Effect Of Snow Depth Research Articles

Effect of Snow Depth on the Hydrogen Content of Steels in Snowy Environment

Effect of Snow Depth on the Hydrogen Content of Steels in Snowy Environment

The effect of snow depth on movement rates of GPS-collared moose

During deep snow conditions, wildlife must balance between minimizing movements to conserve energy while seeking high amounts of browse to gain the energy. Knowledge of how snow begins to hinder their movements is therefore vital when predicting their wintertime behavior. We assessed the phenomenon with moose. Movement data from 122 GPS-collared moose were integrated with snow depth data from designated measurement stations. The effects of increasing snow depths on moose movement rates were then modeled with spline regression. The study was conducted in Finland, between 2009 and 2011. The moose were known for their sex and for the presence of calf at heel. On average, the movement rates decreased sharply until snow depths of ca. 30–40 cm, after which further significant decreases were not seen. The movement rates decreased from several kilometers per day to less than 500 m per day. Moose in the northernmost study area with the deepest snow covers moved as much as the moose in the other areas with less snow. Although we saw differences in the movement rates between males and females, differences between individuals were markedly higher than those caused by sex or a calf at heel. Moose are keystone species whose heavy browsing, especially during winter, can have profound effects on vegetation and forest regeneration. As snow covers in large parts of the boreal zone are predicted to decrease due to warming climate, the wintertime movements of moose and how they affect the local vegetation will remain relevant questions.

Prediction of municipality-level winter wheat yield based on meteorological data using machine learning in Hokkaido, Japan.

This study analyzed meteorological constraints on winter wheat yield in the northern Japanese island, Hokkaido, and developed a machine learning model to predict municipality-level yields from meteorological data. Compared to most wheat producing areas, this island is characterized by wet climate owing to greater annual precipitation and abundant snowmelt water supply in spring. Based on yield statistics collected from 119 municipalities for 14 years (N = 1,516) and high-resolution surface meteorological data, correlation analyses showed that precipitation, daily minimum air temperature, and irradiance during the grain-filling period had significant effects on the yield throughout the island while the effect of snow depth in early winter and spring was dependent on sites. Using 10-d mean meteorological data within a certain period between seeding and harvest as predictor variables and one-year-leave-out cross-validation procedure, performance of machine learning models based on neural network (NN), random forest (RF), support vector machine regression (SVR), partial least squares regression (PLS), and cubist regression (CB) were compared to a multiple linear regression model (MLR) and a null model that returns an average yield of the municipality. The root mean square errors of PLS, SVR, and RF were 872, 982, and 1,024 kg ha−1 and were smaller than those of MLR (1,068 kg ha−1) and null model (1,035 kg ha−1). These models outperformed the controls in other metrics including Pearson’s correlation coefficient and Nash-Sutcliffe efficiency. Variable importance analysis on PLS indicated that minimum air temperature and precipitation during the grain-filling period had major roles in the prediction and excluding predictors in this period (i.e. yield forecast with a longer lead-time) decreased forecast performance of the models. These results were consistent with our understanding of meteorological impacts on wheat yield, suggesting usefulness of explainable machine learning in meteorological crop yield prediction under wet climate.

Snow depth and woody debris drive variation in small‐mammal winter seed removal

AbstractAimsIn temperate forests, small increases in winter temperature can lead to substantial decreases in snow accumulation, which may alter plant–consumer interactions such as seed predation. However, seed predation by small mammals may also be affected by local habitat structure (e.g., downed woody debris). We tested whether the effect of snow depth on seed predation by small mammals depends on habitat structure (woody debris) that may influence small‐mammal foraging behavior.LocationNorthern temperate forests in Wisconsin, USA.MethodsWe performed a factorial manipulation of snow depth and woody debris presence at 10 sites that differed in site‐level ambient woody debris. At these sites, we monitored seed removal of four temperate tree species (Abies balsamea, Acer rubrum, Acer saccharum, Pinus resinosa).ResultsMean rates of winter seed removal varied among species, as did the effects of snow depth and woody debris. The presence of woody debris decreased Abies balsamea seed removal in plots with snow removed. Regardless of woody debris, snow removal increased Acer saccharum seed removal. Acer rubrum seed removal was lowest at sites with high site‐level woody debris volume, especially in plots with snow removed.ConclusionsWarming winter temperatures may amplify seed removal for some tree species, but local‐scale heterogeneity in woody debris may modify these effects. Because the effects of woody debris and snow removal were much stronger for some tree species than others, changes in seed removal associated with reduced future snow cover or changes in forest management may accelerate regional changes in forest composition.

