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Estimates of abundance and survivorship provide quantifiable measures to monitor populations and to define and understand their conservation status. This study investigated changes in abundance and survival rates of fin whales (Balaenoptera physalus) in the northern Gulf of St. Lawrence in the context of anthropogenic pressures and changing environmental conditions. A long‐term data set, consisting of 35 years of photo‐identification surveys and comprising more than 5,000 identifications of 507 individuals, formed the basis of this mark–recapture study. Based on model selection using corrected Akaike Information Criterion, the most parsimonious Cormack–Jolly–Seber model included a linear temporal trend in noncalf apparent survival rates with a sharp decline in the last 5 years of the study and a median survival rate of 0.946 (95% confidence interval (CI) 0.910–0.967). To account for capture heterogeneity due to divergent patterns of site fidelity, agglomerative hierarchical cluster analysis was employed to categorize individuals based on their annual and survey site fidelity indices. However, the negative trend in survivorship remained and was corroborated by a significant decline in the estimated super‐population size from 335 (95% CI 321–348) individuals in 2004–2010 to 291 (95% CI 270–312) individuals in 2010–2016. Concurrently, a negative trend was estimated in recruitment to the population, supported by a sharp decrease in the number of observed calves. Ship strikes and changes in prey availability are potential drivers of the observed decline in fin whale abundance. The combination of clustering methods with mark–recapture represents a flexible way to investigate the effects of site fidelity on demographic variables and is broadly applicable to other individual‐based studies.

The appeal of genetic inference methods to assess population genetic structure and guide management efforts is grounded in the correlation between the genetic similarity and gene flow among populations. Effects of such gene flow are typically genomewide; however, some loci may appear as outliers, displaying above or below average genetic divergence relative to the genomewide level. Above average population, genetic divergence may be due to divergent selection as a result of local adaptation. Consequently, substantial efforts have been directed toward such outlying loci in order to identify traits subject to local adaptation. Here, we report the results of an investigation into the molecular basis of the substantial degree of genetic divergence previously reported at allozyme loci among North Atlantic fin whale (Balaenoptera physalus) populations. We sequenced the exons encoding for the two most divergent allozyme loci (MDH-1 and MPI) and failed to detect any nonsynonymous substitutions. Following extensive error checking and analysis of additional bioinformatic and morphological data, we hypothesize that the observed allozyme polymorphisms may reflect phenotypic plasticity at the cellular level, perhaps as a response to nutritional stress. While such plasticity is intriguing in itself, and of fundamental evolutionary interest, our key finding is that the observed allozyme variation does not appear to be a result of genetic drift, migration, or selection on the MDH-1 and MPI exons themselves, stressing the importance of interpreting allozyme data with caution. As for North Atlantic fin whale population structure, our findings support the low levels of differentiation found in previous analyses of DNA nucleotide loci.