International Journal of Molecular Ecology and Conservation, 2025, Vol.15, No.6, 277-285 http://ecoevopublisher.com/index.php/ijmec 282 participate in ecological processes such as nutrient mineralization, carbon conversion and organic matter decomposition. The adiabatic effect of snow cover protects microbial communities from extreme low temperatures and helps maintain soil ecological functions in winter (Irannezhad et al., 2022). The snowmelt period is the peak stage of microbial activity. A large amount of nutrients are released into the soil, forming the "spring pulse effect", which affects the initial nutrient absorption and carbon cycle rate of vegetation. The reduction of snow cover may lead to frequent freeze-thaw cycles in the soil, damaging the extracellular enzymes of microorganisms and altering the structure of the microbial community, thereby affecting long-term soil fertility. Therefore, snow cover changes not only affect plants and animals, but also profoundly reshape the surface microhabitat and soil ecological processes. 5 Snow cover Changes and Ecosystem Responses 5.1 Spatio-temporal Variation trends of snow cover caused by climate warming Global warming is transforming snowfall into rainfall, shortening the period of snow accumulation and advancing the melting period. Long-term observations show that the snow cover thickness in the Arctic region increases regionally in winter, while the duration of snow cover in spring significantly shortens, forming a compound change of "thickening - early melting". In mountainous areas, it is generally manifested as a decrease in snow water equivalent and a shortening of the snow cover period (Notarnicola, 2020). In addition, abnormal atmospheric circulation and an increase in extreme events have made snow cover changes highly unstable, such as the frequent warm winter events in Europe and America. Snow cover changes are accelerating and the spatial differences are significant. Future prediction models generally suggest that the probability of continuous snow cover reduction in the middle and late 21st century is extremely high (Tang et al., 2022). 5.2 Ecosystem effects The ecosystem effects of snow cover changes are mainly reflected in the following three aspects: The premature melting of snow cover leads to the forward green-up period of vegetation, which may cause phenological mismatch between plants and pollinating insects (Arndt et al., 2020; Mitterwallner et al., 2024). Some tundra and mountain plants are highly dependent on snow cover. If the snow becomes thinner, they may be more vulnerable to frost damage. The thinning of the space under the snow makes it easier for rodents to be preyed upon, affecting the entire structure of the predation web. The migration routes of large animals may change. For instance, North American elk have shortened their migration distances due to reduced snow cover. The early melting of snow and the change in the flow process will increase the risk of spring floods and aggravate summer droughts. These changes have profound impacts on agriculture, urban water supply, hydropower and ecological wetlands (Pedron et al., 2023; Richardson et al., 2024). 5.3 Cross-ecosystem effects Snow cover changes produce significant cross-system linkage effects, mainly manifested in the coupled feedback of land, hydrology and atmosphere. A reduction in snow cover will accelerate the degradation of permafrost, loosen the soil structure, increase the sand-carrying capacity of runoff, and affect the sedimentation process of rivers. The melting snow has prematurely altered the growth rhythm of primary producers in rivers, leading to a decline in wetland water levels and a reduction in waterbird habitats. The decline in albedo will increase surface warming, making the regional climate warmer and drier, and further reducing snow cover. This cross-system chain effect makes snow cover changes have the potential to amplify overall ecological risks (Arndt et al., 2020; Pedron et al., 2023). 6 Management and Protection of Snow Cover Ecosystems 6.1 Monitoring and model prediction Modern snow cover monitoring relies on the fusion of multi-source data such as satellite remote sensing, ground stations and unmanned aerial vehicle observations. Widely used products include MODIS, Sentinel-1/2 and multi-angle passive microwave data, which can provide key parameters such as snow cover area, albedo and water equivalent.
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