Deep Snow Research Articles

Trade-Offs Between Forage Availability, Accessibility, and Predation Risk on Winter Foraging Strategies of Wood Bison (Bison bison athabascae).

Optimal foraging theory (OFT) and the energy maximization hypothesis (EMH) have long been essential when examining wildlife habitat selection. At high latitudes and altitudes, animals in winter face greater limitations in availability and accessibility of forage. Here we explore the foraging behavior of wood bison (Bison bison athabascae) during winter within the Ronald Lake bison herd in northeastern Alberta, Canada, and examine the trade-offs they face due to limitations in forage abundance and availability (snow conditions), as well as the need to minimize predation risk. We used Global Positioning System (GPS) location data collected from 70 female wood bison to identify winter foraging sites and craters selected by bison to access forage beneath the snow. Within wetlands used by bison we selected 190 pairs of used (foraged) and random (available) sites to test eight a priori hypotheses explaining how bison traded-off between forage availability, accessibility, and minimizing predation risk. We found with matched-paired logistic regression that Carex atherodes was 1.21-times more likely to be selected per unit increase in ground cover, compared to 1.17-times per unit ground cover for C. aquatilis and C. utriculata. However, all Carex species showed an increase in selection when cover was > 50% cover within individual craters. While the importance of Carex was clear, forage site selection was still inversely related to snow depth. There is also a neutralizing combined effect of snow depth and Carex species ground cover which suggests that bison maximized their energy return by avoiding areas with deep snow (> 30 cm) that demanded intensive cratering, even when highly selected forage was accessible beneath. Avoidance of forage areas with deep snow demonstrates that wood bison employed a foraging strategy that considers both forage availability and environmental conditions, with snow depth being a limiting factor. We highlight the relationship between optimal foraging based on food availability and the trade-offs within an energy restrictive winter season, furthering the understanding of how large herbivores forage strategically to maximize energy intake in northern environments.

Predicting snow structures relevant to reindeer husbandry

ABSTRACT Snow conditions in the High North are an important control on wintertime forage availability for reindeer, and under climate change, they are changing rapidly. In the European Arctic, this has the potential to disrupt traditional reindeer herding practices, reindeer health, and local culture (including that of Indigenous communities like the Sámi). At the same time, Norwegian coastal cities are competing to act as multi-model transportation hubs as sea-ice retreat creates expectations for increased marine accessibility. An “Arctic Railway” connecting Rovaniemi to Kirkenes has been proposed to support these port developments, but this route passes through rangelands managed by Sámi and local herding communities. This study develops an assessment of past and future snow characteristics relevant to reindeer health to provide a context for understanding the impacts of this infrastructure development. Climate model and detailed snowpack simulations were performed for 1950 to 2100 along the proposed route. Results show that deep snow becomes less frequent and spring thaw advances, favorable to reindeer. However, icy snow conditions become more frequent, potentially forcing herds from tundra and farmland to forested areas. This suggests policy alternatives that focus on the development and maintenance of migration corridors to allow appropriate movement of reindeer herds.

An earthquake-triggered avalanche in Nepal in 2015 was exacerbated by climate variability and snowfall anomalies

On 25 April 2015, the Gorkha earthquake triggered a large rock-ice avalanche and an air blast disaster in the Langtang Valley, Nepal. More than 350 people were killed or left missing. Here we reconstruct the evolution of the Langtang avalanche-air blast using field investigations and numerical modeling and examine the influence of two primary climate-related phenomena: snowfall anomalies and warm temperatures. Our findings suggest a deep snow cover fosters the formation of a dispersed avalanche, which increases the mobility and destructive power of the powder cloud air blast. Elevated air temperatures intensify meltwater production and lubricate the flowing mass. Both mechanisms contributed to the Langtang disaster. Our study underscores the essential impact of snow cover and air temperature on the risk assessment of high-altitude rock-ice avalanches, highlighting how seasonal and climatic variations affect avalanche runout and air blast dynamics.

