Jane Elith of the University of Melbourne and Catherine Graham of SUNY Stony Brook led the team that compared 16 modeling methods for predicting distributions of 226 plant and animal species from six world regions. They used species-occurrence records from museums, herbaria, and incidental surveys, coupled with environmental data. In general, they found that recently developed modeling methods outperformed more traditional, widely used methods, especially for noisy species data. "You can use pretty pathetic data and make decent predictions," says Graham.
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