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1. Distribution maps of vegetation alliances in Europe

Author

Preislerová, Z., Jiménez‐Alfaro, B., Mucina, L., Berg, C., Bonari, G., Kuzemko, A., Landucci, F., Marcenò, C., Monteiro‐Henriques, T., Novák, P., Vynokurov, D., Bergmeier, E., Dengler, J., Apostolova, I., Bioret, F., Biurrun, I., Campos, J.A., Capelo, J., Čarni, A., Çoban, S., Csiky, J., Ćuk, M., Ćušterevska, R., Daniëls, F.J.A., De Sanctis, M., Didukh, Y., Dítě, D., Fanelli, G., Golovanov, Y., Golub, V., Guarino, R., Hájek, M., Iakushenko, D., Indreica, A., Jansen, F., Jašková, A., Jiroušek, M., Kalníková, V., Kavgacı, A., Kucherov, I., Küzmič, F., Lebedeva, M., Loidi, J., Lososová, Z., Lysenko, T., Milanović, Đ., Onyshchenko, V., Perrin, G., Peterka, T., Rašomavičius, V., Rodríguez‐Rojo, M.P., Rodwell, J.S., Rūsiņa, S., Sánchez‐Mata, D., Schaminée, J.H.J., Semenishchenkov, Y., Shevchenko, N., Šibík, J., Škvorc, Ž., Smagin, V., Stešević, D., Stupar, V., Šumberová, K., Theurillat, J‐P, Tikhonova, E., Tzonev, R., Valachovič, M., Vassilev, K., Willner, W., Yamalov, S., Večeřa, M., Chytrý, M., Preislerová, Z., Jiménez‐Alfaro, B., Mucina, L., Berg, C., Bonari, G., Kuzemko, A., Landucci, F., Marcenò, C., Monteiro‐Henriques, T., Novák, P., Vynokurov, D., Bergmeier, E., Dengler, J., Apostolova, I., Bioret, F., Biurrun, I., Campos, J.A., Capelo, J., Čarni, A., Çoban, S., Csiky, J., Ćuk, M., Ćušterevska, R., Daniëls, F.J.A., De Sanctis, M., Didukh, Y., Dítě, D., Fanelli, G., Golovanov, Y., Golub, V., Guarino, R., Hájek, M., Iakushenko, D., Indreica, A., Jansen, F., Jašková, A., Jiroušek, M., Kalníková, V., Kavgacı, A., Kucherov, I., Küzmič, F., Lebedeva, M., Loidi, J., Lososová, Z., Lysenko, T., Milanović, Đ., Onyshchenko, V., Perrin, G., Peterka, T., Rašomavičius, V., Rodríguez‐Rojo, M.P., Rodwell, J.S., Rūsiņa, S., Sánchez‐Mata, D., Schaminée, J.H.J., Semenishchenkov, Y., Shevchenko, N., Šibík, J., Škvorc, Ž., Smagin, V., Stešević, D., Stupar, V., Šumberová, K., Theurillat, J‐P, Tikhonova, E., Tzonev, R., Valachovič, M., Vassilev, K., Willner, W., Yamalov, S., Večeřa, M., and Chytrý, M.

Abstract

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 uncertainti

Published
2022

2. sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

Author

Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., Bates, A., Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., and Bates, A.

Abstract

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.

