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Islands are ideal systems to model temporal changes in biodiversity and reveal the influence of humans on natural communities. Although theory predicts biodiversity on islands tends towards an equilibrium value, the recent extinction of large proportions of island biotas complicates testing this model. The well-preserved subfossil record of Caribbean bats-involving multiple insular radiations-provides a rare opportunity to model diversity dynamics in an insular community. Here, we reconstruct the diversity trajectory in noctilionoid bats of the Greater Antilles by applying a dynamic model of colonization, extinction and speciation to phylogenetic and palaeontological data including all known extinct and extant species. We show species richness asymptotes to an equilibrium value, a demonstration of natural equilibrium dynamics across an entire community. However, recent extinctions-many caused by humans-have wiped out nearly a third of island lineages, dragging diversity away from equilibrium. Using a metric to measure island biodiversity loss, we estimate it will take at least eight million years to regain pre-human diversity levels. Our integrative approach reveals how anthropogenic extinctions can drastically alter the natural trajectory of biological communities, resulting in evolutionary disequilibrium.
Macroecology and biogeography are concerned with understanding biodiversity patterns across space and time. In the past, the two disciplines have addressed this question mainly with correlative approaches, despite frequent calls for more mechanistic explanations. Recent advances in computational power, theoretical understanding, and statistical tools are, however, currently facilitating the development of more system-oriented, mechanistic models. We review these models, identify different model types and theoretical frameworks, compare their processes and properties, and summarize emergent findings. We show that ecological (physiology, demographics, dispersal, biotic interactions) and evolutionary processes, as well as environmental and human-induced drivers, are increasingly modelled mechanistically; and that new insights into biodiversity dynamics emerge from these models. Yet, substantial challenges still lie ahead for this young research field. Among these, we identify scaling, calibration, validation, and balancing complexity as pressing issues. Moreover, particular process combinations are still understudied, and so far models tend to be developed for specific applications. Future work should aim at developing more flexible and modular models that not only allow different ecological theories to be expressed and contrasted, but which are also built for tight integration with all macroecological data sources. Moving the field towards such a ‘systems macroecology’ will test and improve our understanding of the causal pathways through which eco-evolutionary processes create diversity patterns across spatial and temporal scales.