Reduced Snow Cover Research Articles

Projected future changes in the cryosphere and hydrology of a mountainous catchment in the upper Heihe River, China

Abstract. Climate warming exacerbates the degradation of the mountain cryosphere, including glacier retreat, permafrost degradation, and snow cover reduction. These changes dramatically alter the local and downstream hydrological regime, posing significant threats to basin-scale water resource management and sustainable development. However, this issue is still not adequately addressed, particularly in mountainous catchments. We developed an integrated cryospheric–hydrologic model, the FLEX-Cryo model, to comprehensively consider glaciers, snow cover, and frozen soil and their dynamic impacts on hydrological processes. Taking the mountainous Hulu catchment located in the upper Heihe River of China as a case study, we utilized the state-of-the-art climate change projection data under two scenarios (SSP2-4.5 and SSP5-8.5) from the sixth phase of the Coupled Model Intercomparison Project (CMIP6) to simulate the future changes in the mountainous cryosphere and their impacts on hydrology. Our findings showed that under the medium-emission scenario (SSP2-4.5) and high-emission scenario (SSP5-8.5), by the end of the 21st century, the glacier will completely melt out around the years 2051 and 2045, respectively. The annual maximum snow water equivalent is projected to decrease by 41.4 % and 46.0 %, while the duration of snow cover will be reduced by approximately 45 and 70 d. The freeze onset of seasonally frozen soil is expected to be delayed by 10 and 22 d, while the thaw onset of permafrost is likely to advance by 19 and 32 d. Moreover, the maximum freeze depth of seasonally frozen soil is projected to decrease by 5.2 and 10.9 cm per decade, and the depth of the active layer will increase by 8.2 and 15.5 cm per decade. Regarding hydrology, catchment total runoff exhibits a decreasing trend, and the tipping point of glacier runoff occurs approximately between 2019 and 2021. Permafrost degradation will likely reduce the duration of low runoff in the early thawing season; the discontinuous baseflow recession gradually transitions into linear recessions, and the baseflow increases. Our results highlight the significant changes expected in the mountainous cryosphere and hydrology in the future. These findings enhance our understanding of cold-region hydrological processes and have the potential to assist local and downstream water resource management in addressing the challenges posed by climate change.

Analysis of the Spatiotemporal Variability of Hydrological Drought Regimes in the Lowland Rivers of Kazakhstan

Hydrological droughts occur as a result of various hydrometeorological conditions, such as precipitation deficits, reduced snow cover, and high evapotranspiration. Droughts caused by precipitation deficits and occurring during warm seasons are usually longer in duration. This important observation raises the question that climate change associated with global warming may increase drought conditions. Consequently, it is important to understand changes in the processes leading to dry periods in order to predict potential changes in the future. This study is a scientific analysis of the impact of climate change on drought conditions in the Zhaiyk–Caspian, Tobyl–Torgai, Yesil, and Nura–Sarysu water management basins using the standardized precipitation index (SPI) and streamflow drought index (SDI). The analysis methods include the collection of hydrometeorological data for the entire observation period up to and including 2021 and the calculation of drought indices to assess their intensity and duration. The results of this study indicate an increase in the intensity and frequency of drought periods in the areas under consideration, which is associated with changes in climatic conditions. The identified trends have serious implications for agriculture, ecological balance, and water resources. The conclusions of this scientific study can be useful for the development of climate change adaptation strategies and the sustainable management of natural resources in the regions under consideration.

Seasonal response of soil microbial community structure and life history strategies to winter snow cover change in a temperate forest