Teleconnection of the Quasi-biennial oscillation with boreal winter surface climate in Eurasia and North America

An improved understanding of dynamical coupling from regional to global scales via tropospheric or stratospheric region can be helpful in improving seasonal forecasts for a given region of interest. Here we investigate dynamical coupling between the equatorial stratospheric Quasi-biennial oscillation and the boreal winter surface climate of the Northern Hemisphere mid and high latitudes using 42 years of data (1979–2020). For neutral El Niño Southern Oscillation periods, the Quasi-biennial oscillation westerly phase at 70 hPa favors high sea level pressure in the polar region, colder conditions and deeper snow over Eurasia and North America, and the opposite effects for the easterly phase. When Quasi-biennial oscillation anomalies arrive near the tropopause, it is observed that planetary wave activity is enhanced towards to extratropical region during westerly phase and reduced during easterly phase. This teleconnection pathway via the upper troposphere and lower stratosphere to the high latitude surface is independent of the “stratospheric pathway” (Holton-Tan mechanism). Diagnosis of this pathway can help to improve understanding of sub-seasonal to seasonal variations, and long-range forecasting over Eurasia and North America.

Canopy cover and microtopography control precipitation-enhanced thaw of ecosystem-protected permafrost

Northern high-latitudes are projected to get warmer and wetter, which will affect rates of permafrost thaw and mechanisms by which thaw occurs. To better understand the impact of rain, as well as other factors such as snow depth, canopy cover, and microtopography, we instrumented a degrading permafrost plateau in south-central Alaska with high-resolution soil temperature sensors. The site contains ecosystem-protected permafrost, which persists in unfavorable climates due to favorable ecologic conditions. Our study (2020–2022) captured three of the snowiest years and three of the four wettest years since the site was first studied in 2015. Average thaw rates along an across-site transect increased nine-fold from 6 ± 5 cm yr−1 (2015–2020) to 56 ± 12 cm yr−1 (2020–2022). This thaw was not uniform. Hummock locations, residing on topographic high points with relatively dense canopy, experienced only 8 ± 9 cm yr−1 of thaw, on average. Hollows, topographic low points with low canopy cover, and transition locations, which had canopy cover and elevation between hummocks and hollows, thawed 44 ± 6 cm yr−1 and 39 ± 13 cm yr−1, respectively. Mechanisms of thaw differed between these locations. Hollows had high warm-season soil moisture, which increased thermal conductivity, and deep cold-season snow coverage, which insulated soil. Transition locations thawed primarily due to thermal energy transported through subsurface taliks during individual rain events. Most increases in depth to permafrost occurred below the ∼45 cm thickness seasonally frozen layer, and therefore, expanded existing site taliks. Results highlight the importance of canopy cover and microtopography in controlling soil thermal inputs, the ability of subsurface runoff from individual rain events to trigger warming and thaw, and the acceleration of thaw caused by consecutive wet and snowy years. As northern high-latitudes become warmer and wetter, and weather events become more extreme, the importance of these controls on soil warming and thaw is likely to increase.

Improving Mountain Snowpack Estimation Using Machine Learning With Sentinel‐1, the Airborne Snow Observatory, and University of Arizona Snowpack Data

AbstractAccurate mapping of snow amount in the mountains is critical as mountain snowpacks are water supply for millions of people. Satellite remote sensing has been largely unable to reliably detect the amount of snowpack in these areas. Recently, C‐band Synthetic Aperture Radar (SAR) data from the Sentinel‐1 (S1) satellites have shown potential for measuring snow depth in the mountains. However, their spatiotemporal coverage is incomplete, and their evaluation with robust, aerial snow depth data is limited. Here, we evaluate two S1 snowpack datasets with some of the best available gridded snowpack data over the Colorado Rockies and Sierra Nevada mountains in the western US: the Airborne Snow Observatory (ASO) and the University of Arizona (UA) snowpack datasets. Compared to ASO and UA data, the S1 data are biased high when snow is shallow, and biased low when snow is deep (particularly later in spring when there is wet snow), though these biases are reduced for deep snow areas when wet snow pixels are removed. We then apply corrections based on machine learning that account for physiographic characteristics to improve the accuracy of the S1 data. Furthermore, we fill gaps in the S1 data by using snow persistence, but also account for potential snow accumulation and ablation, to generate temporally complete snow depth maps over mountainous areas. Corrected and gap‐filled S1 snow depth mapping could be especially important for snow monitoring in remote mountain areas where other techniques for snow mapping do not work or are logistically infeasible or cost‐prohibitive.

