1 Type: Section Ecoinformatics, Long Database Report 2 3 The Romanian Grassland Database (RGD): historical background, current status and future perspectives 4 5 Kiril Vassilev*, Eszter Ruprecht, Valeriu Alexiu, Thomas Becker, Monica Beldean, Claudia Biță-Nicolae, Anna Mária 6 Csergő, Iliana Dzhovanova, Eva Filipova, József Pál Frink, Dan Gafta, Mariya Georgieva, Markus S. Germany, Irina 7 Goia, Media Gumus, Stephan M. Hennekens, Monika Janišová, Ilona Knollová, Viktoriya Koleva, Sofia Kostadinova, 8 Nevena Kuzmanović, Jacqueline Loos, Constantin Mardari, Thomas Michl, Monica Angela Neblea, Roxana Ion 9 Nicoară, Pavel Novák, Kinga Öllerer, Marilena Onete, Salza Palpurina, Inge Paulini, Hristo Pedashenko, Mihai Pușcaș, 10 Anamaria Roman, Jozef Šibík, Culiță Sîrbu, Daniela Stancu, Laura M.E. Sutcliffe, Anna Szabó, Cezar-Valentin 11 Tomescu, Evelin Totev, Borislav Tsvetanov, Pavel Dan Turtureanu, Plamena Vassileva, Nikolay Velev & Jürgen 12 Dengler *Corresponding author’s address: Institute of Biodiversity and Ecosystem Research, Bulgarian Academy of Sciences, 23 Acad. G. Bonchev Str., 1113 Sofia, Bulgaria; kiril5914@abv.bg. Complete addresses of all authors can be found at the bottom of the paper. 13 14 Running title: Romanian Grassland Database (RGD) 15 1 16 Abstract: This report describes the Romanian Grassland Database (RGD), registered under EU-RO-008 in the Global 17 Index of Vegetation-Plot Databases (GIVD). This collaborative initiative aims to collect all available vegetation-plot 18 data (relevés) of grasslands and other open habitats from the territory of Romania to provide them for science, 19 nationally and internationally, e.g. via the European Vegetation Archive (EVA) and the global database “sPlot”. The 20 database mainly contains vegetation-plots from not only wet, mesic, dry, saline, alpine and rocky grasslands, but also 21 other vegetation types like heathlands, mires, ruderal, segetal, aquatic and cryptogam-dominated vegetation. Currently, 22 21,685 relevés have mainly been digitised from literature sources (90%), while the remainder comes from individual 23 unpublished sources (10%). We report on the background and history of the RGD, explain its “Data Property and 24 Governance Rules” under which data are contributed and retrieved, and outline how the RGD can contribute to research 25 in the fields of vegetation ecology, macroecology and conservation. 26 Keywords: ecoinformatics; European Vegetation Archive (EVA); grassland vegetation; phytosociology; relevé; 27 Romanian Grassland Database (RGD); sPlot; Turboveg; vegetation classification; vegetation-plot data. 28 Abbreviations: EVA = European Vegetation Archive; GIVD = Global Index of Vegetation-Plot Databases; RGD = 29 Romanian Grassland Database. 30 Submitted: 4 September 2017 31 Accepted: 5 October 2017 32 Co-ordinating Editor: Florian Jansen 33 GIVD Fact Sheet #Separate file# 34 Introduction 35 Vegetation-plot databases provide a powerful source of information for plant community ecology, macroecology and 36 conservation biology as they combine fine-grain co-occurrence data of plant species across large spatial extents 37 (Dengler et al. 2011; Chytrý et al. 2016). Europe, due to its strong phytosociological tradition (Braun-Blanquet 1965; 38 Dengler et al. 2008) probably is the continent with the largest number of vegetation-plot records (relevés), totalling 39 several millions (Schaminée et al. 2009; Dengler et al. 2011). Over the last 25 years, in many European countries 40 comprehensive national vegetation-plot databases have emerged (Schaminée et al. 2009), which subsequently gave rise 41 to the integrated European Vegetation Archive (EVA; http://euroveg.org/eva-database; Chytrý et al. 2016) and the 42 global database “sPlot” (https://www.idiv.de/splot; Dengler & sPlot Core Team 2014). Schaminée et al. (2009) 43 estimated that in Romania more than 70,000 relevés exist, although at the time of publication none of these data were 44 digitally available in a database. 