| Summary: | Anthropogenic activities are threatening biodiversity worldwide, with impacts on every biome on Earth. A better understanding of how species will respond to different magnitudes and rates of anthropogenic-induced climatic change and other global change drivers is therefore needed to predict extinction risk and avert future species loss. In this PhD dissertation, I combine contemporary occurrence records and genetic sequences, paleo-archives, and process-explicit models to improve our understanding of biodiversity change and extinction risk, and to test whether inferences from the past can provide more informed predictions of future climate change impacts. In Chapter II, I analysed thousands of mitochondrial DNA sequences across ~1000 bird species to identify whether a relationship exists between conservation status and intra-specific genetic diversity. Results show that threatened birds have lower levels of genetic diversity compared to non-threatened ones, indicating that current assessment criteria already indirectly prioritize the conservation of species with low genetic diversity. Nevertheless, a small proportion of non-threatened species carries low genetic diversity, making them more vulnerable to future environmental changes than their conservation status indicates. In Chapter III and Chapter IV, I used hundreds of thousands of models, that explicitly simulate demographic and dispersal processes responding to different degrees of habitat change and human hunting pressures, to reconstruct the distributions of the muskox and the reindeer over the last 21,000 years. These models, validated using inferences of past demographic change from fossils and ancient DNA, were able to determine the ecological processes that favoured the survival of the two species until present day and to disentangle the roles of climate and humans in driving their range and population dynamics. Results show that high dispersal ability, small Allee effect and broader climatic requirements are important processes for correctly ...
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