Erratum for Arctic Ocean Primary Productivity: The Response of Marine Algae to Climate Warming and Sea Ice Decline
K. E. Frey1, J. C. Comiso2, L. W. Cooper3, J. M. Grebmeier3, and L. V. Stock2
1Graduate School of Geography, Clark University, Worcester, MA, USA
2Cryospheric Sciences Laboratory, Goddard Space Flight Center, NASA, Greenbelt, MD, USA
3Chesapeake Biological Laboratory, University of Maryland Center for Environmental Science, Solomons, MD, USA
The primary productivity data used in recent Arctic Report Card essays on Arctic Ocean primary productivity (Frey et al. 2015, 2016, 2017, 2018, 2019, 2020, 2021) have been based on a global algorithm (Behrenfeld and Falkowski 1997). This algorithm makes use of input data that include sea surface temperatures (SST) and chlorophyll-a concentrations. Several studies focused on both the Arctic and Antarctic regions were previously published using this algorithm (e.g., Smith and Comiso 2008; Comiso 2010), incorporating SST data derived at NASA Goddard Space Flight Center (GSFC) from Advanced Very High Resolution Radiometer (AVHRR) data and chlorophyll-a data from Sea-viewing Wide Field-of-view Sensor (SeaWiFS) and Moderate Resolution Imaging Spectroradiometer (MODIS) ocean color data (also derived at GSFC). For consistency, this same algorithm has been used (up to the present) for the Arctic Report Card essays, although there have been other algorithms that have been developed since 1997 (e.g., Lewis et al. 2020). However, when primary productivity data were initially needed for the Arctic Report Card in 2015, the primary productivity dataset maintained at GSFC shifted to utilize a different SST dataset than those used in previous publications (prior to 2015). In particular, the NOAA/Reynolds Optimum Interpolation SST (OISST) dataset started to be used for convenience since NOAA had begun to incorporate AVHRR data to supplement the in-situ SST measurements. The switch was justified because, with the addition of these AVHRR data, the NOAA OISST product became much more consistent with the GSFC SST product that relied more on satellite data in the polar regions where there is a paucity of in-situ measurements. However, through the process of shifting SST datasets, this led to an inadvertent programming error that is now being reported in this erratum. In the previously revised version of the programming code, SST was set to zero and, in the process, estimates of primary productivity became erroneous. The error was not immediately noticed since the incorrect values appeared realistic and it was not until 2021 that the error was discovered. Since the updated primary productivity values are significantly different from the previous values, this erratum was deemed necessary to inform the public that the values and trends for primary productivity were erroneous in Frey et al. (2015, 2016, 2017, 2018, 2019, 2020). No other variables reported in these essays (chlorophyll-a concentrations and sea ice concentrations) are erroneous and they stand as reported. The primary productivity values and trends reported in Arctic Report Card 2021 (Frey et al. 2021) are correct and reflect values in which SST is appropriately incorporated.
Updated vs. previous dataset comparisons
To assess the overall impact of the updated code that now incorporates SST appropriately, we include analyses that compare primary productivity and trends of primary productivity for our standard nine Arctic regions over the 2003-20 period (Figs. 1 and 2, Table 1). Linear regressions of the updated annual primary productivity values vs. the previous annual primary productivity values show that the updated estimates are all higher than previous estimates. In particular, the updated values range on average from 2.37 to 4.02 times higher than previous estimates (Fig. 1, Table 1), with an average of 2.65 times higher for all nine regions (Fig. 1j, Table 1). The smallest differences occur for regions that exhibit cooler annual SST values (Greenland Sea and Baffin/Labrador Sea; new values average 2.37 times higher; Fig. 1f and 1h), whereas the greatest differences occur for regions that exhibit warmer annual SST values (North Atlantic; new values average 4.02 times higher; Fig. 1i). These results are expected because the cooler regions exhibit SSTs more similar to the previous incorrectly designated SSTs (i.e., those incorrectly set at zero). Given the overall higher primary productivity values in the updated dataset, the updated calculated decadal trends in primary productivity over the years 2003-20 are now higher as well (Fig. 2, Table 1). On average, the updated decadal trends are nearly three times higher than previous trends, with the smallest difference for the Hudson Bay (~1.5 times higher) and the largest difference for the Bering Sea (~6 times higher). Overall, the general story of how primary production is changing across the Arctic does not deviate from what was reported in previous Arctic Report Card essays (i.e., long-term increases in primary productivity across all regions of the Arctic).
|Region||Slope of Updated vs. Previous Primary Productivity Values, 2003-20||Trend in Primary Productivity, 2003-20 (g C/m2/year/decade)|
|Sea of Okhotsk||2.88||1.22||4.66|
|Baffin Bay/Labrador Sea||2.37||4.69||10.52|
|Average of nine regions*||2.65||5.24||15.18|
In summary, with the updated values we now report primary productivity values that are on average 2.65 times higher and trends that are on average 2.91 times steeper than the previous, erroneously reported primary productivity values. Given the linear relationships between previous and updated values, the rankings of trends remain similar with the Eurasian Arctic and Barents Sea exhibiting the greatest trends in primary productivity over the years 2003-20. These updated rates of primary production provide those interested in incorporating primary productivity values into modeling and other synthesis efforts with accurate estimates of organic carbon generation across Arctic waters based on Behrenfeld and Falkowski (1997) and the OISSTv2 SST data.
Behrenfeld, M. J., and P. G. Falkowski, 1997: Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnol. Oceanogr., 42(1), 1-20, https://doi.org/10.4319/lo.1997.42.1.0001.
Comiso, J., 2010: Polar Oceans from Space. Vol. 41. Springer Science & Business Media.
Frey, K. E., J. C. Comiso, L. W. Cooper, L. B. Eisner, R. R. Gradinger, J. M. Grebmeier, and J. -É. Tremblay, 2017: Arctic Ocean primary productivity. Arctic Report Card 2017, J. Richter-Menge, J. E. Overland, J. T. Mathis, and E. Osborne, Eds., https://doi.org/10.25923/8ntk-7817.
Frey, K. E., J. C. Comiso, L. W. Cooper, R. R. Gradinger, J. M. Grebmeier, and J. -É. Tremblay, 2015: Arctic Ocean primary productivity. Arctic Report Card 2015, M. O. Jeffries, J. Richter-Menge, and J. E. Overland, Eds., https://doi.org/10.25923/8h3d-5v51.
Frey, K. E., J. C. Comiso, L. W. Cooper, R. R. Gradinger, J. M. Grebmeier, and J. -É. Tremblay, 2016: Arctic Ocean primary productivity. Arctic Report Card 2016, J. Richter-Menge, J. E. Overland, and J. T. Mathis, Eds., https://doi.org/10.25923/kgx6-f630.
Frey, K. E., J. C. Comiso, L. W. Cooper, J. M. Grebmeier, and L. V. Stock, 2018: Arctic Ocean primary productivity: The response of marine algae to climate warming and sea ice decline. Arctic Report Card 2018, E. Osborne, J. Richter-Menge, and M. Jeffries, Eds., https://doi.org/10.25923/krcx-z320.
Frey, K. E., J. C. Comiso, L. W. Cooper, J. M. Grebmeier, and L. V. Stock, 2019: Arctic Ocean primary productivity: The response of marine algae to climate warming and sea ice decline. Arctic Report Card 2019, J. Richter-Menge, M. L. Druckenmiller, and M. Jeffries, Eds., https://doi.org/10.25923/bw4d-my28.
Frey, K. E., J. C. Comiso, L. W. Cooper, J. M. Grebmeier, and L. V. Stock, 2020: Arctic Ocean primary productivity: The response of marine algae to climate warming and sea ice decline. Arctic Report Card 2020, R. L. Thoman, J. Richter-Menge, and M. L. Druckenmiller, Eds., https://doi.org/10.25923/vtdn-2198.
