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Increasing pollution in the Arctic poses challenges in terms of geographical and ecological monitoring. The Baffin Bay-Davis Strait (BBDS) region in the Canadian Arctic Archipelago is of particular concern due to the potential for increased shipping traffic and oil exploration. However, data on background contaminants associated with oil exploration/spills/natural seeps (e.g., polycyclic aromatic compounds [PAC]) and measures of potential effects for Arctic birds are limited. We developed a toxicogenomics approach to investigate the background gene expression profiles for two Arctic-breeding seabirds, the thick-billed murre (Uria lomvia) and the black guillemot (Cepphus grylle), which will aid effects-based monitoring efforts. Chemical burdens (53 PACs and 5 trace elements) and transcriptomic profiles (31 genes using a ToxChip PCR array) were examined in liver tissues (n = 30) of each species collected from the Qaqulluit and Akpait National Wildlife Areas in the BBDS region. While chemical and transcriptomic profiles demonstrated low variability across individuals for each species, gene expression signatures were able to distinguish guillemots collected from two distinct colonies. This toxicogenomics approach provides benchmark data for two Arctic seabirds and is promising for future monitoring efforts and strategic environmental assessments in this sensitive ecosystem and areas elsewhere in the circumpolar Arctic that are undergoing change.

Highly migratory species pose unique conservation and management challenges, especially when significant mortality occurs away from breeding concentrations. Population genetics and genomics may help with the appropriate management of these species by (1) determining the population genetic structure of a species across its range, and (2) allowing the assignment of individuals to their breeding source. The northern fulmar (Fulmarus glacialis; Procellariiformes: Procellariidae) is a seabird species that breeds in colonies throughout the North Atlantic and Pacific oceans. This species ranges widely across ocean basins during the non-breeding season and is exposed to a variety of threats throughout the annual cycle. The impact of mortality during the nonbreeding season on individual breeding colonies is unknown but has important ramifications for conservation and management. In this study we used restriction site-associated DNA sequencing (RADseq) to provide 6614 genome-wide single nucleotide polymorphisms (SNPs) to investigate population genetic structure of northern fulmars using 127 individuals from six breeding colonies spanning the Atlantic. Additionally, birds of unknown breeding origin were sampled from two locations: (1) offshore in the Labrador Sea, and (2) the Baffin Bay-Davis Strait region (NAFO subarea 0), as bycatch in gillnets set for Greenland halibut (Reinhardtius hippoglossoides). We found weak genetic differentiation among breeding colonies, which we suggest reflects historical associations as well as contemporary gene flow among populations. Most bycatch birds were likely from nearby breeding colonies in the eastern Canadian Arctic, but the exact breeding origins were difficult to determine due to the lack of differentiation between colonies.

While exposure of birds to oil-related contaminants has been documented, the related adverse effects this exposure has on Arctic marine birds remain unexplored. Metabolomics can play an important role to explore biologically relevant metabolite biomarkers in relation to different stressors, even at benchmark levels of contamination. The aim of this study was to characterize the metabolomics profiles in relation to polycyclic aromatic compounds (PACs) and trace elements in the liver of two seabird species in the Canadian Arctic. In July 2018, black guillemots (Cepphus grylle) and thick-billed murres (Uria lomvia) were collected by hunters from a region where natural oil seeps occur in the seabed near Qikiqtarjuaq, Nunavut, Canada. A total of 121 metabolites were identified in liver tissue samples using reversed phase and hydrophilic interaction liquid chromatography coupled to high resolution mass spectrometry platforms to detect non-polar and polar metabolites, respectively. Sixty-nine metabolites showed excellent repeatability and linearity and were used to examine possible effects of oil-related contaminants exposure (PACs and trace elements). Metabolites including 3-hydroxy anthranilic acid, adenine, adenosine, adenosine mono-phosphate, ascorbic acid, butyrylcarnitine, cholic acid, guanosine, guanosine mono-phosphate, inosine, norepinephrine and threonine showed significant differences (more than two fold) between the two species. Elevated adenine and adenosine, along with decreased reduced/oxidized glutathione ratio, highlighted the potential for oxidative stress in murres. Lipid peroxidation and superoxide dismutase activity assays also confirmed these metabolomic findings. These results will help to characterize the baseline metabolomic profiles of Arctic seabird species with different foraging behaviour and trace element burden.

