Snow depthdata of Oberkainz, Schröckalm and Gscheidegg.

soil temperature data at different depths

Snow cover data of Oberkainz, Schröckalm and Gscheidegg.

Snow cover of meteorological Station Rudolfshütte

Snow depth of meteorological Station Rudolfshütte

The dataset provides information about the physical and chemical characteristics of the snowpack. Every year, a snow profile is open and sampled before the beginning of the melting season, close to the Istituto Scientifico Angelo Mosso (45°52'31.27"N, 7°52'17.09"E, elevation: 2900 m a.s.l.). Data are available for the years 2009 and 2010, and the period 2014-2020 (2016 was not analysed). Snow depth and density are measured, and snow water equivalent (SWE) is calculated. The analysed snow chemical parameters are: pH, electrical conductivity (EC), N-NH4, and N-NO3 (period 2009, 2010, 2014-2020); dissolved organic carbon (DOC), total dissolved nitrogen (TDN), and dissolved organic nitrogen (DON) (period 2014-2020); cations (Ca, Mg, Na, K) (years 2009, 2010, 2015); anions (S-SO4, N-NO2, P-PO4, Cl) (years 2009, 2010, 2015); trace elements (Al, Ba, Cd, Co, Cr, Cu, Fe, Mn, Ni, Pb, Rb, Si, Ti, V, Zn) (year 2015).

Dataset provides information about soil temperature, soil C and N dynamics at different sites in the alpine tundra, along an elevational gradient from 2500 to 2900 m asl during the period 2009-2019. Moreover, one snow profile was opened every year before snowpack isothermal condition (to avoid losses via ionic pulse). Nitrate stored in snowpack is rilevant on yearly ion balance.

Dataset provides information about soil temperature, soil C and N dynamics at different sites in the alpine tundra, along an elevational gradient from 2500 to 2900 m asl during the period 2005-2018. Moreover, one snow profile was opened every year before snowpack isothermal condition (to avoid losses via ionic pulse). Nitrate stored in snowpack is rilevant on yearly ion balance.

This dataset includes maps with NDSI values that come from Landsat 5 Surface Reflectance collection images available in Google Eath Engine. TIFF images cropped to a region of Lanjaron where different post-fire treatments were established are presented. This area was affected by a forest fire in September 2005. That is why NDSI values and binary layers are presented for two periods, before and after the fire (hese binary layers are generated based on a threshold of 0.35). Comparisons are made in three forest management treatments after the fire. These treatments were No Intervention (NI), Partial Court (PCL) and Salvage Logging (SL). This dataset also includes a grid with the sizes of the Landsat pixels that includes as information the treatment to which it belongs (column Trat_1). And a folder of outputs where each cell has an associated value of ancillary variables (such as elevation, slope, shadows) and another where they present the NDSI values extracted from the images of the dataset

Climate change scenarios suggest that subalpine forests in the Alps will be affected by a reduction of snow cover duration. Consequently, the alteration of pedoclimatic conditions could determine important consequences on soil nitrogen and carbon dynamics. In this study we consider the effects of snow cover duration (SCD) and pedoclimatic conditions on topsoil carbon and nitrogen cycling during the snow-free season along an altitudinal gradient (1550m-1900m asl) in NW Italian Alps (LTER site Mars). Three study sites under a Larch (Larix decidua) stand were instrumented with suction cup lysimeters and soil temperature and moisture sensors. Sampling and analysis are done monthly during the growing season.