Wind and Snow Loading of Balsam Fir during a Canadian Winter: A Pioneer Study

Widely distributed across Quebec, balsam fir (Abies balsamea (L.) Mill) is highly vulnerable to wind damage. The harsh winter conditions, freezing temperatures, and snow pose an additional risk. It is important to find the mechanical loads experienced by trees during winter to adapt forest management and minimize the risk of damage to this species. Many studies have been carried out on wind and snow loading damage risks in Northern Europe, mostly based on post-storm damage inventories. However, no study has continuously monitored the applied turning moment during a period with snow loading, and no study has investigated wind and snow loading on balsam fir. Therefore, our main objective was to conduct a pioneering study to see how trees bend under wind loading during winter, and to see how snow cover on the canopy contributes to the loading. Two anemometers placed at canopy height and 2/3 canopy height, air and soil temperature sensors, a hunting camera, and strain gauges attached to the trunks of fifteen balsam fir trees, allowed us to measure the wind and snow induced bending moments experienced by the trees together with the meteorological conditions. Data were recorded at a frequency of 5 Hz for more than 2000 h during summer 2018 and winter 2019. Two mixed linear models were used to determine which tree and stand parameters influence the turning moment on the trees and evaluate the effect of winter. The selected model for measurements made during winter found that including the snow thickness on crowns was better than those models that did not consider the effect of snow (ΔAICc > 25), but the effect of snow depth on the bending moment appears to be minor. However, overall, the turning moment experienced by trees during winter was found to be higher than the turning moment experienced at the same wind speed in summer. This is probably a result of increases in the rigidity of the stem and root system during freezing temperatures and the change in wind flow through the forest due to snow on the canopy and on the ground during the winter season.

The Effect of Snow Depth on Spring Wildfires on the Hulunbuir from 2001–2018 Based on MODIS

Wildfires are one of the important disturbance factors in natural ecosystems and occur frequently around the world. Detailed research on the impact of wildfires is crucial not only for the development of livestock husbandry but also for the sustainable use of natural resources. In this study, based on the Moderate Resolution Imaging Spectroradiometer (MODIS) burned area product MC464A1 and site snow depth measurements, the kernel density estimation method (KDE), unary linear regression analysis, Sen + Mann-Kendall trend analysis, correlation analysis, and R/S analysis were used to evaluate the relationship between snow and spring wildfires (SWFs) in Hulunbuir. Our results indicated that SWFs decreased during the period of 2001–2018, were mainly distributed in the eastern portion of the study area, and that the highest SWF density was 7 events/km2. In contrast, the maximum snow depth increased during the period of 2001–2018 and the snow depth was deeper in the middle but shallower in the east and west. The SWFs and snow depth have significant negative correlations over space and time. The snow depth mainly affects the occurrence of SWFs indirectly by affecting the land surface temperature (LST) and Land Surface Water Index (LSWI) in spring. The snow depth was positively correlated with the LSWI in most of Hulunbuir and strongly negatively correlated with the LST, and this correlation was stronger in the eastern and western regions of Hulunbuir. The results of the Hurst exponent indicated that in the future, the snow depth trend will be opposite that of the current state, meaning that the trend of decreasing snow depth will increase dramatically in most of the study area, and SWFs may become more prominent. According to the validation results, the Hurst exponent is a reliable method for predicting the snow depth tendency. This research can be based on the snow conditions of the previous year to identify areas where fires are most likely to occur, enabling an improved and more targeted preparation for spring fire prevention. Additionally, the present study expands the theory and methods of wildfire occurrence research and promotes research on disasters and disaster chains.

