Using probability of persistence to identify important areas for biodiversity conservation.

Most attempts to identify important areas for biodiversity have sought to represent valued features from what is known of their current distribution, and have treated all included records as equivalent. We develop the idea that a more direct way of planning for conservation success is to consider the probability of persistence for the valued features. Probabilities also provide a consistent basis for integrating the many pattern and process factors affecting conservation success. To apply the approach, we describe a method for seeking networks of conservation areas that maximize probabilities of persistence across species. With data for European trees, this method requires less than half as many areas as an earlier method to represent all species with a probability of at least 0.95 (where possible). Alternatively, for trials choosing any number of areas between one and 50, the method increases the mean probability among species by more than 10%. This improvement benefits the least-widespread species the most and results in greater connectivity among selected areas. The proposed method can accommodate local differences in viability, vulnerability, threats, costs, or other social and political constraints, and is applicable in principle to any surrogate measure for biodiversity value.