Snow cover provides a thermally stable and humid soil environment and thereby regulates soil microbial communities and biogeochemical cycling. A warmer world with large reductions in snow cover and earlier spring snowmelt may disrupt this stability and associated ecosystem functioning. Yet, little is known about the response of soil microbial communities to decreased snowpack and potential carry-over effects beyond the snow cover period. Herein, we tested this response by conducting a snowpack manipulation experiment (control, addition, and removal) in a temperate forest. Our results showed that fungi were more sensitive to changes in snowpack. Thicker snowpack increased the diversity of fungi, but had weak effects on the diversity of bacteria in winter. Thickening snow cover promoted the ratio of fungi to bacteria abundance across the year, and such relative increase in fungi abundance was largely driven by Basidiomycota phyla (Agaricomycetes class). Increased snowpack decreased soil nitrate concentration, and produced carry-over biogeochemical effects evidenced by increased summer β-1,4-glucosidase and N-acetyl-β-glucosaminidase activities. On a seasonal scale, microbial biomass peaked at both winter and summer; winter microbial community was fungi dominated, while bacteria dominated in summer. The abundances of bacterial phyla had greater seasonal variation than fungal phyla. Specifically, Actinobacteria had greater dominance in winter than in summer, while Acidobacteria, Proteobacteria, and Verrucomicrobia had greater abundance in summer than in winter. Microbial high yield-resource acquisition-stress tolerance life history strategies showed significant seasonal tradeoffs, i.e., resource acquisition and stress tolerance strategies dominated in summer, while high yield strategy dominated in winter. Overall, our findings underline that climate-induced reductions in snow cover can disrupt soil biogeochemical cycling also beyond the snow cover period due to shifts in soil microbial community structure and life history strategies.

Cryosphere degradation in a changing climate

AbstractOver the last few decades, the instrumental climate record shows a progressive global warming. As one of the most sensitive elements of the Earth's climate system, the cryosphere is significantly affected by this trend. As a result, its various components are readjusting in a situation of disequilibrium with the climate through a series of dynamics. These include the thinning and retreat of glaciers that may lead to the formation of new lakes; the thawing of ground ice, leading to the deformation of terrain; the reduction of snow cover; and the occurrence of mass movements that threaten populations and infrastructures. This Special Issue contains 23 scientific papers with case studies that explore the above issues in the Arctic, Antarctic and high mountain regions.

Germination response to winter temperature changes with seed shape and length of temperature exposure.

In many regions, the climate is changing faster during winter than during the other seasons, and a loss of snow cover combined with increased temperature variability can expose overwintering organisms to harmful conditions. Understanding how species respond to these changes during critical developmental times, such as seed germination, helps us assess the ecological implications of winter climate change. To address this concern, we measured the breaking of seed dormancy and cold tolerance of temperate grassland species in the lab and field. In the lab, we ran germination trials testing the tolerance of 17 species to an extreme cold event. In the field, we deployed seeds of two species within a snow manipulation experiment at three locations and measured germination success biweekly from seeds subjected to ambient and reduced snow cover from winter into spring. From lab trials, cold tolerance varied among species, with seed germination decreasing <10%-100% following extreme cold events. Cold tolerance was related to seed traits, specifically less round seeds, seeds that required cold stratification, and seeds that mature later in the season tended to be more impacted by extreme cold temperatures. This variation in seed cold tolerance may contribute to altered community composition with continued winter climate change. In the field, germination increased through late winter, coinciding with the accumulation of days where temperatures were favorable for cold stratification. Through spring, germination success decreased as warm temperatures accumulated. Collectively, species-specific seed cold tolerances and mortality rates may contribute to compositional changes in grasslands under continued winter climate change.

Detection of land surface albedo changes over Iran using remote sensing data

AbstractAlbedo is one of the key parameters in climatic studies. Investigating its temporal and spatial behavior can be a tool for understanding environmental changes. The MODIS sensor continuously produces the land surface albedo on a global scale and with the appropriate spatial resolution and makes it available to researchers. In this study, to analyze Iran's surface albedo trend, first, the daily albedo data of the MODIS on Iran in the period from January 1, 2001 to December 30, 2021 with a spatial resolution of 500 m were prepared from the NASA website. After the necessary pre‐processing, the long‐term seasonal and annual trend of Iran's albedo was calculated at the 90% confidence level using the non‐parametric Mann–Kendall test. The findings showed that the albedo trend is positive in the lowland interior areas of Iran and negative in the highland areas. Since the decreasing trend of albedo in highland areas indicates the reduction of snow cover in these areas, this issue can challenge the life and water resources of these areas that rely on the accumulation of snow.