45 Meanwhile, the development of the Global Index of Vegetation-Plot Databases (GIVD; http://www.givd.info/; Dengler 46 et al. 2011) inspired several colleagues to establish and register in GIVD smaller databases with plots from Romania, 47 including the “Vegetation Database of Dry Grasslands in the Southeast Romania” (Biță-Nicolae 2012; EU-RO-001), the 48 “Vegetation Database of the Dry Grasslands from the Transylvanian Basin” (Ruprecht et al. 2012; EU-RO-002) and 2 49 “Mesophilic Pastures in Southern Transylvania, Romania” (by L. Sutcliffe; EUR-RO-006). When the EVA was 50 established, its team sought to facilitate the establishment of one or few larger national vegetation databases in Romania 51 that could serve as competent partners for the European initiative. As a result, the three named grassland databases 52 joined to form the Romanian Grassland Database (RGD; EU-RO-008) which aimed to comprise all vegetation types of 53 grasslands and other open habitats from the country. Similarly, several smaller forest databases merged to form the 54 Romanian Forest Database (RGF; EU-RO-007) focusing on forests and shrublands (Indreica et al. in press). 55 In this article we introduce the RGD, its technical and organisational set-up, report on its current content, and provide a 56 view on future activities and opportunities. 57 Knowledge of grasslands and other open habitats in Romania 58 Based on the vast data that have accumulated over time, as a result of field investigations conducted by numerous 59 phytosociologists, a series of syntheses on the vegetation of Romania were published over the past seven decades, at 60 regional (e.g. Soó 1949; Borza 1963; Beldie & Dihoru 1967; Coldea 1991; Chifu et al. 2006) and national levels (e.g. 61 Borza et al. 1960; Pușcaru-Soroceanu et al. 1963; Doniță et al. 1992; Sanda et al. 1998; Coldea 1997, 2012; Chifu 62 2014). According to Coldea (1997, 2012), the herbaceous vegetation of Romania consists of 461 vascular plant 63 associations, grouped into 115 alliances, 56 orders and 35 classes. Of the total number of associations, ca. 42% (from 48 64 alliances, 24 orders and 18 classes) are comprised of natural vegetation and 58% (from 67 alliances, 32 orders and 17 65 classes) of anthropogenic vegetation (including secondary meadows and ruderal vegetation). 66 This diversity of syntaxa reflects the great variety of vegetation cover in Romania, resulting from the geomorphological 67 and climatic diversity of the country and its location at the intersection of several floristic provinces (Coldea 1997). 68 However, all the current classification schemes in Romania are based on “expert knowledge” only. To date, no 69 classification takes advantage of the large amount of existing vegetation-plot data that would allow the sound 70 delimitation of syntaxa and determination of their diagnostic species with transparent and reproducible (statistical) 71 methods (see De Cáceres et al. 2015). 72 Emergence and organisation of the Romanian Grassland Database 73 Unrecognized by the vegetation-plot community outside the country (e.g. Schaminée et al. 2009), 1,467 relevés from 74 dry grassland vegetation types were digitally collected by E. Ruprecht and colleagues in 2002. This later became the 75 “Vegetation Database of the Dry Grasslands from the Transylvanian Basin” (EU-RO-002; Ruprecht et al. 2012). The 76 Romanian Grassland Database (RGD) was created in 2014, via merging the existing Transylvanian database with 77 several smaller datasets of C. Biță-Nicolae, M. Janišová and J. Dengler, resulting in a total of 1,831 relevés. With the 78 establishment of the RGD Data Property and Governance Rules (Supplement S1), we expanded the database to not only 79 include grasslands s.str, but also all vegetation types of open habitats,. This together with an advertising campaign led to 80 dynamic growth of the database content from 7,528 relevés in May 2015 to 21,685 relevés in August 2017. 