Summary1. We present a new R package, diveRsity, for the calculation of various diversity statistics, including common diversity partitioning statistics (h, G ST ) and population differentiation statistics (D Jost , G 0 ST , v 2 test for population heterogeneity), among others. The package calculates these estimators along with their respective bootstrapped confidence intervals for loci, sample population pairwise and global levels. Various plotting tools are also provided for a visual evaluation of estimated values, allowing users to critically assess the validity and significance of statistical tests from a biological perspective.2. diveRsity has a set of unique features, which facilitate the use of an informed framework for assessing the validity of the use of traditional F-statistics for the inference of demography, with reference to specific marker types, particularly focusing on highly polymorphic microsatellite loci. However, the package can be readily used for other co-dominant marker types (e.g. allozymes, SNPs).3. Detailed examples of usage and descriptions of package capabilities are provided. The examples demonstrate useful strategies for the exploration of data and interpretation of results generated by diveRsity. Additional online resources for the package are also described, including a GUI web app version intended for those with more limited experience using R for statistical analysis.

The high level of escapes from Atlantic salmon farms, up to two million fishes per year in the North Atlantic, has raised concern about the potential impact on wild populations. We report on a two-generation experiment examining the estimated lifetime successes, relative to wild natives, of farm, F(1) and F(2) hybrids and BC(1) backcrosses to wild and farm salmon. Offspring of farm and "hybrids" (i.e. all F(1), F(2) and BC(1) groups) showed reduced survival compared with wild salmon but grew faster as juveniles and displaced wild parr, which as a group were significantly smaller. Where suitable habitat for these emigrant parr is absent, this competition would result in reduced wild smolt production. In the experimental conditions, where emigrants survived downstream, the relative estimated lifetime success ranged from 2% (farm) to 89% (BC(1) wild) of that of wild salmon, indicating additive genetic variation for survival. Wild salmon primarily returned to fresh water after one sea winter (1SW) but farm and 'hybrids' produced proportionately more 2SW salmon. However, lower overall survival means that this would result in reduced recruitment despite increased 2SW fecundity. We thus demonstrate that interaction of farm with wild salmon results in lowered fitness, with repeated escapes causing cumulative fitness depression and potentially an extinction vortex in vulnerable populations.

Understanding the population structure and patterns of gene flow within species is of fundamental importance to the study of evolution. In the fields of population and evolutionary genetics, measures of genetic differentiation are commonly used to gather this information. One potential caveat is that these measures assume gene flow to be symmetric. However, asymmetric gene flow is common in nature, especially in systems driven by physical processes such as wind or water currents. As information about levels of asymmetric gene flow among populations is essential for the correct interpretation of the distribution of contemporary genetic diversity within species, this should not be overlooked. To obtain information on asymmetric migration patterns from genetic data, complex models based on maximum‐likelihood or Bayesian approaches generally need to be employed, often at great computational cost. Here, a new simpler and more efficient approach for understanding gene flow patterns is presented. This approach allows the estimation of directional components of genetic divergence between pairs of populations at low computational effort, using any of the classical or modern measures of genetic differentiation. These directional measures of genetic differentiation can further be used to calculate directional relative migration and to detect asymmetries in gene flow patterns. This can be done in a user‐friendly web application called divMigrate‐online introduced in this study. Using simulated data sets with known gene flow regimes, we demonstrate that the method is capable of resolving complex migration patterns under a range of study designs.

Reintroduction of captive-bred animals is a key approach in conservation attempts for many endangered species, however, post-release survival is often low. Rearing conditions may be unlike those encountered upon release and the animals may not have had experiences necessary for survival in the wild. Animals may also habituate in captivity to stimuli that may pose a danger after release and/or there may be selection for behavioural traits, in particular reduced fearfulness, that may not be suited for the wild. Here, variation in boldness was assessed in captive-bred swift fox (Vulpes velox) and tested for influence on survival after release. Radio-tracked individuals that died in the 6 months following release were those judged previously as bold.In the presence of novel stimuli in captivity, they had left their dens more quickly, approached more closely to the stimuli and shown more activities indicating low fear than did those that survived. These individuals were less suited for release. Future selection of release-candidates on the basis of behavioural variation should enhance the success of reintroduction programmes.

Brown trout Salmo trutta is endemic to Europe, western Asia and north‐western Africa; it is a prominent member of freshwater and coastal marine fish faunas. The species shows two resident (river‐resident, lake‐resident) and three main facultative migratory life histories (downstream–upstream within a river system, fluvial–adfluvial potamodromous; to and from a lake, lacustrine–adfluvial (inlet) or allacustrine (outlet) potamodromous; to and from the sea, anadromous). River‐residency v. migration is a balance between enhanced feeding and thus growth advantages of migration to a particular habitat v. the costs of potentially greater mortality and energy expenditure. Fluvial–adfluvial migration usually has less feeding improvement, but less mortality risk, than lacustrine–adfluvial or allacustrine and anadromous, but the latter vary among catchments as to which is favoured. Indirect evidence suggests that around 50% of the variability in S. trutta migration v. residency, among individuals within a population, is due to genetic variance. This dichotomous decision can best be explained by the threshold‐trait model of quantitative genetics. Thus, an individual's physiological condition (e.g., energy status) as regulated by environmental factors, genes and non‐genetic parental effects, acts as the cue. The magnitude of this cue relative to a genetically predetermined individual threshold, governs whether it will migrate or sexually mature as a river‐resident. This decision threshold occurs early in life and, if the choice is to migrate, a second threshold probably follows determining the age and timing of migration. Migration destination (mainstem river, lake, or sea) also appears to be genetically programmed. Decisions to migrate and ultimate destination result in a number of subsequent consequential changes such as parr–smolt transformation, sexual maturity and return migration. Strong associations with one or a few genes have been found for most aspects of the migratory syndrome and indirect evidence supports genetic involvement in all parts. Thus, migratory and resident life histories potentially evolve as a result of natural and anthropogenic environmental changes, which alter relative survival and reproduction. Knowledge of genetic determinants of the various components of migration in S. trutta lags substantially behind that of Oncorhynchus mykiss and other salmonines. Identification of genetic markers linked to migration components and especially to the migration–residency decision, is a prerequisite for facilitating detailed empirical studies. In order to predict effectively, through modelling, the effects of environmental changes, quantification of the relative fitness of different migratory traits and of their heritabilities, across a range of environmental conditions, is also urgently required in the face of the increasing pace of such changes.