Bayesian physical–statistical retrieval of snow water equivalent and snow depth from X- and Ku-band synthetic aperture radar – demonstration using airborne SnowSAr in SnowEx'17

Abstract. A physical–statistical framework to estimate snow water equivalent (SWE) and snow depth from synthetic aperture radar (SAR) measurements is presented and applied to four SnowSAR flight-line data sets collected during the SnowEx'2017 field campaign in Grand Mesa, Colorado, USA. The physical (radar) model is used to describe the relationship between snowpack conditions and volume backscatter. The statistical model is a Bayesian inference model that seeks to estimate the joint probability distribution of volume backscatter measurements, snow density and snow depth, and physical model parameters. Prior distributions are derived from multilayer snow hydrology predictions driven by downscaled numerical weather prediction (NWP) forecasts. To reduce the signal-to-noise ratio, SnowSAR measurements at 1 m resolution were upscaled by simple averaging to 30 and 90 m resolution. To reduce the number of physical parameters, the multilayer snowpack is transformed for Bayesian inference into an equivalent one- or two-layer snowpack with the same snow mass and volume backscatter. Successful retrievals meeting NASEM (2018) science requirements are defined by absolute convergence backscatter errors ≤1.2 dB and local SnowSAR incidence angles between 30 and 45∘ for X- and Ku-band VV-pol backscatter measurements and were achieved for 75 % to 87 % of all grassland pixels with SWE up to 0.7 m and snow depth up to 2 m. SWE retrievals compare well with snow pit observations, showing strong skill in deep snow with average absolute SWE residuals of 5 %–7 % (15 %–18 %) for the two-layer (one-layer) retrieval algorithm. Furthermore, the spatial distributions of snow depth retrievals vis-à-vis lidar estimates have Bhattacharya coefficients above 94 % (90 %) for homogeneous grassland pixels at 30 m (90 m resolution), and values up to 76 % in mixed forest and grassland areas, indicating that the retrievals closely capture snowpack spatial variability. Because NWP forecasts are available everywhere, the proposed approach could be applied to SWE and snow depth retrievals from a dedicated global snow mission.

Characteristics of Fatal Accidents due to Exogenous Causes at Ski Resorts in Japan Over the Past 13 Years: A Retrospective Descriptive Study.

The characteristics of ski- and snowboard-related fatalities at Japanese ski resorts remain unknown. We aimed to analyze the characteristics of this in the current study. Using the Ski Resort Injury Report data for the 13-y period between the 2011-12 and 2022-23 seasons, we described the characteristics of fatal accidents due to exogenous causes. Eighty-four subjects (48 skiers and 36 snowboarders) were analyzed. Males accounted for 73 cases of all 84 fatalities (86.9%), including 44 skiers (91.7%) and 29 snowboarders (80.6%). Skiers aged ≥50 y and snowboarders aged 20-35 y had the highest number of fatal accidents (32 and 18 cases, respectively). Regarding location, 26 fatal accidents occurred on slopes, and 58 occurred out of slopes (skiers, 11 and 37 cases; snowboarders, 15 and 21 cases, respectively). Among skiers, head and neck trauma accounted for the cause of death in 13 cases (27.1%) and asphyxiation in 11 cases (22.9%). Among snowboarders, head and neck trauma accounted for the cause of death in 14 cases (38.9%) and asphyxiation in 14 cases (38.9%). Males, particularly those aged ≥50 among skiers and 20-35 among snowboarders, should be wary of the potential for injuries to the head, neck, and airway when skiing or snowboarding. In this study, traumatic deaths from crashing into trees and asphyxiation from deep snow immersion accidents accounted for approximately half of fatal ski accidents in Japan.

