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

Author

Kambach, Stephan, Sabatini, Francesco Maria, Attorre, Fabio, Biurrun, Idoia, Boenisch, Gerhard, Bonari, Gianmaria, Čarni, Andraž, Carranza, Maria Laura, Chiarucci, Alessandro, Chytrý, Milan, Dengler, Jürgen, Garbolino, Emmanuel, Golub, Valentin, Güler, Behlül, Jandt, Ute, Jansen, Jan, Jašková, Anni, Jiménez-Alfaro, Borja, Karger, Dirk Nikolaus, Kattge, Jens, Knollová, Ilona, Midolo, Gabriele, Moeslund, Jesper Erenskjold, Pielech, Remigiusz, Rašomavičius, Valerijus, Rūsiņa, Solvita, Šibík, Jozef, Stančić, Zvjezdana, Stanisci, Angela, Svenning, Jens-Christian, Yamalov, Sergey, Zimmermann, Niklaus E., and Bruelheide, Helge

Published
2023
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2. Estimation of missing Ellenberg Indicator Values for tree species in South-eastern Europe: a comparison of methods

Author

Leccese, Letizia, Fanelli, Giuliano, Cambria, Vito Emanuele, Massimi, Marco, Attorre, Fabio, Alfò, Marco, Aćić, Svetlana, Bergmeier, Erwin, Čarni, Andraž, Cuk, Mirjana, Custerevska, Renata, Dimopoulos, Panayotis, Hoda, Petrit, Mullaj, Alfred, Šilc, Urban, Skvorc, Zeljko, Stancic, Zvjezdana, Dajic Stevanovic, Zora, Tzonev, Rossen, Vassilev, Kiril, Malatesta, Luca, and De Sanctis, Michele

Published
2024
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3. Diversity and distribution of Raunkiær's life forms in European vegetation

Author

Midolo, Gabriele, Axmanová, Irena, Divíšek, Jan, Dřevojan, Pavel, Lososová, Zdeňka, Večeřa, Martin, Karger, Dirk Nikolaus, Thuiller, Wilfried, Bruelheide, Helge, Aćić, Svetlana, Attorre, Fabio, Biurrun, Idoia, Boch, Steffen, Bonari, Gianmaria, Čarni, Andraž, Chiarucci, Alessandro, Ćušterevska, Renata, Dengler, Jürgen, Dziuba, Tetiana, Garbolino, Emmanuel, Jandt, Ute, Lenoir, Jonathan, Marcenò, Corrado, Rūsiņa, Solvita, Šibík, Jozef, Škvorc, Željko, Stančić, Zvjezdana, Stanišić‐Vujačić, Milica, Svenning, Jens‐Christian, Swacha, Grzegorz, Vassilev, Kiril, Chytrý, Milan, Midolo, Gabriele, Axmanová, Irena, Divíšek, Jan, Dřevojan, Pavel, Lososová, Zdeňka, Večeřa, Martin, Karger, Dirk Nikolaus, Thuiller, Wilfried, Bruelheide, Helge, Aćić, Svetlana, Attorre, Fabio, Biurrun, Idoia, Boch, Steffen, Bonari, Gianmaria, Čarni, Andraž, Chiarucci, Alessandro, Ćušterevska, Renata, Dengler, Jürgen, Dziuba, Tetiana, Garbolino, Emmanuel, Jandt, Ute, Lenoir, Jonathan, Marcenò, Corrado, Rūsiņa, Solvita, Šibík, Jozef, Škvorc, Željko, Stančić, Zvjezdana, Stanišić‐Vujačić, Milica, Svenning, Jens‐Christian, Swacha, Grzegorz, Vassilev, Kiril, and Chytrý, Milan

Abstract

Aims: The Raunkiær's system classifies vascular plants into life forms based on the position of renewal buds during periods unfavourable for plant growth. Despite the importance of Raunkiær's system for ecological research, a study exploring the diversity and distribution of life forms on a continental scale is missing. We aim to (i) map the diversity and distribution of life forms in European vegetation and (ii) test for effects of bioclimatic variables while controlling for habitat-specific responses. Location: Europe. Methods: We used data on life forms of 8883 species recorded in 546,501 vegetation plots of different habitats (forest, grassland, scrub and wetland). For each plot, we calculated: (i) the proportion of species of each life form and (ii) the richness and evenness of life forms. We mapped these plot-level metrics averaged across 50 km × 50 km grid cells and modelled their response to bioclimatic variables. Results: Hemicryptophytes were the most widespread life form, especially in the temperate zone of Central Europe. Conversely, therophyte and chamaephyte species were more common in the Mediterranean as well as in the dry temperate regions. Moreover, chamaephytes were also more common in the boreal and arctic zones. Higher proportions of phanerophytes were found in the Mediterranean. Overall, a higher richness of life forms was found at lower latitudes while evenness showed more spatially heterogeneous patterns. Habitat type was the main discriminator for most of the responses analysed, but several moisture-related predictors still showed a marked effect on the diversity of therophytes and chamaephytes. Conclusions: Our maps can be used as a tool for future biogeographic and macro-ecological research at a continental scale. Habitat type and bioclimatic conditions are key for regulating the diversity and distribution of plant life forms, with concomitant consequences for the response of functional diversity in European vegetation to global environmen

Published
2024

5. Diversity and distribution of Raunkiær's life forms in European vegetation

Author

Midolo, Gabriele, primary, Axmanová, Irena, additional, Divíšek, Jan, additional, Dřevojan, Pavel, additional, Lososová, Zdeňka, additional, Večeřa, Martin, additional, Karger, Dirk Nikolaus, additional, Thuiller, Wilfried, additional, Bruelheide, Helge, additional, Aćić, Svetlana, additional, Attorre, Fabio, additional, Biurrun, Idoia, additional, Boch, Steffen, additional, Bonari, Gianmaria, additional, Čarni, Andraž, additional, Chiarucci, Alessandro, additional, Ćušterevska, Renata, additional, Dengler, Jürgen, additional, Dziuba, Tetiana, additional, Garbolino, Emmanuel, additional, Jandt, Ute, additional, Lenoir, Jonathan, additional, Marcenò, Corrado, additional, Rūsiņa, Solvita, additional, Šibík, Jozef, additional, Škvorc, Željko, additional, Stančić, Zvjezdana, additional, Stanišić‐Vujačić, Milica, additional, Svenning, Jens‐Christian, additional, Swacha, Grzegorz, additional, Vassilev, Kiril, additional, and Chytrý, Milan, additional

Published
2024
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7. Formalized classification of European fen vegetation at the alliance level

Author

Peterka, Tomáš, Hájek, Michal, Jiroušek, Martin, Jiménez-Alfaro, Borja, Aunina, Liene, Bergamini, Ariel, Dítě, Daniel, Felbaba-Klushyna, Ljuba, Graf, Ulrich, Hájková, Petra, Hettenbergerová, Eva, Ivchenko, Tatiana G., Jansen, Florian, Koroleva, Natalia E., Lapshina, Elena D., Lazarević, Predrag M., Moen, Asbjørn, Napreenko, Maxim G., Pawlikowski, Paweł, Plesková, Zuzana, Sekulová, Lucia, Smagin, Viktor A., Tahvanainen, Teemu, Thiele, Annett, Biƫǎ-Nicolae, Claudia, Biurrun, Idoia, Brisse, Henry, Ćušterevska, Renata, De Bie, Els, Ewald, Jörg, FitzPatrick, Úna, Font, Xavier, Jandt, Ute, Kącki, Zygmunt, Kuzemko, Anna, Landucci, Flavia, Moeslund, Jesper E., Pérez-Haase, Aaron, Rašomavičius, Valerijus, Rodwell, John S., Schaminée, Joop H.J., Šilc, Urban, Stančić, Zvjezdana, and Chytrý, Milan

Published
2017

8. A higher-level classification of the Pannonian and western Pontic steppe grasslands (Central and Eastern Europe)

Author

Willner, Wolfgang, Kuzemko, Anna, Dengler, Jürgen, Chytrý, Milan, Bauer, Norbert, Becker, Thomas, Biƫă-Nicolae, Claudia, Botta-Dukát, Zoltán, Čarni, Andraž, Csiky, János, Igić, Ruzica, Kącki, Zygmunt, Korotchenko, Iryna, Kropf, Matthias, Krstivojević-Ćuk, Mirjana, Krstonošić, Daniel, Rédei, Tamás, Ruprecht, Eszter, Schratt-Ehrendorfer, Luise, Semenishchenkov, Yuri, Stančić, Zvjezdana, Vashenyak, Yulia, Vynokurov, Denys, and Janišová, Monika

Published
2017

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

Author

Biología vegetal y ecología, Landaren biologia eta ekologia, Kambach, Stephan, Sabatini, Francesco Maria, Attorre, Fabio, Biurrun Galarraga, Miren Idoia, Boenisch, Gerhard, Bonari, Gianmaria, Čarni, Andraž, Carranza, María Laura, Chiarucci, Alessandro, Chytrý, Milan, Dengler, Jürgen, Garbolino, Emmanuel, Golub, Valentin, Güler, Behlül, Jandt, Ute, Jansen, Jan, Jašková, Anni, Jiménez Alfaro, Borja, Karger, Dirk Nikolaus, Kattge, Jens, Knollová, Ilona, Midolo, Gabriele, Moeslund, Jesper Erenskjold, Pielech, Remigiusz, Rašomavičius, Valerijus, Rūsiņa, Solvita, Šibík, Jozef, Stančić, Zvjezdana, Stanisci, Angela, Svenning, Jens-Christian, Yamalov, Sergey, Zimmermann, Niklaus E., Bruelheide, Helge, Biología vegetal y ecología, Landaren biologia eta ekologia, Kambach, Stephan, Sabatini, Francesco Maria, Attorre, Fabio, Biurrun Galarraga, Miren Idoia, Boenisch, Gerhard, Bonari, Gianmaria, Čarni, Andraž, Carranza, María Laura, Chiarucci, Alessandro, Chytrý, Milan, Dengler, Jürgen, Garbolino, Emmanuel, Golub, Valentin, Güler, Behlül, Jandt, Ute, Jansen, Jan, Jašková, Anni, Jiménez Alfaro, Borja, Karger, Dirk Nikolaus, Kattge, Jens, Knollová, Ilona, Midolo, Gabriele, Moeslund, Jesper Erenskjold, Pielech, Remigiusz, Rašomavičius, Valerijus, Rūsiņa, Solvita, Šibík, Jozef, Stančić, Zvjezdana, Stanisci, Angela, Svenning, Jens-Christian, Yamalov, Sergey, Zimmermann, Niklaus E., and Bruelheide, Helge

Abstract

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.

