Emerging strains of watermelon mosaic virus in Southeastern France: model-based estimation of the dates and places of introduction.

Where and when alien organisms are successfully introduced are central questions to elucidate biotic and abiotic conditions favorable to the introduction, establishment and spread of invasive species. We propose a modelling framework to analyze multiple introductions by several invasive genotypes or genetic variants, in competition with a resident population, when observations provide knowledge on the relative proportions of each variant at some dates and places. This framework is based on a mechanistic-statistical model coupling a reaction-diffusion model with a probabilistic observation model. We apply it to a spatio-temporal dataset reporting the relative proportions of five genetic variants of watermelon mosaic virus (WMV, genus Potyvirus, family Potyviridae) in infections of commercial cucurbit fields. Despite the parsimonious nature of the model, it succeeds in fitting the data well and provides an estimation of the dates and places of successful introduction of each emerging variant as well as a reconstruction of the dynamics of each variant since its introduction.

Combining capture-recapture data and pedigree information to assess heritability of demographic parameters in the wild.

Quantitative genetic analyses have been increasingly used to estimate the genetic basis of life-history traits in natural populations. Imperfect detection of individuals is inherent to studies that monitor populations in the wild, yet it is seldom accounted for by quantitative genetic studies, perhaps leading to flawed inference. To facilitate the inclusion of imperfect detection of individuals in such studies, we develop a method to estimate additive genetic variance and assess heritability for binary traits such as survival, using capture-recapture (CR) data. Our approach combines mixed-effects CR models with a threshold model to incorporate discrete data in a standard 'animal model' approach. We employ Markov chain Monte Carlo sampling in a Bayesian framework to estimate model parameters. We illustrate our approach using data from a wild population of blue tits (Cyanistes caeruleus) and present the first estimate of heritability of adult survival in the wild. In agreement with the prediction that selection should deplete additive genetic variance in fitness, we found that survival had low heritability. Because the detection process is incorporated, capture-recapture animal models (CRAM) provide unbiased quantitative genetics analyses of longitudinal data collected in the wild.

When sinks become sources: Adaptive colonization in asexuals.

The establishment of a population into a new empty habitat outside of its initial niche is a phenomenon akin to evolutionary rescue in the presence of immigration. It underlies a wide range of processes, such as biological invasions by alien organisms, host shifts in pathogens, or the emergence of resistance to pesticides or antibiotics from untreated areas. We derive an analytically tractable framework to describe the evolutionary and demographic dynamics of asexual populations in a source-sink system. We analyze the influence of several factors on the establishment success in the sink, and on the time until establishment. To this aim, we use a classic phenotype-fitness landscape (Fisher's geometrical model in n dimensions) where the source and sink habitats have different phenotypic optima. In case of successful establishment, the mean fitness in the sink follows a typical four-phases trajectory. The waiting time to establishment is independent of the immigration rate and has a "U-shaped" dependence on the mutation rate, until some threshold where lethal mutagenesis impedes establishment and the sink population remains so. We use these results to get some insight into possible effects of several management strategies.