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Semi‐natural lowland and mountain mesic meadows are grasslands rich in species, and their conservation status depends on treatments such as mowing or grazing livestock. In many countries, the condition of grasslands is deteriorating because of their inappropriate use or abandonment. This study aimed to determine the effects of the species composition of plant communities and functional plant groups on the methane yield from biomass harvested from mesic grasslands in the Sudetes Mountains. Biogas potential analysis was performed based on biomass samples collected from Poland and the Czech Republic. The biogas potential was determined in 40 day‐long batch anaerobic digestion tests. The average methane yield obtained from the biomass was 246 ± 16 NL CH4 kg−1 VS, whereas the methane yield per hectare was 870 ± 203 m3 CH4 ha−1. Plant communities comprising different dominant species had no effect on the methane yield but affected the methane yield per hectare. Additionally, the species composition of grasslands with a higher percentage of forbs had lower biomass yield, resulting in lower methane yields per hectare. The continuity of the low‐intensity management of mountain grassland, which can be provided by the utilization of their biomass for bioenergy production, sustains high biodiversity and ensures appropriate meadow conservation. [ABSTRACT FROM AUTHOR]

Aims: River gravel bars are endangered habitats in Europe. However, classification schemes of their vegetation and habitat types differ among European countries, and they are even ignored in some national schemes. This causes problems in conservation planning, monitoring and management. Hence we aimed at building the first unified vegetation classification for river gravel‐bar habitats across European mountain systems. Location: Europe. Methods: In total 4,769 vegetation plot records of river gravel‐bar plant communities were collected from national, regional or private databases, digitized from the literature and newly collected in the field. A hierarchical classification expert system with formal definitions of vegetation types was created. The definitions combined the criteria of presence or cover of groups of species with similar ecology or single species narrowly specialized to a particular gravel‐bar habitat. The TWINSPAN classification was applied to early‐successional vegetation types to check whether the classification based on formal definitions was supported by the results of unsupervised classification. Similarity patterns among vegetation types were visualized using the detrended correspondence analysis (DCA) ordination. Results: Early‐successional and scrub gravel‐bar vegetation types were respectively classified into two classes: Thlaspietea rotundifolii and Salicetea purpureae. Eleven associations and four alliances (Calamagrostion pseudophragmitae, Epilobion fleischeri, Salicion cantabricae and Salicion eleagno‐daphnoidis) were defined formally. Based on a critical revision, some associations or alliances defined in the previous literature were merged or discarded. The main gradient in variability within the gravel‐bar vegetation is connected with the altitudinal gradient, biogeographical variation, local hydromorphological processes and various successional changes. Conclusions: The first unified and formalized classification system of the European mountain river gravel‐bar vegetation was created, and species composition, ecology and distribution of these types were characterized. The syntaxonomical nomenclature of these types was checked and revised. This study provides a base for conservation planning of these threatened and rapidly disappearing habitats. [ABSTRACT FROM AUTHOR]

Aims: To create a comprehensive, consistent and unequivocal phytosociological classification of European marsh vegetation of the class Phragmito‐Magnocaricetea. Location: Europe. Methods: We applied the Cocktail method to a European data set of 249,800 vegetation plots. We identified the main purposes and attributes on which to base the classification, defined assignment rules for vegetation plots, and prepared formal definitions for all the associations, alliances and orders of the class Phragmito‐Magnocaricetea using formal logic. Each formula consists of the combination of "functional species groups", cover values of individual species, and in the case of high‐rank syntaxa also of "discriminating species groups" created using the Group Improvement (GRIMP) method. Results: The European Phragmito‐Magnocaricetea vegetation was classified into 92 associations grouped in 11 alliances and six orders. New syntaxa (previously invalidly published according to the International Code of Phytosociological Nomenclature) were introduced: Bolboschoeno maritimi‐Schoenoplection tabernaemontani, Glycerio maximae‐Sietum latifolii, Glycerio notatae‐Veronicetum beccabungae, Schoenoplectetum corymbosi and Thelypterido palustris‐Caricetum elongatae. Based on a critical revision, some other syntaxa were rejected or excluded from the class Phragmito‐Magnocaricetea. Conclusions: This work provides the first consistent classification of the class Phragmito‐Magnocaricetea at the European scale, which is an important tool for nature conservation. Our classification largely respects previously existing concepts of syntaxa, but it also proposes modifications to the recently published EuroVegChecklist. This work also provides a protocol that can be used for extending the current classification to new syntaxa and geographical regions. [ABSTRACT FROM AUTHOR]

