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24. Mapping species richness of plant families in European vegetation.

Author

Večeřa, Martin, Axmanová, Irena, Cubino, Josep Padullés, Lososová, Zdeňka, Divíšek, Jan, Knollová, Ilona, Aćić, Svetlana, Biurrun, Idoia, Boch, Steffen, Bonari, Gianmaria, Campos, Juan Antonio, Čarni, Andraž, Laura Carranza, Maria, Casella, Laura, Chiarucci, Alessandro, Ćušterevska, Renata, Delbosc, Pauline, Dengler, Jürgen, Fernández-González, Federico, and Gégout, Jean-Claude

Subjects
SPECIES diversity, PLANT species, NUMBERS of species, GRID cells, PLANT species diversity
Abstract

Aims: Biodiversity is traditionally studied mostly at the species level, but biogeographical and macroecological studies at higher taxonomic levels can provide valuable insights into the evolutionary processes at large spatial scales. Our aim was to assess the representation of vascular plant families within different vegetation formations across Europe. Location: Europe. Methods: We used a data set of 816,005 vegetation plots from the European Vegetation Archive (EVA). For each plot, we calculated the relative species richness of each plant family as the number of species belonging to that family divided by the total number of species. We mapped the relative species richness, averaged across all plots in 50 km × 50 km grid cells, for each family and broad habitat groups: forests, grasslands, scrub and wetlands. We also calculated the absolute species richness and the Shannon diversity index for each family. Results: We produced 522 maps of mean relative species richness for a total of 152 vascular plant families occurring in forests, grasslands, scrub and wetlands. We found distinct spatial patterns for many combinations of families and habitat groups. The resulting series of 522 maps is freely available, both as images and GIS layers. Conclusions: The distinct spatial patterns revealed in the maps suggest that the relative species richness of plant families at the community level reflects the evolutionary history of individual families. We believe that the maps and associated data can inspire further biogeographical and macroecological studies and strengthen the ongoing integration of phylogenetic, functional and taxonomic diversity concepts. [ABSTRACT FROM AUTHOR]

Published
2021
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25. Recognizing and interpreting vegetational belts: New wine in the old bottles of a von Humboldt's legacy.

Author

Fattorini, Simone, Di Biase, Letizia, and Chiarucci, Alessandro

Subjects
WINE bottles, CHEMICAL plants, MOUNTAIN ecology, CLIMATE change, PHYTOGEOGRAPHY, DEFINITIONS
Abstract

Since von Humboldt, recognizing and using elevational subdivisions is at the core of biogeographical and ecological studies in mountain ecosystems. However, despite the large use of vegetational belts, their conceptual definition and practical identification appear to be surprisingly loose and inconsistent. Many authors use variations in climatic conditions to identify elevational belts. These belts are useful to set a framework for ecological studies but cannot be considered a surrogate of vegetational belts, because factors different from climate play a major role in determining the distribution of plant assemblages. Vegetation physiognomy can be used to identify 'biome‐type' belts that are useful for comparisons across geographical areas with different floras. However, to properly reflect ecological conditions at local scale, vegetational belts should be based on species composition. One of the most effective statistical approaches for this purpose is the use spatially constrained cluster analysis. The use of indicator species analysis may be also recommended to identify the species that most characterize vegetational belts. This can help researchers to identify belts in the field. Since species identification can be difficult, some authors use plant functional types for belt delimitation. Plant functional types can be helpful to trace the adaptative responses of vegetation along elevational gradients, but cannot be recommended as a standard way to identify belts. In general, criteria to identify vegetational belts can be based on both vegetation structure (namely physiognomy and structural parameters) and/or species composition, depending on the scale and the aim of the analyses, and they should be clearly stated. [ABSTRACT FROM AUTHOR]

Published
2019
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26. Quantifying plant species diversity in a Natura 2000 network: Old ideas and new proposals

Author

Chiarucci, Alessandro, Bacaro, Giovanni, and Rocchini, Duccio

Subjects
*SPECIES diversity, *SPATIAL analysis (Statistics), *PROTECTED areas, *PLANT diversity, *QUANTITATIVE research, *PLANT chemical analysis, *PLANT populations, *NATURE conservation, *PLANT monitoring
Abstract

Assessing the effects of the spatial components on species diversity in a network of protected areas represents an important step for assessing its conservation “capacity”. A clear evaluation on how α-, β-, and γ-diversity are partitioned among and within spatial scales can help to drive manager decisions and provide method for monitoring species diversity. Moving from these concepts, a probabilistic sample of plant species composition was here applied for quantifying plant species diversity within the Sites of Community Importance (SCIs) of the Natura 2000 network in the Siena Province. All analyses were performed separately for all species and those species defined as “focal” (included in regional, national or continental “red” lists). The results indicated that species richness of the SCIs differed from one location to another one independently from the sampling efforts. Diversity partitioning indicated that most of the flora diversity within the network was given by larger-scale β-diversity, i.e. the differences in species composition among SCIs. β-diversity was then decomposed in two components: β Area (due to the differences in area among SCIs) and β Replacement (due to the compositional differences across SCIs). β Area was particularly important for all species, while β Replacement was the most important factor for focal species. The consequent implications for monitoring and nature conservation strategies are discussed. [Copyright &y& Elsevier]

Published
2008
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27. Ellenberg-type indicator values for European vascular plant species

Author

Lubomír, Tichý, Irena, Axmanová, Jürgen, Dengler, Riccardo, Guarino, Florian, Jansen, Gabriele, Midolo, Nobis, Michael P., Koenraad, Van&nbsp, Meerbeek, Svetlana, Aćić, Attorre, Fabio, Erwin, Bergmeier, Idoia, Biurrun, Gianmaria, Bonari, Helge, Bruelheide, Juan Antonio Campos, Andraž, Čarni, Alessandro, Chiarucci, Mirjana, Ćuk, Renata, Ćušterevska, Yakiv, Didukh, Daniel, Dítě, Zuzana, Dítě, Tetiana, Dziuba, Fanelli, Giuliano, Eduardo, Fernández‐pascual, Emmanuel, Garbolino, Gavilán, Rosario G., Jean‐claude, Gégout, Ulrich, Graf, Behlül, Güler, Michal, Hájek, Hennekens, Stephan M., Ute, Jandt, Anni, Jašková, Borja, Jiménez‐alfaro, Philippe, Julve, Stephan, Kambach, Dirk Nikolaus Karger, Gerhard, Karrer, Ali, Kavgacı, Ilona, Knollová, Anna, Kuzemko, Filip, Küzmič, Flavia, Landucci, Attila, Lengyel, Jonathan, Lenoir, Corrado, Marcenò, Jesper Erenskjold Moeslund, Pavel, Novák, Aaron, Pérez‐haase, Tomáš, Peterka, Remigiusz, Pielech, Pignatti, Alessandro, Valerijus, Rašomavičius, Solvita, Rūsiņa, Arne, Saatkamp, Urban, Šilc, Željko, Škvorc, Jean‐paul, Theurillat, Thomas, Wohlgemuth, Milan, Chytrý, Tichy L., Axmanova I., Dengler J., Guarino R., Jansen F., Midolo G., Nobis M.P., VanMeerbeek K., Acic S., Attorre F., Bergmeier E., Biurrun I., Bonari G., Bruelheide H., Campos J.A., Carni A., Chiarucci A., Cuk M., Custerevska R., Didukh Y., Dite D., Dite Z., Dziuba T., Fanelli G., Fernandez-Pascual E., Garbolino E., Gavilan R.G., Gegout J.-C., Graf U., Guler B., Hajek M., Hennekens S.M., Jandt U., Jaskova A., Jimenez-Alfaro B., Julve P., Kambach S., Karger D.N., Karrer G., Kavgaci A., Knollova I., Kuzemko A., Kuzmic F., Landucci F., Lengyel A., Lenoir J., Marceno C., Moeslund J.E., Novak P., Perez-Haase A., Peterka T., Pielech R., Pignatti A., Rasomavicius V., Rusina S., Saatkamp A., Silc U., Skvorc Z., Theurillat J.-P., Wohlgemuth T., Chytry M., Tichý, Lubomír, Axmanová, Irena, Dengler, Jürgen, Guarino, Riccardo, Jansen, Florian, Midolo, Gabriele, Nobis, Michael P., Van Meerbeek, Koenraad, Aćić, Svetlana, Attorre, Fabio, Bergmeier, Erwin, Biurrun, Idoia, Bonari, Gianmaria, Bruelheide, Helge, Campos, Juan Antonio, Čarni, Andraž, Chiarucci, Alessandro, Ćuk, Mirjana, Ćušterevska, Renata, Didukh, Yakiv, Dítě, Daniel, Dítě, Zuzana, Dziuba, Tetiana, Fanelli, Giuliano, Fernández‐Pascual, Eduardo, Garbolino, Emmanuel, Gavilán, Rosario G., Gégout, Jean‐Claude, Graf, Ulrich, Güler, Behlül, Hájek, Michal, Hennekens, Stephan M., Jandt, Ute, Jašková, Anni, Jiménez‐Alfaro, Borja, Julve, Philippe, Kambach, Stephan, Karger, Dirk Nikolau, Karrer, Gerhard, Kavgacı, Ali, Knollová, Ilona, Kuzemko, Anna, Küzmič, Filip, Landucci, Flavia, Lengyel, Attila, Lenoir, Jonathan, Marcenò, Corrado, Moeslund, Jesper Erenskjold, Novák, Pavel, Pérez‐Haase, Aaron, Peterka, Tomáš, Pielech, Remigiusz, Pignatti, Alessandro, Rašomavičius, Valeriju, Rūsiņa, Solvita, Saatkamp, Arne, Šilc, Urban, Škvorc, Željko, Theurillat, Jean‐Paul, Wohlgemuth, Thoma, and Chytrý, Milan

