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1. ReSurveyEurope: A database of resurveyed vegetation plots in Europe

Author

Knollová, I., Chytrý, M., Bruelheide, H., Dullinger, S., Jandt, U., Bernhardt-Römermann, M., Biurrun, I., Roscher, Christiane, Rosenthal, G., et al., Knollová, I., Chytrý, M., Bruelheide, H., Dullinger, S., Jandt, U., Bernhardt-Römermann, M., Biurrun, I., Roscher, Christiane, and Rosenthal, G., et al.

Abstract

Aims We introduce ReSurveyEurope — a new data source of resurveyed vegetation plots in Europe, compiled by a collaborative network of vegetation scientists. We describe the scope of this initiative, provide an overview of currently available data, governance, data contribution rules, and accessibility. In addition, we outline further steps, including potential research questions. Results ReSurveyEurope includes resurveyed vegetation plots from all habitats. Version 1.0 of ReSurveyEurope contains 283,135 observations (i.e., individual surveys of each plot) from 79,190 plots sampled in 449 independent resurvey projects. Of these, 62,139 (78%) are permanent plots, that is, marked in situ, or located with GPS, which allow for high spatial accuracy in resurvey. The remaining 17,051 (22%) plots are from studies in which plots from the initial survey could not be exactly relocated. Four data sets, which together account for 28,470 (36%) plots, provide only presence/absence information on plant species, while the remaining 50,720 (64%) plots contain abundance information (e.g., percentage cover or cover–abundance classes such as variants of the Braun-Blanquet scale). The oldest plots were sampled in 1911 in the Swiss Alps, while most plots were sampled between 1950 and 2020. Conclusions ReSurveyEurope is a new resource to address a wide range of research questions on fine-scale changes in European vegetation. The initiative is devoted to an inclusive and transparent governance and data usage approach, based on slightly adapted rules of the well-established European Vegetation Archive (EVA). ReSurveyEurope data are ready for use, and proposals for analyses of the data set can be submitted at any time to the coordinators. Still, further data contributions are highly welcome.

Published
2024

2. Traits of dominant plant species drive normalized difference vegetation index in grasslands globally

Author

Engel, Thore, Bruelheide, H., Hoss, D., Sabatini, F.M., Altman, J., Arfin-Khan, M.A.S., Bergmeier, E., Černý, T., Chytrý, M., Dainese, M., Dengler, J., Dolezal, J., Field, R., Fischer, F.M., Huygens, D., Jandt, U., Jansen, F., Jentsch, A., Karger, D.N., Kattge, J., Lenoir, J., Lens, F., Loos, J., Niinemets, Ü., Overbeck, G.E., Ozinga, W.A., Penuelas, J., Peyre, G., Phillips, O., Reich, P.B., Römermann, C., Sandel, B., Schmidt, M., Schrodt, F., Velez-Martin, E., Violle, C., Pillar, V., Engel, Thore, Bruelheide, H., Hoss, D., Sabatini, F.M., Altman, J., Arfin-Khan, M.A.S., Bergmeier, E., Černý, T., Chytrý, M., Dainese, M., Dengler, J., Dolezal, J., Field, R., Fischer, F.M., Huygens, D., Jandt, U., Jansen, F., Jentsch, A., Karger, D.N., Kattge, J., Lenoir, J., Lens, F., Loos, J., Niinemets, Ü., Overbeck, G.E., Ozinga, W.A., Penuelas, J., Peyre, G., Phillips, O., Reich, P.B., Römermann, C., Sandel, B., Schmidt, M., Schrodt, F., Velez-Martin, E., Violle, C., and Pillar, V.

Abstract

Aim Theoretical, experimental and observational studies have shown that biodiversity–ecosystem functioning (BEF) relationships are influenced by functional community structure through two mutually non-exclusive mechanisms: (1) the dominance effect (which relates to the traits of the dominant species); and (2) the niche partitioning effect [which relates to functional diversity (FD)]. Although both mechanisms have been studied in plant communities and experiments at small spatial extents, it remains unclear whether evidence from small-extent case studies translates into a generalizable macroecological pattern. Here, we evaluate dominance and niche partitioning effects simultaneously in grassland systems world-wide. Location Two thousand nine hundred and forty-one grassland plots globally. Time period 2000–2014. Major taxa studied Vascular plants. Methods We obtained plot-based data on functional community structure from the global vegetation plot database “sPlot”, which combines species composition with plant trait data from the “TRY” database. We used data on the community-weighted mean (CWM) and FD for 18 ecologically relevant plant traits. As an indicator of primary productivity, we extracted the satellite-derived normalized difference vegetation index (NDVI) from MODIS. Using generalized additive models and deviation partitioning, we estimated the contributions of trait CWM and FD to the variation in annual maximum NDVI, while controlling for climatic variables and spatial structure. Results Grassland communities dominated by relatively tall species with acquisitive traits had higher NDVI values, suggesting the prevalence of dominance effects for BEF relationships. We found no support for niche partitioning for the functional traits analysed, because NDVI remained unaffected by FD. Most of the predictive power of traits was shared by climatic predictors and spatial coordinates. This highlights the importance of community assembly processes for BEF relationships i

Published
2023

3. sPlotOpen – An environmentally balanced, open-access, global dataset of vegetation plots

Author

Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E.A., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jiménez-Alfaro, B., Kattge, J., Virtanen, Risto, von Wehrden, H., et al., Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E.A., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jiménez-Alfaro, B., Kattge, J., Virtanen, Risto, and von Wehrden, H., et al.

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 vasc

Published
2021

4. Global functional variation in alpine vegetation

Author

Testolin, R., Pérez Carmona, C., Attorre, F., Borchardt, P., Bruelheide, H., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Mucina, L., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Vassilev, K., Virtanen, Risto, Wiser, S.K., Zibzeev, E.G., Jiménez‐Alfaro, B., Testolin, R., Pérez Carmona, C., Attorre, F., Borchardt, P., Bruelheide, H., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Mucina, L., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Vassilev, K., Virtanen, Risto, Wiser, S.K., Zibzeev, E.G., and Jiménez‐Alfaro, B.

Abstract

Questions What are the functional trade‐offs of vascular plant species in global alpine ecosystems? How is functional variation related to vegetation zones, climatic groups and biogeographic realms? What is the relative contribution of macroclimate and evolutionary history in shaping the functional variation of alpine plant communities? Location Global. Methods We compiled a data set of alpine vegetation with 5,532 geo‐referenced plots, 1,933 species and six plant functional traits. We used principal component analysis to quantify functional trade‐offs among species and trait probability density to assess the functional dissimilarity of alpine vegetation in different vegetation zones, climatic groups and biogeographic realms. We used multiple regression on distance matrices to model community functional dissimilarity against environmental and phylogenetic dissimilarity, controlling for geographic distance. Results The first two PCA axes explained 66% of the species’ functional variation and were related to the leaf and stem economic spectra, respectively. Trait probability density was largely independent of vegetation zone and macroclimate but differed across biogeographic realms. The same pattern emerged for both species pool and community levels. The effects of environmental and phylogenetic dissimilarities on community functional dissimilarity had similar magnitude, while the effect of geographic distance was negligible. Conclusions Plant species in alpine areas reflect the global variation of plant function, but with a predominant role of resource use strategies. Current macroclimate exerts a limited effect on alpine vegetation, mostly acting at the community level in combination with evolutionary history. Global alpine vegetation is functionally unrelated to the vegetation zones in which it is embedded, exhibiting strong functional convergence across regions.

Published
2021

5. Global patterns and drivers of alpine plant species richness

Author

Testolin, R., Attorre, F., Borchardt, P., Brand, R.F., Bruelheide, H., Chytrý, M., De Sanctis, M., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Kessler, M., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Montesinos‐Tubée, D.B., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Sylvester, S.P., Vassilev, K., Virtanen, Risto, Willner, W., Wiser, S.K., Zibzeev, E.G., Jiménez‐Alfaro, B., Testolin, R., Attorre, F., Borchardt, P., Brand, R.F., Bruelheide, H., Chytrý, M., De Sanctis, M., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Kessler, M., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Montesinos‐Tubée, D.B., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Sylvester, S.P., Vassilev, K., Virtanen, Risto, Willner, W., Wiser, S.K., Zibzeev, E.G., and Jiménez‐Alfaro, B.

