Unusually thick freshwater ice and its impacts on aquatic resources in the National Petroleum Reserve in Alaska (NPR-A) during the winter of 2020–2021
Abstract
Despite a long-term thinning trend in freshwater ice in northern Alaska, cold low-snow cover winters can still emerge to grow thick ice. In 2021, we observed abnormally thick ice by winter's end on lakes and rivers throughout the Fish Creek Watershed in the National Petroleum Reserve in Alaska. This recent and anomalous winter presented an opportunity to assess how such conditions, more typical of many decades previous, affected aquatic habitat and winter water supply. Observed maximum ice thickness in 2021 of 1.9 m closely matched low-snow ice growth simulations, whereas previous records averaged 1.5 m and more closely matched high-snow ice growth simulations. The resulting extent of bedfast lake ice from late winter synthetic aperture radar (SAR) analysis in 2021 was the highest on record since 1992. This SAR analysis suggests a 33% reduction in liquid water below ice by lake surface area compared with the recent thin-ice winter of 2018 (1.2 m). Together, these results help place the cold, low-snow winter of 2020–2021 in context of the long-term trend toward warmer, snowier winters that appear to becoming more common in Arctic Alaska.
Introduction
Long cold winters, continuous permafrost, and expansive, but shallow, lakes and wetlands characterize many coastal plains of the Arctic. These characteristic physio-climatic conditions are thought to protect subaqueous permafrost from talik development (Lachenbruch et al. 1962; Burn 2002) and limit availability of perennial liquid water for overwintering aquatic habitat, as well as water supply for human activities (Jones et al. 2009; Arp et al. 2019). Historically, freshwater ice in northern Alaska could grow to 2 m thick or more by winter's end, resulting in the majority of shallow lakes, wetlands, and streams freezing solid (Brewer 1958; Sellmann et al. 1975; McNamara and Kane 2009).
Maximum ice thicknesses (MIT) exceeding 2 m was often reported during the 1960s and 1970s for lakes on the Barrow Peninsula (Bilello 1980) and north of Teshekpuk Lake (Weeks et al. 1981). As recently as 1992, Jeffries et al. (1994) also reported MIT exceeding 2 m for Arctic Coastal Plain (ACP) of northern Alaska lakes. These and other ice thickness records have been used for long-term models of MIT suggesting an average of 1.9 m between 1947 and 1997 with simulated ice growth up to 2.5 m thick (Zhang and Jeffries 2000). In the northern Canadian Arctic, MIT records have similarly often exceeded 2 m for numerous lakes during the 1960s and 1970s (Bilello 1980), including a High Arctic lake with a MIT of 2.4 m as recently as 1978 (Woo 1980) and lakes with MIT exceeding 2 m along the western Arctic coast as recently as 1997 (Burn 2002). Lake ice growth simulations for northern Canada suggest MITs ranging from 1.4 to 2.0 m from 1960 to 1990 (Brown and Duguay 2011) and simulated ice growth regularly exceeding 2 m thickness on Baker Lake in northern Canada up until 2002 (Dibike et al. 2011). Both modeling and field studies of Arctic freshwater ice suggest that snow depth rather than air temperature exerts the dominant control on lake ice growth (Zhang and Jeffries 2000; Brown and Duguay 2010; Dibike et al. 2011; Arp et al. 2018).
Pronounced winter warming in the Arctic, particularly along northern Alaskan coastlines (Wendler et al. 2014; Box et al. 2019), follows anticipated Arctic amplification in relation to sea ice decline (Serreze and Barry 2011) and corresponding responses in freshwater ice growth (Alexeev et al. 2016). Although observations of MIT in Arctic Alaska have been temporally and spatially patchy up until the last decade (Arp et al. 2018), simulated MIT for Barrow Peninsula lakes suggests a significant thinning trend of 0.14 m/decade since 1976 (Surdu et al. 2014). Decreasing MIT over recent decades has been closely linked to increasing extents of lakes that no longer freeze solid with bedfast ice according to late winter imaging using synthetic aperture radar (SAR) on the Barrow Peninsula (Surdu et al. 2014) and the central ACP (Arp et al. 2012). Model experiments suggest that both thinning lake ice and decreasing bedfast ice are responding to more early winter ocean-effect snowfall with declining sea ice extent along the Beaufort Sea coast (Alexeev et al. 2016). Yet, more recent late winter SAR analysis over a longer period (1992–2016) than other ACP SAR studies by Surdu et al. (2014) and Arp et al. (2012) suggests only high interannual variability in bedfast-ice extents with few significant trends (Engram et al. 2018). Recent field studies also confirm this high variability in both MIT and lake ice regimes (bedfast vs. floating ice) by examining contrasting winters of 2015–2016 (1.8 m MIT) with 2016–2017 (1.2 m MIT) (Arp et al. 2018). However, in the following two winters on the Barrow Peninsula (2017–2018 and 2018–2019), lake MIT was even thinner, less than 1.2 m (Arp et al. 2020), potentially suggesting an even more rapid decline in freshwater ice thickness or perhaps widening ranges and new patterns of Arctic winter variability.
