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Recent glaciations in northwestern Russia completely covered the Barents Sea during four glacial advances. At the peaks of those glacial advances, there were no nearshore macrofauna. Consequently, colonization by species that now inhabit present-day nearshore waters must have occurred since the habitat became available and hospitable, less than 15 ka. We analyzed microsatellite data from Eleginus nawaga (Gadiformes: Gadidae) collected from Khaipudyrskaya Bay in the southeastern Barents Sea with coalescent-based models to estimate the times and effective population sizes that existed before and after major historical demographic changes. Colonization of E. nawaga, which could only follow establishment of a lower trophic-level food web, provides an indicator of the for that timing. The results of the analyses were consistent with two major demographic events. After an initial founding event from a small number of individuals before ~ 140 ka, the population grew to an effective size of about 2700 individuals. Subsequently, probably as the ice receded after the Last Glacial Maximum, it plateaued at ~ 26,000 about 3000 years ago. Colonization likely came from eastern populations following the Saalian Period, after which there was little nearshore ice to the East of the Kara Sea.

We investigated the population structure of the North Pacific giant octopus, Enteroctopus dofleini (Wulker, 1910) in Alaskan waters. Octopuses were collected from five locations (Dutch Harbor (DH; n ¼ 45), Kachemak Bay (KB; n ¼ 45), Prince William Sound (PWS; n ¼ 18), Glacier Bay (GB; n ¼ 33), and Stephen's Passage (SP; n ¼ 39)). All samples were sequenced at the cytochrome oxidase I (COI) locus of the mitochondrial genome. We identified two major mtDNA haplogroups. Sequence divergence ranged from 0.2 to 2.9%. Haplotypes were not distributed evenly among the sampled populations, producing an enigmatic pattern of population structure. We observed no genetic differen- tiation between DH, KB and GB, or between PWS and SP. FST was extremely high for all other pair- wise comparisons, ranging from 0.871-0.948. We did not observe an isolation-by-distance pattern or a strong clinal gradient in haplotype frequencies, as typically detected in other marine species. Strong genetic drift, serial bottlenecks or sweepstakes events may contribute to the pattern observed. The high level of sequence divergence observed at the COI locus could also suggest cryptic species within the E. dofleini complex, with limited geographical overlap of populations and gene flow. Additional samples were contributed by researchers from British Columbia (n ¼ 1), Seaside, Oregon (n ¼ 4), Neah Bay, Washington (n ¼ 2), Puget Sound, Washington (n ¼ 1), and Kodiak Island, Alaska (n ¼ 2)) While sample sizes were low for these locations, prompting their exclusion from population based analyses, all individuals were of the predominate haplotype found in Alaska.

We examined the population genetics and phylogenetics of Falcipennis canadensis isleibi, a subspecies of Spruce Grouse from the Alexander Archipelago of southeast Alaska, which was recently given subspecies status on the basis of subtle differences in plumage coloration and its limited distribution on several islands. The taxonomic status of F c. isleibi is particularly consequential, both because little is known about its evolutionary, demographic, and conservation status and because island endemics often face high extinction risks. Samples were collected from central Alaska, British Columbia, and Prince of Wales (POW) and Zarembo (ZAM) islands in the Alexander Archipelago and identified to subspecies using established morphological traits. We sequenced the cytochrome-c oxidase I (COI) subunit of the mitochondrial genome (n = 62) and genotyped each individual at six nuclear microsatellite loci (n = 65). Individuals from POW and ZAM shared a unique mitochondrial haplotype not observed in other p...

New opportunities for the export of food grade octopus have furthered interest in developing an actively managed directed fishery for North Pacific giant octopus Enteroctopus dofleini in Alaska state waters. Trawl, long-line, and pot fisheries already harvest over 230 metric tons of octopus as bycatch annually. Managed under the authority of commissioner's permits, applications for directed harvest in most management regions have historically been rejected due to the lack of information on stock status. Our limited knowledge of octopus movement, age structure, and demography hamper the ability to successfully manage this potential fishery. Chief among these obstacles is the lack of abundance estimates on which to base harvest guidelines. While catch-per-unit-effort estimates can be made from bycatch data and used as a proxy of abundance, these estimates can often be inaccurate. Mark-recapture estimates can be more accurate, but can also be expensive and require an effective means of marking individuals. We compared two different tags in order to assess their effectiveness for use on octopuses. We tagged 97 octopuses with modified Peterson discs and visible implant elastomer tags in Kachemak Bay, Alaska. Three tagged octopuses were recaptured, making a statistically sound tag comparison difficult. Our data suggest that visible implant elastomer tags will be a more effective means of marking octopuses.

We show that the algorithm in the program flock (Duchesne & Turgeon 2009) can be interpreted as an estimation procedure based on a model essentially identical to the structure (Pritchard et al. 2000) model with no admixture and without correlated allele frequency priors. Rather than using MCMC, the flock algorithm searches for the maximum a posteriori estimate of this structure model via a simulated annealing algorithm with a rapid cooling schedule (namely, the exponent on the objective function →∞). We demonstrate the similarities between the two programs in a two-step approach. First, to enable rapid batch processing of many simulated data sets, we modified the source code of structure to use the flock algorithm, producing the program flockture. With simulated data, we confirmed that results obtained with flock and flockture are very similar (though flockture is some 200 times faster). Second, we simulated multiple large data sets under varying levels of population differentiation for both microsatellite and SNP genotypes. We analysed them with flockture and structure and assessed each program on its ability to cluster individuals to their correct subpopulation. We show that flockture yields results similar to structure albeit with greater variability from run to run. flockture did perform better than structure when genotypes were composed of SNPs and differentiation was moderate (FST= 0.022–0.032). When differentiation was low, structure outperformed flockture for both marker types. On large data sets like those we simulated, it appears that flock's reliance on inference rules regarding its ‘plateau record’ is not helpful. Interpreting flock's algorithm as a special case of the model in structure should aid in understanding the program's output and behaviour.