Intermittently wet meadows of the Molinion alliance, as with many other grasslands of high-nature value, have become increasingly exposed to abandonment due to their low economic value. The potential consequences of land abandonment are the decrease in species diversity and environmental alterations. The issue of land-use induced changes in plant species composition and soil physico-chemical parameters have been rarely studied in species-rich intermittently wet grasslands. In this study we attempt to i) to identify determinants of plant species composition patterns and ii) to investigate the effect of cessation of mowing on vegetation composition and soil properties. The study was conducted in an area of 36 ha covered with Molinion meadows, comprising of mown sites and sites that were left unmown for 10 years. In total, 120 and 80 vegetation plots were sampled from mown and unmown sites, respectively. In these plots we measured plant community composition and soil physico-chemical parameters. The results have shown that the two groups of variables (soil properties and management) differ considerably in their ability to explain variation in plant species data. Soil variables explained four-fold more variation in plant species composition than management did. The content of soil organic matter, moisture, total nitrogen and exchangeable forms of potassium, calcium and magnesium were significantly higher in mown than in unmown grassland systems. The results revealed that soil organic matter was the component of the soil most strongly affected by management, followed by moisture, magnesium, calcium and potassium in that order. Each of these soil parameters was negatively correlated with the abundances of woody plants and invasive species. We concluded that low-intensity, late time of mowing is suitable grassland management practice to ensure high plant species diversity and sustainability of the grassland ecological system while cessation of mowing not only lead to reduced plant species richness and diversity, but also to reduced nutrient levels in grassland soils.

The influence that different sampling methods have on the results and the interpretation of vegetation analysis has been much debated, but little is yet known about how the spatial arrangement of samples affect patterns of species composition and environment–vegetation relationships within the same vegetation type. We compared three data sets of the same sample size obtained by three standard sampling methods: preferential, random, and systematic. These different sampling methods were applied to a study area comprising of 36 ha of intermittently wet Molinia meadows. We compared the performance of the three methods under two management categories: managed (extensively mown) and unmanaged (abandoned for 10 years). A total of 285 vegetation-plots were sampled, with 95 plots recorded per sampling method. In preferential sampling, we sampled only patches of vegetation with an abundance of indicator species of the habitat type, while random and systematic plots were positioned independently from the researcher by using GIS. The effect of each sampling method on the patterns of species composition and species–environment relationships was explored by redundancy analysis and the significance of effects was tested by the randomization test. Preferential sampling revealed different patterns of species composition than random and systematic sampling methods. Random and systematic sampling methods have resulted in broader vegetation variability than with preferential sampling method. Preferential sampling revealed different relationship between soil parameters and species composition in contrast to random and systematic sampling methods. Although we have not found significant differences in vegetation–environment relationships between random and systematic sampling methods, random sampling revealed a more robust correlation of species data to soil factors than preferential and systematic sampling methods. Intentional restriction of vegetation variation sampled preferentially may be detrimental to statistical inference in studies of species composition patterns and vegetation–environment relationships.