Published
2023

10. Disturbance indicator values for European plants

Author

Midolo, Gabriele, Herben, Tomáš, Axmanová, Irena, Marcenò, Corrado, Pätsch, Ricarda, Bruelheide, Helge, Karger, Dirk Nikolaus, Aćić, Svetlana, Bergamini, Ariel, Bergmeier, Erwin, Biurrun, Idoia, Bonari, Gianmaria, Čarni, Andraž, Chiarucci, Alessandro, De Sanctis, Michele, Demina, Olga, Dengler, Jürgen, Dziuba, Tetiana, Fanelli, Giuliano, Garbolino, Emmanuel, Giusso del Galdo, Gianpietro, Goral, Friedemann, Güler, Behlül, Hinojos‐Mendoza, Guillermo, Jansen, Florian, Jiménez‐Alfaro, Borja, Lengyel, Attila, Lenoir, Jonathan, Pérez‐Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Ruprecht, Eszter, Rūsiņa, Solvita, Šilc, Urban, Škvorc, Željko, Stančić, Zvjezdana, Tatarenko, Irina, Chytrý, Milan, Midolo, Gabriele, Herben, Tomáš, Axmanová, Irena, Marcenò, Corrado, Pätsch, Ricarda, Bruelheide, Helge, Karger, Dirk Nikolaus, Aćić, Svetlana, Bergamini, Ariel, Bergmeier, Erwin, Biurrun, Idoia, Bonari, Gianmaria, Čarni, Andraž, Chiarucci, Alessandro, De Sanctis, Michele, Demina, Olga, Dengler, Jürgen, Dziuba, Tetiana, Fanelli, Giuliano, Garbolino, Emmanuel, Giusso del Galdo, Gianpietro, Goral, Friedemann, Güler, Behlül, Hinojos‐Mendoza, Guillermo, Jansen, Florian, Jiménez‐Alfaro, Borja, Lengyel, Attila, Lenoir, Jonathan, Pérez‐Haase, Aaron, Pielech, Remigiusz, Prokhorov, Vadim, Rašomavičius, Valerijus, Ruprecht, Eszter, Rūsiņa, Solvita, Šilc, Urban, Škvorc, Željko, Stančić, Zvjezdana, Tatarenko, Irina, and Chytrý, Milan

Abstract

Motivation: Indicator values are numerical values used to characterize the ecological niches of species and to estimate their occurrence along gradients. Indicator values on climatic and edaphic niches of plant species have received considerable attention in ecological research, whereas data on the optimal positioning of species along disturbance gradients are less developed. Here, we present a new data set of disturbance indicator values identifying optima along gradients of natural and anthropogenic disturbance for 6382 vascular plant species based on the analysis of 736,366 European vegetation plots and using expert-based characterization of disturbance regimes in 236 habitat types. The indicator values presented here are crucial for integrating disturbance niche optima into large-scale vegetation analyses and macroecological studies. Main types of variables contained: We set up five main continuous indicator values for European vascular plants: disturbance severity, disturbance frequency, mowing frequency, grazing pressure and soil disturbance. The first two indicators are provided separately for the whole community and for the herb layer. We calculated the values as the average of expert-based estimates of disturbance values in all habitat types where a species occurs, weighted by the number of plots in which the species occurs within a given habitat type. Spatial location and grain: Europe. Vegetation plots ranging in size from 1 to 1000 m2. Time period and grain: Vegetation plots mostly sampled between 1956 and 2013 (= 5th and 95th quantiles of the sampling year, respectively). Major taxa and level of measurement: Species-level indicator values for vascular plants. Software format: csv file.

Published
2023

11. Pollination patterns of flora and vegetation in northern Croatia with reference to Apis mellifera

Author

Stančić, Zvjezdana, Fiket, Željka, Stančić, Zvjezdana, and Fiket, Željka

Abstract

Pollination patterns i.e. the proportions of entomophilous, anemophilous, autogamous and hydrophilous plant species and those useful for the European honey bee (Apis mellifera L.) in the flora and vegetation of northern Croatia have been determined. The survey included 507 plant taxa, belonging to 95 plant families. The results show that most plant species employ insect pollination (73.6%), followed by self-pollination (30%), wind (25%) and water pollination (0.6%). For some plant species there are one, two or more modes of pollination; the largest group consists of pure insect pollination (43%), followed by both insect and self-pollination (27%), pure wind pollination (22%), insect and wind pollination (2.6%), and so on. Overall, 54% of plant species useful to European honey bees were found, 51% of which provide pollen and 47% nectar. These results suggest that A. mellifera could be a potential pollinator for about half of the flora. Analysis shows significant differences in pollination patterns among habitat types and that most entomophilous plant taxa are found in grassland, forest and ruderal sites, indicating that these habitats are most important for pollinators. Other characteristics of plant species, such as flowering time, plant family, life form and origin, were also analysed to determine a possible relationship with pollination.

Published
2023

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

Author

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

Published
2016

14. Disturbance indicator values for European plants

Author

Midolo, Gabriele, primary, Herben, Tomáš, additional, Axmanová, Irena, additional, Marcenò, Corrado, additional, Pätsch, Ricarda, additional, Bruelheide, Helge, additional, Karger, Dirk Nikolaus, additional, Aćić, Svetlana, additional, Bergamini, Ariel, additional, Bergmeier, Erwin, additional, Biurrun, Idoia, additional, Bonari, Gianmaria, additional, Čarni, Andraž, additional, Chiarucci, Alessandro, additional, De Sanctis, Michele, additional, Demina, Olga, additional, Dengler, Jürgen, additional, Dziuba, Tetiana, additional, Fanelli, Giuliano, additional, Garbolino, Emmanuel, additional, Giusso del Galdo, Gianpietro, additional, Goral, Friedemann, additional, Güler, Behlül, additional, Hinojos‐Mendoza, Guillermo, additional, Jansen, Florian, additional, Jiménez‐Alfaro, Borja, additional, Lengyel, Attila, additional, Lenoir, Jonathan, additional, Pérez‐Haase, Aaron, additional, Pielech, Remigiusz, additional, Prokhorov, Vadim, additional, Rašomavičius, Valerijus, additional, Ruprecht, Eszter, additional, Rūsiņa, Solvita, additional, Šilc, Urban, additional, Škvorc, Željko, additional, Stančić, Zvjezdana, additional, Tatarenko, Irina, additional, and Chytrý, Milan, additional

Published
2022
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17. Neophytes in the flora of Bedekovčina (northwestern Croatia)

Author

Stančić, Zvjezdana and Stančić, Zvjezdana

Abstract

In the flora of Bedekovčina, 43 species of neophytes were recorded, or 8.5% of the 507 wild plant species recorded in total. Among the neophytes, 11 invasive species were identified, representing 2% of the total flora; the most common being Solidago gigantea Aiton, Erigeron annuus (L.) Desf., Echinocystis lobata (Michx.) Torr. & A. Gray, Robinia pseudoacacia L., and Ambrosia artemisiifolia L. Most neophytes grow in anthropogenic habitats, but to a lesser extent also in semi-natural and natural vegetation. The species that grow in the greatest number of habitats are Solidago gigantea and Erigeron annuus. Both species dominate abandoned agricultural lands, Erigeron annuus in the early stages and Solidago gigantea in the later stages of succession. The neophytes were analysed for various characteristics. The results showed that the neophyte flora was dominated by species native to North America (63%), accidentally introduced (86%), belonging to therophytes (49%), annual herbs (47%), good competitors (42%), which reproduce only by seeds (58%), and disperse with autochory (53%).

Published
2022

18. Importance of flora and habitat types for insect pollinators and Apis mellifera in northwestern Croatia

Author

Stančić, Zvjezdana

Subjects
Bedekovčina, European honey bee, flora, pollination
Abstract

For the first time in Croatia and in the wider temperate zone, the proportion of plant species pollinated by insects and useful for the European honey bee (Apis mellifera L.) was determined. The survey included 507 plant taxa, belonging to 95 plant families, covering the flora and all habitat types in the studied area in northwestern Croatia. The results show that most plant species depend on insect pollination (73.6%), followed by self-pollination (30%), wind (25%) and water pollination (0.6%). For some plant species there are one, two or more modes of pollination: the largest group consists of pure insect pollination (43%), followed by both insect and self-pollination (27%), pure wind pollination (22%), insect and wind pollination (2.6), etc. Overall, 54% of plant species useful to European honey bees were found, of which 51% provide pollen, 47% nectar and 4% honeydew. These results suggest that Apis mellifera could be a potential pollinator for about half of the flora. Of the traits studied, habitat types and plant family membership had the greatest influence on the distribution of pollination modes. Habitat analysis showed that most entomophilous plant taxa are found in grasslands, forests, and ruderal sites, suggesting that these habitats are most important for pollinators. Other plant species characteristics such as flowering time, life form, origin, and threat status were also analysed to determine the possible relationship with pollination. The results of this comprehensive study not only demonstrate the importance of simultaneously studying insect pollinated plant species and their habitats, but may also be helpful in determining best management practises to protect insect pollinators.

Published
2022

19. Syntaxonomical delimitation of calcareous perennial dry grasslands and scrub of Southern Europe

Author

Vynokurov, Denys, Biurrun, Idoia, Campos, Juan Antonio, Stančić, Zvjezdana, and García-Mijangos, Itziar

Subjects
syntaxonomy, dry grasslands, scrubland, Southern Europe
Abstract

Syntaxonomy of dry grasslands and scrub in Southern Europe is quite complex and still has numerous issues to unravel. There are many blurry boundaries between the vegetation units, especially in submediterranean areas, which is further complicated by the regional focus of most studies. We aim to delimit geographically, ecologically and floristically the calcareous perennial dry grasslands and scrub of Southern Europe on the level of vegetation classes. This delimitation will help clarify the position of some syntaxonomical units and allow conducting classification studies at lower syntaxonomic levels. Moreover, as many of these vegetation types are vulnerable and endangered, our results might be a basis of proper conservation and management measures. The geographical scope of the project is Southern Europe including Portugal, Spain, France, Italy, Slovenia, Croatia, Bosnia and Herzegovina, Serbia, Montenegro, Kosovo, North Macedonia, Albania, Greece, Bulgaria and Turkey. We used the vegetation plots of calcareous perennial dry grasslands and scrub from the EVA database based on the vegetation class assignment (Astragalo-Brometea, Carici-Genistetea lobelii, Daphno-Festucetea, Elyno-Seslerietea, Festuco hystricis-Ononidetea striatae, Festuco-Brometea, Lygeo sparti-Stipetea tenacissimae, Ononido-Rosmarinetea, Poetea bulbosae, Trifolio anatolici-Polygonetea arenastri) and corresponding units of the EUNIS habitat classification. Altogether we collected 69, 758 relevés from 15 countries. We used only relevés with plot area ranging from 9 m2 to 100 m2 and applied a geographically stratified heterogeneity-constrained resampling. After taxonomic homogenization, we used different classification techniques (such as TWINSPAN and fuzzy C-means) and based on the results, prepared clear floristic definitions with diagnostic species of phytosociological classes and developed an electronic expert system.