Snow tracking reveals different foraging patterns of red foxes and pine martens

Red fox (Vulpes vulpes) shares similar prey preferences and co-occurs with several other carnivores, and is together with pine marten (Martes martes), the most common mesocarnivore in the northern boreal forest. Voles are important prey for both species, but it is unclear to what extent they compete for the same food resources in winter. Here, we use 2139 km and 533 km of meticulous snow tracking of red foxes and pine martens to evaluate their food niches. We measured hunting and digging behaviour, whether successful or not, and the effect of snow depth and temperature. Pine martens were restricted to forested habitats, whereas red foxes used a wide range of habitats. Red foxes were found to dig more often than pine martens, 0.67 vs. 0.39 digging events per kilometre. Hunting was less common and similar in both species, about 0.1 hunting event per kilometre. Pine martens were more efficient in hunting and finding food remains compared to red foxes. Increasing snow depth reduced hunting success and also reduced dig success of red foxes. Food niche overlap was small. Red foxes used mostly voles and carrion remains of ungulates, whereas pine martens used cached eggs and small birds. We suggest that caching eggs is an important strategy for pine martens to survive winter in northern latitudes. Snow depth was important for capturing voles, and thick snow cover appeared to mask the effect of vole peaks. Intensified land use, as clear-cutting and leaving slaughter remains from harvest, will benefit red foxes on the expense of pine martens. The ongoing climate change with warmer winters and less snow will likely further benefit the red fox.

Bud freezing resistance in alpine shrubs across snow depth gradients

Despite the importance of spring freezing events for alpine species distribution, few studies have analysed the response of alpine shrub species to early spring freezes. It is also not known how snow cover gradients influence the process of de-hardening between individuals of the same species and their vulnerability to early spring frosts. We analysed early spring freezing resistance for the buds of eight alpine Ericaceae shrubs growing at 1m snow depth at treeline in the Swiss Alps. Moreover, buds of Rhododendron ferrugineum and Loiseleuria procumbens were analysed for freezing resistance and sugar content along a snow depth gradient. The LT50 (lethal temperature for 50% of samples) of the eight species ranged from −25.1±1.6°C (Vaccinium vitis-idaea) to −11.1±1.2°C (Vaccinium uliginosum), with differences being related to the phenological stage in addition to shrub preferences for contrasting snow cover microsites. Although the effect of snow depth on the freezing resistance of plants was not significant, samples collected from 1m to 1.5m snow depth tended to be more vulnerable to freezing, particularly L. procumbens. Buds collected at shallower snow depths had higher sugar concentrations, indicative of their stronger physiological hardening. Consequently, we conclude that differences in snow cover may significantly affect the physiological hardening of plants during the onset of spring. Individuals growing at less than 0.5m snow cover are hardier, i.e., show moderately higher freezing resistance than individuals from snow banks. Snow cover is a highly important aspect of climate change, and freezing resistance in alpine plants with respect to snow conditions can be a relevant driver of plant responses to climate change.

Effect of snow depth and snow duration on soil N dynamics and microbial activity in the alpine areas of the eastern Tibetan Plateau

The effects of snow regimes (including the depth and duration of snow cover) on soil N dynamics and microbial activity in situ were explored in the alpine belt of the eastern Tibetan Plateau. Deeper snow-cover reduced NH 4 + -N content, microbial biomass carbon and nitrogen, fungi count, and enzyme activities, whereas did not change net N mineralization. No differences in N pools in the soil, microbial biomass, microbial counts, and enzyme activity were found under the different duration of snow cover, showing that accumulation and release in soil N pools did not be significantly changed by earlier continuous snow cover.