Passive microwave remote-sensing-based high-resolution snow depth mapping for Western Himalayan zones using multifactor modeling approach

Abstract. Spatiotemporal snow depth (SD) mapping in the Indian Western Himalayan (WH) region is essential in many applications pertaining to hydrology, natural disaster management, climate, etc. In situ techniques for SD measurement are not sufficient to represent the high spatiotemporal variability in SD in the WH region. Currently, low-frequency passive microwave (PMW) remote-sensing-based algorithms are extensively used to monitor SD at regional and global scales. However, fewer PMW SD estimation studies have been carried out for the WH region to date, which are mainly confined to small subregions of the WH region. In addition, the majority of the available PMW SD models for WH locations are developed using limited data and fewer parameters and therefore cannot be implemented for the entire region. Further, these models have not taken the auxiliary parameters such as location, topography, and snow cover duration (SCD) into consideration and have poor accuracy (particularly in deep snow) and coarse spatial resolution. Considering the high spatiotemporal variability in snow depth characteristics across the WH region, region-wise multifactor models are developed for the first time to estimate SD at a high spatial resolution of 500 m × 500 m for three different WH zones, i.e., Lower Himalayan Zone (LHZ), Middle Himalayan Zone (MHZ), and Upper Himalayan Zone (UHZ). Multifrequency brightness temperature (TB) observations from Advanced Microwave Scanning Radiometer 2 (AMSR2), SCD data, terrain parameters (i.e., elevation, slope, and ruggedness), and geolocation for the winter period (October to March) during 2012–2013 to 2016–2017 are used for developing the SD models for dry snow conditions. Different regression approaches (i.e., linear, logarithmic, reciprocal, and power) are used to develop snow depth models, which are evaluated further to find if any of these models can address the heterogeneous association between SD observations and PMW TB. From the results, it is observed from the analysis that the power regression SD model has improved accuracy in all WH zones with the low root mean square error (RMSE) in the MHZ (i.e., 27.21 cm) compared to the LHZ (32.87 cm) and the UHZ (42.81 cm). The spatial distribution of model-derived SD is highly affected by SCD, terrain parameters, and geolocation parameters and has better SD estimates compared to regional and global products in all zones. Overall results indicate that the proposed multifactor SD models have achieved higher accuracy in deep snowpack (i.e., SD >25 cm) of the WH region compared to previously developed SD models.

Insufficient Cold Resistance as a Possible Reason for the Absence of Darkling Beetles (Coleoptera, Tenebrionidae) in Pleistocene Sediments of Siberia.

The level of diversity and abundance of darkling beetles (Coleoptera, Tenebrionidae) is the main difference between the late Pleistocene and modern insect faunas of arid regions. In the Pleistocene assemblages they are extremely rare, whereas in the modern ones they predominate. It is assumed that the reason for their rarity in fossil entomological complexes is their lack of cold resistance. The supercooling points (SCP) and low lethal temperatures (LLT) of adults from five species of Altai darkling beetles that overwinter in the soil and larvae from one such species were measured in the laboratory. All beetles supercooled at negative temperatures but could not survive freezing, with the average SCP of the most cold-resistant species between -25.7 and -21.7 °C (Bioramix picipes, Anatolica dashidorzsi, and Penthicus altaicus). However, 50% of the individuals from different species in the experiment died after exposure during two days at temperatures ranging from -22 to -20 °C. The focal species are distributed in parts of Central Asia with an extreme continental climate, and the temperatures measured in the soil of these natural areas turned out to be lower than or close to the limit of cold resistance of the beetles. Overwintering of darkling beetles is therefore only possible in areas with deep snow: in hollows, under bushes, and under large cereals. Darkling beetles with poor cold resistance could not have existed in the colder climate of the late Pleistocene, which explains their absence from fossil fauna.

