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8 results on '"vegetation database"'

1. Probabilistic and preferential sampling approaches offer integrated perspectives of Italian forest diversity

Author

Alessi, Nicola, Bonari, Gianmaria, Zannini, Piero, Jiménez‐Alfaro, Borja, Agrillo, Emiliano, Attorre, Fabio, Canullo, Roberto, Casella, Laura, Cervellini, Marco, Chelli, Stefano, Di&nbsp, Musciano, Michele, Guarino, Riccardo, Martellos, Stefano, Massimi, Marco, Venanzoni, Roberto, Zerbe, Stefan, Chiarucci, Alessandro, Alessi, Nicola, Bonari, Gianmaria, Zannini, Piero, Jiménez‐Alfaro, Borja, Agrillo, Emiliano, Attorre, Fabio, Canullo, Roberto, Casella, Laura, Cervellini, Marco, Chelli, Stefano, Di Musciano, Michele, Guarino, Riccardo, Martellos, Stefano, Massimi, Marco, Venanzoni, Roberto, Zerbe, Stefan, Chiarucci, Alessandro, Alessi N., Bonari G., Zannini P., Jimenez-Alfaro B., Agrillo E., Attorre F., Canullo R., Casella L., Cervellini M., Chelli S., DiMusciano M., Guarino R., Martellos S., Massimi M., Venanzoni R., Zerbe S., and Chiarucci A.

Subjects
spatially constrained rarefaction curve, Ecology, co-occurrence data, detrended correspondence analysis, regional survey, temperate forests, vegetation database, indicator species analysis, biodiversity, co-occurrence data, detrended correspondence analysis, indicator species analysis, regional survey, spatially constrained rarefaction curve, temperate forests, vegetation database, zonal vegetation, Plant Science, zonal vegetation, biodiversity
Abstract

Aim: Assessing the performances of different sampling approaches for documenting community diversity may help to identify optimal sampling efforts and strategies, and to enhance conservation and monitoring planning. Here, we used two data sets based on probabilistic and preferential sampling schemes of Italian forest vegetation to analyze the multifaceted performances of the two approaches across three major forest types at a large scale. Location: Italy. Methods: We pooled 804 probabilistic and 16,259 preferential forest plotsassamplesofvascularplantdiversity across the country. We balanced the two data sets in terms of sizes, plot size, geographical position, and vegetation types. For each of the two data sets, 1000 subsets of 201 random plots were compared by calculating the shared and exclusive indicator species, their overlap in the multivariate space, and the areas encompassed by spatially-constrained rarefaction curves. We then calculated an index of performance using the ratio between the additional and total information collected by each sampling approach. The performances were tested and evaluated across the three major forest types. Results: The probabilistic approach performed better in estimating species richness and diversity of species assemblages, but did not detect other components of the regional diversity, such as azonal forests. The preferential approach outperformed the probabilistic approach in detecting forest-specialist species and plant diversity hotspots. Conclusions: Using a novel workflow based on vegetation-plot exclusivities and commonalities, our study suggests probabilistic and preferential sampling approaches are to be used in combination for better conservation and monitor planning purposes to detect multiple aspects of plant community diversity. Our findings can assist the implementation of national conservation planning and large-scale monitoring of biodiversity.

Published
2023

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

Abstract

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

Published
2020

3. EUNIS Habitat Classification : expert system, characteristic species combinations and distribution maps of European habitats

Abstract

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 ex

Published
2020

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

Abstract

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

Published
2020

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

Abstract

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

Published
2020

6. EUNIS Habitat Classification : expert system, characteristic species combinations and distribution maps of European habitats

