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Predicting distributions of known and unknown reptile species in Madagascar

Author

Listed:
  • Christopher J. Raxworthy

    (American Museum of Natural History)

  • Enrique Martinez-Meyer

    (Universidad Nacional Autónoma de México, Ciudad Universitaria)

  • Ned Horning

    (American Museum of Natural History)

  • Ronald A. Nussbaum

    (Museum of Zoology, University of Michigan)

  • Gregory E. Schneider

    (Museum of Zoology, University of Michigan)

  • Miguel A. Ortega-Huerta

    (Universidad Nacional Autónoma de México, Ciudad Universitaria)

  • A. Townsend Peterson

    (Natural History Museum & Biodiversity Research Center, The University of Kansas
    Biodiversity Research Center, The University of Kansas)

Abstract

Despite the importance of tropical biodiversity1, informative species distributional data are seldom available for biogeographical study or setting conservation priorities2,3. Modelling ecological niche distributions of species offers a potential soluion4,5,6,7; however, the utility of old locality data from museums, and of more recent remotely sensed satellite data, remains poorly explored, especially for rapidly changing tropical landscapes. Using 29 modern data sets of environmental land coverage and 621 chameleon occurrence localities from Madagascar (historical and recent), here we demonstrate a significant ability of our niche models in predicting species distribution. At 11 recently inventoried sites, highest predictive success (85.1%) was obtained for models based only on modern occurrence data (74.7% and 82.8% predictive success, respectively, for pre-1978 and all data combined). Notably, these models also identified three intersecting areas of over-prediction that recently yielded seven chameleon species new to science. We conclude that ecological niche modelling using recent locality records and readily available environmental coverage data provides informative biogeographical data for poorly known tropical landscapes, and offers innovative potential for the discovery of unknown distributional areas and unknown species.

Suggested Citation

  • Christopher J. Raxworthy & Enrique Martinez-Meyer & Ned Horning & Ronald A. Nussbaum & Gregory E. Schneider & Miguel A. Ortega-Huerta & A. Townsend Peterson, 2003. "Predicting distributions of known and unknown reptile species in Madagascar," Nature, Nature, vol. 426(6968), pages 837-841, December.
  • Handle: RePEc:nat:nature:v:426:y:2003:i:6968:d:10.1038_nature02205
    DOI: 10.1038/nature02205
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    Citations

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    Cited by:

    1. Carlos Yañez-Arenas & A Townsend Peterson & Pierre Mokondoko & Octavio Rojas-Soto & Enrique Martínez-Meyer, 2014. "The Use of Ecological Niche Modeling to Infer Potential Risk Areas of Snakebite in the Mexican State of Veracruz," PLOS ONE, Public Library of Science, vol. 9(6), pages 1-9, June.
    2. Johnson, Chris J. & Gillingham, Michael P., 2008. "Sensitivity of species-distribution models to error, bias, and model design: An application to resource selection functions for woodland caribou," Ecological Modelling, Elsevier, vol. 213(2), pages 143-155.
    3. Ochoa-Ochoa, Leticia M. & Flores-Villela, Oscar A. & Bezaury-Creel, Juan E., 2016. "Using one vs. many, sensitivity and uncertainty analyses of species distribution models with focus on conservation area networks," Ecological Modelling, Elsevier, vol. 320(C), pages 372-382.
    4. Herkt, K. Matthias B. & Barnikel, Günter & Skidmore, Andrew K. & Fahr, Jakob, 2016. "A high-resolution model of bat diversity and endemism for continental Africa," Ecological Modelling, Elsevier, vol. 320(C), pages 9-28.
    5. Giovanelli, João G.R. & de Siqueira, Marinez Ferreira & Haddad, Célio F.B. & Alexandrino, João, 2010. "Modeling a spatially restricted distribution in the Neotropics: How the size of calibration area affects the performance of five presence-only methods," Ecological Modelling, Elsevier, vol. 221(2), pages 215-224.
    6. Silva, Daniel P. & Gonzalez, Victor H. & Melo, Gabriel A.R. & Lucia, Mariano & Alvarez, Leopoldo J. & De Marco, Paulo, 2014. "Seeking the flowers for the bees: Integrating biotic interactions into niche models to assess the distribution of the exotic bee species Lithurgus huberi in South America," Ecological Modelling, Elsevier, vol. 273(C), pages 200-209.
    7. Peterson, A. Townsend & Papeş, Monica & Soberón, Jorge, 2008. "Rethinking receiver operating characteristic analysis applications in ecological niche modeling," Ecological Modelling, Elsevier, vol. 213(1), pages 63-72.
    8. Pie, Marcio R. & Meyer, Andreas L.S. & Firkowski, Carina R. & Ribeiro, Luiz F. & Bornschein, Marcos R., 2013. "Understanding the mechanisms underlying the distribution of microendemic montane frogs (Brachycephalus spp., Terrarana: Brachycephalidae) in the Brazilian Atlantic Rainforest," Ecological Modelling, Elsevier, vol. 250(C), pages 165-176.
    9. Fois, Mauro & Cuena-Lombraña, Alba & Fenu, Giuseppe & Bacchetta, Gianluigi, 2018. "Using species distribution models at local scale to guide the search of poorly known species: Review, methodological issues and future directions," Ecological Modelling, Elsevier, vol. 385(C), pages 124-132.
    10. Kelly Jane Easterday & Patrick J McIntyre & James H Thorne & Maria J Santos & Maggi Kelly, 2016. "Assessing Threats and Conservation Status of Historical Centers of Oak Richness in California," Urban Planning, Cogitatio Press, vol. 1(4), pages 65-78.
    11. Jing Zhen & Xinyuan Wang & Qingkai Meng & Jingwei Song & Ying Liao & Bo Xiang & Huadong Guo & Chuansheng Liu & Ruixia Yang & Lei Luo, 2018. "Fine-Scale Evaluation of Giant Panda Habitats and Countermeasures against the Future Impacts of Climate Change and Human Disturbance (2015–2050): A Case Study in Ya’an, China," Sustainability, MDPI, vol. 10(4), pages 1-19, April.
    12. Lesley H Thorne & David W Johnston & Dean L Urban & Julian Tyne & Lars Bejder & Robin W Baird & Suzanne Yin & Susan H Rickards & Mark H Deakos & Joseph R Mobley Jr & Adam A Pack & Marie Chapla Hill, 2012. "Predictive Modeling of Spinner Dolphin (Stenella longirostris) Resting Habitat in the Main Hawaiian Islands," PLOS ONE, Public Library of Science, vol. 7(8), pages 1-14, August.

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