Power generation characteristics of vertical bifacial photovoltaic arrays in heavy snow regions

Conventional tilted photovoltaic systems often experience reduced electricity generation and potential damage due to snow accumulation. In contrast, vertical bifacial photovoltaic systems demonstrate greater resilience against snow-related damage, making them particularly suitable for snowy regions. This study explores the electricity generation characteristics of vertical bifacial photovoltaic systems in areas where snow depths exceed 1 meter, through both experimental and simulation analyses. Experiments conducted on a vertical bifacial system over two winter seasons showed no signs of damage or breakage. Additionally, during snowy periods, the power generation ratio relative to global horizontal irradiance increased by 55%, primarily due to irradiance reflected from the snow surface. However, this gain was offset by a 17% decrease due to partial shading by snow. Furthermore, integrating ray tracing with electrical circuit analysis revealed that implementing separate maximum power point tracking for the upper and lower sections of a single-row vertical bifacial photovoltaic array could alleviate losses in electricity generation caused by deep snow covering the photovoltaic cells. This study advances our understanding of the impact of snow on the power generation of vertical bifacial photovoltaic systems in heavy-snow regions and is expected to contribute to the development of more efficient designs in the future.

Parentage of 920 gray‐sided voles (Myodes rufocanus) born in a 3‐ha outdoor enclosure between September 1992 and May 1994

AbstractThis dataset provides the estimated birth location, sex, assigned parents, and estimated birth and death dates of 920 gray‐sided voles (Myodes rufocanus) born in a 3‐ha outdoor enclosure in Sapporo, Japan between September 1992 and May 1994, as well as capture–recapture data for 30 trapping sessions. We introduced 22 males and 25 females from several natural populations into the enclosure in late September 1992. Individuals in the enclosure were captured using live traps every 2 weeks until late April 1994, except for periods with deep snow cover. The location, body weight, and reproductive status of each vole were monitored throughout the study period. Complementary trapping was performed within the home ranges of breeding females to mark juveniles as early as possible. Upon first capture, each individual was marked by toe clipping for subsequent identification, and the clipped toes were used as DNA samples. For each individual, candidate parents were selected based on female reproduction history and capture points. Parentage then was determined using genotypes at 3–5 microsatellite loci with the CERVUS program. The results show that individuals born in the enclosure (N = 920) were derived from 215 litters, among which multiple males sired 51 litters. We used this database to elucidate the promiscuous mating system and inbreeding‐avoidance mechanism of the gray‐sided vole and to develop a new method for estimating the frequency of multiple‐male mating. This dataset will contribute to future behavioral ecological research on this and other small mammal species. The complete data set for this abstract published in the Data Article section of the journal is available in electronic format in MetaCat in JaLTER at http://db.cger.nies.go.jp/JaLTER/metacat/metacat/ERDP-2023-03.1/jalter-en.

Effects of large carnivores, hunter harvest, and weather on the mortality of moose calves in a partially migratory population

