Ice Duration Research Articles

Future Global River Ice in CMIP6 Models under Climate Change

Abstract River ice changes due to climate change significantly impact river hydrology, economies, and societies. This study employed the CMIP6 data and a river ice model to predict global river ice changes in response to climate change. Results indicate significant declines in global river ice due to global warming. With each 1°C increase in surface air temperature (SAT) in the future, river ice extent of ice-affected rivers decrease by 2.11 percentage points, and ice duration shorten by 8.4 days. Under the shared socioeconomic pathways 2-4.5 (SSP2-4.5) scenario, the long-term mean SAT is 1.2°–2.5°C higher than in the near term. This leads to a 1.9–4.4-percentage-point decrease in global river ice extent, a 6.8–15.1-day decrease in river ice duration, and ice-free rivers increasing by up to 4.02%. The SSP5-8.5 scenario predicts a warmer long-term mean SAT, leading to greater reductions in river ice. Geographically, river ice loss is most notable in North America, Europe, Siberia, and the Tibetan Plateau (TIB), particularly in peninsular, coastal, and mountainous regions due to the combined effects of initial temperatures and temperature increases. Overall, the eastern Europe (EEU) shows the greatest loss of river ice on average. Monthly analyses show the most substantial decreases from October to June, indicating pronounced seasonal variability. This study provides valuable insights for addressing challenges related to river ice changes in high-latitude and high-elevation regions. Significance Statement River ice has a significant impact on various aspects, including hydrology, ecology, and the economy. The ongoing global warming phenomenon has resulted in a decline in river ice. This ice acts as a barrier, affecting river gas exchange and influencing the metabolism of the river, which is crucial for regulating greenhouse gas (GHG) emissions. The primary objective of this research is to examine the response of river ice to future climate change. The outcomes of this study will play a role in estimating future GHG emissions and understanding river metabolism, as well as providing a valuable reference for tackling emerging challenges in resource acquisition in high-latitude and high-altitude regions.

Phenological Shifts in Lake Ice Cover Across the Northern Hemisphere: A Glimpse Into the Past, Present, and the Future of Lake Ice Phenology

AbstractLong‐term ice phenology records quantify the effects of climate change on Northern Hemisphere lakes. This study uses lake ice phenological records across a gradient of lake sizes (0.1–31,967.8 km2 in lake surface area) obtained from community science networks. We compiled in situ ice phenological records for 2,499 lakes across 15 countries for an average of 30 years. These data revealed that for the last 50 years (1971–2020), the annual mean duration of lake ice cover decreased at a rate of 9 days per decade, with a regime shift in lake ice phenology in the late 1980s. We projected that at the end of the century (2070–2099), ice duration will decrease by an average of 10 days when compared to the historical time period (1971–2000) for the shared socioeconomic pathway (SSP) 1–2.6 climate scenario (SSP126), 23 days for SSP370, and 28 days for the SSP585. Impending human development can enhance or attenuate lake ice loss, as adaptation strategies can accelerate fossil fuel use, result in conflict, or seek strategies apart from fossil fuel development. These future pathways have critical implications for the future preservation of lake ice cover.

Patterns and Trends in Northern Hemisphere River Ice Phenology from 2000 to 2021

River ice plays a crucial role in hydrology, ecosystems, and socio-economic systems in mid-to-high latitude regions. However, there is a notable gap in the analysis of patterns and trends in river ice phenologies and their influence factors at the river level. In this study, we developed a practical method to identify river ice phenologies by leveraging Landsat observations from 2000 to 2021, and established a comprehensive dataset encompassing 7970 river segments across the entire Northern Hemisphere. Our results revealed that the mean freeze-up date, break-up date, and ice duration for these river segments were October 24, May 4, and 192.1 days, respectively. Notably, 56% of the river segments exhibited a warming trend, with the average freeze-up date delayed by 2.7 days per decade, break-up date advanced by 2.5 days per decade, and ice duration shortened by 5.5 days per decade—nearly five times the documented decrease rate over the past 150 years. Furthermore, high-latitude polar regions and the Qinghai-Tibet Plateau demonstrated the most pronounced decreases in ice duration, exceeding 7.0 days per decade on average. We observed a substantial relative contribution, reaching up to 70%, of surface air temperature (SAT) in middle and low latitude regions characterized by relatively high winter temperatures. However, as winter temperatures decrease, the relative influence of SAT diminishes, while the contributions of precipitation, solar radiation, and residuals increase. Our dataset provided essential baseline for further understanding the fundamental physical processes within river systems, offering crucial insights for river management, hydrological disaster risk control, climate change research, and ecosystem conservation efforts.

