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Data from Bering-Chukchi-Beaufort Seas bowhead whales (Balaena mysticetus), harvested during 1973–2021 by aboriginal subsistence hunters, were used to estimate reproductive parameters: length at sexual maturity (LSM), age at sexual maturity (ASM), pregnancy rate (PR), and calving interval. Sexual maturity (N = 187 females) was determined from the presence/absence of corpora in the ovaries, or a fetus. Using sampling bias-corrected logistic regression, LSM was estimated at 13.5 m, 95% CI [13.0, 13.8]. There was a downward trend in LSM over time, statistically significant with one method but marginal with another. A growth model translated this estimate to an ASM estimate of 23.5 years, 95% CI [20.4, 26.7]. Pregnancy rate was determined from mature females (N = 125), and from a subset limited to certain autumn-caught whales (n = 37) to reduce bias. The PR was estimated at 0.46 globally, 95% CI [0.36, 0.55] and 0.38 for the autumn sample, 95% CI [0.20, 0.51]. Both estimated PRs are consistent with a 3-year calving interval, because the larger estimate includes two cohorts of pregnant whales harvested in spring, and bowhead whale gestation is longer than 12 months. These analyses represent the most conclusive empirical estimates of ASM, LSM, and PR for this bowhead whale stock from the largest available data sets to date.

Six species of cetaceans have been found to occur in the Chukchi Sea adjacent to the Pacific walrus rookery at Cape Vankarem: the gray whale, the bowhead whale, the humpback whale, the killer whale, the beluga whale, and the fin whale. The humpback whale is noted to have become abundant in the Chukchi Sea in the summer in recent years. The coastal mortality of cetaceans in a 100-km section in the western part of the distribution range of both gray and bowhead whales has been established to average 1.66 and 0.3 whales per year, respectively. Mostly young animals of 1–2 years of age appear to die, the main cause of death of which is predation by killer whales. The most common whales in that area in the summer–autumn period are humpback whales, which at the same time form significant concentrations in the coastal waters during the accumulation of the main food items. Both bowhead and gray whales are much less frequent, found rather irregularly, while despite the relative scarcity of encounters, these species account for the lion's share of all dead cetaceans. [ABSTRACT FROM AUTHOR]

Passive acoustic monitoring is a promising method for surveying wildlife populations that are easier to detect acoustically than visually. When animal vocalisations can be uniquely identified on an array of sensors, the potential exists to estimate population density through acoustic spatial capture–recapture (ASCR). However, sound classification is imperfect, and in some situations, a high proportion of sounds detected on just a single sensor ('singletons') are not from the target species. We present a case study of bowhead whale calls (Baleana mysticetus) collected in the Beaufort Sea in 2010 containing such false positives. We propose a novel extension of ASCR that is robust to false positives by truncating singletons and conditioning on calls being detected by at least two sensors. We allow for individual-level detection heterogeneity through modelling a variable sound source level, model inhomogeneous call spatial density, and include bearings with varying measurement error. We show via simulation that the method produces near-unbiased estimates when correctly specified. Ignoring source-level variation resulted in a strong negative bias, while ignoring inhomogeneous density resulted in severe positive bias. The case study analysis indicated a band of higher call density approximately 30 km from shore; 59.8% of singletons were estimated to have been false positives. [ABSTRACT FROM AUTHOR]

Effective protection of highly mobile and data-poor species constitutes a great challenge amid growing ocean exploitation and use. Blue whales and bowhead whales in the North-East Atlantic face several threats, such as climate change, ship strikes, pollution, and entanglement in fishing gear. Consequently, the OSPAR ("Oslo-Paris Convention for the Protection of the Marine Environment of the North-East Atlantic") Commission recognised their need for protection and included them on the OSPAR List of Threatened and/or Declining Species. Two actions to protect these endangered species that OSPAR Contracting Parties have agreed on are (i) identifying areas that play an essential role in the species' life cycle—subsequently called key habitats, and (ii) ensuring that those key habitats are covered by OSPAR marine protected areas (MPAs). In addition, OSPAR has committed to expanding its network of MPAs and other effective area-based conservation measures by 2030 to cover at least 30% of the OSPAR maritime area (termed the 30 × 30 target) from today's approx. 11%. In this paper, we present the results of modelling key habitats for the bowhead and blue whales in the North-East Atlantic, including Arctic waters. Due to the sparse data situation for these species, we apply presence-only modelling methods. As this method can, in principle, produce somewhat biased results, we recommend that systematic, regular surveys on these species in Arctic waters be significantly intensified for future analyses to overcome the data paucity and allow using presence–absence/count data modelling approaches. Key habitats of blue whales were identified between Iceland and Svalbard, extending to the Azores. For bowhead whales, key habitats were identified in the Fram Strait. However, our findings show that only 11.8% of blue whale key habitats and 4.1% of bowhead whale key habitats are currently covered by OSPAR MPAs. To protect 30% of key habitats for these species in the most efficient way, our analyses suggest that suitable areas to designate new OSPAR MPAs are located around the Azores for blue whales and in the Fram Strait for bowhead whales. With these additional MPAs, OSPAR would substantially improve the protection of the two endangered species and, at the same time, progress towards its 30 × 30 target. [ABSTRACT FROM AUTHOR]

Given the increasing challenges that Arctic cetaceans face, it is critical to investigate novel methods for assessing their health. Skin microbiomes have emerged as a promising method of detecting health issues that can help guide conservation efforts for free-ranging cetaceans. This study characterized the skin microbiome of 17 bowhead (BW) and 2 killer whales (KW). Fifty-six amplicon sequence variants were identified exclusively from cetacean samples, 20 belonged to BW, 13 to KW, and 23 to BW and KW. We identified bacteria from the genera Tenacibaculum and Psychrobacter, which have been previously described as bacteria that play a role in the health of cetaceans. In addition, in the healthy bowhead whale (H-BW) samples, we identified Clostridium sensu stricto 1 and 7, Carnobacterium spp., and Yersinia spp. which are of concern because these bacteria are opportunistic pathogens. Stranded BW had a less diverse microbiome than H-BW and had pathogens, including Aeromonas species and Streptococcus agalactia. Opportunistic pathogens of the genera Moritella (previously Vibrio spp.), Shewanella, Psychrilyobacter, and Legionella were discovered in KW. Due to their predator–prey relationships, the findings of this pilot study support the importance of keeping a close eye on the bowhead and killer whale populations in the Arctic.

