Author: "Purschke O" - Searchworks@Jio Institute Digital Library Search Results

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1. Common symptoms and post-COVID associated symptoms in Germany - results from the NAKO study

Author: Diexer, S, Purschke, O, Fricke, J, Ahnert, P, Gabrysch, S, Gottschick, C, Bohn, B, Brenner, H, Buck, C, Castell, S, Gastell, S, Greiser, KH, Harth, V, Heise, JK, Holleczek, B, Kaaks, R, Krist, L, Leitzmann, MF, Meinke-Franze, C, Michels, KB, Moreno, I, Obi, N, Panreck, L, Peters, A, Pischon, T, Schikowski, T, Schmidt, B, Standl, M, Stang, A, Völzke, H, Weber, A, Zeeb, H, Karch, A, Mikolajczyk, R, Diexer, S, Purschke, O, Fricke, J, Ahnert, P, Gabrysch, S, Gottschick, C, Bohn, B, Brenner, H, Buck, C, Castell, S, Gastell, S, Greiser, KH, Harth, V, Heise, JK, Holleczek, B, Kaaks, R, Krist, L, Leitzmann, MF, Meinke-Franze, C, Michels, KB, Moreno, I, Obi, N, Panreck, L, Peters, A, Pischon, T, Schikowski, T, Schmidt, B, Standl, M, Stang, A, Völzke, H, Weber, A, Zeeb, H, Karch, A, and Mikolajczyk, R
Published: 2024

2. Psychosocial stress across times of crises: Results from the population-based German National Cohort study

Author: Costa, D, Kluttig, A, Massag, J, Purschke, O, Mikolajczyk, R, Costa, D, Kluttig, A, Massag, J, Purschke, O, and Mikolajczyk, R
Published: 2024

3. Self-reported complaints and utilization of therapeutic services: Insights from the DigiHero Post-COVID Registry

Author: Pfrommer, L, Frost, J, Diexer, S, Klee, B, Massag, J, Gottschick, C, Purschke, O, Binder, M, Frese, T, Girndt, M, Sedding, D, Rosendahl, J, Hoell, J, Moor, I, Gekle, M, Allwang, C, Junne, F, Mikolajczyk, R, Pfrommer, L, Frost, J, Diexer, S, Klee, B, Massag, J, Gottschick, C, Purschke, O, Binder, M, Frese, T, Girndt, M, Sedding, D, Rosendahl, J, Hoell, J, Moor, I, Gekle, M, Allwang, C, Junne, F, and Mikolajczyk, R
Published: 2024

4. Duration of non-hospitalized acute SARS-CoV-2 first infections with Omicron depending on previous vaccinations

Author: Glaser, N, Diexer, S, Klee, B, Purschke, O, Binder, M, Frese, T, Girndt, M, Hoell, J, Moor, I, Rosendahl, J, Gekle, M, Sedding, D, Gottschick, C, Mikolajczyk, R, Glaser, N, Diexer, S, Klee, B, Purschke, O, Binder, M, Frese, T, Girndt, M, Hoell, J, Moor, I, Rosendahl, J, Gekle, M, Sedding, D, Gottschick, C, and Mikolajczyk, R
Published: 2024

5. Associations between SARS-CoV-2 Infection, burden of the pandemic and mental health in the German population-based cohort for digital health research

Author: Steinmann, L.A., primary, Opel, N., additional, Massag, J., additional, Diexer, S., additional, Klee, B., additional, Costa, D., additional, Gottschick, C., additional, Broda, A., additional, Purschke, O., additional, Binder, M., additional, Sedding, D., additional, Frese, T., additional, Girndt, M., additional, Hoell, J., additional, Moor, I., additional, Rosendahl, J., additional, Gekle, M., additional, and Mikolajczyk, R., additional
Published: 2023
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6. Functional responses of plant communities to management, landscape and historical factors in semi-natural grasslands

Author: Vandewalle, M., Purschke, O., de Bello, F., Reitalu, T., Prentice, H.C., Lavorel, S., Johansson, L.J., and Sykes, M.T.
Published: 2014
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7. sPlotOpen – An environmentally balanced, open‐access, global dataset of vegetation plots

Author: Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., Bates, A., Sabatini, F.M., Lenoir, J., Hattab, T., Arnst, E., Chytrý, M., Dengler, J., De Ruffray, P., Hennekens, S.M., Jandt, U., Jansen, F., Jimenez‐Alfaro, B., Kattge, J., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Álvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El‐Sheikh, M.A.El‐R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán‐de‐Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J‐A, Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Penuelas, J., Pérez‐Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas‐Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J‐C, Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez‐Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H‐F, Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H., and Bates, A.
Abstract: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring.
Published: 2021

8. sPlotOpen:an environmentally balanced, open-access, global dataset of vegetation plots