Published
2022

20. Habitat-specificity of climate-trait relationships in vascular plants

Author

Kambach, Stephan, Sabatini, Francesco Maria, Attorre, Fabio, Stančić, Zvjezdana, and Bruelheide, Helge

Subjects
climate, habitats, traits
Abstract

Ecological theory of environmental filtering predicts close local relationships between microclimatic gradients and functional traits. Yet, on the global scale, climatic gradients are only weakly related to the trait composition of local plant communities, suggesting additional non-climatic factors are at play. To shed more light on this, we may need to investigate climate-trait relationships in more narrowly defined habitats. We used generalized additive models to quantify the relationships between two major climatic gradients (Mediterranean and temperature gradient) and four key functional plant traits (plant height, specific leaf area, seed mass and specific root length) across > 300, 000 European vegetation plots, each one assigned to a hierarchy from broad to more narrowly defined habitats (based on the EUNIS classification). We found that the predictive power of climate increased from broader to more narrowly defined habitats for two out of the four traits (specific leaf area and root length). Although the two climatic gradients were significantly related to all four traits, these relationships varied with the width of the habitat definition and we found the highest degree of habitat-specific relationships in the most narrowly defined habitats. We conclude that climate and local environmental factors jointly drive the functional composition of plant communities. As the relationships between climate and plant traits are not generalizable, the effects of climate change might play out differently, depending on the habitat investigated. Thus, predictions of the effects of climate on plant communities must account for habitat-specificity and how habitats are defined.

Published
2022

23. APPLICATION OF ECOLOGICAL ENGINEERING IN LANDFILL REMEDIATION.

Author

Miletić, Ivana Piljek, Stančić, Zvjezdana, and Fiket, Željka

Subjects
ECOLOGICAL engineering, LANDFILLS, BIOREMEDIATION, PHYTOREMEDIATION, POLLUTANTS
Abstract

Ecological engineering is a new branch of engineering based on ecology that emerged in the 1960s from the growing need for more sustainable biological solutions to environmental problems. It is based on the design of natural ecosystems for the benefit of both nature and human society, and its techniques can be applied to a range of environmental problems, from the restoration of degraded ecosystems to the removal of pollutants. One of the major environmental problems worldwide is waste disposal in the form of landfills, with its various negative impacts on the environment, living beings and human health. Conventional landfill closure and remediation techniques have proven to be economically and energetically challenging and are not sufficiently effective in reducing leachate formation and removing pollutants. For this reason, this article presents several ecological engineering techniques that can be used in landfill remediation. Phytocapping is an alternative to conventional cover systems that uses plants to control and limit water infiltration into waste, leachate formation, stabilize landfills, control erosion, and reduce methane emissions. Phytoremediation is an environmentally friendly technology for soil remediation through natural processes, in two forms: phytoextraction and phytostabilization. Phytoextraction uses plants to extract and remove pollutants from waste and soil, while phytostabilization is used to immobilize pollutants in the root zone. Constructed wetlands, designed and constructed according to the principles of natural wetland ecosystems, can be used to clean leachate. Natural attenuation uses natural biological processes to mitigate pollution without taking specific action. All of these techniques are based on viable natural solutions that can reduce remediation costs and further maintenance of the landfill. Although they are increasingly being considered in developed countries, there are few examples of their application in landfill remediation in Croatia. [ABSTRACT FROM AUTHOR]

Published
2023
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25. sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

Author

Sabatini, Francesco Maria, primary, Lenoir, Jonathan, additional, Hattab, Tarek, additional, Arnst, Elise Aimee, additional, Chytrý, Milan, additional, Dengler, Jürgen, additional, De Ruffray, Patrice, additional, Hennekens, Stephan M., additional, Jandt, Ute, additional, Jansen, Florian, additional, Jiménez‐Alfaro, Borja, additional, Kattge, Jens, additional, Levesley, Aurora, additional, Pillar, Valério D., additional, Purschke, Oliver, additional, Sandel, Brody, additional, Sultana, Fahmida, additional, Aavik, Tsipe, additional, Aćić, Svetlana, additional, Acosta, Alicia T. R., additional, Agrillo, Emiliano, additional, Alvarez, Miguel, additional, Apostolova, Iva, additional, Arfin Khan, Mohammed A. S., additional, Arroyo, Luzmila, additional, Attorre, Fabio, additional, Aubin, Isabelle, additional, Banerjee, Arindam, additional, Bauters, Marijn, additional, Bergeron, Yves, additional, Bergmeier, Erwin, additional, Biurrun, Idoia, additional, Bjorkman, Anne D., additional, Bonari, Gianmaria, additional, Bondareva, Viktoria, additional, Brunet, Jörg, additional, Čarni, Andraž, additional, Casella, Laura, additional, Cayuela, Luis, additional, Černý, Tomáš, additional, Chepinoga, Victor, additional, Csiky, János, additional, Ćušterevska, Renata, additional, De Bie, Els, additional, Gasper, André Luis, additional, De Sanctis, Michele, additional, Dimopoulos, Panayotis, additional, Dolezal, Jiri, additional, Dziuba, Tetiana, additional, El‐Sheikh, Mohamed Abd El‐Rouf Mousa, additional, Enquist, Brian, additional, Ewald, Jörg, additional, Fazayeli, Farideh, additional, Field, Richard, additional, Finckh, Manfred, additional, Gachet, Sophie, additional, Galán‐de‐Mera, Antonio, additional, Garbolino, Emmanuel, additional, Gholizadeh, Hamid, additional, Giorgis, Melisa, additional, Golub, Valentin, additional, Alsos, Inger Greve, additional, Grytnes, John‐Arvid, additional, Guerin, Gregory Richard, additional, Gutiérrez, Alvaro G., additional, Haider, Sylvia, additional, Hatim, Mohamed Z., additional, Hérault, Bruno, additional, Hinojos Mendoza, Guillermo, additional, Hölzel, Norbert, additional, Homeier, Jürgen, additional, Hubau, Wannes, additional, Indreica, Adrian, additional, Janssen, John A. M., additional, Jedrzejek, Birgit, additional, Jentsch, Anke, additional, Jürgens, Norbert, additional, Kącki, Zygmunt, additional, Kapfer, Jutta, additional, Karger, Dirk Nikolaus, additional, Kavgacı, Ali, additional, Kearsley, Elizabeth, additional, Kessler, Michael, additional, Khanina, Larisa, additional, Killeen, Timothy, additional, Korolyuk, Andrey, additional, Kreft, Holger, additional, Kühl, Hjalmar S., additional, Kuzemko, Anna, additional, Landucci, Flavia, additional, Lengyel, Attila, additional, Lens, Frederic, additional, Lingner, Débora Vanessa, additional, Liu, Hongyan, additional, Lysenko, Tatiana, additional, Mahecha, Miguel D., additional, Marcenò, Corrado, additional, Martynenko, Vasiliy, additional, Moeslund, Jesper Erenskjold, additional, Monteagudo Mendoza, Abel, additional, Mucina, Ladislav, additional, Müller, Jonas V., additional, Munzinger, Jérôme, additional, Naqinezhad, Alireza, additional, Noroozi, Jalil, additional, Nowak, Arkadiusz, additional, Onyshchenko, Viktor, additional, Overbeck, Gerhard E., additional, Pärtel, Meelis, additional, Pauchard, Aníbal, additional, Peet, Robert K., additional, Peñuelas, Josep, additional, Pérez‐Haase, Aaron, additional, Peterka, Tomáš, additional, Petřík, Petr, additional, Peyre, Gwendolyn, additional, Phillips, Oliver L., additional, Prokhorov, Vadim, additional, Rašomavičius, Valerijus, additional, Revermann, Rasmus, additional, Rivas‐Torres, Gonzalo, additional, Rodwell, John S., additional, Ruprecht, Eszter, additional, Rūsiņa, Solvita, additional, Samimi, Cyrus, additional, Schmidt, Marco, additional, Schrodt, Franziska, additional, Shan, Hanhuai, additional, Shirokikh, Pavel, additional, Šibík, Jozef, additional, Šilc, Urban, additional, Sklenář, Petr, additional, Škvorc, Željko, additional, Sparrow, Ben, additional, Sperandii, Marta Gaia, additional, Stančić, Zvjezdana, additional, Svenning, Jens‐Christian, additional, Tang, Zhiyao, additional, Tang, Cindy Q., additional, Tsiripidis, Ioannis, additional, Vanselow, Kim André, additional, Vásquez Martínez, Rodolfo, additional, Vassilev, Kiril, additional, Vélez‐Martin, Eduardo, additional, Venanzoni, Roberto, additional, Vibrans, Alexander Christian, additional, Violle, Cyrille, additional, Virtanen, Risto, additional, Wehrden, Henrik, additional, Wagner, Viktoria, additional, Walker, Donald A., additional, Waller, Donald M., additional, Wang, Hua‐Feng, additional, Wesche, Karsten, additional, Whitfeld, Timothy J. S., additional, Willner, Wolfgang, additional, Wiser, Susan K., additional, Wohlgemuth, Thomas, additional, Yamalov, Sergey, additional, Zobel, Martin, additional, Bruelheide, Helge, additional, and Bates, Amanda, additional

Published
2021
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26. Climate and socio‐economic factors explain differences between observed and expected naturalization patterns of European plants around the world

Author

Pouteau, Robin, primary, Thuiller, Wilfried, additional, Hobohm, Carsten, additional, Brunel, Caroline, additional, Conn, Barry J., additional, Dawson, Wayne, additional, Sá Dechoum, Michele, additional, Ebel, Aleksandr L., additional, Essl, Franz, additional, Fragman‐Sapir, Ori, additional, Fristoe, Trevor, additional, Jogan, Nejc, additional, Kreft, Holger, additional, Lenzner, Bernd, additional, Meyer, Carsten, additional, Pergl, Jan, additional, Pyšek, Petr, additional, Verkhozina, Alla, additional, Weigelt, Patrick, additional, Yang, Qiang, additional, Zykova, Elena, additional, Aćić, Svetlana, additional, Agrillo, Emiliano, additional, Attorre, Fabio, additional, Bergamini, Ariel, additional, Berg, Christian, additional, Bergmeier, Erwin, additional, Biurrun, Idoia, additional, Boch, Steffen, additional, Bonari, Gianmaria, additional, Botta‐Dukát, Zoltán, additional, Bruelheide, Helge, additional, Campos, Juan Antonio, additional, Čarni, Andraž, additional, Casella, Laura, additional, Carranza, Maria Laura, additional, Chytrý, Milan, additional, Ćušterevska, Renata, additional, De Sanctis, Michele, additional, Dengler, Jürgen, additional, Dimopoulos, Panayotis, additional, Ejrnæs, Rasmus, additional, Ewald, Jörg, additional, Fanelli, Giuliano, additional, Fernández‐González, Federico, additional, Gavilán, Rosario G., additional, Gegout, Jean‐Claude, additional, Haveman, Rense, additional, Isermann, Maike, additional, Jandt, Ute, additional, Jansen, Florian, additional, Jiménez‐Alfaro, Borja, additional, Kavgacı, Ali, additional, Khanina, Larisa, additional, Knollová, Ilona, additional, Kuzemko, Anna, additional, Lebedeva, Maria, additional, Lenoir, Jonathan, additional, Lysenko, Tatiana, additional, Marcenò, Corrado, additional, Martynenko, Vasiliy, additional, Moeslund, Jesper Erenskjold, additional, Pätsch, Ricarda, additional, Pielech, Remigiusz, additional, Rašomavičius, Valerijus, additional, Ronde, Iris, additional, Ruprecht, Eszter, additional, Rūsiņa, Solvita, additional, Shirokikh, Pavel, additional, Šibík, Jozef, additional, Šilc, Urban, additional, Stanisci, Angela, additional, Stančić, Zvjezdana, additional, Svenning, Jens‐Christian, additional, Swacha, Grzegorz, additional, Dan Turtureanu, Pavel, additional, Valachovič, Milan, additional, Vassilev, Kiril, additional, Yamalov, Sergey, additional, and Kleunen, Mark, additional

