Predicting distributions of known and unknown reptile species in Madagascar.
Despite the importance of tropical biodiversity, informative species distributional data are seldom available for biogeographical study or setting conservation priorities. Modelling ecological niche distributions of species offers a potential solution; 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.
Raxworthy
Christopher J
CJ
American Museum of Natural History, Central Park West at 79th Street, New York, New York 10024-5192, USA. rax@amnh.org
Martinez-Meyer
Enrique
E
Horning
Ned
N
Nussbaum
Ronald A
RA
Schneider
Gregory E
GE
Ortega-Huerta
Miguel A
MA
Townsend Peterson
A
A
D000818:Animals; D044822:Biodiversity; D008116:Lizards / Q000145:classification / Q000502:physiology; D008270:Madagascar; D008954:Models, Biological; D011157:Population Dynamics; D012104:Reptiles / Q000145:classification* / Q000502:physiology*; D013045:Species Specificity