Survival of juvenile ungulates represents an important demographic parameter that influences population dynamics within ecosystems. In many ecological systems, the mortality of juvenile ungulates is influenced by various factors, including predation by large carnivores, human hunting activities and weather. While wolves Canis lupus are known to prey on moose Alces alces throughout all seasons, brown bears Ursus arctos primarily engage in predation during early summer, while human harvest primarily occurs in autumn and early winter. Hence, understanding the impacts of predation, harvest, and weather on the survival of juvenile moose is crucial for adaptive population management and the determination of sustainable harvest rates. To investigate the summer and autumn–winter survival of moose calves in relation to carnivore occurrence (wolf presence and bear density), summer habitat productivity, winter severity, human harvest, and migratory behaviour (migratory versus resident), we analysed data collected from 39 GPS‐collared female moose in south‐central Scandinavia. Our findings revealed significant interannual variation in summer survival rates, with areas with relatively higher bear densities exhibiting calf mortality rates twice as high as those in regions with low bear density. During the autumn–winter period, calf survival was lowest in the presence of wolves and deep snow, and it exhibited a negative correlation with the proportion of clearcuts and young forests within the mother's home range. Additionally, calf survival was negatively correlated with the risk of human hunting, and calves of stationary females displayed ten times higher survival rates compared to migratory individuals. Our study provides valuable insights into the survival of moose calves coexisting with two large carnivores and humans. Improving our understanding of the mechanisms causing calf survival to fluctuate has become increasingly important as many local moose populations in Scandinavia are declining and exposed to expanding predator populations, intense hunting pressure, and other threats associated with climate change.

Quadrupedal terrestrial locomotion in emperor penguins (Aptenodytes forsteri)

ABSTRACT Birds generally employ bipedal terrestrial locomotion; their wings flap synchronously to provide aerial propulsion. Penguins (Spheniscidae) are non-flyers that use their modified wings (flippers) to ‘fly’ underwater, again using synchronous action. The family is distributed from the equator to the Antarctic; the earliest penguins lived at temperate latitudes. On land, penguins usually walk bipedally and slowly (waddling) because their legs are short and their bodies long and fusiform. Their flippers are held out sideways and show little movement; they may function like balance poles. A few penguin species breed at high latitude and make substantial terrestrial migrations over snow and ice; they intermittently use an alternative terrestrial locomotory mode (tobogganing) in which they lie on their ventral surfaces and use the feet alternately to propel them more quickly. The emperor penguin Aptenodytes forsteri makes two-way trips (<250 km) to breed, encountering both ice and several types of snow. The topography varies from flat areas to steep slopes and ridges. In this study we analysed 13 publicly available video records and demonstrate that the flippers are also used for propulsion (particularly for climbing in deep snow). Gait analysis reveals that all four limbs are employed in a quadrupedal, ipsilaterally coordinated manner: the classic mode of tetrapod terrestrial locomotion. During climbing, tetrapod limb action is supplemented by use of the beak as an anchor. During quadrupedal locomotion over snow the flippers move snow on their power strokes, thereby demonstrating exchange of forces.

Hygiene of keeping service horses in the highlands of Armenia

In the Transcaucasus region, the Republic of Armenia is the highest mountainous country, about 90% of its territories are located at altitudes of more than 1000 meters above sea level. On the territory of this region there are high plateaus, volcanic cones with a large abundance of streams and small rivers. With an increase of every 100 meters, the precipitation level increases by approximately 25 mm, and when reaching heights of 3,000 meters, precipitation increases to 1,000 mm per year. A feature of service horse breeding in this region is the tortuosity of most mountain roads, fairly rocky soil, steep ascents and descents, high and inaccessible passes, changes in atmospheric pressure and temperature at different altitudes during the day, frequent and sharp changes in air speed . The difficulty of raising livestock in some high-mountainous regions of Armenia is also due to the presence of landslides, screes, cliffs and glaciers, and in winter conditions, deep snow cover.

Long-term monitoring in the boreal forest reveals high spatio-temporal variability among primary ecosystem constituents

