

Pooled within–group

3 (n = 11)

4 (n = 20)

standardized CV

Mean SD

Mean SD

CV1 CV2 CV3

Trees and logs † Hardwood 28–60 cm DBH (C)

4.38

3.84

18.12

8.61

1.91

2.47

4.40

3.65

–0.78 –0.09 0.31

† Riparian forest width (m)

3.03

1.70

4.75

1.67

6.48

4.38

5.60 2.54

0.28 0.69 –0.44

Conifer 15–27cm DBH (C)

27.31 12.72

7.25

4.49

18.73 10.48

18.90 7.55

0.16 –0.71 –0.54

Conifer 28–60cm DBH (C)

19.31

8.74

4.94

2.89

23.64 13.97

13.20 7.29

0.58 0.32 0.48

Conifer 61–120cm DBH (C)

18.62

9.23

9.75

8.32

22.73

8.70

13.25 7.85

0.37 0.17 0.60

Wilks’ lambda = 0.136; F (df = 18,145) = 8.25; P < 0.0001

Jackknife success (%) = 70.0; Cohen's Kappa = 0.595; P < 0.0001

Understory vegetation † Conifer seedling (%)

0.18

0.15

0.07

0.06

0.09

0.08

0.10 0.05

–0.35 0.95

† Hardwood seedling (%)

0.09

0.05

0.21

0.14

0.05

0.05

0.13 0.05

0.99 0.20

Wilks’ lambda = 0.550; F (df = 6,110) = 6.40; P < 0.0001

Jackknife success (%) = 53.3; Cohen's Kappa = 0.377; P < 0.0001

Ground level vegetation † Fern (%) 0.07

0.07

0.08

0.07

0.03

0.03

0.03 1.87

0.78 0.63

† Grass (%) 0.10

0.08

0.04

0.04

0.09

0.06

0.06 0.04

–0.64 0.77

Wilks’ lambda = 0.639; F (df = 6,110) = 4.60; P < 0.0003 Jackknife success (%) = 40.0; Cohen's Kappa = 0.200; P < 0.0083

Animal Biodiversity and Conservation 33.1 (2010)

73

Table 2. (Cont.)

K–Means cluster groupings

1 (n = 13)

Variables

Mean SD

2 (n = 16)

3 (n = 11)

Mean SD

Mean SD

Pooled within–group

4 (n = 20) Mean

SD

standardized CV CV1 CV2 CV3

Ground cover Leaf (%)

0.85

0.06

0.70

0.19

0.81

0.08

0.61 0.19

0.04 0.98 –0.43

Moss (%)

0.03

0.02

0.18

0.09

0.04

0.05

0.08 0.07

0.99 0.35 0.10

Log (%)

0.10

0.05

0.07

0.04

0.05

0.03

0.07 0.03

–0.36 0.14 0.97

Wilks’ lambda = 0.330; F (df = 9,132) = 8.42; P < 0.0001

Jackknife success (%) = 53.3; Cohen's Kappa = 0.385; P < 0.0001

Forest climate Upland canopy closure (%)

0.83

0.11

0.91

0.05

0.83

0.08

0.75 0.14

1.00

Wilks’ lambda = 0.730; F (df = 3,56) = 6.90; P = 0.0005

Jackknife success (%) = 43.3; Cohen's Kappa = 0.236; P < 0.0035

Composite model Conifer 15–27cm DBH (C)

27.31 12.72

7.25

4.49

18.73 10.48

18.90

7.55

0.29 0.19 –0.85

Conifer 28–60 cm DBH (C)

19.31

8.74

4.94

2.89

23.64 13.97

13.20

7.29

0.55 –0.02 0.55

† Hardwood 28–60 cm DBH (C)

4.38

3.84

18.12

8.61

1.91

2.47

4.40

3.65

–0.89 0.11 0.01

† Riparian forest width (m)

3.03

1.70

4.75

1.67

6.48

4.38

5.60

2.54

0.14 –0.65 0.20

† Fern (%)

0.07

0.07

0.08

0.07

0.03

0.03

0.03

1.87

–0.68 0.14 –0.03

Leaf (%)

0.85

0.06

0.70

0.19

0.81

0.08

0.61

0.19

0.08 0.64 0.61

Wilks’ lambda = 0.086; F (df = 21,144) = 9.28; P < 0.0001

Jackknife success (%) = 78.3; Cohen's Kappa = 0.709; P < 0.0001

to all other groups (table 5). Steelhead trout were more abundant in tributaries of Group 4 compared to the other three groups (table 5). Crayfish were more abundant in tributaries of Group 4 compared with Group 1 (table 5).

Predictive models of bio–indicators The NPMR of amphibian richness used 21 environ� mental variables that were significantly correlated (ap� pendix 1). The best single variable predicting greater amphibian richness was northing (+) (xR2 = 0.226; table 6). The model improved with the addition of elevation (–), stumps (–), hardwood seedlings (+), and moss (+), respectively (xR2 = 0.558; table 6).

The NPMR of the foothill yellow–legged frog used 19 variables correlated with this species (appen� dix 1). The best single variable was soil temperature

(+) (xR2 = 0.243; table 6). This model improved with the addition of sub–basin area (+), % of sub–basin in tree plantations (–), % of sub–basin in hardwoods (–) and elevation (–), respectively (xR2 = 0.514; table 6).

The NPMR of larval tailed frogs used 25 variables correlated with this species (appendix 1). The best single variable was the number of small conifers (+) (xR2 = 0.099; table 6). The model improved with the addition of % soil ground cover (–), % leaf litter (+), % debris ground cover (+) and % stream gravel (+), respectively (xR2 = 0.366; table 6).

The NPMR of steelhead trout used 25 variables correlated with this species (appendix 1). The best single variable was sub–basin area (+) (xR2 = 0.510; table 6). This model improved with the addition of the number of road crossings (+), % soil ground cover (+), % upland rock (+) and % stream gravel (–), respectively (xR2 = 0.719; table 6).

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74

Table 3. Results of discriminant analyses of 19 attributes within the reach. These variables were sub– set into four ecological components, each analyzed separately: † Variable transformed for statistical analysis (see table 1 for variable codes). Variables included in the analyses that did not enter the models are: aquatic conditions (reach aspect, † habitat width, S* sediment index, maximum depth, water temperature daily amplitude, flow in fast habitats, embeddedness in slow habitats); Aquatic substrates († bedrock [%], large woody debris [%], cobble [%], detritus [%], † sand [%]); Composite (pebble [%], gravel [%]); CV. Canonical variable. (Percent data is indicated by (%); means and standard deviations are for untransformed data.)

Tabla 3. Resultados de los análisis discriminantes de 19 atributos de los cursos. Dichas variables se subclasificaron en cuatro componentes ecológicas, y cada una de ellas se analizó por separado: † Variable transformada para el análisis estadístico (ver tabla 1 para los códigos de las variables). Las variables incluidas en los análisis pero que no entraron en los modelos son: condiciones acuáticas (aspecto del cauce, † anchura del hábitat, S* índice sedimentario, profundidad máxima, oscilación máxima diaria de la temperatura del agua, flujo en los hábitats rápidos, encajamiento en los hábitats lentos); Sustratos acuáticos († lecho rocoso [%], restos de madera grandes [%], guijarros [%], detritus [%], † arena [%]); Composición (cantos rodados [%], grava [%]); CV. Variable canónica. (Los datos porcentuales se indican mediante (%); las medias y las desviaciones estándar son para los datos no transformados.)

K–Means cluster grouping

1 (n = 13)

2 (n = 16)

3 (n = 11)

Variables

Mean SD

Mean SD

Mean

SD

Pooled within–group 4 (n = 20) Mean

SD

standardized CV CV1

CV2 CV3

Aquatic conditions Canopy over stream (%)

0.91

0.05

S* fines (%) 0.70 MWMT

13.26

0.96

0.03

0.91

0.07

0.21

0.45

1.20

14.91

0.89 0.04

–0.11 1.03 0.08

0.18

0.36

0.21

0.31 0.08

0.82 –0.10 0.58

1.49

14.55

2.96

16.53 1.81

–0.62 0.14 0.81

Wilks’ lambda = 0.322; F (df = 9,132) = 8.67; P < 0.0001

Jackknife success (%) = 58.3; Cohen's Kappa = 0.436; P < 0.0001

Aquatic substrates Boulder (%) 0.03

0.04

0.16

0.13

0.13

0.11

0.21 0.10

–0.40 0.85 –0.41

Pebble (%) 0.16

0.09

0.21

0.07

0.22

0.07

0.19 0.06

–0.77 0.48 0.87

Gravel (%)

0.12

0.21

0.08

0.20

0.08

0.16 0.05

0.86 –0.03 –0.25

0.19

0.07

0.07

0.02

0.02

0.02 0.02

0.62 0.79 0.10

0.30

† Fines (%) 0.19

Wilks’ lambda = 0.269; F (df = 12,140) = 7.54; P < 0.0001

Jackknife success (%) = 53.3; Cohen's Kappa = 0.373; P < 0.0001

Composite model Canopy over stream (%)

0.91

0.05

0.96

0.03

0.91

0.07

0.89 0.04

–0.10 0.94 –0.30

S* fines (%) 0.70

0.21

0.45

0.18

0.36

0.21

0.31 0.08

0.50 –0.13 0.48

MWMT

13.26

1.20

14.91

1.49

14.55

2.96

16.53 1.81

–0.55 0.24 0.58

Boulder (%) 0.03

0.04

0.16

0.13

0.13

0.11

0.21 0.10

–0.31 0.49 0.43

† Fines (%) 0.19

0.19

0.07

0.07

0.02

0.02

0.02 0.02

0.47 0.48 0.34

Wilks’ lambda = 0.213; F (df = 15,144) = 7.21; P < 0.0001 Jackknife success (%) = 60.0; Cohen's Kappa = 0.457; P < 0.0001

The NPMR of crayfish used 20 correlated variables (appendix 1). The best single variable was mesohabitat width (^; hump–shaped) (xR2 = 0.304; table 6). The

model improved with % of mafic volcanic rock and chert (+), % of young hardwoods (+), % of fern cover (–) and embeddedness (–), respectively (xR2 = 0.557; table 6).

Animal Biodiversity and Conservation 33.1 (2010)

75

Table 4. Results of discriminant analyses of 20 environmental attributes from three spatial scales. P–value to enter was set at 0.10 and P–value to remove was set at 0.05: † Variable transformed for statistical analysis (see table 1 for variable codes). Variables included in the analyses but that did not enter the models are: elevation, precipitation (P), conifer 15–27 cm DBH (C), † fern (%), leaf (%), canopy over stream (%), boulder (%), † fines (%). CV. Canonical variable. (Means and standard deviations are for untransformed data.)

Tabla 4. Resultados de los análisis discriminantes de 20 atributos ambientales de tres escalas espaciales. El valor de P para añadir se situó a 0,10, y el valor de P para quitar se situó a 0,05: † Variable transformada para el análisis estadístico (ver tabla 1 para los códigos de las variables). Las variables incluidas en los análisis pero que no entraron en los modelos son: elevación, precipitación (P), coníferas 15–27 cm DAP (C), † helechos (%), hojas (%), dosel sobre la corriente (%), piedras grandes (%), † granos finos (%). CV. Variable canónica. (Las medias y las desviaciones estándar son de datos no transformados.)

K–Means cluster groupings

1 (n = 13)

Variables

Mean

SD

2 (n = 16) Mean SD

3 (n = 11) Mean

SD

4 (n = 20) Mean SD

Pooled within–group standardized CV CV1 CV2 CV3

Composite of composites Easting Slope (%)

31.28 15.39 0.18

0.07

14.44

5.55

50.95

8.91

38.73 9.49

–0.73 0.27 –0.78

0.19

0.08

0.12

0.08

0.06 0.04

0.50 0.05 0.12

Illumination December

135.33 26.32

96.05 24.67

86.48 31.86

98.26 23.88

0.53 0.62 –0.71

Minimum temperature (P)

3.52

1.45

3.15

0.66

5.56

1.20

2.65 1.42

0.18 –0.05 1.26

† RCM geology (%)

0.35

0.47

0.85

0.34

0.00

0.00

0.81 0.36

0.22 –0.17 –0.45

Conifer 28–60cm DBH (C)

19.31

8.74

4.94

2.89

23.64 13.97

13.20 7.29

–0.05 0.51 0.24

† Hardwood 28–60cm DBH (C)

4.38

3.84

18.13

8.61

1.91

2.47

4.40 3.65

0.65 –0.29 –0.01

† Riparian width

3.03

1.70

4.75

1.67

6.48

4.38

5.60 2.54

–0.37 –0.50 0.23

13.26

1.20

14.91

1.49

14.55

2.96

16.53 1.81

–0.49 –0.31 –0.25

S* fines (%) 0.70

0.21

0.45

0.18

0.36

0.21

0.31 0.08

0.29 0.55 –0.34

MWMT

Wilks’ lambda = 0.008; F (df = 33,136) = 16.78; P < 0.0001 Jackknife success (%) = 86.7; Cohen's Kappa = 0.819; P < 0.0001

Discussion Our objectives were to detect unique sets of head� water tributaries, determine the riverscape patterns, disturbance processes, and environmental gradients associated with each set, and to link the distributions and abundances of riparian and aquatic biota with informative subsets of these attributes (e.g., Dale et al., 1994; Roth et al., 1996; Whittier et al., 2006).

The intent here was that by establishing these link� ages we would provide the basis for employing key elements of this fauna as bio–indicators of ecologi� cal services and network integrity. Any study that

purports to relate environmental conditions across multiple spatial scales and faunal elements must by necessity incorporate a large number of independent variables. Consequently, we needed to reduce a large set of variables from multiple scales into informative subsets for both the tributary groups and the fauna.

We sought to relate these reduced sets of variables to the presence and abundance of readily sampled fauna with sensitivity to system degradation (e.g., Welsh & Ollivier, 1998; Lowe & Bolger, 2002; Wilson & Dorcas, 2003), structuring of benthic communi� ties (Parkyn et al., 1997), or commercial value (i.e., steelhead trout).

Welsh et al.

76

High High Low Canonical axis 1

Slope (0.50) 5) HDWD2 (0.6 9) MWMT (-0.4

Group 1 Group 2

High Low High Low Low High High

Group 3 Group 4

Canonical axis 3

EASTING (-0.78 ) ILL UM D 8-0 .71 ) MINTEMP (1.26 ) RCMPCT (-0.45 ) Low Low High Low

High Low High

is 2 l ax nica o 1) n Ca (0.5 ) IF2 0 CON ID (-0.5 ) 5 RIPW ES (0.5 N S_FI

Low High Low

Fig. 3. Three–dimensional scatter plot of canonical scores from the multi–scale discriminant model (table 4). See appendix 1 for definitions. For illustration we used the highest absolute canonical score to assign each variable to a particular canonical axis, however, each variable loads on each of the axes.

Fig. 3. Diagrama de dispersión tridimensional de los datos canónicos del modelo discriminante multiescala (tabla 4). Para las definiciones, ver el apéndice 1. Para realizar la ilustración utilizamos el dato canónico absoluto más alto para asignar cada variable a un eje canónico en particular, a pesar de que cada variable carga valores en cada uno de los ejes.

Our study differs from previous studies that ex� amined multi–scale environmental relationships of stream–dwelling animals (e.g., Lowe & Bolger, 2002; Roni, 2002; Welsh & Lind, 2002; Stoddard & Hayes, 2005) because many of these studies selected study sites based on categorical distinctions or disjunct dis� tributions. Most studies that claim to examine drivers of environmental suitability for particular taxa at mul� tiple spatial scales, a priori select sites along existing ecological gradients. These studies, therefore, often implicitly substitute anthropogenically forced spatial differences for naturally occurring spatial or temporal differences (Landres et al., 1999). By randomly select� ing sites throughout the SFTR watershed and deter� mining groups a posteriori, our study is unbiased in this respect and thus reveals environmental gradients that occur throughout the SFTR. Our assessment of faunal assemblage responses to this environmental structure was determined at a metacommunity scale (Leibold et al., 2004).

