Salmonine fishes are commonly subjected to strong, novel selective pressures due to anthropogenic activities and global climate change, often resulting in population extinction. Consequently, there is considerable interest in predicting the long-term evolutionary trajectories of extant populations. Knowledge of the genetic architecture of fitness traits is integral to making these predictions. We reviewed the published, peer-reviewed literature for estimates of heritability and genetic correlation for fitness traits in salmonine fishes with two broad goals in mind: summarization of published data and testing for differences among categorical variables (e.g., species, life history type, experimental conditions). Balanced coverage of variables was lacking and estimates for wild populations and behavioral traits were nearly absent. Distributions of heritability estimates were skewed toward low values and distributions of genetic correlations toward large, positive values, suggesting that significant potential for evolution of traits exists. Furthermore, experimental conditions had a direct effect on h2 estimates, and other variables had more complex effects on h2 and rG estimates, suggesting that available estimates may be insufficient for use in models to predict evolutionary change in wild populations. Given this and other inherent complicating factors, making accurate predictions of the evolutionary trajectories of salmonine fishes will be a difficult task.

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Assignment tests are increasingly applied in ecology and conservation, although empirical comparisons of methods are still rare or are restricted to few of the available approaches. Furthermore, the performance of assignment tests in cases with low population differentiation, violations of Hardy-Weinberg equilibrium and unbalanced sampling designs has not been verified. The release of adult hatchery steelhead to spawn in Forks Creek in 1996 and 1997 provided an opportunity to compare the power of different assignment methods to distinguish their offspring from those of sympatric wild steelhead. We compared standard assignment methods requiring baseline samples (frequency, distance and Bayesian) and clustering approaches with and without baseline information, using six freely available computer programs. Assignments were verified by parentage data obtained for a subset of returning offspring. All methods provided similar assignment success, despite low differentiation between wild and hatchery fish (F(ST) = 0.02). Bayesian approaches with baseline data performed best, whereas the results of clustering methods were variable and depended on the samples included in the analysis and the availability of baseline information. Removal of a locus with null alleles and equalizing sample sizes had little effect on assignments. Our results demonstrate the robustness of most assignment tests to low differentiation and violations of assumptions, as well as their utility for ecological studies that require correct classification of different groups.

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