Facilitating adaptation of biodiversity to climate change: a conceptual framework applied to the world’s largest Mediterranean-climate woodland
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The importance of ecological management for reducing the vulnerability of biodiversity to climate change is increasingly recognized, yet frameworks to facilitate a structured approach to climate adaptation management are lacking. We developed a conceptual framework that can guide identification of climate change impacts and adaptive management options in a given region or biome. The framework focuses on potential points of early climate change impact, and organizes these along two main axes. First, it recognizes that climate change can act at a range of ecological scales. Secondly, it emphasizes that outcomes are dependent on two potentially interacting and countervailing forces: (1) changes to environmental parameters and ecological processes brought about by climate change, and (2) responses of component systems as determined by attributes of resistance and resilience. Through this structure, the framework draws together a broad range of ecological concepts, with a novel emphasis on attributes of resistance and resilience that can temper the response of species, ecosystems and landscapes to climate change.We applied the framework to the world’s largest remaining Mediterranean-climate woodland, the ‘Great Western Woodlands’ of south-western Australia. In this relatively intact region, maintaining inherent resistance and resilience by preventing anthropogenic degradation is of highest priority and lowest risk. Limited, higher risk options such as fire management, protection of refugia and translocation of adaptive genes may be justifiable under more extreme change, hence our capacity to predict the extent of change strongly impinges on such management decisions. These conclusions may contrast with similar analyses in degraded landscapes, where natural integrity is already compromised, and existing investment in restoration may facilitate experimentation with higher risk options.
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