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Abstract
The selection pressure experienced by organisms often varies across the species range. It is hence crucial to characterise the link between environmental spatial heterogeneity and the adaptive dynamics of species or populations. We address this issue by studying the phenotypic evolution of a spatial metapopulation using an adaptive dynamics approach. The singular strategy is found to be the mean of the optimal phenotypes in each habitat with larger weights for habitats present in large and well connected patches. The presence of spatial clusters of habitats in the metapopulation is found to facilitate specialisation and to increase both the level of adaptation and the evolutionary speed of the population when dispersal is limited. By showing that spatial structures are crucial in determining the specialisation level and the evolutionary speed of a population, our results give insight into the influence of spatial heterogeneity on the niche breadth of species.
Highlights
Long term evolution of populations can lead to local adaptations to environmental conditions: organisms tend to have a higher fitness in their local habitat than organisms originating from other habitats
How does spatial heterogeneity drive the evolution of specialism vs generalism? And how does habitat spatial structure determine the level and speed of adaptation? To address these questions, a flexible metapopulation model allowing for different metapopulation structures is developed
The singular strategy is the barycentre of habitat optima: it corresponds to a generalist phenotype
Summary
Long term evolution of populations can lead to local adaptations to environmental conditions: organisms tend to have a higher fitness in their local habitat than organisms originating from other habitats. Model The model is based on a discrete-time deterministic description of the population dynamics It deals with a metapopulation composed of several phenotypes that develop on a spatially heterogeneous environment consisting of a network of P patches. The evolutionary speed of the resident phenotype trait x in a monomorphic population is defined as the derivative x_ of x on time at a large scale It can be approximated by the canonical equation of adaptive dynamics [44,45], which is based on asymptotics with three nested time scales. The stochasticity that affects the demography of the mutant when it is still rare was taken into account through a parameter t2(x) that quantifies the variability of the offspring distribution of an individual with trait x (Appendix S2) Under these assumptions, the canonical equation of adaptive dynamics was first obtained in the general case. The consistency between the analytical and the simulation approaches is discussed in Appendix S5 and Figure S2
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