Landscape effects on diversity of semi-natural grasslands

Abstract

We studied how the landscape structure (percentage cover and diversity of surrounding habitats) affects different components of species diversity (alpha, beta and gamma) of vascular plants in semi-natural grasslands in the Slovak Republic. We analyzed all grasslands combined as well as four main types delimited according to their position along a moisture gradient (xerophilous, sub-xerophilous, mesophilous and wet grasslands). We used grassland records stored in the Slovak Vegetation Database. The geographically stratified dataset included 3795 plots with 1221 species of vascular plants. Along with the total number of species in the vegetation plots, we considered the numbers of target grassland species, forest species, archaeophytes, neophytes and species with high fidelity to non-natural habitats. The landscape parameters based on CORINE land cover maps and the National Grassland Inventory, were calculated for plot neighbourhoods of 4km2. Spatially constrained rarefaction curves were constructed to examine how different diversity components behave with changing structure of the surrounding landscape. Our study revealed that alpha diversity was affected by both percentage cover and diversity of different habitats in the plot neighbourhood. It increased with increasing proportion or diversity of different natural and semi-natural habitats and decreased with increasing proportion or diversity of non-natural habitats in the surrounding landscape. Beta and gamma diversities showed opposite pattern to that of alpha diversity for most analyzed factors. Alpha diversity in sub-xerophilous and mesophilous grasslands was more susceptible to changes in landscape structure than alpha diversity in xerophilous or wet grasslands. Regression trees and linear or quadratic regression models revealed that in xerophilous or wet grasslands, high alpha diversity was best predicted by a high proportion of ecologically valuable grasslands in the surroundings. In sub-xerophilous and mesophilous grasslands, the best predictor was proportion of natural and semi-natural habitats followed by the proportion of non-natural habitats. The detected pattern regarding alpha, beta and gamma diversity calculated for grassland target species did not differ from the pattern for the whole species assemblage. However, the surrounding landscape affected the number, proportion and cover of species typical of forest or non-natural habitats (including alien species) in the plots. We explain the results by the interplay of two main mechanisms: species pool and spatial mass effects. In our study, the effect of species pool on alpha diversity was stronger than the spatial mass effect. Based on differences indicated in the responses of various grassland types to the surrounding landscape structure, we suggest adoption of community type specific conservation measures

Both local and landscape factors determine plant and Orthoptera diversity in the semi-natural grasslands of Transylvania, Romania

“…Increasing landscape heterogeneity, i.e., a greater richness and evenness of different habitat types, causes an increase in the potential pool of species available to colonise local sites, provided connectivity is adequate (Tscharntke et al 2012). This appears to be the case for overall plant species richness in this study, supporting the findings of Janišová et al (2013), which showed that plant species richness in Slovakian grasslands increased with increasing diversity of surrounding semi-natural habitats. Particularly the characteristic grassland plant species in this study reacted strongly to landscape heterogeneity.…”

“…The relationships of both plant and Orthoptera to landscape factors is in contrast to the findings of Marini et al (2008), who found no effect of landscape factors on plants, but a significant effect on Orthoptera. Generally, the findings in the literature regarding landscape effects on grassland plant communities are mixed, providing both evidence for (e.g., Söderström et al 2001;Ö ckinger et al 2012;Reitalu et al 2012;Schmucki et al 2012;Janišová et al 2013) and against (e.g., Dauber et al 2003;Krauss et al 2004;Löbel et al 2006;Ö ster et al 2007;Jonason et al 2011). This may be a result of the overriding effects of local factors in some of the investigated grasslands (Dauber et al 2003;Marini et al 2008), which would not have been the case in the low-nutrient semi-natural grasslands in this study.…”

“…The majority of these studies have focused on animal responses (Prevedello and Vieira 2010), however, an increasing number of studies have also shown responses in sessile organisms such as vascular plants (e.g., Ö ckinger et al 2012;Reitalu et al 2012;Schmucki et al 2012;Janišová et al 2013). The properties of the surrounding landscape can significantly affect local species richness and composition in habitat patches through a number of mechanisms.…”

“…Despite several recent landscape-scale studies from Eastern Europe (e.g., Batáry et al 2007b;Aavik et al 2008;K} orösi et al 2012;Janišová et al 2013), there is still relatively little evidence on species responses at this scale in the large areas of low-intensity farmland in eastern countries such as Romania. Several studies suggest that species responses are highly context dependent and can differ between regions, especially between the extensive farmland often found in Eastern Europe and the more intensively studied, and farmed, areas of Western Europe Reif et al 2011;Tryjanowski et al 2011;Szymkowiak et al 2014).…”

Analysing Data of the Integrated Administration and Control System (IACS) to Detect Patterns of Agricultural Land-Use Change at Municipality Level

“…In order to find the 'best' number of clusters, v-fold cross validation was performed (Janisová et al 2014;Flanagan & Cerrato 2015;Gumienna et al 2016). The benefit of v-fold cross validation is that the number of clusters will be determined from the data and must not be known a priori which means prior knowledge about the number of clusters is not essential.…”