Spatially mapped reductions in the length of the Arctic sea ice season

The Impact of Sea Ice Loss on Benthic Communities of the Makarov Strait (Northeastern Barents Sea)

The continental shelf of the northeastern Barents Sea is presently experiencing a weak influx of Atlantic water from the west. In recent times, warming in Arctic regions has led to an increase in extended ice-free periods in this area, instead of significantly elevating water temperatures. The implications of this phenomenon on the structure and functioning of benthic communities were investigated during the autumn of 2019 within the Makarov Strait, located in the southwestern part of the St. Anna Trough. The macrozoobenthic communities exhibited a clear connection with the duration of ice-free periods. This variable influenced a vertical carbon flux, which subsequently served as the primary predictor for faunal abundance and diversity, as demonstrated by redundancy and correlation analyses. Two faunal groups were identified, corresponding to short and long open-water periods. Both groups had similar alpha diversity (65 ± 6 and 61 ± 9 species per station) and biomasses (39 ± 13 and 47 ± 13 g m^-2) but displayed differing abundances (1140 ± 100 vs. 4070 ± 790 ind. m^-2) and other diversity indices. We observed a decline in the proportion of polychaetes, accompanied by an increase in the proportion and diversity of bivalves, as well as a rise in the abundance of infaunal species, sub-surface deposit feeders, and mobile suspension feeders, in response to the increasing vertical carbon flux. The potential increase in anthropogenic pressures related to oil development in the northeastern Barents Sea highlights the importance of our study for conservation and monitoring efforts in the region.

Evaluation of 2-m Air Temperature and Surface Temperature from ERA5 and ERA-I Using Buoy Observations in the Arctic during 2010–2020

In data-sparse regions such as the Arctic, atmospheric reanalysis is one of the key tools for understanding rapid climate change at the regional and global scales. The utility of reanalysis datasets based on data assimilation is affected by their accuracy and biases. Therefore, it is important to evaluate their performance. Here, we conduct inter-comparisons of two temperature variables, namely, the 2-m air temperature (Ta) and the surface temperature (Ts), from the widely used ERA-I and ERA5 reanalysis datasets provided by the European Centre for Medium-Range Weather Forecasts (ECMWF) against in situ observations from three international buoy programs (i.e., the International Arctic Buoy Programme (IABP), the Multidisciplinary Drifting Observatory for the Study of Arctic Climate (MOSAiC), and the Cold Regions Research and Engineering Laboratory (CRREL)) during 2010–2020 in the Arctic. Overall, the results show that both the ERA-I and ERA5 were well correlated with the buoy observations, with the highest correlation coefficient reaching 0.98. There were generally warm Ta biases for both ERA-I (2.27 ± 3.33 °C) and ERA5 (2.34 ± 3.22 °C) when compared with more than 3000 matching pairs of daily buoy observations. The warm Ta biases of both reanalysis datasets exhibited seasonal variations, reaching the maximum of 3.73 ± 2.84 °C in April and the minimum of 1.36 ± 2.51 °C in September. For Ts, both ERA-I and ERA5 exhibited good consistencies with the buoy observations, but have higher amplitude biases compared with those for Ta, with generally negative biases of −4.79 ± 4.86 °C for ERA-I and −4.11 ± 3.92 °C for ERA5. For both reanalysis datasets, the largest bias of Ts (−11.18 ± 3.08 °C) occurred in December, while the biases were rather small (less than −3 °C) in the warmer months (April to October). The cold Ts biases for ERA-I and ERA5 were probably overestimated due to the location of the surface temperature sensors on the buoys, which may have been affected by snow cover. Both the Ta and Ts biases varied for different buoy programs and different sea ice concentration conditions, yet they exhibited similar trends.

Migration dynamics of polar bears (Ursus maritimus) in western Hudson Bay

Migration is predicted to change both spatially and temporally as climate change alters seasonal resource availability. Species in extreme environments are especially susceptible to climate change; hence, it is important to determine environmental and biological variables that influence their migration. Polar bears (Ursus maritimus) are an Arctic apex carnivore whose migration phenology has been affected by climate change and is vulnerable to future changes. Here, we used satellite-linked telemetry collar data from adult female polar bears in western Hudson Bay from 2004 to 2016 and multivariate response regression models to demonstrate that 1) spatial and temporal migration metrics are correlated, 2) ice concentration and wind are important environmental variables that influence polar bear migration in seasonal ice areas, and 3) migration did not vary across the years of our study, highlighting the importance of continued monitoring. Specifically, we found that ice concentration, wind speed, and wind direction affected polar bear migration onto ice during freeze-up and ice concentration and wind direction affected migration onto land during breakup. Bears departed from land earlier with increased wind speed and the effect of wind direction on migration may be linked to prey searching and ice drift. Low ice concentration was associated with higher movement during freeze-up and breakup. Our findings suggest that migration movement may increase in response to climate change as ice concentration and access to prey declines, potentially increasing nutritional stress on bears.