The classification success for ecological com� ponents within spatial scales ranged from 51–75% (sub–basin scale), 40–70% (land–surrounding–the– reach scale), and 53–58% (within–reach scale). Within scales, classification success of the composite models improved markedly over the ecological sub–sets, with 85% success at the sub–basin, 78% at land–sur� rounding–the–reach, and 60% at the within–reach scale. The classification success improved even more with the final across–scales watershed level model, achieving 87% correct. As sets of variables were refined at each step, the improved success indicated an enhanced ability to discern a much reduced, yet more informative, set of attributes able to distinguish tributary types. Similar approaches using multivariate analyses have proven useful in other studies seeking to reduce the dimensionality of large data sets by finding the fewest meaningful variables to differentiate sets of sites (e.g., Radwell & Kwak, 2005; Shrestha & Kazama, 2007 and references therein).

Animal Biodiversity and Conservation 33.1 (2010)

Basin area

77

Stream width

Max pool depth

8.0

4.5

80.0

6.0

3.2

53.3

4.0

1.8

26.7

2.0

1

2 3 4 Reach group

0.5

1

2 3 4 Reach group

Elevation

0.0

MWMT

2,000.0

20.0

7.0

1,333.3

16.0

4.7

666.7

12.0

2.3

8.0

0.0 1

2 3 4 Reach group

1

2 3 4 Reach group

Water temperature amplitude

0.0 1

2 3 4 Reach group

1

2 3 4 Reach group

Fig. 4. Six key environmental attributes of the four reach groups illustrating the overlap in physical attributes consistent with a continuum (Vannote et al., 1980) or a hierarchical channel network (Benda et al., 2004). The boxes represent the middle 50% of the data, lines inside are the median, the T–shaped whiskers represent data 1.5 times past the middle 50%, and dots represent outliers.

Fig. 4. Seis atributos ambientales clave de los cuatro grupos de cursos que ilustran el solapamiento de los atributos físicos, lo que es consistente con un continuum (Vannote et al., 1980) o con una red de canales jerarquizada (Benda et al., 2004). Los cuadrados representan el 50% medio de los datos, las líneas en su interior son las medianas, los signos en forma de T representan los datos que se hallan a 1,5 veces la media del 50%, y los puntos representan los valores atípicos.

The composite multi–scale model greatly improved on the cluster analysis by using just 10 variables compared to 69, and demonstrating greatly improved separation (compare figures 2 and 3). This model distinguished the four tributary groups along informa� tive environmental gradients based on five sub–basin scale variables (50%), three from land–surround� ing–the–reach (30%), and two at the within–reach scale (20%). Four of the 10 variables represented processes or attributes that respond directly to both anthropogenic modifications and/or natural distur� bances within the landscape (conifer and hardwood counts, riparian width, stream temperature [MWMT] and percent fine substrates). The composite models at each of the scales also contained informative at� tributes that respond directly to land management practices such as forestry and road–building (Tang et al., 1997; Hemstad & Newman, 2006).

Several attributes distinguishing the reach groups overlapped in values (fig. 4) indicating that these sets likely represent different positions along a

continuum (Vannote et al., 1980), or gradient, within the dendritic network (Benda et al., 2004). Tributar� ies of Group 1 were the lowest order tributaries, at the highest elevation, with the narrowest riparian zones, lowest water temperatures, lowest daily water temperature fluctuations (amplitudes), highest fine sediment loads, and the fewest road crossings, and represented the highest end of the continuum (tables 2–4). Tributaries of Group 2 were the west� ern– and northernmost streams, received the most precipitation, and with the highest mean annual air temperatures. Although the slopes of these reaches were just slightly greater than those of Group 1, they were the lowest in elevation, and transected the most mafic volcanic rock and chert, parent material that appeared to support more hardwood compared to coniferous forest types. These tributaries also had the highest upland and over–stream canopy, with riparian areas being the highest in mesic and hydric plants (tables 2–4). Tributaries of Group 3 were the eastern– and southernmost, with the lowest winter

Welsh et al.

78

Table 5. ANOVA tests of faunal assemblages and individual amphibian and reptile species, steelhead trout, and crayfish abundances among four stream groups. Data used for individual species were the sums of VES, seeps, and 10 m2 of belts (see text), (n = 60) or electrofished reaches (n = 55).

For assemblages, we used numbers of species detected per tributary, richness including incidentals.

Several riparian and upland taxa were sampled by VES (see text), n = 40: * n = 40 (11, 9, 10, 10); ** n = 55 (12, 14, 10, 19); º Includes incidental observations; † Natural log transformed; †† Square root transformed; Ensatina. Ensatina eschscholtzii; Western fence lizard. Sceloporus occidentalis; Sagebrush lizard. S. graciosus; Northern alligator lizard. Elgaria coerulea.

Tabla 5. Test ANOVA de las abundancias de las comunidades faunísticas y las especies individuales de anfibios y reptiles, la trucha cabeza de acero y el cangrejo señal, entre cuatro grupos de cursos.

Los datos utilizados para las especies individuales fueron las sumas de VES, charcos sin drenaje y 10 m2 de cinturones de muestreo (ver el texto), (n = 60) o cursos en los que se había utilizado la pesca con electricidad (n = 55). Para las comunidades, utilizamos los números de especies detectados por afluente, la riqueza incluyendo los imprevistos. Se recogieron varios taxones de tierras altas y de zona riparia mediante VES (ver el texto), n = 40: * n = 40 (11, 9, 10, 10); ** n = 55 (12, 14, 10, 19); º Incluye observaciones accidentales; † Log natural transformado; †† Raíz cuadrada transformada; Ensatina, Ensatina eschscholtzii; Lagarto de vientre azul del oeste, Sceloporus occidentalis; lagarto de Sagebrush, S. graciosus; lagarto aligator del norte, Elgaria coerulea.

Dependent Dependent variable df MSE

F

P

Groups–mean (standard error)

Multiple comparisons

I

II

III

IV

Richnessº Amphibians 3

1.65

4.06

0.0111 2 > 1, 2 > 3, 2 > 4

Reptiles

3

3.24

0.35

2.38

3.37

1.91

2.05

(0.357) (0.322) (0.388) (0.288)

0.7926

3.64

(0.542)

4.00

3.80

4.40

(0.600) (0.569) (0.569)

Evenness Amphibians 3

0.15

2.14

0.1052

Reptiles

3

0.16

0.46

0.7126

0.61

0.60

0.43

(0.106) (0.095) (0.115) 0.51

0.59

0.63

0.33 (0.85) 0.71

(0.120) (0.133) (0.126) (0.126)

Amphibians Coast giant salamander ††

3

2.05

1.14

0.3425

*Ensatina †† 3

0.40

1.22

0.3158

7.92

10.25

5.00

6.10

(2.181) (1.966) (2.371) (1.759) 0.91

0.55

0.10

0.70

(0.302) (0.334) (0.317) (0.317)

Foothill yellow–legged frog †

3

9.70

2.59

0.0615

2 > 1

0.46

9.06

4.82

3.75

(2.767) (2.494) (3.007) (2.201)

Coast tailed frog ††

3

0.46

7.55

0.0002 1 > 2, 1 > 3, 1 > 4

2.31

0.69

0.54

0.05

(0.445) (0.401) (0.483) (0.358)

Reptiles *Western fence lizard

3

6.08

4.53

0.0085 4 > 1, 4 > 2, 4 > 3

1.36

1.00

2.60

4.70

(0.744) (0.822) (0.780) (0.780)

Animal Biodiversity and Conservation 33.1 (2010)

79

Table 5. (Cont.)

Dependent Dependent variable df MSE

F

P

Groups–mean (standard error)

Multiple comparisons

I

II

III

IV

*Sagebrush lizard ††

3

0.92

2.20

0.1053

1.36

0.33

1.30

3.30

(0.799) (0.883) (0.838) (0.838)

*North. alligator lizard

3

2.40

1.60

0.2056

*Snakes

3

1.02

1.29

0.2919

*Lizards

3 38.05

2.50

0.0750

4 > 2

1.54

2.33

1.30

0.80

(0.467) (0.516) (0.490) (0.490) 0.82

0.22

1.10

0.90

(0.306) (0.338) (0.320) (0.320) 6.82

4.78

8.10

12.2

(1.860) (2.056) (1.951) (1.951)

Fish abundances **Steelhead trout †

3

1.63

8.50

0.0001 4 > 1, 4 > 2, 4 > 3

0.00

0.85

0.95

2.27

(0.000) (0.341) (0.403) (0.293)

Non–parametric ANOVAs (Kruskal–Wallis) Dependent Dependent variable df Χ2

Groups–mean (standard error) P Multiple comparisons

I

II

III

IV

Species abundances Signal crayfish

3

7.14

0.0675

2 > 1, 4 > 1

exposure, highest minimum air temperatures, and lowest annual precipitation; they also had the great� est riparian widths and the most in–stream pebble.

Sub–basins containing these tributaries appeared to support the most coniferous forest with the highest counts of trees in the two largest conifer size classes (tables 2–4). Tributaries of Group 4 were the second lowest in elevation, had the second highest annual precipitation, and the lowest minimum annual air temperatures. These tributaries also had the lowest gradients, highest percent boulder substrates, low� est amounts of gravel, lowest fine sediment loads (tied with Group 3), the least over–stream canopy, highest water temperatures, and highest number of road crossings (tables 2–4).

Responses of the bio–indicators The coastal tailed frog was the only relatively com� mon amphibian associated with tributaries of Group 1.

However, the best predictive model (table 6) was relatively weak and uninformative (cf. Welsh &

0.00

4.06

0.82

11.85

(0.000) (2.507) (0.818) (5.962)

Lind, 2002). This poor performance likely resulted from the uneven distribution and low abundances we found for this species, despite evidence (Bury, 1968) of a once wider distribution throughout this and surrounding major watersheds, including to the east. Such patchy distributions have been observed elsewhere in recent studies, and are likely artifacts of past timber harvesting altering the requisite niche of this ancient frog, a species specifically adapted to conditions that occur most reliably in late succession forests (Welsh, 1990; Welsh & Lind, 2002; Welsh et al., 2005; Spear & Storfer, 2008). Consequently, the tailed frog is an excellent bio–indicator for the more structurally diverse, micro–climatically ameliorated, conditions typical of late seral forests (Welsh, 1990) which also support the highest levels of terrestrial salamander biodiversity (e.g., Davic & Welsh, 2004).

Furthermore, the presence of this frog can indicate the potential of streams to support coho salmon (see Welsh & Hodgson, 2008), a threatened salmonid once common in SFTR but that has not been detected in recent times.

Welsh et al.

80

Table 6. Non–parametric multiplicative regression (NPMR) models for five bio–indicators whose distributions varied significantly among stream groups. The data used in the modeling were those from just the reach groups where each metric was observed. Tolerance is in the units of the response variable and refers to the niche width along that variable; ecological neighborhood size refers to that portion of the data used to determine tolerances for each variable in the model: xR2. Leave–one–out cross–validation R2; Ns. Neighborhood size. (See methods for more details.)

Tabla 6. Modelos de regresión multiplicativa no paramétrica (NPRM) para cinco bioindicadores, cuyas distribuciones variaban significativamente entre los grupos de cauces. Los datos utilizados en la modelización fueron los de los grupos de tramos, en los que se observó todo parámetro métrico. La tolerancia está en las unidades de la variable respuesta y se refiere a la anchura del nicho a lo largo de dicha variable; el tamaño de la vecindad ecológica se refiere a la porción de los datos usados para determinar las tolerancias para cada variable del modelo: xR2. R2 por validación cruzada dejando uno afuera; Ns. Anchura de nicho. (Para más detalles, ver los métodos.)

Models (tolerance)

xR2

Ns

Amphibian richness Northing (10.3 km)

0.226 20.0

Northing (13.7 km), Moss (1.5%)

0.381

5.8

Northing (17.1 km), Moss (1.5%), Stumps (4.8)

0.536

3.6

Northing (20.5 km), Moss (1.5%), Stumps (4.8), Hardwood seedlings (3.1%)

0.552

3.2

Northing (20.5 km), Moss (1.5%), Stumps (4.8), Hardwood seedlings (3.1%), Elevation (1159.2 m)

0.559

3.1

Northing (20.5 km), Moss (1.5%), Stumps (4.8), Hardwood seedlings (4.8%), Elevation (1159.2 m), Shrub (27.2%)

0.556

3.0

Foothill yellow–legged frog Soil temperature (2.2ºC)

0.243 16.5

Soil temperature (1.5ºC), Elevation (82.8 m)

0.453

3.0

Plantation (20.7%), Elevation (165.6 m), Soil temperature (1.5ºC)

0.470

3.5

Plantation (20.7%), Elevation (165.6 m), Soil temperature (2.2ºC), Watershed area (1.8 ha)

0.494

2.8

Plantation (14.8%), Elevation (165.6 m), Soil temperature (2.2ºC), Watershed area (1.8 ha), Hardwood (55.2%)

0.514

2.4

Tailed frog Conifer 15–27 cm DBH (9.2)

0.099 18.5

Conifer 15–27 cm DBH (6.9), Debris (0.9%)

0.209

2.3

Conifer 15–27 cm DBH (9.2 cm), Debris (0.9%), Gravel (13.2%)

0.255

2.1

Conifer 15–27 cm DBH (11.5), Debris (0.9%), Gravel (13.2%), Leaf (30.8%)

0.348

2.0

Conifer 15–27 cm DBH (13.8), Debris (0.9%), Gravel (13.2%), Soil (17.7%), Leaf (30.8%)

0.366

2.0

Steelhead Watershed area (0.7 ha)

0.510 13.7

Watershed area (0.7 ha), Road crossings (0.8)

0.591

5.2

Watershed area (0.7 ha), Road crossings (0.8), Rock (13.3%)

0.650

3.1

Watershed area (0.7 ha), Road crossings (1.1), Rock (13.3%), Soil (3.4%)

0.714

2.8

Watershed area (0.7 ha), Road crossings (1.1), Rock (13.3%), Soil (4.6%), Gravel (13.2%)

0.719

2.5

Animal Biodiversity and Conservation 33.1 (2010)

81

Table 6. (Cont.)

Models (tolerance)

xR2

Ns

Crayfish Mesohabitat width (0.1 m)

0.303 14.8

Mesohabitat width (0.1 m), RCM geology (34.6%)

0.362

8.1

Mesohabitat width (0.1 m), RCM geology (27.3%), Fern (0.6%)

0.511

3.9

Mesohabitat width (0.1 m), RCM geology (34.6%), Fern (0.6%), Hardwood 15–27 cm DBH (10.2)

0.540

3.1

Mesohabitat width (0.1 m), RCM geology (42.2%), Fern (0.6%), Hardwood 15–27 cm DBH (10.2), Embeddedness (19.6 %)

The tributaries of Group 2 supported the highest numbers of foothill yellow–legged frogs (table 5), a species that was best predicted by increased soil temperatures (table 6). While showing a western distribution bias in the SFTR, they differ from the other amphibians by showing a preference for open stream reaches where they can bask (Lind, 2005).

Differences in the predictive models between this frog and amphibian richness (despite the high values may for both, in this tributary group), is best explained by the comparatively high habitat heterogeneity among these streams, along with the specific and unique behavioral adaptations of the yellow–legged frog.

Presence of the southern torrent salamander, the black salamander, the rough–skinned newt, and the Pacific chorus frog, along with the yellow–legged frog, combined to establish the highest amphib� ian richness among the tributary types in Group 2.

This high amphibian richness is likely indicative of conditions that also support higher richness of other aquatic taxa associated with the aquatic and riparian habitats. High amphibian richness can function as an easily measured bio–indicator, where greater values indicate enhanced resilience and an improved likeli� hood that reaches can provide and sustain critical ecological services (Dobson et al., 2006).

None of the fauna in tributaries of Group 3 dif� fered significantly in value from the other groups (table 5). These reaches were the most eastern, had lower winter sun exposures, lower precipitation, lower hardwoods 28–60 cm DBH, and lacked mafic volcanic rock and chert, compared to the other groups. This outcome indicates that for the fauna we assessed, the tributaries of Group 3 appear to be relatively impoverished compared to the other groups.

