Formalized classification of semi-dry grasslands in central and eastern Europe

European semi-dry grasslands are among the most species-rich vegetation types in the northern hemisphere and form an important part of the habitat mosaics in the forest-steppe zone. However. there is no comprehensive evaluation of the variation in their composition and the phytosocio-logical classification of these grasslands. For the syntaxonomic revision, we used a dataset of 34,173 vegetation plot records (releves) from central and eastern Europe. which were assigned to the class Fesiuco-Bromeiea using the diagnostic species listed in the EuroVegChecklist. To determine the diagnostic species of the orders, we used a TWINSPAN classification of the whole dataset. Of the total dataset, 15,449 releves were assigned to the order Brachypodietalia pinnati. which corresponds to semi-dry grasslands. This subset was again classified using TWINSPAN. Formal definitions of the following alliances were established: Mesobromion erecti, Cirsio-Brachypodion pinnati (incl. Fragario-Trifolion montani. Agrosiio-Avenulion schellianae, Scabioso ochroleucae-Poion angustifoliae and Adonido vernalis-Stipion iirsae), Scorzonerion villosae and Chrysopogono-Danshonion. Another alliance, Armerion elongatae (=Koelerio-Phleion phleoidis p.p.). is transitional towards the class Koelerio-Corynephoreiea and its status needs further evaluation. We also established formal definitions of all of the associations of Mesobromion and Cirsio-Brachypodion within the area studied. Associations were identified using (i) a TWINSPAN classification of the whole order, (ii) TWINSPAN classifications of regionally restricted data sets (usually all Brachypodietalia plots in one country) and (iii) existing national classification schemes. All formal definitions were written in the expert system language of the JUICE program. To obtain a more complete picture of the floristic similarities and gradients. we performed a DCA ordination of the associations. Our results revealed that meadow steppes in the forest-steppe zone in eastern Europe are very similar to semi-dry grasslands in central Europe

sPlotOpen – An environmentally balanced, open-access, global dataset of vegetation plots

Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ?sPlot?, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained: Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain: Global, 0.01?40,000 m². Time period and grain: 1888-2015, recording dates. Major taxa and level of measurement: 42,677 vascular plant taxa, plot-level records.Fil: Sabatini, Francesco Maria. Martin-universität Halle-wittenberg; Alemania. German Centre For Integrative Biodiversity Research (idiv) Halle-jena-leipzig; AlemaniaFil: Lenoir, Jonathan. Université de Picardie Jules Verne; FranciaFil: Hattab, Tarek. Université de Montpellier; FranciaFil: Arnst, Elise Aimee. Manaaki Whenua - Landcare Research; Nueva ZelandaFil: Chytrý, Milan. Masaryk University; República ChecaFil: Giorgis, Melisa Adriana. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Córdoba. Instituto Multidisciplinario de Biología Vegetal. Universidad Nacional de Córdoba. Facultad de Ciencias Exactas Físicas y Naturales. Instituto Multidisciplinario de Biología Vegetal; ArgentinaFil: Vanselow, Kim André. University of Erlangen-Nuremberg; AlemaniaFil: Vásquez Martínez, Rodolfo. Jardín Botánico de Missouri Oxapampa; PerúFil: Vassilev, Kiril. Bulgarian Academy of Sciences; BulgariaFil: Vélez-Martin, Eduardo. ILEX Consultoria Científica; BrasilFil: Venanzoni, Roberto. University of Perugia; ItaliaFil: Vibrans, Alexander Christian. Universidade Regional de Blumenau; BrasilFil: Violle, Cyrille. Paul Valéry Montpellier University; FranciaFil: Virtanen, Risto. German Centre for Integrative Biodiversity Research; AlemaniaFil: von Wehrden, Henrik. Leuphana University of Lüneburg; AlemaniaFil: Wagner, Viktoria. University of Alberta; CanadáFil: Walker, Donald A.. University of Alaska; Estados UnidosFil: Waller, Donald M.. University of Wisconsin-Madison; Estados UnidosFil: Wang, Hua-Feng. Hainan University; ChinaFil: Wesche, Karsten. Senckenberg Museum of Natural History Görlitz; Alemania. Technische Universität Dresden; AlemaniaFil: Whitfeld, Timothy J. S.. University of Minnesota; Estados UnidosFil: Willner, Wolfgang. University of Vienna; AustriaFil: Wiser, Susan K.. Manaaki Whenua. Landcare Research; Nueva ZelandaFil: Wohlgemuth, Thomas. Swiss Federal Institute for Forest, Snow and Landscape Research; SuizaFil: Yamalov, Sergey. Russian Academy of Sciences; RusiaFil: Zobel, Martin. University of Tartu; EstoniaFil: Bruelheide, Helge. German Centre for Integrative Biodiversity Research; Alemani

