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      An expanded modern coexistence theory for empirical applications

      1 , 2 , 3 , 4
      Ecology Letters
      Wiley

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          Abstract

          Understanding long-term coexistence of numerous competing species is a longstanding challenge in ecology. Progress requires determining which processes and species differences are most important for coexistence when multiple processes operate and species differ in many ways. Modern coexistence theory (MCT), formalised by Chesson, holds out the promise of doing that, but empirical applications remain scarce. We argue that MCT's mathematical complexity and subtlety have obscured the simplicity and power of its underlying ideas and hindered applications. We present a general computational approach that extends our previous solution for the storage effect to all of standard MCT's spatial and temporal coexistence mechanisms, and also process-defined mechanisms amenable to direct study such as resource partitioning, indirect competition, and life history trade-offs. The main components are a method to partition population growth rates into contributions from different mechanisms and their interactions, and numerical calculations in which some mechanisms are removed and others retained. We illustrate how our approach handles features that have not been analysed in the standard framework through several case studies: competing diatom species under fluctuating temperature, plant-soil feedbacks in grasslands, facilitation in a beach grass community, and niche differences with independent effects on recruitment, survival and growth in sagebrush steppe.

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          Most cited references31

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          The Paradox of the Plankton

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            Pathogens and insect herbivores drive rainforest plant diversity and composition.

            Tropical forests are important reservoirs of biodiversity, but the processes that maintain this diversity remain poorly understood. The Janzen-Connell hypothesis suggests that specialized natural enemies such as insect herbivores and fungal pathogens maintain high diversity by elevating mortality when plant species occur at high density (negative density dependence; NDD). NDD has been detected widely in tropical forests, but the prediction that NDD caused by insects and pathogens has a community-wide role in maintaining tropical plant diversity remains untested. We show experimentally that changes in plant diversity and species composition are caused by fungal pathogens and insect herbivores. Effective plant species richness increased across the seed-to-seedling transition, corresponding to large changes in species composition. Treating seeds and young seedlings with fungicides significantly reduced the diversity of the seedling assemblage, consistent with the Janzen-Connell hypothesis. Although suppressing insect herbivores using insecticides did not alter species diversity, it greatly increased seedling recruitment and caused a marked shift in seedling species composition. Overall, seedling recruitment was significantly reduced at high conspecific seed densities and this NDD was greatest for the species that were most abundant as seeds. Suppressing fungi reduced the negative effects of density on recruitment, confirming that the diversity-enhancing effect of fungi is mediated by NDD. Our study provides an overall test of the Janzen-Connell hypothesis and demonstrates the crucial role that insects and pathogens have both in structuring tropical plant communities and in maintaining their remarkable diversity.
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              General theory of competitive coexistence in spatially-varying environments.

              P Chesson (2000)
              A general model of competitive and apparent competitive interactions in a spatially-variable environment is developed and analyzed to extend findings on coexistence in a temporally-variable environment to the spatial case and to elucidate new principles. In particular, coexistence mechanisms are divided into variation-dependent and variation-independent mechanisms with variation-dependent mechanisms including spatial generalizations of relative nonlinearity and the storage effect. Although directly analogous to the corresponding temporal mechanisms, these spatial mechanisms involve different life history traits which suggest that the spatial storage effect should arise more commonly than the temporal storage effect and spatial relative nonlinearity should arise less commonly than temporal relative nonlinearity. Additional mechanisms occur in the spatial case due to spatial covariance between the finite rate of increase of a local population and its local abundance, which has no clear temporal analogue. A limited analysis of these additional mechanisms shows that they have similar properties to the storage effect and relative nonlinearity and potentially may be considered as enlargements of the earlier mechanisms. The rate of increase of a species perturbed to low density is used to quantify coexistence. A general quadratic approximation, which is exact in some important cases, divides this rate of increase into contributions from the various mechanisms above and admits no other mechanisms, suggesting that opportunities for coexistence in a spatially-variable environment are fully characterized by these mechanisms within this general model. Three spatially-implicit models are analyzed as illustrations of the general findings and of techniques using small variance approximations. The contributions to coexistence of the various mechanisms are expressed in terms of simple interpretable formulae. These spatially-implicit models include a model of an annual plant community, a spatial multispecies version of the lottery model, and a multispecies model of an insect community competing for spatially-patchy and ephemeral food.
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                Author and article information

                Journal
                Ecology Letters
                Ecol Lett
                Wiley
                1461023X
                October 11 2018
                Affiliations
                [1 ]Department of Ecology and Evolutionary Biology; Cornell University; Ithaca NY USA
                [2 ]Department of Biology; Case Western Reserve University; Cleveland OH USA
                [3 ]Department of Wildland Resources and the Ecology Center; Utah State University; Logan UT USA
                [4 ]Department of Biological Statistics and Computational Biology; Cornell University; Ithaca NY USA
                Article
                10.1111/ele.13159
                30311392
                497d47d8-558f-44d4-b121-6347bca15900
                © 2018

                http://doi.wiley.com/10.1002/tdm_license_1.1

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