Delay in Arctic Sea Ice Freeze-Up Linked to Early Summer Sea Ice Loss: Evidence from Satellite Observations

The past decades have witnessed a rapid loss of the Arctic sea ice and a significant lengthening of the melt season. The years with the lowest summertime sea ice minimum were found to be accompanied by the latest freeze-up onset on record. Here, a synthetic approach is taken to examine the connections between sea ice melt timing and summer sea ice evolution from the remote sensing perspective. A 40-year (1979–2018) satellite-based time-series analysis shows that the date of autumn sea ice freeze-up is significantly correlated with the sea ice extent in early summer (r = −0.90, p < 0.01), while the spring melt onset is not a promising predictor of summer sea ice evolution. The delay in Arctic sea ice freeze-up (0.61 days year−1) in the Arctic was accompanied by a decline in surface albedo (absolute change of −0.13% year−1), an increase in net short-wave radiation (0.21 W m−2 year−1), and an increase in skin temperature (0.08 °C year−1) in summer. Sea ice loss would be the key reason for the delay in autumn freeze-up, especially in the Laptev, East-Siberian, Chukchi and Beaufort Seas, where sea ice has significantly declined throughout the summer, and strong correlations were found between the freeze-up onset and the solar radiation budget since early summer. This study highlights a connection between the summer sea ice melting and the autumn refreezing process through the ice-albedo feedback based on multisource satellite-based observations.

A Comparison of Decimeter Scale Variations of Physical and Photobiological Parameters in a Late Winter First-Year Sea Ice in Southwest Greenland

Small-scale variation in the physical and biological properties of sea ice was examined by collecting nine sea ice cores within 1 m2 in a land-fast first-year ice in southwest Greenland in late winter. Cores were sectioned in four segments and sea ice physical, biological, and photobiological parameters were measured. The main purpose was to explore the decimeter-scale horizontal and vertical variations in common sea ice parameters. ANOVA analyses revealed significant within-core variations for bulk salinity, brine salinity, brine volume, gas volume, chlorophyll a (Chl a), and the maximum light-limited photosynthetic efficiency (α). Only temperature and bulk salinity variations were significant between cores, and no significant variations were found within or between cores for other photobiological parameters. Power analyses were applied to determine the number of replicates needed to achieve a significance at p < 0.05 with sufficient power, and showed a minimum of four and preferably five replicate cores to detect the observed variability in this first-year ice. It is emphasized that these results only apply to this type of first-year ice in late winter/early spring, and that different variations may apply to other types of ice.

The stress of Arctic warming on polar bears

Arctic ecosystems are changing rapidly in response to climate warming. While Arctic mammals are highly evolved to these extreme environments, particularly with respect to their stress axis, some species may have limited capacity to adapt to this change. We examined changes in key components of the stress axis (cortisol and its carrier protein-corticosteroid binding globulin [CBG]) in polar bears (Ursus maritimus) from western Hudson Bay (N = 300) over a 33 year period (1983-2015) during which time the ice-free period was increasing. Changing sea ice phenology limits spring hunting opportunities and extends the period of onshore fasting. We assessed the response of polar bears to a standardized stressor (helicopter pursuit, darting, and immobilization) during their onshore fasting period (late summer-autumn) and quantified the serum levels of the maximum corticosteroid binding capacity (MCBC) of CBG, the serum protein that binds cortisol strongly, and free cortisol (FC). We quantified bear condition (age, sex, female with cubs or not, fat condition), sea ice (breakup in spring-summer, 1 year lagged freeze-up in autumn), and duration of fasting until sample collection as well as cumulative impacts of the latter environmental traits from the previous year. Data were separated into "good" years (1983-1990) when conditions were thought to be optimal and "poor" years (1991-2015) when sea ice conditions deteriorated and fasting on land was extended. MCBC explained 39.4% of the variation in the good years, but only 28.1% in the poor ones, using both biological and environmental variables. MCBC levels decreased with age. Changes in FC were complex, but more poorly explained. Counterintuitively, MCBC levels increased with increased time onshore, 1 year lag effects, and in poor ice years. We conclude that MCBC is a biomarker of stress in polar bears and that the changes we document are a consequence of climate warming.