Climate-trait relationships exhibit strong habitat specificity in plant communities across Europe

Ecological theory predicts close relationships between macroclimate and functional traits. Yet, global climatic gradients correlate only weakly with the trait composition of local plant communities, suggesting that important factors have been ignored. Here, we investigate the consistency of climate-trait relationships for plant communities in European habitats. Assuming that local factors are better accounted for in more narrowly defined habitats, we assigned > 300,000 vegetation plots to hierarchically classified habitats and modelled the effects of climate on the community-weighted means of four key functional traits using generalized additive models. We found that the predictive power of climate increased from broadly to narrowly defined habitats for specific leaf area and root length, but not for plant height and seed mass. Although macroclimate generally predicted the distribution of all traits, its effects varied, with habitat-specificity increasing toward more narrowly defined habitats. We conclude that macroclimate is an important determinant of terrestrial plant communities, but future predictions of climatic effects must consider how habitats are defined

EUNIS Habitat Classification: Expert system, characteristic species combinations and distribution maps of European habitats

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

Distribution maps of vegetation alliances in Europe

Aim: The first comprehensive checklist of European phytosociological alliances, orders and classes (EuroVegChecklist) was published by Mucina et al. (2016, Applied Vegetation Science, 19 (Suppl. 1), 3–264). However, this checklist did not contain detailed information on the distribution of individual vegetation types. Here we provide the first maps of all alliances in Europe. Location: Europe, Greenland, Canary Islands, Madeira, Azores, Cyprus and the Caucasus countries. Methods: We collected data on the occurrence of phytosociological alliances in European countries and regions from literature and vegetation-plot databases. We interpreted and complemented these data using the expert knowledge of an international team of vegetation scientists and matched all the previously reported alliance names and concepts with those of the EuroVegChecklist. We then mapped the occurrence of the EuroVegChecklist alliances in 82 territorial units corresponding to countries, large islands, archipelagos and peninsulas. We subdivided the mainland parts of large or biogeographically heterogeneous countries based on the European biogeographical regions. Specialized alliances of coastal habitats were mapped only for the coastal section of each territorial unit. Results: Distribution maps were prepared for 1,105 alliances of vascular-plant dominated vegetation reported in the EuroVegChecklist. For each territorial unit, three levels of occurrence probability were plotted on the maps: (a) verified occurrence; (b) uncertain occurrence; and (c) absence. The maps of individual alliances were complemented by summary maps of the number of alliances and the alliance–area relationship. Distribution data are also provided in a spreadsheet. Conclusions: The new map series represents the first attempt to characterize the distribution of all vegetation types at the alliance level across Europe. There are still many knowledge gaps, partly due to a lack of data for some regions and partly due to uncertainties in the definition of some alliances. The maps presented here provide a basis for future research aimed at filling these gaps

European Vegetation Archive (EVA): an integrated database of European vegetation plots

