The Gulf Coastal Plains and Ozarks Landscape Conservation Cooperative (GCPO) is a regional collaboration across agency and ownership boundaries to conserve sustainable landscapes in the face of global change. Planning for sustainable landscapes is hampered by uncertainty in how species will respond to conservation actions amidst impacts from landscape and climate change, especially when those impacts are also uncertain. Conservation is also complicated by the complexities of the planning decisions, including tradeoffs among competing species objectives. To help guide landscape conservation design, we piloted a process that integrated dynamiclandscape metapopulation models (DLMPs) and Structured Decision Making to choose among scenarios for habitat restoration that best meet desired endpoints for focal wildlife species in the GCPO’s Ozark Highlands (OZHI) region under climate change and urbanization. We coordinated with a team of planners from the OZHI throughout the decision process to determine objectives, design alternative scenarios, and use DLMPs to model the consequences of each given concurrent impacts of climate and landscape change. Overall impact of restoration on focal species was positive and presented evidence to support landscape conservation design. Despite the general effectiveness of restoration, species-specific responses to individual scenarios varied in complex ways through interactions with landscape change processes such as urbanization and climate change and the demographic processes affecting each species. Based on averages across focal species, the planning team identified a scenario that targeted full acreage objectives on both private and protected lands, prioritized based on future landscapes as best reducing the average risk across species. Through this pilot project we demonstrated that planning for viable populations across large scales can be achieved under global change. The integration of DLMPs with Structured Decision Making enabled the decision to be objective and transparent, and thus defensible. Therefore, this approach has the potential to overcome the uncertainties and complexities that are inherent in the process of long-term, large-scale conservation planning.