In a rapidly changing Arctic, multiple lines of evidence suggest that bowhead whale migration is changing. To explore these changes further, we used passive acoustic data to examine bowhead whale presence in the western Beaufort Sea (12 years) and Chukchi Plateau (11 years) spanning 2008 to 2022. Departure from the western Beaufort Sea shifted 45 days later over the 12‐year period. Summer presence increased at both sites, suggesting feeding areas within the Chukchi Sea are becoming more favorable. Likewise, findings from the Bering Strait suggest that some whales are remaining north of the Bering Strait for the winter instead of in the Bering Sea. These Pacific Arctic‐wide changes to migration have occurred over only one decade. Questions remain about prey availability in the Chukchi Sea, implications of migratory changes, such as a northward shift in the core overwintering area, and impact to communities south of the Bering Strait. Plain Language Summary: Bowhead whales are an important top predator in the Pacific Arctic. With increasing temperatures and decreasing sea ice, changes are occurring in the migration patterns of this "ecosystem sentinel" throughout the Pacific Arctic. We analyzed passive acoustic data from the western Beaufort Sea and Chukchi Plateau from 2008 to 2022. Whales are delaying their fall departure from the western Beaufort Sea and spending more time in the western Beaufort Sea and Chukchi Plateau, which, along with increased habitat use on the Chukchi Shelf, suggests that conditions there are becoming more favorable for feeding. Combined with previous data from the Bering Strait, which showed that some whales are spending winter in the southern Chukchi Sea rather than in the northern Bering Sea, these findings suggests that changes are occurring over a short period of time throughout the Pacific Arctic. A northward shift could put bowhead whales in the direct path of ships, especially along the western side of the Chukchi Sea, and impact whaling communities south of the Bering Strait. Key Points: Acoustic data reinforce known delay in bowhead fall departure from the western Beaufort Sea and overwintering in the southern Chukchi SeaIncreased presence in the western Beaufort Sea and Chukchi Plateau suggests these regions are becoming more favorable for bowhead feedingWhales are adapting to a rapidly changing Arctic, but changes and emerging threats may impact them and communities south of Bering Strait [ABSTRACT FROM AUTHOR]

Bowhead whales (Balaena mysticetus) face threats from diminishing sea ice and increasing anthropogenic activities in the Arctic. Passive acoustic monitoring is the most effective means for monitoring their distribution and population trends, based on the detection of their calls. Passive acoustic monitoring, however, is influenced by the sound propagation environment and ambient noise levels, which impact call detection probability. Modeling and simulations were used to estimate detection probability for bowhead whale frequency-modulated calls in the 80-180 Hz frequency band with and without sea ice cover and under various noise conditions. Sound transmission loss for bowhead calls is substantially greater during ice-covered conditions than during open-water conditions, making call detection ~ 3 times more likely in open-water. Estimates of daily acoustic detection probability were used to compensate acoustic detections for sound propagation and noise effects in two recording datasets in the northeast Chukchi Sea, on the outer shelf and continental slope, collected between 2012 and 2013. The compensated acoustic density suggests a decrease in whale presence with the retreat of sea ice at these recording sites. These results highlight the importance of accounting for effects of the environment on ambient noise and acoustic propagation when interpreting results of passive acoustic monitoring.

Effective protection of highly mobile and data-poor species constitutes a great challenge amid growing ocean exploitation and use. Blue whales and bowhead whales in the North-East Atlantic face several threats, such as climate change, ship strikes, pollution, and entanglement in fishing gear. Consequently, the OSPAR (“Oslo-Paris Convention for the Protection of the Marine Environment of the North-East Atlantic”) Commission recognised their need for protection and included them on the OSPAR List of Threatened and/or Declining Species. Two actions to protect these endangered species that OSPAR Contracting Parties have agreed on are (i) identifying areas that play an essential role in the species’ life cycle—subsequently called key habitats, and (ii) ensuring that those key habitats are covered by OSPAR marine protected areas (MPAs). In addition, OSPAR has committed to expanding its network of MPAs and other effective area-based conservation measures by 2030 to cover at least 30% of the OSPAR maritime area (termed the 30 × 30 target) from today’s approx. 11%. In this paper, we present the results of modelling key habitats for the bowhead and blue whales in the North-East Atlantic, including Arctic waters. Due to the sparse data situation for these species, we apply presence-only modelling methods. As this method can, in principle, produce somewhat biased results, we recommend that systematic, regular surveys on these species in Arctic waters be significantly intensified for future analyses to overcome the data paucity and allow using presence–absence/count data modelling approaches. Key habitats of blue whales were identified between Iceland and Svalbard, extending to the Azores. For bowhead whales, key habitats were identified in the Fram Strait. However, our findings show that only 11.8% of blue whale key habitats and 4.1% of bowhead whale key habitats are currently covered by OSPAR MPAs. To protect 30% of key habitats for these species in the most efficient way, our analyses suggest that suitable areas to designate new OSPAR MPAs are located around the Azores for blue whales and in the Fram Strait for bowhead whales. With these additional MPAs, OSPAR would substantially improve the protection of the two endangered species and, at the same time, progress towards its 30 × 30 target.

Abstract In a rapidly changing Arctic, multiple lines of evidence suggest that bowhead whale migration is changing. To explore these changes further, we used passive acoustic data to examine bowhead whale presence in the western Beaufort Sea (12 years) and Chukchi Plateau (11 years) spanning 2008 to 2022. Departure from the western Beaufort Sea shifted 45 days later over the 12‐year period. Summer presence increased at both sites, suggesting feeding areas within the Chukchi Sea are becoming more favorable. Likewise, findings from the Bering Strait suggest that some whales are remaining north of the Bering Strait for the winter instead of in the Bering Sea. These Pacific Arctic‐wide changes to migration have occurred over only one decade. Questions remain about prey availability in the Chukchi Sea, implications of migratory changes, such as a northward shift in the core overwintering area, and impact to communities south of the Bering Strait.

