Planning for Dynamic Connectivity: Operationalizing Robust Decision-Making and Prioritization Across Landscapes Experiencing Climate and Land-Use Change

Preserving landscape connectivity is one of the most frequently recommended strategies to address the synergistic threats of climate change, habitat fragmentation, and intensifying disturbances. Although assessments to develop plans for linked and connected landscapes in response to climate and land-use change have been increasingly employed in the last decade, efforts to operationalize and implement these plans have been limited. Here, we present a framework using existing, available biological data to design an implementable, comprehensive multispecies connectivity plan. This framework uses a scenario-based approach to consider how ecosystems, habitats, and species may need to adapt to future conditions with an ensemble of connectivity models. We use the south coast ecoregion of California as an example to evaluate and prioritize linkages by combining linked metapopulation models and key landscape features (e.g., conservation planning status and implementation feasibility) to identify and prioritize a multispecies linkage network. Our analyses identified approximately 30,000 km² of land, roughly one-fifth of our study area, where actions to preserve or enhance connectivity may support climate adaptation, nearly half of which is already conserved. By developing and implementing a dynamic connectivity assessment with an eye towards projected changes, our analysis demonstrates how dynamic connectivity can be integrated into feasible regional conservation and management plans that account for demographic as well as landscape change. We observed overlap across multiple models, reinforcing the importance of areas that appeared across methods. We also identified unique areas important for connectivity captured by our complementary models. By integrating multiple approaches, the resultant linkage network is robust, building on the strengths of a variety of methods to identify model consensus and reduce uncertainty. By linking quantitative connectivity metrics with prioritized areas for conservation, our approach supports transparent and robust decision-making for landscape planning, despite uncertainties of climate and land-use change.