Global climate change exerts profound effects on snow cover, with consequential impacts on microbial activities and the stability of soil organic carbon (SOC) within aggregates. Northern peatlands are significant carbon reservoirs, playing a critical role in mitigating climate change. However, the effects of snow variations on microbial-mediated SOC stability within aggregates in peatlands remain inadequately understood. Here, an in-situ field experiment manipulating snow conditions (i.e., snow removal and snow cover) was conducted to investigate how snow variations affect soil microbial community and the associated SOC stability within soil aggregates (> 2, 0.25-2, and < 0.25 mm) in a peatland of Northeast China. The results showed that snow removal significantly increased the SOC content and stability within aggregates. Compared to the soils with snow cover, snow removal resulted in decreased soil average temperatures in the topsoil (0-30 cm depth) and subsoil (30-60 cm depth) (by 1.48 and 1.34 degrees C, respectively) and increased freeze-thaw cycles (by 11 cycles), consequently decreasing the stability of aggregates in the topsoil and subsoil (by 23.68% and 6.85%, respectively). Furthermore, more recalcitrant carbon and enhanced SOC stability were present in microaggregates (< 0.25 mm) at two soil depths. Moreover, reductions in bacterial diversity and network stability were observed in response to snow removal. Structural equation modeling analysis demonstrated that snow removal indirectly promoted (P < 0.01) SOC stability by regulating carbon to nitrogen (C:N) ratio within aggregates. Overall, our study suggested that microaggregate protection and an appropriate C:N ratio enhanced carbon sequestration in response to climate change.

Understanding the thermal regime of road embankments in cold climates during winter is essential for efficient road design and accurate estimation of maintenance frequencies to reduce freeze-induced damage. In response to the challenging climate conditions in northern Sweden, an experimental field setup was designed to assess the thermal impact of culverts and accumulated snow in ditches on the thermal regime of road embankments during a winter season. This study provides detailed information on the experimental setup, highlights potential challenges from installation phase to data acquisition, and addresses measurement errors. Methods to ensure accuracy and obtain reliable data are also presented. Additionally, some of the obtained measurement results are included in this paper. The results show that snow impacts the thermal regime of the embankment from the onset of accumulation in the ditch, when the snow cover is still thin, until it reaches a depth of 65 cm. Beyond this depth, the soil beneath the snow remains almost unfrozen throughout the winter season. Additionally, the temperature distribution measurements within the embankment indicate that freezing progresses faster near the culvert compared to the rest of the embankment. However, once the culvert ends are insulated by snow cover, the frost depth in the soil near the culvert does not increase significantly, while the rest of the road continues to freeze gradually to greater depths throughout the winter season. The measurement results presented in this study provide researchers with a reliable dataset for validating numerical models in related research areas simulating cold-climate conditions. Additionally, these results enhance the understanding of the thermal regime of road embankments in typical cold climates and offer valuable insights for planning road maintenance and construction in such regions. Furthermore, this study provides essential information for researchers aiming to design and optimize experimental measurement setups in similar investigations.

Freeze-thaw-induced N2O pulses could account for nearly half of annual N2O fluxes in cold climates, but their episodic nature, sensitivity to snow cover dynamics, and the challenges of cold-season monitoring complicate their accurate estimation and representation in global models. To address these challenges, we combined in situ automated high-frequency flux measurements with cross-ecoregion soil core incubations to investigate the mechanisms driving freeze-thaw-induced N2O emissions. We found that deepened snow significantly amplified freeze-thaw N2O pulses, with these similar to 50-day episodes contributing over 50% of annual fluxes. Additionally, freeze-thaw-induced N2O pulses exhibited significant spatial heterogeneity, ranging from 3.4 to 1184.1 mu g N m(-2) h(-1) depending on site conditions. Despite significant spatiotemporal variation, our results indicated that 68%-86% of this variation can be explained by shifts in controlling factors: from water-filled pore space (WFPS), which drove anaerobic conditions, to microbial constraints as snow depth increases. Below 43% WFPS, soil moisture was the overwhelmingly dominant driver of emissions; between 43% and 66% WFPS, moisture and microbial attributes (including denitrifying gene abundance, nitrogen enzyme kinetics, and microbial biomass) jointly triggered N2O emissions pulses; above 66% WFPS, microbial attributes, particularly nitrogen enzyme kinetics, prevailed. These findings suggested that maintaining higher soil moisture served as a trigger for activating microbial activity, particularly enhancing nitrogen cycling. Furthermore, we showed that hotspots of freeze-thaw-induced N2O emissions were linked to high root production and microbial activity in cold and humid grasslands. Overall, our study highlighted the hierarchical control of WFPS and microbial processes in driving freeze-thaw-induced N2O emission pulses. The easily measurable WFPS and microbial attributes predictable from plant and soil properties could forecast the magnitude and spatial distribution of N2O emission hot moments under changing climate. Integrating these hot moments, particularly the dynamics of WFPS, into process-based models could refine N2O emission modeling and enhance the accuracy of global N2O budget prediction.

