It may often be necessary to perform genetic analyses of temporal replicates to estimate the significance of spatial variation independently from that of temporal variation in order to ensure the reliability of estimates of a defined population structure. Nevertheless, temporal studies of genetic diversity remain scarce in the literature relative to the plethora of empirical studies of population structure. In vertebrates, a limited number of studies have specifically assessed the temporal stability of population structure for more than one generation. In this study, we performed a microsatellite analysis of DNA obtained from archived scales to compare the population structure among four sympatric landlocked populations of Atlantic salmon (Salmo salar) over a time frame of three to five generations. The same patterns of allele frequency distribution, θ, RST and genetic distance estimates were observed among populations for two time periods, confirming the temporal stability of the population structure. Despite population declines and stocking during this period, no statistically significant changes in intrapopulation genetic diversity were apparent. This study illustrates the feasibility and usefulness of microsatellite analysis of temporal samples, not only to infer changes of intrapopulation genetic diversity, but also to assess the stability of population structure over a time frame of several generations.

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.

Lyme borreliosis is rapidly emerging in Canada, and climate change is likely a key driver of the northern spread of the disease in North America. We used field and modeling approaches to predict the risk of occurrence of Borrelia burgdorferi, the bacteria causing Lyme disease in North America. We combined climatic and landscape variables to model the current and future (2050) potential distribution of the black-legged tick and the white-footed mouse at the northeastern range limit of Lyme disease and estimated a risk index for B. burgdorferi from these distributions. The risk index was mostly constrained by the distribution of the white-footed mouse, driven by winter climatic conditions. The next factor contributing to the risk index was the distribution of the black-legged tick, estimated from the temperature. Landscape variables such as forest habitat and connectivity contributed little to the risk index. We predict a further northern expansion of B. burgdorferi of approximately 250–500 km by 2050 – a rate of 3.5–11 km per year – and identify areas of rapid rise in the risk of occurrence of B. burgdorferi. Our results will improve understanding of the spread of Lyme disease and inform management strategies at the most northern limit of its distribution.

Four tributaries of Lake St‐Jean (Québec, Canada) are used for spawning and juvenile habitat by land‐locked Atlantic salmon. Spawning runs have drastically declined since the mid‐1980s, and consequently, a supportive‐breeding programme was undertaken in 1990. In this study, we analysed seven microsatellite loci and mtDNA, and empirically estimated effective population sizes to test the hypotheses that (i) fish spawning in different tributaries form genetically distinct populations and (ii) the supportive breeding programme causes genetic perturbations on wild populations. Allele frequency distribution, molecular variance and genetic distance estimates all supported the hypothesis of genetic differentiation among salmon from different tributaries. Gene flow among some populations was much more restricted than previously reported for anadromous populations despite the small geographical scale (40 km) involved. Both mtDNA and microsatellites revealed a more pronounced differentiation between populations from two tributaries of a single river compared with their differentiation with a population from a neighbouring river. The comparison of wild and F1‐hatchery fish (produced from breeders originating from the same river) indicated significant changes in allele frequencies and losses of low‐frequency alleles but no reduction in heterozygosity. Estimates of variance and inbreeding population size indicated that susceptibility to genetic drift and inbreeding in one population increased by twofold after only one generation of supplementation.

The white-footed mouse (Peromyscus leucopus) has expanded its northern limit into southern Quebec over the last few decades. P. leucopus is a great disperser and colonizer and is of particular interest because it is considered a primary reservoir for the spirochete bacterium that causes Lyme disease. There is no current information on the gene flow between mouse populations on the mountains and forest fragments found scattered throughout the Monteregie region in southern Quebec, and whether various landscape barriers have an effect on their dispersal. We conducted a population genetics analysis on eleven P. leucopus populations using eleven microsatellite markers and showed that isolation by distance was weak, yet barriers were effective. The agricultural matrix had the least effect on gene flow, whereas highways and main rivers were effective barriers. The abundance of ticks collected from mice varied within the study area. Both ticks and mice were screened for the presence of the spirochete bacterium Borrelia burgdorferi, and we predicted areas of greater risk for Lyme disease. Merging our results with ongoing Lyme disease surveillance programs will help determine the future threat of this disease in Quebec, and will contribute toward disease prevention and management strategies throughout fragmented landscapes in southern Canada.