Estimation of effective population sizes (N(e)) and temporal gene flow (N(e)m, m) has many implications for understanding population structure in evolutionary and conservation biology. However, comparative studies that gauge the relative performance of N(e), N(e)m or m methods are few. Using temporal genetic data from two salmonid fish population systems with disparate population structure, we (i) evaluated the congruence in estimates and precision of long- and short-term N(e), N(e)m and m from six methods; (ii) explored the effects of metapopulation structure on N(e) estimation in one system with spatiotemporally linked subpopulations, using three approaches; and (iii) determined to what degree interpopulation gene flow was asymmetric over time. We found that long-term N(e) estimates exceeded short-term N(e) within populations by 2-10 times; the two were correlated in the system with temporally stable structure (Atlantic salmon, Salmo salar) but not in the highly dynamic system (brown trout, Salmo trutta). Four temporal methods yielded short-term N(e) estimates within populations that were strongly correlated, and these were higher but more variable within salmon populations than within trout populations. In trout populations, however, these short-term N(e) estimates were always lower when assuming gene flow than when assuming no gene flow. Linkage disequilibrium data generally yielded short-term N(e) estimates of the same magnitude as temporal methods in both systems, but the two were uncorrelated. Correlations between long- and short-term geneflow estimates were inconsistent between methods, and their relative size varied up to eightfold within systems. While asymmetries in gene flow were common in both systems (58-63% of population-pair comparisons), they were only temporally stable in direction within certain salmon population pairs, suggesting that gene flow between particular populations is often intermittent and/or variable. Exploratory metapopulation N(e) analyses in trout demonstrated both the importance of spatial scale in estimating N(e) and the role of gene flow in maintaining genetic variability within subpopulations. Collectively, our results illustrate the utility of comparatively applying N(e), N(e)m and m to (i) tease apart processes implicated in population structure, (ii) assess the degree of continuity in patterns of connectivity between population pairs and (iii) gauge the relative performance of different approaches, such as the influence of population subdivision and gene flow on N(e) estimation. They further reiterate the importance of temporal sampling replication in population genetics, the value of interpreting N(e)or m in light of species biology, and the need to address long-standing assumptions of current N(e), N(e)m or m models more explicitly in future research.

The genetic structure of brown trout (Salmo trutta) populations inhabiting rivers on the island of Bornholm in the Baltic Sea was studied on a spatial and temporal scale. Low water levels in the rivers during the summer period are assumed to have a significant impact on the persistence of local populations, possibly resulting in a metapopulation structure. Extinctions may, however, also be buffered by a remnant strategy, whereby juveniles escape to river outlets during periods of drought. We compared polymorphism at seven microsatellite DNA loci in contemporary and past samples collected from 1944 to 1997. A principal component analysis, a hierarchical gene diversity analysis and assignment tests showed that the genetic composition of populations was not temporally stable, and that temporal genetic differentiation was much stronger than spatial differentiation. Genetic variability was high and stable over time. Effective population sizes (Ne) and migration rate (m) were estimated using a maximum-likelihood-based implementation of the temporal method. Ne estimates were low (ranging from 8.3 to 22.9) and estimates of m were high (between 0.23 and 0.99), in contrast to other Danish trout populations inhabiting larger and more environmentally stable rivers (Ne between 39.2 and 289.9 and m between 0.01 and 0.09). Thus, the observed spatio-temporal patterns of genetic differentiation can be explained by drift in small persisting populations, where levels of genetic variation are maintained by strong gene flow. However, observations of rivers devoid of trout suggested that population turnover also takes place. We suggest that Bornholm trout represent a metapopulation where the genetic structure primarily reflects strong drift and gene flow, combined with occasional extinction-recolonization events.