Subjects
Vascular plant, bioindication, Ellenberg indicator values, light, moisture, nutrients, reaction, salinity, temperature, vascular plants, Bos- en Landschapsecologie, Environmental Sciences & Ecology, Plant Science, MOISTURE, RICHNESS, FORESTS, GRADIENT, ECOLOGICAL BEHAVIOR, Forest and Landscape Ecology, 577: Ökologie, Vegetatie, Ellenberg indicator value, Vegetation, Science & Technology, NORTH, Ecology, Plant Sciences, SHIFTS, Forestry, bioindication, Ellenberg indicator values, light, moisture, nutrients, reaction, salinity, temperature, vascular plants, REGIONS, 580: Pflanzen (Botanik), Settore BIO/03 - Botanica Ambientale E Applicata, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology, Life Sciences & Biomedicine, Nutrient
Abstract

This is a dataset of Ellenberg-type indicator values for European vascular plant species described in this article: Tichý L., Axmanová I., Dengler J., Guarino R., Jansen F., Midolo G., Nobis M.P., Van Meerbeek K., Aćić S., Attorre F., Bergmeier E., Biurrun I., Bonari G., Bruelheide H., Campos J.A., Čarni A., Chiarucci A., Ćuk M., Ćušterevska M., Didukh Y., Dítě D., Dítě Z., Dziuba T., Fanelli G., Fernández-Pascual E., Garbolino E., Gavilán R.G., Gégout J.-C., Graf U., Güler B., Hájek M., Hennekens S.M., Jandt U., Jašková A., Jiménez-Alfaro B., Julve P., Kambach S., Karger D.N., Karrer G., Kavgacı A., Knollová I., Kuzemko A., Küzmič F., Landucci F., Lengyel A., Lenoir J., Marcenò C., Moeslund J.E., Novák P., Pérez-Haase A., Peterka T., Pielech R., Pignatti A., Rašomavičius V., Rūsiņa S., Saatkamp A., Šilc U., Škvorc Ž., Theurillat J.-P., Wohlgemuth T. & Chytrý M. (2023) Ellenberg-type indicator values for European vascular plant species. Journal of Vegetation Science, 34, e13168. https://doi.org/10.1111/jvs.13168 The dataset contains: 1) Harmonized Ellenberg-type indicator values for light, temperature, moisture, reaction, nutrients, and salinity for European vascular plants. 2) Original indicator values from 13 datasets of Ellenberg-type indicator values: - Germany (Ellenberg & Leuschner 2010) - Austria (Karrer 1992) - Cantabrian Range (Jiménez-Alfaro et al. 2021) - Czech Republic (Chytrý et al. 2018) - European mires (Hájek et al. 2020) - France (Julve 2015) - Great Britain (Hill et al. 2000) - Greece (South Aegean) (Böhling et al. 2002) - Hungary (Borhidi 1995) - Italy (Guarino & La Rosa 2019, modified) - Saline habitats (Dítě et al. 2023) - Switzerland and the Alps (Landolt et al. 2010) - Ukraine (Didukh 2011) 3) Species nomenclature is standardized according to the Euro+Med PlantBase (http://europlusmed.org)., The final version of the paper (accepted 8th Dec 2022; published 22nd Dec 2022). Difference from version 1.0: Minor changes in newly added species values calculated from co-occurrence with other species in the EVA database. They were corrected using straight-line calibration.

Published
2022
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28. Benchmarking plant diversity of Palaearctic grasslands and other open habitats

