Literature DB >> 17542937

Species-area relationships from a spatially explicit neutral model in an infinite landscape.

James Rosindell1, Stephen J Cornell.   

Abstract

We use recently developed technical methods to study species-area relationships from a spatially explicit extension of Hubbell's neutral model on an infinite landscape. Our model includes variable dispersal distances and exhibits qualitatively different behaviour from the cases of nearest-neighbour dispersal and finite periodic landscapes that have previously been studied. We show that different dispersal distances and even different dispersal kernels produce identical species-area curves up to rescaling of the two axes. This scaling property provides a straightforward method for fitting the model to empirical data. The species-area curves display all three phases observed empirically and enable the exponent describing the power law relationship for species-area curves to be identified as the gradient at the central phase. This exponent can take all values between 0 and 1 and is given by a simple function of the speciation rate, independent of all other model variables.

Mesh:

Year:  2007        PMID: 17542937     DOI: 10.1111/j.1461-0248.2007.01050.x

Source DB:  PubMed          Journal:  Ecol Lett        ISSN: 1461-023X            Impact factor:   9.492


  27 in total

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8.  Inferring processes of cultural transmission: the critical role of rare variants in distinguishing neutrality from novelty biases.

Authors:  James P O'Dwyer; Anne Kandler
Journal:  Philos Trans R Soc Lond B Biol Sci       Date:  2017-12-05       Impact factor: 6.237

9.  Ecological equivalence: a realistic assumption for niche theory as a testable alternative to neutral theory.

Authors:  C Patrick Doncaster
Journal:  PLoS One       Date:  2009-10-14       Impact factor: 3.240

10.  Field theory for biogeography: a spatially explicit model for predicting patterns of biodiversity.

Authors:  James P O'Dwyer; Jessica L Green
Journal:  Ecol Lett       Date:  2009-11-10       Impact factor: 9.492

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