Strategies for 21st-century environmental management and conservation under global change require a strong understanding of the biological mechanisms that mediate responses to climate- and human-driven change to successfully mitigate range contractions, extinctions, and the degradation of ecosystem services. Biodiversity responses to past rapid warming events can be followed in situ and over extended periods, using cross-disciplinary approaches that provide cost-effective and scalable information for species’ conservation and the maintenance of resilient ecosystems in many bioregions. Beyond the intrinsic knowledge gain such integrative research will increasingly provide the context, tools, and relevant case studies to assist in mitigating climate-driven biodiversity losses in the 21st century and beyond.

Knowledge of global patterns of biodiversity, ranging from intraspecific genetic diversity (GD) to taxonomic and phylogenetic diversity, is essential for identifying and conserving the processes that shape the distribution of life. Yet, global patterns of GD and its drivers remain elusive. Here we assess existing biodiversity theories to explain and predict the global distribution of GD in terrestrial mammal assemblages. We find a strong positive covariation between GD and interspecific diversity, with evolutionary time, reflected in phylogenetic diversity, being the best predictor of GD. Moreover, we reveal the negative effect of past rapid climate change and the positive effect of inter-annual precipitation variability in shaping GD. Our models, explaining almost half of the variation in GD globally, uncover the importance of deep evolutionary history and past climate stability in accumulating and maintaining intraspecific diversity, and constitute a crucial step towards reducing the Wallacean shortfall for an important dimension of biodiversity.

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In the face of increasing cumulative effects from human and natural disturbances, sustaining coral reefs will require a deeper understanding of the drivers of coral resilience in space and time. Here we develop a high‐resolution, spatially explicit model of coral dynamics on Australia's Great Barrier Reef (GBR). Our model accounts for biological, ecological and environmental processes, as well as spatial variation in water quality and the cumulative effects of coral diseases, bleaching, outbreaks of crown‐of‐thorns starfish (Acanthaster cf. solaris), and tropical cyclones. Our projections reconstruct coral cover trajectories between 1996 and 2017 over a total reef area of 14,780 km2, predicting a mean annual coral loss of −0.67%/year mostly due to the impact of cyclones, followed by starfish outbreaks and coral bleaching. Coral growth rate was the highest for outer shelf coral communities characterized by digitate and tabulate Acropora spp. and exposed to low seasonal variations in salinity and sea surface temperature, and the lowest for inner‐shelf communities exposed to reduced water quality. We show that coral resilience (defined as the net effect of resistance and recovery following disturbance) was negatively related to the frequency of river plume conditions, and to reef accessibility to a lesser extent. Surprisingly, reef resilience was substantially lower within no‐take marine protected areas, however this difference was mostly driven by the effect of water quality. Our model provides a new validated, spatially explicit platform for identifying the reefs that face the greatest risk of biodiversity loss, and those that have the highest chances to persist under increasing disturbance regimes.

Criticism has been levelled at climate-change-induced forecasts of species range shifts that do not account explicitly for complex population dynamics. The relative importance of such dynamics under climate change is, however, undetermined because direct tests comparing the performance of demographic models vs. simpler ecological niche models are still lacking owing to difficulties in evaluating forecasts using real-world data. We provide the first comparison of the skill of coupled ecological-niche-population models and ecological niche models in predicting documented shifts in the ranges of 20 British breeding bird species across a 40-year period. Forecasts from models calibrated with data centred on 1970 were evaluated using data centred on 2010. We found that more complex coupled ecological-niche-population models (that account for dispersal and metapopulation dynamics) tend to have higher predictive accuracy in forecasting species range shifts than structurally simpler models that only account for variation in climate. However, these better forecasts are achieved only if ecological responses to climate change are simulated without static snapshots of historic land use, taken at a single point in time. In contrast, including both static land use and dynamic climate variables in simpler ecological niche models improve forecasts of observed range shifts. Despite being less skilful at predicting range changes at the grid-cell level, ecological niche models do as well, or better, than more complex models at predicting the magnitude of relative change in range size. Therefore, ecological niche models can provide a reasonable first approximation of the magnitude of species' potential range shifts, especially when more detailed data are lacking on dispersal dynamics, demographic processes underpinning population performance, and change in land cover.