Published
2021
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27. Heavy metals alongside railway lines – review

Author

Stančić, Zvjezdana and Fiket, Željka

Subjects
railway transport, pollution, heavy metals
Abstract

Railway transport, in addition to its advantages, also has negative impacts on the environment. One is the emission of heavy metals (HMs) and their deposition in the soil. The highest measured mass concentrations occur in the topsoil in the vicinity of the rails, but some of the HMs are washed into groundwater ; with heavier precipitation, the surface runoff transfers the HMs to more distant areas. Some are also absorbed by plants and enter the food web, ultimately appearing in human food. Most HMs above certain concentrations are toxic to living organisms. With ecological and environmental concerns in mind, studies of HMs alongside railways in various countries of the world are compared. Emphasis is placed on the following topics: which chemical elements (HMs) occur as contaminants in the topsoil, and how distance from the rails and different managed areas alongside railway lines impact mass concentration of HMs in the soil. In general, there is not much published investigation on this issue in the scientific literature ; the greatest contributions are from Poland and China. In most papers, the environmental influence of fewer than 10 chemical elements is analysed, and the most common are Pb, Zn, Cu, Cd, Cr, Ni, Co and Mn.

Published
2021

28. Influence of different habitat types on heavy metal content along railway lines

Author

Stančić, Zvjezdana, Fiket, Željka, and Vuger, Andreja

Subjects
heavy metals, railway, habitats, Croatia
Abstract

There are many studies on heavy metals in the scientific literature, but relatively few of them relate to surfaces along the railway lines. This is worrying because the network of railway lines is built all over the world, and it passes through cities, settlements, agricultural and natural areas, and represents a significant source of environmental pollution. In order to increase knowledge on this issue, during 2014, in the northwestern Croatia, 60 soil samples were collected along railway lines in six common habitat types (i - habitats without plants, ii - with annual plants, iii - with horsetail, iv - mowed surfaces with dandelion, v - abandoned habitats in succession, vi - stands with goldenrod). The content of 29 chemical elements was determined using a high resolution inductively coupled plasma mass spectrometer (HR-ICP-MS). The results show higher mass concentrations of heavy metals in the habitats i, ii and iii. However, beside the habitat types, elevated concentrations of heavy metals are also affected by the following factors: soil texture, humus content, soil reaction, distance from the tracks, sampling site functionality, topography, and age of railway. The concentrations of the following chemical elements (in relation to the median for European soils and background values) were found to be particularly elevated: As, Cd, Cr, Cu, Fe, Mn, Mo, Ni, Pb, Sb, Sn, and Zn.

Published
2021

29. The muddy journey continues… Further developments of the project WetVegEurope

Author

Landucci, Flavia, Šumberová, Kateřina, Sinkevičienė, Zofija, Bita-Nicolae, Claudia, Čarni, Andraž, Golub, Valentin, Hájek, Michal, Hájková, Petra, Hrivnák, Richard, Iemelianova, Svitlana, Jansen, Florian, Kącki, Zygmunt, Lájer, Konrád, Molina, José Antonio, Oosterlynck, Patrik, Papastergiadou, Eva, Šilc, Urban, Stančić, Zvjezdana, Teteryuk, Boris, Tzonev, Rossen, Venanzoni, Roberto, Theurillat, Jean-Paul, Chytrý, Milan, Chytrý, Milan, Biurrun, Idoia, Attorre, Fabio, and Agrillo, Emiliano

Subjects
marsh vegetation, Phragmito-Magnocaricetea, Europe
Abstract

The project WetVegEurope began in 2013, intending to review the existing literature and produce a consistent and unequivocal phytosociological classification of the European marsh and aquatic vegetation at the association level. In 2020, a paper was published with a hierarchical formalized classification of the European marsh vegetation into 92 associations, 11 alliances and 6 orders of the class Phragmito-Magnocaricetea. It was mainly focused on the methodological and conceptual background of the classification. In 2021, the 4th edition of the International Code of Phytosociological Nomenclature was published. Therefore, an update of the syntaxonomic nomenclature of our classification units was needed. Along with this update, we produced an extensive monograph of Phragmito-Magnocaricetea in Europe with a revised syntaxonomic nomenclature (according to the new Code) and descriptions and distribution maps of the associations. The work is still in progress, involving several experts who are writing descriptions of individual units. The distribution maps were created using the same data as used for the classification, literature information and knowledge of the experts involved in the project. The nomenclature part has been revised by some authors with the help of the members of the Steering Committee of the IAVS Group for Phytosociological Nomenclature (GPN).

Published
2021

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

Author

Pouteau, Robin, Thuiller, Wilfried, Hobohm, Carsten, Brunel, Caroline, Conn, Barry J., Dawson, Wayne, Sá Dechoum, Michele, Ebel, Aleksandr L., Essl, Franz, Fragman‐Sapir, Ori, Fristoe, Trevor, Jogan, Nejc, Kreft, Holger, Lenzner, Bernd, Meyer, Carsten, Pergl, Jan, Pyšek, Petr, Verkhozina, Alla, Weigelt, Patrick, Yang, Qiang, Zykova, Elena, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergamini, Ariel, Berg, Christian, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bonari, Gianmaria, Botta‐Dukát, Zoltán, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Carranza, Maria Laura, Chytrý, Milan, Ćušterevska, Renata, De Sanctis, Michele, Dengler, Jürgen, Dimopoulos, Panayotis, Ejrnæs, Rasmus, Ewald, Jörg, Fanelli, Giuliano, Fernández‐González, Federico, Gavilán, Rosario G., Gegout, Jean‐Claude, Haveman, Rense, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jiménez‐Alfaro, Borja, Kavgacı, Ali, Khanina, Larisa, Knollová, Ilona, Kuzemko, Anna, Lebedeva, Maria, Lenoir, Jonathan, Lysenko, Tatiana, Marcenò, Corrado, Martynenko, Vasiliy, Moeslund, Jesper Erenskjold, Pätsch, Ricarda, Pielech, Remigiusz, Rašomavičius, Valerijus, de Ronde, Iris, Ruprecht, Eszter, Rūsiņa, Solvita, Shirokikh, Pavel, Šibík, Jozef, Šilc, Urban, Stanisci, Angela, Stančić, Zvjezdana, Svenning, Jens‐Christian, Swacha, Grzegorz, Dan Turtureanu, Pavel, Valachovič, Milan, Vassilev, Kiril, Yamalov, Sergey, van Kleunen, Mark, Pouteau, Robin, Thuiller, Wilfried, Hobohm, Carsten, Brunel, Caroline, Conn, Barry J., Dawson, Wayne, Sá Dechoum, Michele, Ebel, Aleksandr L., Essl, Franz, Fragman‐Sapir, Ori, Fristoe, Trevor, Jogan, Nejc, Kreft, Holger, Lenzner, Bernd, Meyer, Carsten, Pergl, Jan, Pyšek, Petr, Verkhozina, Alla, Weigelt, Patrick, Yang, Qiang, Zykova, Elena, Aćić, Svetlana, Agrillo, Emiliano, Attorre, Fabio, Bergamini, Ariel, Berg, Christian, Bergmeier, Erwin, Biurrun, Idoia, Boch, Steffen, Bonari, Gianmaria, Botta‐Dukát, Zoltán, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Casella, Laura, Carranza, Maria Laura, Chytrý, Milan, Ćušterevska, Renata, De Sanctis, Michele, Dengler, Jürgen, Dimopoulos, Panayotis, Ejrnæs, Rasmus, Ewald, Jörg, Fanelli, Giuliano, Fernández‐González, Federico, Gavilán, Rosario G., Gegout, Jean‐Claude, Haveman, Rense, Isermann, Maike, Jandt, Ute, Jansen, Florian, Jiménez‐Alfaro, Borja, Kavgacı, Ali, Khanina, Larisa, Knollová, Ilona, Kuzemko, Anna, Lebedeva, Maria, Lenoir, Jonathan, Lysenko, Tatiana, Marcenò, Corrado, Martynenko, Vasiliy, Moeslund, Jesper Erenskjold, Pätsch, Ricarda, Pielech, Remigiusz, Rašomavičius, Valerijus, de Ronde, Iris, Ruprecht, Eszter, Rūsiņa, Solvita, Shirokikh, Pavel, Šibík, Jozef, Šilc, Urban, Stanisci, Angela, Stančić, Zvjezdana, Svenning, Jens‐Christian, Swacha, Grzegorz, Dan Turtureanu, Pavel, Valachovič, Milan, Vassilev, Kiril, Yamalov, Sergey, and van Kleunen, Mark

Abstract

Aim: 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

Published
2021

31. sPlotOpen : an environmentally balanced, open‐access, global dataset of vegetation plots

