ZOOLOGIA 28 (4): 432–439, August, 2011 doi: 10.1590/S1984-46702011000400004 Modeling distribution of Phoneutria bahiensis (Araneae: Ctenidae): an endemic and threatened spider from Brazil Marcelo A. Dias1,2; Miguel Simó1,4; Ismael Castellano1 & Antonio D. Brescovit3 1 Sección Entomología, Facultad de Ciencias, Universidad de la República. Iguá 4225, CP 11400, Montevideo, Uruguay. 2 Centro de Ecologia e Conservação Animal, Universidade Católica de Salvador. Avenida Pinto de Aguiar 2589, Pituaçu, 41740-090 Salvador, BA, Brazil. 3 Laboratório de Artrópodes, Instituto Butantan. Avenida Vital Brasil 1500, 05503-900 São Paulo, SP, Brazil. 4 Corresponding author. E-mail: [email protected] ABSTRACT. Phoneutria bahiensis Simó & Brescovit, 2001 is a large ctenid spider inhabiting the states of Bahia and Espírito Santo, Brazil. Considering that it is probably endemic, this species was included in the Brazilian red book of threatened species. Here, we predict the distribution range of P. bahiensis using 19 bioclimatic variables in the model design. The most septentrional record for this spider was indicated for northern Bahia. The model predicts that the distribution range covers the Atlantic Forest from the state of Paraíba to Rio de Janeiro, with the best suitable area in the Atlantic Forest of the state of Bahia. The bioclimatic variable with the best contribution to the model was precipitation in the driest quarter. Based on collected data, the species inhabits Ombrophilous Forests and Restinga vegetation, two ecosystems of the Atlantic Forest biome. In the best-predicted area of distribution, eleven Conservation Units were included. This information could be considered for future conservation plans of this species. KEY WORDS. Atlantic Forest; niche modeling; bioclimatic variables; spider distribution. Species distribution models (SDMs) have been used to ance of a species, it is possible to predict the potential distribu- predict the potential distribution of living organisms, linking tion area for that species when considering all field sites with records or species abundance with environmental constrains similar climate conditions (ACOSTA 2008). Furthermore, these or spatial characteristics (GUISAN & ZIMMERMANN 2000, ELITH & models can be used for species with few geographic records LEATHWICK 2009). The models can be used to provide under- and scarce information on natural history (GUISAN & standing and generate predictions about species distributions ZIMMERMANN2000, BRITO et al. 2009, BAASCH et al. 2010) and are across a landscape. It has been successfully applied to terres- therefore very important when making decisions regarding the trial, freshwater and marine organisms in studies investigating conservation of threatened species and preservation of the conservation and management of species, conservation of biodiversity (BROOKS et al. 1999). areas with high biodiversity, and studies on biogeography, in- Although the evaluation of climate constraints do not take vasive species and global climate change (CARROLL 2010, GALLIEN into consideration other variables that may restrict geographic et al. 2010, FRANKLIN 2010, BENITO et al. 2009, DE MAS et al. 2009, distributions, for instance habitat accessibility, vegetation, com- ELITH & LEATHWICK 2009, FERRIER et al. 2002, GUISAN & ZIMMERMANN petition, predation, parasitism, dispersal and population genet- 2000). The great demand for these kinds of ecological studies ics, the limitations to the distribution of many species are often has promoted the development of several SDMs computer-based significantly associated with climate (PARMESAN 2006, SEXTON et programs using different algorithms that search for accuracy al. 2009). Moreover, climate constraints represent one of the of a given model and the best prediction power (FIELDING & BELL most consistent predictors for the successful establishment of 1997). While knowledge on the distributional ranges of spe- diverse taxa of plants and poikilothermic animals (ANDREWARTHA cies is clearly needed, the ranges of most species either remain & BIRCH 1984, WOODWARD 1987, VINK et al. 2011). largely unknown or are incomplete, and most of the available Sample size has been an important limitation for the studies are based on records from museum specimens, which performance evaluation of distribution models of species. The may be biased (STOCKMAN et al. 2006). accuracy of the general model increases as the sample size be- Regarding environmental constrains, SDMs based on cli- comes larger (WISZ et al. 2008). Studies based on small samples mate variables are considered useful tools for proposing crite- bring a greater degree of uncertainty to the estimation of pa- ria to select strategic areas for the conservation of species (ACOSTA rameters