Frey, K. E., J. C. Comiso, L. W. Cooper, J. M. Grebmeier, and L. V. Stock, 2021: Arctic Ocean primary productivity: The response of marine algae to climate warming and sea ice decline. Arctic Report Card 2021, https://doi.org/10.25923/kxhb-dw16.
Lewis, K. M., G. L. van Dijken, and K. R. Arrigo, 2020: Changes in phytoplankton concentration now drive increased Arctic Ocean primary production. Science, 369, 198-202, https://doi.org/10.1126/science.aay8380.
Smith, Jr., W. O., and J. C. Comiso, 2008: The influence of sea ice on primary production in the Southern Ocean: A satellite perspective. J. Geophys. Res.,113, C05S93, https://doi.org/10.1029/2007JC004251.
December 7, 2021
K. D. Tape1, J. A. Clark1, B. M. Jones2, H. C. Wheeler3, P. Marsh4, and F. Rosell5
1Geophysical Institute, University of Alaska Fairbanks, Fairbanks, AK, USA
2Water and Environmental Research Center, Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, AK, USA
3School of Life Sciences, Anglia Ruskin University, Cambridge, UK
4Department of Geography, Wilfrid Laurier University, Waterloo, ON, Canada
5Department of Natural Sciences and Environmental Health, University of South-Eastern Norway, Bø, Norway
- Recent satellite imagery and older aerial photography show that North American beavers (Castor canadensis) are colonizing the Arctic tundra of Alaska, with over 12,000 ponds thus far counted in western Alaska, a doubling of ponds since 2000.
- In Canada, beaver pond mapping is underway, complemented by scattered observations of recent changes. Eurasian beavers (C. fiber) are rebounding in Asia but remain south of the Arctic tundra in most locations.
- The Arctic Beaver Observation Network was established in 2020 to help integrate, guide, and disseminate information concerning beaver range expansion into tundra regions and implications for ecosystems and resources.
Research on North American beaver (Castor canadensis) engineering in the Arctic has made great strides in recent years, but most of the work lies ahead. Over the last several decades, people in remote Alaska communities have observed an influx of beavers (ADF&G Reports 1965-2017). We quantified this trend by using satellite imagery to detect beaver pond formation in Alaska tundra regions, mapping approximately 12,000 beaver ponds (e.g., Fig. 1, right panel), including a doubling in most areas during the last 20 years (Tape et al. 2021). We showed that new beavers are controlling surface water increases, which affects underlying permafrost (Jones et al. 2020). Fieldwork is underway to characterize the impacts of beaver ponds on aquatic and terrestrial Arctic ecosystems, starting with hydrology and permafrost, and continuing downstream to methane flux, fish populations, and aquatic food webs. As a result of these efforts, most of the questions surrounding beaver engineering in the Arctic are presently being examined but are unanswered. To coordinate research and action among stakeholders in the circumarctic region, the Arctic Beaver Observation Network (A-BON) was formed in 2020 and a synthesis effort is underway to identify knowledge gaps and support the integration of different approaches and perspectives.
Tundra be dammed
In 2016 we imagined that beaver distribution and possible dispersal in the Arctic could be identified by mapping beaver ponds in satellite imagery and older aerial photography through time. Initial studies confirmed our suspicions (Tape et al. 2018), as did the observations of local people in northwest Alaska, who have been observing the influx of beavers for a half-century (ADF&G Reports 1965-2017). Yet the scale and magnitude of this new disturbance regime was unknown in Alaska and the circumarctic. We have since mapped approximately 12,000 beaver ponds (using 2015-19 imagery) in Arctic tundra of Alaska (e.g., Fig. 2). This mapping excludes southwest Alaska tundra and thus provides an underestimate of the total number of beaver ponds. Most areas show a doubling of beaver ponds in the last 20 years (Tape et al. 2021). In 1949-55 aerial photography covering coastal areas of western Alaska, there are no detectable beaver ponds. Stream by stream and floodplain by floodplain, beavers are transforming lowland tundra ecosystems. Increased vegetation productivity (see essay Tundra Greenness) and the expansion of woody shrubs (Myers-Smith et al. 2015) due to climate change has created more forage and dam construction materials, translating to more favorable habitat. The increase in winter stream discharge (St. Jacques and Sauchyn 2009) also implies greater aqueous habitat. Finally, the earlier end of winter and onset of spring (see essay Terrestrial Snow Cover), when beavers can again begin foraging, effectively shortens what is presumably the most challenging time in the annual life cycle of beavers. It remains unclear whether beaver colonization of the Arctic is occurring due to climate change ameliorating habitat or a decrease in trapping pressure, or some combination of both.
In Canada, beaver distribution changes have also been observed both by local people and scientists. Concern over rising numbers of beavers in the Inuvialuit settlement region in the Northwest Territories in northwestern Canada was sufficient to instigate a harvesting incentive scheme in 2017. Although publications of academic studies of beavers in northern Canada have been sparse to date, there are reports of beavers north of the previously known range (Jung et al. 2016).
In Europe, Eurasian beavers (C. fiber) were widespread from the Arctic to the Mediterranean, before being substantially reduced around the twelfth century, and almost extinct by the sixteenth century. Today, the Eurasian beaver has restored a large area of its original range, and increased in numbers from around 1200 beavers a century ago to an estimated 1.5 million individuals today; beavers distribution reaches the northern coast throughout most of Europe (Halley et al. 2021). In Asia, beaver distribution remains well south of Arctic tundra regions, though recent northward range extensions have been observed (Halley et al. 2021). In general, research on beavers in Arctic tundra regions is in its early stages. A coordinated circumarctic beaver pond mapping effort is underway, which will hopefully establish the footprint, if not the nature, of this new disturbance regime in the Arctic.
Implications of beaver engineering in the Arctic
Beavers are a keystone species whose engineering is known to heavily influence streams, rivers, riparian corridors, and lakes in North America, Eurasia, and South America (Whitfield et al. 2015). Beavers are known to dramatically change the landscapes they inhabit by harvesting shrubs, saplings, and trees, which they use to construct dams, inundate the surrounding landscape, and create their watery world. Beavers build lodges of mud and vegetation in water that is deep enough for an underwater entrance that remains unfrozen and permits access for them, but not predators. By constructing dams, beavers severely alter the stream flow regime, which facilitates the arrival of new species, including riverine plants, invertebrates, and fish (Bunn and Arthington 2002). Beaver ponds in temperate ecosystems enhance aquatic habitat complexity and biodiversity.
It remains unclear how these impacts will be manifest in the Arctic, where low water temperatures inhibit stream productivity and biodiversity, and where permafrost holds much of the soil together. People living in remote communities are concerned for resources such as fish, water quality, and boat access (Moerlein and Carothers 2012). In an area of northwest Alaska with exceptional satellite imagery coverage, we discovered that beavers are the dominant factor (66%) controlling increases in surface water extent (Jones et al. 2020), which thaws underlying permafrost as it inundates tundra vegetation. Beaver dams divert flow, sometimes catastrophically when they fail, and can thaw and destabilize the landscape (Lewkowicz and Coultish 2004) through fluvio-erosional and thermokarst processes (Fig. 3). Thawing of permafrost associated with new beaver ponds would initially release carbon and methane stored in permafrost, though the magnitude and fate of these fluxes are complex and unknown. Permafrost thaw, thermokarst, and the inception of a more dynamic lowland Arctic ecosystem suggest an exacerbation of effects due to warming air temperatures. As beavers create thermal and biological oases by the thousands, they could provide a foothold for boreal aquatic species, including fish and aquatic invertebrates. For now, however, these remain hypotheses that will spawn downstream studies involving field measurements and local knowledge to answer.