Author

Sabatini, Francesco Maria, Lenoir, Jonathan, Hattab, Tarek, Arnst, Elise Aimee, Chytrý, Milan, Dengler, Jürgen, De Ruffray, Patrice, Hennekens, Stephan M., Jandt, Ute, Jansen, Florian, Jiménez‐Alfaro, Borja, Kattge, Jens, Levesley, Aurora, Pillar, Valério D., Purschke, Oliver, Sandel, Brody, Sultana, Fahmida, Aavik, Tsipe, Aćić, Svetlana, Acosta, Alicia T. R., Agrillo, Emiliano, Alvarez, Miguel, Apostolova, Iva, Arfin Khan, Mohammed A. S., Arroyo, Luzmila, Attorre, Fabio, Aubin, Isabelle, Banerjee, Arindam, Bauters, Marijn, Bergeron, Yves, Bergmeier, Erwin, Biurrun, Idoia, Bjorkman, Anne D., Bonari, Gianmaria, Bondareva, Viktoria, Brunet, Jörg, Čarni, Andraž, Casella, Laura, Cayuela, Luis, Černý, Tomáš, Chepinoga, Victor, Csiky, János, Ćušterevska, Renata, De Bie, Els, Gasper, André Luis, De Sanctis, Michele, Dimopoulos, Panayotis, Dolezal, Jiri, Dziuba, Tetiana, El‐Sheikh, Mohamed Abd El‐Rouf Mousa, Enquist, Brian, Ewald, Jörg, Fazayeli, Farideh, Field, Richard, Finckh, Manfred, Gachet, Sophie, Galán‐de‐Mera, Antonio, Garbolino, Emmanuel, Gholizadeh, Hamid, Giorgis, Melisa, Golub, Valentin, Alsos, Inger Greve, Grytnes, John‐Arvid, Guerin, Gregory Richard, Gutiérrez, Alvaro G., Haider, Sylvia, Hatim, Mohamed Z., Hérault, Bruno, Hinojos Mendoza, Guillermo, Hölzel, Norbert, Homeier, Jürgen, Hubau, Wannes, Indreica, Adrian, Janssen, John A. M., Jedrzejek, Birgit, Jentsch, Anke, Jürgens, Norbert, Kącki, Zygmunt, Kapfer, Jutta, Karger, Dirk Nikolaus, Kavgacı, Ali, Kearsley, Elizabeth, Kessler, Michael, Khanina, Larisa, Killeen, Timothy, Korolyuk, Andrey, Kreft, Holger, Kühl, Hjalmar S., Kuzemko, Anna, Landucci, Flavia, Lengyel, Attila, Lens, Frederic, Lingner, Débora Vanessa, Liu, Hongyan, Lysenko, Tatiana, Mahecha, Miguel D., Marcenò, Corrado, Martynenko, Vasiliy, Moeslund, Jesper Erenskjold, Monteagudo Mendoza, Abel, Mucina, Ladislav, Müller, Jonas V., Munzinger, Jérôme, Naqinezhad, Alireza, Noroozi, Jalil, Nowak, Arkadiusz, Onyshchenko, Viktor, Overbeck, Gerhard E., Pärtel, Meelis, Pauchard, Aníbal, Peet, Robert K., Peñuelas, Josep, Pérez‐Haase, Aaron, Peterka, Tomáš, Petřík, Petr, Peyre, Gwendolyn, Phillips, Oliver L., Prokhorov, Vadim, Rašomavičius, Valerijus, Revermann, Rasmus, Rivas‐Torres, Gonzalo, Rodwell, John S., Ruprecht, Eszter, Rūsiņa, Solvita, Samimi, Cyrus, Schmidt, Marco, Schrodt, Franziska, Shan, Hanhuai, Shirokikh, Pavel, Šibík, Jozef, Šilc, Urban, Sklenář, Petr, Škvorc, Željko, Sparrow, Ben, Sperandii, Marta Gaia, Stančić, Zvjezdana, Svenning, Jens‐Christian, Tang, Zhiyao, Tang, Cindy Q., Tsiripidis, Ioannis, Vanselow, Kim André, Vásquez Martínez, Rodolfo, Vassilev, Kiril, Vélez‐Martin, Eduardo, Venanzoni, Roberto, Vibrans, Alexander Christian, Violle, Cyrille, Virtanen, Risto, Wehrden, Henrik, Wagner, Viktoria, Walker, Donald A., Waller, Donald M., Wang, Hua‐Feng, Wesche, Karsten, Whitfeld, Timothy J. S., Willner, Wolfgang, Wiser, Susan K., Wohlgemuth, Thomas, Yamalov, Sergey, Zobel, Martin, Bruelheide, Helge, Sabatini, Francesco Maria, Lenoir, Jonathan, Hattab, Tarek, Arnst, Elise Aimee, Chytrý, Milan, Dengler, Jürgen, De Ruffray, Patrice, Hennekens, Stephan M., Jandt, Ute, Jansen, Florian, Jiménez‐Alfaro, Borja, Kattge, Jens, Levesley, Aurora, Pillar, Valério D., Purschke, Oliver, Sandel, Brody, Sultana, Fahmida, Aavik, Tsipe, Aćić, Svetlana, Acosta, Alicia T. R., Agrillo, Emiliano, Alvarez, Miguel, Apostolova, Iva, Arfin Khan, Mohammed A. S., Arroyo, Luzmila, Attorre, Fabio, Aubin, Isabelle, Banerjee, Arindam, Bauters, Marijn, Bergeron, Yves, Bergmeier, Erwin, Biurrun, Idoia, Bjorkman, Anne D., Bonari, Gianmaria, Bondareva, Viktoria, Brunet, Jörg, Čarni, Andraž, Casella, Laura, Cayuela, Luis, Černý, Tomáš, Chepinoga, Victor, Csiky, János, Ćušterevska, Renata, De Bie, Els, Gasper, André Luis, De Sanctis, Michele, Dimopoulos, Panayotis, Dolezal, Jiri, Dziuba, Tetiana, El‐Sheikh, Mohamed Abd El‐Rouf Mousa, Enquist, Brian, Ewald, Jörg, Fazayeli, Farideh, Field, Richard, Finckh, Manfred, Gachet, Sophie, Galán‐de‐Mera, Antonio, Garbolino, Emmanuel, Gholizadeh, Hamid, Giorgis, Melisa, Golub, Valentin, Alsos, Inger Greve, Grytnes, John‐Arvid, Guerin, Gregory Richard, Gutiérrez, Alvaro G., Haider, Sylvia, Hatim, Mohamed Z., Hérault, Bruno, Hinojos Mendoza, Guillermo, Hölzel, Norbert, Homeier, Jürgen, Hubau, Wannes, Indreica, Adrian, Janssen, John A. M., Jedrzejek, Birgit, Jentsch, Anke, Jürgens, Norbert, Kącki, Zygmunt, Kapfer, Jutta, Karger, Dirk Nikolaus, Kavgacı, Ali, Kearsley, Elizabeth, Kessler, Michael, Khanina, Larisa, Killeen, Timothy, Korolyuk, Andrey, Kreft, Holger, Kühl, Hjalmar S., Kuzemko, Anna, Landucci, Flavia, Lengyel, Attila, Lens, Frederic, Lingner, Débora Vanessa, Liu, Hongyan, Lysenko, Tatiana, Mahecha, Miguel D., Marcenò, Corrado, Martynenko, Vasiliy, Moeslund, Jesper Erenskjold, Monteagudo Mendoza, Abel, Mucina, Ladislav, Müller, Jonas V., Munzinger, Jérôme, Naqinezhad, Alireza, Noroozi, Jalil, Nowak, Arkadiusz, Onyshchenko, Viktor, Overbeck, Gerhard E., Pärtel, Meelis, Pauchard, Aníbal, Peet, Robert K., Peñuelas, Josep, Pérez‐Haase, Aaron, Peterka, Tomáš, Petřík, Petr, Peyre, Gwendolyn, Phillips, Oliver L., Prokhorov, Vadim, Rašomavičius, Valerijus, Revermann, Rasmus, Rivas‐Torres, Gonzalo, Rodwell, John S., Ruprecht, Eszter, Rūsiņa, Solvita, Samimi, Cyrus, Schmidt, Marco, Schrodt, Franziska, Shan, Hanhuai, Shirokikh, Pavel, Šibík, Jozef, Šilc, Urban, Sklenář, Petr, Škvorc, Željko, Sparrow, Ben, Sperandii, Marta Gaia, Stančić, Zvjezdana, Svenning, Jens‐Christian, Tang, Zhiyao, Tang, Cindy Q., Tsiripidis, Ioannis, Vanselow, Kim André, Vásquez Martínez, Rodolfo, Vassilev, Kiril, Vélez‐Martin, Eduardo, Venanzoni, Roberto, Vibrans, Alexander Christian, Violle, Cyrille, Virtanen, Risto, Wehrden, Henrik, Wagner, Viktoria, Walker, Donald A., Waller, Donald M., Wang, Hua‐Feng, Wesche, Karsten, Whitfeld, Timothy J. S., Willner, Wolfgang, Wiser, Susan K., Wohlgemuth, Thomas, Yamalov, Sergey, Zobel, Martin, and Bruelheide, Helge

Abstract

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 m². Time period and grain: 1888–2015, recording dates. Major taxa and level of measurement: 42,677

Published
2021

35. 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, Cuk, Mirjana, Custerevska, 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, Schaminée, Joop, 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, Cuk, Mirjana, Custerevska, 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

Abstract

Contains fulltext : 222360.pdf (publisher's version ) (Open Access), 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 electroni

Published
2020

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

Author

Biología vegetal y ecología, Landaren biologia eta ekologia, 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 Galarraga, Miren Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos Prieto, 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, Korolyuk, Andrey Yu., 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, Schaminée, Joop H. J., Biología vegetal y ecología, Landaren biologia eta ekologia, 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 Galarraga, Miren Idoia, Boch, Steffen, Bölöni, János, Bonari, Gianmaria, Braslavskaya, Tatiana, Bruelheide, Helge, Campos Prieto, 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, Korolyuk, Andrey Yu., 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.

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

37. EUNIS-ESy: Expert system for automatic classification of European vegetation plots to EUNIS 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, Schaminée, Joop H.J., 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.

Abstract

EUNIS-ESy is an expert system for automatic classification of European vegetation plots to habitat types of the EUNIS Habitat Classification. The EUNIS classification and the principles of the expert system are described by Chytrý et al. (2020). The classification of a set of vegetation plots can be run using the JUICE program (Tichý 2002; https://www.sci.muni.cz/botany/juice/), TURBOVEG 3 program (Hennekens 2015) and an R script (Bruelheide et al. 2021). This dataset contains two parts: (1) the expert system and related files necessary for running it; (2) characterization of EUNIS habitats based on the results of the expert system classification., EUNIS-ESy is an expert system for automatic classification of European vegetation plots to habitat types of the EUNIS Habitat Classification. The EUNIS classification and the principles of the expert system are described by Chytrý et al. (2020). The classification of a set of vegetation plots can be run using the JUICE program (Tichý 2002; https://www.sci.muni.cz/botany/juice/), TURBOVEG 3 program (Hennekens 2015) and an R script (Bruelheide et al. 2021). This dataset contains two parts: (1) the expert system and related files necessary for running it; (2) characterization of EUNIS habitats based on the results of the expert system classification. 1. Expert system and related files necessary to run it 1.1. EUNIS-ESy-2021-06-01.txt – a file containing the script for the classification of vegetation plots by EUNIS-ESy. This version contains tested definitions for the revised classification vegetated Marine (coastal saltmarshes), Coastal, Wetland, Grassland, Shrubland, Forest, Inland sparsely vegetated and Man-made habitats, and preliminary non-tested definitions of the older classification of Marine, Aquatic and Inland sparsely vegetated habitats. 1.2. Nomenclature-translation-from-Turboveg-2-databases.zip – an archive containing the scripts for automatic translation of taxon concepts and names used in individual European Turboveg 2 databases (Hennekens & Schaminée 2001; https://www.synbiosys.alterra.nl/turboveg/) to the nomenclature that can be used as an input for EUNIS-ESy. 1.3. EUNIS-ESy-User-Guide.pdf – a brief user guide to the classification of vegetation plots by EUNIS-ESy using the JUICE program. Please read this guide carefully before running the expert system to avoid misclassifications. 2. Characterization of the EUNIS habitats based on the results of the EUNIS-ESy classification 2.1. EUNIS-habitats-2021-06-01.xlsx – the current list o