Comparing sea ice habitat fragmentation metrics using integrated step selection analysis

Habitat fragmentation occurs when continuous habitat gets broken up as a result of ecosystem change. While commonly studied in terrestrial ecosystems, Arctic sea ice ecosystems also experience fragmentation, but are rarely studied in this context. Most fragmentation analyses are conducted using patch-based metrics, which are potentially less suitable for sea ice that has gradual changes between sea ice cover, than distinct "long-term" patches. Using an integrated step selection analysis, we compared the descriptive power of a patch-based metric to a more novel metric, the variation in local spatial autocorrelation over time. We used satellite telemetry data from 39 adult female polar bears (Ursus maritimus) in Hudson Bay to examine their sea ice habitat using Advanced Microwave Scanning Radiometer 2 data during sea ice breakup in May through July from 2013-2018. Spatial autocorrelation resulted in better model fits across 64% of individuals, although both metrics were more effective in describing movement patterns than habitat selection. Variation in local spatial autocorrelation allows for the visualization of sea ice habitat at complex spatial and temporal scales, condensing a targeted time period of habitat that would otherwise have to be analyzed daily.

Interrelated ecological impacts of climate change on an apex predator

Climate change has broad ecological implications for species that rely on sensitive habitats. For some top predators, loss of habitat is expected to lead to cascading behavioral, nutritional, and reproductive changes that ultimately accelerate population declines. In the case of the polar bear (Ursus maritimus), declining Arctic sea ice reduces access to prey and lengthens seasonal fasting periods. We used a novel combination of physical capture, biopsy darting, and visual aerial observation data to project reproductive performance for polar bears by linking sea ice loss to changes in habitat use, body condition (i.e., fatness), and cub production. Satellite telemetry data from 43 (1991-1997) and 38 (2009-2015) adult female polar bears in the Baffin Bay subpopulation showed that bears now spend an additional 30 d on land (90 d in total) in the 2000s compared to the 1990s, a change closely correlated with changes in spring sea ice breakup and fall sea ice formation. Body condition declined for all sex, age, and reproductive classes and was positively correlated with sea ice availability in the current and previous year. Furthermore, cub litter size was positively correlated with maternal condition and spring breakup date (i.e., later breakup leading to larger litters), and negatively correlated with the duration of the ice-free period (i.e., longer ice-free periods leading to smaller litters). Based on these relationships, we projected reproductive performance three polar bear generations into the future (approximately 35 yr). Results indicate that two-cub litters, previously the norm, could largely disappear from Baffin Bay as sea ice loss continues. Our findings demonstrate how concurrent analysis of multiple data types collected over long periods from polar bears can provide a mechanistic understanding of the ecological implications of climate change. This information is needed for long-term conservation planning, which includes quantitative harvest risk assessments that incorporate estimated or assumed trends in future environmental carrying capacity.

Spatial and temporal variability in ringed seal (Pusa hispida) stable isotopes in the Beaufort Sea

Arctic ecosystem dynamics are shifting in response to warming temperatures and sea ice loss. Such ecosystems may be monitored by examining the diet of upper trophic level species, which varies with prey availability. To assess interannual variation in the Beaufort Sea ecosystem, we examined spatial and temporal trends in ringed seal (Pusa hispida) δ13C and δ15N in claw growth layers grown from 1964 to 2011. Stable isotopes were correlated with climate indices, environmental conditions, seal population productivity, and geographic location. Sex and age did not influence stable isotopes. Enriched 13C was linked to cyclonic circulation regimes, seal productivity, and westward sampling locations. Higher δ15N was linked to lower sea surface temperatures, a higher percentage of pups in the subsistence harvest, and sample locations that were eastward and further from shore. From the 1960s to 2000s, ringed seal niche width expanded, suggesting a diversification of diet due to expansion of prey and/or seal space use. Overall, trends in ringed seal stable isotopes indicate changes within the Beaufort Sea ecosystem affected by water temperatures and circulation regimes. We suggest that continued monitoring of upper trophic level species will yield insights into changing ecosystem structure with climate change.