The bowhead whale is a vital component of the maritime environment. Using deep learning techniques to recognize bowhead whales accurately and efficiently is crucial for their protection. Marine acoustic remote sensing technology is currently an important method to recognize bowhead whales. Adaptive SWT is used to extract the acoustic features of bowhead whales. The CNN-LSTM deep learning model was constructed to recognize bowhead whale voices. Compared to STFT, the adaptive SWT used in this study raises the SCR for the stationary and nonstationary bowhead whale whistles by 88.20% and 92.05%, respectively. Ten-fold cross-validation yields an average recognition accuracy of 92.85%. The method efficiency of this work was further confirmed by the consistency found in the Beaufort Sea recognition results and the fisheries ecological study. The research results in this paper help promote the application of marine acoustic remote sensing technology and the conservation of bowhead whales. [ABSTRACT FROM AUTHOR]

Epigenetic approaches for estimating the age of living organisms are revolutionizing studies of long‐lived species. Molecular biomarkers that allow age estimates from small tissue biopsies promise to enhance studies of long‐lived whales, addressing a fundamental and challenging parameter in wildlife management. DNA methylation (DNAm) can affect gene expression, and strong correlations between DNAm patterns and age have been documented in humans and nonhuman vertebrates and used to construct "epigenetic clocks". We present several epigenetic clocks for skin samples from two of the longest‐lived cetaceans, killer whales and bowhead whales. Applying the mammalian methylation array to genomic DNA from skin samples we validate four different clocks with median errors of 2.3–3.7 years. These epigenetic clocks demonstrate the validity of using cytosine methylation data to estimate the age of long‐lived cetaceans and have broad applications supporting the conservation and management of long‐lived cetaceans using genomic DNA from remote tissue biopsies. [ABSTRACT FROM AUTHOR]

Serial measurements of hormone concentrations along baleen plates allow for reconstructions of mysticete whale reproductive histories. We assessed gestation and calving interval in bowhead whales (Balaena mysticetus) by measuring progesterone, oestradiol, corticosterone and nitrogen stable isotope ratios (δ15N) along baleen of 10 females from the eastern Canada-west Greenland population. Three immature females (body size < 14.32 m) had uniformly low progesterone concentrations across their baleen, while seven mature females (body size ≥ 14.35 m) had repeated, sustained elevations of progesterone indicative of pregnancies. The mean duration of progesterone elevations (23.6 ± 1.50 months) was considerably longer than the approximately 14 month gestation previously estimated for this species. We consider several possible explanations for this observation, including delayed implantation or sequential ovulations prior to gestation, strategies that would allow females to maximize their fitness in variable Arctic conditions, as well as suggest modified criteria defining gestation as a shorter component of the entire progesterone peak. Calving intervals varied within and among individuals (mean = 3.7 years; range = range 2.8–5.7 years), providing population-specific reproductive estimates for growth models used in bowhead whale management and conservation.

Sea ice loss is fundamentally altering the Arctic marine environment. Yet there is a paucity of data on the adaptability of food webs to ecosystem change, including predator–prey interactions. Polar bears (Ursus maritimus) are an important subsistence resource for Indigenous people and an apex predator that relies entirely on the under‐ice food web to meet its energy needs. In this study, we assessed whether polar bears maintained dietary energy density by prey switching in response to spatiotemporal variation in prey availability. We compared the macronutrient composition of diets inferred from stable carbon and nitrogen isotopes in polar bear guard hair (primarily representing summer/fall diet) during periods when bears had low and high survival (2004–2016), between bears that summered on land versus pack ice, and between bears occupying different regions of the Alaskan and Canadian Beaufort Sea. Polar bears consumed diets with lower energy density during periods of low survival, suggesting that concurrent increased dietary proportions of beluga whales (Delphinapterus leucas) did not offset reduced proportions of ringed seals (Pusa hispida). Diets with the lowest energy density and proportions from ringed seal blubber were consumed by bears in the western Beaufort Sea (Alaska) during a period when polar bear abundance declined. Intake required to meet energy requirements of an average free‐ranging adult female polar bear was 2.1 kg/day on diets consumed during years with high survival but rose to 3.0 kg/day when survival was low. Although bears that summered onshore in the Alaskan Beaufort Sea had higher‐fat diets than bears that summered on the pack ice, access to the remains of subsistence‐harvested bowhead whales (Balaena mysticetus) contributed little to improving diet energy density. Because most bears in this region remain with the sea ice year round, prey switching and consumption of whale carcasses onshore appear insufficient to augment diets when availability of their primary prey, ringed seals, is reduced. Our results show that a strong predator–prey relationship between polar bears and ringed seals continues in the Beaufort Sea. The method of estimating dietary blubber using predator hair, demonstrated here, provides a new metric to monitor predator–prey relationships that affect individual health and population demographics. [ABSTRACT FROM AUTHOR]

The 2019 ice-based survey of Bering-Chukchi-Beaufort Seas bowhead whales was challenged by missed survey effort, unusual ice conditions and frequent use of motor-powered skiffs by hunters. All three of these likely led to downward bias in the abundance estimate of Givens et al. (2021). Data were collected about boat excursions during the survey period. Indices of short-term whale abundance at the survey perch and short-term boat noise disturbance were computed from the available data, where ‘short term’ refers to a few hours. A generalised additive model (GAM) was fitted to the results, predicting short-term whale abundance as a smooth function of the boat noise disturbance index, after controlling for long-term variation in the whale passage rate over the course of the season. The fitted GAM was then used to predict passage with and without the presence of boat noise. The ratio of the integrals of these two predicted passage curves provided a correction factor which can be applied post hoc to the abundance estimate of Givens et al. (2021). Variance of this correction factor was estimated using two approaches and found to be small. A wide array of sensitivity analyses was conducted to examine the robustness of the result to potential changes in methodology and the correction factor was found to be quite stable. The estimated correction factor would inflate the original abundance estimate by about 12%, yielding a corrected abundance of 14,025 (CV = 0.228). We recommend this replace the original abundance estimate. [ABSTRACT FROM AUTHOR]

Population genetic research is a critical tool for the conservation and management of marine mammals and other species. The bowhead whale (Balaena mysticetus) is subject to aboriginal subsistence hunting in Alaska, Canada, Chukotka (Russian Federation) and Greenland, where, except for Canada, it is managed by the International Whaling Commission (IWC). Molecular genetic studies support conservation management plans and aid determination of sustainable hunting quotas by providing information on levels of genetic diversity, estimates of census size, effective population size and structure. Because bowhead populations are monitored, including genetic monitoring, in several countries, there is a need for genetic methods that can be consistently used in multiple labs and provide comparable data that can be publicly shared and built upon by successive studies. Here we present a new panel of single nucleotide polymorphisms (SNPs), derived from multiple bowhead populations, which meets these criteria. We describe the use of the Fluidigm SNPtype assay for analysing 69 autosomal, six X‐chromosome and one Y‐chromosome SNPs. Results indicate the methods herein have high efficacy and low error rates. Furthermore, because SNPs are discrete sequence‐based genetic markers, the panel of loci described here can be reliably replicated and is directly comparable across different labs, making this SNP panel more useful than existing microsatellite markers. [ABSTRACT FROM AUTHOR]