Here, we report on unusually thick-ice conditions observed during the winter of 2020–2021 in the Fish Creek Watershed (FCW) in the National Petroleum Reserve in Alaska (NPR-A), much more typical of MIT recorded several decades ago (i.e., before the 1990s). Ice thickness observations on lakes and rivers in this recent extreme winter are compared with past observed and simulated records, as well as climate data, to place this winter into a longer-term context. Updated late winter SAR analysis of bedfast-ice extent following Engram et al. (2018) is used to understand how this unusually thick-ice winter may have impacted freshwater habitat and winter water supply. In this region of the NPR-A, both industrial development and subsistence activities are increasingly sensitive to how these natural resources interact with freshwater ice and are responding to climate change, including conditions perhaps more like winters of the past.
Methods
Study area
The FCW drains a 4600 km2 area of the northeastern NPR-A on the ACP approximately equidistance between Prudhoe Bay to the east and Utqiaġvik (formerly Barrow) to the west (Fig. 1). Three alluvial rivers drain the FCW, which is set entirely in the zone of continuous permafrost with depth of frozen ground exceeding 200 m in most upland areas (Jorgenson et al. 2008). The majority of tributary streams have a beaded morphology, initiate from lakes, and serve as important habitat for numerous fish species, both for summer foraging and for migration between shallow lakes and deeper overwintering habitats in rivers and estuaries (Arp et al. 2015; Heim et al. 2019). A recent lake-based classification of the FCW identified 4362 lakes >1 ha covering 19% of the land surface (Jones et al. 2017). Analysis by Grunblatt and Atwood (2014) using late winter SAR imagery shows that 52% of these FCW lakes were shallower than maximum ice thickness (1.6 m) and 48% were deeper with floating-ice regimes (Fig. 1). Drained lake basins cover another 17% of the FCW (Arp et al. 2012) based on regional classification by Frohn et al. (2005) and are considered the dominant wetland type on the ACP (Arp et al. 2019). At least 12 fish species are known to inhabit freshwaters of the FCW (Whitman et al. 2011), several with important subsistence and commercial value, and their presence and abundance are strongly tied to winter ice regimes (Haynes et al. 2014; Beaver et al. 2019). Petroleum development has recently expanded into the FCW and relies heavily on lake water for building winter ice roads and year-round operations (Arp et al. 2019).
Fig. 1.
Ice, snow, and climate observations
Records of lake ice thickness and snow depth measured in late winter (mid-March to early May), when the ice is near its maximum thickness, have been made on the Barrow Peninsula since 1962. Many of these observations were made by the Cold Regions Research and Engineering Lab (Bilello 1980) and later by the Alaska Lake Ice and Snow Observation Network (Morris and Jeffries 2010). A more expansive lake ice monitoring program, the Circumarctic Lakes Observation Network (CALON; Hinkel et al. 2012), began in 2012 and included late winter ice thickness and snow depth measurements at 57 lakes in 10 regions across Alaska's North Slope, including two regions within the FCW (Inigok and Fish Creek). CALON observations consisted of three to five thickness measurements per lake using a 5 cm auger and ice thickness gauge (Kovacs) coupled with snow depth and density measurements (Arp et al. 2020). MIT is estimated from these late winter field observations by fitting lake ice growth curves that were simulated using a model based on Stefan's law (Leppäranta 1983), forced with air temperature and snow depth data on a daily time step as described in greater detail in Arp et al. (2020). The same modeling approach was also used to simulate long-term MIT scenarios in this study for high-snow conditions using a heat exchange coefficient (α) of 2.1 (equivalent to 30 cm snow depth) and low-snow conditions using α of 3.0 (equivalent to 8 cm snow depth) (Arp et al. 2020) driven by National Weather Service mean daily air temperature data from Utqiaġvik and Deadhorse, as well as shorter-term records from local weather stations in the FCW. Climate data, primarily air temperature, wind speed, and snow depth, are also used to characterize the winter of 2020–2021 and place it in a long-term context. Upland and lake snow surveys in the FCW consisted of 50 snow depth measurements at meter spacing along north- and east-oriented transects and 5 snow density samples to estimate snow-water equivalent. A new snow–ice buoy was also installed in a small lake (Richard's Pond) in the FCW starting in 2020, which tracks ice growth at 12 h intervals using thermistors arrayed through the water column at 10 cm spacing, as well as recording above-lake air temperature. In late April 2021, we measured ice thickness and snow depth at the same CALON lakes as previous surveys (2012–2019), as well as 11 additional lakes concurrent with sampling for fish-species environmental DNA (eDNA) (Fig. 1).
