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Research about Bering Sea, Chukchi Sea

Source-linked reports with geographic coverage including Bering Sea, Chukchi Sea.

11 recordsLinked to original sources
USGS2026

A diatom-based quantitative sea-ice proxy for the Bering and Chukchi seas

Sea ice affects Earth's climate system on both regional and global scales. Its incorporation into climate can be used to achieve more accurate predictions of future climate. However, instrumental records of sea-ice concentration do not extend earlier than 1978. In an effort to extend this record, we constructed a proxy using the generalized additive model based on relative abundances of five easy-to-identify diatom species found in sediment samples across the Bering and Chukchi seas. Here we present the first quantitative diatom-based sea-ice proxy developed for Beringia. The developed proxy has been applied to two sediment cores in the Bering Sea ranging from 0 to 25.7 ka (HLY0204 51JPC) and 369 to 430 ka (IODP Exp 323 Site U1345) and one in the Chukchi Sea ranging from 2.7 to 10 ka (HLY0204 24JPC). The obtained reconstructions of sea-ice concentrations are similar, but not identical to previously published qualitative and nearby records based on other proxies. Because our results are quantitative, they can be incorporated into regional climate models. The proxy is publicly available as an R Shiny application (app) and can be applied to any diatom count from marine sediments in the region.

Bering Sea, Chukchi Sea↗
USGS2025

Monitoring Pacific walrus coastal haulouts by satellite to estimate herd abundance and distribution

The Pacific walrus ( Odobenus rosmarus divergens ) has a single, panmictic stock that ranges across the Bering and Chukchi Seas. However, its seasonal distribution is incompletely described, particularly in autumn when herds gather on shore, and abundance is of interest to management entities. We monitored walrus herds using satellite imagery on shore across their summer and autumn range in the Chukchi Sea to provide insights on seasonal distribution and abundance. During each study year (2017–2024), we documented walrus herd abundance at 8 Chukchi Sea haulouts based on the herd area detected in satellite imagery multiplied by herd density estimates derived from aerial survey data. In contrast to historical seasonal use, we found large herds on shore at only 3 sites, 1 in Alaska and 2 in northern Chukotka (Russia). In 2022, we observed a very large herd with an abundance (and 90% prediction interval) of 184,000 (min–max = 153,000–214,000) northwest of the Bering Strait, which enabled us to estimate a minimum population size (N min ) by correcting the abundance estimate by the proportion of walruses that may be hauled out and available for detection. Our estimate of 250,000 was commensurate with the N min estimate (214,000) from a 2013–2017 Pacific walrus genetic mark-recapture study.

Alaska↗
USGS2025

Prevalence of pelagic diatoms and harmful algae in tellinid bivalve diets during record low sea ice in the Pacific Arctic determined by DNA metabarcoding

Understanding changes at the base of the marine food web in the rapidly transforming Arctic is essential for predicting and evaluating ecosystem dynamics. The northern Bering Sea experienced record low sea ice in 2018, followed by the second lowest in 2019, highlighting the urgency of the issue for this region. In this study, we investigated the diet of the clam Macoma calcarea in the Pacific Arctic using DNA metabarcoding, employing 18S and rbcL markers to identify dietary components. Our findings revealed a strong dependence on pelagic diatoms, particularly Chaetoceros sp., with a near absence of ice algae in the clam diet. This pattern reflects the lack of lipid-rich ice algal production during these low sea ice events. Additionally, our analysis detected algae capable of producing harmful toxins, notably Alexandrium dinoflagellates, in the clam diet, underscoring the need for increased monitoring due to potential ecosystem and human health risks. This study demonstrates the utility of DNA metabarcoding in unraveling the complex dynamics of Arctic marine food webs and pelagic-benthic coupling, providing a glimpse of future conditions in a rapidly changing environment.