Impact of Meteorological Factors on the Wire Icing Thickness and Growth Rate in Mountain Areas under Dry and Wet Growth Patterns

Wire icing events pose a significant threat to the southern power grid’s transmission lines in China. Fifteen such events were identified from 2018 to 2020 on the Guilin-Haiyang Mountain transmission line. Hourly measurements of ice thickness and concurrent meteorological data were analyzed using the Makkonen model’s freezing rate formula to categorize the events into distinct growth patterns: dry and wet. The relationship between wire icing and meteorological factors across different micro-topography (windward slope, leeward slope, and pass) was further explored. Several key conclusions can be drawn. First, the altitude is positively correlated to the icing thickness, but relatively independent of the icing rate; however, such independence between the icing rate and altitude cannot be interpreted by the negative correlation of altitude with temperature and the positive relationship between wind speed and liquid water content. Second, a pronounced connection of the icing rate with meteorological factors is not shown until the wet and dry patterns are separated. Notably, the correlations differ between these two patterns, with icing rate being negatively correlated with temperature for the wet growth process, but positively correlated with wind speed and liquid water content for the dry growth process. Third, both wet and dry growth processes exist across the icing events. A shift from wet to dry growth was evident with increasing altitude. At the mountain’s base, wet growth predominates, with the icing rate determined by the temperature close to the freezing point, whereas the higher temperature and lower liquid water flux account for the shorter wire icing duration, lower icing rate, and thus the thinner icing thickness at the leeward slope compared to the windward slope at a similar altitude. This study sheds light on the variations in icing rates under different micro-topographies and the underlying physical mechanisms governing icing growth patterns and provides a much-needed understanding of these distinct growth processes on the development of a more sophisticated predictive model for conductor icing.

Modeling Climate Characteristics of Qinghai Lake Ice in 1979–2017 by a Quasi-Steady Model

Lakes on the Qinghai Tibet Plateau (QTP) are widely distributed spatially, and they are mostly seasonally frozen. Due to global warming, the thickness and phenology of the lake ice has been changing, which profoundly affects the regional climate evolution. There are a few studies about lake ice in alpine regions, but the understanding of climatological characteristics of lake ice on the QTP is still limited. Based on a field experiment in the winter of 2022, the thermal conductivity of Qinghai Lake ice was determined as 1.64 W·m−1·°C−1. Airborne radar ice thickness data, meteorological observations, and remote sensing images were used to evaluate a quasi-steady ice model (Leppäranta model) performance of the lake. This is an analytic model of lake ice thickness and phenology. The long-term (1979–2017) ice history of the lake was simulated. The results showed that the modeled mean ice thickness was 0.35 m with a trend of −0.002 m·a−1, and the average freeze-up start (FUS) and break-up end (BUE) were 30 December and 5 April, respectively, which are close to the field and satellite observations. The simulated trend of the maximum ice thickness from 1979 to 2017 (0.004 m·a−1) was slightly higher than the observed result (0.003 m·a−1). The simulated trend was 0.20 d·a−1 for the FUS, −0.34 d·a−1 for the BUE, and −0.54 d·a−1 for the ice duration (ID). Correlation and detrending analysis were adopted for the contribution of meteorological factors. In the winters of 1979–2017, downward longwave radiation and air temperature were the two main factors that had the best correlation with lake ice thickness. In a detrending analysis, air temperature, downward longwave radiation, and solar radiation contributed the most to the average thickness variability, with contributions of 42%, 49%, and −48%, respectively, and to the maximum thickness variability, with contributions of 41%, 45%, and −48%, respectively. If the six meteorological factors (air temperature, downward longwave radiation, solar radiation, wind speed, pressure, and specific humidity) are detrending, ice thickness variability will increase 83% on average and 87% at maximum. Specific humidity, wind, and air pressure had a poor correlation with ice thickness. The findings in this study give insights into the long-term evolutionary trajectory of Qinghai Lake ice cover and serve as a point of reference for investigating other lakes in the QTP during cold seasons.

