Coupling eco‐evolutionary mechanisms with deep‐time environmental dynamics to understand biodiversity patterns

Ecography(2022)

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摘要
Pioneer naturalists such as Whewell, Lyell, Humboldt, Darwin and Wallace acknowledged the interactions between ecological and evolutionary forces, as well as the roles of continental movement, mountain formation and climate variations, in shaping biodiversity patterns. Recent developments in computer modelling and paleo-environmental reconstruction have made it possible for scientists to study in silico how biodiversity emerges from eco-evolutionary and environmental dynamic processes and their interactions. Simulating emergent biodiversity enables the experimentation of multiple interconnected hypotheses in a largely fragmented scientific landscape, with the final objective of successfully approximating natural mechanisms (i.e. hypothetical spatio-temporally unrestricted generalizations that hold across multiple empirical biodiversity patterns). This new interdisciplinary approach opens unprecedented scientific pathways, facilitating the communication and contemplation of causal implications of complex eco-evolutionary and environmental interactions. In this review I provide a comprehensive overview of the available population-based spatially explicit mechanistic eco-evolutionary models (MEEMs) that rely on paleo-environmental reconstructions, critically discussing their relevance and limitations for our understanding of biodiversity. To achieve this, I first introduce diverse biodiversity models and contextualize MEEMs. Second, I define MEEMs and synthesize the major insights from studies using MEEMs combined with deep-time environmental dynamics (> 0.1 Ma). Lastly, I discuss the challenges and perspectives of solving long-standing biodiversity enigmas by coupling eco-evolutionary mechanisms with deep-time environmental dynamics. Studies show that linking dynamic environments and eco-evolutionary processes is necessary to reproduce multiple large-scale biodiversity patterns simultaneously. Mechanisms related to adaptations (e.g. niche evolution), dispersal abilities and other eco-evolutionary interactions (e.g. those resulting in speciation or extinction events) show universal importance, although their signatures across spatial and temporal scales remain largely unknown. Investigations with MEEMS spanning multiple levels of complexity in space and time foster interdisciplinary cooperation across the natural sciences and show promise for solving some of the enigmas in Earth's biodiversity.
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关键词
biodiversity modelling, complex system, eco-evolutionary modelling, mechanistic model
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