Abstract

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 ex

Published
2020

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

Author

Ioannis Tsiripidis, Dmytro Dubyna, Emin Uğurlu, Federico Fernández-González, Svetlana Aćić, Valerijus Rašomavičius, Anna Kuzemko, Jiří Danihelka, Wolfgang Willner, Christian Berg, Mirjana Ćuk, Pavel Dan Turtureanu, Erwin Bergmeier, Aaron Pérez-Haase, Vadim Prokhorov, Deniz Işık Gürsoy, Zoltán Botta-Dukát, Hristo Pedashenko, John Janssen, Martin Kleikamp, Thomas Wohlgemuth, Martin Jiroušek, S. M. Yamalov, Viktor Onyshchenko, Ilona Knollová, Urban Šilc, Jörg Ewald, Henry Brisse, Xavier Font, Didem Ambarlı, John S. Rodwell, Andraž Čarni, Tatiana Rogova, Lynda Weekes, Solvita Rūsiņa, Gunnar Seidler, Tetiana Dziuba, Milan Chytrý, Desislava Sopotlieva, Risto Virtanen, Nikolai Ermakov, Riccardo Guarino, Maria Pilar Rodríguez-Rojo, Florian Jansen, Michele De Sanctis, Zygmunt Kącki, Domas Uogintas, Itziar García-Mijangos, Ute Jandt, Jürgen Dengler, Úna FitzPatrick, Jens-Christian Svenning, Eszter Ruprecht, Idoia Biurrun, Kiril Vassilev, Borja Jiménez-Alfaro, Stephan M. Hennekens, Tomáš Peterka, Laura Casella, Zvjezdana Stančić, Jonathan Lenoir, Iva Apostolova, Flavia Landucci, Milan Valachovič, Fabio Attorre, Joop H.J. Schaminée, Renata Ćušterevska, Corrado Marcenò, Valentin Golub, Grzegorz Swacha, János Csiky, Patrice de Ruffray, Tatiana Lysenko, Vitaliy Kolomiychuk, Rense Haveman, Luis Carlón, Emiliano Agrillo, Ali Kavgaci, W. Bernhard Dickoré, Els De Bie, Željko Škvorc, Vassiliy Martynenko, Dana Michalcová, Roberto Venanzoni, Rosario G. Gavilán, Jesper Erenskjold Moeslund, Pierangela Angelini, Giuliano Fanelli, Jozef Šibík, Juan Antonio Campos, Yulia Vashenyak, Rasmus Ejrnæs, Adrian Indreica, Panayotis Dimopoulos, Daniel Krstonošić, Zora Dajić Stevanović, Chytrý, M., Hennekens, S., Jiménez-Alfaro, B., Knollová, I., Dengler, J., Jansen, F., Landucci, F., Schaminée, J., Aćić, S., Agrillo, E., Ambarlı, D., Angelini, P., Apostolova, I., Attorre, F., Berg, C., Bergmeier, E., Biurrun, I., Botta-Dukát, Z., Brisse, H., Campos, J., Carlón, L., Čarni, A., Casella, L., Csiky, J., Ćušterevska, R., Dajić Stevanović, Z., Danihelka, J., De Bie, E., de Ruffray, P., De Sanctis, M., Dickoré, W., Dimopoulos, P., Dubyna, D., Dziuba, T., Ejrnaes, R., Ermakov, N., Ewald, J., Fanelli, G., Fernández-González, F., Fitzpatrick, Ú., Font, X., García-Mijangos, I., Gavilán, R., Golub, V., Guarino, R., Haveman, R., Indreica, A., Işık Gürsoy, D., Jandt, U., Janssen, J., Jiroušek, M., Kącki, Z., Kavgacı, A., Kleikamp, M., Kolomiychuk, V., Krstivojević Ćuk, M., Krstonošić, D., Kuzemko, A., Lenoir, J., Lysenko, T., Marcenò, C., Martynenko, V., Michalcová, D., Moeslund, J., Onyshchenko, V., Pedashenko, H., Pérez-Haase, A., Peterka, T., Prokhorov, V., Rašomavičius, V., Rodríguez-Rojo, M., Rodwell, J., Rogova, T., Ruprecht, E., Rūsiņa, S., Seidler, G., Šibík, J., Šilc, U., Škvorc, Ž., Sopotlieva, D., Stančić, Z., Svenning, J., Swacha, G., Tsiripidis, I., Turtureanu, P., Uğurlu, E., Uogintas, D., Valachovič, M., Vashenyak, Y., Vassilev, K., Venanzoni, R., Virtanen, R., Weekes, L., Willner, W., Wohlgemuth, T., Yamalov, S., and Universitat de Barcelona

