Maps of mean relative species richness of vascular plant families in European vegetation

  1. Večeřa, Martin 1
  2. Axmanová, Irena 1
  3. Cubino, Josep Padullés 1
  4. Lososová, Zdeňka 1
  5. Divíšek, Jan 2
  6. Knollová, Ilona 1
  7. Aćić, Svetlana 3
  8. Biurrun, Idoia 4
  9. Boch, Steffen 5
  10. Bonari, Gianmaria 6
  11. Campos, Juan Antonio 4
  12. Čarni, Andraž 7
  13. Carranza, Maria Laura 8
  14. Casella, Laura 9
  15. Chiarucci, Alessandro 10
  16. Ćušterevska, Renata 11
  17. Delbosc, Pauline 12
  18. Dengler, Jürgen 13
  19. Fernández-González, Federico 14
  20. Gégout, Jean-Claude 15
  21. Jandt, Ute 16
  22. Jansen, Florian 17
  23. Jašková, Anni 1
  24. Jiménez-Alfaro, Borja 18
  25. Kuzemko, Anna 19
  26. Lebedeva, Maria 20
  27. Lenoir, Jonathan 21
  28. Lysenko, Tatiana 22
  29. Moeslund, Jesper Erenskjold 23
  30. Pielech, Remigiusz 24
  31. Ruprecht, Eszter 25
  32. Šibík, Jozef 26
  33. Šilc, Urban 27
  34. Škvorc, Željko 28
  35. Swacha, Grzegorz 29
  36. Tatarenko, Irina 30
  37. Vassilev, Kiril 31
  38. Wohlgemuth, Thomas 32
  39. Yamalov, Sergey 20
  40. Chytrý, Milan 1
  41. Mostrar todos os autores +
  1. 1 Department of Botany and Zoology, Faculty of Science, Masaryk University, Brno, Czech Republic
  2. 2 Department of Botany and Zoology, Faculty of Science, Masaryk University, Brno, Czech Republic; Department of Geography, Faculty of Science, Masaryk University, Brno, Czech Republic
  3. 3 Department of Botany, Faculty of Agriculture, University of Belgrade, Belgrade-Zemun, Serbia
  4. 4 Department of Plant Biology and Ecology, Faculty of Science and Technology, University of the Basque Country UPV/EHU, Leioa, Spain
  5. 5 Biodiversity and Conservation Biology Research Unit, WSL Swiss Federal Research Institute, Birmensdorf, Switzerland
  6. 6 Faculty of Science and Technology, Free University of Bozen-Bolzano, Bolzano, Italy
  7. 7 Research Center of the Slovenian Academy of Sciences and Arts, Institute of Biology, Ljubljana, Slovenia; University of Nova Gorica, School for Viticulture and Enology, Vipava, Slovenia
  8. 8 Department of Bioscience and Territory (Envixlab), University of Molise, Campobasso, Italy
  9. 9 ISPRA - Italian National Institute for Environmental Protection and Research
  10. 10 BIOME Lab, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum - University of Bologna
  11. 11 Institute of Biology, Faculty of Natural Sciences and Mathematics, University of Ss. Cyril and Methodius, Skopje, North Macedonia
  12. 12 EA 7462 Géoarchitecture, Université de Bretagne Occidentale UFR Sciences et Techniques, Brest, France
  13. 13 Vegetation Ecology, Institute of Natural Resource Sciences (IUNR), Zurich University of Applied Sciences (ZHAW), Wädenswil, Switzerland; Plant Ecology, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Bayreuth, Bayreuth, Germany; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany
  14. 14 Institute of Environmental Sciences, University of Castilla-La Mancha, Toledo, Spain
  15. 15 Université de Lorraine, AgroParisTech, INRAE, Silva, Nancy, France
  16. 16 German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Leipzig, Germany; Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Halle, Germany
  17. 17 Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany
  18. 18 Research Unit of Biodiversity (CSIC, UO, PA), Oviedo University, Mieres, Spain
  19. 19 Department of Geobotany and Ecology, M.G. Kholodny Institute of Botany, NAS of Ukraine, Kyiv, Ukraine
  20. 20 South Ural Botanical Garden-Institute, Ufa, Russian Federation
  21. 21 Ecologie et Dynamique des Systèmes Anthropisés (EDYSAN, UMR 7058 CNRS), Université de Picardie Jules Verne, Amiens, France
  22. 22 Laboratory of Vegetation Science, Komarov Botanical Institute RAS, Saint-Petersburg, Russian Federation; Laboratory of Phytodiversity Problems, Institute of Ecology of the Volga River Basin RAS - Branch of the Samara Scientific Center RAS, Togliatti, Russian Federation
  23. 23 Department of Bioscience, Faculty of Technical Sciences, Aarhus University, Aarhus, Denmark
  24. 24 Department of Forest Biodiversity, Faculty of Forestry, University of Agriculture in Kraków, Kraków, Poland; Foundation for Biodiversity Research, Wrocław, Poland
  25. 25 Hungarian Department of Biology and Ecology, Faculty of Biology and Geology, Babeș-Bolyai University, Cluj-Napoca, Romania
  26. 26 Plant Science and Biodiversity Center, Slovak Academy of Sciences, Bratislava, Slovakia
  27. 27 Research Center of the Slovenian Academy of Sciences and Arts, Institute of Biology, Ljubljana, Slovenia
  28. 28 Faculty of Forestry, University of Zagreb, Zagreb, Croatia
  29. 29 Botanical Garden, University of Wrocław, Wrocław, Poland
  30. 30 School of Environment, Earth and Ecosystem Sciences, Faculty of STEM, Open University, UK
  31. 31 Department of Plant and Fungal Diversity and Resources, Institute of Biodiversity and Ecosystem Research, Bulgarian Academy of Sciences, Sofia, Bulgaria
  32. 32 Forest Dynamics Research Unit, WSL Swiss Federal Research Institute, Birmensdorf, Switzerland
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Editor: Zenodo