The tributaries of Group 4 supported more steel� head than other groups and more crayfish than Group 1. Crayfish abundance was associated with greater width and less channel embeddedness. Higher steelhead numbers were associated with greater basin area and higher temperatures (both MWMT and MWMT amplitude). The higher abundance in

0.557

2.4

streams with higher temperatures occurred despite potential bioenergetic costs. Employing a subset of streams from each of our three fish–bearing groups (three per group) sampled in 2003, McCarthy et al.

(2009) showed that individuals in higher temperature streams had lower growth efficiency, with some fish losing weight during the summer months. Bioenergetic models suggested that these fish were feeding at lower rate, 25% (or less) of the maximum consump� tion rate, and that projected future increases in stream temperatures could further exacerbate low growth rates and perhaps have population level effects. The streams of Group 4 also had more road crossings and exposed soil cover in the adjacent upland, a condition which can negatively affect salmonids (e.g., Cederholm et al., 1981).

Influences on the fluvial network are hierarchical, with regional controls such as climate, physiogra� phy, and geology shaping sub–basin conditions, and both sets of attributes acting to shape each sub–basin tributary and its within–reach conditions (Knighton, 1984; Poole, 2002). Given the overlaps in the predictive environmental attributes and the distributions of our bio–indicators, we emphasize that these fauna are not associated just with the particular tributary type where they are most com� mon. Rather the faunal elements generally have peak abundances in particular tributary types, but also occur in lower numbers in adjacent types reflecting the continuous nature of the fluvial network (fig. 4) (see Pringle, 2003). It is the collective influences on the greater sub–basin which shape available habitats within tributary types and determine where particular fauna are favored (Gomi et al., 2002; Benda et al., 2004). This conceptualization is supported by the outcome of our predictive modeling where a variety of significant models were derived for co–occurring species. We interpret this outcome as evidence that our set of independent variables represent numer� ous informative environmental gradients within this watershed. Further, because the NPMR models con� sisted of sets of variables acting at different spatial

82

scales, we consider this evidence of the influence of cross–scale interactions (Peters et al., 2007), with attributes acting in unique combinations to influence each bio–indicator depending upon its evolved niche.

The multi–scale analysis was informative because it combined variables affecting natural variability (Lan� dres et al., 1999) and land–use history (Foster et al., 2003), and substantiating their combined influence on headwaters. This analysis illuminated variables that can be managed to improved ecological conditions and enhance headwater health, and recognizing that organisms are integrators of all that happens in a watershed (Karr, 2006), the NPMR models indicated several bio–indicators that could be used to track their improving trajectories (Tabor & Aguirre, 2004; Nichols & Williams, 2006).

Future papers will address metacommunity dynam� ics (e.g., Welsh & Hodgson, 2010) and fine scale (i.e., microscale) responses of faunal assemblages, which may allow us to elucidate additional factors that affect the spatial patterns of stream–dwelling organisms in this watershed.

Acknowledgements We thank D. Ashton, J. Bettaso, C. Collins, T. Fuller, S. Green, L. Heise, A. Herman, N. Karraker, S. Mc� Carthy, B. Norman, J. Sundell, L. Ollivier, K. Schlick, and C. Wheeler for their assistance with field work.

We would also like to thank B. Howard for database management and J. Baldwin for statistical assistance.

W. Duffy, R. Hoffman, T. Krzysik and three anonymous reviewers provided valuable comments on earlier drafts. This research was partially funded by the U.S. interagency Northwest Forest Plan. The use of trade, firm, or corporation names is for the convenience of the reader and does not constitute an official endor� sement or approval by the U.S. Government of any product or service to the exclusion of others that may be suitable.

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Appendix 1. Hierarchical arrangement, by spatial scale and ecological components, of 69 independent variables used to characterize the headwater tributary reaches (300 m) in the South Fork Trinity River Watershed (fig. 1): g. GIS variable derived from ARCInfo or ARCView; p. PRISM data (Daly et al., 1994); t. Count (c) of trees: small trees = 12–60 cm diameter at breast height (DBH) were counted in a 1/10th–ha circle and large trees > 61 cm DBH were counted in a 1/5th–ha circle; u. Percent of 1/10th–ha plot; s. Collected 25 m upslope on both sides of the stream; d. From dataloggers deployed from June to October, 2002; a. Within 1 m aquatic search areas; b. Percent estimates from aquatic search areas; m. Meters; 1 Considered in amphibian richness NMPR models; 2 Considered in foothill yellow–legged frog (Rana boylii) NMPR models; 3 Considered in tailed frog (Ascaphus truei) NMPR models; 4 Considered in signal crayfish NMPR models; 5 Considered in steelhead NMPR models.

Apéndice 1. Disposición jerárquica, en cuanto a escala espacial y components ecológicos, de las 69 variables independientes utilizadas para caracterizar los tramos de las cabeceras de los afluentes (300 m), en la cuenca del río South Fork Trinity (fig. 1): g. Variable SIG derivada de ARCInfo o ARCView; p.

Datos PRISM (Daly et al., 1994); t. Recuento (c) de árboles: árboles pequeños = 12–60 cm de diámetro a la altura del pecho (DBH) que se contaron en un círculo de 1/10 de ha, y árboles pequeños > 61 cm de DBH contados en un círculo de 1/5 de ha; u. Porcentaje de registros de 1/10 de ha; s. Recogidos en los 25 m de ladera a ambos lados de la corriente; d. De dataloggers dispuestos de junio a octubre, 2002; a.

Dentro de areas de búsqueda acuática de 1 m; b. Porcentaje de estimas de las areas de investigación acuática; m. Metros; 1 Considerados en modelos NMPR de la riqueza de anfibios; 2 Consideredos en modelos NMPR de Rana boylii; 3 Consideredos en modelos NMPR de Ascaphus truei; 4 Considerados en los modelos NMPR del cangrejo señal; 5 Considerados en los modelos NMPR de la trucha arco iris.

Sub–basin attributes Geographic relations Easting1, Northing1,3, Sub–basin aspect_g3, Sub–basin area_g2,3,4,5, Reach slope3,4,5, Reach elevation1,2,5, Illumination at December 21st_g1, Day of sample1 Climate Precipitation_ p2, Mean air temperature_p1, Minimum air temperature_p Disturbance regimes Sub–basin road density_g, Sub–basin road crossings_g2,3,4,5, Sub–basin in plantation (%)_g2, Sub–basin in young conifer (%)_g, Sub–basin in young hardwood (%)_g2,3,4,5, Sub–basin in late seral trees (%)_g3,5, Sub–basin in other vegetation (%)_g1, Sub–basin with recent fire history (%)_g, Stump count1 Parent geology Sub–basin in geology types: HF (pre–Cretaceous metamorphic rocks) (%)_g3; RCM (mafic volcanic rock and chert) (%)_g1,3,4

Land surrounding the reach Trees Age of dominant cohort, Age of oldest cohort1, Conifer 15–27 cm_t2,3, Conifer 28–60 cm_t2,4, Conifer 61–120 cm_t4,5, Conifer > 120 cm _t, Hardwood 15–27 cm_t4, Hardwood 28–60 cm_t1,4, Hardwood 61–120 cm_t1, log_c5, Riparian forest width (m)

3,4,5

Shrub and understory vegetation Shrub_u1, Conifer seedling_u3, Hardwood seedling_u1,3 Ground level vegetation Fern_u3,4,5, Grass_u, Herb_u Ground cover Soil_u1,3,5, Leaf_u, Moss_u1,2, Log_u, Rock_u2,5, Debris_u3, Litter depth1,3,4 Forest climate Soil temperature_s2, 1 cm air temperature_s, Canopy_s1,5, Canopy variation_s1

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Appendix 1. (Cont.)

Within the reach Aquatic conditions Reach aspect, Canopy closure above the stream, Habitat width2,3,4,5, S* pool sediment measures1,5, Percent fines from S* pools2,3,5, Maximum depth in S* pools2,3,4,5, Mean weekly maximum water temperature (MWMT)_d2,3,4,5, Water temperature daily amplitude_d3,4,5, Stream flow_a4, Embeddedness (from slow mesohabitats)_a4 Aquatic substrates Bedrock_b, Boulder_b3,4,5, Cobble_b2,3,5, Pebble_b, Gravel_b2,3,5, Sand_b, Fines_b5, Organic fines_b2, Large woody debris_b1,2,4,5

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"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

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Citril finches during the winter: patterns of distribution, the role of pines and implications for the conservation of the species A. Borras, J. C. Senar, F. Alba–Sánchez, J. A. López–Sáez, J. Cabrera, X. Colomé & T. Cabrera Borras, A., Senar, J. C., Alba–Sánchez, F., López–Sáez, J. A., Cabrera, J., Colomé, X. & Cabrera, T., 2010.

Citril finches during the winter: patterns of distribution, the role of pines and implications for the conservation of the species. Animal Biodiversity and Conservation, 33.1: 89–115.

Abstract Citril finches during the winter: patterns of ditribution, the role of pines and implications for the conservation of the species.— The Citril finch Serinus citrinella is a Paleartic endemic species that breeds in the subalpine mountain zones of western temperate Europe. The species seems to be suffering a serious decline in its northern range, mainly in the Black Forest and the NE of the Alps. Numerous reasons have been provided for this decline, but all of them have been related to breeding habitats. Given that the species undergoes an altitudinal migration and that during winter it may use very different habitats, a sound knowledge of the distribution patterns and habitats used outside the breeding period is needed to conduct adequate conservation policies and management. This information, however, is largely lacking. The aim of this paper was to determine the current habitat used by Citril finches in north–eastern Spain during the winter, to analyse habitat suitability and to study movements, by investigating the origin of birds that overwinter in Catalonia. Citril finch distribution was modelled using both discriminant analysis and maximum entropy modelling, on the basis of species occurrences during winter in Catalonia (data from 1972–2009). Results showed that the presence of two tree species, Black pine (Pinus nigra subsp. salzmanii) and Scots pine (Pinus sylvestris), both as part of mixed open forests, and the presence of abundant farmland and arvensic plants —the two vegetation units located in a typical submediterranean context, where the warm temperatures (sunny days) in late winter permit the cones to open—, were the ecological and bioclimatic variables that explain the distribution model. All these variables in tandem seem to be the key for the current potential distribution of the Citril finch in winter (AUC scores: training data AUC = 0.955; test data AUC = 0.953). We analyzed recoveries (N = 238) of 2,368 birds ringed at wintering grounds and 12,648 birds ringed at subalpine localities in the adjacent Pyrenees from 1977–2004. We found that in the study area, we recovered ringed birds from many different locations from across the distributional range of the species, including trans–Pyrenean birds from the Alps. This stresses the high mobility of Citril finch populations to reach wintering areas. From a conservation point of view, the high importance of pines (mainly Black pine) for the wintering distribution of the species stresses that any threat on pines, especially forest fires, will have acute detrimental effects for Citril finch populations.

Key words: Citril finch, Wintering, Habitat selection, Habitat suitability, Movements, Conservation, Black pine, Scots pine.

Resumen El verderón serrano en invierno: patrones de distribución, el papel de los pinos e implicaciones para la conservación de la especie.— El verderón serrano (Serinus citrinella) es una especie paleártica endémica que cría en zonas montañosas subalpinas de la Europa occidental templada. Esta especie parece que está sufriendo un gran declive en su área de distribución septentrional, principalmente en la Selva Negra y en el NE de los Alpes. Se han propuesto muchas razones para dicha disminución, pero todas ellas estaban relacionadas con los hábitats de cría. Dado que esta especie lleva a cabo una migración altitudinal, y que durante el invierno puede utilizar habitats muy distintos, se precisaría un buen conocimiento de los patrones de distribución y de los hábitats utilizados fuera del período reproductor, para poder establecer unas directrices de conservación y gestión adecuadas. Sin embargo, esta información es muy escasa. El propósito de este estudio es determinar ISSN: 1578–665X

© 2010 Museu de Ciències Naturals

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el hábitat común utilizado por los verderones serranos en en nordeste de España durante el invierno, para analizar la idoneidad del habitat, y estudiar los movimientos, investigando el origen de la aves que invernan en Cataluña. La distribución se modelizó utilizando el análisis discriminante y la modelización de entropía máxima con los datos registrados desde 1972 al 2009 sobre la presencia de esta especie durante el invierno en Cataluña. Los resultados evidenciaron que la presencia de bosques abiertos mixtos de pino negral (Pinus nigra subsp. salzmanii) y pino silvestre o albar (Pinus sylvestris), con numerosas tierras de cultivo y plantas arvenses, en areas submediterráneas típicas en las que las temperaturas templadas de finales de invierno (días soleados) facilitan la apertura de las piñas, fueron las variables ecológicas y bioclimáticas claves responsables de la distribución del verderón serrano en invierno (valores AUC o área bajo la curva: datos de entrenamiento AUC = 0,955; datos del test AUC = 0,953). Analizamos las recuperaciones (N = 238) de 2.368 aves anilladas en las áreas de invernada y 12.648 aves anilladas en localizaciones subalpinas en los Pirineos adyacentes, desde 1977 al 2004. Los resultados de los datos de recuperación de anillas muestran que en el área de estudio se capturaron aves procedentes de muy diversas localizaciones dentro del área de distribución de la especie estudiada, incluyendo aves transpirenaicas procedentes de los Alpes. Ello enfatiza la gran movilidad de las poblaciones del verderón serrano hasta alcanzar las áreas de invernada. Desde el punto de vista de la conservación, la gran importancia de los pinos (principalmente del negral) para la distribución invernal de esta especie pone de manifiesto que cualquier amenaza para los pinos, especialmente los incendios forestales, tendrá grandes efectos adversos sobre las poblaciones del verderón serrano.

Palabras clave: Verderón serrano, Invernada, Selección del hábitat, Idoneidad del hábitat, Desplazamientos, Conservación, Pino negral, Pino silvestre, Pino albar.

(Rebut: 3 V 10; Acceptació condicional: 17 V 10; Acceptacio definitiva: 31 V 10) A. Borras, J. C. Senar, J. Cabrera, X. Colomé & T. Cabrera, Evolutionary and Behavioural Ecology Associate Research Unit, CSIC, Museu de Ciències Naturals de Barcelona, Psg. Picasso s/n., E–08003 Barcelona, Espanya (Spain).– F. Alba–Sánchez, Dpto. Botánica, Fac. de Ciencias, Univ. de Granada, E–18071 Granada, España (Spain).– J. A. López–Sáez, Grupo de Investigación "Arqueobiología", Centro de Ciencias Humanas y Sociales (CCHS), CSIC, Albasanz 26–28, E–28037 Madrid, España (Spain).

Correspondence author: J. C. Senar: jcsenar@bcn.cat

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Introduction The Citril finch Serinus citrinella is a Paleartic endemic species that breeds in the subalpine mountain zones of western temperate Europe (Cramp & Perrins, 1994). The status of the species differs considerably throughout its distributional range. While the species seems to be increasing in its southern range (NW and NE of Spain (Borras et al., 2005b; Borras & Senar, 2003), it is suffering a serious decline in the northern range, mainly in the Black Forest (Förschler, 2007) and the NE of the Alps (Bezzel & Brandl, 1988; Mattes & Maurizio, 2005), and predictive models suggest a general decline of the species in the next 100 years (Huntley et al., 2008).

The reasons for this decline are mainly related to changes in land use, basically the loss of pastures due to extensive reforestation and a reduction in cattle transhumance (Förschler, 2007). An additional factor is related to changes in the management of ski areas where typical flower–rich meadows, heavily used as a food source by the species (Borras et al., 2003b), are destroyed to allow a better retention of snow (Bezzel & Brandl, 1988; Rolando et al., 2007).

