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This Long Database Report describes the historical background and current contents of the Nordic-Baltic Grassland Vegetation Database (NBGVD) (GIVD -code EU-00-002). NBGVD is the EDGG -associated collaborative vegetation-plot database that collects vegetation-plot data of grasslands and other open habitats (except segetal and deep aquatic vegetation) from the Nordic-Baltic region excluding Germany, namely Belarus, Denmark, Estonia, Faroe Islands, Finland, Iceland, Latvia, Lithuania, Norway, N Poland, NW Russia, Svalbard and Jan Mayen, and Sweden. Target vegetation types are lowland grasslands and heathlands, arctic-alpine communities, coastal communities, non-forested mires and other wetlands, rocky, tall-herb and ruderal communities. As of March 2024, it included 12,694 relevés recorded between 1910 and 2023. These were mainly digitised from literature sources (84%), while the remainder comes from individual unpublished sources (16%). The data quality is high, with bryophytes and lichens being treated in more than 80% of all plots and measured environmental variables such as topography and soil characteristics often available in standardised form. A peculiarity of the Nordic-Baltic region are the relatively small plot sizes compared to other regions (median: 4 m2). The available data stem from 35 vegetation classes, with Koelerio-Corynephoretea, Festuco-Brometea, Sedo-Scleranthetea, Molinio-Arrhenatheretea and Scheuchzerio-Caricetea being most frequent. We conclude that NBGVD provides valuable data, allowing interesting analyses at the regional scale and fills gaps in continental to global analyses. Still, since there are many more data around, we ask interested readers to contribute their own data or help find and digitise old data from the literature. Taxonomic reference : TURBOVEG species list "Europe". Syntaxonomic reference : Mucina et al. (2016). Abbreviations : EDGG = Eurasian Dry Grassland Group, EVA = European Vegetation Archive, GIVD = Global Index of Vegetation-Plot Databases, NBGVD = Nordic-Baltic Grassland Vegetation Database [ABSTRACT FROM AUTHOR]

Social networks offer communication channels through which people share huge amounts of primary data that can be used for scientific analyses, including biodiversity research. To understand to what extent data extracted from social networks could complement data collected for scientific purposes, it is necessary to quantify the bias of such data.We analysed which plant traits increased the probability of a wild‐growing plant species to be photographed and posted to a social network based on the data from an unstructured citizen science tool; a Facebook group focused on the vascular flora of Sicily (Italy). Then, we compared botanical data collected by this Facebook group members with data collected by scientists in 6,366 vegetation plots sampled across Sicily, stored in the EVA database.Our results suggested that data proceeding from the analysed Facebook group were affected by various sampling biases, which differed from the biases inherent to other types of biodiversity data such as those from vegetation plots.Facebook users recorded a higher proportion of red‐listed and alien species than vegetation scientists. Therefore, social networks can provide a valuable complement to the data collected by scientists for research purposes.Synthesis and applications. Despite Facebook does not support geotagging and interface for data access and analysis, it is an invaluable source of biodiversity data that could complement those collected by professional researchers. The main advantage of data from social networks is their high dynamism, as they report large amounts of species occurrences in almost real time. Therefore, citizen science data from a Facebook group where the records are curated by expert volunteers can be used (a) for monitoring population dynamics of threatened and alien species; (b) as a source of additional data on rare species occurrences, particularly for plants that are attractive for amateur botanists, such as orchids; (c) for early warning systems of potential new invasions; and (4) for phenological studies, especially at the beginning of the flowering season. [ABSTRACT FROM AUTHOR]