Fine-scale winter resource selection by American martens in boreal forests and the effect of snow depth on access to coarse woody debris

Successful management of boreal forests requires an understanding of the scales at which focal species use resources in their environment. Fine-resolution, within-home-range habitat selection by American martens (Martes americana) has not been well studied in boreal forests, although the importance of downed wood seems almost universal for hunting and resting in winter. We examined winter habitat selection by radio-collared martens while the population was at a 5 y low near Kapuskasing, Ontario, Canada. Fine-resolution models were developed using habitat data collected from snow-tracking 5 resident martens. Resource selection models were compared using an information theoretic approach, and model performance was evaluated by the ability of the models to correctly classify resource use events by martens. Our models suggest that martens selected locations within home ranges that had higher subnivean access to large coarse woody debris (CWD), a medium density of large conifers, and a higher proportion of eastern white cedar (Thuja occidentalis) trees compared to random sites within the home ranges. Subnivean access to CWD decreased with increasing snow depth, and sites used by martens had consistently higher access to CWD compared to random sites within home ranges across the entire range of snow depths measured. Areas used by martens also had lower snow depth than the average within home ranges. Our study illustrates how fine-resolution data can increase the predictability of resource use by martens, and suggests that incorporating sub-stand-level measures such as conserving patches of white cedar and ensuring that CWD remains high through forest succession can increase our ability to successfully manage boreal forests for species such as marten that prefer older stands.

Sex‐ and age‐structured models for Alpine ibex Capra ibex ibex population dynamics

Past analysis has shown that the population dynamics of Alpine ibex Capra ibex ibex are regulated by both population density and winter snow accumulation. However, recent time series of the ibex counts in the Gran Paradiso National Park, Italy, show interesting trends in comparison with historical snow data: while the winter snow depth has steadily decreased since the beginning of the 1980s, the ibex population experienced rapid growth during the 1980s and the early 1990s, followed by a strong decrease. To explain these dynamics, we built novel age‐structured population models in which demographic parameters depended on density and snow depth. They included a non‐monotonic effect of snow depth and density on the vital rates, the age and sex structure of the population, and spatial segregation between females and males. Using information criteria (AICc, BIC and SRM), we selected the best models and found that: 1) snow and density interacted in determining the demography of all population sex and age classes, thus confirming that unfavourable climatic conditions intensified the density dependence of the population, 2) the effect of snow was non‐monotonic on weaning success and rate of demographic variation of kids, which were maximal for intermediate snow depths, and 3) accounting for spatial segregation between sexes improved the fitting of the models, which suggests that the different use of space made by males and females influenced intraspecific competition. When the selected models were recalibrated using past data and used to simulate recent trends, they underestimated both the rapid growth of the 1980s‐1990s and the recent decline of the population. Using the novel sex‐ and age‐structured models, we found that the underestimation of the peak was mainly due to deficiencies of adult demography models, while the overestimation of the recent population abundance was caused by shortcomings in the models of recruitment.

Effect of snow depth on the food habits of sika deer during winter periods in western Hokkaido, Japan

Effect of snow depth on the food habits of sika deer during winter periods in western Hokkaido, Japan

The importance of winter in annual ecosystem respiration in the High Arctic: effects of snow depth in two vegetation types

Winter respiration in snow-covered ecosystems strongly influences annual carbon cycling, underlining the importance of processes related to the timing and quantity of snow. Fences were used to increase snow depth from 30 to 150 cm, and impacts on respiration were investigated in heath and mesic meadow, two common vegetation types in Svalbard. We manually measured ecosystem respiration from July 2007 to July 2008 at a temporal resolution greater than previously achieved in the High Arctic (campaigns: summer, eight; autumn, six; winter, 17; spring, nine). Moisture contents of unfrozen soil and soil temperatures throughout the year were also recorded. The increased snow depth resulted in significantly higher winter soil temperatures and increased ecosystem respiration. A temperature–efflux model explained most of the variation of observed effluxes: meadows, 94 (controls) and 93% (fences); heaths, 84 and 77%, respectively. Snow fences increased the total non-growing season efflux from 70 to 92 (heaths) and from 68 to 125 g CO2-C m-2 (meadows). The non-growing season contributed to 56 (heaths) and 42% (meadows) of the total annual carbon respired. This proportion increased with deeper snow to 64% in both vegetation types. Summer respiration rates were unaffected by snow fences, but the total growing season respiration was lower behind fences because of the considerably delayed snowmelt. Meadows had higher summer respiration rates than heaths. In addition, non-steady state CO2 effluxes were measured as bursts lasting several days during spring soil thawing, and when ice layers were broken to carry out winter efflux measurements.