Author

Monika Janišová, Georgios Fotiadis, Honor C. Prentice, Farshid Memariani, Ivan I. Moysiyenko, Pavel Lustyk, Zdenka Preislerová, Hristo Pedashenko, Francesco Santi, Atushi Ushimaru, Steffen Boch, Galina Savchenko, Fabrizio Buldrini, Irena Axmanová, Milan Chytrý, Jiri Dolezal, Denys Vynokurov, Marta Czarniecka-Wiera, Zdeňka Lososová, Robert K. Peet, Simon Stifter, Ricarda Pätsch, Koenraad Van Meerbeek, Alba Gutiérrez-Girón, Simona Maccherini, András Kelemen, Thomas Becker, Michal Hájek, Christian Pedersen, Stefan Widmer, Remigiusz Pielech, Vladimir Ronkin, Kai Jensen, Anna Wróbel, Cristina Chocarro, Sebastian Świerszcz, Lei Deng, Arkadiusz Nowak, Luisa Conti, Eulàlia Pladevall-Izard, Swantje Löbel, Jonathan Etzold, Jan Peters, Hans Henrik Bruun, Elisabeth M. Hüllbusch, Anna Kuzemko, Martin Magnes, Rayna Natcheva, Riccardo Guarino, Joaquín Molero Mesa, Vasco Silva, Pavel Dřevojan, Iuliia Vasheniak, Jan Lepš, Péter Török, Timo Conradi, Marcin Nobis, Aaron Pérez-Haase, Yun Wang, María Rosa Fernández Calzado, Ilaria Bonini, Massimo Terzi, Meelis Pärtel, Liqing Zhao, Csaba Tölgyesi, Frank Weiser, Philipp Kirschner, Juan Antonio Campos, Zuzana Plesková, László Demeter, George Fayvush, Asun Berastegi, Behlül Güler, Diego Liendo, Nancy Langer, Manfred Finckh, Martin Diekmann, Florian Jeltsch, Anke Jentsch, Robin J. Pakeman, Tobias Ceulemans, Javier Etayo, Orsolya Valkó, Carly J. Stevens, Kaoru Kakinuma, Michele Aleffi, Jiří Danihelka, Alicia Teresa Rosario Acosta, Balázs Teleki, Laura M. E. Sutcliffe, Solvita Rusina, Rosario G. Gavilán, Pieter De Frenne, Michele Mugnai, Arantzazu L. Luzuriaga, Marc Olivier Büchler, Lubomír Tichý, Soroor Rahmanian, Zsolt Molnár, Itziar García-Mijangos, Jürgen Dengler, Harald Pauli, Asuka Koyama, Anvar Sanaei, Cecilia Dupré, Parvaneh Ashouri, Vladimir G. Onipchenko, Ute Jandt, Zoltán Bátori, François Gillet, Alla Aleksanyan, Ariel Bergamini, Corrado Marcenò, Constantin Mardari, Nadezda Tsarevskaya, José Luis Benito Alonso, Łukasz Kozub, Ottar Michelsen, Felix May, Goffredo Filibeck, Jan Roleček, Jalil Noroozi, Karsten Wesche, Eva Šmerdová, Michael Manthey, Triin Reitalu, Ana M. Sánchez, Eszter Ruprecht, Regina Lindborg, Idoia Biurrun, Risto Virtanen, Gianpietro Giusso del Galdo, Helmut Mayrhofer, Annika K. Jägerbrand, Mansoureh Kargar, Chrisoula B. Pirini, Dariia Shyriaieva, Sabina Burrascano, Esther Baumann, Christian Dolnik, Kristina Merunková, Ching-Feng Li, Eliane S. Meier, Kuber Prasad Bhatta, Mercedes Herrera, Klaus Ecker, Mohammad Farzam, Marta Torca, Nele Ingerpuu, Philippe Jeanneret, Francesco de Bello, Alireza Naqinezhad, Tünde Farkas, Elena Belonovskaya, Josep M. Ninot, Elias Afif, Munemitsu Akasaka, Lorenzo Lazzaro, András Vojtkó, Leonardo Rosati, Jianshuang Wu, Arshad Ali, Sándor Bartha, Zuoqiang Yuan, Wenhong Ma, Patryk Czortek, Marta Carboni, Franz Essl, Hannah J. White, Carmen Van Mechelen, Brigitta Erschbamer, Marek Malicki, Vasyl Budzhak, Jutta Kapfer, Manuela Winkler, Angela Lomba, Hamid Ejtehadi, Judit Sonkoly, Ingrid Turisová, Thomas Vanneste, Laura Cancellieri, Sonja Škornik, David Zelený, Zygmunt Kącki, Alessandro Chiarucci, Salza Palpurina, Sigrid Suchrow, Kathrin Kiehl, Amir Talebi, Beata Cykowska-Marzencka, Borja Jiménez-Alfaro, Nataša Pipenbaher, Frank Yonghong Li, Wendy Fjellstad, Ivana Vitasović-Kosić, Maria Pilar Rodríguez-Rojo, Álvaro Bueno, Daniele Viciani, Juha M. Alatalo, Emelie Waldén, Sahar Ghafari, Grzegorz Swacha, Anna Mária Csergő, Lu Wen, Balázs Deák, Ioannis Tsiripidis, Luis Villar, Maria-Teresa Sebastià, Svetlana Aćić, Halime Moradi, Kiril Vassilev, Daniel García-Magro, Sebastian Wolfrum, Iva Apostolova, Marko Sabovljevic, Giovanna Potenza, Monika Staniaszek-Kik, Iwona Dembicz, Aveliina Helm, Marta Czarnocka-Cieciura, Marta Gaia Sperandii, John-Arvid Grytnes, Laboratoire Chrono-environnement - CNRS - UBFC (UMR 6249) (LCE), Centre National de la Recherche Scientifique (CNRS)-Université de Franche-Comté (UFC), Université Bourgogne Franche-Comté [COMUE] (UBFC)-Université Bourgogne Franche-Comté [COMUE] (UBFC), Biurrun I., Pielech R., Dembicz I., Gillet F., Kozub L., Marceno C., Reitalu T., Van Meerbeek K., Guarino R., Chytry M., Pakeman R.J., Preislerova Z., Axmanova I., Burrascano S., Bartha S., Boch S., Bruun H.H., Conradi T., De Frenne P., Essl F., Filibeck G., Hajek M., Jimenez-Alfaro B., Kuzemko A., Molnar Z., Partel M., Patsch R., Prentice H.C., Rolecek J., Sutcliffe L.M.E., Terzi M., Winkler M., Wu J., Acic S., Acosta A.T.R., Afif E., Akasaka M., Alatalo J.M., Aleffi M., Aleksanyan A., Ali A., Apostolova I., Ashouri P., Batori Z., Baumann E., Becker T., Belonovskaya E., Benito Alonso J.L., Berastegi A., Bergamini A., Bhatta K.P., Bonini I., Buchler M.-O., Budzhak V., Bueno A., Buldrini F., Campos J.A., Cancellieri L., Carboni M., Ceulemans T., Chiarucci A., Chocarro C., Conti L., Csergo A.M., Cykowska-Marzencka B., Czarniecka-Wiera M., Czarnocka-Cieciura M., Czortek P., Danihelka J., de Bello F., Deak B., Demeter L., Deng L., Diekmann M., Dolezal J., Dolnik C., Drevojan P., Dupre C., Ecker K., Ejtehadi H., Erschbamer B., Etayo J., Etzold J., Farkas T., Farzam M., Fayvush G., Fernandez Calzado M.R., Finckh M., Fjellstad W., Fotiadis G., Garcia-Magro D., Garcia-Mijangos I., Gavilan R.G., Germany M., Ghafari S., Giusso del Galdo G.P., Grytnes J.-A., Guler B., Gutierrez-Giron A., Helm A., Herrera M., Hullbusch E.M., Ingerpuu N., Jagerbrand A.K., Jandt U., Janisova M., Jeanneret P., Jeltsch F., Jensen K., Jentsch A., Kacki Z., Kakinuma K., Kapfer J., Kargar M., Kelemen A., Kiehl K., Kirschner P., Koyama A., Langer N., Lazzaro L., Leps J., Li C.-F., Li F.Y., Liendo D., Lindborg R., Lobel S., Lomba A., Lososova Z., Lustyk P., Luzuriaga A.L., Ma W., Maccherini S., Magnes M., Malicki M., Manthey M., Mardari C., May F., Mayrhofer H., Meier E.S., Memariani F., Merunkova K., Michelsen O., Molero Mesa J., Moradi H., Moysiyenko I., Mugnai M., Naqinezhad A., Natcheva R., Ninot J.M., Nobis M., Noroozi J., Nowak A., Onipchenko V., Palpurina S., Pauli H., Pedashenko H., Pedersen C., Peet R.K., Perez-Haase A., Peters J., Pipenbaher N., Pirini C., Pladevall-Izard E., Pleskova Z., Potenza G., Rahmanian S., Rodriguez-Rojo M.P., Ronkin V., Rosati L., Ruprecht E., Rusina S., Sabovljevic M., Sanaei A., Sanchez A.M., Santi F., Savchenko G., Sebastia M.T., Shyriaieva D., Silva V., Skornik S., Smerdova E., Sonkoly J., Sperandii M.G., Staniaszek-Kik M., Stevens C., Stifter S., Suchrow S., Swacha G., Swierszcz S., Talebi A., Teleki B., Tichy L., Tolgyesi C., Torca M., Torok P., Tsarevskaya N., Tsiripidis I., Turisova I., Ushimaru A., Valko O., Van Mechelen C., Vanneste T., Vasheniak I., Vassilev K., Viciani D., Villar L., Virtanen R., Vitasovic-Kosic I., Vojtko A., Vynokurov D., Walden E., Wang Y., Weiser F., Wen L., Wesche K., White H., Widmer S., Wolfrum S., Wrobel A., Yuan Z., Zeleny D., Zhao L., Dengler J., Biurrun, Idoia, Pielech, Remigiusz, Dembicz, Iwona, Gillet, Françoi, Kozub, Łukasz, Marcenò, Corrado, Reitalu, Triin, Van Meerbeek, Koenraad, Guarino, Riccardo, Chytrý, Milan, Pakeman, Robin J., Preislerová, Zdenka, Axmanová, Irena, Burrascano, Sabina, Bartha, Sándor, Boch, Steffen, Bruun, Hans Henrik, Conradi, Timo, De Frenne, Pieter, Essl, Franz, Filibeck, Goffredo, Hájek, Michal, Jiménez‐Alfaro, Borja, Kuzemko, Anna, Molnár, Zsolt, Pärtel, Meeli, Pätsch, Ricarda, Prentice, Honor C., Roleček, Jan, Sutcliffe, Laura M.E., Terzi, Massimo, Winkler, Manuela, Wu, Jianshuang, Aćić, Svetlana, Acosta, Alicia T.R., Afif, Elia, Akasaka, Munemitsu, Alatalo, Juha M., Aleffi, Michele, Aleksanyan, Alla, Ali, Arshad, Apostolova, Iva, Ashouri, Parvaneh, Bátori, Zoltán, Baumann, Esther, Becker, Thoma, Belonovskaya, Elena, Benito Alonso, José Lui, Berastegi, Asun, Bergamini, Ariel, Bhatta, Kuber Prasad, Bonini, Ilaria, Büchler, Marc‐Olivier, Budzhak, Vasyl, Bueno, Álvaro, Buldrini, Fabrizio, Campos, Juan Antonio, Cancellieri, Laura, Carboni, Marta, Ceulemans, Tobia, Chiarucci, Alessandro, Chocarro, Cristina, Conti, Luisa, Csergő, Anna Mária, Cykowska‐Marzencka, Beata, Czarniecka‐Wiera, Marta, Czarnocka‐Cieciura, Marta, Czortek, Patryk, Danihelka, Jiří, de Bello, Francesco, Deák, Baláz, Demeter, László, Deng, Lei, Diekmann, Martin, Dolezal, Jiri, Dolnik, Christian, Dřevojan, Pavel, Dupré, Cecilia, Ecker, Klau, Ejtehadi, Hamid, Erschbamer, Brigitta, Etayo, Javier, Etzold, Jonathan, Farkas, Tünde, Farzam, Mohammad, Fayvush, George, Fernández Calzado, María Rosa, Finckh, Manfred, Fjellstad, Wendy, Fotiadis, Georgio, García‐Magro, Daniel, García‐Mijangos, Itziar, Gavilán, Rosario G., Germany, Marku, Ghafari, Sahar, Giusso del Galdo, Gian Pietro, Grytnes, John‐Arvid, Güler, Behlül, Gutiérrez‐Girón, Alba, Helm, Aveliina, Herrera, Mercede, Hüllbusch, Elisabeth M., Ingerpuu, Nele, Jägerbrand, Annika K., Jandt, Ute, Janišová, Monika, Jeanneret, Philippe, Jeltsch, Florian, Jensen, Kai, Jentsch, Anke, Kącki, Zygmunt, Kakinuma, Kaoru, Kapfer, Jutta, Kargar, Mansoureh, Kelemen, Andrá, Kiehl, Kathrin, Kirschner, Philipp, Koyama, Asuka, Langer, Nancy, Lazzaro, Lorenzo, Lepš, Jan, Li, Ching‐Feng, Li, Frank Yonghong, Liendo, Diego, Lindborg, Regina, Löbel, Swantje, Lomba, Angela, Lososová, Zdeňka, Lustyk, Pavel, Luzuriaga, Arantzazu L., Ma, Wenhong, Maccherini, Simona, Magnes, Martin, Malicki, Marek, Manthey, Michael, Mardari, Constantin, May, Felix, Mayrhofer, Helmut, Meier, Eliane Seraina, Memariani, Farshid, Merunková, Kristina, Michelsen, Ottar, Molero Mesa, Joaquín, Moradi, Halime, Moysiyenko, Ivan, Mugnai, Michele, Naqinezhad, Alireza, Natcheva, Rayna, Ninot, Josep M., Nobis, Marcin, Noroozi, Jalil, Nowak, Arkadiusz, Onipchenko, Vladimir, Palpurina, Salza, Pauli, Harald, Pedashenko, Hristo, Pedersen, Christian, Peet, Robert K., Pérez‐Haase, Aaron, Peters, Jan, Pipenbaher, Nataša, Pirini, Chrisoula, Pladevall‐Izard, Eulàlia, Plesková, Zuzana, Potenza, Giovanna, Rahmanian, Soroor, Rodríguez‐Rojo, Maria Pilar, Ronkin, Vladimir, Rosati, Leonardo, Ruprecht, Eszter, Rusina, Solvita, Sabovljević, Marko, Sanaei, Anvar, Sánchez, Ana M., Santi, Francesco, Savchenko, Galina, Sebastià, Maria Teresa, Shyriaieva, Dariia, Silva, Vasco, Škornik, Sonja, Šmerdová, Eva, Sonkoly, Judit, Sperandii, Marta Gaia, Staniaszek‐Kik, Monika, Stevens, Carly, Stifter, Simon, Suchrow, Sigrid, Swacha, Grzegorz, Świerszcz, Sebastian, Talebi, Amir, Teleki, Baláz, Tichý, Lubomír, Tölgyesi, Csaba, Torca, Marta, Török, Péter, Tsarevskaya, Nadezda, Tsiripidis, Ioanni, Turisova, Ingrid, Ushimaru, Atushi, Valkó, Orsolya, Van Mechelen, Carmen, Vanneste, Thoma, Vasheniak, Iuliia, Vassilev, Kiril, Viciani, Daniele, Villar, Lui, Virtanen, Risto, Vitasović‐Kosić, Ivana, Vojtkó, Andrá, Vynokurov, Deny, Waldén, Emelie, Wang, Yun, Weiser, Frank, Wen, Lu, Wesche, Karsten, White, Hannah, Widmer, Stefan, Wolfrum, Sebastian, Wróbel, Anna, Yuan, Zuoqiang, Zelený, David, Zhao, Liqing, Dengler, Jürgen, Bavarian Research Foundation, International Association for Vegetation Science, Eusko Jaurlaritza, Czech Science Foundation, Estonian Research Council, Scottish Government's Rural and Environment Science and Analytical Services, Ministero dell'Istruzione, dell'Università e della Ricerca, Agencia Estatal de Investigación (España), Science and Technology Center in Ukraine, Swedish Research Council for Environment, Agricultural Sciences and Spatial Planning, Swedish Institute, Foundation for Introducing Talent of Nanjing University of Information Science and Technology, Hebei Province, Academy of Sciences of the Czech Republic, Hungarian Academy of Sciences, Tyrolean Science Fund, Austrian Academy of Sciences, University of Innsbruck, Ministerio de Economía y Competitividad (España), Comunidad de Madrid, National Geographic Society, Slovak Academy of Sciences, Fundação para a Ciência e a Tecnologia (Portugal), National Science Centre (Poland), Russian Science Foundation, University of Latvia Foundation, Slovenian Research Agency, Biurrun, I, Pielech, R, Dembicz, I, Gillet, F, Kozub, L, Marceno, C, Reitalu, T, Van Meerbeek, K, Guarino, R, Chytry, M, Pakeman, RJ, Preislerova, Z, Axmanova, I, Burrascano, S, Bartha, S, Boch, S, Bruun, HH, Conradi, T, De Frenne, P, Essl, F, Filibeck, G, Hajek, M, Jimenez-Alfaro, B, Kuzemko, A, MOLNAR, Zsolt, Partel, M, Patsch, R, Prentice, HC, Rolecek, J, Sutcliffe, LME, Terzi, M, Winkler, M, Wu, JS, Acic, S, Acosta, ATR, Afif, E, Akasaka, M, Alatalo, JM, Aleffi, M, Aleksanyan, A, Ali, A, Apostolova, I, Ashouri, P, Batori, Z, Baumann, E, BECKER, T, Belonovskaya, E, Alonso, JLB, Berastegi, A, Bergamini, A, Bhatta, KP, Bonini, I, Buchler, MO, Budzhak, V, Bueno, A, Buldrini, F, Campos, JA, Cancellieri, L, Carboni, M, Ceulemans, T, Chiarucci, A, Chocarro, C, Conti, L, Csergo, AM, Cykowska-Marzencka, B, Czarniecka-Wiera, M, Czarnocka-Cieciura, M, Czortek, P, Danihelka, J, Bello, F, Deak, B, Demeter, L, Deng, L, Diekmann, M, Dolezal, J, Dolnik, C, Drevojan, P, Dupre, C, Ecker, K, Ejtehadi, H, Erschbamer, B, Etayo, J, Etzold, J, Farkas, T, Farzam, M, Fayvush, G, Calzado, MRF, Finckh, M, Fjellstad, W, Fotiadis, G, Garcia-Magro, D, Garcia-Mijangos, I, Gavilan, RG, Germany, M, Ghafari, S, del Galdo, GPG, Grytnes, JA, Guler, B, Gutierrez-Giron, A, Helm, A, Herrera, M, Hullbusch, EM, Ingerpuu, N, Jagerbrand, AK, Jandt, U, Janisova, M, Jeanneret, P, Jeltsch, F, Jensen, K, Jentsch, A, Kacki, Z, Kakinuma, K, Kapfer, J, Kargar, M, Kelemen, A, Kiehl, K, Kirschner, P, Koyama, A, Langer, N, Lazzaro, L, Leps, J, Li, CF, Li, FY, Liendo, D, Lindborg, R, Lobel, S, Lomba, A, Lososova, Z, Lustyk, P, Luzuriaga, AL, Ma, WH, Maccherini, S, Magnes, M, Malicki, M, Manthey, M, Mardari, C, May, F, Mayrhofer, H, Meier, ES, Memariani, F, Merunkova, K, Michelsen, O, Mesa, JM, Moradi, H, Moysiyenko, I, Mugnai, M, Naqinezhad, A, Natcheva, R, Ninot, JM, Nobis, M, Noroozi, J, Nowak, A, Onipchenko, V, Palpurina, S, Pauli, H, Pedashenko, H, Pedersen, C, Peet, RK, Perez-Haase, A, Peters, J, Pipenbaher, N, Pirini, C, Pladevall-Izard, E, Pleskova, Z, Potenza, G, Rahmanian, S, Rodriguez-Rojo, MP, Ronkin, V, Rosati, L, Ruprecht, E, Rusina, S, Sabovljevic, M, Sanaei, A, Sanchez, AM, Santi, F, Savchenko, G, Sebastia, MT, Shyriaieva, D, Silva, V, Skornik, S, Smerdova, E, Sonkoly, J, Sperandii, MG, Staniaszek-Kik, M, Stevens, C, Stifter, S, Suchrow, S, Swacha, G, Swierszcz, S, Talebi, A, Teleki, B, Tichy, L, Tolgyesi, C, Torca, M, Torok, P, Tsarevskaya, N, Tsiripidis, I, Turisova, I, Ushimaru, A, Valko, O, VAN MECHELEN, Carmen, Vanneste, T, Vasheniak, I, Vassilev, K, Viciani, D, Villar, L, Virtanen, R, Vitasovic-Kosic, I, Vojtko, A, Vynokurov, D, Walden, E, Wang, Y., Weiser, F, Wen, L, Wesche, K, White, H, Widmer, S, Wolfrum, S, Wrobel, A, Yuan, ZQ, Zeleny, D, Zhao, LQ, Dengler, J., Jiménez‐alfaro, Borja, Sutcliffe, Laura M. E., Acosta, Alicia, Büchler, Marc‐olivier, Cykowska‐marzencka, Beata, Czarniecka‐wiera, Marta, Czarnocka‐cieciura, Marta, Bello, Francesco, García‐magro, Daniel, García‐mijangos, Itziar, Grytnes, John‐arvid, Gutiérrez‐girón, Alba, Li, Ching‐feng, Pérez‐haase, Aaron, Pladevall‐izard, Eulàlia, Rodríguez‐rojo, Maria Pilar, Staniaszek‐kik, Monika, Turisová, Ingrid, and Vitasović‐kosić, Ivana