81 The RGD is registered in the Global Index of Vegetation-Plot Databases (GIVD; http://www.givd.info; Dengler et al. 82 2011) under EU-RO-008 (http://www.givd.info/ID/EU-RO-008). This database has contributed its vegetation-plot data 83 to the European Vegetation Archive (EVA; Chytrý et al. 2016), and to the global vegetation-plot database “sPlot” 3 84 (http://www.idiv.de/splot; Dengler & sPlot Core Team 2014). Since the spring of 2017, the RGD has maintained a 85 webpage on the Ecoinformatics Portal of the University of Bayreuth (http://bit.ly/2vz0l1u). 86 The RGD’s Data Property and Governance Rules (Supplement S1) doubtlessly contributed much to its attractiveness 87 and success. The document regulates the governance of the database, data provision, type of data availability regimes, 88 data requests and terms of data use, rules for authorship and relationships with other databases like EVA, sPlot and 89 GIVD. 90 (http://euroveg.org/download/eva-rules.pdf) and the governance and Data Rules of the sPlot Working Group 91 (http://www.idiv-biodiversity.de/sdiv/workshops/workshops-2013/splot/join/content_815683/sPlot- 92 Rules_approved.pdf). In essence, they show that the RGD is a collaborative, self-governed consortium that elects a 93 Custodian (currently E.R.) and a Deputy-Custodian (currently K.V.) to represent its interests and to coordinate daily 94 business. Currently, the RGD Consortium consists of 50 members of which one half is from Romania and the remainder 95 are people from abroad who study or studied Romanian vegetation. 96 The basic principle of the RGD that makes becoming a member so attractive is the concept of give-and-take. Only those 97 who contribute data to the RGD, and thus become members of the RGD Consortium, have access to full RGD content 98 and can propose projects making use of it. Likewise, RGD Consortium members are informed whenever there are 99 requests to utilize RGD data, either directly or via EVA or sPlot. When requests are made, one of the RGD Consortium 100 members can opt in as active co-author, while they themselves also can propose EVA and sPlot projects using the 101 whole European or global dataset. Over the last two years, data from the RGD were requested and provided for 30 102 projects via the EVA and sPlot databases, and some first papers resulting from these cooperations have been published 103 (e.g. Willner et al. 2017). 104 Technical implementation 105 The relevés of the RGD are managed and stored with the Turboveg v2.101 software (Hennekens & Schaminée 2001). 106 This facilitates effective data import and handling as well as very easy data provision to EVA and sPlot, which are run 107 under Turboveg v3 that allows the combination of many different Turboveg v2 databases. The database structure is 108 based on the standard header data fields of Turboveg v2, but many new fields have been added, both to allow retaining 109 as much as possible of the original information and to support the coordination and the rights management within and 110 between RGD, EVA and sPlot. 111 The species list of vascular plants was originally based on Flora Europaea (Tutin et al. 1964−1980), and augmented 112 with new taxa when needed. We also entered varieties and forms of species in order to keep the original information 113 from digitized publications. All changes in species nomenclature related to the original literature sources follow the 114 Flora 115 (http://www.emplantbase.org/home.html) and are documented in a separate file. Names of bryophytes, lichens and 116 algae are currently stored in their original form and not yet standardized according to uniform checklists. 