Aim: Plant functional traits summarize the main variability in plant form and function across taxa and biomes. We assess whether geographic range size, climatic niche size, and local abundance of plants can be predicted by sets of traits (trait syndromes) or are driven by single traits. Location: Eurasia. Methods: Species distribution maps were extracted from the Chorological Database Halle to derive information on the geographic range size and climatic niche size for 456 herbaceous, dwarf shrub and shrub species. We estimated local species abundances based on 740,113 vegetation plots from the European Vegetation Archive, where abundances were available as plant species cover per plot. We compiled a complete species‐by‐trait matrix of 20 plant functional traits from trait databases (TRY, BiolFlor and CLO‐PLA). The relationships of species’ geographic range size, climatic niche size and local abundance with single traits and trait syndromes were tested with multiple linear regression models. Results: Generally, traits were more strongly related to local abundances than to broad‐scale species distribution patterns in geographic and climatic space (range and niche size), but both were better predicted by trait combinations than by single traits. Local abundance increased with leaf area and specific leaf area (SLA). Geographic range size and climatic niche size both increased with SLA. While range size increased with plant height, niche size decreased with leaf carbon content. Conclusion: Functional traits matter for species’ abundance and distribution at both local and broad geographic scale. Local abundances are associated with different combinations of traits as compared to broad‐scale distributions, pointing to filtering by different environmental and ecological factors acting at distinct spatial scales. However, traits related to the leaf economics spectrum were important for species’ abundance and occurrence at both spatial scales. This finding emphasizes the general importance of resource acquisition strategies for the abundance and distribution of herbaceous, dwarf shrub and shrub species.We studied whether single traits or sets of traits matter for species’ abundance and distribution at both local and broad geographic scale. Traits related to the leaf economics spectrum were important for abundance and occurrence at both spatial scales. This finding emphasizes the general importance of resource acquisition strategies for the abundance and distribution of herbaceous, dwarf shrub and shrub species. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]

The European Boreal Forest Vegetation Database (EBFVD, GIVD ID: EU-00-027) is a repository for vegetation- plot data from the forests of the boreal and hemiboreal zones of Europe. In this report, we describe its structure, current content and future perspectives opened up by the database. In February 2019, the database contained 13 037 vegetation-plot records from Belarus, Estonia, Finland, Latvia, Norway, Russia and Sweden that are not yet stored in the databases of the European Vegetation Archive (EVA). Consequently, this database significantly improves the availability of forest plant community data from Northern Europe. The database is managed by the Vegetation Science Group, Department of Botany and Zoology, Masaryk University, Brno (Czech Republic), in the TURBOVEG 2 program. It is registered in the Global Index of Vegetation Plot Databases (GIVD) and included in EVA. The whole database, or a subset of it, can be requested via EVA, or directly from the database custodian. [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]

Aim: Biodiversity databases are valuable resources for understanding plant species distributions and dynamics, but they may insufficiently represent the actual geographic distribution and climatic niches of species. Here we propose and test a method to assess sampling coverage of species distribution in biodiversity databases in geographic and climatic space. Location: Europe. Methods: Using a test selection of 808,794 vegetation plots from the European Vegetation Archive (EVA), we assessed the sampling coverage of 564 European vascular plant species across both their geographic ranges and realized climatic niches. Range maps from the Chorological Database Halle (CDH) were used as background reference data to capture species geographic ranges and to derive species climatic niches. To quantify sampling coverage, we developed a box‐counting method, the Dynamic Match Coefficient (DMC), which quantifies how much a set of occurrences of a given species matches with its geographic range or climatic niche. DMC is the area under the curve measuring the match between occurrence data and background reference (geographic range or climatic niche) across grids with variable resolution. High DMC values indicate good sampling coverage. We applied null models to compare observed DMC values with expectations from random distributions across species ranges and niches. Results: Comparisons with null models showed that, for most species, actual distributions within EVA are deviating from null model expectations and are more clumped than expected in both geographic and climatic space. Despite high interspecific variation, we found a positive relationship in DMC values between geographic and climatic space, but sampling coverage was in general more random across geographic space. Conclusion: Because DMC values are species‐specific and most biodiversity databases are clearly biased in terms of sampling coverage of species occurrences, we recommend using DMC values as covariates in macro‐ecological models that use species as the observation unit. [ABSTRACT FROM AUTHOR]

