A unified model of species abundance, genetic diversity, and functional diversity reveals the mechanisms structuring ecological communities

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Overcast, Isaac ^{[1, 2, 3]} ; Ruffley, Megan ^{[4, 5]} ; Rosindell, James ^[6] ; Harmon, Luke ^[4] ; Borges, V, Paulo A. ; Emerson, Brent C. ^[7] ; Etienne, Rampal S. ^[8] ; Gillespie, Rosemary ^[9] ; Krehenwinkel, Henrik ^[10] ; Mahler, D. Luke ^[11] ; Massol, Francois ^{[12, 13, 14]} ; Parent, Christine E. ^{[4, 5]} ; Patino, Jairo ^{[7, 15]} ; Peter, Ben ^[16] ; Week, Bob ^[4] ; Wagner, Catherine ^{[17, 18]} ; Hickerson, Michael J. ^{[19, 2, 3]} ; Rominger, Andrew ^{[20, 21]}

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^[1] Amer Museum Nat Hist, Div Vertebrate Zool, New York, NY 10024 - USA

^[2] CUNY, Biol Dept, Grad Ctr, Marshak Sci Bldg, 160 Convent Ave, New York, NY 10031 - USA

^[3] CUNY City Coll, Biol Dept, New York, NY - USA

^[4] Univ Idaho, Dept Biol Sci, Moscow, ID 83843 - USA

^[5] Univ Idaho, Inst Bioinformat & Evolutionary Studies IBEST, Moscow, ID 83843 - USA

^[6] Imperial Coll London, Dept Life Sci, Ascot, Berks - England

^[7] IPNA CSIC, Inst Nat Prod & Agrobiol, Isl Ecol & Evolut Res Grp, Tenerife, Canary Islands - Spain

^[8] Univ Groningen, Groningen Inst Evolutionary Life Sci, Groningen - Netherlands

^[9] Univ Calif Berkeley, Dept Environm Sci Policy & Management, Berkeley, CA 94720 - USA

^[10] Trier Univ, Dept Biogeog, Trier - Germany

^[11] Univ Toronto, Dept Ecol & Evolutionary Biol, Toronto, ON - Canada

^[12] Inst Pasteur, Ctr Infect & Immun Lille, Lille - France

^[13] Univ Lille, CHU Lille, INSERM, CNRS, Lille - France

^[14] Univ Lille, SPICI Grp, Evoecopaleo, CNRS, Lille - France

^[15] Univ La Laguna, Fac Ciencias, Dept Bot Ecol & Fisiol Vegetal, Plant Conservat & Biogeog Grp, Tenerife, Islas Canarias - Spain

^[16] Max Planck Inst Evolutionary Anthropol, Dept Evolutionary Genet, Grp Genet Divers Space & Time, Leipzig - Germany

^[17] Univ Wyoming, Dept Bot, Laramie, WY 82071 - USA

^[18] Univ Wyoming, Biodivers Inst, Laramie, WY 82071 - USA

^[19] Amer Museum Nat Hist, Div Invertebrate Zool, New York, NY 10024 - USA

^[20] Univ Maine, Sch Biol & Ecol, Orono, ME - USA

^[21] Univ Maine, Maine Ctr Genet Environm, Orono, ME - USA

• Tipo de documento: Artigo Científico
• Fonte: MOLECULAR ECOLOGY RESOURCES; v. 21, n. 8, SI OCT 2021.
• Citações Web of Science: 2

Resumo

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. (AU)

• Processo FAPESP: 13/50297-0 - Dimensions US-BIOTA São Paulo: integrando disciplinas para a predição da biodiversidade da Floresta Atlântica no Brasil
• Beneficiário: Cristina Yumi Miyaki
• Modalidade de apoio: Auxílio à Pesquisa - Programa BIOTA - Temático