Detailed linkage and recombination rate maps are necessary to use the full potential of genome sequencing and population genomic analyses. We used a custom collared flycatcher 50 K SNP array to develop a high-density linkage map with 37 262 markers assigned to 34 linkage groups in 33 autosomes and the Z chromosome. The best-order map contained 4215 markers, with a total distance of 3132 cm and a mean genetic distance between markers of 0.12 cm. Facilitated by the array being designed to include markers from most scaffolds, we obtained a second-generation assembly of the flycatcher genome that approaches full chromosome sequences (N50 super-scaffold size 20.2 Mb and with 1.042 Gb (of 1.116 Gb) anchored to and mostly ordered and oriented along chromosomes). We found that flycatcher and zebra finch chromosomes are entirely syntenic but that inversions at mean rates of 1.5–2.0 event (6.6–7.5 Mb) per My have changed the organization within chromosomes, rates high enough for inversions to potentially have been involved with many speciation events during avian evolution. The mean recombination rate was 3.1 cm/Mb and correlated closely with chromosome size, from 2 cm/Mb for chromosomes >100 Mb to >10 cm/Mb for chromosomes <10 Mb. This size dependence seemed entirely due to an obligate recombination event per chromosome; if 50 cm was subtracted from the genetic lengths of chromosomes, the rate per physical unit DNA was constant across chromosomes. Flycatcher recombination rate showed similar variation along chromosomes as chicken but lacked the large interior recombination deserts characteristic of zebra finch chromosomes.

Phenotypic plasticity is an important mechanism via which populations can respond to changing environmental conditions, but we know very little about how natural populations vary with respect to plasticity. Here we use random-regression animal models to understand the multivariate phenotypic and genetic patterns of plasticity variation in two key life-history traits, laying date and clutch size, using data from long-term studies of great tits in The Netherlands (Hoge Veluwe [HV]) and UK (Wytham Woods [WW]).We show that, while population-level responses of laying date and clutch size to temperature were similar in the two populations, between-individual variation in plasticity differed markedly. Both populations showed significant variation in phenotypic plasticity (IxE) for laying date, but IxE was significantly higher in HV than in WW. There were no significant genotype-by-environment interactions (GxE) for laying date, yet differences in GxE were marginally nonsignificant between HV and WW. For clutch size, we only found significant IxE and GxE in WW but no significant difference between populations. From a multivariate perspective, plasticity in laying date was not correlated with plasticity in clutch size in either population. Our results suggest that generalizations about the form and cause of any response to changing environmental conditions across populations may be difficult.

Dispersal is a process of central importance for the ecological and evolutionary dynamics of populations and communities, because of its diverse consequences for gene flow and demography. It is subject to evolutionary change, which begs the question, what is the genetic basis of this potentially complex trait? To address this question, we (i) review the empirical literature on the genetic basis of dispersal, (ii) explore how theoretical investigations of the evolution of dispersal have represented the genetics of dispersal, and (iii) discuss how the genetic basis of dispersal influences theoretical predictions of the evolution of dispersal and potential consequences.Dispersal has a detectable genetic basis in many organisms, from bacteria to plants and animals. Generally, there is evidence for significant genetic variation for dispersal or dispersal‐related phenotypes or evidence for the micro‐evolution of dispersal in natural populations. Dispersal is typically the outcome of several interacting traits, and this complexity is reflected in its genetic architecture: while some genes of moderate to large effect can influence certain aspects of dispersal, dispersal traits are typically polygenic. Correlations among dispersal traits as well as between dispersal traits and other traits under selection are common, and the genetic basis of dispersal can be highly environment‐dependent.By contrast, models have historically considered a highly simplified genetic architecture of dispersal. It is only recently that models have started to consider multiple loci influencing dispersal, as well as non‐additive effects such as dominance and epistasis, showing that the genetic basis of dispersal can influence evolutionary rates and outcomes, especially under non‐equilibrium conditions. For example, the number of loci controlling dispersal can influence projected rates of dispersal evolution during range shifts and corresponding demographic impacts. Incorporating more realism in the genetic architecture of dispersal is thus necessary to enable models to move beyond the purely theoretical towards making more useful predictions of evolutionary and ecological dynamics under current and future environmental conditions. To inform these advances, empirical studies need to answer outstanding questions concerning whether specific genes underlie dispersal variation, the genetic architecture of context‐dependent dispersal phenotypes and behaviours, and correlations among dispersal and other traits.

The authors show that environmental variation may lead to a positive association between the annual strength of selection and expression of genetic variance in a wild bird population, which can speed up microevolution and have important consequences for how fast natural populations adapt to environmental changes.