Seasonal Variations of Arctic Low-Level Clouds and Its Linkage to Sea Ice Seasonal Variations

Using CALIPSO-CloudSat-Clouds and the Earth's Radiant Energy System-Moderate Resolution Imaging Spectrometer data set, this study documents the seasonal variation of sea ice, cloud, and atmospheric properties in the Arctic (70°N-82°N) for 2007-2010. A surface-type stratification-consisting Permanent Ocean, Land, Permanent Ice, and Transient Sea Ice-is used to investigate the influence of surface type on low-level Arctic cloud liquid water path (LWP) seasonality. The results show significant variations in the Arctic low-level cloud LWP by surface type linked to differences in thermodynamic state. Subdividing the Transient Ice region (seasonal sea ice zone) by melt/freeze season onset dates reveals a complex influence of sea ice variations on low cloud LWP seasonality. We find that lower tropospheric stability is the primary factor affecting the seasonality of cloud LWP. Our results suggest that variations in sea ice melt/freeze onset have a significant influence on the seasonality of low-level cloud LWP by modulating the lower tropospheric thermal structure and not by modifying the surface evaporation rate in late spring and midsummer. We find no significant dependence of the May low-level cloud LWP peak on the melt/freeze onset dates, whereas and September/October low-level cloud LWP maximum shifts later in the season for earlier melt/later freeze onset regions. The Arctic low cloud LWP seasonality is controlled by several surface-atmosphere interaction processes; the importance of each varies seasonally due to the thermodynamic properties of sea ice. Our results demonstrate that when analyzing Arctic cloud-sea ice interactions, a seasonal perspective is critical.

Modeling optimal responses and fitness consequences in a changing Arctic

Animals must balance a series of costs and benefits while trying to maximize their fitness. For example, an individual may need to choose how much energy to allocate to reproduction versus growth, or how much time to spend on vigilance versus foraging. Their decisions depend on complex interactions between environmental conditions, behavioral plasticity, reproductive biology, and energetic demands. As animals respond to novel environmental conditions caused by climate change, the optimal decisions may shift. Stochastic dynamic programming provides a flexible modeling framework with which to explore these trade-offs, but this method has not yet been used to study possible changes in optimal trade-offs caused by climate change. We created a stochastic dynamic programming model capturing trade-off decisions required by an individual adult female polar bear (Ursus maritimus) as well as the fitness consequences of her decisions. We predicted optimal foraging decisions throughout her lifetime as well as the energetic thresholds below which it is optimal for her to abandon a reproductive attempt. To explore the effects of climate change, we shortened the spring feeding period by up to 3 weeks, which led to predictions of riskier foraging behavior and higher reproductive thresholds. The resulting changes in fitness may be interpreted as a best-case scenario, where bears adapt instantaneously and optimally to new environmental conditions. If the spring feeding period was reduced by 1 week, her expected fitness declined by 15%, and if reduced by 3 weeks, expected fitness declined by 68%. This demonstrates an effective way to explore a species' optimal response to a changing landscape of costs and benefits and highlights the fact that small annual effects can result in large cumulative changes in expected lifetime fitness.

Are polar bear habitat resource selection functions developed from 1985-1995 data still useful?

Greenhouse-gas-induced warming in the Arctic has caused declines in sea ice extent and changed its composition, raising concerns by all circumpolar nations for polar bear conservation.Negative impacts have been observed in three well-studied polar bear subpopulations. Most subpopulations, however, receive little or no direct monitoring, hence, resource selection functions (RSF) may provide a useful proxy of polar bear distributions. However, the efficacy of RSFs constructed from past data, that is, reference RSFs, may be degraded under contemporary conditions, especially in a rapidly changing environment.We assessed published Arctic-wide reference RSFs using tracking data from adult female polar bears captured in the Beaufort Sea. We compared telemetry-derived seasonal distributions of polar bears to RSF-defined optimal sea ice habitat during the period of RSF model development, 1985-1995, and two subsequent periods with diminished sea ice: 1996-2006 and 2007-2016. From these comparisons, we assessed the applicability of the reference RSFs for contemporary polar bear conservation.In the two decades following the 1985-1995 reference period, use and availability of optimal habitat by polar bears declined during the ice melt, ice minimum, and ice growth seasons. During the ice maximum season (i.e., winter), polar bears used the best habitat available, which changed relatively little across the three decades of study. During the ice melt, ice minimum, and ice growth seasons, optimal habitat in areas used by polar bears decreased and was displaced north and east of the Alaska Beaufort Sea coast. As optimal habitat diminished in these seasons, polar bears expanded their range and occupied greater areas of suboptimal habitat.Synthesis and applications: Sea ice declines due to climate change continue to challenge polar bears and their conservation. The distribution of Southern Beaufort Sea polar bears remained similar during the ice maximum season, so the reference RSFs developed from data collected >20 years ago continue to accurately model their winter distribution. In contrast, reference RSFs for the ice transitional and minimum seasons showed diminished predictive efficacy but were useful in revealing that contemporary polar bears have been increasingly forced to use suboptimal habitats during those seasons.