117 Author and “biblioreference” popup lists were created during digitization. The list of digitized publications and other 118 sources is provided in Supplement S2. Names of syntaxa were harmonized according to Sanda et al. (2008). These rules Europaea are database phrased similarly to the EVA Data (http://rbg-web2.rbge.org.uk/FE/fe.html) Property and the and Governance Euro+Med Rules PlantBase 4 119 Current content of RGD 120 According to its Rules, the RGD collects data from all grassland vegetation types (wet, mesic, dry, saline, alpine, 121 rocky), and also other vegetation types, such as heathlands, ruderal and segetal vegetation, mires and aquatic vegetation 122 as well as cryptogam-dominated types from the territory of Romania (Fig. 1). Forests and the majority of shrublands are 123 not considered because they are captured by a parallel effort of the Romanian Forest Database (RFD; EU-RO-007; 124 Indreica et al. in press). However, there is currently some overlap between both national databases, concerning 125 communities dominated by shrubs and dwarf shrubs, mainly from the subalpine zone. Such stands, dominated by Pinus 126 mugo, Juniperus sibirica, Alnus viridis, Vaccinium, Salix and Rubus species constitute about 5% of the content of RGD 127 and might partly also be contained in RFD. In addition, some data of wetland vegetation (about 1%) are also included in 128 the WetVegEurope database (EU-00-020; Landucci et al. 2015) and some plots with “standard plot sizes” are shared 129 with the Database of Scale-Dependent Phytodiversity Patterns in Palaearctic Grasslands (GrassPlot; EU-00-003; 130 Dengler et al. 2012). We are cooperating with these other databases to avoid duplication of work in the future and to 131 ensure that each vegetation plot is delivered only once to EVA and sPlot. 132 The majority of the data in RGD was digitized from published literature sources (90%), while the rest are unpublished 133 relevés from Consortium members (10%). In total, the RGD currently contains data from nearly 500 different sources. 134 There are two periods during which the majority of vegetation plots were recorded (Fig. 1). The first peak (1960−1980) 135 refers to a large number of vegetation studies in different regions of the country, while the second peak (2001−2010) is 136 related to a great number of relevés sampled as a part of PhD or Master theses. The majority of plots are in the semi- 137 restricted data availability regime (87%; for specific definitions for access see the EVA; Chytrý et al. 2016), while few 138 have restricted access (10%) and even fewer have free access (3%). 139 Geographic coordinates are now available for 99.88% of the relevés (Fig. 2). While most sources (72%) did not contain 140 geographic coordinates, they were geo-referenced a posteriori using Google Earth and other available information 141 about the plot localities, which lead to coarse geographic precision (see Fact Sheet). Most of the relevés come from 142 mountainous and semi-mountainous parts of Romania, which are better explored compared to lowland areas (Fig. 2). 143 Traditionally, researchers focused mainly on the most distant, natural areas, whereas agricultural and rural areas were 144 less studied. 145 To complement the information provided in the Fact Sheet, we summarize the contents of the best-filled header data as 146 follows: 147 148  Plot size ranges from 0.01 to 3,500 m². The most frequently used plot sizes are 100 m² (21.8%), 25 m² (21.0%) and 10 m² (4.3%), while 19.9% of the plots lack such information. 149  Data on non-vascular plants are available for 28% of the relevés. 150  Elevation ranges from 0 to 2,525 m a.s.l., although 35% of the relevés are lacking this information. 