However, all these factors are related to changes in breeding habitats. It is currently widely recognised that a good understanding of the conservation priorities of a species necessarily needs a good knowledge of the habitat requirements during the winter period and the movements that the species undertakes to reach these areas (Dolman & Sutherland, 1995). This approach has recently been applied to the conservation of long–distance migrants (Martin et al., 2007; Robbins et al., 1989), but it is clear that this should be used in any species in which there is an acute change in habitat use between seasons. This is the case of the Citril finch. The species typically breeds in subalpine coniferous forests (Pinus uncinata Ramond ex DC.) from 1.500 m a.s.l. to treeline (Borras & Senar, 2003), foraging on pine and meadow seeds (Borras et al., 2003b). By autumn, snowfalls force birds to undertake a vertical migration to lowlands (300–1200 m a.s.l.).

Although the distance of the move is generally short, compared to true migrants, the shift is linked to an important change in habitat use. In autumn and winter Citril finches inhabit farmland and fragmented coniferous forests (Pinus nigra J. F. Arnold subsp. salzmanii (Dunal) Franco and Pinus sylvestris L.) (Borras & Junyent, 1993) and forage on ruderal and arvensic plants, with a shift to pine seeds by the end of winter (Borras et al., 2003b).

Nevertheless, and in spite of the general picture we have presented, the knowledge we have on the wintering habits and habitats of the Citril finch is very sparse. Some information is available on the movements of Citril finches from France, Switzerland and Germany wintering in mountainous areas of southern France (mostly to the east of Cévennes and to the south of Mont Ventoux) (Bezzel & Brandl, 1988; Cramp & Perrins, 1994; Dejonghe, 1991; Märki, 1976; Zink & Bairlein, 1995). However, information on Citril finch movements in other areas during this period is poorly known. This information is even scarcer

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for the Iberian population, where in fact the species has the highest densities (Baccetti & Märki, 1997).

Nearly 90% of the total world population breeds in Spain (Baccetti & Märki, 1997) and seven breeding nuclei can be distinguished herein (fig. 1) (Borras & Senar, 2003).

The aim of this paper was to determine the current habitat used by Citril finches to winter in north–eastern Spain, as well as their habitat suitability, and to analyse the origin of these birds on the basis of capture–recapture data. This information is used to delineate conservation practices to be undertaken to preserve wintering habitats. The Citril finch may be an ideal model species in this respect because of the interaction between annual biological cycles based on two very different habitats which are differently affected by human activity, land use practices and climatic changes.

Material and methods Study area The study was carried out in Catalonia, a region of 31,900 km2 located in the north–eastern Mediterranean coast of Spain. The relief is highly variable, from sea level to 3,143 m in the Pyrenees, and environmental conditions experiment Mediterranean, Atlantic and even Saharan climatological influences (Ferrer et al., 2006). Rainfall decreases and average temperature increases southwards. A climate gradient is present: on the eastern coast, there is a moist temperate climate, while inland there is a dry continental climate (Ferrer et al., 2006). This high environmental variability of Catalonia climate allows for a better discrimination of variables related to species distribution.

Mapping of Citril finch winter distribution The location of wintering localities was based on: (1) an exhaustive screening of local publications.

References relevant to map Citril finch distribution appear in the appendix; (2) a mailing to ornithologists in Catalonia asking them to report observations about Citril finch wintering; (3) a historical data base (1973– 1977) maintained at the Natural History Museum of Barcelona and now managed by Xavier Ferrer; (4) surveys carried out by the authors from 1972 to 2009, focused on the counties of Bages, Berguedà, Solsones, Cerdanya and Alt Urgell. All the data were mapped in standard 10 x 10 km UTM squares. We considered records obtained from October to April attained that the species typically breeds high in the mountains (> 1,800 m a.s.l.) and favorable breeding conditions there are delayed in comparison to other areas, so that the birds remain in lower localities for more extended periods. We considered records as concerning "wintering" birds only when they referred to altitudes < 1,500 m a.s.l.; hence involving only areas outside the typical subalpine breeding areas.

Subalpine areas may be occasionally used in winter, but this is highly dependent on favourable meteoro-

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logical conditions, absence of snow and presence of a good pine crop. However, given the irregularity of such presence and the low density of populations in these areas, we decided not to include these data in analyses. We determined that a square showed a consistent wintering appearance when we had more than five records per square over the whole period 1972–2009, denoting a consistent use of the area to winter.

Discriminant analysis of Citril finch environmental requirements We used discriminant analysis (Venables & Ripley, 2002) as a preliminary approach to identify main variables favouring the presence (vs. absence) of wintering Citril finches. As a dependent variable we used the presence / absence of Citril finches in the 10 x 10 km UTM grid of Catalonia, taking as "presence" only squares with more than five observations of the Citril finch over the whole study period (see above). As independent variables, we used data on the relative abundance (ha of occupation) of Pinus nigra and Pinus sylvestris, mapped in standard 10 x 10 km UTM squares. This was obtained from the cartographic databases of Catalan habitats (E 1:50,000), Department of Environmental and Housing, Catalan Government. Independent variables concerning geographical position, climate, topography, geology and land–use in Catalonia (i.e., independent variables) were obtained from Ferrer et al. (2006), mapped for the UTM 10 x 10 km grid.

Although discriminant analysis provides a first approach to key variables related to the distribution of a species, the drawback of this analysis is that it assumes a linear response function (Franklin, 2009).

Additionally, given the secretive habits of Citril finches and their difficult detection, and as one of our aims was to identify and model overall suitable areas for the wintering of the species, we additionally used the presence–only data model of maximum entropy modelling (Franklin, 2009; Phillips et al., 2006; Phillips & Dudik, 2008) (see below).

Citril finch distribution model (maximum entropy modelling) The species distribution models (SDMs) can be used to predict potential distributional patterns for a given species (Guisan & Thuiller, 2005; Franklin, 2009).

An SDM represents an approximation of a species’ ecological niche in the environmental dimension being examined, and translated into the geographic space. Based on the environmental conditions of the sites of known occurrence, these models constitute valuable tools for analytical biology (Peterson et al., 1999). Such projections assume that a species is in equilibrium with its environmental requirements —that is, its distribution is determined primarily by the environment, and not by other factors such as competition or dispersal limitation.

In the present study, Citril finch distribution was modelled, first calibrating the model for its current

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distributions in relation to presence / absence and land cover vegetation mapping (six independent variables), and then adjusting it with the above variables as well as the present topo–climatic Catalonian characteristics (sixteen independent variables).

Citril finch records The spatial resolution of available Citril finch records referred to the UTM 10 × 10 km grid. However this biological information extracted from the database was not directly used for the analyses; instead, we proceeded to perform a resample analysis (nearest neighbour method), so that the original resolution was interpolated to 1 km2. This procedure had the advantage of producing data at a resolution relevant to the spatial scale of analysis, especially for Pyrenees where the local climate/vegetation can differ sharply in the corresponding grid box of the models.

A conditional sampling was then used, under the rule of thumb of selecting the closest to the centroid of the UTM cell, in order to locate and select records of Serinus citrinella presence in all of the pixels that complied with both an altitude ranging between 500 to 1,200 m, and aspect ranging between W to E, i.e., the two main variables that determine, a priori, the winter distribution of the Citril finch. In total, 1,273 records of Serinus citrinella were randomly sampled on the raster dataset, ensuring a minimum distance of 2 km between points to avoid sample autocorrelation effects. The dataset was randomly split; 75% was used to calibrate the algorithm MaxEnt (see below), and 25% to evaluate the resulting SDMs. Environmental variables A total of sixteen variables were used as predictors to calibrate SDMs for the Citril finch, all of which had a spatial correlation degree lower than 0.75 (Pearson coefficient).

The Spanish national forest inventory (IFN2) (1:50,000) was the cartographic base used to estimate the current range of coniferous forests in Catalonia (http://www.mma.es). The strata unit was the map information shown (see fig. 1). Based on the mapping information described above, four variables (presence/ absence) were derived. The first three variables corresponded to pure forest, with one species constituting up to 70% or more of the total number of trees. These three variables were called: (i) Pnigra; (ii) Psylvestris; and (iii) Puncinata. The fourth variable represented forest that showed varying degrees of presence of trees such as Pinus nigra, P. sylvestris and even P. uncinata or deciduous trees; it was therefore named: (iv) mixed conifer forest.

The land–cover percentages used were obtained from the Moderate–resolution Imaging Spectroradiometer (MODIS) 44B Global 500 m ISIN Grid data set (http://modis.gsfc.nasa.gov/). In the present study we used the 1 km–resolution; each grid (1 × 1 km) was described as a percent mixture of several vegetation–cover categories, including woody cover percent and herbaceous cover percent. The vari-

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Cantabrian Range Basque Country

Central Range

Pyrenees

NW Iberian Range SE Iberian Range

Betic Range

Fig. 1. Distribution of the main Citril finch breeding nuclei in the Iberian peninsula. Figure based on the Spanish breeding atlas (Borras & Senar, 2003).

Fig. 1. Distribución de los núcleos principales de nidificación del verderón serrano en la península ibérica.

Figura basada en el atlas español de aves nidificantes (Borrás & Senar, 2003).

ables were called (v) MODIS tree and (vi) MODIS herb, respectively. The MODIS land cover was very successful at mapping extensive cover types (e.g. coniferous forest and grasslands) that typically occur in patches that are smaller than the MODIS pixels, but are reported to be very important to biodiversity conservation.

Apart from the variables related to vegetation, ten topo–climatic predictive variables were used. Five of them represented resource gradients (sensu (Austin et al., 1984): (vii) annual precipitation, Pann; (viii) precipitation of the driest month, Pmin; (ix) precipitation of the wettest month, Pmax; (x) maximum annual solar radiation, Rmax; and (xi) minimum annual solar radiation, Rmin. Three other variables refer to direct gradients: (xii) maximum temperature of the hottest month, Tmax; (xiii) minimum temperature of the coldest month, Tmin; and (xiv) annual temperature, Tann. The last two correspond to indirect gradients: (xv) topographic exposure; and (xvi) topographic wetness index, TWI. These latter two variables, derived from the digital elevation model (DEM), are capable of reproducing the physiological role of certain resources (Guisan & Zimmermann, 2000). Climate data (1950–1999) were drawn from the Digital Climatic Atlas of the Iberian peninsula (Ninyerola et al., 2005). The topographic data came from Shuttle Radar Topography Mission (SRTM) (http://srtm.csi.cgiar.org/) and were from 90 m to 1 km

[1,162 x 899 cells, Universal Transverse Mercator (UTM) projection, European datum 1950 (ED50)].

The GRASS–GIS software (Grass Development Team, 2008) was used to provide the geographical framework.

Modelling algorithm: MaxEnt MaxEnt (Maximum entropy) modelling of species geographic distributions; (Phillips et al., 2006; Phillips & Dudik, 2008) is an algorithm specifically designed to calculate the potential geographic distribution of a species. It combines artificial intelligence (Machine Learning) and the Principle of Maximum Entropy (Jaynes, 1957), and thus, out of the wide range of possible modelling algorithms, provides one of the most accurate predictions (Elith et al., 2006). MaxEnt estimates the probability of the presence of any species, determining the maximum entropy distribution (the closest to uniformity) from a set of records of the presence of a taxon and from digital cartography of environmental variables, which influence the species distribution (Phillips et al., 2006).

Model calibration and evaluation A cumulative output format was chosen to determine the potential Citril finch distribution. This output represents habitat suitability with continuous values [0, 100]

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Habitat–suitability maps Pyrenees C

9

Cerdanya Basin Moixeró

8

Cadí

Boumort 7

V Port del Comte B

P

Ensija

Seg

in t Bas rega

Llob

5

Capture–recapture of birds wintering in central Catalonia

Rasos

re B asin

6

Verd

es

ne

yre

rep

4 ne rde Ca in

as rB

3

2

CG 5

4

3

2

1

The MaxEnt algorithm produced maps of habitat–suitability for the Citril finch. Maps derived from MaxEnt algorithm yield values that vary from 0 (minimum habitat quality) to 100 (maximum). These scores were reclassified into four classes of suitability, based on Chefaoui et al. (2005): very low habitat suitability (0–25); low habitat suitability (26–50); high habitat suitability (51–75); very high habitat suitability (76–100).

DG 0

Fig. 2. Study area in Central Catalonia. The 10 x 10 km UTM grid is displayed. The three main rivers that conform river basins are marked. The contour lines refer to 1,500 m a.s.l. Black dots refer to the wintering localities where Citril Finches were sampled. Black dots with letters refer to the three main subalpine sampling locations: B. Bofia, V. Vansa; C. Cap del Rec. Fig. 2. Área de estudio en la Cataluña central.

Se ha incluido una cuadrícula de 10 x 10 km UTM. Se han marcado los tres ríos principales que conforman las cuencas fluviales. Las líneas de contorno representan los 1.500 m s.n.m. Los puntos negros indican las localidades de invernada en las que se capturaron los verderones serranos. Los puntos negros acompañados de letras se refieren a las tres localizaciones de muestreo subalpinas principales: B. Bofia; V. Vansa; C. Cap del Rec.

(Phillips & Dudik, 2008). The algorithm parameters fixed to calibrate the SDMs were stricter than those recommended by Phillips et al. (2006). The SDMs were evaluated by the area under the ROC curve (AUC) test provided by the MaxEnt software using a random data–splitting approach to establish an evaluation dataset (25% of the entire presence dataset) for Serinus citrinella.

Data are based on the analyses of recaptures from a total of 12,648 birds ringed at alpine localities and 2,368 birds ringed at wintering grounds from 1977–2004. However, when analysing long distance recoveries, we additionally used more recent data (up to June of 2010). Birds were trapped using mist nets associated to drinking vessels or natural food resources, and also using live decoys. We routinely trapped birds at subalpine areas in the counties of Solsones, Berguedà, Cerdanya and Alt Urgell from April to November (see (Borras et al., 1998; Borras et al., 2003a; Senar et al., 2002 for details). The main capture localities during the breeding season included Bofia, Vansa and Cap del Rec (fig. 2). Birds at wintering localities were trapped in the counties of Solsonés, Berguedà, Bages, Alt Urgell and Anoia, with a total of 49 localities (fig. 2).

Results Overall winter distribution The distribution of Citril finch records during the winter (from October to the end of April) in Catalonia spread over two main areas: a central area located in Solsonès, Alt Urgell, Bages and Berguedà regions, with many observations, and a coastal–prelitoral area, with occasional observations but a consistent pattern, most recorded in October. A few scattered observations were also recorded in western Catalonia (fig. 3).

Modelling Citril finch distribution based on discriminant analyses Taking localities with a consistent Citril finch winter presence (≥ 5 observations from 1972–2009), the presence of the species was highly related to the presence of Black pine, and to a lesser extent, of Scots pine (table 1, fig. 4). These two variables allowed a correct discrimination on the presence of the species in 93% of cases (Wilks’ Lambda: 0.68001; F2,357 = 83,995; p < 0,0001). The other variables considered (see table 1) did not add any significant information on the wintering distribution of Citril finches.

However, this analysis performed much better in discriminating where the Citril finch should not appear (96% of correct discriminations) than in identifying

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4 3 2 1 0 H 9 8 7 6 5 4 3 2 1 0 G 9 8 7 6 5 4 3 2 1 F 9 8 E 6 7 8 9

95

D

E

C

0 1 2 3 4

5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2

Fig. 3. Distribution of Citril finch wintering records in Catalonia (1972–2009): black squares, ≥ 5 records; large circles, > 2 and < 5 records; small circles, 1 record. (The 10 x 10 km UTM grid is displayed.)

Fig. 3. Distribución de los registros de invernada del verderón serrano en Cataluña (1972–2009): cuadrados negros, registros ≥ 5; círculos grandes, registros > 2 y < 5; círculos pequeños, 1 registro. (Se incluye la cuadrícula de 10 x 10 km UTM.)

where the species should be present (45% of correct discriminations).

Modelling Citril finch distribution based on MaxEnt analysis The first Citril finch distribution model (Model 1) was modelled only with the vegetation data (see fig. 5). The graphical plot of SDM sensitivity shows that AUC scores were high (Model 1: training data AUC = 0.776; test data AUC = 0.789) (fig. 6). The heuristic estimate of relative contributions of the vegetation variables to the MaxEnt model (table 2) showed that the most important variable to predict occurrence of wintering citril finches was the presence of mixed conifer forests (Pinus nigra and P. sylvestris) (fig. 7). The contribution of pure conifer forests, consisting of the species mentioned earlier, was also important for the model distribution (fig. 7).