Author: Sabatini, F. M. (Francesco Maria), Lenoir, J. (Jonathan), Hattab, T. (Tarek), Arnst, E. A. (Elise Aimee), Chytry, M. (Milan), Dengler, J. (Juergen), De Ruffray, P. (Patrice), Hennekens, S. M. (Stephan M.), Jandt, U. (Ute), Jansen, F. (Florian), Jimenez-Alfaro, B. (Borja), Kattge, J. (Jens), Levesley, A. (Aurora), Pillar, V. D. (Valerio D.), Purschke, O. (Oliver), Sandel, B. (Brody), Sultana, F. (Fahmida), Aavik, T. (Tsipe), Acic, S. (Svetlana), Acosta, A. T. (Alicia T. R.), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Apostolova, I. (Iva), Arfin Khan, M. A. (Mohammed A. S.), Arroyo, L. (Luzmila), Attorre, F. (Fabio), Aubin, I. (Isabelle), Banerjee, A. (Arindam), Bauters, M. (Marijn), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Bonari, G. (Gianmaria), Bondareva, V. (Viktoria), Brunet, J. (Jorg), Carni, A. (Andraz), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Custerevska, R. (Renata), De Bie, E. (Els), de Gasper, A. L. (Andre Luis), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dolezal, J. (Jiri), Dziuba, T. (Tetiana), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fazayeli, F. (Farideh), Field, R. (Richard), Finckh, M. (Manfred), Gachet, S. (Sophie), Galan-de-Mera, A. (Antonio), Garbolino, E. (Emmanuel), Gholizadeh, H. (Hamid), Giorgis, M. (Melisa), Golub, V. (Valentin), Alsos, I. G. (Inger Greve), Grytnes, J.-A. (John-Arvid), Guerin, G. R. (Gregory Richard), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hatim, M. Z. (Mohamed Z.), Herault, B. (Bruno), Hinojos Mendoza, G. (Guillermo), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Hubau, W. (Wannes), Indreica, A. (Adrian), Janssen, J. A. (John A. M.), Jedrzejek, B. (Birgit), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kapfer, J. (Jutta), Karger, D. N. (Dirk Nikolaus), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Khanina, L. (Larisa), Killeen, T. (Timothy), Korolyuk, A. (Andrey), Kreft, H. (Holger), Kuehl, H. S. (Hjalmar S.), Kuzemko, A. (Anna), Landucci, F. (Flavia), Lengyel, A. (Attila), Lens, F. (Frederic), Lingner, D. V. (Debora Vanessa), Liu, H. (Hongyan), Lysenko, T. (Tatiana), Mahecha, M. D. (Miguel D.), Marceno, C. (Corrado), Martynenko, V. (Vasiliy), Moeslund, J. E. (Jesper Erenskjold), Monteagudo Mendoza, A. (Abel), Mucina, L. (Ladislav), Muller, J. V. (Jonas V.), Munzinger, J. (Jerome), Naqinezhad, A. (Alireza), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Partel, M. (Meelis), Pauchard, A. (Anibal), Peet, R. K. (Robert K.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Peyre, G. (Gwendolyn), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rivas-Torres, G. (Gonzalo), Rodwell, J. S. (John S.), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schmidt, M. (Marco), Schrodt, F. (Franziska), Shan, H. (Hanhuai), Shirokikh, P. (Pavel), Sibik, J. (Jozef), Silc, U. (Urban), Sklenar, P. (Petr), Skvorc, Z. (Zeljko), Sparrow, B. (Ben), Sperandii, M. G. (Marta Gaia), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Tang, C. Q. (Cindy Q.), Tsiripidis, I. (Ioannis), Vanselow, K. A. (Kim Andre), Vasquez Martinez, R. (Rodolfo), Vassilev, K. (Kiril), Velez-Martin, E. (Eduardo), Venanzoni, R. (Roberto), Vibrans, A. C. (Alexander Christian), Violle, C. (Cyrille), Virtanen, R. (Risto), von Wehrden, H. (Henrik), Wagner, V. (Viktoria), Walker, D. A. (Donald A.), Waller, D. M. (Donald M.), Wang, H.-F. (Hua-Feng), Wesche, K. (Karsten), Whitfeld, T. J. (Timothy J. S.), Willner, W. (Wolfgang), Wiser, S. K. (Susan K.), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zobel, M. (Martin), Bruelheide, H. (Helge), Sabatini, F. M. (Francesco Maria), Lenoir, J. (Jonathan), Hattab, T. (Tarek), Arnst, E. A. (Elise Aimee), Chytry, M. (Milan), Dengler, J. (Juergen), De Ruffray, P. (Patrice), Hennekens, S. M. (Stephan M.), Jandt, U. (Ute), Jansen, F. (Florian), Jimenez-Alfaro, B. (Borja), Kattge, J. (Jens), Levesley, A. (Aurora), Pillar, V. D. (Valerio D.), Purschke, O. (Oliver), Sandel, B. (Brody), Sultana, F. (Fahmida), Aavik, T. (Tsipe), Acic, S. (Svetlana), Acosta, A. T. (Alicia T. R.), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Apostolova, I. (Iva), Arfin Khan, M. A. (Mohammed A. S.), Arroyo, L. (Luzmila), Attorre, F. (Fabio), Aubin, I. (Isabelle), Banerjee, A. (Arindam), Bauters, M. (Marijn), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Bonari, G. (Gianmaria), Bondareva, V. (Viktoria), Brunet, J. (Jorg), Carni, A. (Andraz), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Custerevska, R. (Renata), De Bie, E. (Els), de Gasper, A. L. (Andre Luis), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dolezal, J. (Jiri), Dziuba, T. (Tetiana), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fazayeli, F. (Farideh), Field, R. (Richard), Finckh, M. (Manfred), Gachet, S. (Sophie), Galan-de-Mera, A. (Antonio), Garbolino, E. (Emmanuel), Gholizadeh, H. (Hamid), Giorgis, M. (Melisa), Golub, V. (Valentin), Alsos, I. G. (Inger Greve), Grytnes, J.