Novel approaches to conserving the viability of regional wildlife populations in response to landscape and climate change
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The proactive actions needed to prevent loss of biodiversity from global change have left managers and biologists looking for approaches that can predict how species and populations will respond to this threat and help guide conservation to address it. However, the need to predict how climate change will impact wildlife species has exposed limitations in how well current approaches model important biological processes at scales at which those processes interact with climate. Conservation planning is also hampered by uncertainty in how species will respond to conservation actions amidst impacts from landscape and climate change and complicated by the complexities of the planning decisions, including tradeoffs among competing species objectives. Therefore, we developed approaches to address these issues. We combined recent advances in landscape and population modeling into dynamic-landscape metapopulation models (DLMPs) that predict responses of wildlife populations to threats from landscape and climate change and the conservation actions that address them. We then collaborated with a planning team to pilot a process that integrated DLMPs and Structured Decision Making to overcome the uncertainties and complexities that are inherent in the process of long-term, large-scale conservation planning. Our DLMPs provided a comprehensive approach that captured interactions among climate, landscape, and population processes that allowed us to project complex, species-specific responses to conservation and climate change scenarios for various bird and mammal species. Embedding the models within a structured decision making framework helped to overcome uncertainties and complexities and enabled the team to identify conservation plans. Together this work demonstrated that planning for viable populations across large scales can be achieved under global change.