The boreal forest, the world’s largest terrestrial biome, is undergoing dramatic changes owing to anthropogenic stressors, including those of climate change. To track terrestrial ecosystem changes through space and time, robust monitoring programs are needed that survey a variety of ecosystem constituents. We monitored white spruce (Picea glauca) cone crops, berry (Empetrum nigrum, Shepherdia canadensis) production, above-ground mushroom abundance, and the abundance of small mammals (Clethrionomys rutilus,Peromyscus maniculatus), North American red squirrels (Tamiascirus hudsonicus), snowshoe hares (Lepus americanus), and carnivores (Lynx canadensis,Canis latrans,Vulpes vulpes,Martes americana,Mustela erminea) across 5 sites in the Yukon, Canada. Monitoring began in 1973 at Lhù’ààn Mân’ (Kluane Lake) and additional protocols were added until a complete sequence was fixed in 2005 at all 5 sites and continued until 2022. White spruce cone counts show mast years at 3–7-year intervals. Ground berries and soapberry counts were highly variable among sites and counts did not correlate among sites or between years for different species. Red-backed voles showed clear 3–4-year cycles at Kluane and probably at the Mayo and Watson Lake sites, but showed only annual cycles in Whitehorse and Faro. Snowshoe hares fluctuated in 9–10-year cycles in a travelling wave, peaking one year earlier at Watson Lake but in synchrony at all other sites, with no clear sign of peak density changing or cyclic attenuation over the last 50 years. Red squirrel numbers at Kluane exhibit marked inter-year variability, driven mainly by episodic white spruce cone crops and predation from Canada lynx and coyotes as hare densities undergo cyclic decline. Snow track counts to index mammalian predators have been conducted on our Kluane and Mayo sites, indicating that lynx numbers rise and fall with a 1–2-year lag at these two sites, tracking the hare cycle. Coyotes and lynx at Kluane peak together following the hare cycle, but coyote counts are also depressed during deep snow years. To summarize, we noted considerable inter-site variability in the population dynamics of many boreal forest ecosystem constituents, but the keystone species (snowshoe hare, Canada lynx) exhibit remarkably similar population trends across the region. We continue to monitor wildlife abundance, cone crops, berry production, and mushroom biomass to determine changes associated with increasing temperature and fluctuating rainfall. The Yukon boreal forest is changing as climate shifts, but the changes are slow, variable across sites, taxa specific, and of uncertain predictability.

Reproductive payoffs of territoriality are snow‐dependent in a mountain ungulate, the Alpine chamois

AbstractFemale density and distribution are dependent on resource phenology and female availability strongly influences male mating behaviour and success. When a male adopts a ‘resource defence’ tactic, his reproductive success depends on the location and attractiveness of his territory. Environmental factors associated with territory quality are expected to influence mating success, for example, through territory features or male–male competition. In a protected population of a mountain‐dwelling polygynous herbivore, the Alpine chamois Rupicapra r. rupicapra, we investigated the relationships among mating opportunities, some environmental variables (snow depth, topographic features and size of territories) and male intra‐sexual competition for mating. We recorded the mating behaviour and territory size of 15 GPS‐GSM radio‐tagged territorial males, during five rutting seasons (early November to early December: N = 8 individuals in 2011, N = 9 in 2012, N = 8 in 2015, N = 11 in 2016, N = 7 in 2017; 80% of them were observed for more than one mating season) and related them to snow depth and topography of territories. In ruts with deep snow cover, territorial males had smaller territories and higher number of mating opportunities than in ruts with lower snow cover. Smaller territories showed the highest values of terrain roughness, in turn with little or no snow cover in the mating season, and were visited by a greater number of females, than larger territories. Number of wins was positively influenced by snow depth and negatively related to the frequency of aggressions. The frequency of male–male aggressive interactions was greater during ruts with deep snow cover and for males with territories at higher elevations; additionally, it was negatively related to interactions won. Thus, snow depth, which influences resource distribution and female movements, is confirmed as a strong determinant of male mating opportunities and mating behaviour.

