Climate change is a global threat to species, and their capacity to adapt could be limited by habitat fragmentation. Many initiatives to restore habitats, increase connectivity and/or ensure ‘functioning ecological networks’ are explicitly or implicitly trying to address this threat. However, existing methods of analysing networks mainly treat the landscape as static, and it is difficult to use these to plan restoration.

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Predictions of coastal wetland loss depend on reliable estimations of sea-level rise (SLR) and biological feedbacks to geomorphology, yet it is difficult to manipulate SLR to generate empirical data of impacts on wetland processes. Typically, data have been generated through small-scale mesocosm experiments, an approach that may not fully capture biological responses to SLR.

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