Subjects
Vascular plant, SURROGATE, 333.7: Landflächen, Naturerholungsgebiete, Biome, Lichen, open habitat, Plant Science, DATABASES, Benchmark, Grassland, Scale dependence, benchmark, RICHNESS HOTSPOTS, Vegetation type, Taxonomic rank, SCALE, Macroecology, ComputingMilieux_MISCELLANEOUS, 2. Zero hunger, bryophyte, GLOBAL PATTERNS, geography.geographical_feature_category, Ecology, Open habitat, vascular plant, Forestry, ichen, Vegetation, Vegetation plot, Palaearctic, 580: Pflanzen (Botanik), Geography, Habitat, scale dependence, fine-grain biodiversity, grassland, GrassPlot Diversity Explorer, lichen, species–area relationship, vegetation plot, Life Sciences & Biomedicine, CONSERVATION, Environmental Sciences & Ecology, Fine-grain biodiversity, benchmark, bryophyte, fine-grain biodiversity, grassland, GrassPlot Diversity Explorer, lichen, open habitat, Palaearctic, scale dependence, species–area relationship, vascular plant, vegetation plot, species-area relationship, benchmark, bryophyte, fine-grain biodiversity, grassland, GrassPlot Diversity Explorer, lichen, open habitat, Palaearctic, scale dependence, species-area relationship, vascular plant, vegetation plot, Species–area relationship, Science & Technology, Plant Sciences, Biology and Life Sciences, 15. Life on land, plant diversity, 13. Climate action, Bryophyte, SPECIES-AREA RELATIONSHIPS, VASCULAR PLANTS, BIODIVERSITY, Species richness, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, BRYOPHYTES
Abstract