Successful reproduction is essential to a species existence. Here we summarize Bering–Chukchi–Beaufort (BCB) bowhead whale (Balaena mysticetus Linnaeus, 1758) calf distribution, ratio of calf to adult sightings, and encounter rate from data collected during line–transect aerial surveys conducted from July to October 2012–2019 in the western Beaufort Sea (140°W–157°W). During 223,000 on effort km, a total of 274 calves were seen: 100 in summer (July–August) and 174 in fall (September–October), compared with nearly 3,200 non-calves. Calves were widely distributed in the study area in August and September, with distribution in July largely east of 150°W and distribution in October west of 143°W. Calf ratios and encounter rates appear to follow a 3–4 year cycle. Most calves (240/274; 88%) were seen near an adult assumed to be the maternal female, but 9% (26/274) of all calves were observed unaccompanied at the surface and 3% (8/274) were observed with large whales at the surface but not close by. Of the total calves detected, 60% (165/274) were observed after circling was initiated, highlighting the importance of closely investigating all bowhead whale sightings if identification of calves is critical to project goals. Bowhead whale calf data from the eastern Beaufort Sea and Amundsen Gulf in August 2019 are also summarized.

The bowhead whale is a vital component of the maritime environment. Using deep learning techniques to recognize bowhead whales accurately and efficiently is crucial for their protection. Marine acoustic remote sensing technology is currently an important method to recognize bowhead whales. Adaptive SWT is used to extract the acoustic features of bowhead whales. The CNN-LSTM deep learning model was constructed to recognize bowhead whale voices. Compared to STFT, the adaptive SWT used in this study raises the SCR for the stationary and nonstationary bowhead whale whistles by 88.20% and 92.05%, respectively. Ten-fold cross-validation yields an average recognition accuracy of 92.85%. The method efficiency of this work was further confirmed by the consistency found in the Beaufort Sea recognition results and the fisheries ecological study. The research results in this paper help promote the application of marine acoustic remote sensing technology and the conservation of bowhead whales.

Effective management of animal populations requires knowledge of life history parameters and estimates of population abundance. One method commonly used to estimate abundance is capture–recapture analyses of photographs. Small, relatively inexpensive, rotary-wing drones have become an effective platform for obtaining high-quality aerial photographs of whales. To conduct capture–recapture analyses the animal needs to be defined as marked or unmarked and the photographs must be of high quality. While a system for scoring quality and markedness has previously been developed for bowhead whales (Balaena mysticetus Linnaeus, 1758) (Rugh et al. 1998. Rep. int. Whal. Commn. 48: 501–512), a revised scoring system was needed to incorporate increased information in photographs taken by drones. We present a revised scoring system that enlarges two of the previously defined areas of the whale examined for markings and incorporates smaller markings into the definition of marked whales. We scored 30 whales using the previous criteria and the revised criteria developed in this paper. More whales were identified as marked (23%) and mark scores were higher for 30% of the zones scored using the new system. Increasing the number of marked whales during capture–recapture studies increases the precision of estimated parameters and permits us to make those estimates with smaller samples of photographs.

Information on factors contributing to the morbidity and mortality of the Bering–Chukchi–Beaufort seas stock of bowhead whales (Balaena mysticetus) is fundamental to its successful management and recovery. The Alaska Arctic coastline is remote and expansive, making monitoring for and gross examination of carcasses difficult. However, sighting data and imagery collected during aerial surveys in the eastern Chukchi (EC) and western Beaufort (WB) seas from 2009 through 2019 provide information on bowhead whale mortality. We present bowhead whale carcass data from the 2019 aerial surveys that add to the long series of consistent information on floating and beach-cast bowhead whale carcasses. The 2019 carcass data suggest an increased occurrence of probable killer whale (Orcinus orca) predation on bowhead whales in the WB. Eleven bowhead whale carcasses were photo-documented from July to October 2019 in the EC and WB study areas. Of the 11 carcasses documented, 7 had injuries consistent with probable killer whale predation—2 in the EC and 5 in the WB. Probable cause of death could not be assigned to four carcasses. No carcasses were associated with aboriginal subsistence hunting. Despite similar annual survey effort from 2009 to 2019, several compelling deviations in carcass numbers and locations were observed in 2019. Compared to 2009–2018, 2019 had the highest yearly number of documented carcasses and the most categorized as probable killer whale predation. Carcass locations exhibited a striking shift from the EC to the WB. Lastly, more carcasses were categorized as probable killer whale predation in the WB during 2019 than in 2009–2018 combined. [ABSTRACT FROM AUTHOR]

With global climate change and increasing ocean-based human activities, large whales face novel challenges in the Arctic seas. Understanding and assessing large whale occurrence and the links between occurrence and environmental variables in this region is a key issue in current management and conservation strategies for Arctic marine mammal species. During the Chukchi Sea Environmental Studies Program, large whale occurrence data were collected from vessel surveys during >56,909 km of observation effort in summer and autumn, 2008 to 2014, in the northeastern Chukchi, southern Beaufort, and Bering Seas. The most-recorded species were the Bowhead (Balaena mysticetus) and Gray (Eschrichtius robustus) Whales. Subarctic species recorded included the Humpback Whale (Megaptera novaeangliae), Fin Whale (Balaenoptera physalus), and Minke Whale (Balaenoptera acutorostrata). Sightings data were analyzed with respect to environmental variables: sea-surface temperature (SST), depth (m), and distance from shore (km), by month and year. Investigating occurrence associations with environmental parameters is a key element for predicting large whale trends in these Arctic seas and for understanding marine mammals as sentinels of oceanic shifts. [ABSTRACT FROM AUTHOR]

The remote and harsh environment that endemic Arctic whales (bowhead, narwhal and beluga) reside in has so far limited their exposure to many human activities. However, Arctic industrialisation coupled with increasingly accessible ice-free waters means these species increasingly co-occur, and are exposed to, a number of potentially impactful activities, many of which are directly or indirectly associated with marine vessels. We conducted a systematic map, using five search databases, to ascertain the current level of understanding relating to how Arctic whales respond to marine vessels and vessel-associated activities. We identified a limited volume of literature (n = 169), and a disparity in volume between species, subpopulations, and vessel types. Several vessel types are increasingly present in the Arctic (e.g. cruise ships, fishing vessels), yet received limited consideration. Similarly, several endangered subpopulations have received little attention. Only with sufficient understanding of the associated impacts of vessels can we develop appropriate management and mitigation measures which can effectively conserve these unique, vulnerable and inherently valuable species. [Display omitted] • Marine vessel traffic in the Arctic is increasing, and often overlaps with Arctic whale range (beluga, bowhead, narwhal). • We used a systematic map to review current knowledge of Arctic whale response(s) to vessels, and found research has been limited, and is unequal across species, stocks and vessel types. • Many endangered subpopulations have little research related to their response to vessels. • Vessel types that are increasing in the Arctic, e.g. fishing, cruise, have so far received limited research effort. • Knowledge gaps should be addressed to inform the development of proactive and adaptive vessel-related management approaches. [ABSTRACT FROM AUTHOR]