SAR analysis and classification
As described in the literature as early as 1994 (Jeffries et al. 1994), calibrated C-band SAR can be used to accurately determine lake ice regimes (bedfast vs. floating ice) in shallow lakes because of the interaction of microwave energy with the physical properties of lake ice and ability to image at night, during cloud cover, and through dry snow to detect the presence or absence of liquid water below ice. In this study, we compared additional Sentinel-1 data acquired in mid-April to extend the lake ice regime record to 2021 for Inigok and Fish Creak regions of interest (ROIs), originally analyzed between 1992 and 2016 (Engram et al. 2018). Five additional April SAR scenes from Sentinel-1A and -1B for each region were selected to capture ice conditions as close as possible to MIT, but before the onset of spring melt, which typically occurs in mid-May, to avoid dampening the SAR signal from the presence of liquid water in melting snow or ponded on the ice surface. SAR data processing and ice classification methods followed those of Engram et al. (2018). Briefly, all data were first radiometrically calibrated to sigma-naught (σ0), terrain-corrected, and then geocoded to arrive at intensity terrain-corrected GeoTiff images, using the SNAP tool suite from the European Space Agency with the Copernicus 30 elevation model. Lake perimeters for each region, used to create a land mask to isolate only the lake ice pixels, were derived from IfSAR elevation data including use of Western Arctic Coastal Plain lake perimeters (Jones and Grosse 2013). A unique threshold for each SAR scene for each region was determined by utilizing the expectation–maximization (EM) approach (Ajadi et al. 2016), which assumed the bimodal probability density function of all lake ice pixels was a mixture consisting of the bedfast- and floating-ice pixel distribution. The EM algorithm (Engram et al. 2018) provides the means and variances of SAR σ0 for bedfast- and floating-ice classes as well as the unique threshold to delineate these lake ice regimes. Classification results from SAR data from different C-band platforms can be compared using an interactive threshold intensity for each SAR scene (Engram et al. 2018). Different SAR platforms could be compared since a scene-specific threshold was used instead of an absolute threshold. All platforms from 1992 to 2021 used a C-band wavelength, and five of the six SAR platforms used were European Space Agency instruments specifically designed to follow up previous missions by using comparable imaging parameters. In total from 1992 to 2021, we used 29 scenes for Fish Creek and 29 scenes for Inigok, with no data available for 1 year in each region (Fish Creek has no data for 1999 and Inigok has no data for 1997).
Results
Before any river or lake ice was drilled in late April 2021, thin wind-swept snow conditions were strikingly apparent on lakes with much bare ice, along river corridors with exposed sand bars and shrubs, and across wide expanse of tundra with visible sedges, cottongrass, and dwarf birch (Fig. 2). For comparison, in many if not most years during late winter fieldwork, almost all ACP surfaces are uniformly white and the shadows and orientation of sastrugi snow drifts are the main features visible on otherwise flat topography. However, a newly installed ice thickness buoy that transmitted data via satellite daily at Richard's Pond, approximately 10 km west of Nuiqsut, had indicated that the lake ice had reached nearly 2 m thickness (Fig. 3). Still, these new snow–ice buoy data were not yet calibrated nor had the technique been well tested, such that these readings appeared suspect in comparison to many recent years of physical measurements when MIT barely surpassed 1 m thickness by late April.
Fig. 2.
Fig. 3.