Questions: What vegetation types can be distinguished on the basis of plant functional traits using numerical classification? How do they match syntaxonomical units? Location: Poland. Methods: Six thousand nine hundred and eighty‐five vegetation plots representing mesic and wet grasslands (Molinio‐Arrhenatheretea, Polygono‐Poetea) were retrieved from the Polish Vegetation Database. Plant functional trait data were assembled from the LEDA and Clo‐Pla databases for most species occurring in the data set. Community‐weighted mean for five traits were calculated for each plot: specific leaf area, canopy height, seed mass, bud bank index and clonality index. Plots were classified using Ward's method and iterative relocation based on silhouette widths. The clusters were interpreted and characterized on the basis of species and trait composition, functional diversity, functional redundancy, Ellenberg indicator values, and geographical distribution. The similarity between the trait‐based classification and the syntaxonomical assignment of plots is evaluated both statistically and by expert knowledge. Results: Twelve clusters were distinguished. The classification mirrored the main gradients structuring grasslands in Poland, although, some vegetation types with the strong dominance of functionally unique species appeared more distinct than they are treated in syntaxonomy. Clusters did not differ significantly in functional diversity and redundancy. The differences of clusters in species and trait composition and environmental background are discussed. Conclusion: The application of trait data and numerical methods is a promising approach for obtaining vegetation classifications. Such classifications can be in closer relationship with the most important ecosystem processes than floristic classifications because communities comprising different species but similar functional trait distribution are not separated. Trait‐based classifications match phytosociological units to a variable degree. Functional uniqueness and variation of abundance determines how individual species influence the delimitation of vegetation types using our approach. [ABSTRACT FROM AUTHOR]

Aim: The former continental‐scale studies modelled coarse‐grained plant species‐richness patterns (gamma diversity). Here we aim to refine this information for European forests by (a) modelling the number of vascular plant species that co‐occur in local communities (alpha diversity) within spatial units of 400 m2; and (b) assessing the factors likely determining the observed spatial patterns in alpha diversity. Location: Europe roughly within 12°W–30°E and 35–60°N. Taxon: Vascular plants. Methods: The numbers of co‐occurring vascular plant species were counted in 73,134 georeferenced vegetation plots. Each plot was classified by an expert system into deciduous broadleaf, coniferous or sclerophyllous forest. Random Forest models were used to map and explain spatial patterns in alpha diversity for each forest type separately using 19 environmental, land‐use and historical variables. Results: Our models explained from 51.0% to 70.9% of the variation in forest alpha diversity. The modelled alpha‐diversity pattern was dominated by a marked gradient from species‐poor north‐western to species‐rich south‐eastern Europe. The most prominent richness hotspots were identified in the Calcareous Alps and adjacent north‐western Dinarides, the Carpathian foothills in Romania and the Western Carpathians in Slovakia. Energy‐related factors, bedrock types and terrain ruggedness were identified as the main variables underlying the observed richness patterns. Alpha diversity increases especially with temperature seasonality in deciduous broadleaf forests, on limestone bedrock in coniferous forests and in areas with low annual actual evapotranspiration in sclerophyllous forests. Main conclusions: We provide the first predictive maps and analyses of environmental factors driving the alpha diversity of vascular plants across European forests. Such information is important for the general understanding of European biodiversity. This study also demonstrates a high potential of vegetation‐plot databases as sources for robust estimation of the number of vascular plant species that co‐occur at fine spatial grains across large areas. [ABSTRACT FROM AUTHOR]

Abstract: Aim: We investigate whether (1) environmental predictors allow to delineate the distribution of discrete community types at the continental scale and (2) how data completeness influences model generalization in relation to the compositional variation of the modelled entities. Location: Europe. Methods: We used comprehensive datasets of two community types of conservation concern in Europe: acidophilous beech forests and base‐rich fens. We computed community distribution models (CDMs) calibrated with environmental predictors to predict the occurrence of both community types, evaluating geographical transferability, interpolation and extrapolation under different scenarios of sampling bias. We used generalized dissimilarity modelling (GDM) to assess the role of geographical and environmental drivers in compositional variation within the predicted distributions. Results: For the two community types, CDMs computed for the whole study area provided good performance when evaluated by random cross‐validation and external validation. Geographical transferability provided lower but relatively good performance, while model extrapolation performed poorly when compared with interpolation. Generalized dissimilarity modelling showed a predominant effect of geographical distance on compositional variation, complemented with the environmental predictors that also influenced habitat suitability. Main conclusions: Correlative approaches typically used for modelling the distribution of individual species are also useful for delineating the potential area of occupancy of community types at the continental scale, when using consistent definitions of the modelled entity and high data completeness. The combination of CDMs with GDM further improves the understanding of diversity patterns of plant communities, providing spatially explicit information for mapping vegetation diversity and related habitat types at large scales. [ABSTRACT FROM AUTHOR]

