A unified model of species abundance, ...
Document type :
Article dans une revue scientifique
DOI :
Title :
A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities
Author(s) :
Overcast, Isaac [Auteur]
City College of New York [CUNY] [CCNY]
Ruffley, Megan [Auteur]
University of Idaho [Moscow, USA]
Rosindell, James [Auteur]
Imperial College London
Harmon, Luke [Auteur]
University of Idaho [Moscow, USA]
Borges, Paulo [Auteur]
Universidade dos Açores
Emerson, Brent [Auteur]
Instituto de Productos Naturales y Agrobiologia = Institute of Natural Products and Agrobiology [IPNA]
Etienne, Rampal [Auteur]
University of Groningen [Groningen]
Gillespie, Rosemary [Auteur]
University of California [Berkeley] [UC Berkeley]
Krehenwinkel, Henrik [Auteur]
Trier University
Mahler, D. Luke [Auteur]
University of Toronto
Massol, Francois [Auteur]
Évolution, Écologie et Paléontologie (Evo-Eco-Paleo) - UMR 8198 [Evo-Eco-Paléo (EEP)]
Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 [CIIL]
Parent, Christine [Auteur]
University of Idaho [Moscow, USA]
Patiño, Jairo [Auteur]
Instituto de Productos Naturales y Agrobiologia = Institute of Natural Products and Agrobiology [IPNA]
Universidad de La Laguna [Tenerife - SP] [ULL]
Peter, Ben [Auteur]
Max Planck Institute for Evolutionary Anthropology [Leipzig]
Week, Bob [Auteur]
University of Idaho [Moscow, USA]
Wagner, Catherine [Auteur]
University of Wyoming [UW]
Hickerson, Michael [Auteur]
American Museum of Natural History [AMNH]
City College of New York [CUNY] [CCNY]
Rominger, Andrew [Auteur]
The University of New Mexico [Albuquerque]
City College of New York [CUNY] [CCNY]
Ruffley, Megan [Auteur]
University of Idaho [Moscow, USA]
Rosindell, James [Auteur]
Imperial College London
Harmon, Luke [Auteur]
University of Idaho [Moscow, USA]
Borges, Paulo [Auteur]
Universidade dos Açores
Emerson, Brent [Auteur]
Instituto de Productos Naturales y Agrobiologia = Institute of Natural Products and Agrobiology [IPNA]
Etienne, Rampal [Auteur]
University of Groningen [Groningen]
Gillespie, Rosemary [Auteur]
University of California [Berkeley] [UC Berkeley]
Krehenwinkel, Henrik [Auteur]
Trier University
Mahler, D. Luke [Auteur]
University of Toronto
Massol, Francois [Auteur]

Évolution, Écologie et Paléontologie (Evo-Eco-Paleo) - UMR 8198 [Evo-Eco-Paléo (EEP)]
Centre d’Infection et d’Immunité de Lille - INSERM U 1019 - UMR 9017 - UMR 8204 [CIIL]
Parent, Christine [Auteur]
University of Idaho [Moscow, USA]
Patiño, Jairo [Auteur]
Instituto de Productos Naturales y Agrobiologia = Institute of Natural Products and Agrobiology [IPNA]
Universidad de La Laguna [Tenerife - SP] [ULL]
Peter, Ben [Auteur]
Max Planck Institute for Evolutionary Anthropology [Leipzig]
Week, Bob [Auteur]
University of Idaho [Moscow, USA]
Wagner, Catherine [Auteur]
University of Wyoming [UW]
Hickerson, Michael [Auteur]
American Museum of Natural History [AMNH]
City College of New York [CUNY] [CCNY]
Rominger, Andrew [Auteur]
The University of New Mexico [Albuquerque]
Journal title :
Molecular ecology resources
Publisher :
Wiley/Blackwell
Publication date :
2021-11
ISSN :
1755-098X
HAL domain(s) :
Sciences du Vivant [q-bio]/Ecologie, Environnement
Sciences du Vivant [q-bio]/Biodiversité/Evolution [q-bio.PE]
Sciences du Vivant [q-bio]/Biodiversité/Evolution [q-bio.PE]
English abstract : [en]
Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns ...
Show more >Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce Massive Eco-evolutionary Synthesis Simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: i) species richness and abundances; ii) population genetic diversities; and iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community-scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multi-dimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.Show less >
Show more >Biodiversity accumulates hierarchically by means of ecological and evolutionary processes and feedbacks. Within ecological communities drift, dispersal, speciation, and selection operate simultaneously to shape patterns of biodiversity. Reconciling the relative importance of these is hindered by current models and inference methods, which tend to focus on a subset of processes and their resulting predictions. Here we introduce Massive Eco-evolutionary Synthesis Simulations (MESS), a unified mechanistic model of community assembly, rooted in classic island biogeography theory, which makes temporally explicit joint predictions across three biodiversity data axes: i) species richness and abundances; ii) population genetic diversities; and iii) trait variation in a phylogenetic context. Using simulations we demonstrate that each data axis captures information at different timescales, and that integrating these axes enables discriminating among previously unidentifiable community assembly models. MESS is unique in generating predictions of community-scale genetic diversity, and in characterizing joint patterns of genetic diversity, abundance, and trait values. MESS unlocks the full potential for investigation of biodiversity processes using multi-dimensional community data including a genetic component, such as might be produced by contemporary eDNA or metabarcoding studies. We combine MESS with supervised machine learning to fit the parameters of the model to real data and infer processes underlying how biodiversity accumulates, using communities of tropical trees, arthropods, and gastropods as case studies that span a range of data availability scenarios, and spatial and taxonomic scales.Show less >
Language :
Anglais
Peer reviewed article :
Oui
Audience :
Internationale
Popular science :
Non
Source :
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