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Stocking of eggs is a common strategy to support declining or reintroduce extirpated salmonid populations. Data on how juveniles disperse from stocking points is crucial to be able to design efficient stocking programs. Detailed information of dispersal is limited for many salmonids, for example, brown trout. In this study, dispersal distance was measured at the end of the first growing season in a low gradient (0.7%) stream in Sweden where the trout population had been depleted. Eggs from 17 separate sets of parents were stocked as eyed eggs in March. During the following fall fry were sampled throughout the stream. The majority of the fry dispersed downstream and remained within a distance of 200 m from the stocking point with no difference between sizes of fry and the presence of a competing cohort or not. There was no dissimilarity in dispersal distances across offspring originating from different parents indicating absence of genetic influence. Our results suggest that, in streams similar to our study site, stocking points should be separated by approximately 330 m in order to avoid overlap in habitat use of fry from different stocking points and that the presence of competing cohorts, fry size and within population variability in dispersal can be neglected. [ABSTRACT FROM AUTHOR]

Knowledge of relatedness between pairs of individuals plays an important role in many research areas including evolutionary biology, quantitative genetics, and conservation. Pairwise relatedness estimation methods based on genetic data from highly variable molecular markers are now used extensively as a substitute for pedigrees. Although the sampling variance of the estimators has been intensively studied for the most common simple genetic relationships, such as unrelated, half- and full-sib, or parent--offspring, little attention has been paid to the average performance of the estimators, by which we mean the performance across all pairs of individuals in a sample. Here we apply two measures to quantify the average performance: first, misclassification rates between pairs of genetic relationships and, second, the proportion of variance explained in the pairwise relatedness estimates by the true population relatedness composition (i. e., the frequencies of different relationships in the population). Using simulated data derived from exceptionally good quality marker and pedigree data from five long-term projects of natural populations, we demonstrate that the average performance depends mainly on the population relatedness composition and may be improved by the marker data quality only within the limits of the population relatedness composition. Our five examples of vertebrate breeding systems suggest that due to the remarkably low variance in relatedness across the population, marker-based estimates may often have low power to address research questions of interest.

Abstract Determining population sizes can be difficult, but is essential for conservation. By counting distinct microsatellite genotypes, DNA from noninvasive samples (hair, faeces) allows estimation of population size. Problems arise because genotypes from noninvasive samples are error-prone, but genotyping errors can be reduced by multiple polymerase chain reaction (PCR). For faecal genotypes from wolves in Yellowstone National Park, error rates varied substantially among samples, often above the ‘worst-case threshold’ suggested by simulation. Consequently, a substantial proportion of multilocus genotypes held one or more errors, despite multiple PCR. These genotyping errors created several genotypes per individual and caused overestimation (up to 5.5-fold) of population size. We propose a ‘matching approach’ to eliminate this overestimation bias. [ABSTRACT FROM AUTHOR]