Abstract

Aim Alpine ecosystems differ in area, macroenvironment and biogeographical history across the Earth, but the relationship between these factors and plant species richness is still unexplored. Here, we assess the global patterns of plant species richness in alpine ecosystems and their association with environmental, geographical and historical factors at regional and community scales. Location Global. Time period Data collected between 1923 and 2019. Major taxa studied Vascular plants. Methods We used a dataset representative of global alpine vegetation, consisting of 8,928 plots sampled within 26 ecoregions and six biogeographical realms, to estimate regional richness using sample‐based rarefaction and extrapolation. Then, we evaluated latitudinal patterns of regional and community richness with generalized additive models. Using environmental, geographical and historical predictors from global raster layers, we modelled regional and community richness in a mixed‐effect modelling framework. Results The latitudinal pattern of regional richness peaked around the equator and at mid‐latitudes, in response to current and past alpine area, isolation and the variation in soil pH among regions. At the community level, species richness peaked at mid‐latitudes of the Northern Hemisphere, despite a considerable within‐region variation. Community richness was related to macroclimate and historical predictors, with strong effects of other spatially structured factors. Main conclusions In contrast to the well‐known latitudinal diversity gradient, the alpine plant species richness of some temperate regions in Eurasia was comparable to that of hyperdiverse tropical ecosystems, such as the páramo. The species richness of these putative hotspot regions is explained mainly by the extent of alpine area and their glacial history, whereas community richness depends on local environmental factors. Our results highlight hotspots of species richness at mid‐latitudes, indicating that the div

Published
2021

6. A checklist for using Beals’ index with incomplete floristic monitoring data. Reply to Christensen et al. (2021): Problems in using Beals’ index to detect species trends in incomplete floristic monitoring data

Author

Bruelheide, H., Jansen, F., Jandt, U., Bernhardt-Römermann, M., Bonn, Aletta, Bowler, Diana, Dengler, J., Eichenberg, D., Grescho, Volker, Kellner, S., Klenke, Reinhard, Lütt, S., Lüttgert, L., Sabatini, F.M., Wesche, K., Bruelheide, H., Jansen, F., Jandt, U., Bernhardt-Römermann, M., Bonn, Aletta, Bowler, Diana, Dengler, J., Eichenberg, D., Grescho, Volker, Kellner, S., Klenke, Reinhard, Lütt, S., Lüttgert, L., Sabatini, F.M., and Wesche, K.

Abstract

Christensen et al. criticized the application of Beals’ index of sociological favourability to adjust for incomplete species lists when comparing repeated surveys. Their main argument was that using Beals’ conditional occurrence probabilities would systematically underestimate biodiversity change compared to using observed frequencies. Although this might be the case for rare species, as we explicitly stated in our original publication, we here use a worked-out example to show that this criticism is unjustified for species that are sufficiently represented in the reference data set. In our opinion, the misconception derives from ignoring one of the key requirements for applying Beal's index, which is the use of a sufficiently large reference data set to derive a reliable co-occurrence matrix. We here show how the predicted probability for the occurrence of a species depends on the size of the reference data set and give recommendations on the premises for applying Beals’ approach for monitoring purposes.