© 2021 The Authors., Aims: Understanding fine-grain diversity patterns across large spatial extents is fundamental for macroecological research and biodiversity conservation. Using the GrassPlot database, we provide benchmarks of fine-grain richness values of Palaearctic open habitats for vascular plants, bryophytes, lichens and complete vegetation (i.e., the sum of the former three groups). Location: Palaearctic biogeographic realm. Methods: We used 126,524 plots of eight standard grain sizes from the GrassPlot database: 0.0001, 0.001, 0.01, 0.1, 1, 10, 100 and 1,000 m and calculated the mean richness and standard deviations, as well as maximum, minimum, median, and first and third quartiles for each combination of grain size, taxonomic group, biome, region, vegetation type and phytosociological class. Results: Patterns of plant diversity in vegetation types and biomes differ across grain sizes and taxonomic groups. Overall, secondary (mostly semi-natural) grasslands and natural grasslands are the richest vegetation type. The open-access file ”GrassPlot Diversity Benchmarks” and the web tool “GrassPlot Diversity Explorer” are now available online (https://edgg.org/databases/GrasslandDiversityExplorer) and provide more insights into species richness patterns in the Palaearctic open habitats. Conclusions: The GrassPlot Diversity Benchmarks provide high-quality data on species richness in open habitat types across the Palaearctic. These benchmark data can be used in vegetation ecology, macroecology, biodiversity conservation and data quality checking. While the amount of data in the underlying GrassPlot database and their spatial coverage are smaller than in other extensive vegetation-plot databases, species recordings in GrassPlot are on average more complete, making it a valuable complementary data source in macroecology., GrassPlot development has been supported by the Bavarian Research Alliance (BayIntAn_UBT_2017_58), the Eurasian Dry Grassland Group (EDGG) and the International Association for Vegetation Science (IAVS); IB, CorM, JAC, IGM, DGM, MHe, DL and MTo were supported by the Basque Government (IT936‐16); CorM, IAx, MCh, JDa, PD, MHá, ZL, ZPr, EŠ and LT were supported by the Czech Science Foundation (19‐28491X); TR was supported by the Estonian Research Council (PUT1173); RJP was funded by the Strategic Research Programme of the Scottish Government’s Rural and Environmental Science and Analytical Services Division”; SBa was supported by the GINOP‐2.3.2‐15‐2016‐00019 project; GFi was partially supported by the MIUR initiative “Department of excellence” (Law 232/2016)"; BJA was funded by the Spanish Research Agency (grant AEI/ 10.13039/501100011033); AK, VB, IM, DS, IV and DV were supported by the National Research Foundation of Ukraine (2020.01/0140); MP and AH were supported by the Estonian Research Council (PRG874, PRG609), and the European Regional Development Fund (Centre of Excellence EcolChange); Data collection of HCP was funded by FORMAS (Swedish Research Council for Environment, Agricultural Science and Spatial Planning) and The Swedish Institute; JR was supported by the Czech Science Foundation (grant No. 20‐09895S) and the long‐term developmental project of the Czech Academy of Sciences (RVO 67985939); ATRA was funded by the Grant of Excellence Departments, MIUR‐Italy (ARTICOLO 1, COMMI 314 – 337 LEGGE 232/2016); JMA was supported by Carl Tryggers stiftelse för vetenskaplig forskning and Qatar Petroleum; AAli was supported by the Jiangsu Science and Technology Special Project (Grant No. BX2019084), and Metasequoia Faculty Research Startup Funding at Nanjing Forestry University (Grant No. 163010230), and he is currently supported by Hebei University through Faculty Research Startup Funding Program; ZB was supported by the NKFI K 124796 grant; The GLORIA‐ Aragón project of JLBA was funded by the Dirección General de Cambio Climático del Gobierno de Aragón (Spain); MCs and LDem were supported by DG Environment through the European Forum on Nature Conservation and Pastoralism and Barbara Knowles Fund, in collaboration with Pogány‐havas Association, Romania; JDa was partially supported by long‐term research development project no. RVO 67985939 of the Czech Academy of Sciences; BD and OV were supported by the NKFI KH 126476, NKFI KH 130338, NKFI FK 124404 and NKFI FK 135329 grants; BD, OV and AKe were supported by the Bolyai János Scholarship of the Hungarian Academy of Sciences; BE was funded by the Environmental Department of the Tyrolean Federal State Government, the MAB Programme of the Austrian Academy of Science, the Mountain Agriculture Research Unit and the Alpine Research Centre Obergurgl of Innsbruck University. The GLORIA projects of BE were funded by the EU project no. EVK2‐CT‐2000‐00056, the Earth System Sciences Program of the Austrian Academy of Sciences (project MEDIALPS), the Amt für Naturparke, Autonome Provinz Bozen‐Südtirol, the Südtiroler Wissenschaftsfonds and the Tiroler Wissenschaftsfonds; RGG was supported by the Spanish Ministry of Research to sample GLORIA sites in central Spain (CGL 2008‐00901/BOS) and present works by the Autonomous Region of Madrid (REMEDINAL TE‐CM, S2018/EMT‐4338); MJ was supporteLatviaed by Latvia Grant No. 194051; NP and SŠ were partly supported by the Slovenian Research Agency, core fundings P1‐0403 and J7‐1822.

Published
2021

29. Rarefaction of beta diversity

Author

Alessandro Chiarucci, Alicia Teresa Rosario Acosta, Marta Carboni, Duccio Rocchini, Sandrine Pavoine, Carlo Ricotta, Giovanni Bacaro, Dpt of Environmental Biology [Rome], Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Università degli Studi Roma Tre, University of Trieste, University of Toronto [Scarborough, Canada], University of Bologna, University of Trento [Trento], Fondazione Edmund Mach - Edmund Mach Foundation [Italie] (FEM), Czech University of Life Sciences Prague (CZU), Muséum national d'Histoire naturelle (MNHN), Ricotta, C., Acosta, A. T. R., Bacaro, G., Carboni, M., Chiarucci, Alessandro, Rocchini, D., Pavoine, S., Ricotta, Carlo, Acosta, Alicia T. R., Bacaro, Giovanni, Carboni, Marta, Rocchini, Duccio, and Pavoine, Sandrine

Subjects
0106 biological sciences, Community turnover, Gamma diversity, Species discovery curve, Beta diversity, General Decision Sciences, 010501 environmental sciences, 010603 evolutionary biology, 01 natural sciences, spatial autocorrelation, remote sensing, Statistics, Number of specie, 14. Life underwater, species richness, Spatial analysis, Ecology, Evolution, Behavior and Systematics, biodiversity, 0105 earth and related environmental sciences, Mathematics, Ecology, Sampling (statistics), Vegetation, effective number of plots, 15. Life on land, Directional and non-directional accumulation curve, community turnover, directional and non-directional accumulation curves, Directional and non-directional accumulation curves, Effective number of plots, Number of species, Spatial autocorrelation, Rarefaction (ecology), Species richness, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, human activities, Effective number of plot
Abstract

International audience; Beta diversity has long been used to summarize the amount of variation in species composition among a set of N sampling units. However, while classical beta diversity provides an estimate of multiple-site dissimilarity among all sampling units, it is not informative on the changes of multiple-site dissimilarity as a function of sampling effort. For gamma diversity, this pattern is usually represented as a species accumulation curve, which is the graph of the number of observed species when the number of plots varies from 1 to N. Here, we will show that species accumulation curves may also be used to summarize directional and non-directional beta diversity as a function of sampling effort. The behavior of the proposed measures of beta diversity is illustrated with one worked example on plant species in Mediterranean coastal vegetation. We believe this approach to the measurement of beta diversity provides a relevant contribution to summarize multiple-site dissimilarity as the result of a species turnover process, rather than as a static indicator. For directional species accumulation curves, the method, for which we provide a custom R function, further allows summarizing the spatial autocorrelation in species composition among plots along an a-priori defined spatial, temporal or environmental gradient.

Published
2019

30. Mapping plant community ecology

Author

Meelis Pärtel, Milan Chytrý, Valério D. Pillar, Alessandro Chiarucci, Pärtel, Meeli, Chiarucci, Alessandro, Chytrý, Milan, and Pillar, Valério D.