Published
2020

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

Author

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

Published
2020
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39. Classification of the European marsh vegetation (Phragmito‐Magnocaricetea) to the association level

Author

Landucci, Flavia, primary, Šumberová, Kateřina, additional, Tichý, Lubomír, additional, Hennekens, Stephan, additional, Aunina, Liene, additional, Biță‐Nicolae, Claudia, additional, Borsukevych, Lyubov, additional, Bobrov, Alexander, additional, Čarni, Andraž, additional, Bie, Els De, additional, Golub, Valentin, additional, Hrivnák, Richard, additional, Iemelianova, Svitlana, additional, Jandt, Ute, additional, Jansen, Florian, additional, Kącki, Zygmunt, additional, Lájer, Konrád, additional, Papastergiadou, Eva, additional, Šilc, Urban, additional, Sinkevičienė, Zofija, additional, Stančić, Zvjezdana, additional, Stepanovič, Jazep, additional, Teteryuk, Boris, additional, Tzonev, Rossen, additional, Venanzoni, Roberto, additional, Zelnik, Igor, additional, and Chytrý, Milan, additional

Published
2020
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41. sPlot : a new tool for global vegetation analyses

Author

Bruelheide, Helge, Dengler, Jürgen, Jiménez‐Alfaro, Borja, Purschke, Oliver, Hennekens, Stephan M., Chytrý, Milan, Pillar, Valério D., Jansen, Florian, Kattge, Jens, Sandel, Brody, Aubin, Isabelle, Biurrun, Idoia, Field, Richard, Haider, Sylvia, Jandt, Ute, Lenoir, Jonathan, Peet, Robert K., Peyre, Gwendolyn, Sabatini, Francesco Maria, Schmidt, Marco, Schrodt, Franziska, Winter, Marten, Aćić, Svetlana, Agrillo, Emiliano, Alvarez, Miguel, Ambarlı, Didem, Angelini, Pierangela, Apostolova, Iva, Arfin Khan, Mohammed A. S., Arnst, Elise, Attorre, Fabio, Baraloto, Christopher, Beckmann, Michael, Berg, Christian, Bergeron, Yves, Bergmeier, Erwin, Bjorkman, Anne D., Bondareva, Viktoria, Borchardt, Peter, Botta‐Dukát, Zoltán, Boyle, Brad, Breen, Amy, Brisse, Henry, Byun, Chaeho, Cabido, Marcelo R., Casella, Laura, Cayuela, Luis, Černý, Tomáš, Chepinoga, Victor, Csiky, János, Curran, Michael, Ćušterevska, Renata, Dajić Stevanović, Zora, De Bie, Els, de Ruffray, Patrice, De Sanctis, Michele, Dimopoulos, Panayotis, Dressler, Stefan, Ejrnæs, Rasmus, El‐Sheikh, Mohamed Abd El‐Rouf Mousa, Enquist, Brian, Ewald, Jörg, Fagúndez, Jaime, Finckh, Manfred, Font, Xavier, Forey, Estelle, Fotiadis, Georgios, García‐Mijangos, Itziar, Gasper, André Luis, Golub, Valentin, Gutierrez, Alvaro G., Hatim, Mohamed Z., He, Tianhua, Higuchi, Pedro, Holubová, Dana, Hölzel, Norbert, Homeier, Jürgen, Indreica, Adrian, Işık Gürsoy, Deniz, Jansen, Steven, Janssen, John, Jedrzejek, Birgit, Jiroušek, Martin, Jürgens, Norbert, Kącki, Zygmunt, Kavgacı, Ali, Kearsley, Elizabeth, Kessler, Michael, Knollová, Ilona, Kolomiychuk, Vitaliy, Korolyuk, Andrey, Kozhevnikova, Maria, Kozub, Łukasz, Krstonošić, Daniel, Kühl, Hjalmar, Kühn, Ingolf, Kuzemko, Anna, Küzmič, Filip, Landucci, Flavia, Lee, Michael T., Levesley, Aurora, Li, Ching‐Feng, Liu, Hongyan, Lopez‐Gonzalez, Gabriela, Lysenko, Tatiana, Macanović, Armin, Mahdavi, Parastoo, Manning, Peter, Marcenò, Corrado, Martynenko, Vassiliy, Mencuccini, Maurizio, Minden, Vanessa, Moeslund, Jesper Erenskjold, Moretti, Marco, Müller, Jonas V., Munzinger, Jérôme, Niinemets, Ülo, Nobis, Marcin, Noroozi, Jalil, Nowak, Arkadiusz, Onyshchenko, Viktor, Overbeck, Gerhard E., Ozinga, Wim A., Pauchard, Anibal, Pedashenko, Hristo, Peñuelas, Josep, Pérez‐Haase, Aaron, Peterka, Tomáš, Petřík, Petr, Phillips, Oliver L., Prokhorov, Vadim, Rašomavičius, Valerijus, Revermann, Rasmus, Rodwell, John, Ruprecht, Eszter, Rūsiņa, Solvita, Samimi, Cyrus, Schaminée, Joop H.J., Schmiedel, Ute, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smyth, Anita, Sop, Tenekwetche, Sopotlieva, Desislava, Sparrow, Ben, Stančić, Zvjezdana, Svenning, Jens‐Christian, Swacha, Grzegorz, Tang, Zhiyao, Tsiripidis, Ioannis, Turtureanu, Pavel Dan, Uğurlu, Emin, Uogintas, Domas, Valachovič, Milan, Vanselow, Kim André, Vashenyak, Yulia, Vassilev, Kiril, Vélez‐Martin, Eduardo, Venanzoni, Roberto, Vibrans, Alexander Christian, Violle, Cyrille, Virtanen, Risto, Wehrden, Henrik, Wagner, Viktoria, Walker, Donald A., Wana, Desalegn, Weiher, Evan, Wesche, Karsten, Whitfeld, Timothy, Willner, Wolfgang, Wiser, Susan, Wohlgemuth, Thomas, Yamalov, Sergey, Zizka, Georg, Zverev, Andrei, Bruelheide, Helge, Dengler, Jürgen, Jiménez‐Alfaro, Borja, Purschke, Oliver, Hennekens, Stephan M., Chytrý, Milan, Pillar, Valério D., Jansen, Florian, Kattge, Jens, Sandel, Brody, Aubin, Isabelle, Biurrun, Idoia, Field, Richard, Haider, Sylvia, Jandt, Ute, Lenoir, Jonathan, Peet, Robert K., Peyre, Gwendolyn, Sabatini, Francesco Maria, Schmidt, Marco, Schrodt, Franziska, Winter, Marten, Aćić, Svetlana, Agrillo, Emiliano, Alvarez, Miguel, Ambarlı, Didem, Angelini, Pierangela, Apostolova, Iva, Arfin Khan, Mohammed A. S., Arnst, Elise, Attorre, Fabio, Baraloto, Christopher, Beckmann, Michael, Berg, Christian, Bergeron, Yves, Bergmeier, Erwin, Bjorkman, Anne D., Bondareva, Viktoria, Borchardt, Peter, Botta‐Dukát, Zoltán, Boyle, Brad, Breen, Amy, Brisse, Henry, Byun, Chaeho, Cabido, Marcelo R., Casella, Laura, Cayuela, Luis, Černý, Tomáš, Chepinoga, Victor, Csiky, János, Curran, Michael, Ćušterevska, Renata, Dajić Stevanović, Zora, De Bie, Els, de Ruffray, Patrice, De Sanctis, Michele, Dimopoulos, Panayotis, Dressler, Stefan, Ejrnæs, Rasmus, El‐Sheikh, Mohamed Abd El‐Rouf Mousa, Enquist, Brian, Ewald, Jörg, Fagúndez, Jaime, Finckh, Manfred, Font, Xavier, Forey, Estelle, Fotiadis, Georgios, García‐Mijangos, Itziar, Gasper, André Luis, Golub, Valentin, Gutierrez, Alvaro G., Hatim, Mohamed Z., He, Tianhua, Higuchi, Pedro, Holubová, Dana, Hölzel, Norbert, Homeier, Jürgen, Indreica, Adrian, Işık Gürsoy, Deniz, Jansen, Steven, Janssen, John, Jedrzejek, Birgit, Jiroušek, Martin, Jürgens, Norbert, Kącki, Zygmunt, Kavgacı, Ali, Kearsley, Elizabeth, Kessler, Michael, Knollová, Ilona, Kolomiychuk, Vitaliy, Korolyuk, Andrey, Kozhevnikova, Maria, Kozub, Łukasz, Krstonošić, Daniel, Kühl, Hjalmar, Kühn, Ingolf, Kuzemko, Anna, Küzmič, Filip, Landucci, Flavia, Lee, Michael T., Levesley, Aurora, Li, Ching‐Feng, Liu, Hongyan, Lopez‐Gonzalez, Gabriela, Lysenko, Tatiana, Macanović, Armin, Mahdavi, Parastoo, Manning, Peter, Marcenò, Corrado, Martynenko, Vassiliy, Mencuccini, Maurizio, Minden, Vanessa, Moeslund, Jesper Erenskjold, Moretti, Marco, Müller, Jonas V., Munzinger, Jérôme, Niinemets, Ülo, Nobis, Marcin, Noroozi, Jalil, Nowak, Arkadiusz, Onyshchenko, Viktor, Overbeck, Gerhard E., Ozinga, Wim A., Pauchard, Anibal, Pedashenko, Hristo, Peñuelas, Josep, Pérez‐Haase, Aaron, Peterka, Tomáš, Petřík, Petr, Phillips, Oliver L., Prokhorov, Vadim, Rašomavičius, Valerijus, Revermann, Rasmus, Rodwell, John, Ruprecht, Eszter, Rūsiņa, Solvita, Samimi, Cyrus, Schaminée, Joop H.J., Schmiedel, Ute, Šibík, Jozef, Šilc, Urban, Škvorc, Željko, Smyth, Anita, Sop, Tenekwetche, Sopotlieva, Desislava, Sparrow, Ben, Stančić, Zvjezdana, Svenning, Jens‐Christian, Swacha, Grzegorz, Tang, Zhiyao, Tsiripidis, Ioannis, Turtureanu, Pavel Dan, Uğurlu, Emin, Uogintas, Domas, Valachovič, Milan, Vanselow, Kim André, Vashenyak, Yulia, Vassilev, Kiril, Vélez‐Martin, Eduardo, Venanzoni, Roberto, Vibrans, Alexander Christian, Violle, Cyrille, Virtanen, Risto, Wehrden, Henrik, Wagner, Viktoria, Walker, Donald A., Wana, Desalegn, Weiher, Evan, Wesche, Karsten, Whitfeld, Timothy, Willner, Wolfgang, Wiser, Susan, Wohlgemuth, Thomas, Yamalov, Sergey, Zizka, Georg, and Zverev, Andrei

Abstract

Aims: 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.

