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Uso de Información Biológica Básica para la Predicción Rápida de la Respuesta de Especies a la Pérdida de Hábitat
Author(s) -
HOCKEY PHILIP A. R.,
CURTIS ODETTE E.
Publication year - 2009
Publication title -
conservation biology
Language(s) - English
Resource type - Journals
SCImago Journal Rank - 2.2
H-Index - 222
eISSN - 1523-1739
pISSN - 0888-8892
DOI - 10.1111/j.1523-1739.2008.01028.x
Subject(s) - threatened species , iucn red list , endangered species , habitat , ecology , habitat destruction , critically endangered , lemur , extinction (optical mineralogy) , conservation status , range (aeronautics) , geography , biology , paleontology , materials science , primate , composite material
Much research has focused on identifying traits that can act as useful indicators of how habitat loss affects the extinction risk of species, and the results are mixed. We developed 2 simple, rapid‐assessment models of the susceptibility of species to habitat loss. We based both on an index of range size, but one also incorporated an index of body mass and the other an index combining habitat and dietary specialization. We applied the models to samples of birds (Accipitridae and Bucerotidae) and to the lemurs of Madagascar and compared the models' classifications of risk with the IUCN's global threat status of each species. The model derived from ecological attributes was much more robust than the one derived from body mass. Ecological attributes identified threatened birds and lemurs with an average of 80% accuracy and endangered and critically endangered species with 100% accuracy and identified some species not currently listed as threatened that almost certainly warrant conservation consideration. Appropriate analysis of even fairly crude biological information can help raise early‐warning flags to the relative susceptibilities of species to habitat loss and thus provide a useful and rapid technique for highlighting potential species‐level conservation issues. Advantages of this approach to classifying risk include flexibility in the specialization parameters used as well as its applicability at a range of spatial scales.