New Distribution Records and Potentially Suitable Areas for the Threatened Snake-Necked Turtle Hydromedusa maximiliani (Testudines: Chelidae) Author(s): Henrique C. Costa, Daniella T. de Rezende, Flavio B. Molina, Luciana B. Nascimento, Felipe S.F. Leite, and Ana Paula B. Fernandes Source: Chelonian Conservation and Biology, 14(1):88-94. Published By: Chelonian Research Foundation DOI: http://dx.doi.org/10.2744/ccab-14-01-88-94.1 URL: http://www.bioone.org/doi/full/10.2744/ccab-14-01-88-94.1 BioOne (www.bioone.org) is a nonprofit, online aggregation of core research in the biological, ecological, and environmental sciences. BioOne provides a sustainable online platform for over 170 journals and books published by nonprofit societies, associations, museums, institutions, and presses. Your use of this PDF, the BioOne Web site, and all posted and associated content indicates your acceptance of BioOne’s Terms of Use, available at www.bioone.org/page/terms_of_use. Usage of BioOne content is strictly limited to personal, educational, and non-commercial use. Commercial inquiries or rights and permissions requests should be directed to the individual publisher as copyright holder. BioOne sees sustainable scholarly publishing as an inherently collaborative enterprise connecting authors, nonprofit publishers, academic institutions, research libraries, and research funders in the common goal of maximizing access to critical research. Chelonian Conservation and Biology, 2015, 14(1): 88–94 g 2015 Chelonian Research Foundation New Distribution Records and Potentially Suitable Areas for the Threatened Snake-Necked Turtle Hydromedusa maximiliani (Testudines: Chelidae) 1, 1 2,3 4 HENRIQUE C. COSTA *,DANIELLA T. DE REZENDE ,FLAVIO B. MOLINA ,LUCIANA B. NASCIMENTO , 5 6 FELIPE S.F. LEITE , AND ANA PAULA B. FERNANDES 1Universidade Federal de Minas Gerais, Instituto de Cieˆncias Biolo´gicas, Avenida Antoˆnio Carlos, 6627, Pampulha, CEP 31270-901, Belo Horizonte, Minas Gerais, Brazil [[email protected]; [email protected]]; 2Universidade de Santo Amaro, Campus I, Rua Prof. Eneas de Siqueira Neto, 340, Bairro Cidade Dutra, CEP 04829-300, Sa˜o Paulo, Sa˜o Paulo, Brazil; 3Museu de Zoologia da Universidade de Sa˜o Paulo, Laborato´rio de Herpetologia, Avenida Nazareth, 481, Ipiranga, CEP 04263-000, Sa˜o Paulo, Sa˜o Paulo, Brazil [[email protected]]; 4Pontifı´cia Universidade Cato´lica de Minas Gerais (PUC Minas), Programa de Po´s-graduac¸a˜o em Zoologia de Vertebrados, Museu de Cieˆncias Naturais, Avenida Dom Jose´ Gaspar, 290, CEP 30535-610, Belo Horizonte, Minas Gerais, Brazil [[email protected]]; 5Universidade Federal de Vic¸osa – Campus Florestal, Instituto de Cieˆncias Biolo´gicas, Rodovia LMG 818, km 06, CEP 35690-000, Florestal, Minas Gerais, Brazil [[email protected]]; 6Universidade Federal do Para´,Nu´cleo de Altos Estudos Amazoˆnicos (NAEA), Cidade Universita´ria Jose´ da Silveira Netto / Setor Profissional, sala 201, Av. Perimetral, 1, Bairro do Guama´, CEP 66075-650, Bele´m, Para´, Brazil [[email protected]] *Corresponding author ABSTRACT.–Hydromedusa maximiliani is a freshwater turtle endemic to the Atlantic Forest of eastern and southeastern Brazil and threatened by extinction. Here, we add 15 new locality records for this species based on photographs of specimens encountered in the field and examination of museum collections. We also used ecological niche modeling tools of 3 different algorithms (GARP, SVM, and Maxent) to suggest potential suitable areas for the occurrence of the species. Models predict 53,679–263,844 km2 of suitable habitat for H. maximiliani, with 8396– 31,758 km2 inside protected areas. Besides being useful in a reassessment of the species’ conservation status, our results contribute to the knowledge of distribution patterns of H. maximiliani and highlight potential areas to drive future field surveys. KEY WORDS. – Reptilia; biogeography; conservation; ecological niche; freshwater turtle; geographic distribution; species distribution model Hydromedusa maximiliani (Mikan 1825) is a small of its discovery in previously unknown localities freshwater turtle species endemic to the Atlantic Forest of (Fundac¸a˜o Biodiversitas 2007). eastern and southeastern Brazil (Iverson 1992; Souza and We present new locality records for H. maximiliani Martins 2009). Individuals inhabit clear and cold-water and use ecological niche modeling tools to predict streams with sandy and rocky bottoms (Souza and Martins additional areas with suitable habitats for its occurrence. 