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Ecology, Applied ecology, Ecology (disciplines), Plant community, Plant Science, Vegetation, 15. Life on land, Biology, 010603 evolutionary biology, 01 natural sciences, Plant science, Terrestrial ecosystem, 0105 earth and related environmental sciences
Abstract

Plant communities form the structural and functional basis for nearly all terrestrial ecosystems. Good knowledge about plant communities is therefore necessary to understand and protect life on our planet. Journal of Vegetation Science publishes papers on all aspects of plant community ecology with an emphasis on articles that develop new concepts and methods, test theory, or identify general patterns. This article is protected by copyright. All rights reserved.

Published
2016

31. Are available vegetation data suitable for assessing plant diversity? A study case in the Foreste Casentinesi National Park (Italy)

Author

Chiara Lelli, Juri Nascimbene, Alessandro Chiarucci, Lelli, Chiara, Nascimbene, Juri, and Chiarucci, Alessandro

Subjects
0106 biological sciences, Range (biology), Distribution (economics), 010603 evolutionary biology, 01 natural sciences, Vegetation resurvey, Forest, General Environmental Science, Plant diversity assessment, National park, business.industry, Phytosociological relevé, Species diversity, Vegetation, Geography, Habitat, Agricultural and Biological Sciences (all), General Earth and Planetary Sciences, Rarefaction (ecology), General Agricultural and Biological Sciences, Scale (map), business, Cartography, Earth and Planetary Sciences (all), 010606 plant biology & botany
Abstract

This paper aimed to analyze potentials and shortcomings of existing vegetation data collected in an Italian National Park (Foreste Casentinesi NP) to: (1) assess coarse scale patterns of species diversity, and (2) set up a habitat monitoring system. We generated a specifically designed georeferenced dataset by assembling all available forest vegetation data, and then we analyzed spatial and temporal patterns of data by sample-based accumulation and rarefaction curves. The analyses were performed on data gathered from the year 1934 to 2007. This broad temporal range may provide valuable information about processes occurring over a longer period than the majority of the published resurvey studies. Our study revealed an uneven distribution of the records both in time and space, corroborating the view that this type of data is inappropriate to analyze trends of plant diversity at coarse scale. However, especially the oldest records of the dataset represent a valuable source of information about long-term plant diversity changes, if used in resurvey studies designed with proper techniques. Detecting the directions of vegetation, or habitat, dynamics is crucial for addressing effective conservation actions.

Published
2018

32. GrassPlot – a database of multi-scale plant diversity in Palaearctic grasslands

Author

Jürgen, Dengler, Viktoria, Wagner, Iwona, Dembicz, Itziar, García-Mijangos, Alireza, Naqinezhad, Steffen, Boch, Alessandro, Chiarucci, Timo, Conradi, Goffredo, Filibeck, Riccardo, Guarino, Monika, Janišová, Steinbauer, Manuel J., Svetlana, Aćić, Acosta, Alicia T. R., Munemitsu, Akasaka, Marc-Andre, Allers, Iva, Apostolova, Irena, Axmanová, Branko, Bakan, Alina, Baranova, Manfred, Bardy-Durchhalter, Sándor, Bartha, Esther, Baumann, Thomas, Becker, Ute, Becker, Elena, Belonovskaya, Karin, Bengtsson, José Luis Benito Alonso, Asun, Berastegi, Ariel, Bergamini, Ilaria, Bonini, Hans Henrik Bruun, Vasyl, Budzhak, Alvaro, Bueno, Juan Antonio Campos, Laura, Cancellieri, Marta, Carboni, Cristina, Chocarro, Luisa, Conti, Marta, Czarniecka-Wiera, Pieter De Frenne, Balázs, Deák, Didukh, Yakiv P., Martin, Diekmann, Christian, Dolnik, Cecilia, Dupré, Klaus, Ecker, Nikolai, Ermakov, Brigitta, Erschbamer, Adrián, Escudero, Javier, Etayo, Zuzana, Fajmonová, Felde, Vivian A., Maria Rosa Fernández Calzado, Manfred, Finckh, Georgios, Fotiadis, Mariano, Fracchiolla, Anna, Ganeva, Daniel, García-Magro, Gavilán, Rosario G., Markus, Germany, Itamar, Giladi, François, Gillet, GIUSSO DEL GALDO, Gianpietro, González, Jose M., John-Arvid, Grytnes, Michal, Hájek, Petra, Hájková, Aveliina, Helm, Mercedes, Herrera, Eva, Hettenbergerová, Carsten, Hobohm, Hüllbusch, Elisabeth M., Nele, Ingerpuu, Ute, Jandt, Florian, Jeltsch, Kai, Jensen, Anke, Jentsch, Michael, Jeschke, Borja, Jiménez-Alfaro, Zygmunt, Kącki, Kaoru, Kakinuma, Jutta, Kapfer, Ali, Kavgacı, András, Kelemen, Kathrin, Kiehl, Asuka, Koyama, Koyanagi, Tomoyo F., Łukasz, Kozub, Anna, Kuzemko, Magni Olsen Kyrkjeeide, Sara, Landi, Nancy, Langer, Lorenzo, Lastrucci, Lorenzo, Lazzaro, Chiara, Lelli, Jan, Lepš, Swantje, Löbel, Luzuriaga, Arantzazu L., Simona, Maccherini, Martin, Magnes, Marek, Malicki, Marceno', Corrado, Constantin, Mardari, Leslie, Mauchamp, Felix, May, Ottar, Michelsen, Joaquín Molero Mesa, Zsolt, Molnár, Moysiyenko, Ivan Y., Nakaga, Yuko K., Rayna, Natcheva, Jalil, Noroozi, Pakeman, Robin J., Salza, Palpurina, Meelis, Pärtel, Ricarda, Pätsch, Harald, Pauli, Hristo, Pedashenko, Peet, Robert K., Remigiusz, Pielech, Nataša, Pipenbaher, Chrisoula, Pirini, Zuzana, Plesková, Polyakova, Mariya A., Prentice, Honor C., Jennifer, Reinecke, Triin, Reitalu, Maria Pilar Rodríguez-Rojo, Jan, Roleček, Vladimir, Ronkin, Leonardo, Rosati, Ejvind, Rosén, Eszter, Ruprecht, Solvita, Rusina, Marko, Sabovljević, Ana María Sánchez, Galina, Savchenko, Oliver, Schuhmacher, Sonja, Škornik, Marta Gaia Sperandii, Monika, Staniaszek-Kik, Zora, Stevanović-Dajić, Marin, Stock, Sigrid, Suchrow, Sutcliffe, Laura M. E., Grzegorz, Swacha, Martin, Sykes, Anna, Szabó, Amir, Talebi, Cătălin, Tănase, Massimo, Terzi, Csaba, Tölgyesi, Marta, Torca, Péter, Török, Béla, Tóthmérész, Nadezda, Tsarevskaya, Ioannis, Tsiripidis, Rossen, Tzonev, Atushi, Ushimaru, Orsolya, Valkó, Eddy van der Maarel, Thomas, Vanneste, Iuliia, Vashenyak, Kiril, Vassilev, Daniele, Viciani, Luis, Villar, Risto, Virtanen, Ivana Vitasović Kosić, Yun, Wang, Frank, Weiser, Julia, Went, Karsten, Wesche, Hannah, White, Manuela, Winkler, Zaniewski, Piotr T., Hui, Zhang, Yaron, Ziv, Sergey Znamenskiy &amp, Idoia Biurrun, Dengler, Jürgen, Wagner, Viktoria, Dembicz, Iwona, García-Mijangos, Itziar, Naqinezhad, Alireza, Boch, Steffen, Chiarucci, Alessandro, Conradi, Timo, Filibeck, Goffredo, Guarino, Riccardo, Janišová, Monika, Steinbauer, Manuel J., Acic, Svetlana, Acosta, Alicia T.R., Akasaka, Munemitsu, Allers, Marc-Andre, Apostolova, Iva, Axmanová, Irena, Bakan, Branko, Baranova, Alina, Bardy-Durchhalter, Manfred, Bartha, Sándor, Baumann, Esther, Becker, Thoma, Becker, Ute, Belonovskaya, Elena, Bengtsson, Karin, Alonso, José Luis Benito, Berastegi, Asun, Bergamini, Ariel, Bonini, Ilaria, Bruun, Hans Henrik, Budzhak, Vasyl, Bueno, Alvaro, Campos, Juan Antonio, Cancellieri, Laura, Carboni, Marta, Chocarro, Cristina, Conti, Luisa, Czarniecka-Wiera, Marta, De Frenne, Pieter, Deák, Baláz, Didukh, Yakiv P., Diekmann, Martin, Dolnik, Christian, Dupré, Cecilia, Ecker, Klau, Ermakov, Nikolai, Erschbamer, Brigitta, Escudero, Adrián, Etayo, Javier, Fajmonová, Zuzana, Felde, Vivian A., Calzado, Maria Rosa Fernández, Finckh, Manfred, Fotiadis, Georgio, Fracchiolla, Mariano, Ganeva, Anna, García-Magro, Daniel, Gavilán, Rosario G., Germany, Marku, Giladi, Itamar, Gillet, Françoi, del Galdo, Gian Pietro Giusso, González, Jose M., Grytnes, John-Arvid, Hájek, Michal, Hájková, Petra, Helm, Aveliina, Herrera, Mercede, Hettenbergerová, Eva, Hobohm, Carsten, Hüllbusch, Elisabeth M., Ingerpuu, Nele, Jandt, Ute, Jeltsch, Florian, Jensen, Kai, Jentsch, Anke, Jeschke, Michael, Jiménez-Alfaro, Borja, Kacki, Zygmunt, Kakinuma, Kaoru, Kapfer, Jutta, Kavgaci, Ali, Kelemen, Andrá, Kiehl, Kathrin, Koyama, Asuka, Koyanagi, Tomoyo F., Kozub, Lukasz, Kuzemko, Anna, Kyrkjeeide, Magni Olsen, Landi, Sara, Langer, Nancy, Lastrucci, Lorenzo, Lazzaro, Lorenzo, Lelli, Chiara, Lepš, Jan, Löbel, Swantje, Luzuriaga, Arantzazu L., Maccherini, Simona, Magnes, Martin, Malicki, Marek, Marcenò, Corrado, Mardari, Constantin, Mauchamp, Leslie, May, Felix, Michelsen, Ottar, Mesa, Joaquín Molero, Molnár, Zsolt, Moysiyenko, Ivan Y., Nakaga, Yuko K., Natcheva, Rayna, Noroozi, Jalil, Pakeman, Robin J., Palpurina, Salza, Pärtel, Meeli, Pätsch, Ricarda, Pauli, Harald, Pedashenko, Hristo, Peet, Robert K., Pielech, Remigiusz, Pipenbaher, Nataša, Pirini, Chrisoula, Plesková, Zuzana, Polyakova, Mariya A., Prentice, Honor C., Reinecke, Jennifer, Reitalu, Triin, Rodríguez-Rojo, Maria Pilar, Rolecek, Jan, Ronkin, Vladimir, Rosati, Leonardo, Rosén, Ejvind, Ruprecht, Eszter, Rusina, Solvita, Sabovljevic, Marko, Sánchez, Ana María, Savchenko, Galina, Schuhmacher, Oliver, Škornik, Sonja, Sperandii, Marta Gaia, Staniaszek-Kik, Monika, Stevanovic-Dajic, Zora, Stock, Marin, Suchrow, Sigrid, Sutcliffe, Laura M.E., Swacha, Grzegorz, Sykes, Martin, Szabó, Anna, Talebi, Amir, Tanase, Catalin, Terzi, Massimo, Tölgyesi, Csaba, Torca, Marta, Török, Péter, Tóthmérész, Béla, Tsarevskaya, Nadezda, Tsiripidis, Ioanni, Tzonev, Rossen, Ushimaru, Atushi, Valkó, Orsolya, van der Maarel, Eddy, Vanneste, Thoma, Vashenyak, Iuliia, Vassilev, Kiril, Viciani, Daniele, Villar, Lui, Virtanen, Risto, Kosic, Ivana Vitasovic, Wang, Yun, Weiser, Frank, Went, Julia, Wesche, Karsten, White, Hannah, Winkler, Manuela, Zaniewski, Piotr T., Zhang, Hui, Ziv, Yaron, Znamenskiy, Sergey, Biurrun, Idoia, Aćić, Svetlana, Acosta, Alicia T. R., Luis Benito Alonso, José, Henrik Bruun, Han, Antonio Campos, Juan, Rosa Fernández Calzado, Maria, Pietro Giusso del Galdo, Gian, Kącki, Zygmunt, Kavgacı, Ali, Kozub, Łukasz, Olsen Kyrkjeeide, Magni, Molero Mesa, Joaquín, Pilar Rodríguez-Rojo, Maria, Roleček, Jan, Sabovljević, Marko, María Sánchez, Ana, Sperandii, MARTA GAIA, Stevanović-Dajić, Zora, Sutcliffe, Laura M. E., Tănase, Cătălin, Vitasović Kosić, Ivana, Znamenskiy &amp, Sergey, Goffredo, Filibeck, and Benito Alonso, José Lui