Response of the water level of the Balkash Lake to the distribution of meteorological and hydrological droughts under the conditions of climate change

ABSTRACT Hydrological droughts occur due to a variety of hydrometeorological phenomena, such as lack of precipitation, reduced snow cover and high evaporation. The values of these factors vary depending on the climate and the severity of drought events. Droughts caused by a lack of precipitation and continuing in the warm season have a longer periodicity. This important statement raises the question of whether climate change may exacerbate the phenomenon of drought. Therefore, understanding changes in the formation of hydrological droughts is key to foreseeing possible changes in the future. This scientific study analyzes the spread of hydrometeorological droughts in the Ile-Balkash basin using standardized precipitation indices and the drought index of river runoff. Lake Balkash plays an important role in the hydrological cycle and is a valuable freshwater resource, especially in dry years. Prolonged droughts in the area have serious consequences, including deterioration of water quality and loss of wetlands, which are important to the ecological system and migratory birds. The analysis shows that during the period of instrumental observations, several extreme hydrological droughts were observed in this area, (1943–1946, 1973–1975 and 1983–1987), which emphasizes the relevance and importance of scientific research on the problem of drought.

Intensified warming suppressed the snowmelt in the Tibetan Plateau

Understanding how hydrological factors interrelate is crucial when examining the impact of climate warming on snowmelt. However, these connections are often overlooked, leading to an unclear relationship between temperature and snowmelt. This study investigates the complex interplay between temperature and snowmelt in the Tibetan Plateau from 1961 to 2020, focusing on how extreme high-temperature events affect the frequency of extreme snowmelt. Using a structural equation model, we detected three temperature-related factors that predominantly influenced snowmelt and extreme snowmelt. The annual average temperature was found to have a significant indirect impact on snowmelt, mediated by changes in snowfall, snow depth and snow cover. By contrast, high-temperature days (daily maximum temperatures exceeding the 90th percentile) and heat waves (at least three consecutive high-temperature days) negatively affected extreme snowmelt directly or indirectly. The direct effect of increasing extreme temperature events was associated with an earlier onset of high-temperature periods, which accelerated snowmelt and shortened the duration of extreme snowmelt periods. Additionally, the reduction in snow cover owing to warming emerged as a main factor suppressing snowmelt and extreme snowmelt frequencies. We also revealed spatiotemporal variations in the temperature‒snowmelt relationship that highly depended on changes in snowmelt patterns. The study elucidated why warming suppresses snowmelt and extreme snowmelt events in the Tibetan Plateau, highlighting the mediating roles of snow-related and phenological factors. The findings will provide scientific support for climate simulation and water management policymaking in alpine regions worldwide.

High freezing sensitivity of legumes relative to other herbaceous species in northern temperate plant communities.

Reduced snow cover and increased air temperature variability are predicted to expose overwintering herbaceous plants to more severe freezing in some northern temperate regions. Legumes are a key functional group that may exhibit lower freezing tolerance than other species in these regions, but this trend has been observed only for non-native legumes. Our aim was to confirm if this trend is restricted to non-native legumes or whether native legumes in these regions also exhibit low freezing tolerance. First, we transplanted legumes (five non-native species and four native species) into either an old field (non-native) or a prairie (native) and used snow removal to expose the plots to increased soil freezing. Second, we grew plants in mesocosms (old field) and pots (prairie species) and exposed them in controlled environment chambers to a range of freezing treatments (control, 0, -5 or -10 °C) in winter or spring. We assessed freezing responses by comparing differences in biomass, cover and nodulation between freezing (or snow removal) treatments and controls. Among legume species, lower freezing tolerance was positively correlated with a lower proportion of nodulated plants and active nodules, and under controlled conditions, freezing-induced reductions in above-ground biomass were lower on average in native legumes than in non-native legumes. Nevertheless, both non-native and native legumes (except Desmodium canadense) exhibited greater reductions in biomass in response to increased freezing than their non-leguminous neighbours, both in controlled environments and in the field. These results demonstrate that both native and non-native legumes exhibit low freezing tolerance relative to other herbaceous species in northern temperate plant communities. By reducing legume biomass and nodulation, increased soil freezing could reduce nitrogen inputs into these systems.

