Temporal and small-scale spatial variation in grassland productivity, biomass quality, and nutrient limitation

Characterization of spatial and temporal variation in grassland productivity and nutrition is crucial for a comprehensive understanding of ecosystem function. Although within-site heterogeneity in soil and plant properties has been shown to be relevant for plant community stability, spatiotemporal variability in these factors is still understudied in temperate grasslands. Our study aimed to detect if soil characteristics and plant diversity could explain observed small-scale spatial and temporal variability in grassland productivity, biomass nutrient concentrations, and nutrient limitation. Therefore, we sampled 360 plots of 20 cm × 20 cm each at six consecutive dates in an unfertilized grassland in Southern Germany. Nutrient limitation was estimated using nutrient ratios in plant biomass. Absolute values of, and spatial variability in, productivity, biomass nutrient concentrations, and nutrient limitation were strongly associated with sampling date. In April, spatial heterogeneity was high and most plots showed phosphorous deficiency, while later in the season nitrogen was the major limiting nutrient. Additionally, a small significant positive association between plant diversity and biomass phosphorus concentrations was observed, but should be tested in more detail. We discuss how low biological activity e.g., of soil microbial organisms might have influenced observed heterogeneity of plant nutrition in early spring in combination with reduced active acquisition of soil resources by plants. These early-season conditions are particularly relevant for future studies as they differ substantially from more thoroughly studied later season conditions. Our study underlines the importance of considering small spatial scales and temporal variability to better elucidate mechanisms of ecosystem functioning and plant community assembly

Above- and belowground biodiversity jointly tighten the P cycle in agricultural grasslands

Experiments showed that biodiversity increases grassland productivity and nutrient exploitation, potentially reducing fertiliser needs. Enhancing biodiversity could improve P-use efficiency of grasslands, which is beneficial given that rock-derived P fertilisers are expected to become scarce in the future. Here, we show in a biodiversity experiment that more diverse plant communities were able to exploit P resources more completely than less diverse ones. In the agricultural grasslands that we studied, management effects either overruled or modified the driving role of plant diversity observed in the biodiversity experiment. Nevertheless, we show that greater above- (plants) and belowground (mycorrhizal fungi) biodiversity contributed to tightening the P cycle in agricultural grasslands, as reduced management intensity and the associated increased biodiversity fostered the exploitation of P resources. Our results demonstrate that promoting a high above- and belowground biodiversity has ecological (biodiversity protection) and economical (fertiliser savings) benefits. Such win-win situations for farmers and biodiversity are crucial to convince farmers of the benefits of biodiversity and thus counteract global biodiversity loss

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

Mapping species richness of plant families in European vegetation

Aims: Biodiversity is traditionally studied mostly at the species level, but biogeographical and macroecological studies at higher taxonomic levels can provide valuable insights into the evolutionary processes at large spatial scales. Our aim was to assess the representation of vascular plant families within different vegetation formations across Europe. Location: Europe. Methods: We used a data set of 816,005 vegetation plots from the European Vegetation Archive (EVA). For each plot, we calculated the relative species richness of each plant family as the number of species belonging to that family divided by the total number of species. We mapped the relative species richness, averaged across all plots in 50 km × 50 km grid cells, for each family and broad habitat groups: forests, grasslands, scrub and wetlands. We also calculated the absolute species richness and the Shannon diversity index for each family. Results: We produced 522 maps of mean relative species richness for a total of 152 vascular plant families occurring in forests, grasslands, scrub and wetlands. We found distinct spatial patterns for many combinations of families and habitat groups. The resulting series of 522 maps is freely available, both as images and GIS layers. Conclusions: The distinct spatial patterns revealed in the maps suggest that the relative species richness of plant families at the community level reflects the evolutionary history of individual families. We believe that the maps and associated data can inspire further biogeographical and macroecological studies and strengthen the ongoing integration of phylogenetic, functional and taxonomic diversity concepts.MV, IA, JPC, ZL, IK, AJ and MC were funded by the Czech Science Foundation, programme EXPRO (project no. 19-28491X); JDi by the Czech Science Foundation (18-02773S); IB and JAC by the Basque Government (IT936-16); AČ by the Slovenian Research Agency (ARRS, P1-0236); AK by the National Research Foundation of Ukraine (project no. 2020.01/0140); JŠ by the Slovak Research and Development Agency (APVV 16-0431); KV by the National Science Fund (Contract DCOST 01/7/19.10.2018)

Evaluating model outputs using integrated global speleothem records of climate change since the last glacial

