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 vegetationplot 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 largescale analyses of European vegetation diversity both for fundamental research and nature conservation applications. Updated information on EVA is available online at http://euroveg.org/evadatabase.

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Lysenko 91,92 | Armin Macanović 93 | Parastoo Mahdavi 94 | Peter Manning 35 | Corrado Marcenò 13 | Vassiliy Martynenko 95 | Maurizio Mencuccini 96 | Vanessa Minden 97 | Jesper Erenskjold Moeslund 54 | Marco Moretti 98 | Jonas V. Müller 99 | Abstract Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level.Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale. K E Y W O R D S biodiversity, community ecology, ecoinformatics, functional diversity, global scale, macroecology, phylogenetic diversity, plot database, sPlot, taxonomic diversity, vascular plant, vegetation relevé 166 |

Aims Classification of vegetation is an essential tool to describe, understand, predict and manage biodiversity. Given the multiplicity of approaches to classify vegetation, it is important to develop international consensus around a set of general guidelines and purpose‐specific standard protocols. Before these goals can be achieved, however, it is necessary to identify and understand the different choices that are made during the process of classifying vegetation. This paper presents a framework to facilitate comparisons between broad‐scale plot‐based classification approaches. Results Our framework is based on the distinction of four structural elements (plot record, vegetation type, consistent classification section and classification system) and two procedural elements (classification protocol and classification approach). For each element we describe essential properties that can be used for comparisons. We also review alternative choices regarding critical decisions of classification approaches; with a special focus on the procedures used to define vegetation types from plot records. We illustrate our comparative framework by applying it to different broad‐scale classification approaches. Conclusions Our framework will be useful for understanding and comparing plot‐based vegetation classification approaches, as well as for integrating classification systems and their sections.

A central hypothesis of ecology states that regional diversity influences local diversity through species-pool effects. Species pools are supposedly shaped by large-scale factors and then filtered into ecological communities, but understanding these processes requires the analysis of large datasets across several regions. Here, we use a framework of community assembly at a continental scale to test the relative influence of historical and environmental drivers, in combination with regional or local species pools, on community species richness and community completeness. Using 42,173 vegetation plots sampled across European beech forests, we found that large-scale factors largely accounted for species pool sizes. At the regional scale, main predictors reflected historical contingencies related to post-glacial dispersal routes, whereas at the local scale, the influence of environmental filters was predominant. Proximity to Quaternary refugia and high precipitation were the main factors supporting community species richness, especially among beech forest specialist plants. Models for community completeness indicate the influence of large-scale factors, further suggesting community saturation as a result of dispersal limitation or biotic interactions. Our results empirically demonstrate how historical factors complement environmental gradients to provide a better understanding of biodiversity patterns across multiple regions.

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.

Aim:The former continental-scale studies modelled coarse-grained plant speciesrichness 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 m 2 ; 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.

Aim: Vegetation types of Mediterranean thermophilous pine forests dominated by Pinus brutia, Pinus halepensis, Pinus pinaster and Pinus pinea were studied in various areas. However, a comprehensive formal vegetation classification of these forests based on a detailed data analysis has never been developed. Our aim is to provide the first broad-scale classification of these pine forests based on a large data set of vegetation plots.