Arctic Beaver Observation Network (A-BON): Tracking a new disturbance
Recognizing an impending need to understand the scale, dynamics, and effects of beaver engineering in the tundra, individuals and organizations joined forces across Alaska, Canada, and Eurasia to identify key questions and involve stakeholders and land managers. A-BON involves natural scientists, social scientists, tribal entities and local observers, and agency land managers across the Arctic. A-BON has working groups in Alaska, Canada, Europe, and Asia.
The initial goals of A-BON are to (1) include diverse backgrounds and establish working relationships, (2) identify key questions for study, (3) align study designs and observation methods, (4) facilitate co-production of knowledge between scientists and local observers, (5) understand stakeholder land/resource management objectives, (6) assemble an expert steering committee to advise other Arctic science bodies (e.g., Conservation of Arctic Flora & Fauna, Circumpolar Biodiversity Monitoring Program), and (7) synthesize, archive, and disseminate relevant and co-produced data. These goals are actively being refined.
A synthesis effort underway within A-BON aims to identify key questions and knowledge gaps surrounding beaver colonization in the tundra across natural and social scientists, Indigenous organizations and observers, and land managers. Preliminary results demonstrate the breadth of interests and concerns, spanning beaver ecology, biophysical and socio-cultural impacts, local and Indigenous knowledge, management, and adapting to the evolving relationships with beavers. A-BON will discuss these and other efforts at the first meeting in March 2022 in Fairbanks, Alaska (could be virtual). We welcome participation in A-BON from anyone with interest in the topic.
K. Tape, J. Clark, and B. Jones acknowledge NSF OPP #1850578 and #2114051. H. Wheeler acknowledges the UK-Canada Arctic partnership bursary (NERC/BEIS) and Anglia Ruskin Next Steps QR fund.
ADF&G, 1965-2017: ADF&G (Furbearer) Reports. Alaska Department of Fish & Game, Division of Wildlife Conservation, Juneau, Alaska.
Bunn, S. E., and A. H. Arthington, 2002: Basic principles and ecological consequences of altered flow regimes for aquatic biodiversity. Environ. Manage., 30(4), 492-507, https://doi.org/10.1007/s00267-002-2737-0.
Halley, D. J., A. P. Saveljev, and F. Rosell, 2021: Population and distribution of beavers Castor fiber and Castor canadensis in Eurasia. Mammal Rev., 51, 1-24, https://doi.org/10.1111/mam.12216.
Jones, B. M., K. D. Tape, J. A. Clark, I. Nitze, G. Grosse, and J. Disbrow, 2020: Increase in beaver dams controls surface water and thermokarst dynamics in an Arctic tundra region, Baldwin Peninsula, northwestern Alaska. Environ. Res. Lett., 15(7), 075005, https://doi.org/10.1088/1748-9326/ab80f1.
Jung, T. S., J. Frandsen, D. C. Gordon, and D. H. Mossop, 2016: Colonization of the Beaufort coastal plain by Beaver (Castor canadensis): a response to shrubification of the Tundra? Can. Field Nat., 130(4), 332-335, https://doi.org/10.22621/cfn.v130i4.1927.
Lewkowicz, A. G., and T. L. Coultish, 2004: Beaver damming and palsa dynamics in a subarctic mountainous environment, Wolf Creek, Yukon Territory, Canada. Arct. Antarct. Alp. Res., 36, 208-218, https://doi.org/10.1657/1523-0430(2004)036[0208:bdapdi]2.0.co;2.
Moerlein, K. J., and C. Carothers, 2012: Total environment of change: impacts of climate change and social transitions on subsistence fisheries in northwest Alaska. Ecol. Soc., 17(1), 10, https://doi.org/10.5751/es-04543-170110.
Myers-Smith, I. H., and Coauthors, 2015: Climate sensitivity of shrub growth across the tundra biome. Nat. Climate Change, 5(9), 887-891, https://doi.org/10.1038/nclimate2697.
St. Jacques, J. -M., and D. J. Sauchyn, 2009: Increasing winter baseflow and mean annual streamflow from possible permafrost thawing in the Northwest Territories, Canada. Geophys. Res. Lett., 36(1), L01401, https://doi.org/10.1029/2008gl035822.
Tape, K. D., B. M. Jones, C. D. Arp, I. Nitze, and G. Grosse, 2018: Tundra be dammed: Beaver colonization of the Arctic. Glob. Change Biol., 24(10), 4478-4488, https://doi.org/10.1111/gcb.14332.
Tape, K. D., J. A. Clark, and B. M. Jones, 2021: Beaver Pond Locations in Arctic Alaska, 1949 to 2020. Arctic Data Center. Accessed 15 September 2021, https://doi.org/10.18739/A2QR4NR6D.
Whitfield, C. J., H. M. Baulch, K. P. Chun, and C. J. Westbrook, 2015: Beaver-mediated methane emission: The effects of population growth in Eurasia and the Americas. Ambio, 44(1), 7-15, https://doi.org/10.1007/s13280-014-0575-y.
December 2, 2021
J. N. Cross1, A. Niemi2, N. Steiner3, and D. J. Pilcher1,4
1Pacific Marine Environmental Laboratory, NOAA, Seattle, WA, USA
2Freshwater Institute, Fisheries and Oceans Canada, Winnipeg, MB, Canada
3Institute of Ocean Sciences, Fisheries and Oceans Canada, Sidney, BC, Canada
4Cooperative Institute for Climate, Ocean, and Ecosystem Studies, University of Washington, Seattle, WA, USA
- Recent work has shown that the Arctic Ocean is acidifying faster than the global ocean, but with high spatial variability.
- A growing body of research indicates that acidification in the Arctic Ocean could have implications for the Arctic ecosystem, including influences on algae, zooplankton, and fish.
- Cutting-edge tools like computational models are increasing our capacity to understand patterns, trends, and impacts of ocean acidification in the Arctic region.
The uptake of anthropogenic carbon dioxide (CO2) causes a cascade of chemical reactions that decreases ocean pH and carbonate ion concentrations, a process known as ocean acidification (OA). While OA is a global process, some of the fastest rates of ocean acidification around the world have been observed in the Arctic Ocean (e.g., Qi et al. 2017, 2020). These extremely rapid rates of acidification reflect the Arctic’s natural vulnerability to changes in pH, caused by cold temperatures, naturally higher baseline CO2 concentrations resulting from global circulation processes, seasonal processes that rapidly concentrate CO2 in some water masses, as well as unique land-sea interactions and hydrological mechanisms (circumpolar perspective broadly reviewed by AMAP 2018). Surface waters in some parts of the Arctic Ocean are already undersaturated with respect to some biologically important calcium carbonate minerals (e.g., aragonite and calcite) and most regions of the Arctic are likely to become corrosive (able to dissolve biologically important carbonate minerals) by the end of the century (AMAP 2018). These changes could have serious implications for the regional ecosystem, including detrimental impacts on local wildlife, cultural assets and practices, and subsistence resources.
Robust sampling programs that prioritize the collection of OA data (e.g., pH, partial pressure of CO2, dissolved inorganic carbon (DIC), and total alkalinity (TA)) are extremely difficult to implement in the Arctic. The coastal sub-Arctic seas exhibit a highly dynamic spatial and temporal variability as the underlying biogeochemistry is impacted by a range of land, ocean, and atmosphere processes. Accordingly, mature OA monitoring systems must be highly resolved in both space and time to provide adequate information for decision support. Given the expansive area, the remote geographic location, and harsh winters, traditional monitoring tools are also challenging to deploy consistently in the Arctic region, although some of these time series are starting to mature (e.g., Beaufort Gyre: Zhang et al. 2020; Canadian Archipelago: Beaupré-Laperrière et al. 2020; Eurasian Basin: Ulfsbo et al. 2018; Fram Strait: Chierici et al. 2019; Svalbard: Jones et al. 2021).