This study established the first baseline of changing elemental concentrations in bowhead whale baleen over time (1958–1999). From previously published stable isotope data, year, season (summer or winter), and location (Beaufort or Bering/Chukchi seas) were attributed to each sample. Thirteen elements (Al, Cd, Co, Cr, Cu, Fe, Hg, Mn, Ni, Pb, Se, V, Zn) in baleen from nine subsistence-harvested bowhead whales (n = 138) were detected. Al, Cu, and Fe were the highest concentrations while Cd and V were among the lowest. Our data supports absorption as the main route of exposure to environmental elements rather than biomagnification due to bowhead whales' low trophic position. A linear mixed-effects model confirmed most elements' concentrations increased with time, while location and sex were insignificant explanatory factors. These temporal fluctuations were most likely a product of environmental changes due to a warming climate and human activities. [ABSTRACT FROM AUTHOR]

Bowhead whales occur in the Arctic year‐round. Their movements are largely correlated with seasonal expansions and reductions of sea ice, but a few recent extralimital sightings have occurred in the eastern and western North Atlantic and one was also documented in the western North Pacific over 50 years ago. Here we present details of a juvenile bowhead whale that was photographed and filmed from above and below the water while it was skim‐feeding in Caamaño Sound, BC, Canada on May 31, 2016. This sighting occurred over 2000 km southeast from the nearest known range for this species in the Bering Sea at a time that most bowhead whales in that region would have been migrating northeast. This sighting represents the first and only documentation of a bowhead whale in the eastern North Pacific to date. [ABSTRACT FROM AUTHOR]

The history of bowhead whaling and hunt management in the eastern and central Canadian Arctic is reviewed. Subsistence hunting of bowhead whales by Inuit resumed in the 1990s under co-management arrangements that were part of land-claims settlement agreements. Removals by whaling in both Canada and Greenland have been accounted for in IWC Scientific Committee assessments of the Eastern Canada-West Greenland (EC-WG) stock, but Canada, having withdrawn from IWC membership in 1982, has no legal obligation to consider IWC management advice. From 1994-2021 the total reported catch of bowheads in the central and eastern Canadian Arctic was 39 (not including struck-and-lost whales or whales that died from entanglement in fishing gear). Sixteen different communities, most of which had a long history of bowhead whaling prior to the arrival of commercial whalers, took at least one bowhead over that 27-year period. More than half of the recent catches have been by the communities of Igloolik, Sanijarak, Naujaat and Coral Harbour, all in the Foxe Basin-Repulse Bay-northern Hudson Bay region where at least occasional hunting of bowheads by local people had persisted until well into the 1970s. Greenland's reported landed catches totaled 8 from 2009-2015, with no successful hunts reported since 2015. Well over a third of the whales landed by both countries combined have been mature females, the most valuable class in terms of potential for population increase. Several factors in addition to hunting and entanglement in fishing gear are likely affecting EC-WG bowheads, including increased exposure to killer whale predation (linked to the massive reduction in sea ice) and other changes in ecological conditions driven primarily by climate change (e.g. more industrial activity, more vessel traffic, more noise). Recent analyses suggest the ECWG stock of bowheads has grown considerably since the end of commercial whaling, with best estimates of current abundance in the range of 6,000-7,000 individuals. Even though the population appears capable of sustaining present levels of removal and disturbance, it is important for monitoring efforts to continue in both Canada and Greenland, with regular Indigenous participation. [ABSTRACT FROM AUTHOR]

Abstract Polar bears (Ursus maritimus) from the southern Beaufort Sea (SB) subpopulation have traditionally fed predominantly upon ice‐seals; however, as the proportion of the subpopulation using onshore habitat has recently increased, foraging on land‐based resources, including remains of subsistence‐harvested bowhead whales (Balaena mysticetus) and colonial nesting seabirds has been observed. Adipose tissue samples were collected from this subpopulation during the springs of 2013–2016 and analyzed for fatty acid signatures. Diet estimates were generated for the proportional consumption of ringed seal (Pusa hispida), bearded seal (Erignathus barbatus), and beluga whale (Delphinapterus leucas), relative to onshore foods, including bowhead whale remains and seabird, as represented by black guillemot (Cepphus grylle mandtii) nestlings and eggs. Quantitative fatty acid signature analysis (QFASA) estimated that the ice‐obligate prey, ringed seal, remained the predominant prey species of SB polar bears (46.4 ± 1.8%), with much lower consumption of bearded seal (19.6 ± 2.0%), seabird (17.0 ± 1.2%), bowhead whale (15.0 ± 1.4%), and hardly any beluga whale (2.0 ± 0.5%). Adult and subadult females appeared to depend more on the traditional ringed seal prey than adult and subadult males. Diet estimates of SB polar bears showed significant interannual variability for all prey (F12, 456 = 3.17, p

The Chukchi Sea environment changes considerably in physical and biological conditions, driven by the expanding volume of warm Pacific summer water. These environmental changes can affect the migration timing of baleen whales in the southern Chukchi Sea. However, few studies have been conducted in this area to determine the migration timing of bowhead whales (Balaena mysticetus), the only baleen whale species endemic to the Arctic region. In this study, we conducted a fixed passive acoustic monitoring of bowhead whales in the southern Chukchi Sea from July 2012 to October 2015 and compared the occurrence patterns of vocalizations to physical and biological environmental factors. Bowhead whale calls were detected in fall/winter and spring during the ice-freezing and retreating periods, respectively. The fall migration timing of bowhead whales through the southern Chukchi Sea was delayed in the years when the timing of sea ice formation was late, and it formed increasingly later in the years 2013, 2014, and 2012, in that sequence. Moreover, the sea surface temperature decreased before freeze-up, which affected the timing of fall migration of bowhead whales. There was no clear relationship between the occurrence of bowhead whale calls and the abundance of prey, especially in spring, suggesting that most bowhead whales use the southern Chukchi Sea as a corridor during their spring northward migrations. However, the occurrence of bowhead whales and high abundance of zooplankton in October–November present the possibility that bowhead whales expand their feeding area in the southern Chukchi Sea. [ABSTRACT FROM AUTHOR]

The bowhead whale is the only baleen whale endemic to the Arctic and is well adapted to this environment. Bowheads live near the polar ice edge for much of the year and although sea ice dynamics are not the only driver of their annual migratory movements, it likely plays a key role. Given the intrinsic variability of open water and ice, one might expect bowhead migratory plasticity to be high and linked to this proximate environmental factor. Here, through a network of underwater passive acoustic recorders, we document the first known occurrence of bowheads overwintering in what is normally their summer foraging grounds in the Amundsen Gulf and eastern Beaufort Sea. The underlying question is whether this is the leading edge of a phenological shift in a species' migratory behaviour in an environment undergoing dramatic shifts due to climate change.

