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Due to decades of loss of grassland diversity across Europe, there is a need to identify factors affecting species composition and diversity in managed meadows. The aim of the current study was to assess how ecological, landscape and management factors may affect plant species composition, biodiversity and forage value in Alpine hay meadows. Species composition, Shannon index and forage value were obtained from phytosociological relevés. Twenty explanatory variables were selected from a set of ecological, landscape and management factors. Their effects on plant species composition, Shannon index and forage value were analysed by applying the variation partitioning approach. Plant species composition was related to sixteen factors, explaining 35·6% of the variability. Shannon index and forage value were related to eleven factors, explaining 47·8 and 40·8% of their total variation respectively. Ecological factors were the main set explaining species composition and diversity, whereas none of the three individual groups of factors (ecological, landscape, management) significantly explained variability within forage value. Overall, the effects of the three groups of factors accounted for 70% of the total variability in plant species composition, but less than half that of Shannon index and of forage value. © 2012 John Wiley & Sons Ltd.

The loss of permanent meadows in the lowlands of the European Alps due to land use/land cover changes is a major underestimated process, which affects the status of these habitats and their provision of ecosystem services. In the Italian Valtellina valley (80km2) change detection analysis estimated meadows loss and spatial bivariate analysis and GIS-based logistic regression model analysed the spatial environmental drivers behind meadows loss in the period 1980-2000. A strong decrease in meadows (-18.5%) was found, in a context of agricultural land decrease and human settlements increase. This was the land cover type with highest loss and conversion rate during the study period. Meadows were converted to human settlements (urban, industrial and roads), other agriculture uses (cultivation, orchard, vineyard), bushland and uncultivated land. Meadows loss occurred mainly in soils with good land capability, low slope, exposed to south and in proximity of roads, urban settlements and bushland. Densities of urban, industrial and bushland and land capability were the only significant drivers for meadows loss, while distance to meadow edge, meadows density, distance to roads and soil degradation were the only significant drivers for meadows preservation. The conflict by land in locations densely occupied by other land cover types with good land capability is the major threat to meadows and avoidance of fragmentation may be a good strategy for its preservation. The meadows habitat needs a well-designed landscape and farming planning, which should account the economic value of the ecosystem services provided by this habitat.

The potential of field hyperspectral remote sensing data for non-destructive assessment of hay meadow biomass and vascular plant diversity has been investigated. Spectrometric and agronomic data were acquired at peak biomass over 34 sites distributed at diverse elevation and slopes over an area of 220 km2 in the Central Alps (Valtellina, Northern Italy). Different modelling approaches were tested to evaluate the predictive performance of spectral measurements: (i) the use of two band ratios of reflectance as input in ordinary least square regression models and (ii) the use of all reflectance bands as input in multivariate partial least square regression models. Each model was subjected to leave-one-out cross-validation and evaluated using the cross-validated coefficient of determination and the root mean square error. Fresh biomass and fuel moisture content were predicted with an average error of