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      Coexistence in diverse communities with higher-order interactions

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          Significance

          Some species interactions, termed higher-order interactions, can only emerge when there are many species in an ecological community. These interactions are likely frequent in nature, although their role in shaping the coexistence of species is poorly explored. Here we incorporate higher-order interactions into a mathematical model of the dynamics of diverse communities and show that many of the rules governing the effects of pairwise interactions on coexistence extend to the higher-order case. Our theory requires only a small number of parameters to predict the number of species coexisting at equilibrium. As a result, empiricists can use our framework to generate expectations for how higher-order interactions influence species coexistence in nature.

          Abstract

          A central assumption in most ecological models is that the interactions in a community operate only between pairs of species. However, two species may interactively affect the growth of a focal species. Although interactions among three or more species, called higher-order interactions, have the potential to modify our theoretical understanding of coexistence, ecologists lack clear expectations for how these interactions shape community structure. Here we analytically predict and numerically confirm how the variability and strength of higher-order interactions affect species coexistence. We found that as higher-order interaction strengths became more variable across species, fewer species could coexist, echoing the behavior of pairwise models. If interspecific higher-order interactions became too harmful relative to self-regulation, coexistence in diverse communities was destabilized, but coexistence was also lost when these interactions were too weak and mutualistic higher-order effects became prevalent. This behavior depended on the functional form of the interactions as the destabilizing effects of the mutualistic higher-order interactions were ameliorated when their strength saturated with species’ densities. Last, we showed that more species-rich communities structured by higher-order interactions lose species more readily than their species-poor counterparts, generalizing classic results for community stability. Our work provides needed theoretical expectations for how higher-order interactions impact species coexistence in diverse communities.

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          Mechanisms of Maintenance of Species Diversity

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            Ecological Niches

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              The architecture of mutualistic networks minimizes competition and increases biodiversity.

              The main theories of biodiversity either neglect species interactions or assume that species interact randomly with each other. However, recent empirical work has revealed that ecological networks are highly structured, and the lack of a theory that takes into account the structure of interactions precludes further assessment of the implications of such network patterns for biodiversity. Here we use a combination of analytical and empirical approaches to quantify the influence of network architecture on the number of coexisting species. As a case study we consider mutualistic networks between plants and their animal pollinators or seed dispersers. These networks have been found to be highly nested, with the more specialist species interacting only with proper subsets of the species that interact with the more generalist. We show that nestedness reduces effective interspecific competition and enhances the number of coexisting species. Furthermore, we show that a nested network will naturally emerge if new species are more likely to enter the community where they have minimal competitive load. Nested networks seem to occur in many biological and social contexts, suggesting that our results are relevant in a wide range of fields.
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                Author and article information

                Journal
                Proc Natl Acad Sci U S A
                Proc Natl Acad Sci U S A
                pnas
                PNAS
                Proceedings of the National Academy of Sciences of the United States of America
                National Academy of Sciences
                0027-8424
                1091-6490
                17 October 2022
                25 October 2022
                17 April 2023
                : 119
                : 43
                : e2205063119
                Affiliations
                [1] aLewis-Sigler Institute for Integrative Genomics, Princeton University , Princeton, NJ 08544;
                [2] bDepartment of Ecology and Evolutionary Biology, Princeton University , Princeton, NJ 08544
                Author notes
                1To whom correspondence may be addressed. Email: tgibbs@ 123456princeton.edu .

                Edited by Marten Scheffer, Wageningen University & Research, Wageningen, The Netherlands; received March 23, 2022; accepted September 14, 2022

                Author contributions: T.G. and J.M.L. designed research; T.G. performed research; T.G. and J.M.L. analyzed data; and T.G., S.A.L., and J.M.L. wrote the paper.

                Author information
                https://orcid.org/0000-0002-1515-8420
                https://orcid.org/0000-0002-8216-5639
                https://orcid.org/0000-0003-2857-7904
                Article
                202205063
                10.1073/pnas.2205063119
                9618036
                36252042
                f799c9fb-53a6-4908-8aec-c474d49b23af
                Copyright © 2022 the Author(s). Published by PNAS.

                This article is distributed under Creative Commons Attribution-NonCommercial-NoDerivatives License 4.0 (CC BY-NC-ND).

                History
                : 14 September 2022
                Page count
                Pages: 9
                Funding
                Funded by: NSF | EHR | Division of Graduate Education (DGE) 100000082
                Award ID: DGE-2039656
                Award Recipient : Theo Gibbs
                Funded by: NSF | BIO | Division of Environmental Biology (DEB) 100000155
                Award ID: DEB-2022213
                Award Recipient : Theo Gibbs Award Recipient : Jonathan M Levine
                Funded by: NSF | BIO | Division of Environmental Biology (DEB) 100000155
                Award ID: DEB-2022213
                Award Recipient : Theo Gibbs Award Recipient : Jonathan M Levine
                Funded by: NSF | MPS | Division of Mathematical Sciences (DMS) 100000121
                Award ID: DMS-1951358
                Award Recipient : Simon Asher Levin
                Categories
                414
                Biological Sciences
                Ecology

                coexistence,species interactions,community assembly,competition

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