Measurement of ice at 15 floating-ice lakes revealed an average thickness of 1.8 m, excluding three lakes that were unexpectedly frozen solid with bedfast ice (Fig. 1). Ice ranged from 1.57 m thick on a small oxbow lake with 12 cm average snow depth to 1.93 m thick on two lakes with an average snow depth of 3 cm, including abundant bare, snow-free ice. The average ice thickness on the Ublutouch River was 1.91 m. Using local air temperature data to standardize these late April field observations to MIT, which was estimated to occur in mid-May (Fig. 3), suggested that ice grew to 1.91m thickness in the easterly Fish Creek area and 1.81m thickness in the westerly Inigok area (Fig. 4). For comparison, estimated MIT for the previous 14 years (excluding 2020) in the Fish Creek area averaged 1.46 m and ranged from 1.18 m in 2018 to 1.83 m in 2013. A shorter MIT record from the Inigok area (2011–2019) showed an average of 1.47 m that ranged from 1.32 m in 2018 to 1.79 m in 2013 (Fig. 4).
Fig. 4.
Ice growth model estimates of MIT were simulated for low- and high-snow scenarios from 1990 to 2021 to provide context for the 2020–2021 winter of interest, as well as expected maximum ranges of variation over the past 30 years (Fig. 4). High-snow simulations ranged from 1.18 m MIT in 2018 to 1.50 m MIT in 1992 and low-snow simulations ranged from 1.71 m MIT in 2018 to 2.17 m MIT in 1992. Average winter (October–April) air temperatures recorded at Utqiaġvik for thin- and thick-ice years were −13.7 °C (2017–2018) and −22.0 °C (1991–92), respectively, compared with −17.2 °C in 2020–2021 (Fig. 5). Observed MIT for Barrow Peninsula lakes in 1992 was 202 cm with average snow depths (Jeffries et al. 1994); however, we are not aware of any ice thickness measurements from late winter of 2021 in this region for comparison. For observed MIT in the Fish Creek area, over half (60%) of years were close to or below the high-snow simulations, 33% fell in the middle range, and only the year 2021 tracked the low-snow simulations closely (Fig. 4). A similar distribution was apparent for the shorter record of MIT observations from the Inigok area. In the years when observed MIT closely matched high-snow simulations (2006–2009, 2011–2012, 2014, and 2018–2019), late winter (April) snow depth in Utqiaġvik averaged 31 cm (±9 cm s.d.) compared with 18 cm (±5 cm s.d.) of snow for years when MIT was closer to low-snow simulations of ice growth (Figs. 4 and 5). Late winter snow depth on lakes recorded in the FCW are much more relevant to ice growth conditions than tundra snow and these shorter records only show slightly more snow (21 ± 3 cm s.d.) during years matching high-snow simulations, compared with snow depths (16 ± 4 cm s.d.) in years matching low-snow simulations. End-of-winter snow observed in 2021 on lakes in the FCW averaged 10 cm depth, while tundra snow conditions in the same year in Utqiaġvik were not reported.
Fig. 5.
Fig. 6.
The landscape-scale impact of ice thickness on the ACP may be best seen by analysis and classification of late winter SAR imagery to document the extent of lakes that freeze solid with bedfast ice. In the Fish Creek area in April 2021, 63% of lake surface area had bedfast ice compared with an average extent of 51% for the previous 28 years (Fig. 6A). Observed MIT in the Fish Creek area explained 73% (P < 0.01) of the variation in lake bedfast-ice extent with the winter of 2008 removed from this analysis (Fig. 6B). At the end of 2007, lake levels were notoriously low on the ACP (Jones et al. 2009), which can have an important impact on lake ice regimes in the subsequent winter (Arp et al. 2018). In the Inigok area, where lakes are deeper, but with wide shallow shelves (Fig. 7A), 55% of lake surface area had bedfast ice in April 2021, which was very similar to conditions observed with SAR in April 2013 and higher than the long-term average of 46% lake bedfast-ice extent (Fig. 6A). MIT explained a slightly higher portion of the interannual variation in bedfast-ice extent in the Inigok area compared with the Fish Creek area (Fig. 6B). This slight difference in relationship strength may be because Inigok area lakes are deeper and there are many more lakes in the Fish Creek area that freeze entirely solid in thick-ice years and may support mostly floating ice in thin-ice years. Classification of ice regimes as either bedfast-ice lakes (>95% of surface area frozen solid) or floating-ice lakes (>5% of surface area with liquid water below ice) suggested that of 3618 lakes analyzed in the FCW (both ROIs), 27% had floating-ice regimes in the winter of 2020–2021. This is compared with the recent thin-ice year of 2017–2018 when 54% of the lakes were classified as having floating-ice regimes.