Published
2019

42. Formalized classification of semi-dry grasslands of central and eastern Europe

Author

Willner, Wolfgang, Roleček, Jan, Korolyuk, Andrey, Dengler, Jürgen, Chytrý, Milan, Janišová, Monika, Lengyel, Attila, Aćić, Svetlana, Becker, Thomas, Ćuk, Mirjana, Demina, Olga, Jandt, Ute, Kącki, Zygmunt, Kuzemko, Anna, Kropf, Matthias, Lebedeva, Mariya, Semenishchenkov, Yuri, Šilc, Urban, Stančić, Zvjezdana, Staudinger, Markus, Vassilev, Kiril, Yamalov, Sergey, Willner, Wolfgang, Roleček, Jan, Korolyuk, Andrey, Dengler, Jürgen, Chytrý, Milan, Janišová, Monika, Lengyel, Attila, Aćić, Svetlana, Becker, Thomas, Ćuk, Mirjana, Demina, Olga, Jandt, Ute, Kącki, Zygmunt, Kuzemko, Anna, Kropf, Matthias, Lebedeva, Mariya, Semenishchenkov, Yuri, Šilc, Urban, Stančić, Zvjezdana, Staudinger, Markus, Vassilev, Kiril, and Yamalov, Sergey

Abstract

The European semi-dry grasslands belong to the most species-rich vegetation types of the northern hemisphere and form an important part of habitat mosaics of the forest-steppe zone. However, a comprehensive evaluation of compositional variation and phytosociological classification of these grasslands is still missing. For our syntaxonomic revision, we used a dataset of 34,173 vegetation plot records (relevés) from Central and Eastern Europe which were assigned to the class Festuco-Brometea 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. 15,449 relevés were assigned to the order Brachypodietalia pinnati, which corresponds to semi-dry grasslands. This subset was again classified with TWINSPAN. We established formal definitions for the following alliances: Mesobromion erecti, Cirsio-Brachypodion pinnati (incl. Fragario-Trifolion montani, Agrostio-Avenulion schellianae, Scabioso ochroleucae-Poion angustifoliae and Adonido vernalis-Stipion tirsae), Scorzonerion villosae and Chrysopogono-Danthonion. Another alliance, Armerion elongatae (= Koelerio-Phleion phleoidis p.p.), is transitional towards the class Koelerio-Corynephoretea and its status needs further evaluation. We also established formal definitions of all associations of the Mesobromion and Cirsio-Brachypodion within the study area. Associations were identified using (i) the TWINSPAN classification of the whole order, (ii) TWINSPAN classifications of regionally restricted data sets (usually all Brachypodietalia plots of one country) and (iii) existing national classification schemes. All formal definitions were written in the expert system language of the JUICE program. To get a more complete picture of the floristic similarities and gradients, we performed a DCA ordination of the associations. Our results show that meadow steppes of the forest-steppe zone of Eastern Europe are very similar to s

Published
2019

43. Heavy metals content in soil near railway lines in northwestern Croatia

Author

Stančić, Zvjezdana, Fiket, Željka, Mikac, Nevenka, Gomaz, Ana, Rezo, Milan, Jeftić, Goran, Vujević, Dinko, Radojčić Redovniković, Ivana, Jakovljević, Tamara, Petravić Tominac, Vlatka, Panić, Manuela, Stojaković, Renata, Erdec, Dina, Radošević, Kristina, Gaurina Sarček, Višnja, and Cvjetko Bubalo, Marina

Subjects
heavy metals, soil pollution, railroad, high resolution inductively coupled plasma mass spectrometry (HR-ICP-MS)
Abstract

Railway transport contributes to heavy metals load in the environment due to fuel combustion, corrosion, rinsing of impregnating agents, herbicide use, transshipment and accidents during transport. The aim of this research was to determine potential heavy metals contamination in soil near the three railway lines in northwestern Croatia. In total, 60 samples of soil were collected from 60 localities near the Varaždin-Zagreb, the Varaždin-Golubovec and the Varaždin-Ludbreg railway lines in June and July 2014. Total mass concentrations of six heavy metals (Cd, Cr, Cu, Ni, Pb, Zn) were determined in soil samples with the method of a high resolution inductively coupled plasma mass spectrometry (HR-ICP-MS). Soil texture, pH and organic matter content were also determined. Soil contamination status was evaluated according to the Regulation on the protection of agricultural land from pollution (NN 9/14). Following mean values of the total heavy metal mass concentrations were obtained: Cd 0.62 mg/kg, Cr 96.5 mg/kg, Cu 120 mg/kg , Ni 60.9 mg/kg, Pb 67.8 mg/kg, and Zn 229 mg/kg. Evaluation of soil contamination degrees according to Croatian Regulation showed that soil in 16 localities (27 %) contained one or more heavy metals in concentration more than two times higher than the maximum permissible level (MPL), i.e. above 200 %. More specifically, contamination degree above 200 % was established in 6 localities for Cd, in 11 localities for Cr and Cu, in 12 localities for Ni, in 9 localities for Pb and in 21 locality for Zn. The highest degrees of heavy metal contamination were recorded at the railway station in Varaždin and Podsused, and none of the investigated localities have completely unpolluted soil. This study shows that soil near the mentioned railway lines may contain heavy metals in high concentrations. Since many railway lines in northwestern Croatia meander through arable land, they could also contribute to the entry of heavy metals in the human food chain and reduce the overall soil resource efficiency.

Published
2018

44. Possibility of accumulation of heavy metals in wild-growing plants near the railway lines

Author

Stančić, Zvjezdana, Fiket, Željka, Gomaz, Ana, and Mikac, Nevenka

Subjects
phytoaccumulation, phytoremediation, heavy metals, railway transport contamination, HR-ICP-MS method
Abstract

Phytoremediation is a promising method for removal of contaminants from the environment. It is an environmentally acceptable low cost method applicable to large areas. Use of wild plant species adapted to climate and habitat conditions is preferred. Therefore, the aim of this research was to investigate the possibility of phytoaccumulation of heavy metals (Cd, Cr, Cu, Ni, Pb and Zn) in habitats affected by railway transport. In Croatia, such habitats cover large surfaces. The study included soil and plant collected in June and July 2014 on 60 localities in northwestern Croatia alongside railway lines Zagreb-Varaždin, Varaždin-Golubovec and Varaždin-Ludbreg. The collected plant species included those which are often found near the mentioned railway lines: dandelion (Taraxacum officinale agg., number of samples n=27), goldenrod (Solidago gigantea Ait., n=25), fleabane (Erigeron annuus (L.) Pers., n=8), pepperweed (Lepidium sp., n=7), nettle (Urtica dioica L., n=6), ragweed (Ambrosia artemisiifolia L., n=4) and horsetail (Equisetum arvense L., n=4). Total mass concentrations of heavy metals in both soil and plant samples were detected by high resolution inductively coupled plasma mass spectrometry (HR-ICP-MS) method. The results showed the following: Cd displayed highest average concentration in ragweed (0.30 mg/kg of dry weight, d.w.) and dandelion (0.22 mg/kg d.w.) ; Cr in ragweed (22.9 mg/kg d.w.) and pepperweed (18.2 mg/kg d.w.) ; Cu in ragweed (19.7 mg/kg d.w.), fleabane (12.5 mg/kg d.w.) and dandelion (12.3 mg/kg d.w.) ; Ni in ragweed (9.06 mg/kg d.w.) and pepperweed (7.23 mg/kg d.w.) ; Pb in ragweed (4.05 mg/kg d.w.) ; Zn in ragweed (108 mg/kg d.w.) and dandelion (44.8 mg/kg d.w.). The highest average phytoaccumulation coefficients were calculated for Zn in ragweed (0.55), pepperweed (0.43) and dandelion (0.30) ; for Cd in dandelion (0.47), nettle (0.35), pepperweed (0.35) and ragweed (0.31) ; for Cu in nettle (0.31) ; and for Cr in pepperweed (0.30). In conclusion, ragweed, dandelion, pepperweed and nettle would make good candidates for use in phytoremediation since they are wild-growing and widely distributed alongside railroad lines in Croatia and in the region.

Published
2018

45. Possibility of using foreign invasive species in phytoremediation: example of giant goldenrod (Solidago gigantea Ait.)

Author

Stančić, Zvjezdana, Fiket, Željka, Mikac, Nevenka, Gomaz, Ana, Rezo, Milan, Jeftić, Goran, Kunješić, Natalija, Klarić, Andrej, Radojčić Redovniković, Ivana, Jakovljević, Tamara, Petravić Tominac, Vlatka, Panić, Manuela, Stojaković, Renata, Erdec, Dina, Radošević, Kristina, Gaurina Sarček, Višnja, and Cvjetko Bubalo, Marina

Subjects
railway transport, pollution, heavy metals, phytoremediation, HR-ICP-MS method
Abstract

Soil and giant goldenrod (Solidago gigantea Ait.) samples were collected in June and July 2014 on 25 localities in northwestern Croatia alongside railroad lines Zagreb-Varaždin, Varaždin-Golubovec and Varaždin-Ludbreg. The aim of this research was to investigate the phytoaccumulation potential of giant goldenrod on surfaces affected by railway transport for the following heavy metals: Cd, Cr, Cu, Ni, Pb and Zn. Total concentrations of heavy metals in soil and plant samples were determined by a high resolution inductively coupled plasma mass spectrometry (HR-ICP-MS) method. The results of the analysis showed the following: goldenrod samples contained the highest average concentration of Zn (27.0 mg/kg, d.w.), followed by Cu (6.36 mg/kg, d.w.), Cr (1.54 mg/kg, d.w.), Ni (0.844 mg/kg, d.w.), Pb (0.544 mg/kg, d.w.) and Cd (0.068 mg/kg, d.w.). Phytoaccumulation coefficients, which show how successfully a plant removes certain pollutants from the environment, were calculated from the mass concentrations of heavy metals in plant and soil samples. The average phytoaccumulation coefficients for goldenrod were the following: for Zn (0.215), for Cd (0.185), for Cu (0.180), for Cr (0.023), for Ni (0.023) and for Pb (0.017). According to the literature, phytoaccumulation coefficients of plant species suitable for phytoremediation should be greater than 1. However, goldenrod has several advantages in comparison with other plants hyperaccumulators which should be considered. Goldenrod creates large biomass per unit area during the vegetation season and stands cover large areas of abandoned arable land, meadows and similar habitats in continental Croatia. Also, goldenrod is an invasive species in Croatian flora and its removal by mowing, alongside heavy metal phytoremediation, would be also desirable from the aspect of nature protection, as this creates conditions for the restoration of autochthonous vegetation.