-A. (John-Arvid), Guerin, G. R. (Gregory Richard), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hatim, M. Z. (Mohamed Z.), Herault, B. (Bruno), Hinojos Mendoza, G. (Guillermo), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Hubau, W. (Wannes), Indreica, A. (Adrian), Janssen, J. A. (John A. M.), Jedrzejek, B. (Birgit), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kapfer, J. (Jutta), Karger, D. N. (Dirk Nikolaus), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Khanina, L. (Larisa), Killeen, T. (Timothy), Korolyuk, A. (Andrey), Kreft, H. (Holger), Kuehl, H. S. (Hjalmar S.), Kuzemko, A. (Anna), Landucci, F. (Flavia), Lengyel, A. (Attila), Lens, F. (Frederic), Lingner, D. V. (Debora Vanessa), Liu, H. (Hongyan), Lysenko, T. (Tatiana), Mahecha, M. D. (Miguel D.), Marceno, C. (Corrado), Martynenko, V. (Vasiliy), Moeslund, J. E. (Jesper Erenskjold), Monteagudo Mendoza, A. (Abel), Mucina, L. (Ladislav), Muller, J. V. (Jonas V.), Munzinger, J. (Jerome), Naqinezhad, A. (Alireza), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Partel, M. (Meelis), Pauchard, A. (Anibal), Peet, R. K. (Robert K.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Peyre, G. (Gwendolyn), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rivas-Torres, G. (Gonzalo), Rodwell, J. S. (John S.), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schmidt, M. (Marco), Schrodt, F. (Franziska), Shan, H. (Hanhuai), Shirokikh, P. (Pavel), Sibik, J. (Jozef), Silc, U. (Urban), Sklenar, P. (Petr), Skvorc, Z. (Zeljko), Sparrow, B. (Ben), Sperandii, M. G. (Marta Gaia), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Tang, C. Q. (Cindy Q.), Tsiripidis, I. (Ioannis), Vanselow, K. A. (Kim Andre), Vasquez Martinez, R. (Rodolfo), Vassilev, K. (Kiril), Velez-Martin, E. (Eduardo), Venanzoni, R. (Roberto), Vibrans, A. C. (Alexander Christian), Violle, C. (Cyrille), Virtanen, R. (Risto), von Wehrden, H. (Henrik), Wagner, V. (Viktoria), Walker, D. A. (Donald A.), Waller, D. M. (Donald M.), Wang, H.-F. (Hua-Feng), Wesche, K. (Karsten), Whitfeld, T. J. (Timothy J. S.), Willner, W. (Wolfgang), Wiser, S. K. (Susan K.), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zobel, M. (Martin), and Bruelheide, H. (Helge)
Abstract: Motivation: Assessing biodiversity status and trends in plant communities is critical for understanding, quantifying and predicting the effects of global change on ecosystems. Vegetation plots record the occurrence or abundance of all plant species co-occurring within delimited local areas. This allows species absences to be inferred, information seldom provided by existing global plant datasets. Although many vegetation plots have been recorded, most are not available to the global research community. A recent initiative, called ‘sPlot’, compiled the first global vegetation plot database, and continues to grow and curate it. The sPlot database, however, is extremely unbalanced spatially and environmentally, and is not open-access. Here, we address both these issues by (a) resampling the vegetation plots using several environmental variables as sampling strata and (b) securing permission from data holders of 105 local-to-regional datasets to openly release data. We thus present sPlotOpen, the largest open-access dataset of vegetation plots ever released. sPlotOpen can be used to explore global diversity at the plant community level, as ground truth data in remote sensing applications, or as a baseline for biodiversity monitoring. Main types of variable contained: Vegetation plots (n = 95,104) recording cover or abundance of naturally co-occurring vascular plant species within delimited areas. sPlotOpen contains three partially overlapping resampled datasets (c. 50,000 plots each), to be used as replicates in global analyses. Besides geographical location, date, plot size, biome, elevation, slope, aspect, vegetation type, naturalness, coverage of various vegetation layers, and source dataset, plot-level data also include community-weighted means and variances of 18 plant functional traits from the TRY Plant Trait Database. Spatial location and grain: Global, 0.01–40,000 m². Time period and grain: 1888–2015, recording dates. Major taxa and level of measuremen
Published: 2021