151  Aspect and slope are the two most often recorded environmental parameters and are available for 55% and 152 54% of the relevés, respectively, while land use and soil parameters are unfortunately rather sparse (< 10%) in 153 the current database (see Fact Sheet). 154 155  Cover of vegetation: Total vegetation cover is provided for 31% of the relevés, while availability of individual vegetation strata cover varies from 35% for the tree layer to 8% for the cryptogam layer. 5 156  Syntaxa: 77.6% of the relevés in the RGD are classified into syntaxa of different levels (Table 1; Supplement 157 S1). Non-classified relevés (22.4%) mainly come from unpublished data sources or are cryptogam 158 communities, which are not included in syntaxon popup list. 159 Summary and outlook 160 With this Long Database Report we give credit to all of the vegetation scientists who actively contributed to mobilizing 161 Romanian vegetation-plot data, either by providing their own plots or helping with the digitization of data from the 162 literature for the RGD. From now on, we ask that this report be cited when data from the RGD are used. 163 The RGD has undergone dynamic development during recent years and now nicely complements the Romanian Forest 164 Database (RFD; Indreica et al. in press). We believe the success of the RGD is largely due to our transparent rules that 165 balance the interests of data providers, data managers and data users in a fair manner. The RGD and RFD together 166 currently contain more than 31,000 relevés, which is nearly half the amount of existing relevés from the country as 167 estimated by Schaminée et al. (2009). However, our estimate exceeds Schaminée et al.’s in that there are at least 168 100,000 relevés alone of open habitats, so in short about 75% still remain to be mobilized. Thus, we hope that this 169 publication together with Indreica et al. (in press) will further stimulate researchers to contribute their data and join one 170 or the other consortium. The RGD has already become the 16th biggest member database of EVA 171 (http://euroveg.org/eva-database-participating-databases). Compared to mid-June 2015 (Chytrý et al. 2016), the two 172 national Romanian databases together have nearly tripled the density of available data from the country from 5.2 173 plots/100 km² to 13.1 plots/100 km². 174 The RGD is one of the regional databases established under the umbrella of the Eurasian Dry Grassland Group (EDGG; 175 http://www.edgg.org/; Vrahnakis et al. 2013). Other regional databases include the Balkan Dry Grassland Database 176 (BDGD; EU-00-013; http://bit.ly/2upRrDz), the German GrassVeg.DE (EU-DE-020; http://bit.ly/2qgX208; Dengler et 177 al. 2017), the Nordic-Baltic Grassland Vegetation Database (NBGVD; EU-00-002; http://bit.ly/2vzz3YT) and the multi- 178 scale database GrassPlot for high-quality, standardized data from throughout the Palaearctic biogeographic realm (EU- 179 00-003; http://bit.ly/2qKTQt2). Together these databases make a major contribution to better data availability of 180 grassland data for a multitude of analyses. They thus help to approach the ideal of a broad-scale vegetation 181 classification of Palaearctic grasslands that is data-driven and consistent (Dengler et al. 2013; Janišová et al. 2016). One 182 first such example is the high-rank classification of Pannonian-Pontic Festuco-Brometea communities by Willner et al. 183 (2017), which received data for western Romania from the predecessors of the RGD, similarly emerging more detailed 184 studies can now rely on much more extensive data from the current RGD. Also, for the recent re-classification and 185 parameterisation of EUNIS grassland habitats, the Romanian data from the RGD was essential (Schaminée et al. 2016). 