Fences are more effective than repellents in reducing deer browsing on planted two conifer species but their effectiveness is reduced by higher deer density, deeper snow, and steeper slope

Population expansion of deer and the damage to planted trees caused by them is becoming a serious conflict between deer and humans. Although there are many methods for tree protection, their effectiveness varies from case to case, and the determinant of effectiveness has rarely been clarified. We investigated the following three specific questions: 1) What factors influence forest managers' choice of protection methods? 2) What factors were important in reducing tree damage by each protection method? 3) Which of the repellents and fences was more effective in reducing tree damage? In 2018, we obtained data of plantation tree damages caused by sika deer (Cervus nippon) and tree protection methods from 1424 plantations in Japan. No protection was chosen at low deer densities, and repellents and fences were chosen at middle and high densities by forest managers. In the case of repellents, the damage rank increased with increasing deer density, tree age, and maximum snow depth, but was not affected by planted tree species (Cryptomeria japonica and Chamaecyparis obtusa). In the case of fences, the damage rank increased with increasing deer density, tree age, maximum snow depth, slope, and decreasing net height. The damage rank also increased with the usage of separable digging prevention net and the net without stainless wire. When the age of planted trees is seven, repellents can suppress the tree damage under 50% only when the deer density is below 10 deer/km2 (no snow) or 6 deer/km2 (snow depth is 16 cm). Fences can suppress tree damage below 50% when deer density was below 38 deer/km2 (snow depth: 0, slope: 35°) or 25 deer/km2 (snow depth: 16, slope: 35°). Deer protection methods should be selected according to environmental conditions such as deer density, snow depth, and slope degree in the case of our treated tree species.

More Snow Accelerates Legacy Carbon Emissions From Arctic Permafrost

AbstractSnow is critically important to the energy budget, biogeochemistry, ecology, and people of the Arctic. While climate change continues to shorten the duration of the snow cover period, snow mass (the depth of the snow pack) has been increasing in many parts of the Arctic. Previous work has shown that deeper snow can rapidly thaw permafrost and expose the large amounts of ancient (legacy) organic matter contained within it to microbial decomposition. This process releases carbonaceous greenhouse gases but also nutrients, which promote plant growth and carbon sequestration. The net effect of increased snow depth on greenhouse gas emissions from Arctic ecosystems remains uncertain. Here we show that 25 years of snow addition turned tussock tundra, one of the most spatially extensive Arctic ecosystems, into a year‐round source of ancient carbon dioxide. More snow quadrupled the amount of organic matter available to microbial decomposition, much of it previously preserved in permafrost, due to deeper seasonal thaw, soil compaction and subsidence as well as the proliferation of deciduous shrubs that lead to 10% greater carbon uptake during the growing season. However, more snow also sustained warmer soil temperatures, causing greater carbon loss during winter (+200% from October to May) and year‐round. We find that increasing snow mass will accelerate the ongoing transformation of Arctic ecosystems and cause earlier‐than‐expected losses of climate‐warming legacy carbon from permafrost.

Widespread Permafrost Degradation and Thaw Subsidence in Northwest Canada

AbstractLong‐term (1991–2018) thaw tube measurements highlight widespread permafrost thaw and ground surface (GS) subsidence over a large portion of northwest Canada. Statistically significant positive trends in thaw penetration (TP), measured with respect to a fixed datum, were observed at 18 of 28 sites with data that span three decades at a median rate of 0.8 cm a−1. This rate implies thawing of about 22 cm of permafrost over the study period. Similarly significant trends in GS subsidence occurred at 21 of 28 sites, at a median rate of 0.4 cm a−1. In contrast with TP and GS elevation, long‐term trends in active layer thickness (ALT) were less consistent, with 10 of 28 sites having statistically significant trends indicating increasing ALT (median rate: 0.6 cm a−1), and 7 sites having trends indicating decrease in ALT (median: 0.3 cm a−1). The ALT measurements underestimated the thawing of ice‐rich permafrost due to GS subsidence. Sites with high rates of thaw had relatively warm permafrost, deep snow cover, and poor drainage. Masking of ice‐rich permafrost degradation by ALT measurements has important implications for modeling permafrost thaw and climate change reporting. Accurate simulation of ice‐rich permafrost thaw is conceivable for sites where conditions are well‐defined. However, the prediction of subsidence and TP at regional or broader scales is only possible in general terms due to variation in surface conditions and ground ice content. Trends in TP and GS subsidence more accurately characterize ice‐rich permafrost degradation than trends in ALT.