Published
2021

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

Author

Chytrý, M., Tichý, L., Hennekens, S.M., Knollová, I., Janssen, J.A.M., Rodwell, J.S., Peterka, T., Marcenò, C., Landucci, F., Danihelka, J., Hájek, M., Dengler, J., Novák, P., Zukal, D., Jiménez‐Alfaro, B., Mucina, L., Abdulhak, S., Aćić, S., Agrillo, E., Attorre, F., Bergmeier, E., Biurrun, I., Boch, S., Bölöni, J., Bonari, G., Braslavskaya, T., Bruelheide, H., Campos, J.A., Čarni, A., Casella, L., Ćuk, M., Ćušterevska, R., De Bie, E., Delbosc, P., Demina, O., Didukh, Y., Dítě, D., Dziuba, T., Ewald, J., Gavilán, R.G., Gégout, J‐C, Giusso del Galdo, G.P., Golub, V., Goncharova, N., Goral, F., Graf, U., Indreica, A., Isermann, M., Jandt, U., Jansen, F., Jansen, J., Jašková, A., Jiroušek, M., Kącki, Z., Kalníková, V., Kavgacı, A., Khanina, L., Yu. Korolyuk, A., Kozhevnikova, M., Kuzemko, A., Küzmič, F., Kuznetsov, O.L., Laiviņš, M., Lavrinenko, I., Lavrinenko, O., Lebedeva, M., Lososová, Z., Lysenko, T., Maciejewski, L., Mardari, C., Marinšek, A., Napreenko, M.G., Onyshchenko, V., Pérez‐Haase, A., Pielech, R., Prokhorov, V., Rašomavičius, V., Rodríguez Rojo, M.P., Rūsiņa, S., Schrautzer, J., Šibík, J., Šilc, U., Škvorc, Ž., Smagin, V.A., Stančić, Z., Stanisci, A., Tikhonova, E., Tonteri, T., Uogintas, D., Valachovič, M., Vassilev, K., Vynokurov, D., Willner, W., Yamalov, S., Evans, D., Palitzsch Lund, M., Spyropoulou, R., Tryfon, E., Schaminée, J.H.J., Schmidtlein, S., Chytrý, M., Tichý, L., Hennekens, S.M., Knollová, I., Janssen, J.A.M., Rodwell, J.S., Peterka, T., Marcenò, C., Landucci, F., Danihelka, J., Hájek, M., Dengler, J., Novák, P., Zukal, D., Jiménez‐Alfaro, B., Mucina, L., Abdulhak, S., Aćić, S., Agrillo, E., Attorre, F., Bergmeier, E., Biurrun, I., Boch, S., Bölöni, J., Bonari, G., Braslavskaya, T., Bruelheide, H., Campos, J.A., Čarni, A., Casella, L., Ćuk, M., Ćušterevska, R., De Bie, E., Delbosc, P., Demina, O., Didukh, Y., Dítě, D., Dziuba, T., Ewald, J., Gavilán, R.G., Gégout, J‐C, Giusso del Galdo, G.P., Golub, V., Goncharova, N., Goral, F., Graf, U., Indreica, A., Isermann, M., Jandt, U., Jansen, F., Jansen, J., Jašková, A., Jiroušek, M., Kącki, Z., Kalníková, V., Kavgacı, A., Khanina, L., Yu. Korolyuk, A., Kozhevnikova, M., Kuzemko, A., Küzmič, F., Kuznetsov, O.L., Laiviņš, M., Lavrinenko, I., Lavrinenko, O., Lebedeva, M., Lososová, Z., Lysenko, T., Maciejewski, L., Mardari, C., Marinšek, A., Napreenko, M.G., Onyshchenko, V., Pérez‐Haase, A., Pielech, R., Prokhorov, V., Rašomavičius, V., Rodríguez Rojo, M.P., Rūsiņa, S., Schrautzer, J., Šibík, J., Šilc, U., Škvorc, Ž., Smagin, V.A., Stančić, Z., Stanisci, A., Tikhonova, E., Tonteri, T., Uogintas, D., Valachovič, M., Vassilev, K., Vynokurov, D., Willner, W., Yamalov, S., Evans, D., Palitzsch Lund, M., Spyropoulou, R., Tryfon, E., Schaminée, J.H.J., and Schmidtlein, S.

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

4. Post-glacial migration lag restricts range filling of plants in the European Alps.

Author

Dullinger, S., Willner, W., Plutzar, C., Englisch, T., Schratt-Ehrendorfer, L., Moser, D., Ertl, S., Essl, F., and Niklfeld, H.