2006, 2009), from coastal rivers below 100 m to water These new data may be useful to better understand the bodies above 600 m elevation (Souza 2005; Souza and species’ distribution pattern and to guide a more realistic Martins 2009). evaluation in future reviews of its conservation status. Anthropogenic threats, including habitat loss and water pollution, are the main factors affecting populations METHODS of H. maximiliani (Souza and Martins 2009). This species is considered Vulnerable by the International Union for In order to update the information on its geographic Conservation of Nature Red List, although its evaluation distribution, we gathered records of H. maximiliani from needs updating (Tortoise & Freshwater Turtle Specialist the following sources: 1) literature records; 2) photo- Group 1996). It is not included in the Brazilian Red List graphs of unvouchered field specimens taken by us and (Ministe´rio do Meio Ambiente 2014), but is considered other colleagues allowing unambiguous identification of locally threatened in the states of Espı´rito Santo the species; and 3) voucher specimens in herpetological (Secretaria de Estado de Meio Ambiente e Recursos collections (Table 1). We do not consider a record from Hı´dricos [SEAMA] 2005; Almeida et al. 2007) and Minas EmySystem (2010) based on a specimen from the British Gerais (Conselho de Polı´tica Ambiental [COPAM] 2010). Museum of Natural History, London (BMNH 1965.823), In the first edition of the List of Endangered Species of because of uncertainty of sampling locality (C. McCarthy, the state of Minas Gerais, H. maximiliani was considered in litt., January 2011). Critically Endangered (COPAM 1995; Moreira 1998). Additionally, we used ecological niche modeling Following the latest review of that list, the species’ tools to suggest potential suitable areas for the occurrence conservation status was changed to Vulnerable on account of H. maximiliani (Guisan and Thuiller 2005). The study COSTA ET AL. — Ecological Niche Modeling of Hydromedusa maximiliani 89 area was delimited by a buffer of 500 km around known a ‘‘lowest presence’’ value was used as a threshold in occurrences, in order to reduce the area where background order to obtain a binary map of presence and absence (Liu points (pseudo-absence) could be generated in the et al. 2005). An ensemble of binary maps from the 3 modeling process, being closer to species’ known algorithms was made and only areas identified by all occurrences. This method is more reliable because the 3 were considered to be potentially suitable for the species’ absence in places too far from its known species’ occurrence (Arau´jo and New 2006). occurrence is more likely to be influenced by another Available data indicate that H. maximiliani popula- factor such as geographic isolation, than by environmental tions depend on forest remnants for survival (e.g., Souza variables. 2005). Thus, the final distribution map was superimposed To generate the models, environmental layers were onto a map of vegetation remnants (http://siscom.ibama. obtained from WorldClim (www.worldclim.org) for bio- gov.br/monitorabiomas/) to better estimate where the climatic variables and EROS Data Center (eros. species would be able to occur, considering 2 hypothetical usgs.gov) for digital elevation model (DEM). Slope layer scenarios: one where suitable areas cannot be . 0.5 km was derived from DEM considering differences in altitude from a stream margin, and the other where the distance between cells of a raster map. Using 19 bioclimatic layers cannot exceed 1.5 km. These results were superimposed and 2 aspect layers, a correlation analysis was carried to on a map of Brazilian protected areas to estimate the choose the variables to be used in the distribution range of the species within conservation units. modeling, excluding variables with correlation value below 0.8 to avoid model overfitting (Jime´nez-Valverde RESULTS et al. 2011). An analysis of correlation using Moran’s I index was also conducted to evaluate the spatial The search for new specimens of H. maximiliani led autocorrelation of the records used. us to add 15 new localities where the species occurs, all in The species’ records were combined with 8 environ- the state of Minas Gerais. The historical distribution of mental layers (annual mean temperature, mean diurnal this species is now composed of 48 localities: 5 in the range, temperature seasonality, temperature annual range, state of Bahia, 2 in the state of Espı´rito Santo, 21 in the annual precipitation, precipitation seasonality, altitude, state of Minas Gerais, 10 in the state of Rio de Janeiro, and slope) from current climate data in 0.04u resolution and 10 in the state of Sa˜o Paulo (Fig. 1; Table 1). (Hijmans et al. 2005) using 3 algorithms: Genetic Presently, H. maximiliani is known to occur in small Algorithm for Rule-set Production (GARP), support rivers belonging to 1) the Catole´, Cachoeira, Contas, vector machine (SVM), and Maximum Entropy Modeling Jiquiric¸a´