Despite these advances, we do not have a synoptic understanding of OA across the pan-Arctic system. Accordingly, computational models grounded in observable data have emerged as a useful tool to help explore spatial-temporal variability due to their much finer spatial and temporal resolution. Using these outputs, researchers are better able to explore the intensity, duration, and extent of ecosystem exposure to OA processes. In recent years, regional and global modeling studies have been used to explore both long- and short-term aspects of OA in the Arctic (e.g., Bering Sea: Pilcher et al. 2019; pan-Arctic, Terhaar et al. 2020), as well as the processes leading to these trends that are notoriously difficult to observe (e.g., pan-Arctic sea-ice related impacts: Mortenson et al. 2020). However, there is substantial regional and seasonal variability especially where land processes can influence OA, highlighting potential problems with interpolating sparse measurements (e.g., Chierici et al. 2019; Jones et al. 2021). Better regional to local climate projections may provide key improvements. Model studies continue to be refined and will likely form a pivotal part of future Arctic OA research.
As the observational record of OA in the Arctic continues to grow, research on the possible impact of OA on Arctic ecosystems continues to progress both in the laboratory and in the field (Fig. 1). The primary concern is that the short food web linkages so characteristic of the Arctic may lead to widespread impacts of OA across the ecosystem, creating both winners and losers. This is evident at the very base of the food chain: for example, OA negatively affects the calcification of some Arctic phytoplankton (pan-Arctic: Ardyna and Arrigo 2020) and may shift the community toward smaller species (western Arctic: Sugie et al. 2020). Some primary producers may experience little impact; research syntheses indicate that OA likely has a limited effect on sea ice algae, given that the biogeochemistry of the ice matrix itself naturally undergoes extreme fluctuations that result in evolutionary resilience (central Arctic: Torstensson et al. 2021).
At the zooplankton trophic level, the quintessential species for detrimental OA impacts is the pteropod (sea snail). These organisms are extremely sensitive to ocean pH and are often used around the world as indicators that can inform OA conditions. Both laboratory and field observations have shown that pteropod responses to OA include reduced juvenile survival, reduced shell growth and condition, as well as costly metabolic regulation. Arctic population connectivity and morphological characteristics of pteropods is a growing area of research. For example, recent studies of natural populations indicate a high occurrence of severe shell dissolution in the Bering Sea, Amundsen Gulf, and Svalbard margin (Niemi et al. 2021; Bednaršek et al. 2021; Anglada-Ortiz et al. 2021, respectively). While pteropods are an important biological indicator, research on other organisms specific to Arctic ecosystems will also support regional relevance. For example, fish show sensitivities to OA, including important species such as Arctic cod (e.g., western Arctic cod populations: Steiner et al. 2019; eastern Arctic cod: Hänsel et al. 2020). However, key questions remain to fully understand the mechanisms that produce individual and population-level responses to OA. Across species (fish, benthic and pelagic invertebrates) repair, adaptability, and associated tolerance have been linked to resource availability (e.g., Niemi et al. 2021; Hänsel et al. 2020; Duarte et al. 2020; Goethel et al. 2017), indicating the importance of a holistic ecosystem approach to understand OA biological responses (Fig. 2).
Seals, walrus, and marine birds may be impacted by the inherent vulnerability of their preferred foods to acidification. Calcifying bivalves are particularly sensitive to acidified conditions; weakly acidified waters can reduce growth, while severely corrosive waters can eventually begin to dissolve shells. Although laboratory experiments have identified resilience to acidification in Arctic invertebrates (Goethel et al. 2017), some model research suggests that they are likely to be among the most negatively impacted invertebrate populations in the world (Tai et al. 2021). Though the specifics remain uncertain, it is likely that the consequences of continuing OA will be detrimental for parts of the marine food web over the next decade. Warming and acidification are likely to become compounding stressors for the Arctic ecosystem by the end of the century. More research will be necessary to determine how acidification-stressed marine invertebrate populations may influence the Arctic ecosystem. This work will be especially important given that invertebrates as well as their predators are important commercial, cultural, and subsistence resources across the region.
Building ecosystem and human resilience to OA in the Arctic in part will require global solutions, given that OA is primarily caused by global carbon dioxide emissions. However, regional decision makers are likely to benefit from continually improving resolution of both data collection and regional modeling, which will provide additional support for Arctic decision makers and ecosystem management. Measurements from novel sensors, especially those collecting surface data are likely to improve the resolution of regional CO2 flux products and provide a better understanding of the surface CO2 sink for carbon across the Arctic. Additionally, short-term forecasting applications are likely to be developed for regional and pan-Arctic models in support of ecosystem management systems. Through this process, development of connections between biogeochemical and ecosystem models, based on empirical laboratory and in-situ data, are likely to allow researchers to continue to explore the impact of OA on regional ecosystems. The ultimate goal is to develop an interdisciplinary, hybridized approach that will allow the scientific community to develop annual OA products of the type now produced for temperature or sea ice extent for the Arctic Report Card. Given the high connectivity of processes leading to OA and its downstream effects, trans-national data access and collaboration will be essential for success.
In addition to improvements in data collection, it also seems likely that coastal marine CO2 removal may scale inside coastal waters in the Arctic. The IPCC has acknowledged that achieving climate goals requires substantial changes to atmospheric greenhouse gas concentrations. While emissions-reduction approaches are an essential component of addressing this challenge, negative emissions strategies will be necessary for keeping global temperatures at recommended levels (IPCC 2021). Negative emissions strategies refer to a portfolio of techniques that are used to manually remove greenhouse gases from the atmosphere and store them away from the atmosphere. Carbon dioxide removal (CDR) specifically references techniques that remove legacy emissions of CO2 from the atmosphere. Where these techniques involve the coastal oceans, there may be opportunities to remediate acidified ocean conditions in some instances. However, these marine CDR techniques are in their infancy and will require additional study to limit the risks associated with deployment, despite the potential benefits of atmospheric carbon sequestration and OA mitigation. It will also be essential to consider the ethical and climate justice ramifications of these techniques, especially regarding Arctic communities and peoples (Cassotta 2021).
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November 23, 2021
R. M. Holmes1, A. I. Shiklomanov2,3, A. Suslova1, M. Tretiakov3, J. W. McClelland4, L. Scott1, R. G. M. Spencer5, and S. E. Tank6
1Woodwell Climate Research Center, Falmouth, MA, USA
2University of New Hampshire, Durham, NH, USA
3Arctic and Antarctic Research Institute, St. Petersburg, Russia
4Marine Science Institute, University of Texas at Austin, Port Aransas, TX, USA
5Florida State University, Tallahassee, FL, USA
6University of Alberta, Edmonton, AB, Canada
- In 2021, the combined discharge (January through October) from the six Eurasian rivers was 1850 km3, which was 81 km3 or ~5% greater than during the 1981-2010 reference period.
- In 2020, the combined discharge of the eight largest Arctic rivers was 2623 km3, ~12% greater than the average over the 1981-2010 reference period.
- In 2019, the combined discharge of the eight largest Arctic rivers was 2233 km3, 5% less than the 1981-2010 average.
- In 2020, an extraordinarily high May discharge from Eurasian rivers of 443 km3 (96% above average) was followed by an extraordinarily low June discharge of 432 km3 (21% below average), indicating a shift of the freshet to earlier in the season.
- The long-term observations for Eurasian and North American Arctic river discharges demonstrate an upward trend, providing evidence for the intensification of the Arctic hydrologic cycle.
