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How to not inflate population estimates? Spatial density distribution of white-lipped peccaries in a continuous Atlantic forest
2011; Wiley; Volume: 14; Issue: 5 Linguagem: Inglês
10.1111/j.1469-1795.2011.00450.x
ISSN1469-1795
AutoresDarren Norris, Fabiana Rocha-Mendes, Sílvio Frosini de Barros Ferraz, João Paulo Villani, Mauro Galetti,
Tópico(s)Ecology and Vegetation Dynamics Studies
ResumoAnimal ConservationVolume 14, Issue 5 p. 492-501 How to not inflate population estimates? Spatial density distribution of white-lipped peccaries in a continuous Atlantic forest D. Norris, D. Norris Laboratório de Biologia da Conservação, Departamento de Ecologia, Universidade Estadual Paulista (UNESP), Rio Claro, SP, BrazilSearch for more papers by this authorF. Rocha-Mendes, F. Rocha-Mendes Laboratório de Biologia da Conservação, Departamento de Ecologia, Universidade Estadual Paulista (UNESP), Rio Claro, SP, Brazil Neotropical Institute: Research and Conservation, Curitiba, PR, BrazilSearch for more papers by this authorS. Frosini de Barros Ferraz, S. Frosini de Barros Ferraz Departamento de Ciências Florestais, Escola Superior de Agricultura 'Luiz de Queiroz', Universidade de São Paulo, Piracicaba, SP, BrazilSearch for more papers by this authorJ. P. Villani, J. P. Villani Parque Estadual da Serra do Mar – Núcleo Santa Virgínia, São Luiz de Paraitinga, SP, BrazilSearch for more papers by this authorM. Galetti, M. Galetti Laboratório de Biologia da Conservação, Departamento de Ecologia, Universidade Estadual Paulista (UNESP), Rio Claro, SP, BrazilSearch for more papers by this author D. Norris, D. Norris Laboratório de Biologia da Conservação, Departamento de Ecologia, Universidade Estadual Paulista (UNESP), Rio Claro, SP, BrazilSearch for more papers by this authorF. Rocha-Mendes, F. Rocha-Mendes Laboratório de Biologia da Conservação, Departamento de Ecologia, Universidade Estadual Paulista (UNESP), Rio Claro, SP, Brazil Neotropical Institute: Research and Conservation, Curitiba, PR, BrazilSearch for more papers by this authorS. Frosini de Barros Ferraz, S. Frosini de Barros Ferraz Departamento de Ciências Florestais, Escola Superior de Agricultura 'Luiz de Queiroz', Universidade de São Paulo, Piracicaba, SP, BrazilSearch for more papers by this authorJ. P. Villani, J. P. Villani Parque Estadual da Serra do Mar – Núcleo Santa Virgínia, São Luiz de Paraitinga, SP, BrazilSearch for more papers by this authorM. Galetti, M. Galetti Laboratório de Biologia da Conservação, Departamento de Ecologia, Universidade Estadual Paulista (UNESP), Rio Claro, SP, BrazilSearch for more papers by this author First published: 24 March 2011 https://doi.org/10.1111/j.1469-1795.2011.00450.xCitations: 14 Darren Norris, Laboratório de Biologia da Conservação, Departamento de Ecologia, Universidade Estadual Paulista (UNESP), Caixa Postal 199, Rio Claro, 13506-900 SP, Brazil. Tel/Fax: +55 51 3332 0762Email: dnorris75@gmail.com Editor: Res Altwegg Read the full textAboutPDF ToolsRequest permissionExport citationAdd to favoritesTrack citation ShareShare Give accessShare full text accessShare full-text accessPlease review our Terms and Conditions of Use and check box below to share full-text version of article.I have read and accept the Wiley Online Library Terms and Conditions of UseShareable LinkUse the link below to share a full-text version of this article with your friends and colleagues. Learn more.Copy URL Share a linkShare onFacebookTwitterLinked InRedditWechat Abstract In a world with poor biological inventorying and rapid land-use change, predicting the spatial distribution of species is fundamental for the effective management and conservation of threatened taxa. However, on a regional scale, predicting the distribution of rare terrestrial mammals is often unreliable and/or impractical, especially in tropical forests. We apply a recently developed analytic process that integrates density estimation (kernel smoothing), niche-analysis and geostatistics (regression-kriging) to model the occupancy and density distribution of a threatened population of white-lipped peccaries Tayassu pecari in a Brazilian Atlantic forest. Locations (n=45) within a protected area of the Serra-do-Mar state park were obtained from diurnal line transect census (233 km), camera-trapping (751 camera-trap days) and surveys (>626 km) conducted by park rangers. Niche modelling (environmental niche-factor analysis and MAXENT) revealed a restricted niche compared with the available habitat as defined by seven environmental variables. From the occupancy model obtained from regression-kriging, we found that 72% of a 170 km2 protected area is likely to be used by peccaries. We demonstrate that the distribution of large mammals can be restricted within continuous areas of Atlantic forest and therefore population estimates based on the size of protected areas can be overestimated. Our findings suggest that the generation of realized density distributions should become the norm rather than the exception to enable conservation managers and researchers to extrapolate abundance and density estimates across continuous habitats and protected areas. Citing Literature Supporting Information Appendix S1. Sampling representativeness. Appendix S2. Principal Components. Appendix S3. Habitat Suitability. Appendix S4. Generation of pseudo-absences. Appendix S5. Regression – Kriging. Appendix S6. Literature Review. As a service to our authors and readers, this journal provides supporting information supplied by the authors. Such materials are peer-reviewed and may be re-organized for online delivery but are not copy-edited or typeset. Technical support issues arising from supporting information (other than missing files) should be addressed to the authors. Filename Description acv_450_sm_supporting-material.doc471.5 KB Supporting info item Please note: The publisher is not responsible for the content or functionality of any supporting information supplied by the authors. Any queries (other than missing content) should be directed to the corresponding author for the article. Volume14, Issue5October 2011Pages 492-501 RelatedInformation
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