9. Disturbed habitats locally reduce the signal of deep evolutionary history in functional traits of plants

Author: Prinzing, A., Pavoine, S., Jactel, H., Hortal, J., Hennekens, S.M., Ozinga, W.A., Bartish, I.V., Bartish, M.R., Kühn, Ingolf, Moen, D.S., Weiher, E., Brändle, M., Winter, M., Violle, C., Venail, P., Purschke, O., Yguel, B., Prinzing, A., Pavoine, S., Jactel, H., Hortal, J., Hennekens, S.M., Ozinga, W.A., Bartish, I.V., Bartish, M.R., Kühn, Ingolf, Moen, D.S., Weiher, E., Brändle, M., Winter, M., Violle, C., Venail, P., Purschke, O., and Yguel, B.
Abstract: The functioning of present ecosystems reflects deep evolutionary history of locally co-occurring species if their functional traits show high phylogenetic signal (PS). However, we do not understand what drives local PS. We hypothesize that local PS is high in undisturbed and stressful habitats – either due to ongoing local assembly of species that maintained ancestral traits, or past evolutionary maintenance of ancestral traits within habitat species-pools, or both.We quantified PS and diversity of 10 traits within 6704 local plant communities across 38 Dutch habitat types differing in disturbance or stress.Mean local PS varied 50-fold among habitat types, often independently of phylogenetic or trait diversity. Mean local PS decreased with disturbance but showed no consistent relationship to stress. Mean local PS exceeded species-pool PS, reflecting non-random subsampling from the pool. Disturbance or stress related more strongly to mean local than to species-pool PS.Disturbed habitats harbour species with evolutionary divergent trait values, likely driven by ongoing, local assembly of species: environmental fluctuations might maintain different trait values within lineages through an evolutionary storage effect. If functional traits do not reflect phylogeny, ecosystem functioning might not be contingent on the presence of particular lineages, and lineages might establish evolutionarily novel interactions.
Published: 2021