Most researches assume snow cover as an unventilated thermal resistance to discuss its impacts on the crushed-rock interlayer embankment (CRIE). However, as a porous medium, its role in altering ventilation cooling remains elusive. We developed a numerical model particularly consisting of ventilated snow cover to investigate impacts on the cooling mechanisms and performance of CRIE under climate change. We found that the cooling performance is seriously underestimated if the ventilation of snow cover is ignored. Natural convection and forced convection coexist in cold seasons, and snow cover is conducive to the former, but not to the latter. Snow cover weakens the cooling performance depending on external wind speeds, ambient temperature and relevant properties of snow cover. Before the limit thickness (about 0.5 m) of snow cover, thermal insulation effect would be enhanced with snow cover thickening. On the contrary, it would be weakened and the cooling role increases relatively after the limit. The same goes for total natural convection strength over the entire period of snow cover. Increased snow cover porosity could enhance the cooling performance, while the increase of external wind speeds and extended duration of snow cover might warm the underlying permafrost. The findings provide a valuable reference for its application in snowy permafrost regions.

Snow amounts and duration are susceptible to climate change and may significantly affect plant diversity and biomass in grassland ecosystems. Yet, the combined effects of grassland use (type and intensity) and snow depth on plant diversity and productivity remain poorly understood. We established two complementary field experiments to explore the mechanisms driving the effects of grassland use (type and intensity) and snow manipulation on plant diversity and productivity in the meadow steppe. An experiment on grassland use type and snow manipulation showed that lower snow cover in winter reduced soil moisture in the snowmelt period, significantly increased the abundance of ammonia-oxidizing archaea and ammonia-oxidizing bacteria, and initiated nitrification earlier, resulting in the loss of soil available nitrogen, and then reduced the aboveground biomass of early grasses. An experiment on grassland mowing intensity and snow manipulation showed that moderate mowing intensity can restrain the loss of grass biomass and soil nutrients and maintain grassland sustainability in winters with less snow. Stochasticity has played a more important role in plant community assembly in higher intensity of grassland use. Based on our results, we recommend that optimal defoliation height can restrain the loss of grass biomass and soil nutrients and maintain grassland sustainability in winters with less snow. This study has potential benefits for optimizing sustainable production and maintaining ecosystem function under winter snowfall changes in the future across large regions of arid and semiarid grasslands. (c) 2024 The Society for Range Management. Published by Elsevier Inc. All rights are reserved, including those for text and data mining, AI training, and similar technologies.

The impact of global climate change and human-induced nitrogen (N) deposition on winter weather patterns will have consequences for soil N cycling and greenhouse gas emissions in temperate deserts. Biological soil crusts (referred to as biocrusts) are crucial communities in soil and significant sources of nitrous oxide (N2O) emission in desert ecosystems and are sensitive to environmental changes. The contribution of bacteria and fungi to N2O production in drylands has been acknowledged. However, the effect of changes in snow cover and N deposition on the N2O production of different microbial groups of microorganisms is not yet clear. In this study, we examine the responses of fungi and bacteria mediated pathways involved in soil N2O production from biocrusts to longterm snow cover manipulation and N addition experiments in the Gurbantunggut Desert. These soils were incubated and subjected to biocide treatments (such as cycloheximide and streptomycin, and fungal and bacterial inhibitors), after which rates of potential nitrification and N2O production were measured. Compared with controls, snow removal treatments from bare sand, lichen crust and moss crust reduced background rates of N2O production by 29.41 %, 26.21 % and 20.49 %, respectively; N2O production rates were 1.53-fold higher in bare sand, 1.38-fold higher in lichen crust, and 1.56-fold higher in moss crust after N addition. The addition of streptomycin significantly reduced the potential nitrification rates of bare sand and biocrusts, indicating that bacteria may be important sources of NO3- production in biocrusts rather than fungi. Conversely, fungi were main sources of N2O production in biocrusts. Additionally, fungi also played a major role in N2O production in biocrusts after snow cover manipulation and N addition. Both snow cover manipulation and N addition treatment indirectly affected the N2O production in biocrusts by considerably affecting the content of substrate N and the abundance of microbial groups. Our research suggests that fungi are main contributors for denitrification in biocrusts, and that snow cover changes (removal snow and double snow) and N addition alter the contribution of biotic pathways responsible for N cycling.