Effects of reduced snowpack due to climate warming on abiotic and biotic soil properties in alpine and boreal forest systems

Reduction in snow cover, depth, onset, and duration of seasonal snow in mid-latitude regions due to climate warming has multiple global and local scale ecosystem impacts. These effects include modulations of the hydrological cycles and increases in land surface solar radiation absorption due to decreased albedo. Changes in snow cover characteristics also affect underlying soils. Snow has an insulating effect on soils by decoupling air and soil temperatures, thus seasonal snow cover reduction leads to overall lower soil temperatures and an increase in freeze-thaw cycles. This is especially prominent during the fall and spring thaw seasons when the snow cover is not as extensive. This in turn has downstream impacts on soil physical, chemical, and biological properties. Among these impacts are soil moisture reduction, temperature, frost regimes, soil pH shifts, and alteration in nutrient flux dynamics during winter, snowmelt period and the following summer growing season. These changes in soil physicochemical properties due to snowpack reduction can then impact the biological soil properties via increased plant root mortality, reduced abundance and diversity of soil arthropods, and shifts in composition, abundance and activity of soil microbial communities. All these soil biotic factors can in turn alter the dynamics of soil nutrient fluxes and future greenhouse gas emissions. Here, we integrate data on the effects of snow cover reduction on abiotic and biotic soil properties, with focus on temperate alpine and forest ecosystems and with an outlook on future impacts.

Increased Extreme Precipitation in May over Southwestern Xinjiang in Relation to Eurasian Snow Cover in Recent Years

Abstract In this study, the interdecadal variations of extreme precipitation in May over southwestern Xinjiang (SWX) and related mechanisms were investigated. The extreme precipitation in May over SWX exhibited a decadal shift in the 1990s (negative phase during 1970–86 and positive phase during 2003–18). The decadal shift corresponded to strengthened moist airflow from the Indian Ocean and an anomalous cyclone over SWX during 2003–18. It is found that the interdecadal change of the wave trains in Eurasia might account for the differences in atmospheric circulation between the above two periods. Further analyses reveal that spring snow cover over Eurasia is closely linked to extreme precipitation over SWX during 2003–18. Increased snow cover in western Europe (WE) from February to March is accompanied by more snowmelt. This resulted in less local snow cover and lower albedo, leading to warm temperatures over WE in May. The changes in temperatures increase the local 1000–500-hPa thickness over WE. These factors provide favorable conditions for the enhancement of the Eurasian wave trains, which significantly influence extreme precipitation over SWX. On the other hand, corresponding to decreased albedo caused by the reduction of snow cover in northern Eurasia (NE) in May, anomalous surface warming occurs over NE. The anomalous warming results in positive geopotential height anomalies that intensify the meridional geopotential height gradient over Eurasia and cause an acceleration of the westerly jet in May. Anomalous upper-level divergence in SWX induced by the enhanced westerly jet provides a favorable dynamical condition for increased extreme precipitation.

Comparative Analysis of Characteristics and Physical Mechanisms for Typical Summer Extreme Precipitation in Pakistan

Abstract The 2022 floods in Pakistan resulted in severe losses and garnered global attention. This study aims to enhance the understanding of extreme precipitation (EP) events in Pakistan by examining the characteristics and mechanisms behind the persistent EP during summer, utilizing daily precipitation data from the Climate Prediction Center (CPC). Results showed that the monsoon precipitation in 2010, 2020 and 2022 are the highest three years on record. Notably, these peak events in 2010 (concentrating in the north) and 2022 (concentrating in the south) spanned from July through August. Conversely, the extreme precipitation in August 2020 was concentrated in northern Pakistan. For the circulation patterns, the intensification of the South Asian High and the western Pacific subtropical high with a strong Indian monsoon is a unifying feature, but the Iranian high and monsoon low-pressure system on the south of Pakistan was different. Additionally, the EP in July 2010 and August 2022 were also influenced by the teleconnection associated with European Blocking. La Niña events and the negative-phase Indian Ocean Dipole (IOD) also played a role in affecting summer EP, with the strongest La Niña occurring in 2010 and a notable triple-dip La Niña coinciding with a significant negative IOD phase in 2022. La Niña contributed to the formation of an anomalously strong anticyclone over the northwest Pacific and easterly winds along the southern Himalayas, impacting moisture transport to Pakistan. Conversely, the negative IOD phase amplified EP in Pakistan by enhancing the northward movement of convective systems and westerly winds over the Indian Ocean. Furthermore, reduced snow cover on the Tibetan Plateau in the springs of 2010 and 2022 likely induced a stronger thermal dynamical effect, acting as a heat source in summer and increasing precipitation in Pakistan.

