Predicting distributions of known and unknown reptile species in Madagascar

Christopher J. Raxworthy (), Enrique Martinez-Meyer, Ned Horning, Ronald A. Nussbaum, Gregory E. Schneider, Miguel A. Ortega-Huerta and A. Townsend Peterson
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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

Nature, 2003, vol. 426, issue 6968, 837-841

Abstract: 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.

Date: 2003
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DOI: 10.1038/nature02205

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