However, analyses also stressed the importance of open habitat availability (high scores for woody and herbaceous cover percent variables), so that highly dense forest masses were avoided (table 2, fig. 7).

The habitat–suitability map based on this model (Model 1, fig. 8) displays the typical wintering area

where the species has been regularly observed, but also areas where the species only appears on a very irregular basis (compare figures 3 and 8).

The second Citril finch distribution model (Model 2) was modelled using topo–climatic variables in addition to vegetation variables. The goodness of fit for this second model was very high (Model 2: training data AUC = 0.955; test data AUC = 0.953) (fig. 9). Annual temperature (Tann) and precipitation during the driest month (Pmin) were the two main variables explaining the distribution of the Citril finch during the winter (table 2). Response curves showed that the species favours a warm temperate climate with occasional (30 mm) rain during the summer (fig. 10). Vegetation variables also had some relative contribution to the model (table 2).

The habitat–suitability map based on this model had a high overlap with the observed distribution of the species (Model 2, fig. 11). The only two 10 x 10 km squares where the species has been regularly recorded but the model does not display presence (southeast corner) correspond to areas with largely urbanized landscape or large plains with a high thermic inversion; the species appears here only on the edge of the squares.

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Table 1. Results from the discriminant analysis to identify variables that explain the distribution of the Citril finch in winter. Variables are ordered by their contribution to explain Citril finch distribution. The abundance of the different vegetation types and land uses refers to the relative extension of each vegetation and land use within each UTM square. For details on each variable see Ferrer et al. (2006).

Tabla 1. Resultados del análisis discriminativo para identificar variables que expliquen la distribución del verderón serrano en invierno. Las variables se han ordenado por su contribución a explicar la distribución del verderón serrano. La abundancia de los distintos tipos de vegetación y de los usos de la tierra se refiere a la extension relativa de cada vegetación y cada uso de la tierra en cada cuadrado UTM. Para los detalles sobre cada variable ver Ferrer et al. (2006). r

p

Black pine abundance

0.89 < 0.001

Solar radiation

Scots pine abundance

0.46 < 0.001

Scrubland presence

r

p

–0.08

ns

0.08

ns

Average temperature January –0.27

ns

Deciduous forest presence

0.07

ns

Urban area presence

–0.21

ns

Average altitude

0.04

ns

Farmland presence

–0.17

ns

Dryland farming presence

0.03

ns

Irrigated land presence

–0.15

ns

Sclerophyll forest presence

0.01

ns

Vineyard presence

–0.11

ns

Origin of birds wintering in central Catalonia Analysis of captures showed that Citril finches appeared in the wintering grounds from October to May (fig. 12).

Analysis of ring recovery data showed that birds wintering in the main wintering area in central Catalonia (Solsonès, Alt Urgell, Bages and Berguedà regions, fig. 2) proceeded mainly from adjacent Pyrenean mountain ranges (N = 238 recoveries from 2,368 birds ringed at wintering grounds and 12,648 birds ringed at alpine localities from 1977–2004). We also had some distant recoveries: three birds from the Western Pyrenees (Navarra), two from central Pyrenees (Pallars and Vall d’Aran) and two birds from the Eastern Pyrenees (Girona). We also identified three birds from trans–Pyrenean populations (from the Alps) (table 3, figs. 13, 14).

Capture / recapture efforts additionally provided information on movements of Citril finches in or away from our study area, not directly related to the wintering season (table 4). Such data interconnected our study area with far–apart populations (table 4; fig. 15). Most movements between areas referred to birds originally marked as juvenile or first–year birds (tables 3, 4) Discussion Citril finch winter distribution and the role of pines The low detectability of the Citril finch in wintering areas coupled with the low familiarity of ornithologists

with this elusive species has made it difficult to locate their wintering ranges (Benoit & Märki, 2004; Dejonghe, 1991). Extensive surveys of Citril finches carried out in northeast Spain show that the species typically winters in mountainous areas (300–1,200 m a.s.l.) at continental ranges in submediterranean and Mediterranean habitats, in clearly xerophilous environments (figs. 3, 11). The species favours sunny slopes, avoiding foggy plains with frequent thermal inversions (e.g.: Vic, Bages and Lleida plains at the Central Depression).

This preference for thermophilous areas is also typical of the French areas, where the population north of the Pyrenees winters (Crousaz & Lebreton, 1963; Dejonghe, 1991; Märki, 1976; Praz & Oggier, 1973).

The typical habitat used by the species in Catalonia includes farmland and fragmented forests of Black pine (Pinus nigra), Scots pine (Pinus sylvestris), Pubescent oak (Quercus pubescens Willd.) and Lusitanian oak (Quercus faginea Lam.), with ruderal and arvensic (nitrophilous) communities from which they feed (Borras & Junyent, 1993). Sporadically, the species may be found during autumn migration in the mountain ranges close to the coast (Serralada Litoral and Prelitoral) (fig. 3).

Although this is the general description of the winter habitat of the species, discriminant analysis showed the high importance of the presence of the Black pine, and to a lesser extent of the Scots pine, in the winter distribution of the Citril finch. The abundance of these two mountain pines allowed to predict the wintering presence of the Citril finch with an accuracy of 93%. The marked preference for the Black pine over the Scots pine may be due to the combined ef-

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D

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Pinus sylvestris 5 6 7 8 9 0 1 2 3 4 5 6 7 8 9 0 1 2

Fig. 4. Distribution and relative abundance of Black pine (A) and Scots pine (B) in Catalonia. The 10 x 10 km UTM grid is displayed: black squares, occupation by pines ≥ 25%; large circles, occupation ≥ 10 and < 25%; small open circles, occupation ≥ 5 and < 10%. Squares with a pine abundance < 5% are not displayed. As a reference, we provide a map with the distribution of each pine on the Iberian peninsula.

Fig. 4. Distribución y abundancia relativa del pino negral (A) y el pino silvestre (B) en Cataluña. Se incluye la cuadrícula de 10 x 10 km UTM: cuadrados negros: ocupación de los pinos ≥ 25%; círculos grandes, ocupación ≥ 10 y < 25%; círculos pequeños abiertos, ocupación ≥ 5 y < 10%. No se han consignado los cuadrados con una ocupación de pinos < 5%. Como referencia se incluye un mapa con la distribución de cada pino en la península ibérica.

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Presence of Citril finch UTM 10 x 10 km Pinus uncinata Mixed conifer forest Pinus nigra Pinus sylvestris

0

12.5

25

50

75

100 km

Fig. 5. Distribution of pure and mixed conifer forests of Black pine and Scots pine in Catalonia. Black–lined squares refer to UTM 10 x 10 km squares where the Citril finch was detected in winter (> 5 observational records) during the study period (1972–2009) (see fig. 3).

Fig. 5. Distribución de bosques de coníferas puros y mixtos de pino negral y pino silvestre en Cataluña.

Los cuadrados con líneas negras son los de 10 x 10 km UTM en los que se detectó la presencia del verderón serrano en invierno (observaciones > 5) durante el período de estudio (1972–2009) (ver fig. 3).

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Sensitivity (1 – Omission rate)

1.0 0.9 0.8 07 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 Specificity (fractional predicted area)

Training data (AUC = 0.776) Test data (AUC = 0.769) Random prediction (AUC = 0.5)

Fig. 6. Graphical plot of the sensitivity for a binary classifier system as its discrimination threshold for Model 1. The figure displays the Receiver Operating Characteristic (ROC) curve for both the training and the test presence records of the Citril finch.

Fig. 6. Registro gráfico de la sensibilidad para un sistema de clasificación binario como su umbral de discriminación para el Modelo 1. Esta figura muestra la curva ROC (Receiver Operating Characteristic) para los registros tanto de entrenamiento como de frecuencia para el verderón serrano.

fect of the differences between these two pines. The Black pine, for instance, produces larger and hence more energetic seeds than the Scots pine (Ceballos & Ruiz de la Torre, 1971). Competition with other pine–seed eaters can also have a role: red squirrels (Sciurus vulgaris), for instance, appear to be more abundant among Scots pine than in Black pine forests, presumably because of the higher interannual stability in crop production of the former (Ceballos & Ruiz de la Torre, 1971) (J. Pique, pers. comm.). This association of the Citril finch with the Black pine is remarkable not only in NE Spain but in the whole range of the species in Iberia, with several records in Spain of wintering birds being linked to the distributional area of this pine (e.g. Cuenca [García–Rua, 1974], Cazorla [Muñoz–Cobo, 1976], Gúdar, Javalambre and Albarracín [T. Polo, pers. comm.] [García–Páez, 1999]). The main wintering area for birds north of the Pyrenees, Cevennes and the region from the south of Vercors to the plains of Vaucluse (Crousaz & Lebreton, 1963; Märki, 1976), is interestingly also linked to the main French distribution area of the Black pine (Isajev et al., 2003). This could perhaps be related to the fact that this tree species was very abundant and widely spread in the Mediterranean after the last glaciation (Carrión, 2003; Carrión & Van Geel, 1999; Regato–Pajares & Elena–Rosselló, 1995; Soto et al., 2010), so that in addition to ecological factors, there may be some kind of atavistic preference for this coniferous species.

However, although the Citril finch showed a preference for the Black pine, MaxEnt analysis stressed

the importance of the presence of both species of pines in mixed–conifer forests (fig. 5). This is probably due to the fact that although the seeds of the Black pine may be favoured as a food source, this tree only produces a high crop every 3–5 years (Borras et al., 1996; Kerr et al., 2008). The additional presence of Scots pine, with a more regular yearly fructification (Kantorowicz, 2000), could therefore act as a buffer, ensuring food availability in other years. We should point out here that in the years in which the Black pine produces very small crops and the Scots pine has high cone availability (Borras et al., 1996), the Citril finch can be found to exploit Scots pine in more hygrophilous areas. This would explain the observation by Benoit & Märki (2004) of birds wintering in Scots pine in the south–east of Spain during late January 2001, interestingly, a year when the Black pine had a low fructification. It is of interest to stress that in other areas of Spain (e.g. Alto Tajo and Central Range), the Citril finch may winter in forests of Scots pine (L. M. Carrascal, pers. comm.), indicating that the presence of the Black pine is not indispensable.

MaxEnt analysis also stressed the need for open forests and the presence of grasses. This can be linked to the fact that the Citril finch needs both seed plants and conifer seeds to survive the winter.

Ruderal and arvensic plants are heavily used during autumn (Borras & Senar, 1991). However, at the start of the wintering period (January), ruderal and arvensic plants reduce their seed offer just when pines start opening their cones. It is by then when

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Table 2. Heuristic estimates of relative contributions of the environmental variables to the MaxEnt models 1 and 2. Variables used in the models include presence/absence of pure forests (when a given species makes > 70% of the total number of trees) of: (i) Pinus nigra; (ii) P. sylvestris; (iii) P. uncinata; and (iv) presence / absence of mixed conifer forest (including these three pines and deciduous trees).

Land–cover percentages by: (v) woody cover and (vi) herbaceous cover. Topo–climatic predictive variables including: (vii) annual precipitation, Pann; (viii) precipitation of the driest month, Pmin; (ix) precipitation of the wettest month, Pmax; (x) maximum annual solar radiation, Rmax; (xi) minimum annual solar radiation, Rmin; (xii) maximum temperature of the hottest month, Tmax; (xiii) minimum temperature of the coldest month, Tmin; (xiv) annual temperature, Tann; (xv) topographic exposure; and (xvi) topographic wetness index, TWI. Tabla 2. Estimación heurística de la contribución relativa de las variables ambientales para los modelos 1 y 2 de MaxEnt. Las variables utilizadas en los modelos incluyen la presencia/ausencia de bosques puros (cuando una especie dada constituye > 70% del número total de árboles) de: (i) Pinus nigra; (ii) P. sylvestris; (iii) P. uncinata; (iv) presencia / ausencia de bosques de coníferas mixtos (incluyendo estos tres pinos y árboles caducifolios). Porcentajes de cubierta del suelo por (v) cubierta leñosa y (vi) cubierta herbácea. Variables topoclimáticas predictivas incluyendo: (vii) precipitación anual, Pann; (viii) precipitación del mes más seco, Pmin; (ix) precipitación del mes más húmedo, Pmax; (x) radiación solar anual máxima, Rmax; (xi) radiación solar mínima, Rmin; (xii) temperatura máxima del mes más cálido, Tmax; (xiii) temperatura mínima del mes más frío, Tmin; (xiv) temperatura anual, Tann; (xv) exposición topográfica; y (xvi) índice topográfico de humedad, TWI).

Model 1

Model 2

Variable

Variable

Percent contribution

Percent contribution

Mixed conifer forest

50.6

Tann

45.7

MODIS tree

18.9

Pmin

29.8

Pnigra

14.9

Tmin

8.0

Psylvestris

14.0

Rmin

4.4

Puncinata

1.2

Tmax

4.3

MODIS herb

0.3

Pmax

2.1

Rmax

1.7

Mixed conifer forest

1.6

Psylvestris

0.8

Pnigra

0.6

Pann

0.4

MODIS herb

0.3

MODIS tree

0.1

TWI

0

Topographic exposure

0

Puncinata

0

the species shifts its diet to pine seeds (Borras et al., 2003b; Borras & Senar, 1991).

The presence of pines seems to be neccesary for the presence of wintering Citril finches. Discriminant analysis showed that the probability for Citril finch wintering appearence is very low when Black and Scots pines are not present. However, it is not sufficient; the inclusion of topo–climatic variables in MaxEnt approach stressed that in addition to these

pines, a warm general temperature and some summer rain is basic to model the presence of wintering Citril finches. This is partly because these climatic variables are largely responsible for submediterranean climate and hence for the occurrence of these two species of pines in these areas (García López & Allué Camacho, 2008; Grau et al., 1999; Regato et al., 1995; Rouget et al., 2001; Thuiller et al., 2003).

The warm temperature, specially at the end of win-

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x 10–4

1.8

3.6 3.4 3.2 3.0 2.8 2.6 2.4 2.2 2.0 1.8 1.6 1.4 1.2 1.0

1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0

Logistic output (probability of presence)

–0.1 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1.1 Mixed conifer forest

20 40 60 80 Presence of woody cover

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4.5

6.5 6.0

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x 10–4

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1.8

1.2

1.6 1.4

1.1

1.2

1.0

1.0

0.9

0.8

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0.5

0

20 40 60 80 100 Presence of herbaceous cover

Fig. 7. Response curves displaying the probability of Citril finch occurrence (under Model 1) in relation to the main variables explaining its current distribution (table 2). The variables included presence/absence of pure forests (when a given species makes > 70% of the total number of trees) of: (i) Pinus nigra; (ii) Pinus sylvestris; and (iii) Pinus uncinata; (iv) presence / absence of mixed conifer forest (including these three pines and deciduous trees). Land–cover percentages by (v) woody cover and by (vi) herbaceous cover.

Fig. 7. Curvas de respuesta que muestran la probabilidad de presencia del verderón serrano (con el Modelo 1) en relación con las variables principales que explican su distribución actual (tabla 2). Las variables incluían presencia / ausencia de bosques puros (cuando una especie dada constituye > 70% del número total de árboles) de (i) Pinus nigra; (ii) Pinus sylvestris y (iii) Pinus uncinata; (iv) presencia / ausencia de bosque mixto de coníferas (incluyendo estos tres pinos y árboles caducifolios). Porcentajes de cubierta vegetal (v) cubierta leñosa y (vi) cubierta herbácea.

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0–25 Very low habitat suitability 26–50 Low habitat suitability 51–75 High habitat suitability 76–100 Very high habitat suitability

0

12.5

25

50

75

100 km

Fig. 8. Habitat suitability map for the Citril finch according to Model 1 (see table 2 and figs. 6 and 7).