Global reduction of snow cover in ski areas under climate change.

Ongoing climate change substantially alters snowfall patterns with severe but diverging consequences for global ski areas. A global assessment as well as the investigation of potential implications for mountain ecosystems is currently lacking. We quantify future trends in natural snow cover days under different climate change scenarios until 2100 in seven major global skiing regions and discuss implications for mountainous biodiversity by analysing how natural snow cover days relate to regional human population density. Within all major skiing regions, snow cover days are projected to decrease substantially under every assessed climate change scenario. Thirteen percent of all current ski areas are projected to completely lose natural annual snow cover and one fifth will experience a reduction of more than 50% by 2071-2100 relative to historic baselines. Future skiable areas will concentrate in less populated areas, towards continental regions and inner parts of the mountain ranges. As skiable areas will be located at greater distances to highly populated areas in the future, we expect an expansion of infrastructure and increasing intervening actions (i.e., artificial snowmaking, slope grooming) to prolong snow duration. Our results are concerning for both the recreational and economic value of skiing as well as for mountain biodiversity since vulnerable high-altitude species might be threatened by space reductions with ski area expansion.

Impacts of physical parameterization scheme of snow and soil properties over the Tibetan Plateau on the simulation of summer rainfall in China

Accurate representation of soil and snow state variables in the land surface model is crucial for good simulation results. In order to investigate the potential impacts of the overestimated snow cover over the Tibetan Plateau (TP) on precipitation over China, we designed comparative experiments over TP with and without updated soil texture data, soil hydrological parameters, and the fresh snow density scheme to address this issue with the Weather Research and Forecasting Model (WRF). The results show that snow cover fraction (SCF) and surface albedo in winter on the TP were overestimated in the WRF control experiment (CTL), with albedo bias exceeding 0.4 in the western TP. The SCF in the WRF improved experiment (WRFIM) is about 8% lower than that of the CTL, and the bias is decreased to 0.2–0.3 in the interior of the TP. The thermal and dynamic effects of the TP in winter have a significant impact on the weather and climate of East Asia during summer. Thus, the simulated summer rainfall bias is significantly reduced by WRFIM in North China, and the mid-lower reaches of the Yangtze River, along with the spatial correlation coefficient between the observed-based and WRF-simulated rainfall increased from 0.76 in CTL to 0.88 in WRFIM. The WRFIM-simulated reductions in snow cover and albedo cause a decrease in upward shortwave radiation and eventually increase net surface radiation. The horizontal temperature gradient of the atmosphere is increased in the WRFIM compared to the CTL, and the increased temperature in the lower and middle layers accommodates more water vapor, which is not conducive to precipitation formation. Correspondingly, the Western Pacific Subtropical High at 500 hPa in the middle troposphere weakened. The low-level anticyclonic circulation at 850 hPa also weakened to the east, affecting water vapor transport in eastern China. It leads to a decrease in the water vapor transported northward by southeasterly from the western Pacific Ocean and a decrease in the water vapor flux reaching North China. This work indicates that accurate characterization of soil properties and snow cover on the TP is crucial for improving the simulation bias of summer rainfall in China.

Climate change disrupts the seasonal coupling of plant and soil microbial nutrient cycling in an alpine ecosystem.

The seasonal coupling of plant and soil microbial nutrient demands is crucial for efficient ecosystem nutrient cycling and plant production, especially in strongly seasonal alpine ecosystems. Yet, how these seasonal nutrient cycling processes are modified by climate change and what the consequences are for nutrient loss and retention in alpine ecosystems remain unclear. Here, we explored how two pervasive climate change factors, reduced snow cover and shrub expansion, interactively modify the seasonal coupling of plant and soil microbial nitrogen (N) cycling in alpine grasslands, which are warming at double the rate of the global average. We found that the combination of reduced snow cover and shrub expansion disrupted the seasonal coupling of plant and soil N-cycling, with pronounced effects in spring (shortly after snow melt) and autumn (at the onset of plant senescence). In combination, both climate change factors decreased plant organic N-uptake by 70% and 82%, soil microbial biomass N by 19% and 38% and increased soil denitrifier abundances by 253% and 136% in spring and autumn, respectively. Shrub expansion also individually modified the seasonality of soil microbial community composition and stoichiometry towards more N-limited conditions and slower nutrient cycling in spring and autumn. In winter, snow removal markedly reduced the fungal:bacterial biomass ratio, soil N pools and shifted bacterial community composition. Taken together, our findings suggest that interactions between climate change factors can disrupt the temporal coupling of plant and soil microbial N-cycling processes in alpine grasslands. This could diminish the capacity of these globally widespread alpine ecosystems to retain N and support plant productivity under future climate change.