Subjects
0106 biological sciences, International Association for Vegetation Science, Bos- en Landschapsecologie, Ecoinformatic, 01 natural sciences, Ecoinformatics, Forest and Landscape Ecology, Vegetació, Ecology, Environmental resource management, PE&RC, Vegetation plot, Europe, Centralized database, Geography, Cartografia de la vegetació, Plantenecologie en Natuurbeheer, Vegetatie, Bos- en Landschapsecologie, medicine.symptom, Geographic coordinate system, Europa, Releve, Plant Ecology and Nature Conservation, European Vegetation Survey, Management, Monitoring, Policy and Law, Biodiversity informatics, 010603 evolutionary biology, Plot (graphics), Relevé, Database, Phytosociological data, Vegetation database, medicine, biodiversity informatics, database, ecoinformatics, european vegetation survey, international association for vegetation science, phytosociological data, relevé, vegetation database, vegetation plot, ecology, nature and landscape conservation, management, monitoring, policy and law, Vegetatie, Nature and Landscape Conservation, Vegetation mapping, Vegetation, business.industry, 15. Life on land, Defensie, Taxon, Biodiversity informatic, Integrated database, Vegetation, Forest and Landscape Ecology, business, Vegetation (pathology), 010606 plant biology & botany
Abstract

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/0000-0001-8621-0890 WOS: 000368074600018 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. 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).

Published
2016

8. EUNIS Habitat Classification : expert system, characteristic species combinations and distribution maps of European habitats

Author

Chytrý, Milan, Tichý, Lubomír, Hennekens, Stephan M., Knollová, Ilona, Janssen, John A. M., Rodwell, John S., Peterka, Tomáš, Marcenò, Corrado, Landucci, Flavia, Danihelka, Jiří, Hájek, Michal, Dengler, Jürgen, Novák, Pavel, Zukal, Dominik, Jiménez‐Alfaro, Borja, Mucina, Ladislav, Abdulhak, Sylvain, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Ćuk, Mirjana, Ćušterevska, Renata, De Bie, Els, Delbosc, Pauline, Demina, Olga, Didukh, Yakiv, Dítě, Daniel, Dziuba, Tetiana, Ewald, Jörg, Gavilán, Rosario G., Gégout, Jean‐Claude, Giusso del Galdo, Gian Pietro, Golub, Valentin, Goncharova, Nadezhda, Goral, Friedemann, Graf, Ulrich, Indreica, Adrian, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jansen, Jan, Jašková, Anni, Jiroušek, Martin, Kącki, Zygmunt, Kalníková, Veronika, Kavgacı, Ali, Khanina, Larisa, Yu. Korolyuk, Andrey, Kozhevnikova, Mariya, Kuzemko, Anna, Küzmič, Filip, Kuznetsov, Oleg L., Laiviņš, Māris, Lavrinenko, Igor, Lavrinenko, Olga, Lebedeva, Maria, Lososová, Zdeňka, Lysenko, Tatiana, Maciejewski, Lise, Mardari, Constantin, Marinšek, Aleksander, Napreenko, Maxim G., Onyshchenko, Viktor, Pérez‐Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Rodríguez Rojo, Maria Pilar, Rūsiņa, Solvita, Schrautzer, Joachim, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smagin, Viktor A., Stančić, Zvjezdana, Stanisci, Angela, Tikhonova, Elena, Tonteri, Tiina, Uogintas, Domas, Valachovič, Milan, Vassilev, Kiril, Vynokurov, Denys, Willner, Wolfgang, Yamalov, Sergey, Evans, Douglas, Palitzsch Lund, Mette, Spyropoulou, Rania, Tryfon, Eleni, and Schaminée, Joop H. J.

Subjects
Coastal habitat, Distribution map, 15. Life on land, Dune vegetation, Grassland, Habitat classification, Vegetation plot, Shrubland, Diagnostic species, Man‐made habitat, Vegetation database, Wetland, 14. Life underwater, Forest, 577: Ökologie, European Nature Information System (EUNIS), Expert system, European Vegetation Archive (EVA)
Abstract

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 EUNISESy. The data provided and the expert system have considerable potential for future use in European nature conservation planning, monitoring and assessment.

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