The scale on the right shows values that vary from 0 (minimum habitat quality) to 100 (maximum habitat quality). The scores were reclassified into four classes of suitability, so the map shows areas that are of: very low habitat suitability (0–25); low habitat suitability (26–50); high habitat suitability (51–75); very high habitat suitability (76–100).

Fig. 8. Mapa de idoneidad del hábitat para el verderón serrano según el Modelo 1 (ver tabla 2 y figs.

6 y 7). La escala de la derecha muestra valores que varían de 0 (calidad mínima del hábitat) a 100 (calidad máxima del hábitat). Los registros se reclasificaron en cuatro clases de idoneidad, de manera que el mapa muestra áreas que son de: idoneidad del hábitat muy baja (0–25); idoneidad del hábitat baja (26–50); idoneidad del hábitat alta (51–75); idoneidad del hábitat muy alta (76–100).

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Sensitivity (1 – Omission rate)

1.0 0.9 0.8 0.7 0.6 0.5 0.4 0.3 0.2 0.1 0.0 0.0 0.1 0.2 0.3 0.4 0.5 0.6 0.7 0.8 0.9 1.0 1 – Specificity (fractional predicted area)

Training data (AUC = 0.955 Test data (AUC = 0.953) Random prediction (AUC = 0.5)

Fig. 9. Graphical plot of the sensitivity for a binary classifier system as its discrimination threshold for Model 2. The figure displays the Receiver Operating Characteristic (ROC) curve for both the training and the test presence records of the Citril finch.

Fig. 9. Registro gráfico de la sensibilidad para un sistema de clasificación binario como su umbral de discriminación para el Modelo 2. Esta figura muestra la curva ROC (Receiver Operating Characteristic) para los registros tanto de entrenamiento como de frecuencia para el verderón serrano.

ter, is basic for the Citril finch, because the typical anticyclonic stability (in positive NAO years) in this period reduces precipitation and increases insulation and hence temperature (Folch, 1981), thereby favouring the spontaneous opening of cones and making pine seeds easily available to the species (Kerr et al., 2008).

Summarising, the presence of mixed open forests of Black and Scots pines in typical submediterranean areas, where the warm temperatures at the end of the winter open the cones, are the key ecological and bioclimatic variables responsible for the distribution of the Citril finch in winter.

What is the origin of central Catalonia wintering birds?

Birds wintering in our area mainly came from the nearby Pyrenean Mountains, located just a few kilometers away. This seems to suggest that the species carries out simple altitudinal or transhumance movements.

This is in accordance with the view of the species in some earlier publications (Bernis, 1972; Tellería et al., 1999). However, reports on recoveries of ringed birds and on visible directional movements in the north of the Pyrenees led several authors to suggest that the species could also entail a true (short) migration from breeding to wintering areas (Baccetti & Märki, 1997; Bourrillon, 1961; Crousaz & Lebreton, 1963; Fornasari et al., 1998; Praz & Oggier, 1973; Schifferli, 1961; Spina & Volponi, 2008). This "migration hypothesis" (Fornasari et al., 1998) would explain the recovery in our area of ringed birds from many different locations across the distributional range of the species (table 3,

figs. 13, 14), including even birds coming from the Alps and crossing the Pyrenees (Borras et al., 2005a).

Citril finch movements in or away from our study area, not directly related to the wintering season, stress even more that the species may be highly mobile within Iberia (table 4, fig. 15). Our E–Pyrenees mountain ranges have exchanged birds with Central Range (Guadarrama), NW Iberian Range (Urbión) and central (Vall d’Aran) and W–Pyrenees (Navarra) (table 4, fig. 15). Additionally, there are records between SE Iberian Range (Cuenca) and W–Pyrenees (Navarra) (Alonso & Arizaga, 2004) and between the SE Iberian Range (Teruel) and E–Pyrenees (Andorra) (Toni Polo & Roger Sanmartí, pers. comm.), and an additional record of a bird ringed in coast of Liguria (Italy) and recovered during winter in Valencia (E Spain) (Spina & Volponi, 2008). All these ring–recovery data stress the apparent exchange of individuals between the different Iberian populations.

This could be caused by the movement of juvenile birds in post–natal dispersal (table 4), as in other more widespread species (Newton, 2008). Indeed, analysis of movements of the Citril finch at more local scales stresses that while adult birds are very site–faithful, a high proportion (30%) of juveniles may disperse to adjacent areas (Senar et al., 2002).

Future studies will test to what point this exchange of individuals can revert in gene flow.

Citril finch conservation biology and management The presence and abundance of the Citril finch, as with other Cardueline finches (Newton, 1972), has

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x 10–4

Logistic output (probability of presence)

8 7 6 5 4 3 2 1 0 –2

0

2

x 10–4

4

6 8 10 12 Annual temperature

14

16

18

Logistic output (probability of presence)

1.6 1.4 1.2 1.0 0.8 0.6 0.4 0.2 0.0 –10

0

10

20 30 40 50 60 70 Precipitation of the driest month

80

90

Fig. 10. Response curves displaying the probability of Citril finch occurrence (under Model 2) in relation to the two main variables explaining its current distribution (table 2): annual mean temperature (Tann) and precipitation of the driest month (Pmin).

Fig. 10. Curvas de respuesta que muestran la probabilidad de presencia del verderón serrano (con el Modelo 2) en relación con las variables principales que explican su distribución actual (tabla 2): temperatura media anual (Tann) y precipitación durante el mes más seco (Pmin).

been historically linked to man–induced environmental changes. The species suffered a drastic bottleneck during the Middle Holocene (Förschler et al., 2010), when human–induced fires and climatic changes devastated great extensions of pine forests (mainly Black pines) (Carcaillet et al., 2002; Carrion et al., 2001a; Carrion et al., 2001b; Carrión, 2003; Carrión & Van Geel, 1999).

Conversely, the desertion of large extensions of vineyards in the Mediterranean area at the end of 19th c. and early 20th c. because of the damage caused by the grape phylloxera (Dactylosphaera vitifoliae) favoured the resurgence of many secondary woods of Black pine which then favoured the spread of the Citril finch (Borras et al., 2005b; Borras & Junyent, 1993). Economic development in Spain during the 1950s brought about changes that again favoured Citril finches; extensive pine reforestation was undertaken

in the Iberian Peninsula (Tapias et al., 2001) and subalpine skiing stations were built, creating openings in available pine forests.

Currently, human activities and climatic changes again seem to be acting detrimentally on the species.

Since any conservation strategy concerning wildlife should be based on a dynamic view of the biological cycle of the species, both from a spatial and a temporal perspective, we should look into the current conservation needs of Citril finch on the basis of its biological cycle.

According to previously published information on the species (Borras et al., 2003a, 2003b, 2005b; Borras & Junyent, 1993; Borras & Senar, 1991, 2003; Förschler et al., 2005) the annual biological cycle of the Citril finch in Iberia comprises four phases (or quadrants) (fig. 16):

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0–25 Very low habitat suitability 26–50 Low habitat suitability 51–75 High habitat suitability 76–100 Very high habitat suitability

0

12.5

25

50

75

100 km

Fig. 11. Model 2. Habitat suitability map for the Citril finch according to Model 2 (see table 2 and figs. 9, 10). The scale on the right shows values that vary from 0 (minimum habitat quality) to 100 (maximum habitat quality). The scores were reclassified into four classes of suitability, so the map shows areas that are of: very low habitat suitability (0–25); low habitat suitability (26–50); high habitat suitability (51–75); very high habitat suitability (76–100).

Fig. 11. Modelo 2. Mapa de idoneidad del hábitat para el verderón serrano según el Modelo 2 (ver tabla 2 y figs. 9, 10). La escala de la derecha muestra valores que varían de 0 (calidad mínima del hábitat) a 100 (calidad máxima del hábitat). Los registros se reclasificaron en cuatro clases de idoneidad, de manera que el mapa muestra áreas que son de: idoneidad del hábitat muy baja (0–25); idoneidad del hábitat baja (26–50); idoneidad del hábitat alta (51–75); idoneidad del hábitat muy alta (76–100).

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Percentage of occurrence

25 20 15 10 5 0

O

N

D

J

F

M

A

M

Fig. 12. Frequency distribution of Citril finch captures in different months in typical wintering areas (< 1,500 m a.s.l.). Data based on 2,368 captures from 1977 to 2004: O. October; N. November; D. December; J. January; F. February; M. March; A. April; M. May. Fig. 12. Distribución de frecuencias de las capturas de verderón serrano en distintos meses en las áreas de invernada típicas (< 1.500 m s.n.m.). Basado en 2.368 capturas de 1977 al 2004. (Para las abreviaturas de los meses, ver arriba.)

Table 3. Movements of Citril finches between wintering and breeding areas. We provide the ring number of the bird, the date and locality where the bird was captured during winter, and the date, locality and location where the bird was captured away from the wintering study area. The distance and direction of the movement are also given: Rf. Labels in figures 7 and 8 mapping the location of each ringing and recovery. Localities: B. Barcelona; Gi. Girona; F. France; N. Navarra; S. Switzerland; Ll. Lleida.

Tabla 3. Desplazamientos de los verderones serranos entre sus áreas de invernada y de cría.

Proporcionamos el número de la anilla del ave, la fecha y localidad en las que se capturó el ave durante el invierno, y la fecha, la localidad y la localización donde el ave fue capturada lejos del área de invernada de este estudio. También se proporcionan la distancia y la dirección de los desplazamientos: Rf. Indica las aves anilladas y recuperadas marcadas en las figuras 7 y 8. Localidades: B. Barcelona; Gi. Girona; F. Francia; N. Navarra; S. Suiza; Ll. Lleida.

Locality within study area Ring Date 0558135 24 XII 93 0391081 26 XII 95 0506825 29 II 92 0641964 13 XI 93 4429564 14 XII 03 913199 26 II 00 980773 07 XII 99 444781 25 X 59 559154 16 V 93 P38188 14 III 81 Colour ring 01 I 85 N309684 28 X 06 DN3175 31 I 09 FN4363 25 X 08 Z24710 06 III 10

Locality out of study area

Locality Date Castellar R. 07 X 93 Montmajor 23 IX 95 Lladurs 11 VII 93 Solsona 20 V 95 Solsona 29 III 03 Olius 11 IV 99 Lladurs 25 VII 99 Sallent 25 VI 59 Lladurs 25 VI 93 Berga 20 VI 78 Navès 00 VII 84 Lladurs 29 VII 06 Lladurs 08 VII 07 Lladurs 09 VIII 08 Lladurs 14 IV 07

Locality Coll de Pal (B) Coll de Pal (B) Setcases (Gi) Chamaloc, Sarthe (F) Vallon de Combeau (F) Bigüezal (N) Isaba (N) Coll Bretolet (S) La Molina (Gi) La Creu Cerdana (Ll) Rasos Peguera (B) Queralbs (Gi) Beret, Val d’Aran (Ll) Rialp (Ll) Bigüezal (N)

Localization Km/dir. Rf. 42.15 N 01.52 E 45 WSW 1 42.15 N 01.52 E 29 SSW 2 42.23 N 02.18 E 78 ENE 3 44.48 N 05.23 E 440 NNE 4 44.44 N 05.33 E 445 WSW 5 42.40 N 01.08 W 234 WNW 6 45.58 N 00.48 W 212 WNW 7 46.09 N 06.47 E 625 SW 8 42.10 N 01.57 E 190 NE 9 42.17 N 01.40 E 27 NW 10 42.11 N 01.80 E 23 NE 11 42.22 N 02.09 E 65 ENE 12 42.45 N 00.58 E 91 NNE 13 42.25 N 01.12 E 53 NNE 14 42.40 N 01.08 W 228 WNW 15

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Bohemian Forest

s

ge

s Vo

ps

Al

8

D a in

ps

ric

4 5

Al

A

A

s lp

if ss l Ma ntra e C

ps

Al

ra

Ju

pe nn

3 12

e in s

7 13 15 6 14 Pyrenees

Fig. 13. Citril finch movements in winter, showing the original location (marked as a number) of the different birds either captured or recaptured at our wintering study area (marked as a rectangle). Numbers correspond to that in table 3 and in fig. 14. The contour lines refer to 1,500 m a.s.l.

Fig. 13. Desplazamientos del verderón serrano en invierno, mostrando la localización original (indicada con un número) de las distintas aves capturadas o recapturadas en nuestra área de estudio de invernada (marcada como un rectángulo). Los números corresponden a los de la tabla 3 y la fig. 14. Las líneas de contorno indican la altitud de 1.500 m s.n.m.

R

9

8

Fig. 14. Map of the wintering study area (as in fig. 2), showing the exact location of capture (marked as numbers) of birds originally captured or later recaptured during the breeding season away from our study area. Numbers correspond to those in table 3 and fig. 13. The contour lines refer to 1,500 m a.s.l.

Fig. 14. Mapa del area de studio de invernada (como en la fig. 2), mostrando las localizaciones exactas de captura (marcadas en forma de números) de las aves originalmente capturadas o recapturadas más tarde durante la estación de cría lejos de nuestra area de estudio. Los números corresponden a los de la tabla 3 y la fig. 13. Las líneas de contorno indican la altitud de 1.500 m s.n.m.

Segre

7

V B

6

15 13

9

5

10 712 14 3 4 5

1

Llobregat 6

2

11

4

3

Cardener

2 CG DG 5

6

7

8

9

0

8

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Table 4. Movements of Citril finches between our study area and distant localities, exemplifying the potential for dispersal of the species. We provide the ring number of the bird, the date and locality where the bird was captured within our study area, and the date, locality and location where the bird was captured away from our study area. We additionally provide the distance and direction of the movement: Ar. Age at ringing; Rf. Labels in figures 8 and 9 mapping the location of each ringing and recovery. Localities: S. Soria; N. Navarra; M. Madrid; Gi. Girona; Ll. Lleida.

Tabla 4. Desplazamientos de los verderones serranos entre nuestra área de estudio y localidades lejanas, ejemplificando el potencial de dispersión de esta especie. Proporcionamos el número de la anilla del ave, la fecha y localidad en que el ave fue capturada dentro de nuestra área de estudio, y la fecha, la localidad y la localización en que se capturó el ave lejos de nuestra área de estudio. Además proporcionamos la distancia y la dirección del desplazamiento: Rf. Indica las aves anilladas y recuperadas marcadas en las figuras 8 y 9. Localidades: S. Soria; N. Navarra; M. Madrid; Gi. Girona; Ll. Lleida.

Locality within study area

Locality out of study area

Ring

Date

Locality

Date

Locality Ar

Localization

Km/dir

Rf.

L038356 31 VIII 96 Vansa

3

07 IV 97

Sierra Urbión (S)

L137009 23 VI 97 Vansa

3J

14 VI 98

Sierra Uztarrotz (N) 42.54 N 00.56 W 228 WNW 17

AT2344

3J

18 IV 03

Sierra Uztarrotz (N) 42.54 N 00.56 W 224 WNW 18

Vansa

5

02 V 99

Bigüezal (N)

42.40 N 01.08 W 231 WNW 19

L153412 13 IV 00 Vansa

5

17 III 02

Bigüezal (N)

42.40 N 01.08 W 231 WNW 20

24 VIII 02 Vansa

L070480 22 V 97 AP8819

Cap Rec 6

24 III 02

Bigüezal (N)

42.40 N 01.08 W 236 WNW 21

L498597 07 VI 03 Cap Rec 6

20 III 04

Bigüezal (N)

42.40 N 01.08 W 236 WNW 22

N165870 11 VI 05 Vansa

21 I 06

Navacerrada (M)

40.45 N 04.03 W

523 SW

23

25 VI 93

La Molina (Gi)

42.10 N 01.57 E

40 SW

24

562894

11 X 03

41.55 N 02.46 W 359 WSW 16

28 VII 93 Bofia

L842392 29 V 04 ER3560

5 3J

Cap Rec 5

28 III 09 Navés

N558807 23 VI 10 Bofia

04 VII 08 Rialp (Ll)

42.25 N 01.12 E

39 W

25

6

03 VII 09 Rialp (Ll)

42.25 N 01.12 E

52 NNW

26

3J

03 VII 09 Rialp (Ll)

42.25 N 01.12 E

45 NW

27

Quadrant 1 In spring (vernal period), the species breeds in subalpine open coniferous forests with abundant meadows. The species relies then on Pinus uncinata seeds complemented by herbaceous seeds from meadow grasses (e.g. Taraxacum officinale Weber ex F. H. Wigg.) (Borras et al., 2003b).

