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Dispersal and spatial heterogeneity: single species

Overview of attention for article published in Journal of Mathematical Biology, April 2015
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Title
Dispersal and spatial heterogeneity: single species
Published in
Journal of Mathematical Biology, April 2015
DOI 10.1007/s00285-015-0879-y
Pubmed ID
Authors

Donald L. DeAngelis, Wei-Ming Ni, Bo Zhang

Abstract

A recent result for a reaction-diffusion equation is that a population diffusing at any rate in an environment in which resources vary spatially will reach a higher total equilibrium biomass than the population in an environment in which the same total resources are distributed homogeneously. This has so far been proven by Lou for the case in which the reaction term has only one parameter, [Formula: see text], varying with spatial location [Formula: see text], which serves as both the intrinsic growth rate coefficient and carrying capacity of the population. However, this striking result seems rather limited when applies to real populations. In order to make the model more relevant for ecologists, we consider a logistic reaction term, with two parameters, [Formula: see text] for intrinsic growth rate, and [Formula: see text] for carrying capacity. When [Formula: see text] and [Formula: see text] are proportional, the logistic equation takes a particularly simple form, and the earlier result still holds. In this paper we have established the result for the more general case of a positive correlation between [Formula: see text] and [Formula: see text] when dispersal rate is small. We review natural and laboratory systems to which these results are relevant and discuss the implications of the results to population theory and conservation ecology.

Mendeley readers

Mendeley readers

The data shown below were compiled from readership statistics for 23 Mendeley readers of this research output. Click here to see the associated Mendeley record.

Geographical breakdown

Country Count As %
Unknown 23 100%

Demographic breakdown

Readers by professional status Count As %
Researcher 7 30%
Student > Ph. D. Student 5 22%
Other 3 13%
Professor 2 9%
Student > Master 2 9%
Other 2 9%
Unknown 2 9%
Readers by discipline Count As %
Environmental Science 8 35%
Agricultural and Biological Sciences 7 30%
Mathematics 3 13%
Computer Science 1 4%
Medicine and Dentistry 1 4%
Other 0 0%
Unknown 3 13%