gen3sis: A general engine for eco-evolutionary simulations of the processes that shape Earth’s biodiversity

Abstract

Understanding the origins of biodiversity has been an aspiration since the days of early naturalists. The immense complexity of ecological, evolutionary, and spatial processes, however, has made this goal elusive to this day. Computer models serve progress in many scientific fields, but in the fields of macroecology and macroevolution, eco-evolutionary models are comparatively less developed. We present a general, spatially explicit, eco-evolutionary engine with a modular implementation that enables the modeling of multiple macroecological and macroevolutionary processes and feedbacks across representative spatiotemporally dynamic landscapes. Modeled processes can include species’ abiotic tolerances, biotic interactions, dispersal, speciation, and evolution of ecological traits. Commonly observed biodiversity patterns, such as α, β, and γ diversity, species ranges, ecological traits, and phylogenies, emerge as simulations proceed. As an illustration, we examine alternative hypotheses expected to have shaped the latitudinal diversity gradient (LDG) during the Earth’s Cenozoic era. Our exploratory simulations simultaneously produce multiple realistic biodiversity patterns, such as the LDG, current species richness, and range size frequencies, as well as phylogenetic metrics. The model engine is open source and available as an R package, enabling future exploration of various landscapes and biological processes, while outputs can be linked with a variety of empirical biodiversity patterns. This work represents a key toward a numeric, interdisciplinary, and mechanistic understanding of the physical and biological processes that shape Earth’s biodiversity.

Earth history events shaped the evolution of uneven biodiversity across tropical moist forests

“…To investigate how paleoenvironmental dynamics have shaped present-day patterns of biodiversity across tropical moist forests, we implemented a spatially explicit process-based simulation model of diversification ( 34 ) using global paleoenvironmental reconstructions of temperature and aridity dynamics from the Mid-Cretaceous ( 41 ). We ran the simulation model 500 times, starting with a single ancestral species distributed throughout the equatorial tropics at 110 Ma.…”

“…We also applied a subset of parsimonious and generalized initialization and dispersal scenarios to taxa with a diverse range of biogeographic and evolutionary histories. We consider an important next step to be investigations of how adding or subtracting different ecological and evolutionary model components changes biodiversity patterns ( 34 ). In addition, the parameters of simulation models could be tailored to specific clades based on biogeographic reconstructions from molecular and fossil data to understand how processes such as long-distance dispersal have shaped present-day phylogenetic diversity.…”

“…We implemented the spatial model of diversification using the general engine for ecoevolutionary simulations, gen3sis ( 34 ). Each simulation followed the diversification of a clade from a single ancestral species distributed broadly throughout nonarid sites within of the equator 110 Ma ( Movie S1 ).…”

“…Instead, by combining paleoenvironmental reconstructions with spatially explicit models of ecoevolutionary processes, simulation models offer a unique but largely underused resource (but see, for example, refs. 31 – 34 ) to directly explore the evolutionary mechanisms behind the origins of biodiversity patterns in silico ( 30 , 34 ). In this study, we explored the origins of the PDD in three steps.…”

Numerical modeling of subduction: State of the art and future directions

“…successfully reproduced the observed longitudinal gradient in species richness, the empirical pattern of beta-diversity, and also provided inference on diversification rates (Descombes et al, 2018). Hagen et al (2021) presented next-generation biogeographical modeling tool GEN3SIS aimed at simulating eco-evolutionary processes coupled to plate tectonics and long-term climate variations. This tool allows simulation of species ranges, alpha-and beta-diversity patterns, ecological traits as well as phylogenies that can be compared to observations.…”