Abstract

Abstract Understanding patterns of vascular plant diversity in managed temperate grasslands and the processes that determine them requires analyses at multiple spatial scales. In this study, we applied additive partitioning to plant species richness data of two contrasting management regimes (meadow vs. pasture) collected from a nested sampling design that consisted of two hierarchical scales. At the local scale, we quantified additive diversity components in 180 vegetation plots, and at the regional scale in 60 grassland parcels. Total observed regional species richness (γr) was partitioned into its additive components within (αl) and among vegetation plots (βl) and among grassland parcels (βr). We used the same approach in a comparison of common and infrequent plant species. Partitioning analyses revealed that the relative contributions of diversity components to total observed regional species richness changed as a function of spatial scale. We found that species richness among grassland parcels (βr) of both meadows and pastures contributed most to total observed regional species richness (γr) of all and infrequent plant species (up to 81% and 96%, respectively), whereas for common species only up to 51% of γr were attributable to species richness among grassland parcels (βr). To gain insight into the processes that may affect local patterns of species richness in grasslands, we analysed the observed local species diversity components with respect to management regime, nitrogen fertilisation and abiotic environmental factors (slope angle and soil quality). Our results show that grazing at a low-to-moderate stocking density promotes the β-diversity of all plant species at the local scale due to increased within-habitat heterogeneity. Low application rates of nitrogen fertilisers and abiotic environmental conditions such as steep slopes and soils with a low nutrient status generally benefited local species diversity components. We conclude that the observed patterns of plant species diversity are shaped by processes at multiple spatial scales.

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