Arctic river discharge is a key indicator reflecting changes in the hydrologic cycle associated with widespread environmental change in the Arctic. It is the most accurately measured component of the Arctic water cycle (Shiklomanov et al. 2006). Records of Arctic river discharge since the early 1930s reveal a long-term increase of freshwater flux to the Arctic Ocean, providing compelling evidence of intensification of the Arctic water cycle (Peterson et al. 2002; McClelland et al. 2006). This hydrologic and associated biogeochemical change has significant ramifications for the Arctic Ocean, which contains only about 1% of global ocean water yet receives 11% of the global river discharge (Aagaard and Carmack 1989; McClelland et al. 2012).
Of the eight largest Arctic rivers by annual discharge, six lie in Eurasia (Kolyma, Yenisey, Lena, Ob’, Pechora, and Severnaya Dvina) and two are in North America (Mackenzie and Yukon). Collectively, the watersheds of these eight rivers cover approximately 70% of the pan-Arctic drainage area and account for the majority of river water input to the Arctic Ocean (Fig. 1). In this report we present river discharge values for these eight rivers for 2019 and 2020, and for the Eurasian portion of these same rivers for the first ten months of 2021, updating the 2018 Arctic Report Card (Holmes et al. 2018). 2021 data are not available for the two North American rivers at the time of this report. Here, we use a common baseline period of 1981-2010 to compare and contextualize recent observations.
In 2021, the combined discharge (January through October) from the six Eurasian rivers was 1850 km3, which was 81 km3 or ~5% greater than during 1981-2010 reference period. The majority of this increase was driven by the Yenisey River. The Pechora and Severnaya Dvina showed below average discharge, 26% and 28%, respectively (Fig. 2).
In 2020, the combined annual discharge of the eight largest Arctic rivers was 2623 km3, which was 272 km3 or ~12% greater than the 30-year average. This increase is greater than the annual average discharge of the Yukon River. Discharge from the two North American rivers combined was 630 km3, ~28% greater than their 1981-2010 average. Discharge from the six Eurasian rivers combined was 1992 km3, ~7% greater than the average over the 1981-2010 reference period, or ~10% greater than average for whole period of record from 1936 to 2020 (Table 1).
|All time average||206||286||101||110||404||586||541||73||2307|
High annual discharge of the North American rivers in 2020 was primarily driven by the high discharge values in July, August, and September (+2.1, +2.6, +2.8 std. dev. above average, respectively; Fig. 3). This is attributed to an unusually wet summer, the wettest summer since 1985 based on analysis of precipitation aggregated over the Mackenzie and Yukon watersheds (Hersbach et al. 2020).
For the Eurasian rivers in 2020, extraordinarily high May discharge (+3.1 std. dev. above average) was followed by extraordinarily low June discharge (-2.3 std. dev. below average; Fig. 3). This pattern observed across the Eurasian rivers is consistent with the observed high terrestrial snow cover and snow water equivalent during winter 2019/20, followed by a remarkably warm spring in 2020 (Ballinger et al. 2020; Mudryk et al. 2020). This led to an early melt of a large snowpack, shifting more of the freshet runoff period from June to May. Discharge for May and June combined was 13% higher in 2020 compared to the baseline period.
In contrast to 2020, 2019 was a relatively low-discharge year. The combined discharge of the eight largest Arctic rivers was 2233 km3, 118 km3 or 5% less than the 1981-2010 average (Fig. 4). Discharge from the two North American rivers and the six Eurasian rivers was ~9% and ~4% less than average, respectively.
Low annual discharge in 2019 from the North American rivers was driven by low May, June, and July discharge (-0.8, -0.9, -1.4 std. dev. below average, respectively; Fig. 3). Similarly, Eurasian rivers had lower than average discharge in May and June (-0.5, -0.9 std. dev. below average, respectively; Fig. 3). These low summer discharge observations are consistent with the below-average snow water equivalent in April 2019 in both the Eurasian and North American Arctic (Mudryk et al. 2019).
The 85-year time series available for the Eurasian Arctic rivers demonstrates a positive linear trend. Their combined annual discharge is increasing by 2.5 km3 per year. For the North American Arctic rivers, the increase over the period of record (1976-2020) was 1.1 km3 per year (Fig. 4). These long-term observations indicate that Arctic river discharge continues to trend upward, providing powerful evidence for the intensification of the Arctic hydrologic cycle (Shiklomanov et al. 2021).
Methods and data
Discharge values are based on observational discharge data from the downstream-most stations listed in Table 2. Discharge measurements for the six Eurasian rivers began in 1936, whereas discharge measurements did not begin until 1973 for the Mackenzie River and 1976 for the Yukon River. Discharge data for the Kolyma at Srednekolymsk are not available for 2019 and 2020; they were calculated based on monthly correlations with the next downstream station, the Kolyma at Kolymskoe. Average monthly values for 1978-2001 were used to calculate the correction factor. The Yukon is missing discharge values from October-December 2020. We therefore used long-term average values for those three months, which account for less than 17% of the mean annual discharge. All discharge data reported here are available through the Arctic Great Rivers Observatory at arcticgreatrivers.org/discharge/.
|River||Station Location||Station Code||Latitude (°)||Longitude (°)||Catchment Area (km2)|
|Severnaya Dvina||Ust’ Pinega||70801||64.13||41.92||348000|
|Mackenzie||Arctic Red River||10LC014||67.45||-133.74||1750600|
We thank the United States Geological Survey (Yukon), Water Survey of Canada (Mackenzie) and Roshydromet (Severnaya Dvina, Pechora, Ob’, Yenisey, Lena, and Kolyma) for the discharge data used here. This work was supported by grants from the National Science Foundation in support of the Arctic Great Rivers Observatory (NSF 1602615, 1603149, 1602680, 1602879). The processing and analysis of near-real time data for Russian Arctic rivers were supported in part by the Russian Foundation for Basic Research (grant 18-05-60192).
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November 17, 2021
G. Sheffield1, A. Ahmasuk2, F. Ivanoff3, A. Noongwook4, and J. Koonooka5
1Alaska Sea Grant, Marine Advisory Program, University of Alaska Fairbanks, Nome, AK, USA
2Marine Advocate, Kawerak Inc., Nome, AK, USA
3Norton Sound Economic Development Corporation, Unalakleet, AK, USA
4Tribal Council, Native Village of Savoonga, Savoonga, AK, USA
5Tribal Council, Native Village of Gambell, Gambell, AK, USA
- During 2020, the Bering Strait region of Alaska experienced a marine debris event that brought garbage ashore that was different from the types and amount typically observed.
- Notification of, and response to, this event was undertaken by the regional public out of concern for their food security, marine wildlife health, human health, and conservation.
- Without significant collaborative transboundary communication and/or enforcement of existing international marine pollution rules, the Bering Strait region should expect similar or higher levels of marine garbage in the future as industrial maritime ship traffic increases.
The Bering Strait region of Eastern Chukotka (Russia) and western Alaska (USA) encompasses a narrow international waterway providing the sole transit corridor for a diverse assortment of federally-managed marine resources (e.g., marine mammals, seabirds, fish, and invertebrates), as well as all vessel traffic between the Pacific and Arctic Oceans. Two prominent northward flowing currents, the Anadyr and Alaska Coastal currents, produce a strong, typically one-way flow from the Bering Sea to the Chukchi Sea (Overland and Roach 1987) and are considered responsible for carrying anthropogenic debris northward (Mua et al. 2019; Kylin 2020).
The Alaskan Bering Strait region is extremely remote with an expansive coastline and little to no presence from the authorized federal agencies tasked with research, management, or response to the marine environment. Those personnel are typically located in the urban centers of Alaska and/or Washington state, far from western Alaska’s coast.