186 Last but not least, we hope this paper contributes to raising the awareness of the RGD as a highly useful source for 187 studies of flora, vegetation and habitats at the national scale, including the development of a national syntaxonomic 188 scheme based on numerical analysis, similar to the achievements of the Czech Republic (Chytrý 2007) and Slovakia 189 (Janišová 2007; Jarolímek & Šibík 2008). Furthermore, the RGD is an excellent source for ecology studies as well, as 190 shown by one of the first data requests from a project intending to evaluate the ecological impact of invasive plant 191 species on Romanian grasslands. The compilation of biodiversity datasets with broad taxonomic and biogeographic 192 extents that the computation of a range of biodiversity indicators is necessary to enable better understanding of 6 193 historical processes and to project future biodiversity changes (Hudson et al. 2014). To model the future, we need to 194 examine the past (Griffin 2017) therefore the collection and preservation of digitized data is a huge responsibility. 195 When researchers learn of once-neglected data that have been revived and transformed via modern insight, they 196 themselves are more likely to recognize such hidden opportunities (Griffin 2017). The Romanian vegetation database is 197 one of these projects that not only preserves historical data, but at the same time also offers the opportunity for various 198 broader scientific purposes and activity that will benefit humankind. 199 Author contributions 200 K.V. and E.R., Deputy-custodian and Custodian of the RGD, carried out the major part of the data digitalization and 201 standardization, while S.M.H. and I.K. helped with database management. Except the latter two, all authors contributed 202 published or unpublished data in electronic or printed format. This report was drafted by K.V. with major input by E.R. 203 and J.D., while all co-authors checked, improved and approved the manuscript before submission. 204 Acknowledgements 205 K.V.’s work on the RGD was supported by two joint projects of the Eurasian Dry Grassland Group (EDGG) and the 206 European Vegetation Survey (EVS), paid for by the International Association for Vegetation Science (IAVS). 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(eds.) 297 Steppenlebensräume Europas – Gefährdung, Erhaltungsmaßnahmen und Schutz, pp. 417–434, Thüringer 298 Ministerium für Landwirtschaft, Forsten, Umwelt und Naturschutz, Erfurt, DE. 299 Willner, W., Kuzemko, A., Dengler, J., Chytrý, M., Bauer, N., Becker, T., Bita-Nicolae, C., Botta-Dukát, Z., Čarni, A., 300 (…) & Janišová, M. 2017. A higher-level classification of the Pannonian and western Pontic steppe grasslands 301 (Central and Eastern Europe). Applied Vegetation Science 20: 143−158. 9 302 Author addresses 303 Vassilev, K. (Corresponding author, kiril5914@abv.bg)1, Ruprecht, E. (eszter.ruprecht@ubbcluj.ro)2, Alexiu, V. 304 (alexiuvaleriu@gmail.com)3, Becker, T. (beckerth@uni-trier.de)4, Beldean, M. (beldean.monica@yahoo.com)2, Bita- 305 Nicolae, 306 (msjovanova@abv.bg) , Filipova, E. (eveto_filipova@abv.bg) , Frink, J.P. (jpfrink@gmail.com) , Gafta, D. 307 (dan.gafta@ubbcluj.ro)2, Georgieva, M. (meri.xai@abv.bg)9, Germany, M.S. (mgermany@ecology.uni-kiel.de)10,11, 308 Goia, I. (igoia@yahoo.com)2, Gumus, M. (med_i@abv.bg)12, Hennekens, S.M. (stephan.hennekens@wur.nl)13, 309 Janišová, M. (monika.janisova@gmail.com)14, Knollová, I. (ikuzel@sci.muni.cz)15, Koleva, V. (vikshan@abv.bg)9, 310 Kostadinova, 311 (jacqueline.loos@agr.uni-goettingen.de)17, Mardari, C. (constantin.mardari@uaic.ro)18, Michl, T. (michl@buero- 312 huck.de)19, Neblea, M.A. (monica_neb@yahoo.com)3, Nicoară, R.I. (roxanaion85@gmail.com)5, Novák, P. 313 (pavenow@seznam.cz)15, Öllerer, K. (kinga.ollerer@gmail.com)5,20, Onete, M. (marilena.onete@gmail.com)5, 314 Palpurina, 315 (hristo_pedashenko@yahoo.com)1, 316 (anamaria.roman@icbcluj.ro) , Šibík, J. (jozef.sibik@savba.sk) , Sîrbu, C. (culita69@yahoo.com) , Stancu, D. 317 (stancuileana@yahoo.com )25, Sutcliffe, L.M.E. (sutcliffe.laura@gmail.com)26, Szabó, A. (annuc19@gmail.com)2, 318 Tomescu, 319 (borislav.tzvetanov@abv.bg) , 320 (p.plamena@abv.bg)9, Velev, N. (nikolay.velev@abv.bg)1 & Dengler, J. (juergen.dengler@uni-bayreuth.de)28, 29, 30 C. (claudia.bita@ibiol.ro)5, Csergő, A.M. (csergo.anna.maria@gmail.com)6, 7 S. S. 7 (sofiq_borisova@abv.bg)9, (salza.palpurina@gmail.com)7, Pușcaș, Kuzmanović, Paulini, M. 23 C.