A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities.
community ecology
community genetic diversity
community phylogenetics
comparative phylogeography
population genetics
Journal
Molecular ecology resources
ISSN: 1755-0998
Titre abrégé: Mol Ecol Resour
Pays: England
ID NLM: 101465604
Informations de publication
Date de publication:
Nov 2021
Nov 2021
Historique:
revised:
01
09
2021
received:
15
09
2020
accepted:
07
09
2021
pubmed:
28
9
2021
medline:
9
11
2021
entrez:
27
9
2021
Statut:
ppublish
Résumé
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 ecoevolutionary 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 multidimensional 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.
Identifiants
pubmed: 34569715
doi: 10.1111/1755-0998.13514
pmc: PMC9297962
doi:
Types de publication
Journal Article
Langues
eng
Sous-ensembles de citation
IM
Pagination
2782-2800Subventions
Organisme : Deutsche Forschungsgemeinschaft
ID : FZT 118
Organisme : Fundação de Amparo à Pesquisa do Estado de São Paulo
ID : 2013/50297-0
Organisme : National Science Foundation
ID : DBI 1927319
Organisme : National Science Foundation
ID : DEB 1745562
Organisme : National Science Foundation
ID : DEB-1253710
Organisme : Natural Environment Research Council
ID : NE/I021179
Organisme : Natural Environment Research Council
ID : NE/L011611/1
Organisme : National Aeronautics and Space Administration
ID : DOB 1343578
Informations de copyright
© 2021 The Authors. Molecular Ecology Resources published by John Wiley & Sons Ltd.
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