Published
2021

7. TRY plant trait database - enhanced coverage and open access

Author

Kattge, J., Bonisch, G., Diaz, S., Lavorel, S., Prentice, I. C., Leadley, P., Tautenhahn, S., Werner, G. D. A., Aakala, T., Abedi, M., Acosta, A. T. R., Ciccarelli, D., Fontana, V., Roberts, S., Robroek, B., Roddy, A., Marchetti, Z., Rodrigues, A. V., Bekker, R., Honnay, O., Chapin, F. S., Bauters, M., Amiaud, B., Rogers, A., Rollinson, E., Rolo, V., Romermann, C., Ronzhina, D., Amoroso, M. M., Marchino, L., Coll, L., Roscher, C., Cherubini, P., Kloeppel, B., Rosell, J. A., Rosenfield, M. F., Kraft, N. J. B., Hornstein, D., Rossi, C., Roy, D. B., Belfry, G., Royer-Tardif, S., Marcilio-Silva, V., Pakeman, R. J., Ruger, N., Ma, S. Y., Ruiz-Peinado, R., Forey, E., Rumpf, S. B., Collins, C. G., Kramer, K., Rusch, G. M., Hou, E. Q., Ryo, M., Papageorgiou, A. C., Sack, L., Falster, D. S., Ammer, C., Saldana, A., Salgado-Negret, B., Salguero-Gomez, R., Belluau, M., Santa-Regina, I., Forgiarini, C., Bahalkeh, K., Parfionova, E., Santacruz-Garcia, A. C., Santos, J., Asmara, D. H., Morrison, J., Marcon, E., Conti, L., Sardans, J., Schamp, B., Scherer-Lorenzen, M., Schleuning, M., Koike, F., Schmid, B., Schmidt, M., Kreft, H., Schmitt, S., Mucina, L., Francois, L., Marignani, M., Beloiu, M., Ejtehadi, H., Schneider, J. V., Partel, M., Schowanek, S. D., Coomes, D., Schrader, J., Schrodt, F., Schuldt, B., Mueller, S., Kuhn, I., Schurr, F., Kitzberger, T., Garvizu, G. S., Patacca, M., Semchenko, M., Frangipani, M., Hough-Snee, N., Seymour, C., Sfair, J. C., Benavides, R., Muir, C. D., Sharpe, J. M., Albert, C. H., Kumarathunge, D., Finegan, B., Cailleret, M., Sheppard, C. S., Sheremetiev, S., Shiodera, S., Shipley, B., Shovon, T. A., Adamidis, G. C., Muller, S. C., Frank, D., Siebenkas, A., Baldocchi, D., Sierra, C., Silva, V., Markesteijn, L., Kuppler, J., Silva, M., Benomar, L., Cornelissen, J. H. C., Sitzia, T., Baruch, Z., Sjoman, H., Moravcova, L., Slot, M., Hovstad, K. A., Smith, N. G., Frenette-Dussault, C., Martin, A., Sodhi, D., Kurokawa, H., Soltis, P., Soltis, D., Heuertz, M., Camac, J., Somers, B., Sonnier, G., Sorensen, M. V., Cornwell, W. K., Berdugo-Lattke, M. L., Ichie, T., Cavender-Bares, J., Sosinski, E. E., Soudzilovskaia, N. A., Carbognani, M., Paula, S., Munoz, F., Freschet, G. T., Souza, A. F., Spasojevic, M., Sperandii, M. G., Stan, A. B., Stegen, J., Steinbauer, K., Baltzer, J., Stephan, J. G., Paule, J., Igic, B., Myers-Smith, I. H., Corona, P., Hattingh, W., Sterck, F., Berenguer, E., Fry, E. L., Stojanovic, D. B., Strydom, T., Suarez, M. L., Pauli, H., Martinez-Garza, C., Svenning, J. C., Pereira, C. M. R., Svitkova, I., Svitok, M., Illa, E., Kurosawa, Y., Svoboda, M., Swaine, E., Coyea, M., Pausas, J. G., Swenson, N., Byun, C., Martinez-Vilalta, J., Esquivel-Muelbert, A., Tabarelli, M., Bergamin, R., Takagi, K., Tappeiner, U., Tarifa, R., Burrascano, S., Peco, B., Isaac, M., Tauugourdeau, S., Tavsanoglu, C., te Beest, M., Myster, R. W., Maskova, T., Tedersoo, L., Craine, J., Fyllas, N. M., Thiffault, N., Chianucci, F., Thom, D., Thomas, E., Kuyah, S., Bergmann, J., Ishihara, M., Nagano, M., Thompson, K., Mason, K., Thornton, P. E., Thuiller, W., Kollmann, J., Tichy, L., Tissue, D., Tjoelker, M. G., Mazzochini, G. G., Craven, D., Laclau, J. P., Feng, Y. H., Tng, D. Y. P., Tobias, J., Fan, Y., Bazzato, E., Ivanov, L., Torok, P., Tarin, T., Carlucci, M. B., Torres-Ruiz, J. M., Tothmeresz, B., Treurnicht, M., Chelli, S., Trivellone, V., Lafleur, B., Penuelas, J., Anand, M., Kjoller, R., Trolliet, F., Cromsigt, J. P. G. M., Ivanova, L., Trotsiuk, V., Tsakalos, J. L., Tsiripidis, I., Naidu, S., Tysklind, N., Barneche, D. R., Umehara, T., Berner, L., Lallai, E., Mason, N., Usoltsev, V. A., Vadeboncoeur, M., Gachet, S., Vaezi, J., Elser, J., Narayanan, A., Helm, A., Valladares, F., Csecserits, A., Vamosi, J., van Bodegom, P. M., van Breugel, M., E-Vojtko, A., Bahn, M., Van Cleemput, E., van de Weg, M., van der Merwe, S., Perea, A., Natesan, B., Bernhardt-Romermann, M., Gallagher, R., Iversen, C. M., van der Plas, F., van der Sande, M. T., van Kleunen, M., Massad, T. J., Cufar, K., Lamb, E., Peri, P. L., Van Meerbeek, K., Negoita, L., Vanderwel, M., Vanselow, K. A., Varhammar, A., Varone, L., Valderrama, M. Y., Asner, G. P., Ganade, G., Masse, J., Hipp, A. L., Vassilev, K., Bigler, C., Hickler, T., Lamprecht, A., Vellend, M., Veneklaas, E. J., Cuntz, M., Verbeeck, H., Verheyen, K., Vibrans, A., Firn, J., Vieira, I., Mayrose, I., Camarero, J. J., Mack, M., Villacis, J., Ganga, F., Larkin, D. J., Violle, C., Vivek, P., Wagner, K., Petisco-Souza, A. C., Bjorkman, A. D., Waldram, M., Alcantara, J. M., McCarthy, J., Nelson, A. S., Waldron, A., Walker, A. P., Izquierdo, J., Waller, M., Hawes, J. E., Petraglia, A., Walther, G., Garcia-Palacios, P., Wang, H., Wang, F., Wang, W. Q., Han, W. X., Cerabolini, B. E. L., Watkins, H., Watkins, J., Blackman, C., Petritan, A. M., da Silva, A. C., Jackson, R. B., Laughlin, D., Weber, U., Weedon, J. T., Wei, L. P., Neuschulz, E. L., Gargaglione, V., McCormack, M. L., Weigelt, P., Phillips, O. L., Weiher, E., Wells, A. W., Wellstein, C., Wenk, E., Westoby, M., Carvalho, F., Jackson, B., Bastianelli, D., Westwood, A., Dahlin, K. M., Komac, B., Banerjee, A., Blanco, C., White, P. J., Garnier, E., Whitten, M., Williams, M., Winkler, D. E., Winter, K., Ni, J., Esser, G., Moreno-Martinez, A., Womack, C., Jactel, H., McCulloh, K., Wright, I. J., Wright, S. J., Wright, J., Dainese, M., Pinho, B. X., Marques, M., Niedrist, G., Pierce, S., Blonder, B., Ximenes, F., Le Bagousse-Pinguet, Y., Yamada, T., Klein, T., Yamaji, K., Jagodzinski, A. M., Yanai, R., Yankov, N., Yguel, B., Kitajima, K, Fernandez-Mendez, F., Zanini, K. J., Zanne, A. E., Dalke, I., Garrido, J. L., le Maire, G., McFadden, I. R., Zeleny, D., Zhao, Y. P., Blumenthal, D., Pillar, V. D., Jandt, U., Nieto, J., Zheng, J. M., Zheng, J., Zieminska, K., Zirbel, C. R., Zizka, G., Zo-Bi, I. C., Fang, J. Y., le Roux, P. C., Choat, B., Zotz, G., de Gasper, A. L., Chen, S. C., Dalle Fratte, M., Wirth, C., Jansen, S., Bocanegra-Gonzalez, K. T., Boeckx, P., Bohlman, S., Bohning-Gaese, K., Pisek, J., Hempel, S., Boisvert-Marsh, L., le Roux, E., Niinemets, U., Bond, W., Bond-Lamberty, B., Boom, A., Gea-Izquierdo, G., Boonman, C. C. F., Emilio, T., Beckmann, M., Anh, T. D. L., Bordin, K., McGill, B. J., Boughton, E. H., Maire, V., Boukili, V., Lee, T., Bowman, D. M. J. S., Bravo, S., Brendel, M. R., Hirons, A., Broadley, M. R., Brown, K. A., Anderson, C., Jenkins, T., McPartland, M. Y., Nolan, R., Bruelheide, H., Brumnich, F., Danihelka, J., Lens, F., Pomogaybin, A., Bruun, H. H., Bruy, D., Buchanan, S. W., Bucher, S. F., Buchmann, N., Buitenwerf, R., Ashman, T. L., Medeiros, J. S., Bunker, D. E., Jentsch, A., Flowers, T. J., Gibson, D., Burger, J., Baker, T., Dannoura, M., Dawson, S., de Beer, A. J., Alcazar, C. C., Baastrup-Spohr, L., De Frutos, A., Medlyn, B., Poorter, H., De Long, J. R., Dechant, B., Delagrange, S., Jespersen, J. R. P., Delpierre, N, He, T. H., Gillison, A. N., Derroire, G., Nottebrock, H., Dias, A. S., Moretti, M., Diaz-Toribio, M. H., Meerts, P., Dimitrakopoulos, P. G., Dobrowolski, M., Aleixo, I., Doktor, D., Drevojan, P., Campany, C., Lewis, S. L., Nouvellon, Y., Portsmuth, A., Dong, N., Dransfield, J., Giroldo, A., Mehrabi, Z., Dressler, S., Duarte, L., Ducouret, E., Dullinger, S., Durka, W., Duursma, R., Canullo, R., Novakovskiy, A., Ali, H., Lhotsky, B., Aspinwall, M., Dymova, O., Cervellini, M., Glasenhardt, M. C., Gleason, S., Gliesch, M., Scalon, M. C., Catford, J. A., Goldberg, E., Nystuen, K. O., Goldel, B., Gonzalez-Akre, E., Gonzalez-Andujar, J. L., Li, Y. Z., Anten, N., Kleyer, M., Jiang, G. F., Gonzalez-Melo, A., Poschlod, P., Gonzalez-Robles, A., Graae, B. J., O'Grady, A., Granda, E., Graves, S., Caccianiga, M., Green, W. A., Gregor, T., Estiarte, M., Meir, P., Potvin, C., Gross, N., Guerin, G. R., Johansen, J. L., Battles, J., Gunther, A., Antos, J., Gutierrez, A. G., Haddock, L, Haines, A., Hall, J., Pounds, D., Cadotte, M., Melo, F. P. L., Casanoves, F., Hambuckers, A., Ferrara, C., Johnson, D., Jokela, E. J., Joly, C. A., Engemann, K., Jordan, G. J., Powell, A. S., Joseph, G. S., Junaedi, D., Junker, R. R., Baranger, A., Campetella, G., Makela, A., Li, X. E., Justes, E., Atkin, O., Kabzems, R., Power, S. A., Kane, J., Kaplan, Z., Erfanian, M. B., Kattenborn, T., Kavelenova, L., Hentschel, J., O'Hara, K., Kearsley, E., Kempel, A., Lichstein, J. W., Chung, K. S., Kenzo, T., Campos, J. A., Kerkhoff, A., Khalil, M. I., Aubin, I., Kinlock, N. L., Erfmeier, A., O'Reilly-Nugent, A., Farris, E., Kissling, W. D., Hock, M., Liebergesell, M., Lim, J. Y., Lin, Y. S., Apgaua, D. M. G., Linares, J. C., Liu, C. J., Baker, W. J., Liu, D. J., Chen, A. P., Domingues, T. F., Mori, A. S., Mencuccini, M., Liu, U., Castagneyrol, B., Livingstone, S., Llusia, J., Lohbeck, M., He, P. C., Lopez-Garcia, A., Lopez-Gonzalez, G., Klotz, S., Prinzing, A., Lososova, Z., Louault, F., Meredieu, C., Lukacs, B. A., Fagan, W. F., Bakker, J. P., Lukes, P., Adamson, K., Luo, Y. J., Heberling, J. M., Puglielli, G., Hietz, P., Lussu, M., Messier, J., Meszaros, I., Metsaranta, J., Cano-Arboleda, L., Michaletz, S. T., Michelaki, C., Chacon-Madrigal, E., Migalina, S., Flynn, D. F. B, Herault, B., Oakley, S., Milla, R., Fazlioglu, F., Miller, J. E. D., Barlow, J., Minden, V., Klimesova, J., Ming, R., Mokany, K., Mallik, A., Moles, A. T., Molnar, V. A., Oberhuber, W., Molofsky, J., Heres, A. M., Chapin, K., Molz, M., Burslem, D. F. R. P., Montgomery, R. A., Klipel, J., Komatsu, K., Monty, A., Ohtsuka, T., Oliveira, R., Ollerer, K., Fagundez, J., Olson, M. E., Onipchenko, V., Ferreira, J., Onoda, Y., Knops, J. M. H., Beeckman, H., Bauerle, W., Higuchi, P., Onstein, R. E., Aiba, M., Ordonez, J. C., Makinen, H., Osada, N., Ostonen, I., Ottaviani, G., Otto, S., Pysek, P., Overbeck, G. E., Kohyama, T., Fidelis, A., Ozinga, W. A., Eckstein, R. L., Pahl, A. T., Malhado, A. C. M., Paine, C. E. T., Raevel, V., Rammig, A., Ransijn, J., Herz, K., Ray, C. A., Reich, P. B., Hogan, J. A., Reichstein, M., Manning, P., Chytry, M., Konig, C., Reid, D. E. B., Butterfield, B. J., Rejou-Mechain, M., Mori, S., de