Ground-Penetrating Radar (GPR) provides high-resolution, non-invasive insights into the subsurface, making it an essential tool for assessing climate change impacts and managing infrastructure in Arctic and sub-Arctic environments. This review examines GPR applications in mapping and characterizing cold-region features to enhance our understanding of the Critical Zone at high latitudes. Specifically, we focus on permafrost, including its active layer and embedded ice structures, as well as glaciers and front moraine, ice sheets, and snow cover. Furthermore, driven by advancements in miniaturization and energy efficiency, we extend our review to GPR-based subsurface exploration on the Moon and Mars, where environmental conditions and frozen geomorphological structures share similarities with terrestrial cold regions. Finally, we highlight the interconnection between hardware and software advancements and the expanding applications of GPR in cryospheric research.

In Central Asia, the ground thermal regime is strongly affected by the interplay between topographic factors and ecosystem properties. In this study, we investigate the governing factors of the ground thermal regime in an area in Central Mongolia, which features discontinuous permafrost and is characterized by grassland and forest ecosystems. Miniature temperature dataloggers were used to measure near-surface temperatures at c. 100 locations throughout the 6 km2 large study area, with the goal to obtain a sample of sites that can represent the variability of different topographic and ecosystem properties. Mean annual near-surface ground temperatures showed a strong variability, with differences of up to 8 K. The coldest sites were all located in forests on north-facing slopes, while the warmest sites are located on steep south-facing slopes with sparse steppe vegetation. Sites in forests show generally colder near-surface temperatures in spring, summer and fall compared to grassland sites, but they are warmer during the winter season. The altitude of the measurement sites did not play a significant role in determining the near-surface temperatures, while especially solar radiation was highly correlated. In addition, we investigated the suitability of different hyperspectral indices calculated from Sentinel-2 as predictors for annual average near-surface ground temperatures. We found that especially indices sensitive to vegetation properties, such as the Normalized Difference Vegetation Index (NDVI), show a strong correlation. The presented observations provide baseline data on the spatiotemporal patterns of the ground thermal regime which can be used to train or validate modelling and remote sensing approaches targeting the impacts of climate change.

Snow distribution has been altered over the past decades under global warming, with a significant reduction in duration and extent of snow cover and an increase in unprecedented snowstorms across large areas in cold regions. The altered snow conditions are likely to have immediate (in winter) and carry-over or legacy (which an extended effect might continue in the following spring, summer and autumn) impacts on soil processes and functioning, but a quantification of the legacy effect of snow coverage alternation is still lacking. Furthermore, studies investigating the effect of snow cover changes on soil respiration, soil carbon pools and microbial activity are increasing, but contrasting results of different studies makes it difficult to assess the overall effect of snow cover changes and the underlying mechanisms, thus a systematic and comprehensive meta-analysis is required. In this study, we synthesized the results from 60 papers based on field snow manipulation experiments and conducted a meta-analysis to evaluate immediate and prolonged effects on eight variables related to soil carbon dynamics and microbial activity to snow coverage alternation. Results showed that snow removal had no significant effect on soil respiration, but increased dissolved organic carbon (DOC) (11.5%) and fungal abundance (32.0%). By contrast, snow addition significantly increased soil respiration (16.3%) and microbial biomass carbon (MBC) (6.6%). Snow addition had immediate and prolonged impacts on soil carbon dynamics and microbial activity lasting from winter to the following autumn, whereas an effect of snow removal on total organic carbon (TOC) and DOC was detectable only in the following spring. Snow depth, ecosystem and soil types determined the extent of the impact of snow treatments on soil respiration, DOC, MBC and microbial biomass nitrogen (MBN). Our findings provide critical insights into understanding how changes in snow coverage affect soil respiration and microbial activity. We suggest future field-based experiments to enhance our understanding the effect of climate change on soil processes and functioning in the winter and the following seasons.

Snow is an important factor controlling vegetation functions in high latitudes/altitudes. However, due to the lack of reliable in -situ measurements, the effects of snow on vegetation phenology remains poorly understood. Here, we examine the effects of snow cover duration (SCD) on the start of growing season (SOS) for different vegetation types. SOS and SCD were extracted from in -situ carbon flux and albedo data, respectively, at 51 eddy covariance flux sites in the northern mid -high latitudes. The effects of SCD on SOS vary substantially among different vegetation types. For grassland, preseason SCD outperforms other factors controlling grassland SOS. However, for forests and cropland, the preseason air temperature is the dominant factor in controlling SOS. Preseason SCD mainly influences the SOS by regulating preseason air and soil temperature rather than soil moisture. The CMIP6 Earth system models (ESMs) fail to capture the effect of SCD on SOS. Thus, Random Forest (RF) models were established to predict future SOS changing trends considering the effect of SCD. For grassland and evergreen needleleaf forest, the projected SOS advance rate is slower when SCD is considered. These findings can help us better understand impacts of snow on vegetation phenology and carbon -climate feedbacks in the warming world.