Fig. 7.
Taking advantage of the widely varying MIT and bedfast-ice extents for recent late winters allowed us to estimate the extent of lake area available for overwintering habitat and liquid water extraction in a warm, snowy winter (2018) vs. a very cold, low-snow winter (2021) (Fig. 7). This analysis suggests that an approximate additional 78 km2 of lake surface area (12%) was potentially available for overwintering fish habitat and liquid water extraction over the full winter of 2017–2018 compared with the recent winter of 2020–2021 in the Inigok area. In the smaller Fish Creek SAR analysis area, approximately 49 km2 more lake surface area (27%) was potentially available for overwinter fish habitat and liquid water extraction in 2017–2018 compared with 2020–2021. The majority of this transient winter aquatic habitat in the Inigok area is along shelf margins of large deep lakes and a few very small lakes and ponds that freeze entirely with bedfast in some years and retain some liquid water below floating ice in others (Fig. 7A). In the Fish Creek area, however, many relatively large lakes were entirely bedfast with no potential overwinter habitat in 2020–2021, while these same lakes maintained liquid water through the entire winter in 2017–2018 (Fig. 7B), as well as the majority of previous years.
Differences in winter water availability between the extremely thick-ice winter of 2020–2021 and lower ice growth winter of 2017–2018 were also estimated based on the same SAR classifications of bedfast vs. floating ice in both ROIs, though variation in lake bathymetry or shallow-zone depth distributions among lakes and region will have some impact on estimation accuracy. In the Inigok area, we estimated that end-of-winter water availability was 0.49 m greater per lake in 2018 compared with 2021, equivalent to 7800 hectare -meters (20.6 billion US gallons or 78 million m3). In the smaller Fish Creek ROI where differences in MIT were greater between these years, we estimated that end-of-winter water availability was 0.74 m greater per lake in 2018 compared with 2021, equivalent to 3626 hectare-meters (9.6 billion US gallons or 36 million m3). Winter water use from lakes in the northeastern NPR-A varies greatly from year to year depending on industrial exploration activities ranging from <50 hectare -meters (132 million US gallons or 500 000 m3) in 2010–2016 to 200 hectare-meters (528 million US gallons or 2 million m3) in 2017 and 2018 (Arp et al. 2019).
Discussion
Large interannual variations in freshwater MIT and its consequences for key components of the Arctic system (habitat, water supply, and permafrost) have long been recognized in northern Alaska (Zhang and Jeffries 2000). Despite a long-term trend toward declining MIT (Arp et al. 2012; Surdu et al. 2014), along with several winters of record thin MIT and low extents of bedfast ice (Arp et al. 2018), widely varying winter air temperatures, and particularly snow accumulation, still appear to make high interannual variability in MIT the dominant pattern.
A number of studies in northern Alaska have documented the importance of MIT relative to water depth for predicting summer fish (Haynes et al. 2014; Laske et al. 2016; Heim et al. 2019) and plankton (Beaver et al. 2019) communities based on classifying waters as freezing solid (bedfast ice) or maintaining liquid water through the winter (floating ice). What is less certain is how aquatic biota respond to changing winter habitat from year to year in a particular lake or stream, watershed, or regionally. Management of winter water supply for industry on Alaska's North Slope is primarily based on fish communities present during summer inventories and water available under static MIT and lake levels (Arp et al. 2019). Understanding whether unusually thin- or thick-ice conditions and corresponding expansion and contraction (or elimination) of overwintering habitat have a significant effect on fish communities and other aquatic biota is warranted. Do species of long-standing subsistence value, such as broad whitefish (Coregonus nasus), thrive in thick-ice winters and do important forage-based species such as ninespine stickleback (Pungitius pungitius) explode following warm snowier winters because of greatly expanded overwintering habitat? Pacific salmon (Oncorhynchus spp.), which may be expanding their range into North Slope rivers (Nielsen et al. 2013), may find suitable spawning habitat in multiple winters with thin ice and then have a subsequent cohort limited by a thick-ice winter in following years.
