Conservation and diversity of Palaearctic grasslands – Editorial to the 5th EDGG special issue in Hacquetia

Non peer reviewe

Drivers of plant diversity in Bulgarian dry grasslands vary across spatial scales and functional-taxonomic groups

Questions: Studying dry grasslands in a previously unexplored region, we asked: (a) which environmental factors drive the diversity patterns in vegetation; (b) are taxonomic groups (vascular plants, bryophytes, lichens) and functional vascular plant groups differently affected; and (c) how is fine-grain beta diversity affected by environmental drivers? Location: Northwestern and Central Bulgaria. Methods: We sampled environmental data and vascular plant, terricolous bryophyte and lichen species in 97 10-m2 plots and 15 nested-plot series with seven grain sizes (0.0001–100 m2) of ten grassland sites within the two regions. We used species richness as measure of alpha-diversity and the z-value of the power-law species–area relationship as measure of beta-diversity. We analysed effects of landscape, topographic, soil and land-use variables on the species richness of the different taxonomic and functional groups. We applied generalised linear models (GLMs) or, in the presence of spatial autocorrelation, generalised linear mixed-effect models (GLMMs) in a multi-model inference framework. Results: The main factors affecting total and vascular plant species richness in 10-m2 plots were soil pH (unimodal) and inclination (negative). Species richness of bryophytes was positively affected by rock cover, sand proportion and negatively by inclination. Inclination and litter cover were also negative predictors of lichen species richness. Elevation negatively affected phanerophyte and therophyte richness, but positively that of cryptophytes. A major part of unexplained variance in species richness was associated with the grassland site. The z-values for total richness showed a positive relationship with elevation and inclination. Conclusions: Environmental factors shaping richness patterns strongly differed among taxonomic groups, functional vascular plant groups and spatial scales. The disparities between our and previous findings suggest that many drivers of biodiversity cannot be generalised but rather depend on the regional context. The large unexplained variance at the site level calls for considering more site-related factors such as land-use history

GrassPlot v. 2.00 – first update on the database of multi-scale plant diversity in Palaearctic grasslands

Abstract: GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). Following a previous Long Database Report (Dengler et al. 2018, Phyto- coenologia 48, 331–347), we provide here the first update on content and functionality of GrassPlot. The current version (GrassPlot v. 2.00) contains a total of 190,673 plots of different grain sizes across 28,171 independent plots, with 4,654 nested-plot series including at least four grain sizes. The database has improved its content as well as its functionality, including addition and harmonization of header data (land use, information on nestedness, structure and ecology) and preparation of species composition data. Currently, GrassPlot data are intensively used for broad-scale analyses of different aspects of alpha and beta diversity in grassland ecosystems

GrassPlot - a database of multi-scale plant diversity in Palaearctic grasslands

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (releves) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001;... 1,000 m(2)) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database " sPlot". Its main aim is to facilitate studies on the scale-and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board

Conservation and diversity of Palaearctic grasslands – Editorial to the 5th EDGG special issue in Hacquetia

Palaearctic grasslands are diverse and dynamic ecosystems that are in the focus of ecology, conservation biology and agronomy. This special issue is dedicated to the biodiversity and conservation issues of Palaearctic grasslands and was initiated by the Eurasian Dry Grassland Group members attending the 14th Eurasian Dry Grassland Conference (EDGC) at Sulmona, Italy in 2018. The papers in this special issue cover a wide range of grassland ecosystems from mountain dry grasslands to lowland loess grasslands, feathergrass steppes and wet grasslands, and focus on the biodiversity values and conservation issues of Palaearctic grasslands. We believe that this compilation will contribute to a better understanding of the ecology of grasslands and support their more effective conservation

Wagner et al. 2016. R scripts and data

Data and R scripts analyze how species shifts in soil pH niche parameter (optimum, width) are linked to regional changes in mean precipitation, substrate availability and species traits indicative of competitive ability.<br><br>Requirement: R (https://www.r-project.org/) and R packages (see scripts for further specifications)<br><br>Data structure is explained in the R scripts.<br

Fine-grain beta diversity of Palaearctic grassland vegetation

Questions: Which environmental factors influence fine-grain beta diversity of vegetation and do they vary among taxonomic groups? Location: Palaearctic biogeographic realm. Methods: We extracted 4,654 nested-plot series with at least four different grain sizes between 0.0001 m² and 1,024 m² from the GrassPlot database, covering a wide range of different grassland and other open habitat types. We derived extensive environmental and structural information for these series. For each series and four taxonomic groups (vascular plants, bryophytes, lichens, all), we calculated the slope parameter (z-value) of the power law species–area relationship (SAR), as a beta diversity measure. We tested whether z-values differed among taxonomic groups and with respect to biogeographic gradients (latitude, elevation, macroclimate), ecological (site) characteristics (several stress–productivity, disturbance and heterogeneity measures, including land use) and alpha diversity (c-value of the power law SAR). Results: Mean z-values were highest for lichens, intermediate for vascular plants and lowest for bryophytes. Bivariate regressions of z-values against environmental variables had rather low predictive power (mean R² = 0.07 for vascular plants, less for other taxa). For vascular plants, the strongest predictors of z-values were herb layer cover (negative), elevation (positive), rock and stone cover (positive) and the c-value (U-shaped). All tested metrics related to land use (fertilization, livestock grazing, mowing, burning, decrease in naturalness) led to a decrease in z-values. Other predictors had little or no impact on z-values. The patterns for bryophytes, lichens and all taxa combined were similar but weaker than those for vascular plants. Conclusions: We conclude that productivity has negative and heterogeneity positive effects on z-values, while the effect of disturbance varies depending on type and intensity. These patterns and the differences among taxonomic groups can be explained via the effects of these drivers on the mean occupancy of species, which is mathematically linked to beta diversity

Fine‐grain beta diversity of Palaearctic grassland vegetation

Questions Which environmental factors influence fine-grain beta diversity of vegetation and do they vary among taxonomic groups? Location Palaearctic biogeographic realm. Methods We extracted 4,654 nested-plot series with at least four different grain sizes between 0.0001 m2 and 1,024 m2 from the GrassPlot database, covering a wide range of different grassland and other open habitat types. We derived extensive environmental and structural information for these series. For each series and four taxonomic groups (vascular plants, bryophytes, lichens, all), we calculated the slope parameter (z-value) of the power-law species–area relationship (SAR), as a beta diversity measure. We tested whether z-values differed among taxonomic groups and with respect to biogeographic gradients (latitude, elevation, macroclimate), ecological (site) characteristics (several stress-productivity, disturbance and heterogeneity measures, including land use) and alpha diversity (c-value of the power-law SAR). Results Mean z-values were highest for lichens, intermediate for vascular plants and lowest for bryophytes. Bivariate regressions of z-values against environmental variables had rather low predictive power (mean R2 = 0.07 for vascular plants, less for other taxa). For vascular plants, the strongest predictors of z-values were herb layer cover (negative), elevation (positive), rock and stone cover (positive) and the c-value (u-shaped). All tested metrics related to land use (fertilisation, livestock grazing, mowing, burning, decrease in naturalness) led to a decrease in z-values. Other predictors had little or no impact on z-values. The patterns for bryophytes, lichens and all taxa combined were similar but weaker than those for vascular plants. Main conclusions We conclude that productivity has negative and heterogeneity positive effects on z-values, while the effect of disturbance varies depending on type and intensity. These patterns and the differences among taxonomic groups can be explained via the effects of these drivers on the mean occupancy of species, which is mathematically linked to beta diversity