Holocene paleoceanographic variability in Robertson Bay, Ross Sea, Antarctica: A marine record of ocean, ice sheet, and climate connectivity

Accelerating ocean-driven basal melting of Antarctic ice shelves in recent decades has implications for sea level rise and global overturning circulation. Here, we reconstruct oceanographic conditions at the confluence of the Ross Sea and the Southern Ocean by analyzing a multi-proxy Holocene marine sedimentary record collected from Robertson Bay. A ramped pyrolysis oxidation radiocarbon age-depth model provides a timeline for glacial behavior and oceanographic changes over the last 6700 years. The diatom assemblage, magnetic susceptibility, grain size, total organic carbon and nitrogen, trace elements, and bulk δ13C are used as proxies for changing ocean and glacial conditions, which we interpret in the context of modern oceanographic measurements.Our record shows evidence of persistent ice cover in the northwestern Ross Sea during the Antarctic mid-Holocene climate optimum (ca. 5 cal kyr BP). Based on this observation, we suggest that meltwater and iceberg discharge associated with ice sheet retreat in the Ross Sea region altered local oceanography during the mid-Holocene. The onset of modern style oceanographic conditions in Robertson Bay occurred at ca. 4 cal kyr BP. Stable late Holocene conditions in are punctuated by a period of enhanced polynya activity and upwelling of nutrient rich Circumpolar Deep Water ca. 0.8 cal kyr BP and an increase in the seasonal duration of sea ice after 0.7 cal kyr BP, during the Little Ice Age. The response of the marine environment in Robertson Bay to mid-Holocene ice sheet retreat and natural climate variability during the last millennium underscores the sensitivity of the Antarctic ice-ocean interface to projected changes in coming decades.

Nonlinear responses in interannual variability of lake ice to climate change

AbstractClimate change is contributing to rapid changes in lake ice cover across the Northern Hemisphere, thereby impacting local communities and ecosystems. Using lake ice cover time‐series spanning over 87 yr for 43 lakes across the Northern Hemisphere, we found that the interannual variability in ice duration, measured as standard deviation, significantly increased in only half of our studied lakes. We observed that the interannual variability in ice duration peaked when lakes were, on average, covered by ice for about 1 month, while both longer and shorter long‐term mean ice cover duration resulted in lower interannual variability in ice duration. These results demonstrate that the ice cover duration can become so short that the interannual variability rapidly declines. The interannual variability in ice duration showed a strong dependency on global temperature anomalies and teleconnections, such as the North Atlantic Oscillation and El Niño–Southern Oscillation. We conclude that many lakes across the Northern Hemisphere will experience a decline in interannual ice cover variability and shift to open water during the winter under a continued global warming trend which will affect lake biological, cultural, and economic processes.

Lipid composition, caloric content, and novel oxidation products from microbial communities within seasonal pack ice cores

Sea ice is a critical feature of polar environments with importance for coastal ecosystems. Along the West Antarctic Peninsula (WAP), climate change is causing decreases in seasonal sea ice duration and extent. Organic carbon within sea ice is an important aspect of southern ocean carbon cycling but less studied than water column or sedimentary carbon reservoirs. Though conditions within sea ice can be extreme, phytoplankton are able to flourish and serve as a key food source for higher trophic levels, especially in the spring and fall. A portion of this sea ice phytoplankton biomass is composed of lipids, which are both calorically dense and useful as tracers of biological processes within the sea ice. To better understand both the trophic value and the diversity of lipids present within sea ice we employed high-resolution accurate-mass mass spectrometry to analyze ice core samples from six sites collected along the peninsula in November 2018. Using untargeted methods we annotated 1,173 intact lipid species across 14 classes of intact polar lipids, triacylglycerols, and pigments. We compared lipids’ physical distribution within sea ice cores and found they are highly geographically and physically heterogenous within sites. Ratios between intact polar lipid classes show little signs of phytoplankton nutrient stress; a finding consistent with internally nutrient replete sea ice brines. We found key differences in the composition between pack ice versus fast ice and observed chlorophyll a to be inconsistently correlated with triacylglycerol content. We determined the mean caloric content of lipids within pack ice (4.45 ± 3.47 kJ m−2) and found that caloric densities from the lipids alone were in the range of total water column energy content. Lastly, we show evidence of fatty acid hydroxy fatty acid triacylglycerols within the ice matrix and discuss possible biochemical sources of these novel biomarkers in an ocean system. These results shed light on the chemical diversity of a dynamic and ecosystem relevant carbon pool.