The communities of the Alaskan Bering Strait region are diverse and include Iñupiaq, St. Lawrence Island/Siberian Yupik, Yup’ik, as well as non-Native peoples. All reside along the coast, reflecting the importance of the marine ecosystem (see Fig. 1.). Reliance on marine resources for subsistence purposes is essential to each community’s nutritional, cultural, and economic well-being. Though there is often a lack of science data from western Alaska, there is no lack of regional knowledge regarding the marine environment. Coastal communities with active and comprehensive maritime subsistence activities typically are the first to discover anomalous events, alert regional partner institutions, and subsequently conduct the event response. The regional impetus to respond is out of food security, wildlife health, human health, and/or conservation concerns.
In the last decade, the peoples of the region have responded to anomalous events affecting marine species, including petroleum oil-fouling (Stimmelmayr et al. 2018), biogenic oil-fouling (Smith 2020), and novel disease and/or mortality events (Stimmelmayr et al. 2013; Bodenstein et al. 2015; Van Hemert et al. 2021). Additionally, the Bering Strait region experiences industrial fisheries debris washing ashore. Since 2006, the Norton Sound Economic Development Corporation (NSEDC) has conducted community environmental clean-up efforts (e.g., historic industrial, military materials, etc.). Over 1.1 million pounds (approximately 500 metric tons) have been collected from 15 member communities, with much of that as commercial fisheries equipment typically in the form of nets, floats, and other equipment (Fred Jay Ivanoff, Senior Crew Leader, NSEDC, 2021, personal communication). With large international commercial fisheries in the southern Bering Sea and strong northward flowing ocean currents, St. Lawrence Island consistently receives fisheries equipment ashore. Overall, the rest of the Bering Strait region receives a much lesser amount of fisheries-related materials ashore.
As a result of less and thinner seasonal sea ice, more open water, and rapidly reorganizing marine ecosystems (Stevenson and Lauth 2019; Eisner et al. 2020; Thoman et al. 2020), industrial maritime vessel traffic (e.g., Pollock and Pacific cod commercial fishing, Northern Sea Route large vessel traffic, etc.), which mostly originates far from the Bering Strait region, has significantly increased in frequency and duration in the northern Bering Sea (USCMTS 2019). These intensified activities increase the likelihood of future anomalous marine events that will require community vigilance and response throughout the Bering Strait region.
Marine debris event in 2020
Starting during late July 2020, tribal leadership at St. Lawrence Island voiced serious concerns regarding the amounts and types of debris washing ashore and provided qualitative reports (Table 1) to Kawerak, Inc. and the University of Alaska-Alaska Sea Grant (UAF-ASG) office in Nome. Kawerak and UAF-ASG responded initially by contacting the federal authorities. They used the existing regional communication network to gather and provide information as the event unfolded. Additionally, Kawerak and UAF-ASG created a regionally relevant public awareness poster with contact information for regional distribution, coordinated with regional media to provide information, and worked with the urban-based federal response agencies to provide the opportunity to speak (remotely) to the public about the emerging event. Through mid-November, individuals from 14 coastal communities (Fig. 1) discovered and documented over 350 individual items ashore, most with Russian, Korean, and/or other Asian lettering or branding (Table 2, Fig. 2). This number should be considered a minimum, with qualitative reports of mostly uncounted debris extending for miles. Reporting communities included locations in Norton Sound (Elim, Kotlik, Shaktoolik, Unalakleet), Bering Strait (Gambell, Savoonga, Diomede, Brevig Mission, Wales, Nome), and the Chukchi Sea region (Shishmaref, Deering, Kivalina, Wainwright). Additional reports of debris ashore (e.g., deck boots) were also received from the US Coast Guard during their aerial missions in the Bering Strait region, and these were incorporated with all reports received.
|July||Gambell||“5-10 miles of litter”|
|July||Savoonga||“There is trash and debris for miles along the shoreline”|
|July||Nome||“From Sinuk River to Nome (~25 miles) there were 174 items noted”|
|August||Gambell||“In 3 miles of shoreline we picked up trash that filled 19 (40 gal.) trash bags that each weighed ~50 lbs/apiece”|
|August||Savoonga||“Lots of trash washed in with lots of dead seabirds (murres, fulmars)” and “seen quite a bit of [deck boots] to the East and to the West”|
|August||Unalakleet||“Lots of Russian plastic [water] jugs”|
|September||Gambell||“Seeing lots of debris and even vegetables [washed in] of late”|
|September||Brevig Mission||“Quite a bit of debris of different varieties”|
|September||Wales||“In 4 miles there were a handful of milk bottles, > dozen beer/alcohol bottles, several aerosol cans, and one can of aerosol foam”.|
|September||Shishmaref||“During the flight from Wales to Shishmaref (~50 miles), recently washed in trash (plastic bags, pallets, plastic bottles, small plastic containers, deck boots, and even a large black ship’s fender) was consistently observed on the beach.”|
|Type||# of Items||Examples|
|Water||117 bottles||Russian brands (6), Korean brands (3), Chinese brand (1), and 43 undetermined bottles with no label but similar in shape and size to labelled water/beverage containers.|
|Beverages||46 bottles||Juice: aloe vera, pineapple, peach, tomato, and “cocktail”; Dairy/yogurt beverages; soda; milk; kvass; and one undetermined beverage|
|Deck Boots||47 boots||Several styles and colors, primarily orange.|
|Equipment||~46 items||Russian “pike” bamboo pole with welded hooks for retrieving longline buoys, 55 gallon oil drums (empty), long line buoy with a fishing company’s (Vladivostok, Russia) Pacific Cod permit tag number, a case of packing bands in a cardboard(!) box from Busan, S. Korea, two trawl net floats, packet of crystalline polypropylene, life jackets, chemical bottle, lighter, various plastic containers, and plastic bags, etc.|
|Food packaging||32 items||Cheese, chips, jam, candy, chocolate/peanut butter paste, cookies, pickles, dessert topping, garlic, ginger, peppers, instant pasta/soup, mayonnaise, ketchup, sour cream, tomatoes, soy sauce, yogurt, soybean oil, and undetermined condiment bottles|
|Aerosol cans||26 cans||Roach insecticide, lubricating oil, spray paint, butane, polyurethane foam, air freshener, and muscular pain relief spray|
|Bathroom cleaner||14 bottles||Toilet bowl cleaners, drain clog remover, dishwashing liquid|
|Hygienic products||8 items||Shampoo, stick deodorant, body wash (Men’s)|
|Alcohol||5 bottles||Beer, vodka|
|Foods||9 items||Biscuits (in a repurposed Russian food container), apple, lemon, green pepper, pumpkins, orange|
|Clothing (adult)||4 items||Russian Navy sailor cap, patent leather shoe, plastic slipper with liner, slip-on shoe|
|Water bottle||(1) six liter bottle containing 78 items||Plastic food packaging wrappers: meat, vegetables, pasta, rice, candy/gum, spice packets, baking powder, yogurt; disposable gloves, sponge, etc.|
The equipment washed ashore was commercial fisheries related, including a case of packing bands still in a cardboard box from Busan, South Korea, several life jackets, two 55-gallon drums with Russian branding, dozens of deck boots, countless blue plastic “bucket liner” or packaging bags, and even a longline buoy with permit tag (for Pacific cod) belonging to a Vladivostok-based commercial fishing company. The predominant debris washed ashore were empty single serving beverages, bottled water, and/or packaging associated with foods and snacks. Most plastic items were un-weathered, in pristine condition, indicating they had entered the water recently. The most recent date of manufacturing noted on any item was April 2020. Hazardous materials included cans and other containers that had and/or still contained roach insecticides, toilet cleaners, drain clog remover, lubricating oils, butane gas, and spray paints. Of note, one large plastic water bottle recovered near the community of Shishmaref contained 78 plastic and/or foil items associated with cooking meats, vegetables, starches, as well as cooking for a large number of people (e.g., disposable gloves, etc.). This one bottle containing multiple items was a reminder that the items documented were an absolute minimum, and highlighted the potential for more plastics to be released in the future. There was no clothing or hygienic debris typically associated with women or children, which supports attributing this mass debris event to commercial fisheries, which mostly employ male crew members.