Quadrant 2 In late summer (serotinal period), Citril finches disperse over the tree line, on alpine meadows and heaths, feeding on a great variety of grassland plants, including nitrophilous plants linked to cattle (e.g.

Chenopodium bonus–henricus L.); some individuals, mainly juvenile birds, may move to feed on ruderal communities of Compositae plants (e.g. Cirsium sp., Carduus sp.). During this period the birds moult.

Quadrant 3 By autumn, the birds move to lower altitudes (300– 1.200 m a.s.l.) to winter. In this period they feed on ruderal and arvensic communities on fallow fields (e.g.

Inula viscosa L., Chenopodium sp. and Amaranthus sp.) (Borras et al., 2003b).

Quadrant 4 Well into the winter, when herbaceous resources become exhausted, Citril finches shift diet to pine seeds (Pinus nigra and Pinus sylvestris) as cones start to open during this period (Borras et al., 2003b). Then, in the prevernal period, provided that pine fructification is abundant and meteorological conditions are adequate, the species may undergo opportunistic breeding in those montaneous areas (Borras & Senar, 1991). In Central Europe, the fourth quadrant in figure 10 has not been described. At the end of the winter, Citril finches move again to subalpine areas (Quadrant 1).

This cycle has two main components: an altitudinal component, with birds moving from subalpine/alpine areas( highland) to mountainous areas (lowland), and a trophic component, with birds shifting from pine to herbaceous resources (fig. 16).

We stressed earlier (see introduction) that most discussion on the conservation of the species has focused on the highland component. However, as in many other species, a good knowledge of the habitat requirements during the winter period may be equally important (Dolman & Sutherland, 1995), especially so in species like the Citril finch, which like other

Animal Biodiversity and Conservation 33.1 (2010)

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17, 18 19, 20, 22

s

21

E Pyren ee

s

24

Prepyrenees

e Ib n ria M

ou

nt ai ns

ns ai nt

and ins nta tains u Mo oun 16 M an bri est a t s n th W n a i C or ta N un Mo m ste 23 Sy Guadarrama l ra nt e C Gredos

25, 26, 27

W Pyren ee

B

et ic

M

ou

Cazorla and Segura

Sierra Nevada

Fig. 15. Citril finch movements showing the location (marked as a number) of the different birds either captured or recaptured in our study area (marked as a rectangle) during the breeding season and recaptured or originally captured away from our study area during another breeding season. Numbers correspond to those in table 4. The contour lines refer to 1,500 m a.s.l.

Fig. 15. Desplazamientos del verderón serrano mostrando la localización (marcada como un número) de las distintas aves capturadas o recapturadas en nuestra area de estudio (señalada como un rectángulo) durante la estación de cría, y recapturadas u originalmente capturadas lejos de nuestra área de estudio durante otra estación de cría. Los números corresponden a los de la tabla 4. Las líneas de contorno indican la altitud de 1.500 m s.n.m.

Cardueline finches, mate during the winter (Senar & Borras, 2004).

The present study has shown that the distributional range of the Citril finch in winter is closely related to montane pines, mainly Pinus nigra. This link is largely trophic, occuring mainly during the second half of winter (Borras et al., 2003b). These forests are therefore critical to conservation of the species, and any threat to them, specially forest fires, will have acute detrimental effects on Citril finch populations. The devastating forest fires in Catalonia in the 1980s and 1990s, within our study area, greatly reduced availability of Black pine forest (Borras et al., 2005b). The non–serotinous cones of this pine, which open in absence of fire, increases the effect of forest fires in these trees even more (Tapias et al., 2001. Traditional Spanish forest management practices increase canopy density, thereby also favouring the frequency and intensity of these fires (Tapias et al., 2001, 2004). The slow growth of this pine and its difficulties for reforestation (Ceballos & Ruiz de la Torre, 1971) lead us to predict a marked decline in the availability of suitable habitat for the Citril finch in coming years. This will affect not only Citril finch survival over winter, but also opportunistic breeding activities (Quadrant 4).

During autumn, the main threats to the species come from the recently introduced agricultural practices of plowing fields and using herbicides, which reduce the availability of arvensic grassland communities on fallow fields. Given the importance of these dietary resources for the species at this time of year (Quadrant 3) (Borras et al., 2003b), we should advise a return to traditional agricultural practices (Borras et al., 2003b, 2005b).

During the vernal and estival seasons (Quadrant 1), the threats to the species are mainly related to a loss of pastures due to extensive reforestations and a reduction in cattle and sheep transhumance (Förschler, 2007), and to the destruction of the typical flower–rich meadows brought about by changes in ski–station management aiming to improve the retention of snow (Bezzel & Brandl, 1988; Rolando et al., 2007).

The framework we have presented for the conservation of the Citril finch stresses the need to match conservation activities with the dynamic nature of the annual cycle of the species. A conservation policy can only succeed, therefore, if actions are integrated within the different seasonal, habitat and trophic levels.

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I

Serotinal Period

Alpine Meadows Heaths

Estival Period

Ruderal Communities

Vernal Period

Subalpine Meadows and Grassland

Pinus uncinata

Subalpine Breeding

Moulting

Q2

Q1 Subalpine Stage

MIGRATION AND TRANSHUMANCE

Montaneous Stage Q3

Arvensic Communities

Q4

Ruderal Communities Pinus sylvestris

Autumnal Period

Hivernal Period

Opportunistic Breeding

Mating

Herbaceous Stage

Pinus nigra

Prevernal Period

Forestal Stage

Fig. 16. Schematic diagram of the annual biological cycle of the Citril finch. The diagram shows the different periods of the year, along with the trophic sources and habitats used within each period, and the biological events that characterize that period. The diagram is divided in four quadrants which represent four main periods within the biological cycle of the species. The cycle is based on previously published information on the species (Borras et al., 2003a, 2003b, 2005b; Borras & Junyent, 1993; Borras & Senar, 1991, 2003; Förschler et al., 2005).

Fig. 16. Diagrama del ciclo biológico anual del verderón serrano. El diagrama muestra los distintos períodos a lo largo del año, junto con los recursos tróficos y los habitats utilizados en cada período, y los sucesos biológicos que caracterizan el período. El diagrama está dividido en cuatro cuadrantes, que representan los cuatro períodos principales del ciclo biológico de esta especie. El ciclo se ha basado en información sobre la especie previamente publicada (Borras et al., 2003a, 2003b, 2005b; Borras & Junyent, 1993; Borras & Senar, 1991, 2003; Förschler et al., 2005).

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Acknowledgements We wish to thank Jose Molina, Jordi Calaf, Miquel Cabrera, Carles Serrasolsas, Dolors Camps, Montse Mateu, Alex Borràs and Eduard Borràs for assistance ringing the birds and Anna Moreso, Albert Solé, Alex Mazcuñan, Toni Beltran, Mar Masanés, Jordi Garcia, Iolanda Garcia, Albert Garcia, Jordi Cerdeira, Mariona Monròs and Olga Nicolas for field assistance; Hans Märki, Luis María Carrascal and Lluís Brotons for comments on the paper; Ramón Monell, Josep Codina, Florenci Codina, Schmith de Solanes, Isidre de Serinyana and Joan Perramón for allowing us to work in their properties; Toni Polo, Roger Sanmartí, Lluís Gustamante, Ponç Feliu, Victor Sanz, Jaume Soler, Josep Bosch and Joan Parramón for providing data on the observations of wintering birds and Raül Aymi (ICO) and Xavier Ferrer (Vertebracat, UB) for providing information from their data–bases; Toni Polo (Grupo de Anillamiento Llebeig), Roger Sanmartí, Juanjo Calleja (Grupo Ornitológico Monticola), Juli Merino (Societat "El Passerell" de Solsona), Daniel Alonso and Juan Arizaga (Sociedad de Ciencias Aranzadi) for providing data on Citril finch ring recoveries; Oscar Gordo and Jordi Calaf for providing UTM databases on the distribution of land use, meteorological data and abundance of pines; the Cos d’Agents Forestals, Generalitat de Catalunya, especially Daniel Mañas, Josep Gilibets and Lluís Novellas, for facilities during field work. Birds were handled with the permission of the Catalan Ringing Office (ICO) and the Departament of Medi Ambient, Generalitat de Catalunya. This work was supported by grants from the Ministerio de Ciencia e Innovación (CGL 2009–10652).

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"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

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Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

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Imaginary populations A. Martínez–Abraín

Martínez–Abraín, A., 2010. Imaginary populations. Animal Biodiversity and Conservation, 33.1: 117.

A few years ago, Camus & Lima (2002) wrote an essay to stimulate ecologists to think about how we define and use a fundamental concept in ecology: the population. They concluded, concurring with Berryman (2002), that a population is "a group of individuals of the same species that live together in an area of sufficient size to permit normal dispersal and/or migration behaviour and in which population changes are largely the results of birth and death processes". They pointed out that ecologists often forget "to acknowledge that many study units are neither natural nor even units in terms of constituting a population system", and hence claimed that we "require much more accuracy than in past decades in order to be more effective to characterize populations and predict their behaviour". They stated that this is especially necessary "in disciplines such as conservation biology or resource pest management, to avoid reaching wrong conclusions or making inappropriate decisions".

As a population ecologist and conservation biologist I totally agree with these authors and, like them, I believe that greater precision and care is needed in the use and definition of ecological terms. The point I wish to stress here is that we ecologists tend to forget that when we use statistical tools to infer results from our sample to a population we work with what statisticians term "imaginary", "hypothetical" or "potential" populations. As Zar (1999) states, if our sample data consist of 40 measurements of growth rate in guinea pigs "the population about which conclusions might be drawn is the growth rates of all the guinea pigs that conceivably might have been administered the same food supplement under identical conditions". Such a population does not really exist, and hence it is considered a hypothetical or imaginary population. Compare that definition with the population concept that would be in our minds when performing such measurements. We would probably assume that our study population consisted of pigs (not the growth rates of pigs!) and probably all the pigs at the farm we were sampling, rather than the all the growth rates of the pigs that might conceivably have been administered the same food.

We overlook the fact that we are using the statistical tools to try to estimate ecological population parameters (and test specific hypotheses on the values of these population parameters) but that the ecological population which is in our minds and the statistical (imaginary) population of our tests need not necessarily be the same (and most often are not). So, to avoid wrong inferences (with wide–ranging consequences if we are dealing with decision–making processes) we should do all we possibly can to ensure that our natural populations are as similar as possible to the imaginary populations of statisticians, or at least we should discuss our results within the framework in which our inference was developed. Statistics is not an ad hoc tool invented for us, but rather a tool that we have borrowed from statisticians for our purposes. We should always keep this in mind.

References Berryman, A. A., 2002. Population: a central concept for ecology? Oikos, 97: 439–442.

Camus, P. A. & Lima, M., 2002. Populations, metapopulations, and the open-closed dilemma: the conflict between operational and natural population concepts. Oikos 97: 433–438.

Zar, J. H., 1999. Biostatistical analysis. Prentice hall, New Jersey.

(Received: 1 X 09; Conditional acceptance: 13 XI 09; Final acceptance: 24 XI 09) Alejandro Martínez–Abraín, IMEDEA (CSIC–UIB), c/ Miquel Marquès 21, 07190 Esporles, Mallorca, Espanya (Spain). E–mail: a.abrain@uib.es ISSN: 1578–665X

© 2010 Museu de Ciències Naturals

"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

Animal Biodiversity and Conservation 33.1 (2010)

Animal Biodiversity and Conservation Animal Biodiversity and Conservation (abans Miscel·lània Zoològica) és una revista inter­ disciplinària 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, fisiologia i genètica) procedents de totes les regions del món amb especial énfasis als estudis que d'una manera o altre tinguin relevància en la biología de la conservació. La revista no publica compilacions bibliogràfiques, catàlegs, llistes d'espècies o cites puntuals. Els estudis realit­ zats 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 http://www.bcn.cat/ABC, 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.

Normes de publicació Els treballs s'enviaran preferentment de forma electrònica (abc@bcn.cat). El format preferit és un document Rich Text Format (RTF) o DOC que inclogui les figures i les taules. Les figures s'hauran d'enviar també en arxius apart en format TIFF, EPS o JPEG. Si s'opta per la versió impresa, s'han d'enviar quatre còpies del treball juntament amb una còpia en disquet a la Secretaria de Redacció. Cal incloure, juntament amb l'article, una carta on es faci constar que el treball està basat en investigacions originals no publicades anterior­ment i que està sotmès a Animal Biodiversity and Conservation en exclusiva. A la carta també ha de constar, per a aquells treballs en que calgui manipular animals, que els autors disposen dels permisos necessaris i que compleixen la normativa de protecció animal vigent. També es poden suggerir possibles assessors.

Quan l'article sigui acceptat, els autors hauran d'enviar a la Redacció una còpia impresa de la versió final acompanyada d'un disquet indicant el progra­ ma utilitzat (preferiblement en Word). Les proves d'impremta enviades a l'autor per a la correcció, seran retornades al Consell Editor en el termini de 10 dies. Aniran a càrrec dels autors les despeses degudes a modificacions substancials introduïdes per ells en el text original acceptat.

ISSN: 1578–665X

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El primer autor rebrà 50 separates del treball sense càrrec a més d'una separata electrònica en format PDF. Manuscrits Els treballs seran presentats en format DIN A­–4 (30 línies de 70 espais cada una) a doble espai i amb totes les pàgines numerades. Els manus­crits han de ser complets, amb taules i figures. No s'han d'enviar les figures originals fins que l'article no hagi estat acceptat.

El text es podrà redactar en anglès, castellà o català. Se suggereix als autors que enviïn els seus treballs en anglès. La revista els ofereix, sense cap càrrec, un servei de correcció per part d'una persona especialitzada en revistes científiques. En tots els casos, els textos hauran de ser redactats correctament i amb un llenguatge clar i concís. La redacció del text serà impersonal, i s'evitarà sempre la primera persona.

Els caràcters cursius s’empraran per als noms científics de gèneres i d’espècies i per als neologis­ mes intraduïbles; les cites textuals, independentment de la llengua, seran consignades en lletra rodona i entre cometes i els noms d’autor que segueixin un tàxon aniran en rodona.

Quan se citi una espècie per primera vegada en el text, es ressenyarà, sempre que sigui possible, el seu nom comú.

Els topònims s’escriuran o bé en la forma original o bé en la llengua en què estigui escrit el treball, seguint sempre el mateix criteri.

Els nombres de l’u al nou, sempre que estiguin en el text, s’escriuran amb lletres, excepte quan precedeixin una unitat de mesura. Els nombres més grans s'escriuran amb xifres excepte quan comencin una frase.

Les dates s’indicaran de la forma següent: 28 VI 99 (un únic dia); 28, 30 VI 99 (dies 28 i 30); 28–30 VI 99 (dies 28 a 30).

S’evitaran sempre les notes a peu de pàgina.

Format dels articles Títol. Serà concís, però suficientment indicador del contingut. Els títols amb desig­nacions de sèries numèriques (I, II, III, etc.) seran acceptats previ acord amb l'editor.

Nom de l’autor o els autors.

Abstract en anglès que no ultrapassi les 12 línies mecanografiades (860 espais) i que mostri l’essència del manuscrit (introducció, material, mètodes, resultats i discussió). S'evitaran les especulacions i les cites bibliogràfiques. Estarà encapçalat pel títol del treball en cursiva.

Key words en anglès (sis com a màxim), que orientin sobre el contingut del treball en ordre d’importància.

Resumen en castellà, traducció de l'Abstract. De la traducció se'n farà càrrec la revista per a aquells autors que no siguin castellano­parlants.

Palabras clave en castellà. © 2010 Museu de Ciències Naturals

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Adreça postal de l’autor o autors.