Declining lake ice in response to climate change can impact spending for local communities.

Lake ice is an important socio-economic resource that is threatened by climate change. The cover and duration of lake ice are expected to decline as air temperatures warm in the coming decades, disrupting a previously reliable source of income for many activities dependent on lake ice. The economic consequences of climate-induced lake ice loss remain unexplored, creating a significant research gap. The purpose of this study was to quantify the monetary spending associated with lake ice and how climate change may impact that value. Using a series of General Circulation Models (GCMs), greenhouse gas emissions scenarios, and models for lake ice cover, we predicted changes in lake ice by the end of the 21st century for the Northern Hemisphere. We also synthesized examples of spending associated with lake ice activities and discussed the potential implications expected with declining ice cover. We found that lake ice will decrease in area by 44,000-177,000 km2 and shorten in duration by 13-43 days by 2100. Using 31 examples of revenue from lake ice, we found that lake ice generates spending of over USD 2.04 billion to local communities and economies. We also found that countries predicted to experience the greatest ice loss by the end of the century are those that currently have the largest GDP, highest greenhouse gas emissions, and are most dependent on freshwater withdrawal. Our findings confirm predicted losses in lake ice that are expected because of climate change and quantify some of the potential consequences for local communities. Here we highlight lake ice as another casualty of human-caused climate change that will have profound socio-economic implications.

The Impact of Bare Ice Duration and Geo‐Topographical Factors on the Darkening of the Greenland Ice Sheet

AbstractDark (low albedo) surface ice on the Greenland Ice Sheet enhances melting and subsequent runoff, a major mass loss contributor during the ablation season. The accumulation of both biological (e.g., glacier ice algae) and abiotic (e.g., mineral dust) light‐absorbing particulates are important darkening factors, that are potentially influenced by the duration of snow‐free, bare ice (a phenological factor), and other geo‐topographical factors such as elevation, slope, aspect and the distance from the ice margin. Here, we present the first medium‐resolution (30 m) analysis of the phenological and geo‐topographical controls on the distribution of dark ice in SE and SW Greenland from statistical analysis of data derived from a harmonized satellite albedo product and ArcticDEM. The duration of bare ice primarily controls the distribution of dark surface ice, allowing for algae growth on inland ice surfaces in particular, whereas geo‐topographical factors are only secondary controls.

Мониторинг гололедно-изморозевых отложений на территории России

A methodology for monitoring glaze-rime deposits (GRD) is developed to be included in the national climate monitoring system. Based on this methodology, in order to assess the current state of GRD characteristics, the standard station characteristics (total number of cases, total duration, and average weight) are calculated for each type of GRD for the period of 1991-2020. The anomalous pattern of GRD throughout Russia is assessed. The trends are analyzed that are characterized by linear trend coefficients based on the weather station data and on the average values for quasihomogeneous regions (1984-2021). The study showed a statistically significant positive trend for the number of cases, duration, and weight of wet snow deposits in several regions. In some quasihomogeneous regions, both positive and negative significant trends in the number of cases, duration, and weight of crystal rime are obtained. In some quasihomogeneous regions, a significant positive trend for the number of cases and duration of glaze ice is also obtained. Keywords: monitoring methodology, glaze-rime deposits, glaze ice, rime, wet snow, anomaly, trend

Monitoring of Lake Ice Phenology Changes in Bosten Lake Based on Bayesian Change Detection Algorithm and Passive Microwave Remote Sensing (PMRS) Data.