Community members remained vigilant and voluntarily reported, documented, and even shipped debris to Nome in hopes of identifying the responsible party for these violations of the existing international pollution convention, and to get them to stop polluting regional waters. The largest number of villages’ simultaneously reporting trash ashore occurred during September 2020, with the last foreign debris reported from Little Diomede in mid-November at the start of seasonal sea ice formation. Regional residents continued to note that the 2020 event was more widespread, of longer duration, and included more internationally manufactured or branded everyday garbage (e.g., water/beverage bottles, snack packaging, aerosol cans, and foods) ashore than previous years. Of note, there were two items of clothing (a Russian Navy cap and a patent leather shoe, both in pristine condition) that washed ashore on St. Lawrence Island during September that were potentially associated with a large Russian military exercise near St. Lawrence Island during late August (Isachenkov 2020; Sutton 2020).
During 2020 it was not just commercial fishing equipment coming ashore; debris also included everyday garbage such as plastics, food items, and hazardous materials. Each item documented ashore is in violation of international regulations to prevent garbage pollution from ships as outlined in Annex V of the International Convention for the Prevention of Pollution from Ships (MARPOL) (International Maritime Organization 2021). The documented plastic debris, fishing equipment, and hazardous materials not only negatively impact regional marine resources, but also the peoples and communities that directly rely on them for nutritional, cultural, and economic well-being.
Possible reasons for the increase of marine debris in the Bering Strait region during 2020 include:
- An increase in marine traffic to the region: Unfortunately, however, we have not found accessible quantitative information on the change in ship traffic in the northern Bering Sea during 2020.
- Different people are now using the Bering Strait region: During 2020, industrial fishing vessels and/or commerce vessels, originating far from the Bering Strait region, arrived to exploit novel volumes of commercially-viable marine resources (e.g., Pacific cod and pollock) (Spies et al. 2020; Stevenson and Lauth 2019) and/or unprecedented maritime northern transit conditions (Humpbert 2021; Smith 2021).
- A foreign vessel sunk: Based on authors’ consultation with the US Coast Guard, such information may not be currently available at the international level for the Bering and Chukchi Seas.
The 2020 debris event and response demonstrated that, during a maritime environmental or food security-related event in the Bering Strait region, the federally-authorized responding agencies located far from the coast of western Alaska are reliant on regional peoples—not only for awareness of the event but also for detailed information and response. Regional residents, tribal leadership, and communities documented, reported, conducted clean-up activities, and investigated the source of debris on a voluntary basis using personal resources, little to no training, and limited response capacity.
Without regular and relevant collaborative transboundary communications and/or enforcement of existing international marine pollution rules, the Bering Strait region should expect similar or higher levels of marine garbage in the future as industrial ship traffic increases. The Arctic Council’s working group Protection of the Arctic Marine Environment (PAME) seems an appropriate forum for collaboration on addressing this issue. Identifying a primary point of contact within the Russian Federation would be ideal for collaborative time-sensitive communications to address the immediate and shared environmental, ecological, and industrial concerns regarding marine debris that face both Alaska and Chukotka in the unique Bering Strait region.
The authors would like to acknowledge the community members and tribal leadership throughout the Bering Strait region that acted on their food security and wildlife/public health concerns by responding to this anomalous marine debris event. Without their voluntary efforts to communicate, document, and in many cases, package and send in what they were seeing, we would not have the information presented here. We also thank the US Coast Guard (District 17), NOAA Marine Debris Program (Genwest Systems), Alaska Dept. of Environmental Conservation, NOAA Office of Response and Restoration, NOAA Office of Emergency Response (Genwest Systems), NOAA National Ocean Service, Alaska Division of Community and Regional Affairs, US Fish and Wildlife Service, US Environmental Protection Agency, and the Inuit Circumpolar Council for their interest in the debris event and attempts to identify a point of contact with the Russian Federation to discuss this emerging issue.
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November 24, 2021
G. J. Wolken1,2, A. K. Liljedahl3, M. Brubaker4, J. A. Coe5, G. Fiske3, H. Hvidtfeldt Christiansen6, M. Jacquemart7,8, B. M. Jones9, A. Kääb10, F. Løvholt11, S. Natali3, A. C. A. Rudy12, and D. Streletskiy13
1International Arctic Research Center, University of Alaska Fairbanks, Fairbanks, AK, USA
2Alaska Division of Geological & Geophysical Surveys, Department of Natural Resources, Fairbanks, AK, USA
3Woodwell Climate Research Center, Falmouth, MA, USA
4Alaska Native Tribal Health Consortium, Anchorage, AK, USA
5Geologic Hazards Science Center, USGS, Golden, CO, USA
6The University Centre in Svalbard, UNIS, Svalbard, Norway
7Laboratory of Hydraulics, Hydrology, and Glaciology (VAW), Department of Civil, Environmental and Geomatic Engineering, ETH Zurich, Zurich, Switzerland
8Swiss Federal Institute of Forest, Snow, and Landscape Research (WSL), Birmensdorf, Switzerland
9Water and Environmental Research Center, Institute of Northern Engineering, University of Alaska Fairbanks, Fairbanks, AK, USA
10Department of Geosciences, University of Oslo, Oslo, Norway
11Geohazards and Dynamics, NGI, Oslo, Norway
12Northwest Territories Geological Survey, Government of the Northwest Territories, Yellowknife, NT, Canada
13Department of Geography, The George Washington University, Washington, DC, USA
- Retreating glaciers and thawing permafrost are causing local- to regional-scale hazards that threaten lives and livelihoods, infrastructure, sustainable resource development, and national security.
- Permafrost hazards are gradually impacting people across the Arctic, while glacier/permafrost hazard cascades are abrupt, more localized, and most life threatening.
- Broad-scale hazard identification and assessment across the Arctic are needed to better inform stakeholder decision making.
Air temperature increases in the Arctic over the last two decades have been more than twice the global average, prompting an acceleration in glacier mass loss and permafrost degradation (IPCC 2019; Hugonnet et al. 2021; Smith et al. 2021). Beyond the global implications of these rapid changes (e.g., carbon release and sea level rise), the emergence and increase in cryosphere hazards threaten national security (e.g., military infrastructure and population displacement) and the lives of Arctic residents across local to regional scales. Here, we focus on hazards related to glaciers and permafrost and define hazard as the potential occurrence of a natural physical process that may adversely impact human or ecological systems (IPCC 2019).
