In the next century, global climate change is predicted to have large influences on species' distributions. Much of the research in this area has focused on predicting the areas where conditions will be suitable for the species in future, and thus the potential distribution of the species. However, it is equally important to predict the relative abilities of species to migrate into new suitable areas as conditions shift, while accounting for dynamic processes, such as dispersal, maturation, mortality, and reproduction, as well as landscape characteristics, such as level of habitat fragmentation and connectivity. In this study, we developed a spatially explicit individual-based model that addresses these factors. As a motivating case study, we based aspects of the model on southwest Australia, a global biodiversity hotspot, but stress that the results obtained are generalizable beyond this region. Using the model, we enhanced current understanding of climate change impacts by investigating how and to what extent the functional traits of plant species affect their ability to move with climate change across landscapes with various levels of fragmentation. We also tested the efficacy of strategic restoration, such as planting corridors to increase connectivity among fragments. We found that even if the landscape is fully intact, only an average of 34.2% of all simulated functional groups had a good chance of successfully tracking climate change. However, our study highlights the power of strategic restoration as a tool for increasing species persistence. Corridors linking fragments increased species persistence rates by up to 24%. The lowest persistence rates were found for trees, a functional group with high dispersal but also long generation times. Our results indicate that for trees intervention techniques, such as assisted migration might be required to prevent species losses.
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