10. sPlot:a new tool for global vegetation analyses

Author: Bruelheide, H. (Helge), Dengler, J. (Juergen), Jimenez-Alfaro, B. (Borja), Purschke, O. (Oliver), Hennekens, S. M. (Stephan M.), Chytry, M. (Milan), Pillar, V. D. (Valerio D.), Jansen, F. (Florian), Kattge, J. (Jens), Sandel, B. (Brody), Aubin, I. (Isabelle), Biurrun, I. (Idoia), Field, R. (Richard), Haider, S. (Sylvia), Jandt, U. (Ute), Lenoir, J. (Jonathan), Peet, R. K. (Robert K.), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Schmidt, M. (Marco), Schrodt, F. (Franziska), Winter, M. (Marten), Acic, S. (Svetlana), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Ambarli, D. (Didem), Angelini, P. (Pierangela), Apostolova, I. (Iva), Khan, M. A. (Mohammed A. S. Arfin), Arnst, E. (Elise), Attorre, F. (Fabio), Baraloto, C. (Christopher), Beckmann, M. (Michael), Berg, C. (Christian), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Bjorkman, A. D. (Anne D.), Bondareva, V. (Viktoria), Borchardt, P. (Peter), Botta-Dukat, Z. (Zoltan), Boyle, B. (Brad), Breen, A. (Amy), Brisse, H. (Henry), Byun, C. (Chaeho), Cabido, M. R. (Marcelo R.), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Curran, M. (Michael), Custerevska, R. (Renata), Stevanovic, Z. D. (Zora Dajic), De Bie, E. (Els), de Ruffray, P. (Patrice), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dressler, S. (Stefan), Ejrnaes, R. (Rasmus), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fagundez, J. (Jaime), Finckh, M. (Manfred), Font, X. (Xavier), Forey, E. (Estelle), Fotiadis, G. (Georgios), Garcia-Mijangos, I. (Itziar), de Gasper, A. L. (Andre Luis), Golub, V. (Valentin), Gutierrez, A. G. (Alvaro G.), Hatim, M. Z. (Mohamed Z.), He, T. (Tianhua), Higuchi, P. (Pedro), Holubova, D. (Dana), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Indreica, A. (Adrian), Gursoy, D. I. (Deniz Isik), Jansen, S. (Steven), Janssen, J. (John), Jedrzejek, B. (Birgit), Jirousek, M. (Martin), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Knollova, I. (Ilona), Kolomiychuk, V. (Vitaliy), Korolyuk, A. (Andrey), Kozhevnikova, M. (Maria), Kozub, L. (Lukasz), Krstonosic, D. (Daniel), Kuehl, H. (Hjalmar), Kuehn, I. (Ingolf), Kuzemko, A. (Anna), Kuzmic, F. (Filip), Landucci, F. (Flavia), Lee, M. T. (Michael T.), Levesley, A. (Aurora), Li, C.-F. (Ching-Feng), Liu, H. (Hongyan), Lopez-Gonzalez, G. (Gabriela), Lysenko, T. (Tatiana), Macanovic, A. (Armin), Mahdavi, P. (Parastoo), Manning, P. (Peter), Marceno, C. (Corrado), Martynenko, V. (Vassiliy), Mencuccini, M. (Maurizio), Minden, V. (Vanessa), Moeslund, J. E. (Jesper Erenskjold), Moretti, M. (Marco), Mueller, J. V. (Jonas V.), Munzinger, J. (Jerome), Niinemets, U. (Ulo), Nobis, M. (Marcin), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Ozinga, W. A. (Wim A.), Pauchard, A. (Anibal), Pedashenko, H. (Hristo), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rodwell, J. (John), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schaminee, J. H. (Joop H. J.), Schmiedel, U. (Ute), Sibik, J. (Jozef), Silc, U. (Urban), Skvorc, Z. (Zeljko), Smyth, A. (Anita), Sop, T. (Tenekwetche), Sopotlieva, D. (Desislava), Sparrow, B. (Ben), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Swacha, G. (Grzegorz), Tang, Z. (Zhiyao), Tsiripidis, I. (Ioannis), Turtureanu, P. D. (Pavel Dan), Ugurlu, E. (Emin), Uogintas, D. (Domas), Valachovic, M. (Milan), Vanselow, K. A. (Kim Andre), Vashenyak, Y. (Yulia), Vassilev, K. (Kiril), Velez-Martin, E. (Eduardo), Venanzoni, R. (Roberto), Vibrans, A. C. (Alexander Christian), Violle, C. (Cyrille), Virtanen, R. (Risto), von Wehrden, H. (Henrik), Wagner, V. (Viktoria), Walker, D. A. (Donald A.), Wana, D. (Desalegn), Weiher, E. (Evan), Wesche, K. (Karsten), Whitfeld, T. (Timothy), Willner, W. (Wolfgang), Wiser, S. (Susan), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zizka, G. (Georg), Zverev, A. (Andrei), Bruelheide, H. (Helge), Dengler, J. (Juergen), Jimenez-Alfaro, B. (Borja), Purschke, O. (Oliver), Hennekens, S. M. (Stephan M.), Chytry, M. (Milan), Pillar, V. D. (Valerio D.), Jansen, F. (Florian), Kattge, J. (Jens), Sandel, B. (Brody), Aubin, I. (Isabelle), Biurrun, I. (Idoia), Field, R. (Richard), Haider, S. (Sylvia), Jandt, U. (Ute), Lenoir, J. (Jonathan), Peet, R. K. (Robert