The importance of winter in annual ecosystem respiration in the High Arctic: effects of snow depth in two vegetation types

Winter respiration in snow-covered ecosystems strongly influences annual carbon cycling, underlining the importance of processes related to the timing and quantity of snow. Fences were used to increase snow depth from 30 to 150 cm, and impacts on respiration were investigated in heath and mesic meadow, two common vegetation types in Svalbard. We manually measured ecosystem respiration from July 2007 to July 2008 at a temporal resolution greater than previously achieved in the High Arctic (campaigns: summer, eight; autumn, six; winter, 17; spring, nine). Moisture contents of unfrozen soil and soil temperatures throughout the year were also recorded. The increased snow depth resulted in significantly higher winter soil temperatures and increased ecosystem respiration. A temperature–efflux model explained most of the variation of observed effluxes: meadows, 94 (controls) and 93% (fences); heaths, 84 and 77%, respectively. Snow fences increased the total non-growing season efflux from 70 to 92 (heaths) and from 68 to 125 g CO2-C m-2 (meadows). The non-growing season contributed to 56 (heaths) and 42% (meadows) of the total annual carbon respired. This proportion increased with deeper snow to 64% in both vegetation types. Summer respiration rates were unaffected by snow fences, but the total growing season respiration was lower behind fences because of the considerably delayed snowmelt. Meadows had higher summer respiration rates than heaths. In addition, non-steady state CO2 effluxes were measured as bursts lasting several days during spring soil thawing, and when ice layers were broken to carry out winter efflux measurements.

Effect of snow depth on under-ice irradiance and growth of Aulacoseira baicalensis in Lake Baikal

Lake Baikal freezes for 4–5 months each year; yet the planktonic diatoms that grow under the ice include some of the largest species found in freshwater. An important factor influencing their growth is the depth of snow. In this study, a population of Aulacoseira baicalensis developed where there was little or no snow on the ice but declined where there was 10 cm of snow, because 99% of the available light was attenuated. Culture studies of light response showed that A. baicalensis was adapted to relatively low light intensities ( 10 m depth but narrow (<15 μm) diameter cells trapped in high light intensities in sub-ice layers switched to auxosporulation and size regeneration.

Relationships between sex ratio, climate and density in red deer: the importance of spatial scale

Summary 1. Recently, contrasting evidence of density‐dependent offspring sex ratio variation in red deer (Cervus elaphus L.) has been presented. Kruuk et al. (1999) reported that the proportion of male red deer born on the island of Rum, Scotland, each year declined with increasing population density and with winter rainfall, i.e. as nutritional stress in females increased. In contrast, Post et al. (1999a) reported increasing male‐biased offspring sex ratios in Hordaland, Norway, with both rising numbers of hinds and increasing values of the North Atlantic Oscillation (NAO), which they regarded an index of severe winters. 2. Compared to Post et al. (1999a), we reanalysed sex ratio variation on a greatly extended data set, including four populations of Norwegian red deer, taking into account a finer population substructure. 3. The proportion of male calves shot each autumn declined markedly as density increased in all four populations. The proportion of male calves shot each autumn increased significantly with an increasing NAO index in one of the four populations, but there was no residual effect of the NAO once the effect of snow depth (at low elevation) was controlled for (decreasingly male biased harvest with increasing snow depth). 4. At the west coast of Norway, the NAO is positively correlated with temperature and precipitation. However, since temperatures in this region often are around 0 °C during winter, the relationship between the NAO and snow depth may be difficult to predict. 5. An analysis of variation in snow depth revealed that snow depth was negatively correlated with the NAO at low altitudes (below 400 m), but this relationship was reversed at high altitudes giving a positive correlation between snow depth and the NAO. We therefore suggest that a high NAO index indicates favourable winter conditions for red deer, as red deer winter at low altitude, and since recent studies show that a high index of the NAO is generally positively correlated with body weight in red deer. 6. Female red deer thus reared fewer sons as nutritional stress increased with increasing density and severity of climate in Norway, which is consistent with the birth sex ratios observed on Rum, Scotland.

Range-body mass interactions of a northern ungulate - a test of hypothesis.