Subjects
*PLANT migration, *GLACIAL isostasy, *MOUNTAIN plants, *DISPERSAL (Ecology), *SPECIES distribution, *PLEISTOCENE Epoch
Abstract

ABSTRACT Aim To evaluate the effect of post-glacial migration lags on the current distribution of Alpine plants and the factors responsible for possible range-filling differences among species. Location Austrian Alps. Methods We used species distribution models to predict environmentally suitable sites for 183 Alpine plants at a fine spatial resolution (100 × 100 m2). We overlaid these predictions with independent mapping data (3′× 5′) and calculated the extent to which species fill their potential ranges at this coarser grain based on several different approaches. Moreover, we correlated range-filling estimates with the magnitude of improvement of distribution models when using the distance to putative glacial refugia as an additional independent variable. Finally, we compared species-specific range-filling estimates with traits related to dispersal capacity and competitive ability of these species as well as with characteristics of their habitats. Results Even under a conservative approach, incomplete range filling appears common, with 46% and 31% of the species studied occurring in less than 75% and 50% of their predicted suitable ranges, respectively. Proximity to glacial refugia generally accounts for a lower percentage of the deviance in species distribution data (0-20%, mean 4%) than environmental variables (9-57%, mean 27%). However, its importance correlates closely and negatively with the calculated range-filling estimates. Range filling significantly increases with the dispersal capacity of a species' propagules and the breadth of its altitudinal niche. Calcicolous species have lower range filling than silicicolous plants and substrate generalists. Conclusions Our results suggest that the current ranges of many Alpine plants are still shaped by delayed Holocene recolonization of suitable sites. Hence, long-term migration lags also affect plant distribution in mountainous areas, at least on regional scales. These findings question whether high mountain floras will be able to track the expected rapid, climate change driven shifts in habitat. [ABSTRACT FROM AUTHOR]

Published
2012
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5. Imprints of glacial history and current environment on correlations between endemic plant and invertebrate species richness.

Author

Essl, F., Dullinger, S., Plutzar, C., Willner, W., and Rabitsch, W.

Subjects
ANIMAL-plant relationships, SPECIES diversity, ENDEMIC plants, BEETLES, GLACIAL Epoch, STATISTICAL correlation
Abstract

We evaluate how closely diversity patterns of endemic species of vascular plants, beetles, butterflies, molluscs and spiders are correlated with each other, and to what extent similar environmental requirements or survival in common glacial refugia and comparable dispersal limitations account for their existing congruence. Austria. We calculated pairwise correlations among species numbers of the five taxonomic groups in 1405 cells of a 3′ × 5′ raster ( c. 35 km) using the raw data as well as the residuals of regression models that accounted for: (1) environmental variables, (2) environmental variables and the occurrence of potential refugia during the Last Glacial Maximum, or (3) environmental variables, refugia and spatial filters. Pairwise cross-taxonomic group Spearman's rank correlations in the raw data were significantly positive in most cases, but only moderate (0.3 < ρ < 0.5) to weak (ρ < 0.3) throughout. Correlations were closest between plants and beetles, plants and butterflies, and plants and snails, respectively, whereas the distribution of endemic spiders was largely uncorrelated with those of the other groups. Environmental variables explained only a moderate proportion of the variance in endemic richness patterns, and the response of individual groups to environmental gradients was only partly consistent. The inclusion of refugium locations and the spatial filters increased the goodness of model fit for all five taxonomic groups. Moreover, removing the effects of environmental conditions reduced congruence in endemic richness patterns to a lesser extent than did filtering the influence of refugium locations and spatial autocorrelation, except for spiders, which are probably the least dispersal-limited of the five groups. The moderate to weak congruence of endemic richness patterns clearly limits the usefulness of a surrogacy approach for designating areas for the protection of regional endemics. On the other hand, our results suggest that dispersal limitations still shape the distributions of many endemic plant, snail, beetle and butterfly species, even at the regional scale; that is, survival in shared refugia and subsequent restricted spread retain a detectable signal in existing correlations. Concentrating conservation efforts on well-known Pleistocene refugia hence appears to be a reasonable first step towards a strategy for protecting regional endemics of at least the less mobile invertebrate groups. [ABSTRACT FROM AUTHOR]

Published
2011
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