Spatiotemporal patterns of microclimatic buffering in relict alpine communities

AbstractQuestionsIn alpine landscapes, topography creates a mosaic of microclimatic niches that might prevent local extinctions, but the influence of this spatial heterogeneity on plant communities is largely unknown. Here we ask (1) how soil microclimatic variation is comparable at temporal and spatial scales, and (2) how such variation influences species composition and local extinctions in relict alpine communities.LocationPicos de Europa National Park, northern Spain.MethodsWe resurveyed permanent plots in four alpine sites following the recording of soil temperatures (temporal survey) for 10 years. We then sampled the spatial variation in species composition and microclimatic temperatures in 80 plots around the permanent plots (spatial survey). We evaluated the variation of six microclimatic indices between the temporal and the spatial surveys, and calculated the temporal trends observed in species cover. We finally predicted local extinction rates under microclimatic scenarios based on the observed microclimate–community relations.ResultsDespite high interannual variation, we found a 10‐year trend of temperature warming on (microridge) fellfields and (microvalley) snowbeds. Microclimatic variation was larger in space than in time, with little temperature variation in snowbeds and extreme low temperatures recorded in fellfields. Species composition was mainly influenced by growing degree days (GDD) and freezing degree days (FDD), which were both related to snow cover duration. Plant cover of 16 species (out of 36 frequent species) showed significant responses to microclimatic variation. Local extinctions were mainly predicted under relatively hotter and more freezing conditions.ConclusionsOur results support the idea that microclimatic spatial heterogeneity can reduce the negative influence of climate change on alpine plant communities. However, a continuous reduction of snow cover will result in a tipping point beyond which the buffer effect of this spatial heterogeneity will not be effective in protected microsites, leading to community homogenization. This process may have started in relict alpine communities where species from snowy microclimates are being outcompeted by species adapted to below‐zero winter temperatures.

Experimental Whole‐Ecosystem Warming Enables Novel Estimation of Snow Cover and Depth Sensitivities to Temperature, and Quantification of the Snow‐Albedo Feedback Effect

AbstractClimate change is reducing the amount, duration, and extent of snow across high‐latitude ecosystems. But, in landscapes where persistent winter snow cover develops, experimental platforms to specifically investigate interactions between warming and changes in snowpack, and impacts on ecosystem processes, have been lacking. We leveraged a whole‐ecosystem warming experiment in a boreal peatland forest to quantify how snow duration, depth, and fractional cover vary with warming of up to +9°C. We found that every snow‐related quantity we examined declined precipitously as the amount of warming increased. The importance of deep, continuous snow cover for moderating shallow soil temperature is highlighted by an increase in soil temperature variance and the frequency of short‐duration freeze‐thaw cycles in the warmer plots. We used a paired‐plot approach to estimate the magnitude of the snow‐albedo feedback effect, and demonstrate that albedo‐driven warming linked to reduced snow cover varies between December (+0.4°C increase in maximum air temperature) and March (+1.2°C increase) because of differences in insolation. Overall, results show that even modest future warming will have profound impacts on northern winters and cold‐season ecosystem processes. Plot‐level data from this warming experiment, and emergent relationships between warming and quantities related to snow cover and duration, could be of enormous value for testing and improving the representation of snow processes in simulation models, especially under future climate scenarios that are outside of the range of historically observed variability.