K.), Peyre, G. (Gwendolyn), Sabatini, F. M. (Francesco Maria), Schmidt, M. (Marco), Schrodt, F. (Franziska), Winter, M. (Marten), Acic, S. (Svetlana), Agrillo, E. (Emiliano), Alvarez, M. (Miguel), Ambarli, D. (Didem), Angelini, P. (Pierangela), Apostolova, I. (Iva), Khan, M. A. (Mohammed A. S. Arfin), Arnst, E. (Elise), Attorre, F. (Fabio), Baraloto, C. (Christopher), Beckmann, M. (Michael), Berg, C. (Christian), Bergeron, Y. (Yves), Bergmeier, E. (Erwin), Bjorkman, A. D. (Anne D.), Bondareva, V. (Viktoria), Borchardt, P. (Peter), Botta-Dukat, Z. (Zoltan), Boyle, B. (Brad), Breen, A. (Amy), Brisse, H. (Henry), Byun, C. (Chaeho), Cabido, M. R. (Marcelo R.), Casella, L. (Laura), Cayuela, L. (Luis), Cerny, T. (Tomas), Chepinoga, V. (Victor), Csiky, J. (Janos), Curran, M. (Michael), Custerevska, R. (Renata), Stevanovic, Z. D. (Zora Dajic), De Bie, E. (Els), de Ruffray, P. (Patrice), De Sanctis, M. (Michele), Dimopoulos, P. (Panayotis), Dressler, S. (Stefan), Ejrnaes, R. (Rasmus), El-Sheikh, M. A. (Mohamed Abd El-Rouf Mousa), Enquist, B. (Brian), Ewald, J. (Joerg), Fagundez, J. (Jaime), Finckh, M. (Manfred), Font, X. (Xavier), Forey, E. (Estelle), Fotiadis, G. (Georgios), Garcia-Mijangos, I. (Itziar), de Gasper, A. L. (Andre Luis), Golub, V. (Valentin), Gutierrez, A. G. (Alvaro G.), Hatim, M. Z. (Mohamed Z.), He, T. (Tianhua), Higuchi, P. (Pedro), Holubova, D. (Dana), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Indreica, A. (Adrian), Gursoy, D. I. (Deniz Isik), Jansen, S. (Steven), Janssen, J. (John), Jedrzejek, B. (Birgit), Jirousek, M. (Martin), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Kavgaci, A. (Ali), Kearsley, E. (Elizabeth), Kessler, M. (Michael), Knollova, I. (Ilona), Kolomiychuk, V. (Vitaliy), Korolyuk, A. (Andrey), Kozhevnikova, M. (Maria), Kozub, L. (Lukasz), Krstonosic, D. (Daniel), Kuehl, H. (Hjalmar), Kuehn, I. (Ingolf), Kuzemko, A. (Anna), Kuzmic, F. (Filip), Landucci, F. (Flavia), Lee, M. T. (Michael T.), Levesley, A. (Aurora), Li, C.-F. (Ching-Feng), Liu, H. (Hongyan), Lopez-Gonzalez, G. (Gabriela), Lysenko, T. (Tatiana), Macanovic, A. (Armin), Mahdavi, P. (Parastoo), Manning, P. (Peter), Marceno, C. (Corrado), Martynenko, V. (Vassiliy), Mencuccini, M. (Maurizio), Minden, V. (Vanessa), Moeslund, J. E. (Jesper Erenskjold), Moretti, M. (Marco), Mueller, J. V. (Jonas V.), Munzinger, J. (Jerome), Niinemets, U. (Ulo), Nobis, M. (Marcin), Noroozi, J. (Jalil), Nowak, A. (Arkadiusz), Onyshchenko, V. (Viktor), Overbeck, G. E. (Gerhard E.), Ozinga, W. A. (Wim A.), Pauchard, A. (Anibal), Pedashenko, H. (Hristo), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Peterka, T. (Tomas), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Prokhorov, V. (Vadim), Rasomavicius, V. (Valerijus), Revermann, R. (Rasmus), Rodwell, J. (John), Ruprecht, E. (Eszter), Rusina, S. (Solvita), Samimi, C. (Cyrus), Schaminee, J. H. (Joop H. J.), Schmiedel, U. (Ute), Sibik, J. (Jozef), Silc, U. (Urban), Skvorc, Z. (Zeljko), Smyth, A. (Anita), Sop, T. (Tenekwetche), Sopotlieva, D. (Desislava), Sparrow, B. (Ben), Stancic, Z. (Zvjezdana), Svenning, J.-C. (Jens-Christian), Swacha, G. (Grzegorz), Tang, Z. (Zhiyao), Tsiripidis, I. (Ioannis), Turtureanu, P. D. (Pavel Dan), Ugurlu, E. (Emin), Uogintas, D. (Domas), Valachovic, M. (Milan), Vanselow, K. A. (Kim Andre), Vashenyak, Y. (Yulia), Vassilev, K. (Kiril), Velez-Martin, E. (Eduardo), Venanzoni, R. (Roberto), Vibrans, A. C. (Alexander Christian), Violle, C. (Cyrille), Virtanen, R. (Risto), von Wehrden, H. (Henrik), Wagner, V. (Viktoria), Walker, D. A. (Donald A.), Wana, D. (Desalegn), Weiher, E. (Evan), Wesche, K. (Karsten), Whitfeld, T. (Timothy), Willner, W. (Wolfgang), Wiser, S. (Susan), Wohlgemuth, T. (Thomas), Yamalov, S. (Sergey), Zizka, G. (Georg), and Zverev, A. (Andrei)
Abstract: Aims: Vegetation‐plot records provide information on the presence and cover or abundance of plants co‐occurring in the same community. Vegetation‐plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community‐weighted means and variances of traits using gap‐filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community‐weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.
Published: 2019