Bering Sea, Chukchi Sea↗
USGS2024

Photogrammetry-based body condition for monitoring an Arctic marine mammal experiencing habitat loss

Monitoring animal body condition can provide insight on population responses to environmental change. Pacific walruses ( Odobenus rosmarus divergens ) are experiencing loss of their sea ice habitat which has decreased the time that females spend foraging during a critical period of pregnancy and lactation. Here we investigate the potential for body condition to track demographic change and be monitored via two-dimensional aerial imagery by (1) examining whether walrus somatic growth and body mass data tracked estimated historic demographic changes, (2) collecting morphometric and body mass data and aerial imagery of walruses in human care to determine if sex, age group, and body size and condition can be determined from imagery, and (3) examining aerial imagery from a large coastal haulout used primarily by females and young to estimate potential sample sizes of measurable walruses. Body mass and growth in body length decreased between the last 1970s and early 1980s concurrent with a period when the population apparently approached carrying capacity and subsequently declined. Measures from aerial imagery (1) accurately distinguished reproductive age females from subadults and adult males and (2) enabled body mass estimates with 6-7% error using either areal footprint or a combination of length and width. We found a mean of 216 ± 77 walruses appropriately positioned for measurement from aerial surveys of the haulout enabling measurements of ≥7000 individuals annually via repeated daily imagery. Our results suggest that body mass of reproductive age females and growth of dependent young may be useful indicators to augment monitoring of the Pacific walrus population and can be achieved via non-invasive aerial imagery collections.

Alaska↗
USGS2023

Partnering in search of answers: Seabird die-offs in the Bering and Chukchi Seas

Prior to 2015, seabird die-offs in Alaskan waters were rare; they typically occurred in mid-winter, linked to epizootic disease events or above-average ocean temperatures associated with strong El Nino-Southern Oscillation events (Bodenstein et al. 2015, Jones et al. 2019, Romano et al. 2020). Since 2015, the U.S. Fish and Wildlife Service (USFWS) has monitored mortality events that have become annual occurrences in Alaska (Fig. 1). Since 2017, communities on the coasts of the northern Bering and southern Chukchi Seas have annually observed dead and dying seabirds along their coasts, although such die-offs have not been reported from communities north of Point Hope. (Fig. 2). Affected species included planktivorous birds such as auklets ( Aethia spp.) and shearwaters ( Ardenna spp.), piscivorous murres ( Uria spp.), puffins ( Fratercula spp.), and kittiwakes ( Rissa spp.), as well as low numbers of benthic feeding sea ducks ( Somateria spp.). The range of seabird species and the different prey species involved, with localized events throughout summer and over widespread areas, indicate environmental causes at multiple trophic levels. Such wildlife mortality events are a public health concern for coastal communities that rely on ocean resources for their nutritional, cultural, and economic well-being. They have also been seen as a harbinger of concern for the state of the Arctic Ocean itself.

Alaska↗
USGS2022

Estimating Pacific walrus abundance and survival with multievent mark-recapture models

Arctic marine ecosystems are undergoing rapid physical and biological change associated with climate warming and loss of sea ice. Sea ice loss will impact many species through altered spatial and temporal availability of resources. In the Bering and Chukchi Seas, the Pacific walrus Odobenus rosmarus divergens is one species that could be impacted by rapid environmental change, and thus, population assessments are needed to monitor changes in the status of this ecologically and culturally important marine mammal. We conducted a 5 yr genetic mark-recapture study to estimate demographic parameters for the Pacific walrus. We developed a Bayesian multievent mark-recapture model to estimate walrus survival and abundance while accounting for age misclassification. We estimated the probability of juvenile annual survival as 0.63 (95% credible interval [CrI]: 0.39-0.87) and adult female annual survival as 0.90 (95% CrI: 0.74-1.00). We estimated total abundance as 257 193 (95% CrI: 171 138-366 366). We provide the first estimate of total Pacific walrus abundance since an aerial survey in 2006, which generated a substantially less precise total population size estimate (129 000; 95% CI: 55 000-507 000). The emerging ecosystem state in the northern Bering and Chukchi Seas will likely result in a decline in Pacific walrus abundance, but there is substantial uncertainty regarding the magnitude of the anticipated decline. Our demographic estimates provide critical information to evaluate future population trends of this subsistence resource vital to communities that border the Bering and Chukchi Seas in the USA and Russia.