Subjects
0106 biological sciences, Biodiversity, Plant Science, computer.software_genre, 01 natural sciences, Grassland, SAMPLING-DESIGN, RICHNESS, Ecoinformatics, ddc:550, biodiversity, European Vegetation Archive (EVA), Eurasian Dry Grassland Group (EDGG), grassland vegetation, GrassPlot, macroecology, multi-taxon, nested plot, scale-dependence, species-area relationship (SAR), sPlot, vegetation-plot database, Macroecology, 2. Zero hunger, SCALE DEPENDENCE, geography.geographical_feature_category, Database, Vegetation, Geography, Institut für Geowissenschaften, EUROPE, nested plot, scale-dependence, 010603 evolutionary biology, 577: Ökologie, METAANALYSIS, ENVIRONMENT, Data collection, grass- land vegetation, DRY GRASSLANDS, 15. Life on land, biodiversity • European Vegetation Archive (EVA) • Eurasian Dry Grassland Group (EDGG) • grassland vegetation • GrassPlot • macroecology • multi-taxon • nested plot • scale-dependence • species-area relationship (SAR) • sPlot • vegetation-plot database, Metadata, PATTERNS, SPECIES-AREA RELATIONSHIPS, Nested plot, scale-dependence, VEGETATION, Species richness, computer, 010606 plant biology & botany
Abstract

GrassPlot is a collaborative vegetation-plot database organised by the Eurasian Dry Grassland Group (EDGG) and listed in the Global Index of Vegetation-Plot Databases (GIVD ID EU-00-003). GrassPlot collects plot records (relevés) from grasslands and other open habitats of the Palaearctic biogeographic realm. It focuses on precisely delimited plots of eight standard grain sizes (0.0001; 0.001; ... 1,000 m²) and on nested-plot series with at least four different grain sizes. The usage of GrassPlot is regulated through Bylaws that intend to balance the interests of data contributors and data users. The current version (v. 1.00) contains data for approximately 170,000 plots of different sizes and 2,800 nested-plot series. The key components are richness data and metadata. However, most included datasets also encompass compositional data. About 14,000 plots have near-complete records of terricolous bryophytes and lichens in addition to vascular plants. At present, GrassPlot contains data from 36 countries throughout the Palaearctic, spread across elevational gradients and major grassland types. GrassPlot with its multi-scale and multi-taxon focus complements the larger international vegetation-plot databases, such as the European Vegetation Archive (EVA) and the global database “sPlot”. Its main aim is to facilitate studies on the scale- and taxon-dependency of biodiversity patterns and drivers along macroecological gradients. GrassPlot is a dynamic database and will expand through new data collection coordinated by the elected Governing Board. We invite researchers with suitable data to join GrassPlot. Researchers with project ideas addressable with GrassPlot data are welcome to submit proposals to the Governing Board. Abbreviations: EDGG = Eurasian Dry Grassland Group; EVA = European Vegetation Archive; GrassPlot = Database of Scale-Dependent Phytodiversity Patterns in Palaearctic Grasslands; SAR = species-area relationship.

Published
2018

33. The influence of vegetation and landscape structural connectivity on butterflies (Lepidoptera: Papilionoidea and Hesperiidae), Carabids (Coleoptera: Carabidae), Syrphids (Diptera: Syrphidae), and sawflies (Hymenoptera: Symphyta) in Northern Italy farmland

Author

Antonio Masetti, Giovanna Puppi, Marco Genghini, Joop C. van Lenteren, Enrico Muzzi, Giovanni Burgio, Sara Landi, Fausto Pesarini, Mario Marini, Alessandro Chiarucci, Daniele Sommaggio, Roberto Ferrari, Roberto Fabbri, Burgio, Giovanni, Sommaggio, Daniele, Marini, Mario, Puppi, Giovanna, Chiarucci, Alessandro, Landi, Sara, Fabbri, Roberto, Pesarini, Fausto, Genghini, Marco, Ferrari, Roberto, Muzzi, Enrico, Van Lenteren, Joop C., and Masetti, Antonio

Subjects
agroecosystem, ved/biology.organism_classification_rank.species, agri-environment scheme, Biology, hedgerow network, Shrub, Abundance (ecology), Animals, insect biodiversity, Laboratory of Entomology, Ecology, Evolution, Behavior and Systematics, Ecosystem, insect biodiversity, rural landscape, agri-environment scheme, hedgerow network, agroecosystem, Ecology, ved/biology, Diptera, Insect biodiversity, Agriculture, Vegetation, Biodiversity, Plants, biology.organism_classification, PE&RC, Laboratorium voor Entomologie, Hymenoptera, Coleoptera, Italy, Insect Science, Papilionoidea, rural landscape, Rarefaction (ecology), Species richness, Landscape ecology, Butterflies
Abstract

Landscape structure as well as local vegetation influence biodiversity in agroecosystems. A study was performed to evaluate the effect of floristic diversity, vegetation patterns, and landscape structural connectivity on butterflies (Lepidoptera: Papilionoidea and Hesperiidae), carabids (Coleoptera: Carabidae), syrphids (Diptera: Syrphidae), and sawflies (Hymenoptera: Symphyta). Vegetation analysis and insect samplings were carried out in nine sites within an intensively farmed landscape in northern Italy. Plant species richness and the percentage of tree, shrub, and herb cover were determined by means of the phytosociological method of Braun-Blanquet. Landscape structural connectivity was measured as the total length of hedgerow network (LHN) in a radius of 500 m around the center of each sampling transect. Butterflies species richness and abundance were positively associated both to herb cover and to plant species richness, but responded negatively to tree and shrub cover. Shrub cover was strictly correlated to both species richness and activity density of carabids. The species richness of syrphids was positively influenced by herb cover and plant richness, whereas their abundance was dependent on ligneous vegetation and LHN. Rarefaction analysis revealed that sawfly sampling was not robust and no relationship could be drawn with either vegetation parameters or structural connectivity. The specific responses of each insect group to the environmental factors should be considered in order to refine and optimize landscape management interventions targeting specific conservation endpoints.