Dios, V. R., Beierkuhnlein, C., Ribeiro, S, Richardson, S, Riibak, K., Manzoni, S., Holl, K., Rillig, M. C., Harrison, S. P., Riviera, F., Morris, D., Robert, E. M. R., Kattge, J., Bonisch, G., Diaz, S., Lavorel, S., Prentice, I. C., Leadley, P., Tautenhahn, S., Werner, G. D. A., Aakala, T., Abedi, M., Acosta, A. T. R., Ciccarelli, D., Fontana, V., Roberts, S., Robroek, B., Roddy, A., Marchetti, Z., Rodrigues, A. V., Bekker, R., Honnay, O., Chapin, F. S., Bauters, M., Amiaud, B., Rogers, A., Rollinson, E., Rolo, V., Romermann, C., Ronzhina, D., Amoroso, M. M., Marchino, L., Coll, L., Roscher, C., Cherubini, P., Kloeppel, B., Rosell, J. A., Rosenfield, M. F., Kraft, N. J. B., Hornstein, D., Rossi, C., Roy, D. B., Belfry, G., Royer-Tardif, S., Marcilio-Silva, V., Pakeman, R. J., Ruger, N., Ma, S. Y., Ruiz-Peinado, R., Forey, E., Rumpf, S. B., Collins, C. G., Kramer, K., Rusch, G. M., Hou, E. Q., Ryo, M., Papageorgiou, A. C., Sack, L., Falster, D. S., Ammer, C., Saldana, A., Salgado-Negret, B., Salguero-Gomez, R., Belluau, M., Santa-Regina, I., Forgiarini, C., Bahalkeh, K., Parfionova, E., Santacruz-Garcia, A. C., Santos, J., Asmara, D. H., Morrison, J., Marcon, E., Conti, L., Sardans, J., Schamp, B., Scherer-Lorenzen, M., Schleuning, M., Koike, F., Schmid, B., Schmidt, M., Kreft, H., Schmitt, S., Mucina, L., Francois, L., Marignani, M., Beloiu, M., Ejtehadi, H., Schneider, J. V., Partel, M., Schowanek, S. D., Coomes, D., Schrader, J., Schrodt, F., Schuldt, B., Mueller, S., Kuhn, I., Schurr, F., Kitzberger, T., Garvizu, G. S., Patacca, M., Semchenko, M., Frangipani, M., Hough-Snee, N., Seymour, C., Sfair, J. C., Benavides, R., Muir, C. D., Sharpe, J. M., Albert, C. H., Kumarathunge, D., Finegan, B., Cailleret, M., Sheppard, C. S., Sheremetiev, S., Shiodera, S., Shipley, B., Shovon, T. A., Adamidis, G. C., Muller, S. C., Frank, D., Siebenkas, A., Baldocchi, D., Sierra, C., Silva, V., Markesteijn, L., Kuppler, J., Silva, M., Benomar, L., Cornelissen, J. H. C., Sitzia, T., Baruch, Z., Sjoman, H., Moravcova, L., Slot, M., Hovstad, K. A., Smith, N. G., Frenette-Dussault, C., Martin, A., Sodhi, D., Kurokawa, H., Soltis, P., Soltis, D., Heuertz, M., Camac, J., Somers, B., Sonnier, G., Sorensen, M. V., Cornwell, W. K., Berdugo-Lattke, M. L., Ichie, T., Cavender-Bares, J., Sosinski, E. E., Soudzilovskaia, N. A., Carbognani, M., Paula, S., Munoz, F., Freschet, G. T., Souza, A. F., Spasojevic, M., Sperandii, M. G., Stan, A. B., Stegen, J., Steinbauer, K., Baltzer, J., Stephan, J. G., Paule, J., Igic, B., Myers-Smith, I. H., Corona, P., Hattingh, W., Sterck, F., Berenguer, E., Fry, E. L., Stojanovic, D. B., Strydom, T., Suarez, M. L., Pauli, H., Martinez-Garza, C., Svenning, J. C., Pereira, C. M. R., Svitkova, I., Svitok, M., Illa, E., Kurosawa, Y., Svoboda, M., Swaine, E., Coyea, M., Pausas, J. G., Swenson, N., Byun, C., Martinez-Vilalta, J., Esquivel-Muelbert, A., Tabarelli, M., Bergamin, R., Takagi, K., Tappeiner, U., Tarifa, R., Burrascano, S., Peco, B., Isaac, M., Tauugourdeau, S., Tavsanoglu, C., te Beest, M., Myster, R. W., Maskova, T., Tedersoo, L., Craine, J., Fyllas, N. M., Thiffault, N., Chianucci, F., Thom, D., Thomas, E., Kuyah, S., Bergmann, J., Ishihara, M., Nagano, M., Thompson, K., Mason, K., Thornton, P. E., Thuiller, W., Kollmann, J., Tichy, L., Tissue, D., Tjoelker, M. G., Mazzochini, G. G., Craven, D., Laclau, J. P., Feng, Y. H., Tng, D. Y. P., Tobias, J., Fan, Y., Bazzato, E., Ivanov, L., Torok, P., Tarin, T., Carlucci, M. B., Torres-Ruiz, J. M., Tothmeresz, B., Treurnicht, M., Chelli, S., Trivellone, V., Lafleur, B., Penuelas, J., Anand, M., Kjoller, R., Trolliet, F., Cromsigt, J. P. G. M., Ivanova, L., Trotsiuk, V., Tsakalos, J. L., Tsiripidis, I., Naidu, S., Tysklind, N., Barneche, D. R., Umehara, T., Berner, L., Lallai, E., Mason, N., Usoltsev, V. A., Vadeboncoeur, M., Gachet, S., Vaezi, J., Elser, J., Narayanan, A., Helm, A., Valladares, F., Csecserits, A., Vamosi, J., van Bodegom, P. M., van Breugel, M., E-Vojtko, A., Bahn, M., Van Cleemput, E., van de Weg, M., van der Merwe, S., Perea, A., Natesan, B., Bernhardt-Romermann, M., Gallagher, R., Iversen, C. M., van der Plas, F., van der Sande, M. T., van Kleunen, M., Massad, T. J., Cufar, K., Lamb, E., Peri, P. L., Van Meerbeek, K., Negoita, L., Vanderwel, M., Vanselow, K. A., Varhammar, A., Varone, L., Valderrama, M. Y., Asner, G. P., Ganade, G., Masse, J., Hipp, A. L., Vassilev, K., Bigler, C., Hickler, T., Lamprecht, A., Vellend, M., Veneklaas, E. J., Cuntz, M., Verbeeck, H., Verheyen, K., Vibrans, A., Firn, J., Vieira, I., Mayrose, I., Camarero, J. J., Mack, M., Villacis, J., Ganga, F., Larkin, D. J., Violle, C., Vivek, P., Wagner, K., Petisco-Souza, A. C., Bjorkman, A. D., Waldram, M., Alcantara, J. M., McCarthy, J., Nelson, A. S., Waldron, A., Walker, A. P., Izquierdo, J., Waller, M., Hawes, J. E., Petraglia, A., Walther, G., Garcia-Palacios, P., Wang, H., Wang, F., Wang, W. Q., Han, W. X., Cerabolini, B. E. L., Watkins, H., Watkins, J., Blackman, C., Petritan, A. M., da Silva, A. C., Jackson, R. B., Laughlin, D., Weber, U., Weedon, J. T., Wei, L. P., Neuschulz, E. L., Gargaglione, V., McCormack, M. L., Weigelt, P., Phillips, O. L., Weiher, E., Wells, A. W., Wellstein, C., Wenk, E., Westoby, M., Carvalho, F., Jackson, B., Bastianelli, D., Westwood, A., Dahlin, K. M., Komac, B., Banerjee, A., Blanco, C., White, P. J., Garnier, E., Whitten, M., Williams, M., Winkler, D. E., Winter, K., Ni, J., Esser, G., Moreno-Martinez, A., Womack, C., Jactel, H., McCulloh, K., Wright, I. J., Wright, S. J., Wright, J., Dainese, M., Pinho, B. X., Marques, M., Niedrist, G., Pierce, S., Blonder, B., Ximenes, F., Le Bagousse-Pinguet, Y., Yamada, T., Klein, T., Yamaji, K., Jagodzinski, A. M., Yanai, R., Yankov, N., Yguel, B., Kitajima, K, Fernandez-Mendez, F., Zanini, K. J., Zanne, A. E., Dalke, I., Garrido, J. L., le Maire, G., McFadden, I. R., Zeleny, D., Zhao, Y. P., Blumenthal, D., Pillar, V. D., Jandt, U., Nieto, J., Zheng, J. M., Zheng, J., Zieminska, K., Zirbel, C. R., Zizka, G., Zo-Bi, I. C., Fang, J. Y., le Roux, P. C., Choat, B., Zotz, G., de Gasper, A. L., Chen, S. C., Dalle Fratte, M., Wirth, C., Jansen, S., Bocanegra-Gonzalez, K. T., Boeckx, P., Bohlman, S., Bohning-Gaese, K., Pisek, J., Hempel, S., Boisvert-Marsh, L., le Roux, E., Niinemets, U., Bond, W., Bond-Lamberty, B., Boom, A., Gea-Izquierdo, G., Boonman, C. C. F., Emilio, T., Beckmann, M., Anh, T. D. L., Bordin, K., McGill, B. J., Boughton, E. H., Maire, V., Boukili, V., Lee, T., Bowman, D. M. J. S., Bravo, S., Brendel, M. R., Hirons, A., Broadley, M. R., Brown, K. A., Anderson, C., Jenkins, T., McPartland, M. Y., Nolan, R., Bruelheide, H., Brumnich, F., Danihelka, J., Lens, F., Pomogaybin, A., Bruun, H. H., Bruy, D., Buchanan, S. W., Bucher, S. F., Buchmann, N., Buitenwerf, R., Ashman, T. L., Medeiros, J. S., Bunker, D. E., Jentsch, A., Flowers, T. J., Gibson, D., Burger, J., Baker, T., Dannoura, M., Dawson, S., de Beer, A. J., Alcazar, C. C., Baastrup-Spohr, L., De Frutos, A., Medlyn, B., Poorter, H., De Long, J. R., Dechant, B., Delagrange, S., Jespersen, J. R. P., Delpierre, N, He, T. H., Gillison, A. N., Derroire, G., Nottebrock, H., Dias, A. S., Moretti, M., Diaz-Toribio, M. H., Meerts, P., Dimitrakopoulos, P. G., Dobrowolski, M., Aleixo, I., Doktor, D., Drevojan, P., Campany, C., Lewis, S. L., Nouvellon, Y., Portsmuth, A., Dong, N., Dransfield, J., Giroldo, A., Mehrabi, Z., Dressler, S., Duarte, L., Ducouret, E., Dullinger, S., Durka, W., Duursma, R., Canullo, R., Novakovskiy, A., Ali, H., Lhotsky, B., Aspinwall, M., Dymova, O., Cervellini, M., Glasenhardt, M. C., Gleason, S., Gliesch, M., Scalon, M. C., Catford, J. A., Goldberg, E., Nystuen, K. O., Goldel, B., Gonzalez-Akre, E., Gonzalez-Andujar, J. L., Li, Y. Z., Anten, N., Kleyer, M., Jiang, G. F., Gonzalez-Melo, A., Poschlod, P., Gonzalez-Robles, A., Graae, B. J., O'Grady, A., Granda, E., Graves, S., Caccianiga, M., Green, W. A., Gregor, T., Estiarte, M., Meir, P., Potvin, C., Gross, N., Guerin, G. R., Johansen, J. L., Battles, J., Gunther, A., Antos, J., Gutierrez, A. G., Haddock, L, Haines, A., Hall, J., Pounds, D., Cadotte, M., Melo, F. P. L., Casanoves, F., Hambuckers, A., Ferrara, C., Johnson, D., Jokela, E. J., Joly, C. A., Engemann, K., Jordan, G. J., Powell, A. S., Joseph, G. S., Junaedi, D., Junker, R. R., Baranger, A., Campetella, G., Makela, A., Li, X. E., Justes, E., Atkin, O., Kabzems, R., Power, S. A., Kane, J., Kaplan, Z., Erfanian, M. B., Kattenborn, T., Kavelenova, L., Hentschel, J., O'Hara, K., Kearsley, E., Kempel, A., Lichstein, J. W., Chung, K. S., Kenzo, T., Campos, J. A., Kerkhoff, A., Khalil, M. I., Aubin, I., Kinlock, N. L., Erfmeier, A., O'Reilly-Nugent, A., Farris, E., Kissling, W. D., Hock, M., Liebergesell, M., Lim, J. Y., Lin, Y. S., Apgaua, D. M. G., Linares, J. C., Liu, C. J., Baker, W. J., Liu, D. J., Chen, A. P., Domingues, T. F., Mori, A. S., Mencuccini, M., Liu, U., Castagneyrol, B., Livingstone, S., Llusia, J., Lohbeck, M., He, P. C., Lopez-Garcia, A., Lopez-Gonzalez, G., Klotz, S., Prinzing, A., Lososova, Z., Louault, F., Meredieu, C., Lukacs, B. A., Fagan, W. F., Bakker, J. P., Lukes, P., Adamson, K., Luo, Y. J., Heberling, J. M., Puglielli, G., Hietz, P., Lussu, M., Messier, J., Meszaros, I., Metsaranta, J., Cano-Arboleda, L., Michaletz, S. T., Michelaki, C., Chacon-Madrigal, E., Migalina, S., Flynn, D. F. B, Herault, B., Oakley, S., Milla, R., Fazlioglu, F., Miller, J. E. D., Barlow, J., Minden, V., Klimesova, J., Ming, R., Mokany, K., Mallik, A., Moles, A. T., Molnar, V. A., Oberhuber, W., Molofsky, J., Heres, A. M., Chapin, K., Molz, M., Burslem, D. F. R. P., Montgomery, R. A., Klipel, J., Komatsu, K., Monty, A., Ohtsuka, T., Oliveira, R., Ollerer, K., Fagundez, J., Olson, M. E., Onipchenko, V., Ferreira, J., Onoda, Y., Knops, J. M. H., Beeckman, H., Bauerle, W., Higuchi, P., Onstein, R. E., Aiba, M., Ordonez, J. C., Makinen, H., Osada, N., Ostonen, I., Ottaviani, G., Otto, S., Pysek, P., Overbeck, G. E., Kohyama, T., Fidelis, A., Ozinga, W. A., Eckstein, R. L., Pahl, A. T., Malhado, A. C. M., Paine, C. E. T., Raevel, V., Rammig, A., Ransijn, J., Herz, K., Ray, C. A., Reich, P. B., Hogan, J. A., Reichstein, M., Manning, P., Chytry, M., Konig, C., Reid, D. E. B., Butterfield, B. J., Rejou-Mechain, M., Mori, S., de Dios, V. R., Beierkuhnlein, C., Ribeiro, S, Richardson, S, Riibak, K., Manzoni, S., Holl, K., Rillig, M. C., Harrison, S. P., Riviera, F., Morris, D., and Robert, E. M. R.