-V. 7 (nkuzmanovic@bio.bg.ac.rs)16, (ipaulini@uni-bonn.de)21, (mihai.puscas@ubbcluj.ro)22, 14 (tomcezar@yahoo.com)27, Turtureanu, Totev, P.D. E. I. 8 N. I. Dzhovanova, Loos, J. Pedashenko, H. Roman, A. 24 (evelintotev@abv.bg)7, Tsvetanov, B. (pavel.turtureanu@ubbcluj.ro) , Vassileva, P. 22 321 322 Institute of Biodiversity and Ecosystem Research, Bulgarian Academy of Sciences, Acad. G. Bonchev str. 23, 1113 1 323 Sofia, Bulgaria 324 2 Faculty of Biology and Geology, Babeș–Bolyai University, Republicii str. 42, 400015 Cluj-Napoca, Romania 325 3 Faculty of Sciences, Physical Education and Informatics, University of Pitești, Târgul din Vale str. 1, 110040 Pitești, 326 Romania 327 4 Faculty of Geography and Geosciences, University of Trier, Behringstr. 21, 54296 Trier, Germany 328 5 Institute of Biology Bucharest, Romanian Academy, Splaiul Independenței 296, 060031 Bucharest, Romania 329 6 School of Natural Sciences, Trinity College Dublin, College Green, Dublin 2, Dublin, Ireland 330 7 Department of Ecology and Environmental Protection, Faculty of Biology, St. Kliment Ohridski University of Sofia, 331 Dragan Tzankov Blvd. 8, 1164 Sofia, Bulgaria 332 8 National Institute for Research and Development in Forestry “Marin Drăcea”, Cluj-Napoca Research Branch, Horea 333 str. 65, 400275 Cluj-Napoca, Romania 334 9 Faculty of Geology and Geography, University of Sofia “St. Kliment Ohridski”, Tzar Osvoboditel Blvd. 8, 1000 Sofia, 335 Bulgaria 336 10 Institut für Spezielle Botanik, Johannes Gutenberg Universität Mainz, 55099 Mainz, Germany 337 11 Institute for Ecosystem Research, Christian-Albrechts University of Kiel, Olshausenstr. 75, 24118 Kiel, Germany 338 12 Faculty of Biology, University of Plovdiv Paisii Hilendarski, Todor Samodumov str. 2, 4000 Plovdiv, Bulgaria 339 13 Alterra, Wageningen UR, P.O. Box 47, 6700AA, Wageningen, Netherlands 10 340 14 Institute of Botany, Plant Science and Biodiversity Center, Slovak Academy of Sciences, Institute of Botany, 341 Dúbravská cesta 9, SK-845 23, Bratislava, Slovakia 342 15 343 Republic 344 16 Institute of Botany, Faculty of Biology, University of Belgrade, Takovska 43, 11000 Belgrade, Serbia 345 17 Agroecology, University of Göttingen, Grisebachstr. 6, 37077 Göttingen, Germany 346 18 Anastasie Fătu Botanic Garden, Alexandru Ioan Cuza University, Dumbrava Roșie str. 7−9, 700487 Iași, Romania 347 19 Planungsbüro Dr. Huck, General-Colin-Powell-Str. 4a, 63571 Gelnhausen, Germany 348 20 Centre for Ecological Research, Hungarian Academy of Sciences, Alkotmány str. 2–4, 2163 Vácrátót, Hungary 349 21 350 Katzenburgweg 1, 53115 Bonn, Germany 351 22 Alexandru Borza Botanical Garden, Babeș-Bolyai University, Republicii str. 42, 400015 Cluj-Napoca, Romania 352 23 Institute of Biological Research Cluj-Napoca, Branch of the National Institute of Research and Development for Faculty of Science, Department of Botany and Zoology, Masaryk University, Kotlářská 2, 611 37 Brno, Czech Institute of Crop Science and Resource Conservation, Rheinische Friedrich-Wilhelms-Universität Bonn, 353 Biological Sciences, 48 Republicii str. 48, 400015 Cluj-Napoca, Romania 354 24 355 Mihail Sadoveanu Alley 3, 700490 Iași, Romania 356 357 25 358 Göttingen, Germany 359 27 Faculty of Forestry, “Ștefan cel Mare” University, Universității str. 13, 720229 Suceava, Romania 360 28 Vegetation Ecology Research Group, Institute of Natural Resource Sciences (IUNR), Zurich University of Applied 26 “Ion Ionescu de la Brad” University of Agricultural Sciences and Veterinary Medicine ”Ion Ionescu de la Brad”, Argeș County Museum, Armand Călinescu str. 44, 110047 Pitești, Romania Department of Plant Ecology and Ecosystems Research, University of Göttingen, Untere Karspüle 2, 37073 361 Sciences (ZHAW), Grüentalstr. 