Reproductive success and its determinants are difficult to infer for wild populations of species with no parental care where behavioural observations are difficult or impossible. In this study, we characterized the breeding system and provide estimates of individual reproductive success under natural conditions for an exhaustively sampled stream-resident brown trout (Salmo trutta) population. We inferred parentage using a full probability Bayesian model that combines genetic (microsatellite) with phenotypic data. By augmenting the potential parents file with inferred parental genotypes from sib-ship analysis in cases where large families had unsampled parents, we could make more precise inference on variance of family size. We observed both polygamous and monogamous matings and large reproductive skew for both sexes, particularly in males. Correspondingly, we found evidence for sexual selection on body size for both sexes. We show that the mating system of brown trout has the potential to be very flexible and we conjecture that environmental uncertainty could be driving the evolution and perhaps select for the maintenance of plasticity of the mating system in this species.

The effective population size (N e ) is notoriously difficult to accurately estimate in wild populations as it is influenced by a number of parameters that are difficult to delineate in natural systems. The different methods that are used to estimate N e are affected variously by different processes at the population level, such as the life-history characteristics of the organism, gene flow, and population substructure, as well as by the frequency patterns of genetic markers used and the sampling design. Here, we compare N e estimates obtained by different genetic methods and from demographic data and elucidate how the estimates are affected by various factors in an exhaustively sampled and comprehensively described natural brown trout (Salmo trutta) system. In general, the methods yielded rather congruent estimates, and we ascribe that to the adequate genotyping and exhaustive sampling. Effects of violating the assumptions of the different methods were nevertheless apparent. In accordance with theoretical studies, skewed allele frequencies would underestimate temporal allele frequency changes and thereby upwardly bias N e if not accounted for. Overlapping generations and iteroparity would also upwardly bias N e when applied to temporal samples taken over short time spans. Gene flow from a genetically not very dissimilar source population decreases temporal allele frequency changes and thereby acts to increase estimates of N e . Our study reiterates the importance of adequate sampling, quantification of life-history parameters and gene flow, and incorporating these data into the N e estimation.T HE effective population size (N e ) is an essential concept in evolutionary and conservation biology as it determines the strength of stochastic evolutionary processes relative to deterministic forces (Crow and Kimura 1970). In the absence of gene flow, the rate of loss of genetic diversity via genetic drift is greater in populations with small N e . The effective population size is, however, notoriously difficult to accurately estimate in wild populations as it is influenced by a number of parameters that are difficult to characterize in natural systems. A number of different methods have been developed for estimating N e , and these are affected variously by different processes at the population level such as immigration, fluctuations in population size, population substructure, and life-history characteristics. When possible, it is therefore important to compare N e estimates obtained using different methods and elucidate how different processes affect the various methods for N e estimation (Fraser et al. 2007).Two main types of approaches have been used to estimate N e : genetic and demographic. Genetic methods attempt to infer the magnitude of the effective population size by characterizing the genetic consequences of limited population size, whereas demographic methods depend upon measurement of demographic parameters that have theoretically been shown to influence N e. The most common genetic approach is ...

A number of demographic factors, many of which related to human-driven encroachments, are predicted to decrease the effective population size (Ne) relative to the census population size (N), but these have been little investigated. Yet, it is necessary to know which factors most strongly impact Ne, and how to mitigate these effects through sound management actions. In this study, we use parentage analysis of a stream-living brown trout (Salmo trutta) population to quantify the effect of between-individual variance in reproductive success on the effective number of breeders (Nb) relative to the census number of breeders (Ni). Comprehensive estimates of the Nb/N ratio were reduced to 0.16–0.28, almost entirely due to larger than binomial variance in family size. We used computer simulations, based on empirical estimates of age-specific survival and fecundity rates, to assess the effect of repeat spawning (iteroparity) on Ne and found that the variance in lifetime reproductive success was substantially higher for repeat spawners. Random family-specific survival, on the other hand, acts to buffer these effects. We discuss the implications of these findings for the management of small populations, where maintaining high and stable levels of Ne is crucial to extenuate inbreeding and protect genetic variability.

Many animals move among habitats, and even small-scale dispersal of individuals between habitat patches may have strong implications for population dynamics and structure. Here, we use long-term mark–recapture data combined with extensive genotyping and parentage assignment to investigate the importance of small-scale location change of resident brown trout ( Salmo trutta ) in a small stream (1500 m). During the first summer, juvenile fish dispersed downstream (mean displacement 200 m), with smaller juveniles dispersing longer distances. Downstream movement was also predominant during the first winter, but older fish moved little. This limited dispersal resulted in a significant isolation-by-distance structure for ages 1 and 2, but not for older age groups or for the mature fish. Individual pairwise relatedness coefficients decreased with waterway distance for mature fish during the 2002 and 2003 spawning seasons, but only weakly. Overall, between-site genetic differentiation was stronger for the younger age classes, and the signal decayed with age, indicating that the genetic structure observed in the stream is mainly driven by spatial aggregation of close relatives.

Adaptability depends on the presence of additive genetic variance for important traits. Yet few estimates of additive genetic variance and heritability are available for wild populations, particularly so for fishes. Here, we estimate heritability of length‐at‐age for wild‐living brown trout (Salmo trutta), based on long‐term mark‐recapture data and pedigree reconstruction based on large‐scale genotyping at 15 microsatellite loci. We also tested for the presence of maternal and paternal effects using a Bayesian version of the Animal model. Heritability varied between 0.16 and 0.31, with reasonable narrow confidence bands, and the total phenotypic variance increased with age. When introducing dam as an additional random effect (accounting for c. 7% of total phenotypic variance), the level of additive genetic variance and heritability decreased (0.12–0.21). Parental size (both for sires and for dams) positively influenced length‐at‐age for juvenile trout – either through direct parental effects or through genotype‐environment correlations. Length‐at‐age is a complex trait reflecting the effects of a number of physiological, behavioural and ecological processes. Our data show that fitness‐related traits such as length‐at‐age can retain high levels of additive genetic variance even when total phenotypic variance is high.