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Reconciling empirical interactions and species coexistence
Authors:Daniel S. Maynard,J. Timothy Wootton,Carlos A. Serv  n,Stefano Allesina
Affiliation:Daniel S. Maynard,J. Timothy Wootton,Carlos A. Serván,Stefano Allesina
Abstract:Coexistence in ecological communities is governed largely by the nature and intensity of species interactions. Countless studies have proposed methods to infer these interactions from empirical data, yet models parameterised using such data often fail to recover observed coexistence patterns. Here, we propose a method to reconcile empirical parameterisations of community dynamics with species‐abundance data, ensuring that the predicted equilibrium is consistent with the observed abundance distribution. To illustrate the approach, we explore two case studies: an experimental freshwater algal community and a long‐term time series of displacement in an intertidal community. We demonstrate how our method helps recover observed coexistence patterns, capture the core dynamics of the system, and, in the latter case, predict the impacts of experimental extinctions. Collectively, these results demonstrate an intuitive approach for reconciling observed and empirical data, improving our ability to explore the links between species interactions and coexistence in natural systems.
Keywords:coexistence  dynamical modelling  Lotka–  Volterra equation  quadratic programming  replicator equation  species abundance  species interactions
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