ArticlePLoS biology2021
gen3sis: A general engine for eco-evolutionary simulations of the processes that shape Earth's biodiversity.
Article in PLoS biology, 2021. The graph could read no effect estimate from its abstract, so it casts no vote on the map. Cited by 31 papers.
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Who cites it
31 citing papers in PubMed.
- Calibration, Sensitivity and Uncertainty Analysis of Complex Ecological Models-A Review.Ecology letters · 2026Review
- Enhancing island biogeography: improving identification of potential species pools via environmental filtering.Scientific reports · 2026Article
- Loss of vegetation functions during the Paleocene-Eocene Thermal Maximum.Nature communications · 2025Article
- Evolutionary age correlates with range size across plants and animals.Nature communications · 2025Article
- Landscape-explicit phylogeography illuminates the ecographic radiation of early archosauromorph reptiles.Nature ecology & evolution · 2025Article
- Cenozoic geoclimatic changes drove the evolutionary dynamics of floristic endemism on the Qinghai-Tibet Plateau.Proceedings of the National Academy of Sciences of the United States of America · 2025Article
- Life-history adaptation under climate warming magnifies the agricultural footprint of a cosmopolitan insect pest.Nature communications · 2025Article
- Deep time evolution of the Latitudinal Diversity Gradient: Insights from mechanistic models.PloS one · 2025Article
- Simulating macroevolutionary trends and open-ended evolution with a novel mechanistic multi-level approach.PloS one · 2025Article
- The macro-eco-evolutionary interplay between dispersal, competition and landscape structure in generating biodiversity.Philosophical transactions of the Royal Society of London. Series B, Biological sciences · 2024Article
- Deep Learning and Likelihood Approaches for Viral Phylogeography Converge on the Same Answers Whether the Inference Model Is Right or Wrong.Systematic biology · 2024Article
- DeepDive: estimating global biodiversity patterns through time using deep learning.Nature communications · 2024Article
- Ecological niche conservatism spurs diversification in response to climate change.Nature ecology & evolution · 2024Article
- Speed of thermal adaptation of terrestrial vegetation alters Earth's long-term climate.Science advances · 2024Article
- Eco-evolutionary priority and the assembly of the New Zealand flora.Journal of the Royal Society of New Zealand · 2024Review
- Diversity across organisational scale emerges through dispersal ability and speciation dynamics in tropical fish.BMC biology · 2023Article
- Article
- Freshwater fish diversity in the western Amazon basin shaped by Andean uplift since the Late Cretaceous.Nature ecology & evolution · 2023Article
- Thermodynamics of continental deformation.Scientific reports · 2023Article
- Global determinants of insect mitochondrial genetic diversity.Nature communications · 2023Article
Corrections and comments
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Authors and funding
8 authors.
Funding
No grant is acknowledged in the PubMed record.
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.
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