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.

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.

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.

The fourth edition of the International Code of Phytosociological Nomenclature (ICPN) was prepared by the Steering Committee of the IAVS Working Group for Phytosociological Nomenclature (GPN). The edition consists of 14 Definitions, 7 Principles, 53 Articles, and 7 Appendices. When compared with the previous edition, the main amendments are: (a) the acceptance of electronic publications (Art. 1); (b) the introduction of binding decisions (Definition XIV, Principle II, Articles 1, 2b, 3c, 29b, 40, 42, 44, Appendices 6 and 7); (c) the mandatory use of the English or Latin terminology for syntaxonomic novelties (Definition II, Principle II, Articles 3d and 3i); (d) the introduction of autonyms for the main ranks when the corresponding secondary ranks are created (Articles 13b and 24); (e) the automatic correction of the taxon names (name‐giving taxa) used in the names of syntaxa in accordance with the International Code of Nomenclature for algae, fungi, and plants (ICN) (Article 44); (f) the possibility to mutate the name of a syntaxon in using other correct, alternative names for the name‐giving taxa (Article 45); (g) the introduction of inadequate names, a new category of rejected names (Definition V, Articles 43 through 45); and (h) the introduction of a conserved type (Definition XIII, Article 53). The fourth edition of ICPN was approved by the GPN on 25 May 2019 and becomes effectively binding on 1 January 2021.

Aims: Ellenberg‐type indicator values are expert‐based rankings of plant species according to their ecological optima on main environmental gradients. Here we extend the indicator‐value system proposed by Heinz Ellenberg and co‐authors for Central Europe by incorporating other systems of Ellenberg‐type indicator values (i.e., those using scales compatible with Ellenberg values) developed for other European regions. Our aim is to create a harmonized data set of Ellenberg‐type indicator values applicable at the European scale.Methods: We collected European data sets of indicator values for vascular plants and selected 13 data sets that used the nine‐, ten‐ or twelve‐degree scales defined by Ellenberg for light, temperature, moisture, reaction, nutrients and salinity. We compared these values with the original Ellenberg values and used those that showed consistent trends in regression slope and coefficient of determination. We calculated the average value for each combination of species and indicator values from these data sets. Based on species’ co‐occurrences in European vegetation plots, we also calculated new values for species that were not assigned an indicator value.Results: We provide a new data set of Ellenberg‐type indicator values for 8908 European vascular plant species (8168 for light, 7400 for temperature, 8030 for moisture, 7282 for reaction, 7193 for nutrients, and 7507 for salinity), of which 398 species have been newly assigned to at least one indicator value.Conclusions: The newly introduced indicator values are compatible with the original Ellenberg values. They can be used for large‐scale studies of the European flora and vegetation or for gap‐filling in regional data sets. The European indicator values and the original and taxonomically harmonized regional data sets of Ellenberg‐type indicator values are available in the Supporting Information and the Zenodo repository.