Abstract

Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives.

Published
2020

8. Using incomplete floristic monitoring data from habitat mapping programmes to detect species trends

Author

Bruelheide, H., Jansen, F., Jandt, U., Bernhardt-Römermann, M., Bonn, Aletta, Bowler, Diana, Dengler, J., Eichenberg, D., Grescho, Volker, Harter, D., Jugelt, M., Kellner, S., Ludwig, M., Wesche, K., Lütt, S., Bruelheide, H., Jansen, F., Jandt, U., Bernhardt-Römermann, M., Bonn, Aletta, Bowler, Diana, Dengler, J., Eichenberg, D., Grescho, Volker, Harter, D., Jugelt, M., Kellner, S., Ludwig, M., Wesche, K., and Lütt, S.

Abstract

Aim The loss of biodiversity has raised serious concerns about the entailing losses of ecosystem services. Here, we explore the potential of repeated habitat mapping data to identify floristic changes over time. Using one German federal state as a case study, we assessed floristic changes between the 1980s and 2010s. These habitat data have great potential for analysis because of their high spatial coverage while also posing methodological challenges such as incomplete observation data. We developed a modelling approach that accounts for incomplete observations and explored the ability to detect temporal trends. Location The Federal State of Schleswig‐Holstein (Germany) Methods We compiled plant species lists from the earliest (1980s) and most recent (2010s) habitat mapping survey and aligned differing habitat definitions across mapping campaigns. A total of 5,503 mapped polygons, each with a list of species records, intersected the two surveys. We accounted for underrecorded species by assigning occurrence probabilities, based on species co‐occurrence information across all surveys, using Beals' index and tested the robustness of this approach by simulation experiments. For those species with significant increases and decreases in occurrence probability, we linked these trends to the species' functional characteristics. Results We found a systematic loss of species that are moderately threatened. Species that indicate low nitrogen supply and high soil moisture declined, suggesting a shift towards a more eutrophic and drier landscape. Importantly, assessing specific plant traits associated with losses, we also detected a decrease in species with reddish and blueish flowers and species providing nectar, pointing to a decrease of insect‐pollinated taxa. Main conclusions The identified changes raise concerns that plant biodiversity has fundamentally changed over the last three decades, with concomitant consequences for ecosystem services, especially pollination. Given

Published
2020

9. Testing macroecological abundance patterns: The relationship between local abundance and range size, range position and climatic suitability among European vascular plants

Author

Sporbert, M., Keil, P., Seidler, G., Bruelheide, H., Jandt, U., Aćić, S., Biurrun, I., Campos, J.A., Čarni, A., Chytrý, M., Ćušterevska, R., Dengler, J., Golub, V., Jansen, F., Kuzemko, A., Lenoir, J., Marcenò, C., Moeslund, J.E., Pérez‐Haase, A., Rūsiņa, S., Šilc, U., Tsiripidris, I., Vandvik, V., Vasilev, K., Virtanen, Risto, Welk, E., Sporbert, M., Keil, P., Seidler, G., Bruelheide, H., Jandt, U., Aćić, S., Biurrun, I., Campos, J.A., Čarni, A., Chytrý, M., Ćušterevska, R., Dengler, J., Golub, V., Jansen, F., Kuzemko, A., Lenoir, J., Marcenò, C., Moeslund, J.E., Pérez‐Haase, A., Rūsiņa, S., Šilc, U., Tsiripidris, I., Vandvik, V., Vasilev, K., Virtanen, Risto, and Welk, E.

Abstract

Aim A fundamental question in macroecology centres around understanding the relationship between species’ local abundance and their distribution in geographical and climatic space (i.e. the multi‐dimensional climatic space or climatic niche). Here, we tested three macroecological hypotheses that link local abundance to the following range properties: (a) the abundance–range size relationship, (b) the abundance–range centre relationship and (c) the abundance–suitability relationship. Location Europe. Taxon Vascular plants. Methods Distribution range maps were extracted from the Chorological Database Halle to derive information on the range and niche sizes of 517 European vascular plant species. To estimate local abundance, we assessed samples from 744,513 vegetation plots in the European Vegetation Archive, where local species’ abundance is available as plant cover per plot. We then calculated the ‘centrality’, that is, the distance between the location of the abundance observation and each species’ range centre in geographical and climatic space. The climatic suitability of plot locations was estimated using coarse‐grain species distribution models (SDMs). The relationships between centrality or climatic suitability with abundance was tested using linear models and quantile regression. We summarized the overall trend across species’ regression slopes from linear models and quantile regression using a meta‐analytical approach. Results We did not detect any positive relationships between a species’ mean local abundance and the size of its geographical range or climatic niche. Contrasting yet significant correlations were detected between abundance and centrality or climatic suitability among species. Main conclusions Our results do not provide unequivocal support for any of the relationships tested, demonstrating that determining properties of species’ distributions at large grains and extents might be of limited use for predicting local abundance, including current S

Published
2020

10. Widespread decline in Central European plant diversity across six decades

Author

Eichenberg, David, Bowler, Diana, Bonn, Aletta, Bruelheide, H., Grescho, Volker, Harter, D., Jandt, U., May, R., Winter, M., Jansen, F., Eichenberg, David, Bowler, Diana, Bonn, Aletta, Bruelheide, H., Grescho, Volker, Harter, D., Jandt, U., May, R., Winter, M., and Jansen, F.