Lake ice phenology (LIP), hiding information about lake energy and material exchange, serves as an important indicator of climate change. Utilizing an efficient technique to swiftly extract lake ice information is crucial in the field of lake ice research. The Bayesian ensemble change detection (BECD) algorithm stands out as a powerful tool, requiring no threshold compared to other algorithms and, instead, utilizing the probability of abrupt changes to detect positions. This method is predominantly employed by automatically extracting change points from time series data, showcasing its efficiency and accuracy, especially in revealing phenological and seasonal characteristics. This paper focuses on Bosten Lake (BL) and employs PMRS data in conjunction with the Bayesian change detection algorithm. It introduces an automated method for extracting LIP information based on the Bayesian change detection algorithm. In this study, the BECD algorithm was employed to extract lake ice phenology information from passive microwave remote sensing data on Bosten Lake. The reliability of the passive microwave remote sensing data was further investigated through cross-validation with MOD10A1 data. Additionally, the Mann-Kendall non-parametric test was applied to analyze the trends in lake ice phenology changes in Bosten Lake. Spatial variations were examined using MOD09GQ data. The results indicate: (1) The Bayesian change detection algorithm (BCDA), in conjunction with PMRS data, offers a high level of accuracy and reliability in extracting the lake ice freezing and thawing processes. It accurately captures the phenological parameters of BL's ice. (2) The average start date of lake ice freezing is in mid-December, lasting for about three months, and the start date of ice thawing is usually in mid-March. The freezing duration (FD) of lake ice is relatively short, shortening each year, while the thawing speed is faster. The stability of the lake ice complete ice cover duration is poor, averaging 84 days. (3) The dynamic evolution of BL ice is rapid and regionally distinct, with the lake center, southwest, and southeast regions being the earliest areas for ice formation and thawing, while the northwest coastal and Huang Shui Gou areas experience later ice formation. (4) Since 1978, BL's ice has exhibited noticeable trends: the onset of freezing, the commencement of thawing, complete thawing, and full freezing have progressively advanced in regard to dates. The periods of full ice coverage, ice presence, thawing, and freezing have all shown a tendency toward shorter durations. This study introduces an innovative method for LIP extraction, opening up new prospects for the study of lake ecosystem and strategy formulation, which is worthy of further exploration and application in other lakes and regions.

Unveiling lake ice phenology in Central Asia under climate change with MODIS data and a two-step classification approach

Lakes in Central Asia, characterized largely by a semiarid climate and delicate ecosystems, are quite sensitive and vulnerable to climate change but remain less exploited, due mostly to a lack of in-situ measurements. Lake ice phenology is an essential climate variable identified by the Global Climate Observation System. To overcome the overestimation of clouds by the MODIS cloud mask, we developed and distributed a two-step Random Forest algorithm based on MODIS data on the Google Earth Engine. This algorithm first distinguishes cloudy pixels from non-cloudy pixels, and then ice pixels are discriminated from non-cloudy pixels using additional thermal infrared information. We validated the algorithm by implementing it over several boreal lakes with in-situ records in North America and compared our results with existing lake ice phenology datasets. We subsequently retrieved lake ice phenology for 20 large lakes (> 100 km2) in Central Asia from 2001 to 2021 and examined trends in lake ice phenology over this period. On average, lakes in Central Asia underwent later freezing at 0.13 d/yr, earlier thawing at 0.32 d/yr, and shorter ice duration at 0.45 d/yr, with over half of the lakes witnessing significant trends in at least one ice phenology indicator. To evaluate the impact of meteorological factors on lake ice phenology, we built a linear mixed model that predicts ice phenology using meteorological variables from ERA5. Daily mean air temperature dominates ice phenology, with mean air temperature during October to June in the following year explaining approximately 35% of the variance of the duration between freezing and thawing for each lake. Our study offers a comprehensive analysis of lake ice phenology in Central Asia under climate change.

Variability in lake bacterial growth and primary production under lake ice: Evidence from early winter to spring melt

AbstractClimate change is causing seasonally ice‐covered lakes of the boreal region to undergo changes in their winter regime by altering patterns of precipitation and temperature, often reflected as reduced snow and ice cover duration. The duration, extent and quality of ice, and snow cover have a pivotal role for production and carbon cycling in lakes in winter, with potentially cascading effects for the following open water period. We investigated under‐ice carbon cycling by assessing bacterial growth (including bacterial production, bacterial respiration, and bacterial growth efficiency) and primary production at five water depths during early winter, midwinter, late winter and melting season in a boreal lake, and report significantly different temporal patterns. Bacterial respiration was dominant in early and midwinter, whereas the late winter and melting season were dominated by bacterial production. Multiple linear regression models indicated that high early winter bacterial respiration was associated with senescing phytoplankton, whereas bacterial production was promoted by the onset of spring processes. Collectively, bacterial growth indices were inherently linked with bacterioplankton community composition and specific biomarker taxa. Primary production under ice increased in late winter when light‐blocking snow cover melted, and primary production measured from the lake ice exceeded that of the water column at the melting season. Ice samples hosted diverse eukaryotic communities including photoautotrophs, suggesting that the habitat potential of the understudied lake ice and the role of ice for ecological processes at ice melt should be further explored.