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). GrassPlot collects plot records (relevés) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001; ... 1,000 m?) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetationplot databases, such as the European Vegetation Archive (EVA) and the global database "sPlot". Its main aim is to facilitate studies on the scale- and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board. [ABSTRACT FROM AUTHOR]

This report describes the Romanian Grassland Database (RGD), registered under EU-RO-008 in the Global Index of Vegetation-Plot Databases (GIVD). This collaborative initiative aims to collect all available vegetationplot data (relevés) of grasslands and other open habitats from the territory of Romania to provide them for science, nationally and internationally, e.g. via the European Vegetation Archive (EVA) and the global database "sPlot". The database mainly contains vegetation-plots from not only wet, mesic, dry, saline, alpine and rocky grasslands, but also other vegetation types like heathlands, mires, ruderal, segetal, aquatic and cryptogamdominated vegetation. Currently, 21,685 relevés have mainly been digitised from literature sources (90%), while the remainder comes from individual unpublished sources (10%). We report on the background and history of the RGD, explain its "Data Property and Governance Rules" under which data are contributed and retrieved, and outline how the RGD can contribute to research in the fields of vegetation ecology, macroecology and conservation. [ABSTRACT FROM AUTHOR]

The Republic of Tatarstan is situated between forest and steppe natural zones in the boreal mega-ecotone and has a high species and plant community diversity. The Vegetation Database of Tatarstan (GIVD Database ID: EU-RU-011) is based on phytosociological relevés, herbaria and floristic records. It includes over 8,000 plot records, almost half of them being georeferenced. The database is part of the European Vegetation Archive (EVA) and sPlot projects. In EVA it has a semi-restricted access mode. [ABSTRACT FROM AUTHOR]

In recent years, interest in availability of georeferenced vegetation plots has stimulated or reinvigorated national initiatives to compile these data. In Italy, eleven vegetation databases are currently registered in the Global Index of Vegetation-Plot Databases (GIVD). In this paper we describe the Vegetation Plot Database - Sapienza University of Rome (VPD-Sapienza; GIVD code EU-IT-011), which started in 2012 and rapidly became one of the most prominent ones with a total of 21,917 georeferenced vegetation plots spanning across the country. These plots include 286,650 vascular plant species occurrences. Most of the plots belong to temperate deciduous forests (Querco roboris-Fagetea sylvaticae) and broadleaved evergreen forests (Quercetea ilicis), which together account for about 40% of the database. The need for the establishment of a national federated database integrating other national, regional, local and thematic databases is discussed in order to avoid setbacks such as duplication of data, taxonomic and syntaxonomic inconsistencies, and reduced efficiencies in collaborative projects, both at national and international levels. [ABSTRACT FROM AUTHOR]

For the purpose of an ongoing research project dealing with the classification of European river gravel bar vegetation, we collected and digitized vegetation-plot data included in the Gravel Bar Vegetation Database (GIVD ID: EU-00-025, http: //www.givd.info/ID/EU-00-025). The database consists of vegetation plots obtained from the literature and from our own field sampling in the countries where this vegetation has not previously been studied or is less explored, especially in southeastern and northern Europe and the Caucasus. The database currently contains 1,738 vegetation plots from 18 countries representing different types and successional stages in the range of gravel bar vegetation from the initial herbaceous stands to scrub, mainly of the order Epilobietalia fleischeri (class Thlaspietea rotundifolii) and the class Salicetea purpureae. Geographical coordinates are available for all plots; accuracy of those derived from the literature depends on the precision of the location descriptions. European montane and submontane gravel-bed rivers with their typical vegetation belong to most endangered habitats; thus the database should complete the information about their distribution and their typical vegetation types. It also serves as data source for studies of vegetation structure and dynamics. The database is managed by the Vegetation Science Group at the Department of Botany and Zoology, Masaryk University, Brno. It has been integrated in the European Vegetation Archive (EVA). [ABSTRACT FROM AUTHOR]