Summer diet, summer temperature, length of the growth season and animal density appeared to best explain annual and regional differences in calf and yearling body mass in moose from southeastern Norway. In general animals inhabiting steep, alpine landscapes had less body mass than animals using flat, low-altitude habitats. Autumn body mass of calves and yearlings decreased with increasing snow depth during the preceding winter and spring. However, calf body mass was more influenced by the summer range and less by the winter range than was body mass of yearlings. There was no indication that the effect of snow depth on autumn body mass was greater in moose living on poor than on good summer ranges. Body mass decreased with increasing competition for summer forage, while the winter range mainly had an density-independent effect. Habitat quality, expressed as regression lines between calf and yearling body mass and animal density (hunting yield), differed between regions. On ranges of medium and high altitude where birch (Betula spp.) rowan (Sorbus aucuparia) and bilberry (Vaccinium myrtillus) dominated moose summer diet, body mass decreased at a rapid rate with increasing animal density. Body mass decreased at a slower rate at low-altitude ranges and at high-altitude ranges where willow (Salix spp.) and forbs dominated the diet. Body mass of lactating cows decreased with increasing animal density, but animal density did not affect body mass of non-lactating cows. There was no indication that the decrease in autumn body mass with increasing moose density over the last 25 years has caused a decrease in animal condition (ability to survive the winter). The results are discussed in relation to the effect of summer and winter range on population regulation in moose. It is concluded that a density-dependent effect is apparent on the summer range even at low and intermediate population densities. On the winter range, on the other hand, density-dependence is likely to occur only at high levels of population density.

Effects of snow depth on food and habitat selection by roe deerCapreolus capreolusalong an altitudinal gradient in south‐central Norway

Roe deerCapreolus capreolusfood and feeding habitat selection was studied by snow tracking on transects along an altitudinal gradient in Flatdal, the county of Telemark, south‐central Norway, during winter 1979/80. The main food was bilberryVaccinium myrtillus(36.8%), rowanSorbus aucuparia(24.4%) and arboreal lichensAlectoria sarmentosa, Bryoniaspp.,Hypogymnia physodes, Usneaspp. (17.4%), which were also the only preferred food plants. The amount of food removed from the field layer was stable through the winter. Roe deer used the lower part of the study area most heavily. At lower altitudes, older mature stands and edges between medium‐aged stands and clear‐cuts/plantations were preferred, pole‐sized stands and edges between older mature stands and clear‐cuts/plantations were used as expected from their availabilities, whereas medium‐aged stands, clear‐cuts and young plantations were avoided. That snow depth was an important factor determining habitat use by roe deer was evident in three ways: 1) use of areas at higher elevations decreased as winter progressed, 2) use of mature forest stands increased from early to late winter relative to open habitats, and 3) use of mature forest stands was more extensive at higher than at lower elevations compared to open habitats.

Erratum: Effect of snow depth on wolf activity and prey selection in north central Minnesota

Erratum: Effect of snow depth on wolf activity and prey selection in north central Minnesota

Effect of snow depth on wolf activity and prey selection in north central Minnesota

Wolf (Canis lupus) activity and interactions with white-tailed deer (Odocoileus virginianus) were monitored in north central Minnesota during six winters in which mean January–February snow depth alternated between shallow (19–26 cm) and relatively deep (40–47 cm) and winters (winter severity index; L. J. Verme. 1968. J. Wildl. Manage. 32: 566–574) alternated between mild (71–98) and moderately severe (126–137). Wolves traveled farther and more often and spent less time with other pack members in mild than in severe winters. Radio-marked wolves and deer used conifer cover less, and fewer deer were killed there, when snow was shallow. Similarly, fewer wolf-killed deer were found in and near deer concentration areas during mild winters. Of the 74 deer killed by wolves, the proportion that were fawns (54%) differed from the proportion of fawns in the winter population (27%), but neither varied with winter severity. Few deer killed by wolves appeared debilitated. Carcass consumption was high in all winters, regardless of their severity, but wolves scavenged less in mild than in severe winters (10 vs. 29% of deer carcasses observed). Thus, wolves changed winter activity, movement patterns, sociality, and feeding behavior in response to snow-induced changes in deer distribution and mobility.