Observations of glacier and permafrost hazards
About five million people live in the Northern Hemisphere permafrost region, which includes glaciers, and within this region, glacier and permafrost hazards are affecting lives, infrastructure, and ecosystem services (Ramage et al. 2021; Fig. 1). Recent degradation of glaciers and permafrost in the Arctic are leading to emerging biogeochemical threats that have the potential to disrupt ecosystem function and endanger human health (Miner et al. 2021). Thawing of ice-rich permafrost can cause ground subsidence with negative implications for infrastructure, ecosystems, and human lives and livelihoods (Suter et al. 2019; Gibson et al. 2021), while even a warming of permafrost can cause a reduction in its bearing capacity, impacting its ability to support structures (Streletskiy et al. 2012). This is especially apparent in the Russian Arctic where there are centers of high population and industrial economic activity in permafrost zones that act as foci of human-induced permafrost degradation, exacerbating climatically driven changes in the permafrost system (Vasiliev et al. 2020). For example, the recent oil tank collapse in Norilsk, Russia that resulted in the release of 21,000 cubic meters of diesel oil was at least partially attributed to the extremely warm conditions of 2020 in addition to a long-term warming trend in the region (Rajendran et al. 2021). Thawing of cold continuous permafrost in Point Lay and Wainwright, Alaska, caused a complete water system failure for multiple homes and buildings, including the health clinic (Cameron and Romanovsky 2021). As recently as 2009, the borough assumed the risk of thawing as “low” because the permafrost was classified as “continuous” and thought to be cold and stable (Cameron and Romanovsky 2021), yet permafrost degradation through the process of thermal erosion of ground ice also drained the community’s drinking water source lake (Fig. 2; Dobbin 2016). Mountain permafrost degradation can also increase the likelihood of landslides (Hock et al. 2019). For example, a rock avalanche endangered two farms and destroyed a considerable amount of livestock pastures in Signaldalen, northern Norway (Frauenfelder et al. 2018). Field observations showed that the upper limit of the failure corresponded to the lower altitudinal limit of permafrost. The combination of gradual long-term warming and record-high mean near-surface temperatures caused the rock avalanche.
Glacier retreat exposes over-steepened slopes that are prone to destabilization and, if in the presence of deep water, can cause landslide-generated tsunamis (Dai et al. 2020). The Karrat Fjord rock avalanche in 2017 generated a tsunami that killed four people in the village of Nuugaatsiaq, Greenland (Gauthier et al. 2018). Persistent unstable slope hazards keep residents of Nuugaatsiaq from returning home, while similar hazards (Barry Arm fjord) in northwest Prince William Sound, Alaska, have prompted advisories of unsafe travel and possible tsunami inundation. Unstable glacierized mountain regions in southeast Alaska have produced landslides that have generated the tallest tsunamis in the world (Higman et al. 2018), and despite the remote location, these hazards threaten communities, marine traffic, and infrastructure including major communication cables of importance to national security. Glacial lake outburst floods (GLOFs or Jökulhlaups) are abrupt releases of water from glacierized catchments that can significantly endanger downstream communities and infrastructure as well (Kienholz et al. 2020). In response to regular GLOFs from the Vatnajökull ice cap, the government of Iceland has developed a warning system to give local residents time to evacuate and, considering the regularity of GLOF occurrences, knowledge of where to expect flooding. Surging glaciers, where the glacier moves 10-100 times faster than typical, can also be hazardous and have made travel routes impassable in Svalbard, Norway.
A cascade of glacier and permafrost hazards
Glacier and permafrost hazards occur along a spectrum of spatial, temporal, and intensity scales. The largest disasters in terms of reach, damage, and lives lost that involve glaciers and permafrost occur typically through a combination or chain of processes, each potentially representing a hazard by itself. For instance, slope failures and glacier detachments can trigger cascading hazards, especially when slope failures enter water bodies and cause outburst floods, debris flows, and tsunamis (Haeberli et al. 2017; Higman et al. 2018; Jacquemart et al. 2020). These cascading hazards can present a risk to people and infrastructure at great distances (102 km) from the initiating slope failure, and changes in climate can shift hazard zones and scales. For instance, as calving glaciers retreat, larger water bodies are often exposed, increasing the potential for rock avalanches to enter the water and generate devastating displacement waves, which increase the reach and intensity of the hazard.
Drivers of glacier and permafrost hazards
Thawing of permafrost and melting of land ice that formed and was retained over millennia are altering the Arctic landscape baseline condition, with extreme weather events further amplifying the potential for glacier and permafrost hazards. Permafrost temperatures have increased across the circumpolar region since the 1980s (Smith et al. 2021), and permafrost degradation has been documented across much of the Arctic (Liljedahl et al. 2016; Vasiliev et al. 2020). The onset of ice-rich permafrost degradation has been linked to long-term gradual warming combined with extreme events such as unusually warm summers and deep snow cover (Farquharson et al. 2019). A period of unusually warm air temperatures between 2012 and 2016 in southeast Alaska coincided with an increase in rock-avalanche activity and size (Bessette-Kirton and Coe 2020). The influence of degrading permafrost on landslide occurrence is increasingly recognized throughout the Arctic, including Norway (Hilger et al. 2021), Iceland (Sæmundsson et al. 2018), Russia (Leibman et al. 2015), and Canada (Lewkowicz and Way 2019).
Observations of extreme precipitation, such as more intense and prolonged rainfall (e.g., atmospheric rivers), appear to be increasing (Francis et al. 2021). While extreme precipitation events alone can trigger deadly debris flows, such as in Sitka (August 2015) and Haines, Alaska (December 2020), increased rainfall, combined with warming air temperatures, is also documented to drive landslide development in ice-rich permafrost terrain (Kokelj et al. 2015). Similarly, the combination of increased rainfall, unusual warmth that increases glacial ice melt, more crevasses, and retreat and steepening of a glacier appears to encourage glacier surges (Sevestre et al. 2018).
Mountain permafrost is the least monitored permafrost type in the Arctic, and processes linking glaciers and permafrost are poorly understood. Paleorecords and newly discovered processes, however, point to conditions that elevate hazard potential in glacier and permafrost areas. In Norway, the frequency of postglacial landslide activity was dominated by events in the beginning of the Holocene when and where ice sheet retreat was most rapid (Bellwald et al. 2016). Newly discovered processes, e.g., the release of entire glacier tongues from their beds, have been documented in the Arctic, but more data are needed to understand the conditions that favor devastating mass flows of water, ice, and debris (Jacquemart et al. 2020).
Outlook and needs
As the Arctic landscape continues to respond to warming conditions, attention to glacier and permafrost hazards will become increasingly important. The clustering of landslide and glacier detachment events in the immediate aftermath of warming episodes, such as following the last deglaciation, clearly flags the likelihood of increased hazard due to global warming. The recent major landslide tsunami events in Paatuut, Greenland 2000 (Dahl-Jensen et al. 2004), Karrat Fjord, Greenland 2017 (Svennevig et al. 2020), and Taan Fjord, Alaska 2017 (Higman et al. 2018) serve as recent stand-out examples of glacier and permafrost hazards in the Arctic. These events highlight the need for broad-scale hazard identification and assessment to improve our knowledge of glacier and permafrost hazards and better inform stakeholder decision making.
The following are challenges and needs regarding Arctic glacier and permafrost hazards:
- A core need is more extensive baseline data (e.g., ground ice content), via remote sensing, field observations, and community science, to identify hazards and evaluate potential landscape change for adaptation and mitigation planning;
- Existing permafrost and glacier monitoring networks could assist in identifying areas of concern, while also guiding the formation of new monitoring networks;
- Long-term observation of mountain permafrost in the Arctic and refined understanding of how permafrost degradation and glacier retreat processes impact slope stability are needed; and
- Future efforts to address glacier and permafrost hazards in the Arctic will require implementation of a co-production approach (e.g., community members, scientists, and engineers) to find effective adaptation and preparedness options (i.e., early warning systems) to enhance resilience.
We thank Matt Thomas, Twila Moon, Rick Thoman, Rex Baum, Brian Shiro, Janet Slate, and three anonymous reviewers for their constructive reviews of this article. G. J. Wolken received partial support from the Alaska Climate Adaptation Science Center. B. M. Jones was supported by the US National Science Foundation under grants OISE-1927553 and OPP-1806213. Any use of trade, firm, or product names is for descriptive purposes only and does not imply endorsement by the U.S. Government.
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