14, Postfach, 8820 Wädenswil, Switzerland 362 29 363 95447 Bayreuth, Germany 364 30 365 Germany Plant Ecology Group, Bayreuth Center of Ecology and Environmental Research (BayCEER), Universitätsstr. 30, German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, 366 367 Electronic Supplements 368 Supplementary material associated with this article is embedded in the article´s pdf. The online version of 369 Phytocoenologia 370 www.schweizerbart.com/journals/phyto. The publisher does not bear any liability for the lack of usability or correctness 371 of supplementary material. 372 Supplement S1: Data Property and Governance Rules of RGD. 373 Supplement S2: List of publications and other sources currently included in RGD. is hosted at www.ingentaconnect.com/content/schweiz/phyt and the journal’s website 11 374 7000 6000 Number of relevés 5000 4000 3000 2000 1000 20 11 -2 01 7 20 01 -2 01 0 19 91 -2 00 0 19 81 -1 99 0 19 71 -1 98 0 19 61 -1 97 0 19 51 -1 96 0 19 41 -1 95 0 < 19 40 0 375 376 377 Fig. 1. Temporal distribution of relevés currently contained in the Romanian Grassland Database. 12 378 379 380 Fig. 2. Spatial distribution of the vegetation plots currently contained in the Romanian Grassland Database, shown as 381 density of plots with geographic coordinates in square grids of 100 km². 382 13 383 Table. 1. Frequency of different phytosociological classes among the relevés in the Romanian Grassland Database, 384 grouped into several broad types. Statistics are based on the 17,747 relevés that currently have a phytosociological 385 assignment. The typology of classes follows Sanda et al. (2008). Code Class name Number of orders Number of alliances Number of associations & communities Number of relevés 01 Lemnetea 3 4 12 400 02 Charetea fragilis 2 5 8 99 04 Ruppietea maritimae - - - 4 05 Potamogenetea pectinati 2 4 23 560 06 Littorelletea uniflorae 1 1 1 12 07 Isoeto-Nanojuncetea 2 2 7 59 08 Phragmito-Magnocaricetea 5 6 43 1,584 09 Montio-Cardaminetea 1 3 7 215 10 Scheuchzerio-Caricetea nigrae 3 5 14 574 11 Oxycocco-Sphagnetea 1 1 2 71 Total Wetland vegetation 20 31 117 3,578 12 Festucetea vaginatae 1 3 6 131 13 Puccinellio-Salicornietea 3 6 22 566 14 Juncetea maritimi 1 2 4 55 16 Ammophiletea 1 1 2 11 23 Nardo-Callunetea 1 2 4 764 27 Molinio-Arrhenatheretea 4 9 38 2,256 28 Festuco-Brometea 4 9 46 2,582 29 Koelerio-Corynephoretea 3 3 7 125 35 Trifolio-Geranietea sanguinei 2 3 4 80 20 38 133 6,570 Total Grassland vegetation of lowlands 19 Asplenietea trichomanis 3 7 22 569 20 Thlaspietea rotundifolii 3 4 16 415 21 Salicetea herbaceae 2 3 12 299 22 2 2 8 896 24 Juncetea trifidi Carici rupestris-Kobresietea bellardi 1 1 2 44 25 Seslerietea albicantis 1 3 13 753 26 Betulo-Adenostyletea 1 3 12 321 13 23 85 3,297 Total Subalpine and alpine vegetation 15 Cakiletea maritimae 2 2 5 43 18 Bidentetea tripartiti 1 2 8 142 30 Stellarietea mediae 4 13 27 966 31 Plantaginetea majoris 1 3 6 180 32 Artemisietea vulgaris 3 7 25 449 33 Galio-Urticetea 2 5 17 298 34 Epilobietea angustifolii 2 3 7 206 15 35 95 2,284 2 4 5 22 Total 36 Ruderal and segetal vegetation Salicetea purpureae 14 386 37 Alnetea glutinosae 2 2 2 21 38 Querco-Fagetea 1 2 9 82 39 Querco pubescenti-petreae 1 3 6 146 40 Rhamno-Prunetea 1 2 2 50 41 Erico-Pinetea 1 1 1 26 42 Vaccinio-Piceetea 5 7 12 764 13 21 37 1,111 - - - 907 81 148 467 17,747 Total Woodland vegetation Total Cryptogam-dominated vegetation Grand total 15