Although quantitative isotopic data from speleothems has been used to evaluate isotope-enabled model simulations, currently no consensus exists regarding the most appropriate methodology through which to achieve this. A number of modelling groups will be running isotope-enabled palaeoclimate simulations in the framework of the Coupled Model Intercomparison Project Phase 6, so it is timely to evaluate different approaches to use the speleothem data for data-model comparisons. Here, we illustrate this using 456 globally-distributed speleothem δ18O records from an updated version of the Speleothem Isotopes Synthesis and Analysis (SISAL) database and palaeoclimate simulations generated using the ECHAM5-wiso isotope-enabled atmospheric circulation model. We show that the SISAL records reproduce the first-order spatial patterns of isotopic variability in the modern day, strongly supporting the application of this dataset for evaluating model-derived isotope variability into the past. However, the discontinuous nature of many speleothem records complicates procuring large numbers of records if data-model comparisons are made using the traditional approach of comparing anomalies between a control period and a given palaeoclimate experiment. To circumvent this issue, we illustrate techniques through which the absolute isotopic values during any time period could be used for model evaluation. Specifically, we show that speleothem isotope records allow an assessment of a model’s ability to simulate spatial isotopic trends. Our analyses provide a protocol for using speleothem isotopic data for model evaluation, including screening the observations to take into account the impact of speleothem mineralogy on 18O values, the optimum period for the modern observational baseline, and the selection of an appropriate time-window for creating means of the isotope data for palaeo time slices

EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

Aim: The EUNIS Habitat Classification is a widely used reference framework for European habitat types (habitats), but it lacks formal definitions of individual habitats that would enable their unequivocal identification. Our goal was to develop a tool for assigning vegetation‐plot records to the habitats of the EUNIS system, use it to classify a European vegetation‐plot database, and compile statistically‐derived characteristic species combinations and distribution maps for these habitats. Location: Europe. Methods: We developed the classification expert system EUNIS‐ESy, which contains definitions of individual EUNIS habitats based on their species composition and geographic location. Each habitat was formally defined as a formula in a computer language combining algebraic and set‐theoretic concepts with formal logical operators. We applied this expert system to classify 1,261,373 vegetation plots from the European Vegetation Archive (EVA) and other databases. Then we determined diagnostic, constant and dominant species for each habitat by calculating species‐to‐habitat fidelity and constancy (occurrence frequency) in the classified data set. Finally, we mapped the plot locations for each habitat. Results: Formal definitions were developed for 199 habitats at Level 3 of the EUNIS hierarchy, including 25 coastal, 18 wetland, 55 grassland, 43 shrubland, 46 forest and 12 man‐made habitats. The expert system classified 1,125,121 vegetation plots to these habitat groups and 73,188 to other habitats, while 63,064 plots remained unclassified or were classified to more than one habitat. Data on each habitat were summarized in factsheets containing habitat description, distribution map, corresponding syntaxa and characteristic species combination. Conclusions: EUNIS habitats were characterized for the first time in terms of their species composition and distribution, based on a classification of a European database of vegetation plots using the newly developed electronic expert system EUNIS‐ESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment

Intransitive competition is common across five major taxonomic groups and is driven by productivity, competitive rank and functional traits

1. Competition can be fully hierarchical or intransitive, and this degree of hierarchy is driven by multiple factors, including environmental conditions, the functional traits of the species involved or the topology of competition networks. Studies simultaneously analysing these drivers of competition hierarchy are rare. Additionally, organisms compete either directly or via interference competition for resources or space, within a local neighbourhood or across the habitat. Therefore, the drivers of competition could change accordingly and depend on the taxa studied. 2. We performed the first multi-taxon study on pairwise competition across major taxonomic groups, including experiments with vascular plants, mosses, saprobic fungi, aquatic protists and soil bacteria. We evaluated how general is competition intransitivity from the pairwise competition matrix including all species and also for each possible three-species combination (triplets). We then examined which species were likely to engage in competitive loops and the effects of environmental conditions, competitive rank and functional traits on intransitive competition. 3. We found some degree of competition intransitivity in all taxa studied, with 38% to 5% of triplets being intransitive. Variance in competitive rank between species and more fertile conditions strongly reduced intransitivity, with triplets composed of species differing widely in their competitive ranks much less likely to be intransitive. 4. Including functional traits of the species involved more than doubled the variation explained compared to models including competitive rank only. Both trait means and variance within triplets affected the odds of them being intransitive. However, the traits responsible and the direction of trait effects varied widely between taxa, suggesting that traits can have a wide variety of effects on competition. 5. Synthesis. We evaluated the drivers of competition across multiple taxa and showed that productivity and competitive rank are fundamental drivers of intransitivity. We also showed that not only the functional traits of each species, but also those of the accompanying species, determine competition intransitivity. Intransitive competition is common across multiple taxa but can dampen under fertile conditions or for those species with large variance in their competitive abilities. This provides a first step towards predicting the prevalence of intransitive competition in natural communities.TRY is currently supported by DIVERSITAS/Future Earth and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. S.S. was supported by the Spanish Government under a Ramón y Cajal contract (RYC-2016-20604). A.L. and M.C.R. acknowledge funding from Deutsche Forschungsgemeinschaft (DFG, grant no: RI 1815/16-1). F.A. has been supported by the Swiss National Science Foundation (grants no. 31003A_135622 and PP00P3_150698). M.D.-B. acknowledges support from the Marie Sklodowska-Curie Actions of the Horizon 2020 Framework Program H2020-MSCA-IF-2016 under REA grant agreement no. 702057. E.A. received financial support from the Swiss National Science Foundation (grant number 31003A_160212). S.B., E.A. and S.S. were partly funded by the DFG Priority Program 1374 “Infrastructure-Biodiversity-Exploratories” (Fi-1246/6-1). Fieldwork permits were issued by the responsible state environmental offices of Baden-Württemberg. B.K.S. is supported by Australian Research Council (DP170104634)