(Títol, Nom, Abstract, Key words, Resumen, Pala­ bras clave i Adreça postal, conformaran la primera pàgina.)

Introducción. S'hi donarà una idea dels antecedents del tema tractat, així com dels objectius del treball.

Material y métodos. Inclourà la informació pertinent de les espècies estudiades, aparells emprats, mèto­ des d’estudi i d’anàlisi de les dades i zona d’estudi.

Resultados. En aquesta secció es presentaran úni­ cament les dades obtingudes que no hagin estat publicades prèviament.

Discusión. Es discutiran els resultats i es compa­ raran amb treballs relacionats. Els sug­geriments de recerques futures es podran incloure al final d’aquest apartat.

Agradecimientos (optatiu).

Referencias. Cada treball haurà d’anar acom­ panyat de les referències bibliogràfiques citades en el text.

Les referències han de presentar–se segons els models següents (mètode Harvard): * Articles de revista: Conroy, M. J. & Noon, B. R., 1996. Mapping of spe­ cies richness for conservation of biological diversity: conceptual and methodological issues. Ecological Applications, 6: 763–773. * Llibres o altres publicacions no periòdiques: Seber, G. A. F., 1982. The estimation of animal abundance. C. Griffin & Company, London. * Treballs de contribució en llibres: Macdonald, D. W. & Johnson, D. P., 2001. Dispersal in theory and practice: consequences for conserva­ tion biology. In: Dispersal: 358–372 (T. J. Clober, E. Danchin, A. A. Dhondt & J. D. Nichols, Eds.).

Oxford University Press, Oxford. * Tesis doctorals: Merilä, J., 1996. Genetic and quantitative trait vari­ ation in natural bird populations. Tesis doctoral, Uppsala University. * Els treballs en premsa només han d’ésser citats si han estat acceptats per a la publicació: Ripoll, M. (in press). The relevance of population

studies to conservation biology: a review. Anim.

Biodivers. Conserv.

La relació de referències bibliogràfiques d’un tre­ ball serà establerta i s’ordenarà alfabè­ticament per autors i cronològicament per a un mateix autor, afegint les lletres a, b, c,... als treballs del mateix any. En el text, s’indi­caran en la forma usual: "... segons Wemmer (1998)...", "...ha estat definit per Robinson & Redford (1991)...", "...les prospeccions realitzades (Begon et al., 1999)...".

Taules. Es numeraran 1, 2, 3, etc. i han de ser sempre ressenyades en el text. Les taules grans seran més estretes i llargues que amples i curtes ja que s'han d'encaixar en l'amplada de la caixa de la revista.

Figures. Tota classe d’il·lustracions (gràfics, figures o fotografies) entraran amb el nom de figura i es numeraran 1, 2, 3, etc. i han de ser sempre ressen­ yades en el text. Es podran incloure fotografies si són imprescindibles. Si les fotografies són en color, el cost de la seva publicació anirà a càrrec dels au­ tors. La mida màxima de les figures és de 15,5 cm d'amplada per 24 cm d'alçada. S'evitaran les figures tridimensionals. Tant els mapes com els dibuixos han d'incloure l'escala. Els ombreigs preferibles són blanc, negre o trama. S'evitaran els punteigs ja que no es repro­dueixen bé.

Peus de figura i capçaleres de taula. Seran clars, concisos i bilingües en la llengua de l’article i en anglès.

Els títols dels apartats generals de l’article (Intro­ ducción, Material y métodos, Resultados, Discusión, Conclusiones, Agradecimientos y Referencias) no aniran numerats. No es poden utilitzar més de tres nivells de títols.

Els autors procuraran que els seus treballs originals no passin de 20 pàgines (incloent–hi figures i taules).

Si a l'article es descriuen nous tàxons, caldrà que els tipus estiguin dipositats en una insti­tució pública.

Es recomana als autors la consulta de fascicles recents de la revista per tenir en compte les seves normes.

Animal Biodiversity and Conservation 33.1 (2010)

Animal Biodiversity and Conservation Animal Biodiversity and Conservation (antes Miscel·lània Zoològica) es una revista inter­ disciplinar, 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, mor­ fología, biogeografía, ecología, etología, fisiología y genética) procedentes de todas las regiones del mundo, con especial énfasis en los estudios que de una manera u otra tengan relevancia en la biología de la conservación. La revista no publica compila­ ciones 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 http://www.bcn.cat/ABC, 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 siem­ pre que es posible. La publicación de los trabajos aceptados se realiza con la mayor rapidez posible, normalmente dentro de los 12 meses siguientes a la recepción del trabajo.

Una vez aceptado, el trabajo pasará a ser propie­ dad de la revista. Ésta se reserva los derechos de autor, y ninguna parte del trabajo podrá ser reprodu­ cida sin citar su procedencia.

Normas de publicación Los trabajos se enviarán preferentemente de forma electrónica (abc@bcn.cat). El formato preferido es un documento Rich Text Format (RTF) o DOC, que incluya las figuras y las tablas. Las figuras deberán enviarse también en archivos separados en formato TIFF, EPS o JPEG. Si se opta por la versión impresa, deberán remitirse cuatro copias juntamente con una copia en disquete a la Secretaría de Redacción. Debe incluirse, con el artículo, una carta donde conste que el trabajo versa sobre inves­tigaciones originales no publi­cadas an­te­rior­mente y que se somete en ex­ clusiva a Animal Biodiversity and Conservation.

En dicha carta también debe constar, para trabajos donde sea necesaria la manipulación de animales, que los autores disponen de los permisos necesa­ rios y que han cumplido la normativa de protección animal vigente. Los autores pueden enviar también sugerencias para asesores.

Cuando el trabajo sea aceptado los autores de­ berán enviar a la Redacción una copia impresa de la versión final junto con un disquete del manuscrito ISSN: 1578–665X

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preparado con un pro­cesador de textos e indican­ do el programa utilizado (preferiblemente Word).

Las pruebas de imprenta enviadas a los autores deberán remitirse corregidas al Consejo Editor en el plazo máximo de 10 días. Los gastos debidos a modificaciones sustanciales en las pruebas de im­ pren­­ta, introducidas por los autores, irán a ­cargo de los mismos.

El primer autor recibirá 50 separatas del trabajo sin cargo alguno y una copia electrónica en for­ mato PDF. Manuscritos Los trabajos se presentarán en formato DIN A–4 (30 líneas de 70 espacios cada una) a doble espacio y con las páginas numeradas. Los manuscritos de­ ben 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 especula­ © 2010 Museu de Ciències Naturals

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ciones 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. Anim.

Biodivers. Conserv.

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, Dis­ cusión, Agradecimientos y Referencias) no se nume­ rarán. 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 fascículos recientes de la revista para seguir sus directrices.

Animal Biodiversity and Conservation 33.1 (2010)

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Animal Biodiversity and Conservation

Manuscripts

Animal Biodiversity and Conservation (formerly Miscel·lània Zoològica) is an interdisciplinary journal published by the Natural Science Museum of Barce­ lona since 1958. It includes empirical and theoretical research from around the world that examines any aspect of Zoology (Systematics, Taxonomy, Morphol­ ogy, Biogeography, Ecology, Ethology, Physiology and Genetics). It gives special emphasis to studies related to Conservation Biology. The journal does not publish bibliographic compilations, listings, catalogues or col­ lections of species, or isolated descriptions of a single specimens. 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 http://www.bcn.cat/ABC, assuring world–wide access to articles published therein.

All manuscripts are screened by the Executive Edi­ tor, 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 prop­ erty 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 Cata­ lan, 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 gen­ era and species as well as untranslatable neologisms must be in italics. Quotations in whatever language used must be typed in ordinary print between quota­ tion 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 proper nouns (e.g.

Iberian rock lizard). Place names may appear ei­ ther in their original form or in the langua ge 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.

If a printed version is sent, four copies should be forwarded to the Editorial Office, together with a copy on computer disc. A cover letter stating that the article reports original research that has not been published elsewhere and has been submitted exclusively for consideration 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 protec­ tion 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 50 reprints free of charge and an electronic version of the article in PDF format.

ISSN: 1578–665X

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 au­ thors will be translated by the journal on request.

Palabras clave in Spanish.

Address of the author or authors.

(Title, Name, Abstract, Key words, Resumen, Palabras 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. © 2010 Museu de Ciències Naturals

VI

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 re­ lated 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. Anim.

Biodivers. Conserv.

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 Refer­ ences) 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.

Animal Biodiversity and Conservation 33.1 (2010)

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Psg. Picasso s/n.

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Lluïsa Arroyo Dept. of Scientific Publications Museu de Ciències Naturals de Barcelona Psg. Picasso s/n.

08003 Barcelona, Spain

VII

"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

Animal Biodiversity and Conservation 33.1 (2010)

IX

Welcome to the electronic version of Animal Biodiversity and Conservation

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http://www.bcn.cat/ABC

Animal Biodiversity and Conservation joins the recent worldwide Open Access Initiative of providing a permanent online version free of charge and access barriers This is the result of the growing point of view that open access to research is essential for efficient and rapid scientific communication

ABC alert, a free alerting service, provides eâ&#x20AC;&#x201C;mail information on the latest issue To sign on for this service, please send an eâ&#x20AC;&#x201C;mail to: abc@bcn.cat

"La tortue greque" Oeuvres du Comte de Lacépède comprenant L'Histoire Naturelle des Quadrupèdes Ovipares, des Serpents, des Poissons et des Cétacés; Nouvelle édition avec planches coloriées dirigée par M. A. G. Desmarest; Bruxelles: Th. Lejeuné, Éditeur des oeuvres de Buffon, 1836. Pl. 7

Editor executiu / Editor ejecutivo / Executive Editor Joan Carles Senar

Secretaria de Redacció / Secretaría de Redacción / Editorial Office

Secretària de Redacció / Secretaria de Redacción / Managing Editor Montserrat Ferrer

Museu de Zoologia Passeig Picasso s/n 08003 Barcelona, Spain Tel. +34–93–3196912 Fax +34–93–3104999 E–mail mzbpubli@intercom.es

Consell Assessor / Consejo asesor / Advisory Board Oleguer Escolà Eulàlia Garcia Anna Omedes Josep Piqué Francesc Uribe

Editors / Editores / Editors Antonio Barbadilla Univ. Autònoma de Barcelona, Bellaterra, Spain Xavier Bellés Centre d' Investigació i Desenvolupament CSIC, Barcelona, Spain Juan Carranza Univ. de Extremadura, Cáceres, Spain Luís Mª Carrascal Museo Nacional de Ciencias Naturales CSIC, Madrid, Spain Adolfo Cordero Univ. de Vigo, Vigo, Spain Mario Díaz Univ. de Castilla–La Mancha, Toledo, Spain Xavier Domingo Univ. Pompeu Fabra, Barcelona, Spain Francisco Palomares Estación Biológica de Doñana, Sevilla, Spain Francesc Piferrer Inst. de Ciències del Mar CSIC, Barcelona, Spain Ignacio Ribera The Natural History Museum, London, United Kingdom Alfredo Salvador Museo Nacional de Ciencias Naturales, Madrid, Spain José Luís Tellería Univ. Complutense de Madrid, Madrid, Spain Francesc Uribe Museu de Zoologia de Barcelona, Barcelona, Spain

Consell Editor / Consejo editor / Editorial Board José A. Barrientos Univ. Autònoma de Barcelona, Bellaterra, Spain Jean C. Beaucournu Univ. de Rennes, Rennes, France David M. Bird McGill Univ., Québec, Canada Mats Björklund Uppsala Univ., Uppsala, Sweden Jean Bouillon Univ. Libre de Bruxelles, Brussels, Belgium Miguel Delibes Estación Biológica de Doñana CSIC, Sevilla, Spain Dario J. Díaz Cosín Univ. Complutense de Madrid, Madrid, Spain Alain Dubois Museum national d’Histoire naturelle CNRS, Paris, France John Fa Durrell Wildlife Conservation Trust, Trinity, United Kingdom Marco Festa–Bianchet Univ. de Sherbrooke, Québec, Canada Rosa Flos Univ. Politècnica de Catalunya, Barcelona, Spain Josep Mª Gili Inst. de Ciències del Mar CMIMA–CSIC, Barcelona, Spain Edmund Gittenberger Rijksmuseum van Natuurlijke Historie, Leiden, The Netherlands Fernando Hiraldo Estación Biológica de Doñana CSIC, Sevilla, Spain Patrick Lavelle Inst. Français de recherche scient. pour le develop. en cooperation, Bondy, France Santiago Mas–Coma Univ. de Valencia, Valencia, Spain Joaquín Mateu Estación Experimental de Zonas Áridas CSIC, Almería, Spain Neil Metcalfe Univ. of Glasgow, Glasgow, United Kingdom Jacint Nadal Univ. de Barcelona, Barcelona, Spain Stewart B. Peck Carleton Univ., Ottawa, Canada Eduard Petitpierre Univ. de les Illes Balears, Palma de Mallorca, Spain Taylor H. Ricketts Stanford Univ., Stanford, USA Joandomènec Ros Univ. de Barcelona, Barcelona, Spain Valentín Sans–Coma Univ. de Málaga, Málaga, Spain Tore Slagsvold Univ. of Oslo, Oslo, Norway

Animal Biodiversity and Conservation 24.1, 2001 © 2001 Museu de Zoologia, Institut de Cultura, Ajuntament de Barcelona Autoedició: Montserrat Ferrer Fotomecànica i impressió: Sociedad Cooperativa Librería General ISSN: 1578–665X Dipòsit legal: B–16.278–58

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, Current Primate References, DIALNET, DOAJ, Ecological Abstracts, Ecology Abstracts, Entomology Abstracts, Environmental Abstracts, Environmental Periodical Bibliography, Genetic Abstracts, Geographical Abstracts, Índice Español de Ciencia y Tecnología, International Abstracts of Biological Sciences, International Bibliography of Periodical Literature, International Developmental Abstracts, Marine Sciences Contents Tables, Oceanic Abstracts, RACO, Recent Ornithological Literature, Referatirnyi Zhurnal, Science Abstracts, Scientific Commons, SCImago, SCOPUS, Serials Directory, Ulrich’s International Periodical Directory, Zoological Records.

Índex / Índice / Contents Animal Biodiversity and Conservation 33.1 (2010) ISSN 1578–665X

1–13 C. A. Strojny & M. L. Hunter Jr. Relative abundance of amphibians in forest canopy gaps of natural origin vs. timber harvest origin

53–61 J. Quesada & I. MacGregor–Fors Avian community r esponses to the establisment of small garden allotments within a Mediterranean habitat mosaic

15–18 J. J. Bellido, J. C. Báez, J. J. Castillo, J. J. Martín, J. L. Mons & R. Real Unusual behaviour of an immature loggerhead turtle released in the Alboran Sea

63–87 H. H. Welsh Jr., G. R. Hodgson, J. J. Duda & J. M. Emlen Faunal assemblages and multi–scale habitat patterns in headwater tributaries of the South Fork Trinity River – an unregulated river embedded within a multiple–use landscape

19–29 Y. Ferrer Sánchez, D. Denis Ávila & I. Ruiz Companioni Caracterización y selección del sitio de anidación de la grulla cubana (Grus canadensis nesiotes) en el herbazal del Refugio de Fauna El Venero, Cuba 31–45 J. A. González–Oreja, A. A. de la Fuente–Díaz– Ordaz, L. Hernández–Santín, D. Buzo–Franco & C. Bonache–Regidor Evaluación de estimadores no paramétricos de la riqueza de especies. Un ejemplo con aves en áreas verdes de la ciudad de Puebla, México 47–51 M. Kadej & J. Háva, J. Anthrenus (Florilinus) loebli n. sp. (Coleoptera, Dermestidae, Anthrenini) from the Middle East

89–115 A. Borras, J. C. Senar, F. Alba–Sánchez, J. A. López– Sáez, J. Cabrera, X. Colomer & T. Cabrera Citril finches during the winter: patterns of distribution, the role of pines and implications for the conservation of the species 117 A. Martínez–Abraín Imaginary populations

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