and consider fewer biological factors that may influ- 2008, RUBIO et al. 2010). Based on the expected climate toler- ence the relationships between species and their environment © 2011 Sociedade Brasileira de Zoologia | www.sbzoologia.org.br | All rights reserved. Modeling distribution of Phoneutria bahiensis: an endemic and threatened spider from Brazil 433 (CILIBERTI et al. 2009). Still, relatively few records may be enough The distribution patterns of Phoneutria spp. have not been to characterize the distribution of species with narrow envi- studied. Similarly, the factors which have restricted their dis- ronmental tolerances (KADMON et al. 2003). In this sense, good tributional range have not been investigated. As demonstrated predictions were obtained with modeling algorithms based on in previous studies on spiders and other invertebrates, tem- few geographic records and scarce information on natural his- perature and humidity are likely the two most important vari- tory (PEARSON et al. 2007, BRITO et al. 2009, KUMAR & STOHLGREN ables that constrain ecological niches. Taking into account the 2009, BAASCH et al. 2010). These models have been applied suc- important qualities of the tools used by SMDs in several stud- cessfully in the design of conservation plans for rare species ies, and the scarce application of this methodology in spiders, (GUISAN et al. 2006). the main objectives of this study were to predict the geographi- Published studies on the distribution of species of spi- cal distribution of P. bahiensis based on climatic variables and ders using SDMs are scarce. STOCKMAN et al. (2006) used the pro- to analyze its potential occurrence in Conservation Units in gram GARP to predict the spatial distribution of three species Brazil, an important contribution to the future management of trapdoor spiders of Promyrmekiaphila Schenkel, 1950 plans for this species. (Cyrtaucheniidae) in California, USA. They used several types of variables including soil, temperature, altitude, precipitation MATERIAL AND METHODS and vegetation. Studies based only upon climatic variables have also been successfully applied to spiders. VINK et al. (2011) stud- Occurrence data ied the current and world potential distribution and impacts Twenty-three records of P. bahiensis were analyzed: 22 of the invasive species Latrodectus hasseltii Thorell, 1870 (The- from the state of Bahia and one from the state of Espírito Santo. ridiidae) using the program CLIMEX. RUBIO et al. (2010) ana- The records were obtained from the literature (SIMÓ & BRESCOVIT lyzed the potential distribution range of Dubiaranea difficilis 2001, MARTINS & BERTANI 2007, BRAZIL et al. 2009) and from re- (Mello-Leitão, 1944) (Linyphiidae) in Argentina based on rela- cently collected specimens (by M.A.D.) in Mata de São João, in tively few locality records using Maxent. the Northern coast of the state of Bahia, Brazil. The specimens The Neotropical Phoneutria Perty, 1833 includes eight were deposited in the following institutions: Instituto Butantan, species of large wandering spiders which are considered to be São Paulo, São Paulo (IBSP), Universidade Federal of Bahia, Sal- of medical importance due to the neurotoxic effects of their vador, Bahia (UFBA) and Centro de Ecologia e Conservação venom (SIMÓ & BRESCOVIT 2001, MARTINS & BERTANI 2007). The Animal of the Universidade Católica do Salvador, Bahia (ECOA), genus is distributed from Central America to the northern all in Brazil. Argentina (SIMÓ & BRESCOVIT 2001, PLATNICK 2010) in three main Records areas: one from Central America to northeastern South-America, BRASIL, Bahia: Ilhéus 14°47’51”S, 39°02’13”W, 1 male (IBSP through the Andes, which includes Colombia, Ecuador, Peru, 19027); 1 female (IBSP 19040); 1 male (IBSP 19344); 1 female and Bolivia; a second area, situated in the Amazon region; and (IBSP 24057); 1 female (IBSP 22076); 1 female (UFBA/LAP-A a third covering northeastern and southern Brazil, northern 172); Ilhéus, 14°47’20”S, 39°02’58”W, 1 male (UFBA/LAP-A Argentina and Paraguay (MARTINS & BERTANI 2007). 173); 1 female (UFBA/LAP-A 1317); Itapebi 15°57’S, 39°32’W, 1 Phoneutria bahiensis Simó & Brescovit, 2001 was described male (IBSP 58193); 2 males 2 females (ECOA 00709); Porto from specimens collected from different sites of the Atlantic Seguro 16°26’59”S, 39°03’53”W, 1 female (IBSP 9516); Una, Forest biome in the state of Bahia, northeastern Brazil. DIAS et Reserva Biológica de Una, 15°16’20.08”S, 39°03’54.88”W, 1 fe- al. (2005a) and BRAZIL et al. (2009) reported new field records male (IBSP 45022); 1 male (IBSP 45023); 1 male (IBSP 45024); from Bahia. MARTINS & BERTANI (2007) indicated the southern- Lomanto Júnior, 14°81’S, 39°47’W, 1 female (IBSP 2427). Sal- most record in the state of Espírito