Migration load in plants: role of pollen and seed dispersal in heterogeneous landscapes

Abstract

Evolution of local adaptation depends critically on the level of gene flow, which, in plants, can be due to either pollen or seed dispersal. Using analytical predictions and individual‐centred simulations, we investigate the specific influence of seed and pollen dispersal on local adaptation in plant populations growing in patchy heterogeneous landscapes. We study the evolution of a polygenic trait subject to stabilizing selection within populations, but divergent selection between populations. Deviations from linkage equilibrium and Hardy–Weinberg equilibrium make different contributions to genotypic variance depending on the dispersal mode. Local genotypic variance, differentiation between populations and genetic load vary with the rate of gene flow but are similar for seed and pollen dispersal, unless the landscape is very heterogeneous. In this case, genetic load is higher in the case of pollen dispersal, which appears to be due to differences in the distribution of genotypic values before selection.

Evolution of Quantitative Traits under a Migration-Selection Balance: When Does Skew Matter?

“…Our expression improves previous derivations (e.g., Hendry et al 2001;Lopez et al 2008) by incorporating the skew (third moment) of that distribution. We then use individual-based simulations to explicitly link the amount of genetic skew in the trait under divergent selection with the details of its genetic architecture.…”

“…This expression is unclosed: it depends on the levels of variance and skew maintained in the population, which are themselves variables of the model and depend on population parameters, such as the strength of selection and the proportion of migrants at each generation, but also on the genetic architecture of the trait. Still, this derivation provides the analytical confirmation that neglecting the skewness of distributions can lead to underestimation of predictions of population differentiation when selection is spatially heterogeneous (Lopez et al 2008;Yeaman and Guillaume 2009). Our analytical predictions match results from individual-based simulations, quantitatively improving previous predictions made with the assumption of Gaussian distributions (Hendry et al 2001;Yeaman and Guillaume 2009).…”

“…Quantitative-genetic models can be used to address this question when the traits controlling adaptation are continuous. Even in the case of subdivided populations under divergent selection (so-called migration-selection models), it is common to use the simplifying assumption that the local distributions of genotypic and phenotypic values are Gaussian (Hendry et al 2001;Ronce and Kirkpatrick 2001;Lopez et al 2008;Tufto 2010), and formulas derived in this context have been used in empirical studies (Saint-Laurent et al 2003;Moore et al 2007). Under divergent selection, however, the trait difference between local and immigrant individuals is susceptible to generating asymmetries (skew) in the local distributions of traits, thus violating the Gaussian model assumption.…”

Estimating gametic introgression rates in a risk assessment context: a case study with Scots pine relicts

“…The possibility of obtaining uniparental gametic immigration measures on a landscape scale is relevant to many scientific and practical problems, such as evolutionary investigations about the consequences of sex-biased dispersal among populations (Hu and Ennos, 1999;Lopez et al, 2008) or conservation studies evaluating the relative exposure of natural plant populations to seed and pollen from exotic or transgenic plantations. The percentage of times that the lower confidence limit was too high (LLTH) and the upper limit too low (ULTL) were assessed based on 10 000 independent simulations of the immigration process, assuming different sample sizes (n) and immigration rates (m).…”

Decoupling of differentiation between traits and their underlying genes in response to divergent selection

“…Here, we address their transient dynamics over time and consider different genetic architectures of the trait undergoing selection. Interest in the speed of adaptive differentiation in heterogeneous landscapes has increased recently (Kawecki, 2008;Lopez et al, 2008;Bjorklund et al, 2009). Evolutionary responses are often inferred from the divergence or differentiation of adaptive traits observed in a set of populations undergoing divergent selection (Hendry et al, 2001;Crispo, 2008;Rasanen and Hendry, 2008) or from the molecular divergence of genes of adaptive relevance (Kapralov and Filatov, 2006;Nosil et al, 2009).…”