Abstract: Museum records have great potential to provide valuable insights into the vulnerability, historic distribution, and conservation of species, especially when coupled with species‐distribution models used to predict species' ranges. Yet, the increasing dependence on species‐distribution models in identifying conservation priorities calls for a more critical evaluation of model robustness. We used 11 bird species of conservation concern in Brazil's highly fragmented Atlantic Forest and data on environmental conditions in the region to predict species distributions. These predictions were repeated for five different model types for each of the 11 bird species. We then combined these species distributions for each model separately and applied a reserve‐selection algorithm to identify priority sites. We compared the potential outcomes from the reserve selection among the models. Although similarity in identification of conservation reserve networks occurred among models, models differed markedly in geographic scope and flexibility of reserve networks. It is essential for planners to evaluate the conservation implications of false‐positive and false‐negative errors for their specific management scenario before beginning the modeling process. Reserve networks selected by models that minimized false‐positive errors provided a better match with priority areas identified by specialists. Thus, we urge caution in the use of models that overestimate species' occurrences because they may misdirect conservation action. Our approach further demonstrates the great potential value of museum records to biodiversity studies and the utility of species‐distribution models to conservation decision‐making. Our results also demonstrate, however, that these models must be applied critically and cautiously.
Conservation Biology – Wiley
Published: Dec 1, 2003
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