Abstract

Vegetation types confi ned to calcareous bedrocks are often characterized by high species richness, and rare and red- listed plants occur frequently. Snow depth and duration are of particular importance for the fl oristic composition of mountain vegetation and we therefore wanted to quantify the importance of the date of snowmelt and thereby discuss possible effects of future climate change. In two mountain areas with calcium-rich bedrocks, 106 sample plots (2 x 2 m) were selected by a stratifi ed random sampling, to cover a broad range of snow cover, topography and vegetation composition. Study plots include both the northern boreal zone (NB), the low alpine zone (LA), and the middle alpine zone (MA). Soil data, soil temperature and day of snowmelt were sampled from all plots. Fifteen vegetation (cluster) types were classifi ed by the use of TWINSPAN, and these were well separated in a DCA (Detrended Correspondence Analysis) ordination. A CVA (Canonical Variates Analysis) and Monte Carlo Permutation tests showed that the vegetation types were signifi cantly associated with most of the measured environmental variables, with relative altitude, potassium, and Julian day of snowmelt as the most important variables. All study plots showed relatively high values for soil richness and were signifi cantly negatively correlated with the Julian day when the soil temperature threshold (6 °C) was reached. The signifi cant relationships between altitude, Julian day of snowmelt, and vegetation composition indicate that major changes may be expected as a consequence of an earlier snowmelt in a warmer world.

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