Aims: Vegetation classification consistent with the Braun‐Blanquet approach is widely used in Europe for applied vegetation science, conservation planning and land management. During the long history of syntaxonomy, many concepts and names of vegetation units have been proposed, but there has been no single classification system integrating these units. Here we (1) present a comprehensive, hierarchical, syntaxonomic system of alliances, orders and classes of Braun‐Blanquet syntaxonomy for vascular plant, bryophyte and lichen, and algal communities of Europe; (2) briefly characterize in ecological and geographic terms accepted syntaxonomic concepts; (3) link available synonyms to these accepted concepts; and (4) provide a list of diagnostic species for all classes.Location: European mainland, Greenland, Arctic archipelagos (including Iceland, Svalbard, Novaya Zemlya), Canary Islands, Madeira, Azores, Caucasus, Cyprus.Methods: We evaluated approximately 10 000 bibliographic sources to create a comprehensive list of previously proposed syntaxonomic units. These units were evaluated by experts for their floristic and ecological distinctness, clarity of geographic distribution and compliance with the nomenclature code. Accepted units were compiled into three systems of classes, orders and alliances (EuroVegChecklist,EVC) for communities dominated by vascular plants (EVC1), bryophytes and lichens (EVC2) and algae (EVC3).Results: EVC1 includes 109 classes, 300 orders and 1108 alliances;EVC2 includes 27 classes, 53 orders and 137 alliances, andEVC3 includes 13 classes, 24 orders and 53 alliances. In total 13 448 taxa were assigned as indicator species to classes ofEVC1, 2087 to classes ofEVC2 and 368 to classes ofEVC3. Accepted syntaxonomic concepts are summarized in a series of appendices, and detailed information on each is accessible through the software tool EuroVegBrowser.Conclusions: This paper features the first comprehensive and critical account of European syntaxa and synthesizes more than 100 yr of classification effort by European phytosociologists. It aims to document and stabilize the concepts and nomenclature of syntaxa for practical uses, such as calibration of habitat classification used by the European Union, standardization of terminology for environmental assessment, management and conservation of nature areas, landscape planning and education. The presented classification systems provide a baseline for future development and revision of European syntaxonomy.

Questions: The co‐existence of high numbers of species has always fascinated ecologists, but what and where are the communities with the world records for plant species richness? The species–area relationship is among the best‐known patterns in community ecology, but does it give a consistent global pattern for the most saturated communities, the global maxima?Location: The world.Methods: We assembled the maximum values recorded for vascular plant species richness for contiguous areas from 1 mm² up to 1 ha. We applied the power function to relate maximal richness to area and to make extrapolations to the whole Earth.Results: Only two community types contain global plant species maxima. The maxima at smaller spatial grain were from oligo‐ to meso‐trophic, managed, semi‐natural, temperate grasslands (e.g. 89 species on 1 m²), those at larger grains were from tropical rain forests (e.g. 942 species on 1 ha). The maximum richness values closely followed a power function with z = 0.250: close to Preston's ‘canonical’ value of 0.262. There was no discernable difference between maxima using rooted presence (i.e. including only plants rooted in the plot) vs shoot presence (i.e. including any plant with physical cover over the plot). However, shoot presence values must logically be greater, with the curves flattening out at very small grain, and there is evidence of this from point quadrats. Extrapolating the curve to the terrestrial surface of the Earth gave a prediction of 219 204 vascular plant species, surprisingly close to a recent estimate of 275 000 actual species.Conclusions: Very high richness at any spatial grain is found only in two particular habitat/community types. Nevertheless, these high richness values form a very strong, consistent pattern, not greatly affected by the method of sampling, and this pattern extrapolates amazingly well. The records challenge ecologists to consider mechanisms of species co‐existence, answers to the ‘Paradox of the Plankton’.

Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.

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.

This article introduces a Special Issue on biodiversity of Palaearctic grasslands and provides a synthesis of the current knowledge on this topic. Four major categories of grasslands can be distinguished in the Palaearctic biogeographic realm: (a) zonal steppes (in areas too dry for forests), (b) arctic-alpine grasslands (in areas too cold for forests), (c) azonal and extrazonal grasslands (where hydrology, soil conditions, relief or natural disturbances within the forest biomes prevent tree growth locally) and (d) secondary grasslands (which replace natural forests in consequence of human land use). We summarize the present knowledge about species richness patterns (mainly of vascular plants) along abiotic and land use gradients. Further, we highlight the usefulness of diversity measures not based on species richness, namely functional diversity, phylogenetic diversity and within-species diversity. The strong differences observed for diversity patterns according to analyzed biodiversity parameter, spatial scale or taxonomic group call for comparative studies and caution when generalizing results. A particular challenge are the extreme plot-scale species richness values found in grasslands of a few European regions. We propose a conceptual model that explains the findings by an interplay of various factors acting at different levels: (i) The largest species pool is expected for habitats under conditions that prevailed over the last few million years, with a slight shift towards intermediate positions, i.e. for the Palaearctic in open, semi-dry, base-rich situations. (ii) The landscape-level species pool is increased by continuity of a grassland patch in space and time and heterogeneity of the surrounding landscape. (iii) The coexistence of regionally available species at a plot scale is due to reduced competitive exclusion according to Intermediate Disturbance Hypothesis, mowing once a year without fertilization being particularly effective. Ecosystem functions and services of Palaearctic grasslands are often positively connected to their biodiversity. At the same time, these communities and their biota are nowadays highly endangered. The semi-natural (High Nature Value) grasslands of Europe are mainly threatened by agricultural intensification or abandonment on low-productive sites in remote areas, while the natural steppes of the Palaearctic have largely been destroyed by conversion into arable land. Finally, we present some promising conservation and management approaches and call for a strong and comprehensive Convention on Grassland Conservation

The European Vegetation Archive (EVA) is a centralized database of European vegetation plots developed by the IAVS Working Group European Vegetation Survey. It has been in development since 2012 and first made available for use in research projects in 2014. It stores copies of national and regional vegetation‐ plot databases on a single software platform. Data storage in EVA does not affect on‐going independent development of the contributing databases, which remain the property of the data contributors. EVA uses a prototype of the database management software TURBOVEG 3 developed for joint management of multiple databases that use different species lists. This is facilitated by the SynBioSys Taxon Database, a system of taxon names and concepts used in the individual European databases and their corresponding names on a unified list of European flora. TURBOVEG 3 also includes procedures for handling data requests, selections and provisions according to the approved EVA Data Property and Governance Rules. By 30 June 2015, 61 databases from all European regions have joined EVA, contributing in total 1 027 376 vegetation plots, 82% of them with geographic coordinates, from 57 countries. EVA provides a unique data source for large‐scale analyses of European vegetation diversity both for fundamental research and nature conservation applications. Updated information on EVA is available online at http://euroveg.org/eva-database.