Abstract

Based on plant occurrence data covering all parts of Germany, we investigated changes in the distribution of 2136 plant species between 1960 and 2017. We analyzed 29 million occurrence records over an area of ~350,000 km2 on a 5 × 5 km grid using temporal and spatiotemporal models and accounting for sampling bias. Since the 1960s, more than 70% of investigated plant species showed declines in nationwide occurrence. Archaeophytes (species introduced before 1492) most strongly declined but also native plant species experienced severe declines. In contrast, neophytes (species introduced after 1492) increased in their nationwide occurrence but not homogeneously throughout the country. Our analysis suggests that the strongest declines in native species already happened in the 1960s–1980s, a time frame in which often few data exist. Increases in neophytic species were strongest in the 1990s and 2010s. Overall, the increase in neophytes did not compensate for the loss of other species, resulting in a decrease in mean grid cell species richness of −1.9% per decade. The decline in plant biodiversity is a widespread phenomenon occurring in different habitats and geographic regions. It is likely that this decline has major repercussions on ecosystem functioning and overall biodiversity, potentially with cascading effects across trophic levels. The approach used in this study is transferable to other large‐scale trend analyses using heterogeneous occurrence data.

Published
2020

12. Assessing sampling coverage of species distribution in biodiversity databases

Author

Sporbert, M., Bruelheide, H., Seidler, G., Keil, P., Jandt, U., Austrheim, G., Biurrun, I., Campos, J.A., Carni, A., Chytry, M., Csiky, J., De Bie, E., Dengler, Jürgen, Sporbert, M., Bruelheide, H., Seidler, G., Keil, P., Jandt, U., Austrheim, G., Biurrun, I., Campos, J.A., Carni, A., Chytry, M., Csiky, J., De Bie, E., and Dengler, Jürgen

Abstract

Aim: Biodiversity databases are valuable resources for understanding plant species distributions and dynamics, but they may insufficiently represent the actual geographic distribution and climatic niches of species. Here we propose and test a method to assess sampling coverage of species distribution in biodiversity databases in geographic and climatic space. Location: Europe. Methods: Using a test selection of 808,794 vegetation plots from the European Vegetation Archive (EVA), we assessed the sampling coverage of 564 European vascular plant species across both their geographic ranges and realized climatic niches. Range maps from the Chorological Database Halle (CDH) were used as background reference data to capture species geographic ranges and to derive species climatic niches. To quantify sampling coverage, we developed a box‐counting method, the Dynamic Match Coefficient (DMC), which quantifies how much a set of occurrences of a given species matches with its geographic range or climatic niche. DMC is the area under the curve measuring the match between occurrence data and background reference (geographic range or climatic niche) across grids with variable resolution. High DMC values indicate good sampling coverage. We applied null models to compare observed DMC values with expectations from random distributions across species ranges and niches. Results: Comparisons with null models showed that, for most species, actual distributions within EVA are deviating from null model expectations and are more clumped than expected in both geographic and climatic space. Despite high interspecific variation, we found a positive relationship in DMC values between geographic and climatic space, but sampling coverage was in general more random across geographic space. Conclusion: Because DMC values are species‐specific and most biodiversity databases are clearly biased in terms of sampling coverage of species occurrences, we recommend using DMC values as covariates in macroec

Published
2019

13. Similar factors underlie tree abundance in forests in native and alien ranges

Author

van der Sande, Masha Tamara, Bruelheide, H., Dawson, W., Dengler, J., Essl, F., Field, R., Haider, S., van Kleunen, M., Kreft, H., Pagel, J., Pergl, J., Purschke, O., Pyšek, P., Weigelt, P., Winter, M., Attorre, F., Aubin, I., Bergmeier, E., Chytrý, M., Dainese, M., De Sanctis, M., Fagundez, J., Golub, V., Guerin, G.R., Gutiérrez, A.G., Jandt, U., Jansen, F., Jiménez‐Alfaro, B., Kattge, J., Kearsley, E., Klotz, Stefan, Kramer, K., Moretti, M., Niinemets, Ü., Peet, R.K., Penuelas, J., Petřík, P., Reich, P.B., Sandel, B., Schmidt, M., Sibikova, M., Violle, C., Whitfeld, T.J.S., Wohlgemuth, T., Knight, Tiffany, van der Sande, Masha Tamara, Bruelheide, H., Dawson, W., Dengler, J., Essl, F., Field, R., Haider, S., van Kleunen, M., Kreft, H., Pagel, J., Pergl, J., Purschke, O., Pyšek, P., Weigelt, P., Winter, M., Attorre, F., Aubin, I., Bergmeier, E., Chytrý, M., Dainese, M., De Sanctis, M., Fagundez, J., Golub, V., Guerin, G.R., Gutiérrez, A.G., Jandt, U., Jansen, F., Jiménez‐Alfaro, B., Kattge, J., Kearsley, E., Klotz, Stefan, Kramer, K., Moretti, M., Niinemets, Ü., Peet, R.K., Penuelas, J., Petřík, P., Reich, P.B., Sandel, B., Schmidt, M., Sibikova, M., Violle, C., Whitfeld, T.J.S., Wohlgemuth, T., and Knight, Tiffany

Abstract

AimAlien plant species can cause severe ecological and economic problems, and therefore attract a lot of research interest in biogeography and related fields. To identify potential future invasive species, we need to better understand the mechanisms underlying the abundances of invasive tree species in their new ranges, and whether these mechanisms differ between their native and alien ranges. Here, we test two hypotheses: that greater relative abundance is promoted by (a) functional difference from locally co‐occurring trees, and (b) higher values than locally co‐occurring trees for traits linked to competitive ability. LocationGlobal. Time periodRecent. Major taxa studiedTrees. MethodsWe combined three global plant databases: sPlot vegetation‐plot database, TRY plant trait database and Global Naturalized Alien Flora (GloNAF) database. We used a hierarchical Bayesian linear regression model to assess the factors associated with variation in local abundance, and how these relationships vary between native and alien ranges and depend on species’ traits. ResultsIn both ranges, species reach highest abundance if they are functionally similar to co‐occurring species, yet are taller and have higher seed mass and wood density than co‐occurring species. Main conclusionsOur results suggest that light limitation leads to strong environmental and biotic filtering, and that it is advantageous to be taller and have denser wood. The striking similarities in abundance between native and alien ranges imply that information from tree species’ native ranges can be used to predict in which habitats introduced species may become dominant.

Published
2019

14. sPlot – a new tool for global vegetation analyses

Author

Bruelheide, H., Dengler, J., Jiménez‐Alfaro, B., Purschke, O., Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R.K., Peyre, G., Sabatini, F.M., Schmidt, M., Schrodt, F., Winter, M., Aćić, S., Agrillo, E., Alvarez, M., Ambarlı, D., Angelini, P., Apostolova, I., Khan, M.A.S.A., Arnst, E., Attorre, F., Baraloto, C., Beckmann, Michael, Kühn, Ingolf, Virtanen, Risto, Berg, C., et al., Bruelheide, H., Dengler, J., Jiménez‐Alfaro, B., Purschke, O., Hennekens, S.M., Chytrý, M., Pillar, V.D., Jansen, F., Kattge, J., Sandel, B., Aubin, I., Biurrun, I., Field, R., Haider, S., Jandt, U., Lenoir, J., Peet, R.K., Peyre, G., Sabatini, F.M., Schmidt, M., Schrodt, F., Winter, M., Aćić, S., Agrillo, E., Alvarez, M., Ambarlı, D., Angelini, P., Apostolova, I., Khan, M.A.S.A., Arnst, E., Attorre, F., Baraloto, C., Beckmann, Michael, Kühn, Ingolf, Virtanen, Risto, and Berg, C., et al.

Abstract

QuestionsVegetation‐plot records provide information on 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. LocationsPlot 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 between 1885 and 2015. MethodsWe 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. ResultsWe present the first maps of global patterns of community richness and community‐weighted means of key traits. ConclusionsThe availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

Published
2019

21. Global patterns and drivers of alpine plant species richness

Author

Andreas Hemp, Jonathan Lenoir, Evgeny G. Zibzeev, Steven P. Sylvester, N. I. Makunina, Michele De Sanctis, Risto Virtanen, Robert F. Brand, Wolfgang Willner, Arkadiusz Nowak, Ute Jandt, Riccardo Testolin, Francesco Maria Sabatini, Sylvia Haider, George P. Malanson, Susan K. Wiser, Gwendolyn Peyre, Kiril Vassilev, Milan Chytrý, Fabio Attorre, Borja Jiménez-Alfaro, Petr Sklenář, Jalil Noroozi, Manfred Finckh, Andrey Yu. Korolyuk, Peter Borchardt, Daniel B. Montesinos-Tubée, Helge Bruelheide, Robert K. Peet, Jozef Šibík, Jiri Dolezal, Michael Kessler, Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Centre National de la Recherche Scientifique (CNRS)-Université de Picardie Jules Verne (UPJV), Testolin R., Attorre F., Borchardt P., Brand R.F., Bruelheide H., Chytry M., De Sanctis M., Dolezal J., Finckh M., Haider S., Hemp A., Jandt U., Kessler M., Korolyuk A.Y., Lenoir J., Makunina N., Malanson G.P., Montesinos-Tubee D.B., Noroozi J., Nowak A., Peet R.K., Peyre G., Sabatini F.M., Sibik J., Sklenar P., Sylvester S.P., Vassilev K., Virtanen R., Willner W., Wiser S.K., Zibzeev E.G., and Jimenez-Alfaro B.