Ano de publicación: 2021

Tipo: Dataset

CC BY 4.0

DOI: 10.5281/ZENODO.4688660 lock_openAcceso aberto editor

Resumo

This set of maps shows the representation of 152 vascular plant families within forest, grassland, scrub and wetland plant communities across Europe. We used a set of 816,005 vegetation plots from the European Vegetation Archive (EVA; Chytrý et al. 2016), and for each plot, we calculated the relative species richness of individual plant families (number of species belonging to the family divided by the total number of species in the plot). The relative species richness was then mapped, averaged across all plots in 50 km × 50 km UTM grid cells, for each family and broad habitat groups – forests, grasslands, scrub and wetlands. Here we provide the maps as (i) images (PDF files) and (ii) tables (XLSX files) containing the source data to be used for visualization in R or GIS software. The colour scale in the maps was generated from the data using the <em>k</em>-means algorithm. For each map, the distribution of the values and the minimum, maximum and median values are shown. The maps only show grid cells containing at least five vegetation plots. Of these grid cells, those with mean relative species richness of the mapped family equal to zero are in grey. For each map, we also provide the number of genera/species included, the Shannon diversity index for the combination of the family and the habitat group, and the number of plots included (both absolute and relative to the total number of plots in the habitat group). The Shannon diversity index is based on species occurrences in vegetation plots: higher values indicate that the family is represented by many species with relatively even occurrence frequencies, while lower values indicate that it is represented by few species or some species is much more frequent than the others. For the combinations of families and habitat groups not represented in the dataset, blank maps were generated and the respective columns in tables filled with NAs. For further details, see Večeřa et al. (2021) <em>Journal of Vegetation Science</em> https://doi.org/10.1111/jvs.13035. Contents: <strong>Families_maps_all.pdf</strong> – a file containing maps of mean relative species richness of all the families <strong>Families_maps_one-by-one.rar</strong> – separate files of individual families <strong>Families_attribute_table_data.xlsx</strong> – a matrix of mean relative species richness for vascular plant families (columns) in 50 km × 50 km UTM grid cells (rows) in forests, grasslands, scrub and wetlands (four sheets); a family is considered absent (the mean relative species richness equal to zero) only in grid cells containing at least five vegetation plots; grid cells with no data or containing less than five plots are marked NA. <strong>Colour_scale_codes.xlsx</strong> – a table of colours (HEX and RGB definitions) used for generating colour scales in the maps, with colour-scale codes (0–7) that may be used in combination with the file Families_attribute_table_colour-codes.xlsx to generate maps with the same colour representation as the original maps. <strong>Families_attribute_table_colour-codes.xlsx</strong> – a matrix of colour-scale codes representing eight classes of the mean relative species richness (columns) in 50 km × 50 km UTM grid cells (rows) in forests, grasslands, scrub and wetlands (four sheets). In combination with the file Colour_scale_codes.xlsx, this table enables to reproduce the maps with the original colour representation. A family is considered absent (colour-scale code equal to zero) only in grid cells containing at least five vegetation plots; grid cells with no data or containing less than five plots are marked NA. <strong>Europe_CGRS_grid.rar</strong> – a shapefile of the 50 km × 50 km UTM grid for Europe (originally available at: https://www.eea.europa.eu/data-and-maps/data/common-european-chorological-grid-reference-system-cgrs) to which data from the files Families_attribute_table_data.xlsx and Families_attribute_table_colour-codes.xlsx may be joined.