Alaska↗
USGS2020

DNA metabarcoding of feces to infer summer diet of Pacific walruses

Environmental conditions in the Chukchi Sea are changing rapidly and may alter the abundance and distribution of marine species and their benthic prey. We used a metabarcoding approach to identify potentially important prey taxa from Pacific walrus ( Odobenus rosmarus divergens ) fecal samples ( n = 87). Bivalvia was the most dominant class of prey (66% of all normalized counts) and occurred in 98% of the samples. Polychaeta and Gastropoda occurred in 70% and 62% of the samples, respectively. The remaining nine invertebrate classes comprised <21% of all normalized counts. The common occurrence of these three prey classes is consistent with examinations of walrus stomach contents. Despite these consistencies, biases in the metabarcoding approach to determine diet from feces have been highlighted in other studies and require further study, in addition to biases that may have arisen from our opportunistic sampling. However, this noninvasive approach provides accurate identification of prey taxa from degraded samples and could yield much‐needed information on shifts in walrus diet in a rapidly changing Arctic.

Alaska↗
USGS2016

Effects of Lead Exposure, Environmental Conditions, and Metapopulation Processes on Population Dynamics of Spectacled Eiders.

Spectacled eider Somateria fischeri numbers have declined and they are considered threatened in accordance with the US Endangered Species Act throughout their range. We synthesized the available information for spectacled eiders to construct deterministic, stochastic, and metapopulation models for this species that incorporated current estimates of vital rates such as nest success, adult survival, and the impact of lead poisoning on survival. Elasticities of our deterministic models suggested that the populations would respond most dramatically to changes in adult female survival and that the reductions in adult female survival related to lead poisoning were locally important. We also examined the sensitivity of the population to changes in lead exposure rates. With the knowledge that some vital rates vary with environmental conditions, we cast stochastic models that mimicked observed variation in productivity. We also used the stochastic model to examine the probability that a specific population will persist for periods of up to 50 y. Elasticity analysis of these models was consistent with that for the deterministic models, with perturbations to adult female survival having the greatest effect on population projections. When used in single population models, demographic data for some localities predicted rapid declines that were inconsistent with our observations in the field. Thus, we constructed a metapopulation model and examined the predictions for local subpopulations and the metapopulation over a wide range of dispersal rates. Using the metapopulation model, we were able to simulate the observed stability of local subpopulations as well as that of the metapopulation. Finally, we developed a global metapopulation model that simulates periodic winter habitat limitation, similar to that which might be experienced in years of heavy sea ice in the core wintering area of spectacled eiders in the central Bering Sea. Our metapopulation analyses suggested that no subpopulation is independent and that future management actions may be improved through a metapopulation framework. For example, management actions could include displacement of breeding females from"sink" areas that reduce the growth potential of the population as a whole. However, this action is contingent upon dispersal among local populations, for which there is limited information. Thus, we recommend that researchers examine dispersal behavior among areas on the Yukon-Kuskokwim Delta in western Alaska. The metapopulation framework could also be applied at the rangewide scale to address the density-dependent limitation of available polynya habitat during winter that may limit the recovery of small subpopulations, such as that on the Yukon-Kuskokwim Delta. Reductions in other subpopulations may be necessary to ensure an increase in the Yukon-Kuskokwim Delta population. Thus, we recommend that managers consider the interpopulation dynamics of spectacled eiders at different spatial scales in future management actions.