Ringed seal demography in a changing climate

Climate change is affecting species' distributions and abundances worldwide. Baseline population estimates, against which future observations may be compared, are necessary if we are to detect ecological change. Arctic sea ice ecosystems are changing rapidly and we lack baseline population estimates for many ice-associated species. Provided we can detect them, changes in Arctic marine ecosystems may be signaled by changes in indicator species such as ringed seals (Pusa hispida). Ringed seal monitoring has provided estimates of survival and fertility rates, but these have not been used for population-level inference. Using matrix population models, we synthesized existing demographic parameters to obtain estimates of historical ringed seal population growth and structure in Amundsen Gulf and Prince Albert Sound, Canada. We then formalized existing hypotheses about the effects of emerging environmental stressors (i.e., earlier spring ice breakup and reduced snow depth) on ringed seal pup survival. Coupling the demographic model to ice and snow forecasts available from the Coupled Model Intercomparison Project resulted in projections of ringed seal population size and structure up to the year 2100. These projections showed median declines in population size ranging from 50% to 99%. Corresponding to these projected declines were substantial changes in population structure, with increasing proportions of ringed seal pups and adults and declining proportions of juveniles. We explored if currently collected, harvest-based data could be used to detect the projected changes in population stage structure. Our model suggests that at a present sample size of 100 seals per year, the projected changes in stage structure would only be reliably detected by mid-century, even for the most extreme climate models. This modeling process revealed inconsistencies in existing estimates of ringed seal demographic rates. Mathematical population models such as these can contribute both to understanding past population trends as well as predicting future ones, both of which are necessary if we are to detect and interpret future observations.

Temporal Means and Variability of Arctic Sea Ice Melt and Freeze Season Climate Indicators Using a Satellite Climate Data Record

Information on the timing of Arctic snow and ice melt onset, sea ice opening, retreat, advance, and closing, can be beneficial to a variety of stakeholders. Sea ice modelers can use information on the evolution of the ice cover through the rest of the summer to improve their seasonal sea ice forecasts. The length of the open water season (as derived from retreat/advance dates) is important for human activities and for wildlife. Long-term averages and variability of these dates as climate indicators are beneficial to business strategic planning and climate monitoring. In this study, basic characteristics of temporal means and variability of Arctic sea ice climate indicators derived from a satellite-based climate data record from March 1979 to February 2017 melt and freeze seasons are described. Our results show that, over the Arctic region, anomalies of snow and ice melt onset, ice opening and retreat dates are getting earlier in the year at a rate of more than 5 days per decade, while that of ice advance and closing dates are getting later at a rate of more than 5 days per decade. These significant trends resulted in significant upward trends for anomalies of inner and outer ice-free periods at a rate of nearly 12 days per decade. Small but significant downward trends of seasonal ice loss and gain period anomalies were also observed at a rate of −1.48 and −0.53 days per decade, respectively. Our analyses also demonstrated that the means of these indicators and their trends are sensitive to valid data masks and regional averaging methods.

Sea-ice loss boosts visual search: fish foraging and changing pelagic interactions in polar oceans

Light is a central driver of biological processes and systems. Receding sea ice changes the lightscape of high-latitude oceans and more light will penetrate into the sea. This affects bottom-up control through primary productivity and top-down control through vision-based foraging. We model effects of sea-ice shading on visual search to develop a mechanistic understanding of how climate-driven sea-ice retreat affects predator-prey interactions. We adapt a prey encounter model for ice-covered waters, where prey-detection performance of planktivorous fish depends on the light cycle. We use hindcast sea-ice concentrations (past 35 years) and compare with a future no-ice scenario to project visual range along two south-north transects with different sea-ice distributions and seasonality, one through the Bering Sea and one through the Barents Sea. The transect approach captures the transition from sub-Arctic to Arctic ecosystems and allows for comparison of latitudinal differences between longitudes. We find that past sea-ice retreat has increased visual search at a rate of 2.7% to 4.2% per decade from the long-term mean; and for high latitudes, we predict a 16-fold increase in clearance rate. Top-down control is therefore predicted to intensify. Ecological and evolutionary consequences for polar marine communities and energy flows would follow, possibly also as tipping points and regime shifts. We expect species distributions to track the receding ice-edge, and in particular expect species with large migratory capacity to make foraging forays into high-latitude oceans. However, the extreme seasonality in photoperiod of high-latitude oceans may counteract such shifts and rather act as a zoogeographical filter limiting poleward range expansion. The provided mechanistic insights are relevant for pelagic ecosystems globally, including lakes where shifted distributions are seldom possible but where predator-prey consequences would be much related. As part of the discussion on photoperiodic implications for high-latitude range shifts, we provide a short review of studies linking physical drivers to latitudinal extent.