Abstract: Aims: Although many phytosociological studies have provided detailed local and regional descriptions of coastal dune vegetation, a unified classification of this vegetation in Europe and the Mediterranean Basin has been missing. Our aim is to produce a formalized classification of this vegetation and to identify the main factors driving its plant species composition at a continental scale. Location: Atlantic and Baltic coasts of Europe, Mediterranean Basin and the Black Sea region. Methods: We compiled a database of 30,759 plots of coastal vegetation, which were resampled to reduce unbalanced sampling effort, obtaining a data set of 11,769 plots. We classified these plots with TWINSPAN, interpreted the resulting clusters and used them for developing formal definitions of phytosociological alliances of coastal dune vegetation, which were included in an expert system for automatic vegetation classification. We related the alliances to climatic factors and described their biogeographic features and their position in the coastal vegetation zonation. We examined and visualized the floristic relationships among these alliances by means of DCA ordination. Results: We defined 18 alliances of coastal dune vegetation, including the newly described Centaureo cuneifoliae‐Verbascion pinnatifidi from the Aegean region. The main factors underlying the differentiation of these alliances were biogeographic and macroclimatic contrasts between the Atlantic–Baltic, Mediterranean and Black Sea regions, along with ecological differences between shifting and stable dunes. The main difference in species composition was between the Atlantic–Baltic and Mediterranean–Black Sea regions. Within the former region, the main difference was driven by the different ecological conditions between shifting and stable dunes, whereas within the latter, the main difference was biogeographic between the Mediterranean and the Black Sea. Conclusions: The first formal classification of the European coastal dune vegetation was established, accompanied by an expert system containing the formal definitions of alliances, which can be applied to new data sets. The new classification system critically revised the previous concepts and integrated them into a consistent framework, which reflects the main gradients in species composition driven by biogeographic influences, macroclimate and the position of the sites in the coast–inland zonation of the dune systems. A revision of the class concept used in EuroVegChecklist is also proposed. [ABSTRACT FROM AUTHOR]

Abstract: Aim: To construct a classification system for Irish aquatic river vegetation that is directly comparable to European aquatic vegetation classification units. Location: A total of 2,415 river vegetation plots with a wide geographic distribution across both the Republic and Northern Ireland. Methods: The plots were recorded from a range of river types from upland streams to wadeable lowland rivers. A total of 1,613 plots were classified using supervised K‐means clustering through the programme JUICE. The Phi co‐efficient for presence/absence data was used to measure fidelity of the vegetation communities. Results: The vegetation communities could be initially sub‐divided in to four main categories: (1) bryophyte‐dominated aquatic vegetation, (2) bryophyte‐dominated marginal vegetation, (3) vascular plant‐dominated aquatic vegetation and (4) vascular plant‐dominated marginal/emergent vegetation. Within these four categories the vegetation was classified into seven classes, 18 alliances and 30 associations. Descriptions are given for each including variants and sub‐associations if found at association level. Conclusions: There is a rich diversity of bryophyte communities within Irish rivers and they are an integral part of the river network, whereas there was less diversity among vascular plant communities. The distinction between some communities was not as sharp as expected for a variety of reasons discussed in this paper, nevertheless, a working classification system was constructed. [ABSTRACT FROM AUTHOR]

Questions Which are the main vegetation types of lowland hay meadows and pastures in Western and Central Europe? What are the main environmental gradients that drive patterns of species composition? Is it possible to classify these grasslands to phytosociological alliances that reflect management practices? Location Western and Central Europe (excluding the Alps and Carpathians). Methods A database of 21 400 vegetation plots of mesic grasslands across Western and Central Europe was compiled. After geographically stratified resampling, semi-supervised classification based on the K-means algorithm was applied to assign a subset of plots into 32 a priori association-level vegetation types and to search for new types within the subset of non-assigned plots. The vegetation plots assigned into the final vegetation types were submitted to another K-means classification to show the grouping into higher-level vegetation types. Results A total of 36 associations were distinguished in the resampled subset of 8277 vegetation plots and were grouped into four large groups: (1) eutrophic and intensively managed hay meadows and permanent pastures; (2) nutrient-rich grasslands developed from recently abandoned fields or managed under irregular practices of mowing and manuring; (3) non-eutrophic lowland and submontane hay meadows; (4) extensively managed pastures and Atlantic grazed hay meadows. A PCoA of the associations of these four groups showed that extensively managed pastures were floristically more similar to non-eutrophic hay meadows than to permanent intensively managed pastures, which was more obvious in the Atlantic region than in Central Europe. Species composition of the lowland hay meadows was clearly differentiated according to biogeographic sectors. Other floristic differences were related to climate, altitude, soil base status and topography. Conclusions This analysis challenges the traditional concept of mesic grassland alliances separating hay meadows from pastures. New classification should be based mainly on the differences in management intensity rather than in management practice. Consequently, nutrient-poor extensive pastures, which currently are not considered in the European Habitats Directive, should receive the same conservation attention as low-intensive hay meadows, because both types of vegetation can be equally species-rich and do not differ substantially in floristic composition from each other. [ABSTRACT FROM AUTHOR]

