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

Abstract

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.

Global determinants of insect mitochondrial genetic diversity

“…To more directly test such hypotheses, process-explicit models will be required to uncover causal processes that drive the structure of genetic diversity as well as discriminate among the processes that do not 120, 121 . These models will be especially valuable in revealing the underlying mechanisms of unexpected correlations found here and in other macrogenetic studies 122 .…”

pastclim 1.2: an R package to easily access and use paleoclimatic reconstructions

“…Climatic changes have also played a (sometimes major) role in the macroevolution of several species, including humans (Saupe et al 2014, Will et al 2021, Fordham et al 2022, Timmermann et al 2022, Troyer et al 2022). Integrating the climate of the past into evolutionary biology studies can help gaining a better understanding of its impact in macroevolutionary dynamics such as adaptation, speciation and extinction (Hagen 2022).…”

Paleoenvironments shaped the exchange of terrestrial vertebrates across Wallace’s Line

“…This is particularly true in the Indo-Australian archipelago, where biological ivasions are contributing to some of the highest rates of native species extinction on the planet ( 45 ). An emerging view of global biodiversity patterns is that they are largely the outcome of historical changes in plate tectonics shuffling lineages around the planet, in concert with major fluctuations in precipitation and temperature shaping dispersal, speciation, and extinction dynamics through environmental niches ( 46 , 47 ). A mechanistic modeling approach enables us to move beyond “lines” in biogeography and instead consider the processes that shape global variation in biodiversity patterns.…”