Mating systems are an important factor influencing the variance in reproductive success among individuals within natural populations and thus have important ecological and evolutionary implications. We used molecular pedigree reconstruction techniques with microsatellite DNA data to characterize the genetic mating system and mate selection in adult smallmouth bass spawning in Lake Opeongo. The genetic mating system of smallmouth bass in this system can be characterized as predominantly monogamous with a low rate of polygynandry particularly among larger individuals. Iteroparous individuals showed a complete absence of interannual mate fidelity, presumably due to the low annual return rate of spawning adults. Within a season, individuals from both sexes pursued additional mating opportunities with males showing greater variance in mate number than females. Female mate selection appeared to be largely random with little evidence for elevated levels of inbreeding in this population. Multiple mating females pursued additional males to whom they were less related than the first male with which they spawned within a given season, however, this pattern varied among years. The mating pattern observed in this population would likely limit the strength of sexual selection and thus could account for the lack of sexual dimorphism and the absence of alternative reproductive tactics in this species.

There is a growing understanding of how oil pollution can affect aquatic ecosystems, including physical and chemical effects. One of the biggest challenges with detecting the effects of oil-related contaminants on biota from resource development is understanding the background levels and potential effects of the exposure of biota to contaminants from various natural and anthropogenic sources prior to large scale oil and gas operations. Seabirds are effective indicators of pollution, and can be useful for tracking oil-related contaminants in the marine environment. We sampled four seabird species (black guillemot, Cepphus grylle; thick-billed murre, Uria lomvia; black-legged kittiwake, Rissa tridactyla; and northern fulmar, Fulmarus glacialis) in the Baffin Bay-Davis Strait region of the Northwest Atlantic and Arctic oceans, an area where natural oil and gas seeps are present but lacking any large-scale oil and gas projects. We found detectable levels of PACs and several trace elements in all species examined. Alkylated PAC levels were higher than parent compounds in all four seabird species examined, with fulmars and murres having the highest levels detected; mean hepatic concentrations of ∑16PAC were 99.05, 46.42, 12.78 and 9.57 ng/g lw, respectively, for guillemots, murres, fulmars and kittiwakes. Overall, PAC concentrations in the seabird species examined were similar to PAC concentrations measured in other bird species in regions with more industrialization. These findings provide data which can be used to assess the current oil-related contaminant exposure of biota in the region. As well, they provide background levels for the region at a time when shipping activity is relatively low, which can used for future comparisons following expected increases in shipping and oil and gas activities in the region.

In landscape genetics, model selection procedures based on Information Theoretic and Bayesian principles have been used with multiple regression on distance matrices (MRM) to test the relationship between multiple vectors of pairwise genetic, geographic, and environmental distance. Using Monte Carlo simulations, we examined the ability of model selection criteria based on Akaike's information criterion (AIC), its small-sample correction (AICc), and the Bayesian information criterion (BIC) to reliably rank candidate models when applied with MRM while varying the sample size. The results showed a serious problem: all three criteria exhibit a systematic bias toward selecting unnecessarily complex models containing spurious random variables and erroneously suggest a high level of support for the incorrectly ranked best model. These problems effectively increased with increasing sample size. The failure of AIC, AICc, and BIC was likely driven by the inflated sample size and different sum-of-squares partitioned by MRM, and the resulting effect on delta values. Based on these findings, we strongly discourage the continued application of AIC, AICc, and BIC for model selection with MRM.