Published
2015

34. How to publish a good journal in plant community ecology?

Author

Milan Chytrý, Meelis Pärtel, Valério D. Pillar, Alessandro Chiarucci, Partel, Meeli, Chiarucci, Alessandro, Chytry, Milan, and Pillar, Valerio D.

Subjects
0106 biological sciences, 010504 meteorology & atmospheric sciences, Ecology, Impact factor, Web of science, business.industry, Ecology (disciplines), Plant community, Plant Science, 15. Life on land, 010603 evolutionary biology, 01 natural sciences, vegetation, Political science, business, Publication, 0105 earth and related environmental sciences
Abstract

We are pleased to publish the 27th volume of the Journal of Vegetation Science (JVS). Since its inception in 1990, JVS has been increasingly recognized by readers as a leading publication in the field of plant community ecology. This is reflected in its steadily increasing impact factor according to Thomson Reuters Web of Science. The current IF for JVS is 3.709, well comparable to many other established ecological journals. Although a high impact factor is definitely not our central goal, it is, nonetheless, an indication of visibility and recognition of the research published in the journal.

Published
2015

35. Incorporating spatial autocorrelation in rarefaction methods: Implications for ecologists and conservation biologists

Author

Enrico Tordoni, Daniela Ciccarelli, Samuel M. Scheiner, Michael W. Palmer, Duccio Rocchini, Alfredo Altobelli, Carlo Ricotta, Alessandro Chiarucci, Michela Cameletti, Giovanni Bacaro, Stefano Martellos, Bacaro, Giovanni, Altobelli, Alfredo, Cameletti, Michela, Ciccarelli, Daniela, Martellos, Stefano, Palmer, Michael W, Ricotta, Carlo, Rocchini, Duccio, Scheiner, Samuel M., Tordoni, Enrico, Chiarucci, Alessandro, and Palmer, Michael W.

Subjects
0106 biological sciences, Evolution, Computer science, Settore BIO/03 - BOTANICA AMBIENTALE E APPLICATA, General Decision Sciences, Conservation, 010603 evolutionary biology, 01 natural sciences, Rarefaction Curve, Behavior and Systematics, Econometrics, Site of Community Importance, Spatial analysis, Ecology, Evolution, Behavior and Systematics, Coastal Dune Vegetation, Ecology, Spatial structure, 010604 marine biology & hydrobiology, Sampling (statistics), Biodiversity,Coastal dune vegetation,Conservation,Rarefaction curves,Reserve selection,Site of Community Importance,Spatial autocorrelation,Spatially Explicit Rarefaction, Biodiversity, Vegetation, 15. Life on land, Rarefaction Curves, Spatial Autocorrelation, Decision Sciences (all), Coastal dune vegetation, Rarefaction curves, Reserve selection, Spatial autocorrelation, Spatially Explicit Rarefaction, Reserve Selection, Rarefaction (ecology), Species richness, Settore SECS-S/01 - Statistica
Abstract

Recently, methods for constructing Spatially Explicit Rarefaction (SER) curves have been introduced in the scientific literature to describe the relation between the recorded species richness and sampling effort and taking into account for the spatial autocorrelation in the data. Despite these methodological advances, the use of SERs has not become routine and ecologists continue to use rarefaction methods that are not spatially explicit. Using two study cases from Italian vegetation surveys, we demonstrate that classic rarefaction methods that do not account for spatial structure can produce inaccurate results. Furthermore, our goal in this paper is to demonstrate how SERs can overcome the problem of spatial autocorrelation in the analysis of plant or animal communities. Our analyses demonstrate that using a spatially-explicit method for constructing rarefaction curves can substantially alter estimates of relative species richness. For both analyzed data sets, we found that the rank ordering of standardized species richness estimates was reversed between the two methods. We strongly advise the use of spatially-explicit rarefaction methods when analyzing biodiversity: the inclusion of spatial autocorrelation into rarefaction analyses can substantially alter conclusions and change the way we might prioritize or manage nature reserves.

Published
2016

36. Shape matters in sampling plant diversity: evidence from the field

Author

Margherita Gioria, Matteo Marcantonio, Simona Maccherini, Sara Landi, Alfredo Altobelli, Giovanni Bacaro, Valerio Amici, Martin Diekmann, Alessandro Chiarucci, Duccio Rocchini, Patrizia Gasparini, Enrico Tordoni, Dino Torri, Miris Castello, Bacaro, Giovanni, Rocchini, Duccio, Diekmann, Martin, Gasparini, Patrizia, Gioria, Margherita, Maccherini, Simona, Marcantonio, Matteo, Tordoni, Enrico, Amici, Valerio, Landi, Sara, Torri, Dino, Castello, Miri, Altobelli, Alfredo, Chiarucci, Alessandro, and Tordonia, Enrico

Subjects
Evolution, Biology, Behavior and Systematics, Settore BIO/07 - ECOLOGIA, Statistics, Sampling design, Biodiversity monitoring, Environmental gradient, Rarefaction, Shape, Species richness, Ecology, Evolution, Behavior and Systematics, Ecological Modeling, biodiversity, Ecology, Species diversity, Sampling (statistics), Vegetation, biodiversity monitoring, rarefaction, sampling design, shape, species richness, test site shape, Rarefaction (ecology), Subplot
Abstract

The identification of shape and size of sampling units that maximises the number of plant species recorded in multiscale sampling designs has major implications in conservation planning and monitoring actions. In this paper we tested the effect of three sampling shapes (rectangles, squared, and randomly shaped sampling units) on the number of recorded species. We used a large dataset derived from the network of protected areas in the Siena Province, Italy. This dataset is composed of plant species occurrence data recorded from 604 plots (10 m × 10 m), each divided in a grid of 16 contiguous subplot units (2.5 m × 2.5 m). Moreover, we evaluated the effect of plot orientation along the main environmental gradient, to examine how the selection of plot orientation (when elongated plots are used) influences the number of species collected. In total, 1041 plant species were recorded from the study plots. A significantly higher species richness was recorded by the random arrangement of 4 subplots within each plot in comparison to the ‘rectangle’ and ‘square’ shapes. Although the rectangular shape captured a significant larger number of species than squared ones, plot orientation along the main environmental gradient did not show a systematic effect on the number of recorded species. We concluded that the choice of whether or not using elongated (rectangular) versus squared plots should dependent upon the objectives of the specific survey with squared plots being more suitable for assessing species composition of more homogeneous vegetation units and rectangular plots being more suited for recording more species in the pooled sample of a large area.

Published
2015

37. Quantifying plant species diversity in a Natura 2000 network: Old ideas and new proposals

Author

Alessandro Chiarucci, Duccio Rocchini, Giovanni Bacaro, CHIARUCCI A., BACARO G., ROCCHINI D., Chiarucci, Alessandro, Bacaro, Giovanni, and Rocchini, Duccio

Subjects
Plant communitie, Reserve network, Vegetation, Plant communities, Ecology, Evolution, Conservation biology, Biodiversity, Species diversity, Plant community, Biodiversity monitoring, Biology, Biodiversity assessment, Ecology, Evolution, Behavior and Systematics, Nature and Landscape Conservation, Ecology, Evolution, Behavior and Systematic, Behavior and Systematics, Alpha diversity, Species richness, Natura 2000
Abstract

Assessing the effects of the spatial components on species diversity in a network of protected areas represents an important step for assessing its conservation “capacity”. A clear evaluation on how α -, β -, and γ -diversity are partitioned among and within spatial scales can help to drive manager decisions and provide method for monitoring species diversity. Moving from these concepts, a probabilistic sample of plant species composition was here applied for quantifying plant species diversity within the Sites of Community Importance (SCIs) of the Natura 2000 network in the Siena Province. All analyses were performed separately for all species and those species defined as “focal” (included in regional, national or continental “red” lists). The results indicated that species richness of the SCIs differed from one location to another one independently from the sampling efforts. Diversity partitioning indicated that most of the flora diversity within the network was given by larger-scale β -diversity, i.e. the differences in species composition among SCIs. β -diversity was then decomposed in two components: β Area (due to the differences in area among SCIs) and β Replacement (due to the compositional differences across SCIs). β Area was particularly important for all species, while β Replacement was the most important factor for focal species. The consequent implications for monitoring and nature conservation strategies are discussed.

Published
2008

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