Climate change is raising challenging questions for systematic conservation planning. Are methods of planning based on the current spatial patterns of biodiversity effective given long-term climate change trends? In response to this concern, some conservation scientists argue that conservation planning should focus on protecting the abiotic diversity in the landscape, which drives patterns of biological diversity, rather than focusing on the distribution of focal species or community types, which shift in response to climate change. Climate diversity is one important abiotic driver of biodiversity patterns, as different climates host different biological communities and genetic pools. We theorize that networks of protected areas that capture the full range of climatic diversity in a region will be more resilient to climate change compared to networks that do not. In this study we use historical and future climate-hydrology projections from a high resolution Basin Characterization Model to explore the utility of directly targeting climatic diversity in planning. Using the spatial planning tool, Marxan, we designed conservation networks to capture the diversity of climate types, at the regional and sub-regional scale, and compared them to networks designed to capture the diversity of vegetation types. By focusing on Conservation Lands Network of the San Francisco Bay Area as a real-world case study, we compare how well the different networks capture climate space under current and future climates. We found that networks targeted on vegetation types capture a similar distribution of climate space at the regional scale to networks targeted on climate types. However, at sub-regional scales, networks targeted on climate types capture a significantly greater range of climate space, and show greater climate stability (defined as the degree of overlap in historic and future climate conditions for a specified region) over time in response to climatic change. Overall, climate stability was more influenced by GCM and emission scenario, and topography, than by network scenario. Topographically heterogeneous areas consistently show greater climate stability than homogenous areas. The analysis suggests that utilizing high-resolution climate and hydrological data in conservation planning is a useful technique for improving the likely resilience of biodiversity to climate change.