Subjects
0106 biological sciences, biodiversity hotspot, 010504 meteorology & atmospheric sciences, Alpine plant, global pattern, [SDE.MCG]Environmental Sciences/Global Changes, [SDV.BID]Life Sciences [q-bio]/Biodiversity, biogeographical history, 010603 evolutionary biology, 01 natural sciences, plant species richness, Temperate climate, global patterns, Alpine vegetation, biodiversity hotspots, multiscale analysis, Ecosystem, Ecology, Evolution, Behavior and Systematics, 0105 earth and related environmental sciences, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Global and Planetary Change, Ecology, multiscale analysi, Vegetation, 15. Life on land, Biodiversity hotspot, Taxon, Geography, Rarefaction (ecology), Species richness, [SDE.BE]Environmental Sciences/Biodiversity and Ecology
Abstract

B.J.-A. was funded by the Marie Curie Clarín-COFUND program of the Principality of Asturias-EU (ACB17-26) and the Spanish Research Agency (AEI/10.13039/501100011033)., Testolin, R., Attorre, F., Borchardt, P., Brand, R.F., Bruelheide, H., Chytrý, M., De Sanctis, M., Dolezal, J., Finckh, M., Haider, S., Hemp, A., Jandt, U., Kessler, M., Korolyuk, A.Y., Lenoir, J., Makunina, N., Malanson, G.P., Montesinos-Tubée, D.B., Noroozi, J., Nowak, A., Peet, R.K., Peyre, G., Sabatini, F.M., Šibík, J., Sklenář, P., Sylvester, S.P., Vassilev, K., Virtanen, R., Willner, W., Wiser, S.K., Zibzeev, E.G., Jiménez-Alfaro, B.

Published
2021

22. The relationship between niche breadth and range size of beech (Fagus) species worldwide

Author

Cindy Q. Tang, Andraž Čarni, Jianxiao Zhu, Wenjing Fang, Francesco Maria Sabatini, Hamid Gholizadeh, Wolfgang Willner, Zhiyao Tang, Jens-Christian Svenning, Robert K. Peet, Franziska Schrodt, Adrian Indreica, Chengjun Ji, Remigiusz Pielech, Jonathan Lenoir, Süleyman Çoban, Jiangling Zhu, Dirk Nikolaus Karger, József Pál Frink, Jingyun Fang, Richard Field, Kubota Yasuhiro, Juan Antonio Campos, Jiri Dolezal, Erik Welk, Qiong Cai, Michele De Sanctis, Helge Bruelheide, Ioannis Tsiripidis, Milan Chytrý, Ute Jandt, Fabio Attorre, Jürgen Dengler, Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), Cai Q., Welk E., Ji C., Fang W., Sabatini F.M., Zhu J., Tang Z., Attorre F., Campos J.A., Carni A., Chytry M., Coban S., Dengler J., Dolezal J., Field R., Frink J.P., Gholizadeh H., Indreica A., Jandt U., Karger D.N., Lenoir J., Peet R.K., Pielech R., De Sanctis M., Schrodt F., Svenning J.-C., Tang C.Q., Tsiripidis I., Willner W., Yasuhiro K., Fang J., and Bruelheide H.

Subjects
0106 biological sciences, Range (biology), [SDE.MCG]Environmental Sciences/Global Changes, Niche, niche evolution, [SDV.BID]Life Sciences [q-bio]/Biodiversity, 010603 evolutionary biology, 01 natural sciences, co-occurrence data, niche breadth, Fagus, geographical range size, Beech, Ecology, Evolution, Behavior and Systematics, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Fagu, climatic niche, deciduous species, Fagus, geographical range size, phylogenetic signal, temperate forest flora, vegetation-plot data, Ecology, biology, Phylogenetic tree, Vegetation, 15. Life on land, biology.organism_classification, Deciduous, Taxon, 580: Pflanzen (Botanik), deciduous specie, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Temperate rainforest, 010606 plant biology & botany
Abstract

Aim: This work explores whether the commonly observed positive range size-niche breadth relationship exists for Fagus, one of the most dominant and widespread broad-leaved deciduous tree genera in temperate forests of the Northern Hemisphere. Additionally, we ask whether the 10 extant Fagus species' niche breadths and climatic tolerances are under phylogenetic control. Location: Northern Hemisphere temperate forests. Taxon: Fagus L. Methods: Combining the global vegetation database sPlot with Chinese vegetation data, we extracted 107,758 releves containing Fagus species. We estimated biotic and climatic niche breadths per species using plot-based co-occurrence data and a resource-based approach, respectively. We examined the relationships of these estimates with range size and tested for their phylogenetic signal, prior to which a Random Forest (RF) analysis was applied to test which climatic properties are most conserved across the Fagus species. Results: Neither biotic niche breadth nor climatic niche breadth was correlated with range size, and the two niche breadths were incongruent as well. Notably, the widespread North American F. grandifolia had a distinctly smaller biotic niche breadth than the Chinese Fagus species (F. engleriana, F. hayatae, F. longipetiolata and F. lucida) with restricted distributions in isolated mountains. The RF analysis revealed that cold tolerance did not differ among the 10 species, and thus may represent an ancestral, fixed trait. In addition, neither biotic nor climatic niche breadths are under phylogenetic control. Main Conclusions: We interpret the lack of a general positive range size-niche breadth relationship within the genus Fagus as a result of the widespread distribution, high among-region variation in available niche space, landscape heterogeneity and Quaternary history. The results hold when estimating niche sizes either by fine-scale co-occurrence data or coarse-scale climate data, suggesting a mechanistic link between factors operating across spatial scales. Besides, there was no evidence for diverging ecological specialization within the genus Fagus. National Natural Science Foundation of ChinaNational Natural Science Foundation of China (NSFC); Ministry of Science and Technology of ChinaMinistry of Science and Technology, China; National Key Research and Development Program of China; Grantova Agentura Ceske RepublikyGrant Agency of the Czech Republic; Chinese Scholarship CouncilChina Scholarship Council; Independent Research Fund Denmark; Villum Fonden; German Research FoundationGerman Research Foundation (DFG); Ministry of Education, Youth and Sport of the Czech Republic, program Inter-Excellence; Natural Sciences project TREECHANGE National Natural Science Foundation of China; Ministry of Science and Technology of China; National Key Research and Development Program of China; Grantova Agentura Ceske Republiky; Chinese Scholarship Council; Independent Research Fund Denmark; Natural Sciences project TREECHANGE; Villum Fonden; German Research Foundation; Ministry of Education, Youth and Sport of the Czech Republic, program Inter-Excellence

Published
2021

23. Revealing the functional traits linked to hidden environmental factors in community assembly

Author

Valério D. Pillar, Francesco Maria Sabatini, Ute Jandt, Sergio Camiz, Helge Bruelheide, Pillar V.D., Sabatini F.M., Jandt U., Camiz S., and Bruelheide H.

Subjects
Beals smoothing, fuzzy-weighting, Ecology, business.industry, environmental filtering, Plant Science, Data science, Text mining, Geography, species traits, species co-occurrence, community assembly, hidden environmental factor, business
Abstract

Aim: To identify functional traits that best predict community assembly without knowing the underlying environmental drivers. Methods: We propose a new method based on the correlation r(XY) between two matrices of potential community composition: the matrix X is fuzzy-weighted by trait similarities of species, and the matrix Y is derived by Beals smoothing using the probabilities of species co-occurrences. Since X is based on one or more traits, r(XY) measures how well the traits used for fuzzy-weighting reflect the species co-occurrence patterns in Y. We developed an optimisation algorithm to identify the traits maximising this correlation, together with an appropriate permutational test for significance. Using metacommunity data generated by a stochastic, individual-based, spatially explicit model, we assessed the type I error and the power of our method across different simulation scenarios, varying environmental filtering parameters, number of traits and trait correlation structures. Then, we applied the method to real-world community and trait data of dry calcareous grassland communities across Germany to identify, out of 49 traits, the combination of traits that maximised r(XY). Results: The method correctly identified the relevant traits involved in the assembly mechanisms of simulated communities, showing high power and accurate type I error. It proved to be robust against confounding aspects related to interactions between environmental factors, strength of limiting factors, and trait collinearity. In the grassland dataset, the method identified five traits that best explained community assembly. These traits reflect the size and the leaf economics spectrum, which are related to succession and resource supply, factors that may not be always measured in real-world situations. Conclusions: Our method successfully identified the relevant traits mediating community assembly, therefore providing insights on the underlying environmental and biotic factors, even if these are hidden, unmeasured or not accessible at the spatial or temporal scale of the study.