Questions What are the main floristic patterns in European beech forests? Which classification at the alliance and suballiance level is the most convincing? Location Europe and Asia Minor. Methods We applied a TWINSPAN classification to a data set of 24 605 relevés covering the whole range of Fagus sylvatica forests and the western part of Fagus orientalis forests. We identified 24 'operational phytosociological units' (OPUs), which were used for further analysis. The position of each OPU along the soil pH and temperature gradient was evaluated using Ellenberg Indicator Values. Fidelity of species to OPUs was calculated using the phi coefficient and constancy ratio. We compared alternative alliance concepts, corresponding to groups of OPUs, in terms of number and frequency of diagnostic species. We also established formal definitions for the various alliance concepts based on comparison of the total cover of the diagnostic species groups, and evaluated alternative geographical subdivisions of beech forests. Results The first and second division levels of TWINSPAN followed the temperature and soil pH gradients, while lower divisions were mainly geographical. We grouped the 22 OPUs of Fagus sylvatica forests into acidophytic, meso-basiphytic and thermo-basiphytic beech forests, and separated two OPUs of F. orientalis forests. However, a solution with only two ecologically defined alliances of F. sylvatica forests (acidophytic vs basiphytic) was clearly superior with regard to number and frequency of diagnostic species. In contrast, when comparing groupings with three to six geographical alliances of basiphytic beech forests, respectively, we did not find a strongly superior solution. Conclusions We propose to classify F. sylvatica forests into 15 suballiances - three acidophytic and 12 basiphytic ones. Separating these two groups at alliance or order level was clearly supported by our results. Concerning the grouping of the 12 basiphytic suballiances into ecological or geographical alliances, as advocated by many authors, we failed to find an optimal solution. Therefore, we propose a multi-dimensional classification of basiphytic beech forests, including both ecological and geographical groups as equally valid concepts which may be used alternatively depending on the purpose and context of the classification. [ABSTRACT FROM AUTHOR]

Questions What are the main floristic patterns in the Pannonian and western Pontic steppe grasslands? What are the diagnostic species of the major subdivisions of the class Festuco-Brometea (temperate Euro-Siberian dry and semi-dry grasslands)? Location Carpathian Basin (E Austria, SE Czech Republic, Slovakia, Hungary, Romania, Slovenia, N Croatia and N Serbia), Ukraine, S Poland and the Bryansk region of W Russia. Methods We applied a geographically stratified resampling to a large set of relevés containing at least one indicator species of steppe grasslands. The resulting data set of 17 993 relevés was classified using the TWINSPAN algorithm. We identified groups of clusters that corresponded to the class Festuco-Brometea. After excluding relevés not belonging to our target class, we applied a consensus of three fidelity measures, also taking into account external knowledge, to establish the diagnostic species of the orders of the class. The original TWINSPAN divisions were revised on the basis of these diagnostic species. Results The TWINSPAN classification revealed soil moisture as the most important environmental factor. Eight out of 16 TWINSPAN groups corresponded to Festuco-Brometea. A total of 80, 32 and 58 species were accepted as diagnostic for the orders Brometalia erecti, Festucetalia valesiacae and Stipo-Festucetalia pallentis, respectively. In the further subdivision of the orders, soil conditions, geographic distribution and altitude could be identified as factors driving the major floristic patterns. Conclusions We propose the following classification of the Festuco-Brometea in our study area: (1) Brometalia erecti (semi-dry grasslands) with Scabioso ochroleucae-Poion angustifoliae (steppe meadows of the forest zone of E Europe) and Cirsio-Brachypodion pinnati (meadow steppes on deep soils in the forest-steppe zone of E Central and E Europe); (2) Festucetalia valesiacae (grass steppes) with Festucion valesiacae (grass steppes on less developed soils in the forest-steppe zone of E Central and E Europe) and Stipion lessingianae (grass steppes in the steppe zone); (3) Stipo-Festucetalia pallentis (rocky steppes) with Asplenio septentrionalis-Festucion pallentis (rocky steppes on siliceous and intermediate soils), Bromo-Festucion pallentis (thermophilous rocky steppes on calcareous soils), Diantho-Seslerion (dealpine Sesleria caerulea grasslands of the Western Carpathians) and Seslerion rigidae (dealpine Sesleria rigida grasslands of the Romanian Carpathians). [ABSTRACT FROM AUTHOR]