Perhaps an even more interesting example of a range-expanding aquatic organism and ice is the North American beaver (Castor canadensis), which has expanded into NW Arctic Canada (Jung et al. 2017) and has been hypothesized to be advancing toward Alaska's North Slope (Tape et al. 2018). Thick winter ice may have historically excluded beavers from many regions of the Arctic, but recently these limitations may be relaxing—with the exception of the winter of 2020–2021 on Alaska's North Slope. Another aquatic mammal that relies on under-ice habitat, the muskrat (Ondatra zibethicus), has in fact been observed increasingly along the Colville River in northern Alaska in recent years (Fish Creek Traditional Ecological Knowledge Workshop 2016). During the summers of 2018 and 2019, we made several surprising first-time muskrat sightings in lakes, streams, and rivers of the FCW, yet none were observed during the summers of 2021 and 2022. These anecdotal observations only serve to open broader questions about how to monitor and manage aquatic organisms, habitats, and water supply with ongoing climate change, which includes occasional winters more typical of historically thick-ice conditions.
Our report here on the very thick freshwater ice conditions in response to a cold and, likely more importantly, unusually low-snow winter helps to provide a context for better understanding how long-term trends in winter climate, including perhaps increasingly extreme variability, may impact resources of management concern in the NPR-A and the Arctic more broadly. For example, impacts to overwintering fish and winter water supply during sudden thick-ice years will be magnified in regions with many shallow lakes versus regions with deeper lakes or lakes of varying depth. Incorporating both fundamental techniques, such as traditional ecological knowledge, and emerging technologies, such as eDNA to detect fish presence, may provide a path forward to understanding the role of new Arctic winters on aquatic natural resources. Continued tracking of winter ice conditions, in addition to the weather and climate factors that regulate ice growth, particularly snow, and the biological response to winter conditions, particularly fish abundance and distribution, will be crucial to such efforts.
Acknowledgements
Funding for this research was provided by the Bureau of Land Management's Arctic Office and a grant from the National Science Foundation (#183662). Many scientists contributed valuable ice thickness measurements in this study region over the past six decades. The National Weather Service provided important climate data to support this analysis. The Alaska Satellite Facility provided the Sentinel-1 data from the European Space Agency for this study. We also thank O. Ajadi for the use of Matlab EM algorithm code.
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Information & Authors
Information
Published In
Arctic Science
Volume 9 • Number 2 • June 2023
Pages: 497 - 505
History
Received: 12 May 2022
Accepted: 8 September 2022
Accepted manuscript online: 23 September 2022
Version of record online: 7 November 2022
Copyright
© 2022 The Author(s). This work is licensed under a Creative Commons Attribution 4.0 International License (CC BY 4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original author(s) and source are credited.
Data Availability Statement
The majority of background data presented in this paper are archived with the Arctic Data Center, specifically Melanie Engram. 2018. Floating and bedfast lake ice regimes across Arctic Alaska using space-borne SAR imagery from 1992–2016; Arctic Data Center. Doi:10.18739/A2CJ87K8H; Christopher Arp and Jessica Cherry. 2020. Seasonal maximum ice thickness data for rivers and lakes in Alaska from 1962 to 2019. Arctic Data Center. Doi:10.18739/A26688J9Z; and Christopher Arp. 2018. Arctic Alaska tundra and lake snow surveys from 2012–2018. Arctic Data Center. Doi:10.18739/A2086356K. Meteorological data are publicly available from NOAA through the National Climate Data Center (https://www.ncei.noaa.gov/). Additional data collected in 2021 that are not yet archived are available upon request to the authors.
Key Words
Authors
Author Contributions
C.A.: Conceptualization, Data curation, Formal analysis, Funding acquisition, Investigation, Methodology, Project administration, Resources, Supervision, Visualization, Writing – original draft. M.E.: Formal analysis, Methodology, Software, Visualization, Writing – review & editing. A.B.: Formal analysis, Investigation, Methodology, Writing – review & editing. K.D.: Project administration, Resources, Supervision, Writing – review & editing.
Competing Interests
The authors declare there are no competing interests.
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Cite As
Christopher D. Arp, Melanie Engram, Allen C. Bondurant, and Katie A. Drew. 2023. Unusually thick freshwater ice and its impacts on aquatic resources in the National Petroleum Reserve in Alaska (NPR-A) during the winter of 2020–2021. Arctic Science.
9(2): 497-505. https://doi.org/10.1139/as-2022-0027
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