Since the first studies on bowhead whale singing behaviour, song variations have been consistently reported. However, there has been little discussion regarding variability in bowhead whale singing display and its ecological significance. Unlike the better studied humpback whales, bowhead whales do not appear to share songs at population level, but several studies have reported song sharing within clusters of animals. Over the winter season 2013–2014, in an unstudied wintering ground off Northeast Greenland, 13 song groups sharing similar hierarchical structure and units were identified. Unit types were assessed through multidimensional maps, showing well separated clusters corresponding to manually labelled units, and revealing the presence of unit subtypes. Units presented contrasting levels of variability over their acoustic parameters, suggesting that bowhead whales keep consistency in some units while using a continuum in values of frequency, duration and modulation parameters for other unit types. Those findings emphasise the need to account for variability in song analysis to better understand the behavioural ecology of this endangered species. Additionally, shifting from song toward units or phrase-based analysis, as it has been suggested for humpback whales, offers the opportunity to identify and track similarities in songs over temporal and geographical scales relevant to population monitoring. [ABSTRACT FROM AUTHOR]

An ice‐based visual survey of the Bering‐Chukchi‐Beaufort Seas stock of bowhead whales (Balaena mysticetus) was conducted in spring 2019 near Utqiaġvik (formerly Barrow), Alaska. A Horvitz‐ Thompson‐type estimator is used to estimate population abundance from the resulting data, correcting for detection probabilities, whale availability within visual range, and whale passage during periods of missed effort. Analytical methods mirror those used for the 2011 survey as much as possible; however, unlike 2011, no simultaneous acoustic monitoring was conducted in 2019, so the availability correction factor had to be estimated from past years. The estimated abundance was 12,505 with 95% confidence interval of (7,994, 19,560) and a CV of 0.228. This estimated abundance is markedly lower than the 2011 estimate of 16,820, but the 2019 confidence interval wholly encompasses the 2011 interval. We do not interpret this finding as evidence of a decline for many reasons including: highly unusual ice conditions, an unusual migration route that was sometimes too distant from observers to detect whales, failure to conduct watch because of closed leads during the early weeks of the migration when numerous whales likely passed, an unusually short perch, and hunters’ heavy use of powered skiffs near the observation perch which likely disturbed the whales during the survey. Furthermore, bowhead health assessment information for 2019 suggests that harvested bowheads did not exhibit obvious reductions in health condition, and aerial surveys in summer 2019 indicated high calf production. Despite the challenges of this survey, the estimate is adequate for use with the International Whaling Commission’s management procedure and complies with the survey requirements of the Aboriginal Whaling Scheme. [ABSTRACT FROM AUTHOR]

Sound propagation models were developed for modally dispersed seismic shots to determine range to a seismic source from two High-frequency Acoustic Recording Packages (HARPs) deployed on the continental slope break north-northwest of Point Barrow, Alaska in the fall of 2007.Received levels at the HARPs had an average received sound level of 112.8 dB rms. These received level measurements coincide with levels that have shown to elicit behavioral responses in bowhead whales, and raise concerns about how seismic activities may potentially impact marine mammals across large spatial scales and international maritime boundaries. Although guidelines have been established to reduce such impacts, current mitigation measures show considerable variation between countries and do not take into account the transboundary nature of sound in the ocean. To provide an international framework for the regulation of seismic surveys in the Arctic, a better understanding of how sound propagates in a changing Arctic environment, in addition to how the cumulative impacts of multiple seismic activities may influence ambient noise levels across large spatial scales is needed. A collaborative approach to management, mitigation, and research is essential to provide effective protection for marine mammals as a result of increased international and multi-industry interest in the Arctic and its natural resources.

The hunting of bowhead whales (Balaena mysticetus) is an integral part of Inuit culture. An up-to-date abundance estimate of the entire Eastern Canada – West Greenland (EC-WG) bowhead population is necessary to support sustainable management of this harvest. The High Arctic Cetacean Survey (HACS) was conducted in August 2013, primarily to update abundance estimates for known stocks of Baffin Bay narwhal (Monodon monoceros). As the ranges of narwhal and bowhead largely overlap, the survey area was expanded to cover the summer range of bowhead whales. Bowhead whale abundance was estimated using 3 aircraft to cover the large survey area within a short time frame. Distance sampling methods were used to estimate detection probability away from the track line. Double platform with mark-recapture methods were used to correct for the proportion of whales missed by visual observers on the track line (perception bias). Abundance in Isabella Bay, an area known for high bowhead density, was estimated using density surface modelling to account for its complex shape and uneven coverage. Estimates were corrected for availability bias (whales that were not available for detection because they were submerged when the aircraft passed overhead) using a recent analysis of satellite-linked time depth recorders transmitting information on the diving behaviour of bowhead whales in the study area in August of the same survey year. The fully corrected abundance estimate for the EC-WG bowhead whale population was 6,446 (95% CI: 3,838–10,827). Possible sources of uncertainty include incomplete coverage and the diving behaviour of bowhead whales. These results confirm earlier indications that the EC-WG stock is continuing to recover from past overexploitation.

Estimating abundance is one of the most fundamental and important aspects of population biology, with major implications on how the status of a population is perceived and thus on conservation and management efforts. Although typically based on one of two methods (distance sampling or mark-recapture), there are many individual identification methods that can be used for mark-recapture purposes. In recent years, the use of genetic data for individual identification and abundance estimation through mark-recapture analyses have increased, and in some situations such genetic identifications are more efficient than their field-based counterparts for population monitoring. One issue with mark-recapture analyses, regardless of which method of individual identification is used, is that the study area must provide adequate opportunities for “capturing” all individuals within a population. However, many populations are unevenly and widely distributed, making it unfeasible to adequately sample all necessary areas. Here we develop an analytical technique that accounts for unsampled locations, and provides a means to infer “missing” individuals from unsampled locations, and therefore obtain more accurate abundance estimates when it is not possible to sample all sites. This method is validated using simulations and is used to estimate abundance of the Eastern Canada-West Greenland (EC-WG) bowhead whale population. Based on these analyses, the estimated size of this population is 11,747 individuals during the sampling period, with a 95% highest density interval of 8,169–20,043.

