Identifying areas of optimal multispecies conservation value by accounting for incompatibilities between species

Conservation planning is designed to optimize conservation actions when only limited resources are available for managing habitats and mitigating threats, and excels at selecting reserve networks that protect the largest number of species. However, the spatial optimization of the protection of multiple species can be complicated by interactions among those species and incompatibilities in their habitat needs. The challenge is to identify an optimal solution when two species with similar habitat needs cannot co-occur. We propose here a new approach to find the optimal conservation planning solution in cases of species incompatibilities, and demonstrate this solution for a 144km2 area (a 160,000-cell grid) in northern Wisconsin. Specifically, our study objectives were to simultaneously (a) identify the smallest area needed to meet minimum habitat requirements for every species considered, (b) maximize the compactness of that area, and (c) avoid any overlap between species with incompatible habitat requirements. We found an optimized solution based on potential habitat models for 19 bird species using a novel application of mixed integer linear programming, with a clustering approach suited for large cell arrays. Under this solution, 9.9% of the study plot was sufficient to meet the minimum requirements for every species considered, maximize the compactness of that area, and avoid any overlap between species with incompatible habitat requirements. Our results are useful to assist managers in providing well-connected, sufficient habitat to at-risk species while minimizing costs and land use conflicts.