Published
2021

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

Author

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

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

Biurrun, Idoia/0000-0002-1454-0433; Rojo, Maria Pilar Rodriguez/0000-0001-5449-9386; Ermakov, Nikolai/0000-0001-7550-990X; De Sanctis, Michele/0000-0002-7280-6199; Svenning, Jens-Christian/0000-0002-3415-0862; Virtanen, Risto/0000-0002-8295-8217; Agrillo, Emiliano/0000-0003-2346-8346; Onyshchenko, Viktor/0000-0001-9079-7241; Marceno, Corrado/0000-0003-4361-5200; Willner, Wolfgang/0000-0003-1591-8386; Fernandez-Gonzalez, Federico/0000-0003-1234-4065; Jansen, Florian/0000-0002-0331-5185; Swacha, Grzegorz/0000-0002-6380-2954; Dengler, Jurgen/0000-0003-3221-660X; Guarino, Riccardo/0000-0003-0106-9416; Sopotlieva, Desislava/0000-0002-9281-7039; Venanzoni, Roberto/0000-0002-7768-0468; Chytry, Milan/0000-0002-8122-3075; Kuzemko, Anna/0000-0002-9425-2756; Danihelka, Jiri/0000-0002-2640-7867; Kuzemko, Anna/0000-0002-9425-2756; Venanzoni, Roberto/0000-0002-7768-0468; Gavilan, Rosario G./0000-0002-1022-445X; Jansen, Florian/0000-0002-0331-5185; Wohlgemuth, Thomas/0000-0002-4623-0894; Svenning, Jens-Christian/0000-0002-3415-0862; Sibik, Jozef/0000-0002-5949-862X; Casella, Laura/0000-0003-2550-3010; Lenoir, Jonathan/0000-0003-0638-9582; Attorre, Fabio/0000-0002-7744-2195; Kacki, Zygmunt/0000-0002-2241-1631; Jandt, Ute/0000-0002-3177-3669; Carni, Andraz/0000-0002-8909-4298; Jirousek, Martin/0000-0002-4293-478X; GARCIA-MIJANGOS, ITZIAR/0000-0002-6642-7782; Campos, Juan Antonio/0000-0001-5992-2753; Fanelli, Giuliano/0000-0002-3143-1212; Haveman, Rense/0000-0001-9127-4549; Acic, Svetlana/0000-0001-6553-3797; De Bie, Els/0000-0001-7679-743X; Font, Xavier/0000-0002-7253-8905; Moeslund, Jesper Erenskjold/0000-0001-8591-7149; Martynenko, Vasiliy/0000-0002-9071-3789; Jimenez-Alfaro, Borja/0000-0001-6601-9597; Ejrnaes, Rasmus/0000-0003-2538-8606; Carlon Ruiz, Luis/0000-0003-3442-8710; Angelini, Pierangela/0000-0002-5321-9757; Silc, Urban/0000-0002-3052-699X; Landucci, Flavia/0000-0002-6848-0384; Ewald, Jorg/0000-0002-2758-9324; Dziuba, Tetiana/0000-0001-8621-0890 WOS: 000368074600018 The European Vegetation Archive (EVA) is a centralized database of European vegetation plots developed by the IAVS Working Group European Vegetation Survey. It has been in development since 2012 and first made available for use in research projects in 2014. It stores copies of national and regional vegetation-plot databases on a single software platform. Data storage in EVA does not affect on-going independent development of the contributing databases, which remain the property of the data contributors. EVA uses a prototype of the database management software TURBOVEG 3 developed for joint management of multiple databases that use different species lists. This is facilitated by the SynBioSys Taxon Database, a system of taxon names and concepts used in the individual European databases and their corresponding names on a unified list of European flora. TURBOVEG 3 also includes procedures for handling data requests, selections and provisions according to the approved EVA Data Property and Governance Rules. By 30 June 2015, 61 databases from all European regions have joined EVA, contributing in total 1 027 376 vegetation plots, 82% of them with geographic coordinates, from 57 countries. EVA provides a unique data source for large-scale analyses of European vegetation diversity both for fundamental research and nature conservation applications. Updated information on EVA is available online at http://euroveg.org/eva-database. Czech Science Foundation (Centre of Excellence PLADIAS) [14-36079G] Our major thanks go to thousands of European vegetation scientists of several generations who collected the original vegetation-plot data in the field, published them or made their unpublished data available to others, and to those who spent myriad hours digitizing data and managing the contributing databases. EVA data management has been partly funded by the Czech Science Foundation (Centre of Excellence PLADIAS, 14-36079G).

Published
2016

25. Process-induced cell cycle oscillations in CHO cultures: Online monitoring and model-based investigation.

Author

Möller J, Bhat K, Riecken K, Pörtner R, Zeng AP, and Jandt U

Subjects
Animals, CHO Cells, Cricetinae, Cricetulus, Biological Clocks, Cell Cycle, Models, Biological
Abstract

The influence of process strategies on the dynamics of cell population heterogeneities in mammalian cell culture is still not well understood. We recently found that the progression of cells through the cell cycle causes metabolic regulations with variable productivities in antibody-producing Chimese hamster ovary (CHO) cells. On the other hand, it is so far unknown how bulk cultivation conditions, for example, variable nutrient concentrations depending on process strategies, can influence cell cycle-derived population dynamics. In this study, process-induced cell cycle synchronization was assessed in repeated-batch and fed-batch cultures. An automated flow cytometry set-up was developed to measure the cell cycle distribution online, using antibody-producing CHO DP-12 cells transduced with the cell cycle-specific fluorescent ubiquitination-based cell cycle indicator (FUCCI) system. On the basis of the population-resolved model, feeding-induced partial self-synchronization was predicted and the results were evaluated experimentally. In the repeated-batch culture, stable cell cycle oscillations were confirmed with an oscillating G1 phase distribution between 41% and 72%. Furthermore, oscillations of the cell cycle distribution were simulated and determined in a (bolus) fed-batch process with up to 25 × 1 0 6 cells/ml. The cell cycle synchronization arose with pulse feeding only and ceased with continuous feeding. Both simulated and observed oscillations occurred at higher frequencies than those observable based on regular (e.g., daily) sample analysis, thus demonstrating the need for high-frequency online cell cycle analysis. In summary, we showed how experimental methods combined with simulations enable the improved assessment of the effects of process strategies on the dynamics of cell cycle-dependent population heterogeneities. This provides a novel approach to understand cell cycle regulations, control cell population dynamics, avoid inadvertently induced oscillations of cell cycle distributions and thus to improve process stability and efficiency., (© 2019 The Authors. Biotechnology and Bioengineering published by Wiley Periodicals, Inc.)

Published
2019
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26. Model-based identification of cell-cycle-dependent metabolism and putative autocrine effects in antibody producing CHO cell culture.

Author

Möller J, Korte K, Pörtner R, Zeng AP, and Jandt U

Subjects
Ammonium Compounds metabolism, Animals, Batch Cell Culture Techniques, CHO Cells, Cell Proliferation physiology, Cricetinae, Cricetulus, Lactic Acid metabolism, Antibodies metabolism, Autocrine Communication physiology, Cell Cycle physiology, Models, Biological, Recombinant Proteins metabolism
Abstract

The understanding of cell-cycle-dependent population heterogeneities in mammalian cell culture and their influence on production rates is still limited. Furthermore, metabolic regulations arising from self-expressed signaling factors (autocrine/autoinhibitory factors) have been postulated in the past, but no determination of such effects have been made so far for fast-growing production Chinese hamster ovary (CHO) cells in chemically defined media. In this study, a novel approach combining near-physiological treatment of cells (including synchronization), population resolved mechanistic modeling and statistical analysis was developed to identify population inhomogeneities. Cell-cycle-dependent population dynamics and metabolic regulations due to a putative autocrine factor were examined and their impact on the metabolic rates and antibody production of near-physiologically synchronized CHO DP-12 cell cultures was determined. To achieve this, a population resolved model was extended to describe putative autocrine-dependentt and cell-cycle-related metabolic rates for glucose, glutamine, lactate, ammonia, and antibody production. The model parameters were estimated based on data of two repeated batch cultivations (three batches each), with main substrates in excess and potentially inhibiting waste products (lactate and ammonium) controlled within narrow ranges. Significant changes, due to a putative autocrine factor, were identified for lactate and ammonia formation and antibody production. The cell growth and the uptake of glucose and glutamine were only partially affected by the putative autocrine under the given conditions. The results indicate the presence of a self-expressed autocrine factor and its strong impact on the metabolism of CHO DP-12 cells. Furthermore, glucose and glutamine uptake, as well as the formation of ammonium and antibody were found to be significantly cell-cycle-dependent. The combined approach has a strong potential to improve the understanding of the interplay of population heterogeneities and signal factors in mammalian cell culture., (© 2018 Wiley Periodicals, Inc.)

Published
2018
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27. Spatiotemporal modeling and analysis of transient gene delivery.

Author

Jandt U, Shao S, Wirth M, and Zeng AP

Subjects
Cell Nucleus genetics, DNA Replication genetics, HEK293 Cells, Humans, Microscopy, Confocal, Microtubule-Organizing Center physiology, Microtubules genetics, Plasmids administration & dosage, Plasmids genetics, Polymerase Chain Reaction, Systems Biology, Algorithms, Gene Expression physiology, Gene Transfer Techniques, Models, Biological, Transfection methods
Abstract

A quantitative and mechanistic understanding of intracellular transport processes in eukaryotic cells during transient transfection is an important prerequisite for the systematic and specific optimization of transient gene expression procedures for pharmaceutic and industrial protein production. There is evidence that intracellular transport processes during gene delivery and their regulation may have significant influence on the transfection efficiency. This contribution describes a compartmented, spatiotemporally resolved and stochastic modeling approach that describes intracellular transport processes responsible for gene delivery during transient transfection. It enables a detailed prediction and analysis and identification of potential bottlenecks. This model is currently being adapted to a model cell line, HEK293s. The simulated results are compared with experimental quantitative polymerase chain reaction (qPCR) data and confocal imaging data obtained with transfected and stained HEK293 cells. Global parameter estimation is performed to qPCR data based on two different novel plasmid constructs in order to identify candidates for plasmid-specific transport parameter variations. The influence of the specific property of HEK293 cells to grow in clusters is investigated and the impact of active microtubule transport depending on cell morphology and clustering is examined. A general sensitivity analysis allows for the identification of the sensitive parameters., (Copyright © 2011 Wiley Periodicals, Inc.)

Published
2011
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