Published
2018

46. Evaluating climatic threats to habitat types based on co-occurrence patterns of characteristic species

Author

Baatar, Undrakh-Od, primary, Dirnböck, Thomas, additional, Essl, Franz, additional, Moser, Dietmar, additional, Wessely, Johannes, additional, Willner, Wolfgang, additional, Jiménez-Alfaro, Borja, additional, Agrillo, Emiliano, additional, Csiky, János, additional, Indreica, Adrian, additional, Jandt, Ute, additional, Kącki, Zygmunt, additional, Šilc, Urban, additional, Škvorc, Željko, additional, Stančić, Zvjezdana, additional, Valachovič, Milan, additional, and Dullinger, Stefan, additional

Published
2019
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47. sPlot – A new tool for global vegetation analyses

Author

Bruelheide, Helge, primary, Dengler, Jürgen, additional, Jiménez‐Alfaro, Borja, additional, Purschke, Oliver, additional, Hennekens, Stephan M., additional, Chytrý, Milan, additional, Pillar, Valério D., additional, Jansen, Florian, additional, Kattge, Jens, additional, Sandel, Brody, additional, Aubin, Isabelle, additional, Biurrun, Idoia, additional, Field, Richard, additional, Haider, Sylvia, additional, Jandt, Ute, additional, Lenoir, Jonathan, additional, Peet, Robert K., additional, Peyre, Gwendolyn, additional, Sabatini, Francesco Maria, additional, Schmidt, Marco, additional, Schrodt, Franziska, additional, Winter, Marten, additional, Aćić, Svetlana, additional, Agrillo, Emiliano, additional, Alvarez, Miguel, additional, Ambarlı, Didem, additional, Angelini, Pierangela, additional, Apostolova, Iva, additional, Arfin Khan, Mohammed A. S., additional, Arnst, Elise, additional, Attorre, Fabio, additional, Baraloto, Christopher, additional, Beckmann, Michael, additional, Berg, Christian, additional, Bergeron, Yves, additional, Bergmeier, Erwin, additional, Bjorkman, Anne D., additional, Bondareva, Viktoria, additional, Borchardt, Peter, additional, Botta‐Dukát, Zoltán, additional, Boyle, Brad, additional, Breen, Amy, additional, Brisse, Henry, additional, Byun, Chaeho, additional, Cabido, Marcelo R., additional, Casella, Laura, additional, Cayuela, Luis, additional, Černý, Tomáš, additional, Chepinoga, Victor, additional, Csiky, János, additional, Curran, Michael, additional, Ćušterevska, Renata, additional, Dajić Stevanović, Zora, additional, De Bie, Els, additional, de Ruffray, Patrice, additional, De Sanctis, Michele, additional, Dimopoulos, Panayotis, additional, Dressler, Stefan, additional, Ejrnæs, Rasmus, additional, El‐Sheikh, Mohamed Abd El‐Rouf Mousa, additional, Enquist, Brian, additional, Ewald, Jörg, additional, Fagúndez, Jaime, additional, Finckh, Manfred, additional, Font, Xavier, additional, Forey, Estelle, additional, Fotiadis, Georgios, additional, García‐Mijangos, Itziar, additional, de Gasper, André Luis, additional, Golub, Valentin, additional, Gutierrez, Alvaro G., additional, Hatim, Mohamed Z., additional, He, Tianhua, additional, Higuchi, Pedro, additional, Holubová, Dana, additional, Hölzel, Norbert, additional, Homeier, Jürgen, additional, Indreica, Adrian, additional, Işık Gürsoy, Deniz, additional, Jansen, Steven, additional, Janssen, John, additional, Jedrzejek, Birgit, additional, Jiroušek, Martin, additional, Jürgens, Norbert, additional, Kącki, Zygmunt, additional, Kavgacı, Ali, additional, Kearsley, Elizabeth, additional, Kessler, Michael, additional, Knollová, Ilona, additional, Kolomiychuk, Vitaliy, additional, Korolyuk, Andrey, additional, Kozhevnikova, Maria, additional, Kozub, Łukasz, additional, Krstonošić, Daniel, additional, Kühl, Hjalmar, additional, Kühn, Ingolf, additional, Kuzemko, Anna, additional, Küzmič, Filip, additional, Landucci, Flavia, additional, Lee, Michael T., additional, Levesley, Aurora, additional, Li, Ching‐Feng, additional, Liu, Hongyan, additional, Lopez‐Gonzalez, Gabriela, additional, Lysenko, Tatiana, additional, Macanović, Armin, additional, Mahdavi, Parastoo, additional, Manning, Peter, additional, Marcenò, Corrado, additional, Martynenko, Vassiliy, additional, Mencuccini, Maurizio, additional, Minden, Vanessa, additional, Moeslund, Jesper Erenskjold, additional, Moretti, Marco, additional, Müller, Jonas V., additional, Munzinger, Jérôme, additional, Niinemets, Ülo, additional, Nobis, Marcin, additional, Noroozi, Jalil, additional, Nowak, Arkadiusz, additional, Onyshchenko, Viktor, additional, Overbeck, Gerhard E., additional, Ozinga, Wim A., additional, Pauchard, Anibal, additional, Pedashenko, Hristo, additional, Peñuelas, Josep, additional, Pérez‐Haase, Aaron, additional, Peterka, Tomáš, additional, Petřík, Petr, additional, Phillips, Oliver L., additional, Prokhorov, Vadim, additional, Rašomavičius, Valerijus, additional, Revermann, Rasmus, additional, Rodwell, John, additional, Ruprecht, Eszter, additional, Rūsiņa, Solvita, additional, Samimi, Cyrus, additional, Schaminée, Joop H.J., additional, Schmiedel, Ute, additional, Šibík, Jozef, additional, Šilc, Urban, additional, Škvorc, Željko, additional, Smyth, Anita, additional, Sop, Tenekwetche, additional, Sopotlieva, Desislava, additional, Sparrow, Ben, additional, Stančić, Zvjezdana, additional, Svenning, Jens‐Christian, additional, Swacha, Grzegorz, additional, Tang, Zhiyao, additional, Tsiripidis, Ioannis, additional, Turtureanu, Pavel Dan, additional, Uğurlu, Emin, additional, Uogintas, Domas, additional, Valachovič, Milan, additional, Vanselow, Kim André, additional, Vashenyak, Yulia, additional, Vassilev, Kiril, additional, Vélez‐Martin, Eduardo, additional, Venanzoni, Roberto, additional, Vibrans, Alexander Christian, additional, Violle, Cyrille, additional, Virtanen, Risto, additional, von Wehrden, Henrik, additional, Wagner, Viktoria, additional, Walker, Donald A., additional, Wana, Desalegn, additional, Weiher, Evan, additional, Wesche, Karsten, additional, Whitfeld, Timothy, additional, Willner, Wolfgang, additional, Wiser, Susan, additional, Wohlgemuth, Thomas, additional, Yamalov, Sergey, additional, Zizka, Georg, additional, and Zverev, Andrei, additional

Published
2019
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48. Formalized classification of semi-dry grasslands in central and eastern Europe

Author

Willner, Wolfgang, primary, Roleček, Jan, additional, Korolyuk, Andrey, additional, Dengler, Jürgen, additional, Chytrý, Milan, additional, Janišová, Monika, additional, Lengyel, Attila, additional, Aćić, Svetlana, additional, Becker, Thomas, additional, Ćuk, Mirjana, additional, Demina, Olga, additional, Jandt, Ute, additional, Kącki, Zygmunt, additional, Kuzemko, Anna, additional, Kropf, Matthias, additional, Lebedeva, Mariya, additional, Semenishchenkov, Yuri, additional, Šilc, Urban, additional, Stančić, Zvjezdana, additional, Staudinger, Markus, additional, Vassilev, Kiril, additional, and Yamalov, Sergey, additional

Published
2019
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50. Određivanje mase teških metala koju je moguće ukloniti fitoremedijacijom pomoću čestih samoniklih biljaka sa zelenih površina grada Varaždina (rad nagrađen Rektorovom nagradom za 2016. godinu)

Author

Košić, Mijo, Habulan, Nikolina, and Filipašić, Valentina (mentor: Stančić, Zvjezdana)

Subjects
fitoremedijacija, teški metali, maslačak, uskolisni trputac, bijela djetelina
Abstract

U današnje vrijeme teški metali u okolišu su sve veći problem za zdravlje ljudi. Stoga je cilj ovog rada bio utvrditi koliko se teških metala može ukloniti sa zelenih gradskih površina pomoću tri česte samonikle biljne vrste: maslačka (Taraxacum officinale agg.), uskolisnog trputca (Plantago lanceolata L.) i bijele djeteline (Trifolium repens L.). Pomoću metode atomske apsorpcijske spektrometrije u uzorcima tla i biljaka određivani su sljedeći teški metali: bakar (Cu), cink (Zn), kadmij (Cd), mangan (Mn), nikal (Ni), olovo (Pb) i željezo (Fe). Prikupljanje uzoraka tla i biljaka za laboratorijske analize teških metala provedeno je tijekom 2013. godine, a maseni udjeli ispitivanih biljaka na plohama veličine 1 m2 određeni su tijekom 2014. godine. I prvo i drugo uzorkovanje provedeno je na istih 16 postaja na području grada Varaždina i bliže okolice. Rezultati istraživanja pokazali su da je tlo na svih 16 postaja onečišćeno teškim metalima s različitim stupnjevima onečišćenja prema važećem Pravilniku. Od ispitivanih biljnih vrsta, maslačak je pokazao najbolju sposobnost fitoakumulacije kadmija (FAF=0, 88), uskolisni trputac također kadmija (FAF=0, 90), a bijela djetelina cinka (FAF=0, 62). Međutim, osim same sposobnosti akumulacije teških metala, važna je i biomasa koju pojedine vrste stvaraju po jedinici površine. Maslačak je sačinjavao 9, 79 % biomase u srpnju i 7, 96 % biomase u listopadu, uskolisni trputac 19, 38 % biomase u srpnju i 19, 36 % biomase u listopadu, a bijela djetelina 19, 15 % biomase u srpnju i 17, 65 % biomase u listopadu 2014. godine. Izračunato je da se pomoću sve tri biljke, koje sačinjavaju nešto manje od 50 % ukupne biomase biljaka na gradskim travnjacima, tijekom jedne godine može ukloniti 794, 64 mg/m2 željeza, 476, 53 mg/m2 cinka, 147, 07 mg/m2 mangana, 123, 16 mg/m2 bakra, 0, 50 mg/m2 nikla, 0, 46 mg/m2 olova i 0, 09 mg/m2 kadmija. Na temelju provedenih istraživanja može se zaključiti da se uklanjanjem otkosa s onečišćenih gradskih travnjačkih površina kroz određeni vremenski period može ukloniti određena količina teških metala. Prednost korištenja samoniklih biljaka je u tome što se njihovim korištenjem znatno pojeftinjuje i pojednostavljuje postupak fitoremedijacije tla.

Published
2016

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