Biurrun, Idoia/0000-0002-1454-0433; Rojo, Maria Pilar Rodriguez/0000-0001-5449-9386; Ermakov, Nikolai/0000-0001-7550-990X; De Sanctis, Michele/0000-0002-7280-6199; Svenning, Jens-Christian/0000-0002-3415-0862; Virtanen, Risto/0000-0002-8295-8217; Agrillo, Emiliano/0000-0003-2346-8346; Onyshchenko, Viktor/0000-0001-9079-7241; Marceno, Corrado/0000-0003-4361-5200; Willner, Wolfgang/0000-0003-1591-8386; Fernandez-Gonzalez, Federico/0000-0003-1234-4065; Jansen, Florian/0000-0002-0331-5185; Swacha, Grzegorz/0000-0002-6380-2954; Dengler, Jurgen/0000-0003-3221-660X; Guarino, Riccardo/0000-0003-0106-9416; Sopotlieva, Desislava/0000-0002-9281-7039; Venanzoni, Roberto/0000-0002-7768-0468; Chytry, Milan/0000-0002-8122-3075; Kuzemko, Anna/0000-0002-9425-2756; Danihelka, Jiri/0000-0002-2640-7867; Kuzemko, Anna/0000-0002-9425-2756; Venanzoni, Roberto/0000-0002-7768-0468; Gavilan, Rosario G./0000-0002-1022-445X; Jansen, Florian/0000-0002-0331-5185; Wohlgemuth, Thomas/0000-0002-4623-0894; Svenning, Jens-Christian/0000-0002-3415-0862; Sibik, Jozef/0000-0002-5949-862X; Casella, Laura/0000-0003-2550-3010; Lenoir, Jonathan/0000-0003-0638-9582; Attorre, Fabio/0000-0002-7744-2195; Kacki, Zygmunt/0000-0002-2241-1631; Jandt, Ute/0000-0002-3177-3669; Carni, Andraz/0000-0002-8909-4298; Jirousek, Martin/0000-0002-4293-478X; GARCIA-MIJANGOS, ITZIAR/0000-0002-6642-7782; Campos, Juan Antonio/0000-0001-5992-2753; Fanelli, Giuliano/0000-0002-3143-1212; Haveman, Rense/0000-0001-9127-4549; Acic, Svetlana/0000-0001-6553-3797; De Bie, Els/0000-0001-7679-743X; Font, Xavier/0000-0002-7253-8905; Moeslund, Jesper Erenskjold/0000-0001-8591-7149; Martynenko, Vasiliy/0000-0002-9071-3789; Jimenez-Alfaro, Borja/0000-0001-6601-9597; Ejrnaes, Rasmus/0000-0003-2538-8606; Carlon Ruiz, Luis/0000-0003-3442-8710; Angelini, Pierangela/0000-0002-5321-9757; Silc, Urban/0000-0002-3052-699X; Landucci, Flavia/0000-0002-6848-0384; Ewald, Jorg/0000-0002-2758-9324; Dziuba, Tetiana/0000-0001-8621-0890WOS: 000368074600018The 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.Czech Science Foundation (Centre of Excellence PLADIAS) [14-36079G]Our major thanks go to thousands of European vegetation scientists of several generations who collected the original vegetation-plot data in the field, published them or made their unpublished data available to others, and to those who spent myriad hours digitizing data and managing the contributing databases. EVA data management has been partly funded by the Czech Science Foundation (Centre of Excellence PLADIAS, 14-36079G)

sPlotOpen - An environmentally balanced, open-access, global dataset of vegetation plots

Motivation Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called 'sPlot', compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain Global, 0.01-40,000 m(2). Time period and grain 1888-2015, recording dates. Major taxa and level of measurement 42,677 vascular plant taxa, plot-level records. Software format Three main matrices (.csv), relationally linked

Climate and socio- economic factors explain differences between observed and expected naturalization patterns of European plants around the world

The number of naturalized (i.e. established) alien species has increased rapidly over recent centuries. Given the differences in environmental tolerances among species, little is known about what factors determine the extent to which the observed size of the naturalized range of a species and hence the extent to which the observed richness of naturalized species of a region approach their full potential. Here, we asked which region- and species-specific characteristics explain differences between observed and expected naturalizations. Location: Global. Time period: Present. Major taxa studied: Vascular plants. Methods: We determined the observed naturalized distribution outside Europe for 1,485 species endemic to Europe using the Global Naturalized Alien Flora (GloNAF) database and their expected distributions outside Europe using species distribution models. First, we investigated which of seven socio-economic factors related to introduction pathways, anthropogenic pressures and inventory effort best explained the differences between observed and expected naturalized European floras. Second, we examined whether distributional features, economic use and functional traits explain the extent to which species have filled their expected ranges outside Europe. Results: In terms of suitable area, more than 95% of expected naturalizations of European plants were not yet observed. Species were naturalized in only 4.2% of their suitable regions outside of Europe (range filling) and in 0.4% of their unsuitable regions (range expansion). Anthropogenic habitat disturbance primarily explained the difference between observed and expected naturalized European floras, as did the number of treaties relevant to invasive species. Species of ornamental and economic value and with large specific leaf area performed better at filling and expanding beyond their expected range. Main conclusions: The naturalization of alien plant species is explained by climate matching but also by the regional level of human development, the introduction pressure associated with the ornamental and economic values of the species and their adaptation to disturbed environments

European vegetation archive (EVA). An integrated database of European vegetation plots