As zooplanktivorous predators, bowhead whales (Balaena mysticetus) must routinely locate patches of prey that are energy-rich enough to meet their metabolic needs. However, little is known about how the quality and quantity of prey might influence their feeding behaviours. We addressed this question using a new approach that included: (1) multi-scale biologging and unmanned aerial system observations of bowhead whales in Cumberland Sound, Nunavut (Canada), and (2) an optical plankton counter (OPC) and net collections to identify and enumerate copepod prey species through the water column. The OPC data revealed two prey layers comprised almost exclusively of lipid-rich calanoid copepods. The deep layer contained fewer, but larger, particles (10% greater overall biomass) than the shallow prey layer. Dive data indicated that the whales conducted long deep Square-shaped dives (80% of dives; averaging depth of 260.4 m) and short shallow Square-shaped dives (16%; averaging depth of 22.5 m) to feed. The whales tended to dive proportionally more to the greater biomass of zooplankton that occurred at depth. Combining behavioural recordings with prey sampling showed a more complex feeding ecology than previously understood, and provides a means to evaluate the energetic balance of individuals under current environmental conditions. [ABSTRACT FROM AUTHOR]

Aim: Species distribution models (SDMs) are a widely used tool to estimate and map habitat suitability for wildlife populations. Most studies that model marine mammal density or distributions use oceanographic proxies for marine mammal prey. However, proxies could be a problem for forecasting because the relationships between the proxies and prey may change in a changing climate. We examined the use of model‐derived prey estimates in SDMs using an iconic species, the western Arctic bowhead whale (Balaena mysticetus). Location: Western Beaufort Sea, Alaska, USA. Methods: We used Biology Ice Ocean Modeling and Assimilation System (BIOMAS) to simulate ocean conditions important to western Arctic bowhead whales, including important prey species. Using both static and dynamic predictors, we applied Maxent and boosted regression tree (BRT) SDMs to predict bowhead whale habitat suitability on an 8‐day timescale. We compared results from models that used bathymetry with those that used only BIOMAS simulated variables. Results: The best model included bathymetry and BIOMAS variables. Inclusion of dynamic variables in SDMs produced predictions that reflected temporal dynamics evident from the survey data. Bathymetry was the most influential variable in models that included that variable. Zooplankton was the most important variable for models that did not include bathymetry. Models with bathymetry performed slightly better than models with only BIOMAS derived variables. Main conclusions: Bathymetry and modelled zooplankton were the most important predictor variables in bowhead whale distribution models. Our predictions reflected within‐year variability in bowhead whale habitat suitability. Using modelled prey availability, rather than oceanographic proxies, could be important for forecasting species distributions. Predictor variables used in our study were derived from a biophysical ocean model with demonstrated ability to project future ocean conditions. A natural next step is to use output from our biophysical ocean model to understand the effects of Arctic climate change. [ABSTRACT FROM AUTHOR]

Mouse and rats are staple model organisms that have been traditionally used for oncological studies; however, their short lifespan and highly prone to cancers limit their utilizationsin understanding the mechanisms of cancer resistance. In recent years, several studies of the non-standard long-lived mammalian species like naked mole rat (NMR) have provided new insights of mechanisms in natural anti-cancer. How long-lived species genetically maintain longevity and cancer-resistance remains largely elusive. To better understand the underlying anti-cancer mechanisms in long-lived mammals, we genome widely identified long noncoding RNA (lncRNA) transcripts of two longevous mammals, bowhead whale (BW, Balaena mysticetus) and Brandt's bat (BB, Myotis brandtii) and featured their sequence traits, expression patterns, and their correlations with cancer-resistance. Similar with naked mole rat (NMR, Heterocephalus glaber), the most long-lived rodent, BW and BB lncRNAs show low sequence conservation and dynamic expressions among tissues and physiological stages. By utilizing k-mers clustering, 75–136 of BW, BB and NMR lncRNAs were found in close relation (Pearson's r ≥0.9, p < 0.01) with human ageing diseases related lncRNAs (HAR-Lncs). In addition, we observed thousands of BB and BW lncRNAs strongly co-expressed (r > 0.8 or r <-0.8, p < 0.01) with potential tumour suppressors, indicating that lncRNAs are potentially involved in anti-cancer regulation in long-lived mammals. Our study provides the basis for lncRNA researches in perspectives of evolution and anti-cancer studies. Abbreviations: BW: bowhead whale; BB: Brandt's bat; NMR: naked mole rat; LLM: long-lived mammal; HTS: human tumour-suppressors; PTS: potential tumour suppressor; ARD: ageing related diseases; HAR-Lncs: lncRNAs that related with human ageing diseases; Kmer-lncs: lncRNAs in long-lived mammal species that corelated (Pearson'sr ≥0.9, p < 0.01) with the 10 HAR-Lncs by k-mers clustering; All-lncs: all the lncRNAs in long-lived mammal species; SDE-lncs: significant differentially expressed lncRNAs [ABSTRACT FROM AUTHOR]

Imagery and sighting data on bowhead whale (Balaena mysticetus) carcasses documented from 2009 to 2018 during aerial surveys in the eastern Chukchi and western Beaufort seas have provided evidence for killer whale (Orcinus orca) predation on bowhead whales of the Bering–Chukchi–Beaufort Seas stock. The Aerial Surveys of Arctic Marine Mammals (ASAMM) project provides information on distribution, behavior, and relative density of marine mammals. ASAMM surveys large areas of bowhead whale and killer whale summer and autumn habitat and offers consistent information on bowhead whale carcasses. Thirty-three bowhead whale carcasses were documented in July–October, from 2009 to 2018. Carcasses were distributed across the eastern Chukchi and western Beaufort seas from 141.6° W to 168.1° W and 68.9° N to 72.0° N. Carcass sighting rates (carcasses/1000 km) varied by month, year, and region. Statistical results suggest an alternating series of high and low annual carcass sighting rates. Eighteen bowhead whale carcasses having injuries consistent with probable killer whale predation were photo-documented: four each in 2016 and 2018, three each in 2013 and 2015, two in 2012, and one each in 2010 and 2017. Four carcasses, two in 2015 and one each in 2013 and 2018, were likely whales struck and lost during aboriginal subsistence hunting. Cause of death could not be determined for 11 carcasses. This study is the first systematic inquiry into non-harvest related mortality of bowhead whales in the U.S. Pacific Arctic and provides multi-year evidence for killer whale predation on bowhead whales in this portion of their range. [ABSTRACT FROM AUTHOR]