Temperature drives variability in recent satellite-derived ice cover trends in Nebraska Sand Hill lakes

ABSTRACT The timing and duration of lake ice cover is a critical driver of lake ecosystem dynamics and an important indicator of climatic change. While much research has focused on lake ice dynamics at high latitudes and in north-temperate lakes, few studies have considered ice dynamics in lakes at lower latitudes. Here we use high-resolution satellite imagery to determine patterns of lake ice cover for 128 Sand Hill lakes from 2016 to 2023. Average ice duration was 112 days and varied between 74 and 158 days. The average dates for ice-on and ice-off were 25 November and 17 March. Ice cover duration for Sand Hill lakes was long compared to lakes at higher latitudes. October–November–December and February–March–April mean atmospheric temperatures were strong drivers of lake ice cover compared to lake-specific factors (e.g., lake area, shoreline complexity). To our knowledge, this represents the first study of lake ice cover in Nebraska Sand Hills and provides baseline data to help determine the effect of climatic changes on lake ecosystems in the Nebraska Sand Hills.

Patterns and drivers for benthic algal biomass in sub-Arctic mountain ponds

This study investigated the spatial variation in total benthic algal biomass and within cyanobacteria, green algae, and diatoms in sub-Arctic ponds. Additionally to more widely used explanatory variables, snowmelt and ice duration were considered as their importance on algal communities is poorly understood. The data comprised algal biomasses from 45 sub-Arctic ponds in the Finnish Lapland. A generalized linear model and hierarchical partitioning were used to identify the significantly influential variables. Cyanobacteria were the most abundant algal group. Trace elements (e.g. Fe, Al, and Mn) were the most significant explanatory variable group in explaining algal biomasses. Macronutrients apart from K were found insignificant in all models. There were positive relationships between some algal biomasses indicating no strong competition between them. Snow and ice variables were found insignificant for all models, but they could have an important secondary role on algal communities. The results highlight the importance of trace elements in shaping algal biomasses in sub-Arctic ponds and thus their wider use in research can be advocated to better understand the productivity of nutrient poor and acidic waters in sub-Arctic regions. Focussing on benthic algal biomasses and the chemical composition of sub-Arctic freshwaters provides important information on the aquatic primary production.

Running overnight and struggling to find sea ice: long-distance movement by an Arctic fox (Vulpes lagopus) from Russia

Given the scale, speed, and complexity of recent changes in the Arctic, our understanding of their multiple implications for Arctic biota is still limited. We detail for the first time in the vast Russian Arctic the long-distance movement of an Arctic fox ( Vulpes lagopus (Linnaeus, 1758)) tracked with a GPS/iridium collar providing considerably high precision (several meters) and frequency of locations (every 4 h). Revealed diurnal activity patterns of the Arctic fox indicate that it ran greater distances in night hours and shortest in day hours during the most intense movement period. The movement records suggested several attempts to leave the land, as it seemed to encounter open water four times on different parts of Yamal peninsula. The Arctic fox crossed the Ob Bay towards the Gydan peninsula and satellite imagery of discontinuous ice during crossing suggested that it might have stayed on pieces of floating ice. Our observation may support evidence that a reduction in the duration and extent of sea ice could affect the ability of Arctic foxes to cover long distances and thus, in the long term, the connectivity between populations. Similar studies are needed aiming to understand movement ecology of the Arctic foxes in the changing Arctic.

Arctic and red fox population responses to climate and cryosphere changes at the Arctic's edge.

