Soil properties and plant phenology in snowbed communities (NW- Italian Alps)

A long-lasting, thick snow cover and a relatively high humidity and low temperatures characterize snowbed communities, which are thus particularly sensitive to climate change. In a warming climate, changes in precipitation and temperature will likely lead to shorter snow-covered periods. This will modify soil temperatures, water and nutrient fluxes during the snow-free season, causing modifications in plant phenology and increased colonization by alpine grassland species. Considering the high vulnerability of snowbed areas to climate change, during a four-year monitoring, we studied the floristic composition, phenology and soil C and N dynamics of snowbed communities, evaluating, among climatic, pedoclimatic and vegetation variables, the main drivers acting on soil C and N forms in these high-elevation ecosystems. The research was carried out at the LTER Site Angelo Mosso Scientific Institute, located in the Western Italian Alps, close to the Monte Rosa Massif (4634 m a.s.l.). The work was performed on 8 permanent snowbed plots located between 2686 and 2850 m a.s.l, characterized by skeletic Dystric Regosol, Skeletic Umbrisol, and Skeletic Dystric Cambisol, according to WRB classification (2015). The results indicated that soil water content, snow melt-out day, and duration of soil freezing were the main abiotic factors driving soil C and N dynamics. Greater soil water content and delayed melt-out day increased N-NH4+, N-NO3–, DOC, TDN, Nmicr, Cmicr and C:Nmicr ratio, while the duration of soil freezing increased DON and TDN. Considering the vegetation variables, the phenology of Salix herbacea played a fundamental role, reducing N-NH4+ and increasing DOC concentrations in soil, revealing a strong plant-soil relationship. The predicted changes in the amount, timing of snowfall and melt-out day, coupled with increased air temperature, might alter the biogeochemical cycles and phenology dynamics of snowbed communities, which can be considered an ideal natural sentry to detect the effect of climate change on high-elevation ecosystems. Thus, the monitoring of selected site-specific indexes could represent a useful tool to detect the effects of climate change in the framework of long-term ecological research efforts.