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

sPlot - A new tool for global vegetation analyses

Dengler, Jurgen/0000-0003-3221-660X; Chytry, Milan/0000-0002-8122-3075; de Gasper, Andre Luis/0000-0002-1940-9581; Marceno, Corrado/0000-0003-4361-5200; Swacha, Grzegorz/0000-0002-6380-2954; He, Tianhua/0000-0002-0924-3637; Haider, Sylvia/0000-0002-2966-0534; Kuhn, Ingolf/0000-0003-1691-8249; Svenning, Jens-Christian/0000-0002-3415-0862; Jansen, Florian/0000-0002-0331-5185; Casella, Laura/0000-0003-2550-3010; Schmidt, Marco/0000-0001-6087-6117; Chepinoga, Victor/0000-0003-3809-7453; Petrik, Petr/0000-0001-8518-6737; Willner, Wolfgang/0000-0003-1591-8386; Jansen, Steven/0000-0002-4476-5334; De Sanctis, Michele/0000-0002-7280-6199; Niinemets, Ulo/0000-0002-3078-2192; Pauchard, Anibal/0000-0003-1284-3163; Vibrans, Alexander C./0000-0002-8789-5833; Biurrun, Idoia/0000-0002-1454-0433; De Patta Pillar, Valerio/0000-0001-6408-2891; Phillips, Oliver L/0000-0002-8993-6168; Sibik, Jozef/0000-0002-5949-862X; Lenoir, Jonathan/0000-0003-0638-9582; Venanzoni, Roberto/0000-0002-7768-0468; Gutierrez, Alvaro G./0000-0001-8928-3198; Cayuela, Luis/0000-0003-3562-2662; Nobis, Marcin/0000-0002-1594-2418; Agrillo, Emiliano/0000-0003-2346-8346; Manning, Peter/0000-0002-7940-2023; Venanzoni, Roberto/0000-0002-7768-0468; Virtanen, Risto/0000-0002-8295-8217; Higuchi, Pedro/0000-0002-3855-555X; Sopotlieva, Desislava/0000-0002-9281-7039; Kuzemko, Anna/0000-0002-9425-2756; Hatim, Mohamed/0000-0002-0872-5108; Mencuccini, Maurizio/0000-0003-0840-1477; Enquist, Brian J./0000-0002-6124-7096; De Bie, Els/0000-0001-7679-743X; Samimi, Cyrus/0000-0001-7001-7893; Nowak, Arkadiusz/0000-0001-8638-0208; Jimenez-Alfaro, Borja/0000-0001-6601-9597; Font, Xavier/0000-0002-7253-8905; Levesley, Aurora/0000-0002-7999-5519; Acic, Svetlana/0000-0001-6553-3797; Kattge, Jens/0000-0002-1022-8469; Silc, Urban/0000-0002-3052-699X; Arnst, Elise/0000-0003-2388-7428; Moretti, Marco/0000-0002-5845-3198; Kozub, Lukasz/0000-0002-6591-8045; Kacki, Zygmunt/0000-0002-2241-1631; Fagundez, Jaime/0000-0001-6605-7278; Purschke, Oliver/0000-0003-0444-0882; Martynenko, Vasiliy/0000-0002-9071-3789; Jandt, Ute/0000-0002-3177-3669; Peyre, Gwendolyn/0000-0002-1977-7181; SABATINI, FRANCESCO MARIA/0000-0002-7202-7697; Bruelheide, Helge/0000-0003-3135-0356; Wohlgemuth, Thomas/0000-0002-4623-0894; Onyshchenko, Viktor/0000-0001-9079-7241; Kuzmic, Filip/0000-0002-3894-7115; Ejrnaes, Rasmus/0000-0003-2538-8606; Jirousek, Martin/0000-0002-4293-478X; Noroozi, Jalil/0000-0003-4124-2359; Curran, Michael/0000-0002-1858-5612; Baraloto, Christopher/0000-0001-7322-8581; Ozinga, Wim/0000-0002-6369-7859WOS: 000466421500001Aims 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.German Research FoundationGerman Research Foundation (DFG) [DFG FZT 118]; TRY initiative on plant traitsWe are grateful to thousands of vegetation scientists who sampled vegetation plots in the field or digitized them into regional, national or international databases. We also appreciate the support of the German Research Foundation for funding sPlot as one of the iDiv (DFG FZT 118) research platforms, and the organization of three workshops through the sDiv calls. We acknowledge this support with naming the database "sPlot", where the "s" refers to the sDiv synthesis workshops. The study was supported by the TRY initiative on plant traits (http://www.try-db.org). For all further acknowledgements see Appendix S10. We thank Meelis Partel for his very fast and constructive feedback on an earlier version of this manuscript