Abstract—The bay waters of the Sea of Okhotsk near the Shantar Islands are the most important summer grazing areas for bowhead whales (Balaena mysticetus) of the Okhotsk population. A hydrobiological survey during the period from July 12–28th, 2016, demonstrated that waters around the Shantar archipelago are characterized by high concentrations of humic substance supplied by the peat-laden banks of rivers flowing into the bays. The average chlorophyll concentrations in bottom waters of Uda and Academy bays were 1.1 and 4.3 mg/m3, respectively. Uda and Academy bays are mainly considered heterotrophic and autotrophic basins, respectively. The measured zooplankton biomass in Uda Bay ranged from 9.5 to 2513 mg/m3, averaging 736 mg/m3; the corresponding characteristics in Academy Bay were 0.38 to 3620 mg/m3, averaging 458 mg/m3. In the Shantar water area, copepods of the species Calanus glacialis were the dominant contributor in terms of zooplankton biomass and species abundance. During early summer, nine bowhead whales were sighted south off Feklistov Island and lone whales were recorded in the North Strait and at the mouth of Nikolai Bay. The low density of polar whales in the Shantar water area in early summer may be due to the low zooplankton biomass after spring bloom and the last spawning. [ABSTRACT FROM AUTHOR]

Polar bears (Ursus maritimus) from the southern Beaufort Sea (SB) subpopulation have traditionally fed predominantly upon ice‐seals; however, as the proportion of the subpopulation using onshore habitat has recently increased, foraging on land‐based resources, including remains of subsistence‐harvested bowhead whales (Balaena mysticetus) and colonial nesting seabirds has been observed. Adipose tissue samples were collected from this subpopulation during the springs of 2013–2016 and analyzed for fatty acid signatures. Diet estimates were generated for the proportional consumption of ringed seal (Pusa hispida), bearded seal (Erignathus barbatus), and beluga whale (Delphinapterus leucas), relative to onshore foods, including bowhead whale remains and seabird, as represented by black guillemot (Cepphus grylle mandtii) nestlings and eggs. Quantitative fatty acid signature analysis (QFASA) estimated that the ice‐obligate prey, ringed seal, remained the predominant prey species of SB polar bears (46.4 ± 1.8%), with much lower consumption of bearded seal (19.6 ± 2.0%), seabird (17.0 ± 1.2%), bowhead whale (15.0 ± 1.4%), and hardly any beluga whale (2.0 ± 0.5%). Adult and subadult females appeared to depend more on the traditional ringed seal prey than adult and subadult males. Diet estimates of SB polar bears showed significant interannual variability for all prey (F12, 456 = 3.17, p <.001). Longer‐term estimates suggested that both types of onshore prey, bowhead whale remains and seabird, have represented a moderate proportion of the food resources used by SB polar bears since at least the start of the 21st Century. [ABSTRACT FROM AUTHOR]

This study addresses the question: why do rats get cataracts at 2 years, dogs at 8 years, and whales do not develop cataracts for 200 years? Whale lens lipid phase transitions were compared with the phase transitions of other species that were recalculated. The major phospholipids of the whale lens were sphingolipids, mostly dihydrosphingomyelins with an average molar cholesterol/phospholipid ratio of 10. There was a linear correlation between the percentage of lens sphingolipid and lens lipid hydrocarbon chain order until about 60% sphingolipid. The percentage of lens sphingolipid correlated with the lens lipid phase transition temperature. The lifespan of the bowhead whale was the longest of the species measured and the percentage of whale lens sphingolipid fit well in the correlation between the percentage of lens sphingolipid and lifespan for many species. In conclusion, bowhead whale lens membranes have a high sphingolipid content that confers resistance to oxidation, allowing these lenses to stay clear relatively longer than many other species. The strong correlation between sphingolipid and lifespan may form a basis for future studies, which are needed because correlations do not infer cause. One could hope that if human lenses could be made to have a lipid composition similar to whales, like the bowhead, humans would not develop age-related cataracts for over 100 years.

Bowhead whales vocalize during their annual fall migration from the Beaufort Sea to the Bering Sea, but the calling rates of individual animals are so low that tracking an individual trajectory is impractical using passive acoustic methods. However, the travel speed and direction of the migrating population can be inferred on a statistical basis by cross-correlating time sequences of call density measured at two locations spaced several kilometers apart. By using the triangulation abilities of a set of vector sensors deployed offshore the Alaskan North Slope between 2008 and 2014, call density time sequences were generated from 1-km wide and 40-km tall rectangular "zones" that were separated by distances ranging from 3.5 to 15 km. The cross-covariances between the two sequences generate a peak corresponding to the average time it takes for whales to travel between the zones. Consistent westward travel speeds of ∼5 km/h were obtained from four different locations on 6 of the 7 years of the study, independent of whether the zones were separated by 3.5, 7, or 15 km. Some sites, however, also revealed a less prominent eastern movement of whales, and shifts in migration speed were occasionally detectable over week-long time scales., (© 2024 Acoustical Society of America.)

The Bering‐Chukchi‐Beaufort Seas (BCBS) bowhead whale (Balaena mysticetus) has been considered at low‐risk for entanglement injuries and ship strikes because their range is mainly north of commercial fisheries; nevertheless, changes to their arctic habitat, including a longer open water period and declining sea ice, have resulted in increasing commercial activity and concern about fisheries interactions. We examined interyear matches (between 1985 and 2011) from a photo identification project and identified whales that had acquired entanglement injuries. We estimated the probability of a bowhead acquiring an entanglement injury using two statistical methods: interval censored survival analysis and a simple binomial model. Both methods give similar results, suggesting a 2.2% (95% CI: 1.1%–3.3%) annual probability of acquiring a scar. We also include an entanglement scar frequency analysis of aerial photographs from the 2011 spring and fall surveys near Point Barrow, Alaska, which suggest 12.4% of live bowheads show evidence of entanglement scarring. Entanglement rates for the BCBS bowhead stock are lower than many other large whale stocks, and abundance has increased over the past 35 yr; however, our findings indicate that fishing gear entanglement is a more serious concern for the BCBS bowhead whale population than previously thought. [ABSTRACT FROM AUTHOR]