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Given the importance of dispersal distance in range expansion (Simmons and Thomas 2004; Phillips et al. 2008) or spatial populations dynamics (Leibold et al. 2004; Cousens et al. 2008), it is surprising that the evolution of dispersal kernels has only received marginal attention (Ronce 2007).
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In the case of climate and health studies, specifically, such studies typically use projected outputs from global circulation models to generate modeled, spatially distributed exposure concentrations that are linked with known or modeled spatial population distributions (Huang et al. 2011).
Dispersal is a fundamental component of many spatial population models.
The fixation of mutant alleles has been studied with models assuming various spatial population structures.
We mapped the spatial population genetic structure for 13 datasets across the PLB.
Spatial population models typically simulate birth, death, and migration on an input map that describes habitat.
The relationship between local population density and habitat area is an important factor in spatial population ecology.
Here we demonstrate how spatial population expansion, a widespread natural phenomenon [6 11], promotes the evolution of cooperation.
In contrast, past deforestation seems to have no significant effect on the current spatial population structure of A. cepistipes.
Linking individual behavior to spatial population processes, may clarify the complex link between species distribution and landscape properties.
This paper describes an approach for conducting spatial uncertainty analysis of spatial population models, and illustrates the ecological consequences of spatial uncertainty for landscapes with different properties.
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