Warmer future climate in Canada—implications for winter survival of perennial forage crops

Significant increase in wintertime air temperature, especially the reduced cold extremes under climate change, might be beneficial to the winter survival of perennial crops. However, climate warming could result in less snowfall, reduced snow cover, as well as changes in climate conditions for fall hardening and winter thaws. How these changes might impact the risks of winter damages to overwintering crops, such as perennial forage crops requires a comprehensive assessment for proactively adapting to climate change in the agricultural sector, especially the beef and dairy industries. Based on the most up-to-date climate projections from a set of global climate models, we used a snow model and a suite of agroclimatic indices for perennial forage crops to assess potential changes in the risks of winter injury to perennial forage crops across Canada in the near-term (2030s), the mid-term (2050s), and the distant future (2070s). Our results show that the risk of exposure to extremely low temperatures (daily Tmin ≤ −15 °C) without snow protection is projected to decrease across Canada with improved conditions for fall hardening. However, winter thaws and rainfall are projected to increase, and this would increase the risk of winter injury due to loss of hardiness together with potential soil heaving and ice encasement.

Snow cover-related camouflage mismatch increases detection by predators.

Camouflage expressed by animals is an adaptation to local environments that certain animals express to maximize survival and fitness. Animals at higher latitudes change their coat color according to a seasonally changing environment, expressing a white coat in winter and a darker coat in summer. The timing of molting is tightly linked to the appearance and disappearance of snow and is mainly regulated by photoperiod. However, due to climate change, an increasing mismatch is observed between the coat color of these species and their environment. Here, we conducted an experiment in northern Sweden, with white and brown decoys to study how camouflage (mis)-match influenced (1) predator attraction to decoys, and (2) predation events. Using camera trap data, we showed that mismatching decoys attracted more predators and experienced a higher likelihood of predation events in comparison to matching decoys, suggesting that camouflage mismatched animals experience increased detection by predators. These results provide insight into the function of a seasonal color coat and the need for this adaptation to maximize fitness in an environment that is exposed to high seasonality. Thus, our results suggest that, with increasing climate change and reduced snow cover, animals expressing a seasonal color coat will experience a decrease in survival.

Exploring urban land surface temperature with geospatial and regression modelling techniques in Uttarakhand using SVM, OLS and GWR models

Given the climate change challenges, Uttarakhand has become crucial for examining land dynamics and regional climate interactions. This study employed a Support Vector Machine (SVM) for land use and land cover mapping for 2024, achieving 94% accuracy and a Kappa coefficient of 0.90, indicating robust mapping. Key land indices such as NDVI, NDWI, NDBI, NDSI, and NDBaI were calculated, along with Land Surface Temperature (LST) from Landsat 8 imagery. These indices were selected for their relevance in representing vegetation health (NDVI), measuring water content (NDWI), assessing urban areas (NDBI), identifying snow cover (NDSI), and highlighting the barren land (NDBaI), which all influence LST. Hotspot analysis with Getis-Ord Gi∗ revealed spatial distribution patterns of LST. Regression analysis showed significant relationships: a strong positive correlation between LST and NDBI (R2 = 0.78) and a substantial negative correlation between LST and NDSI (R2 = −0.80). The strong positive correlation highlights how urbanization contributes to rising surface temperatures, while the substantial negative correlation underscores the cooling effect of snow cover, which is particularly relevant as reduced snow cover could lead to higher LST in the context of climate change. These correlations offer deeper insights into how land cover changes can exacerbate or mitigate climate impacts in Uttarakhand. Two regression models were used for statistical modeling and spatial analysis: Ordinary Least Squares (OLS) and Geographically Weighted Regression (GWR). In OLS, the results reveal non-stationarity (p = 0.000) with an R2 value of 0.79 while GWR significantly enhanced performance, achieving an R2 value of 0.94. The improved performance of GWR (R2 = 0.94) compared to OLS (R2 = 0.79) can be attributed to GWR’s ability to account for spatial non-stationarity. This method allows for variations in relationships between LST and explanatory variables across different locations, effectively capturing local patterns that OLS may overlook. Spatial autocorrelation analysis, utilizing Moran’s I, exhibited a decrease from 0.606 (OLS) to 0.02 (GWR), This reduction indicates that GWR effectively captures spatial non-stationarity, minimizing residual autocorrelation by modeling local relationships between LST and its predictors that often remain in global models like OLS, thereby demonstrating its advantages in heterogeneous regions. The findings underscore the importance of employing GWR to better elucidate the connection between LST and its predictors, specifically in regions characterized by spatial non-stationarity, thereby offering insights crucial for informed decision-making amidst changing climatic conditions.