Alaska↗
USGS2010

Arctic sea ice decline: Projected changes in timing and extent of sea ice in the Bering and Chukchi Seas

The Arctic region is warming faster than most regions of the world due in part to increasing greenhouse gases and positive feedbacks associated with the loss of snow and ice cover. One consequence has been a rapid decline in Arctic sea ice over the past 3 decades?a decline that is projected to continue by state-of-the-art models. Many stakeholders are therefore interested in how global warming may change the timing and extent of sea ice Arctic-wide, and for specific regions. To inform the public and decision makers of anticipated environmental changes, scientists are striving to better understand how sea ice influences ecosystem structure, local weather, and global climate. Here, projected changes in the Bering and Chukchi Seas are examined because sea ice influences the presence of, or accessibility to, a variety of local resources of commercial and cultural value. In this study, 21st century sea ice conditions in the Bering and Chukchi Seas are based on projections by 18 general circulation models (GCMs) prepared for the fourth reporting period by the Intergovernmental Panel on Climate Change (IPCC) in 2007. Sea ice projections are analyzed for each of two IPCC greenhouse gas forcing scenarios: the A1B `business as usual? scenario and the A2 scenario that is somewhat more aggressive in its CO2 emissions during the second half of the century. A large spread of uncertainty among projections by all 18 models was constrained by creating model subsets that excluded GCMs that poorly simulated the 1979-2008 satellite record of ice extent and seasonality. At the end of the 21st century (2090-2099), median sea ice projections among all combinations of model ensemble and forcing scenario were qualitatively similar. June is projected to experience the least amount of sea ice loss among all months. For the Chukchi Sea, projections show extensive ice melt during July and ice-free conditions during August, September, and October by the end of the century, with high agreement among models. High agreement also accompanies projections that the Chukchi Sea will be completely ice covered during February, March, and April at the end of the century. Large uncertainties, however, are associated with the timing and amount of partial ice cover during the intervening periods of melt and freeze. For the Bering Sea, median March ice extent is projected to be about 25 percent less than the 1979-1988 average by mid-century and 60 percent less by the end of the century. The ice-free season in the Bering Sea is projected to increase from its contemporary average of 5.5 months to a median of about 8.5 months by the end of the century. A 3-month longer ice- free season in the Bering Sea is attained by a 1-month advance in melt and a 2-month delay in freeze, meaning the ice edge typically will pass through the Bering Strait in May and January at the end of the century rather than June and November as presently observed.

Alaska↗
USGS2003

Advection, pelagic food webs and the biogeography of seabirds in Beringia

Despite its great distance from productive shelf-edge habitat, the inner shelf area of the Bering Sea, from St. Lawrence Island to the Bering Strait, supports a surprisingly large number (>5 million) of seabirds during summer, mostly small plantivorous auklets (65%) and large piscivorous murres (19%) and kittiwakes (5%). This paradox of seabird biogeography is explained by the Anadyr “Green Belt” - a current that advects nutrients and plankton over 1200 km from the outer Bering Sea shelf-edge to the central Chukchi Sea. Turbulent upwelling of this nutrient-rich water at Anadyr and Bering straits further enhances high levels of primary production (360 gC m -2 y -1 ) and helps sustain the enormous biomass of zooplankton entrained in the Anadyr Current. Primary production in adjacent waters of the Chukchi Sea (420 gC m -2 y -1 ) exceeds that observed below Bering Strait, and zooplankton are equally abundant. Auklets account for 49% of total food consumption below Bering Strait (411 mt d -1 ), whereas piscivores dominate (88% of 179 mt d -1 ) in the Chukchi Sea. Of 2 million seabirds in the Chukchi region, auklets (6%) are supplanted by planktivorous phalaropes (25%), and piscivorous murres (38%) and kittiwakes (15%). Average carbon flux to seabirds (0.65 mgC m -2 d -1 ) over the whole region is more typical of upwelling than shelf ecosystems. The pelagic distribution of seabirds in the region appears to be a function of advection, productivity and water column stability. Planktivores flourish in areas with high zooplankton concentrations on the edge of productive upwelling and frontal zones along the “Green Belt”, whereas piscivores avoid turbulent, mixed waters and forage in stable, stratified waters along the coast and in the central Chukchi Sea.

Alaska↗