11. 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

12. 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

13. Global trait–environment relationships of plant communities

Author: Bruelheide, H., Dengler, J., Purschke, O., Ozinga, W.A., Wirth, C., and Jandt, U.
Subjects: Plant Ecology
Abstract: Contains fulltext : 199662.pdf (Publisher’s version ) (Closed access)
Published: 2018

14. Global trait:environment relationships of plant communities

Author: Bruelheide, H. (Helge), Dengler, J. (Juergen), Purschke, O. (Oliver), Lenoir, J. (Jonathan), Jimenez-Alfaro, B. (Borja), Hennekens, S. M. (Stephan M.), Botta-Dukat, Z. (Zoltan), Chytry, M. (Milan), Field, R. (Richard), Jansen, F. (Florian), Kattge, J. (Jens), Pillar, V. D. (Valerio D.), Schrodt, F. (Franziska), Mahecha, M. D. (Miguel D.), Peet, R. K. (Robert K.), Sandel, B. (Brody), van Bodegom, P. (Peter), Altman, J. (Jan), Alvarez-Davila, E. (Esteban), Khan, M. A. (Mohammed A. S. Arfin), Attorre, F. (Fabio), Aubin, I. (Isabelle), Baraloto, C. (Christopher), Barroso, J. G. (Jorcely G.), Bauters, M. (Marijn), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Blonder, B. (Benjamin), Carni, A. (Andraz), Cayuela, L. (Luis), Cerny, T. (Tomas), Cornelissen, J. H. (J. Hans C.), Craven, D. (Dylan), Dainese, M. (Matteo), Derroire, G. (Geraldine), De Sanctis, M. (Michele), Diaz, S. (Sandra), Dolezal, J. (Jiri), Farfan-Rios, W. (William), Feldpausch, T. R. (Ted R.), Fenton, N. J. (Nicole J.), Garnier, E. (Eric), Guerin, G. R. (Greg R.), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hattab, T. (Tarek), Henry, G. (Greg), Herault, B. (Bruno), Higuchi, P. (Pedro), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Karger, D. N. (Dirk N.), Kessler, M. (Michael), Kleyer, M. (Michael), Knollova, I. (Ilona), Korolyuk, A. Y. (Andrey Y.), Kuehn, I. (Ingolf), Laughlin, D. C. (Daniel C.), Lens, F. (Frederic), Loos, J. (Jacqueline), Louault, F. (Frederique), Lyubenova, M. I. (Mariyana, I), Malhi, Y. (Yadvinder), Marceno, C. (Corrado), Mencuccini, M. (Maurizio), Mueller, J. V. (Jonas, V), Munzinger, J. (Jerome), Myers-Smith, I. H. (Isla H.), Neill, D. A. (David A.), Niinemets, U. (Ulo), Orwin, K. H. (Kate H.), Ozinga, W. A. (Wim A.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Partel, M. (Meelis), Reich, P. B. (Peter B.), Roemermann, C. (Christine), Rodrigues, A. V. (Arthur, V), Sabatini, F. M. (Francesco Maria), Sardans, J. (Jordi), Schmidt, M. (Marco), Seidler, G. (Gunnar), Silva Espejo, J. E. (Javier Eduardo), Silveira, M. (Marcos), Smyth, A. (Anita), Sporbert, M. (Maria), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Thomas, R. (Raquel), Tsiripidis, I. (Ioannis), Vassilev, K. (Kiril), Violle, C. (Cyrille), Virtanen, R. (Risto), Weiher, E. (Evan), Welk, E. (Erik), Wesche, K. (Karsten), Winter, M. (Marten), Wirth, C. (Christian), Jandt, U. (Ute), Bruelheide, H. (Helge), Dengler, J. (Juergen), Purschke, O. (Oliver), Lenoir, J. (Jonathan), Jimenez-Alfaro, B. (Borja), Hennekens, S. M. (Stephan M.), Botta-Dukat, Z. (Zoltan), Chytry, M. (Milan), Field, R. (Richard), Jansen, F. (Florian), Kattge, J. (Jens), Pillar, V. D. (Valerio D.), Schrodt, F. (Franziska), Mahecha, M. D. (Miguel D.), Peet, R. K. (Robert K.), Sandel, B. (Brody), van Bodegom, P. (Peter), Altman, J. (Jan), Alvarez-Davila, E. (Esteban), Khan, M. A. (Mohammed A. S. Arfin), Attorre, F. (Fabio), Aubin, I. (Isabelle), Baraloto, C. (Christopher), Barroso, J. G. (Jorcely G.), Bauters, M. (Marijn), Bergmeier, E. (Erwin), Biurrun, I. (Idoia), Bjorkman, A. D. (Anne D.), Blonder, B. (Benjamin), Carni, A. (Andraz), Cayuela, L. (Luis), Cerny, T. (Tomas), Cornelissen, J. H. (J. Hans C.), Craven, D. (Dylan), Dainese, M. (Matteo), Derroire, G. (Geraldine), De Sanctis, M. (Michele), Diaz, S. (Sandra), Dolezal, J. (Jiri), Farfan-Rios, W. (William), Feldpausch, T. R. (Ted R.), Fenton, N. J. (Nicole J.), Garnier, E. (Eric), Guerin, G. R. (Greg R.), Gutierrez, A. G. (Alvaro G.), Haider, S. (Sylvia), Hattab, T. (Tarek), Henry, G. (Greg), Herault, B. (Bruno), Higuchi, P. (Pedro), Hoelzel, N. (Norbert), Homeier, J. (Juergen), Jentsch, A. (Anke), Juergens, N. (Norbert), Kacki, Z. (Zygmunt), Karger, D. N. (Dirk N.), Kessler, M. (Michael), Kleyer, M. (Michael), Knollova, I. (Ilona), Korolyuk, A. Y. (Andrey Y.), Kuehn, I. (Ingolf), Laughlin, D. C. (Daniel C.), Lens, F. (Frederic), Loos, J. (Jacqueline), Louault, F. (Frederique), Lyubenova, M. I. (Mariyana, I), Malhi, Y. (Yadvinder), Marceno, C. (Corrado), Mencuccini, M. (Maurizio), Mueller, J. V. (Jonas, V), Munzinger, J. (Jerome), Myers-Smith, I. H. (Isla H.), Neill, D. A. (David A.), Niinemets, U. (Ulo), Orwin, K. H. (Kate H.), Ozinga, W. A. (Wim A.), Penuelas, J. (Josep), Perez-Haase, A. (Aaron), Petrik, P. (Petr), Phillips, O. L. (Oliver L.), Partel, M. (Meelis), Reich, P. B. (Peter B.), Roemermann, C. (Christine), Rodrigues, A. V. (Arthur, V), Sabatini, F. M. (Francesco Maria), Sardans, J. (Jordi), Schmidt, M. (Marco), Seidler, G. (Gunnar), Silva Espejo, J. E. (Javier Eduardo), Silveira, M. (Marcos), Smyth, A. (Anita), Sporbert, M. (Maria), Svenning, J.-C. (Jens-Christian), Tang, Z. (Zhiyao), Thomas, R. (Raquel), Tsiripidis, I. (Ioannis), Vassilev, K. (Kiril), Violle, C. (Cyrille), Virtanen, R. (Risto), Weiher, E. (Evan), Welk, E. (Erik), Wesche, K. (Karsten), Winter, M. (Marten), Wirth, C. (Christian), and Jandt, U. (Ute)
Abstract: Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait–environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.
Published: 2018

