title: A stochastic dispersal-limited trait-based model of community dynamics.
abstract: I present a model of stochastic community dynamics in which death occurs randomly in the community, propagules disperse randomly from a regional pool, and recruitment of new individuals of a species is proportional to the species local abundance multiplied by its local competitive ability. The competitive ability of a species is assumed to be determined by a function of one trait of the species, and I call this function the environmental filtering function. I show that information on local species abundances in a network of plots, together with trait data for each species, enables the inference of both the immigration rate and the environmental filtering function in each plot. I further study how the diversity patterns produced by this model deviate from the neutral predictions, and how this deviation depends on the characteristics of the environmental filtering function. I show that this inference framework is more powerful at detecting trait-based environmental filtering than existing statistical approaches based on trait distributions, and discuss how the predictions of this model could be used to assess environmental heterogeneity in a plot, to detect functionally meaningful trade-offs among species traits, and to test the assumption that there exists a simple relationship between species traits and local competitive ability.
authors.affiliation: Laboratoire Evolution et Diversité Biologique, CNRS, Université Paul Sabatier, Bâtiment 4R3, 31062 Toulouse cedex 4, France. franck.jabot@m4x.org
authors.forename: Franck
authors.initials: F
authors.lastname: Jabot
mesh_terms: D000465:Algorithms; D025041:Animal Migration; D000818:Animals; D001499:Bayes Theorem; D044822:Biodiversity; D003198:Computer Simulation; D017753:Ecosystem; D004777:Environment; D016013:Likelihood Functions; D008954:Models, Biological; D015233:Models, Statistical; D008962:Models, Theoretical; D011156:Population Density; D011157:Population Dynamics; D013045:Species Specificity; D013269:Stochastic Processes