Responses of one species to climate change may influence the population dynamics of others, particularly in the Arctic where food webs are strongly linked. Specifically, changes to the cryosphere may limit prey availability for predators. We examined Arctic (Vulpes lagopus) and red fox (V. vulpes) population dynamics near the southern edge of the Arctic fox distribution using fur harvest records from Churchill, Manitoba, Canada between 1955 and 2012. Arctic foxes showed a declining population trend over time (inferred from harvest records corrected for trapping effort), whereas the red fox population trend was relatively stable. The positive relationship between the annual Arctic and red fox harvests suggested interspecific competition did not promote the Arctic fox decline. To investigate alternative mechanisms, we evaluated the relative influence of sea-ice phenology, snow depth, snow duration, winter thaws, and summer temperature on the harvest dynamics of both species in the most recent 32years (1980-2012; n = 29) of our data. Arctic fox harvests were negatively related to the length of time Hudson Bay was free of sea ice. Shorter sea ice duration may reduce access to seal carrion as an alternative winter food source when lemming densities decline. Contrary to our prediction, red fox harvest was not related to summer temperature but was positively related to snow depth, suggesting winter prey availability may limit red fox population growth. Predators have an important ecological role, so understanding the influence of changes in the cryosphere on predator-prey interactions may better illuminate the broader influence of climate change on food-web dynamics.

Uncertainty in projections of future lake thermal dynamics is differentially driven by lake and global climate models.

Freshwater ecosystems provide vital services, yet are facing increasing risks from global change. In particular, lake thermal dynamics have been altered around the world as a result of climate change, necessitating a predictive understanding of how climate will continue to alter lakes in the future as well as the associated uncertainty in these predictions. Numerous sources of uncertainty affect projections of future lake conditions but few are quantified, limiting the use of lake modeling projections as management tools. To quantify and evaluate the effects of two potentially important sources of uncertainty, lake model selection uncertainty and climate model selection uncertainty, we developed ensemble projections of lake thermal dynamics for a dimictic lake in New Hampshire, USA (Lake Sunapee). Our ensemble projections used four different climate models as inputs to five vertical one-dimensional (1-D) hydrodynamic lake models under three different climate change scenarios to simulate thermal metrics from 2006 to 2099. We found that almost all the lake thermal metrics modeled (surface water temperature, bottom water temperature, Schmidt stability, stratification duration, and ice cover, but not thermocline depth) are projected to change over the next century. Importantly, we found that the dominant source of uncertainty varied among the thermal metrics, as thermal metrics associated with the surface waters (surface water temperature, total ice duration) were driven primarily by climate model selection uncertainty, while metrics associated with deeper depths (bottom water temperature, stratification duration) were dominated by lake model selection uncertainty. Consequently, our results indicate that researchers generating projections of lake bottom water metrics should prioritize including multiple lake models for best capturing projection uncertainty, while those focusing on lake surface metrics should prioritize including multiple climate models. Overall, our ensemble modeling study reveals important information on how climate change will affect lake thermal properties, and also provides some of the first analyses on how climate model selection uncertainty and lake model selection uncertainty interact to affect projections of future lake dynamics.

Ice Freeze‐Up and Break‐Up in Arctic Rivers Observed With Satellite L‐Band Passive Microwave Data From 2010 to 2020

AbstractThe timing of ice freeze‐up and break‐up in the Arctic may be responding to climate change. Passive microwave remote sensing is a powerful technique for monitoring this timing. We processed low‐frequency microwave time series from the European Space Agency Soil Moisture and Ocean Salinity (SMOS) mission for a set of 31 satellite gauging reaches (SGRs) above 65°N between 2010 and 2020 to determine timing of freeze‐up and break‐up and annual river ice durations. We found indication of progressive ice cover reduction over more than half of the monitored river reaches, with possibly the fastest rate occurring over northeast Russia. Some rivers in high‐latitude North America experienced a slight increase in ice cover. Across the data set, we observed an average 2.2 days shift toward later ice freeze‐up in autumn and an average 0.6 days shift toward earlier ice break‐up in spring, resulting in an average decrease of 3.4 days in ice duration between 2010 and 2020. River reaches with the longest duration of ice cover appeared to have experienced the fastest rate of decrease. A possible reduction of the time lag between air temperature rise or fall and corresponding river ice break‐up and freeze‐up was also observed. Yet results on variability are carefuly interpreted given the short length of the time series (2010–2020) and the low statistical confidence rates calculated for the decadal tendency. Still outcomes are consistent with increases in global and Arctic surface air temperature. Following these time series over the next decade using passive microwave satellite sensors can monitor ice cover duration in the Arctic and will further determine temporal and regional trends.