15. Measurement of Biodiversity (MoB): A method to separate the scale‐dependent effects of species abundance distribution, density, and aggregation on diversity change

Author: McGlinn, D.J., Xiao, X., May, F., Gotelli, N.J., Engel, T., Blowes, S.A., Knight, Tiffany, Purschke, O., Chase, J.M., McGill, B.J., McGlinn, D.J., Xiao, X., May, F., Gotelli, N.J., Engel, T., Blowes, S.A., Knight, Tiffany, Purschke, O., Chase, J.M., and McGill, B.J.
Abstract: 1.Little consensus has emerged regarding how proximate and ultimate drivers such as productivity, disturbance, and temperature may affect species richness and other aspects of biodiversity. Part of the confusion is that most studies examine species richness at a single spatial scale and ignore how the underlying components of species richness can vary with spatial scale.2.We provide an approach for the measurement of biodiversity (MoB) that decomposes changes in species rarefaction curves into proximate components attributed to: 1) the species abundance distribution, 2) density of individuals, and 3) the spatial arrangement of individuals. We decompose species richness by comparing spatial and nonspatial sample‐ and individual‐based species rarefaction curves that differentially capture the influence of these components to estimate the relative importance of each in driving patterns of species richness change.3.We tested the validity of our method on simulated data, and we demonstrate it on empirical data on plant species richness in invaded and uninvaded woodlands. We integrated these methods into a new R package (mobr).4.The metrics that mobr provides will allow ecologists to move beyond comparisons of species richness in response to ecological drivers at a single spatial scale towards a dissection of the proximate components that determine species richness across scales.
Published: 2018

16. Embracing scale‐dependence to achieve a deeper understanding of biodiversity and its change across communities

Author: Chase, J.M., McGill, B.J., McGlinn, D.J., May, F., Blowes, S.A., Xiao, X., Knight, Tiffany, Purschke, O., Gotelli, N.J., Adler, F., Chase, J.M., McGill, B.J., McGlinn, D.J., May, F., Blowes, S.A., Xiao, X., Knight, Tiffany, Purschke, O., Gotelli, N.J., and Adler, F.
Abstract: Because biodiversity is multidimensional and scale‐dependent, it is challenging to estimate its change. However, it is unclear (1) how much scale‐dependence matters for empirical studies, and (2) if it does matter, how exactly we should quantify biodiversity change. To address the first question, we analysed studies with comparisons among multiple assemblages, and found that rarefaction curves frequently crossed, implying reversals in the ranking of species richness across spatial scales. Moreover, the most frequently measured aspect of diversity – species richness – was poorly correlated with other measures of diversity. Second, we collated studies that included spatial scale in their estimates of biodiversity change in response to ecological drivers and found frequent and strong scale‐dependence, including nearly 10% of studies which showed that biodiversity changes switched directions across scales. Having established the complexity of empirical biodiversity comparisons, we describe a synthesis of methods based on rarefaction curves that allow more explicit analyses of spatial and sampling effects on biodiversity comparisons. We use a case study of nutrient additions in experimental ponds to illustrate how this multi‐dimensional and multi‐scale perspective informs the responses of biodiversity to ecological drivers.
Published: 2018

17. Biodiversity and ecosystem functioning relations in European forests depend on environmental context

Author: Ratcliffe, S., Wirth, C., Jucker, T., van der Plas, F., Scherer-Lorenzen, M., Verheyen, K., Allan, E., Benavides, R., Bruelheide, H., Ohse, B., Paquette, A., Ampoorter, E., Bastias, C.C., Bauhus, J., Bonal, D., Bouriaud, O., Bussotti, F., Carnol, M., Castagneyrol, B., Chećko, E., Dawud, S.M., De Wandeler, H., Domisch, T., Finer, L., Fischer, M., Fotelli, M., Gessler, A., Granier, A., Grossiord, C., Guyot, V., Haase, J., Hättenschwiler, S., Jactel, H., Jaroszewicz, B., Joly, F.-X., Kambach, Stephan, Kolb, S., Koricheva, J., Liebersgesell, M., Milligan, H., Müller, S., Muys, B., Nguyen, D., Nock, C., Pollastrini, M., Purschke, O., Radoglou, K., Raulund-Rasmussen, K., Roger, F., Ruiz-Benito, P., Seidl, R., Selvi, F., Seiferling, I., Stenlid, J., Valladares, F., Vesterdal, L., Baeten, L., Ratcliffe, S., Wirth, C., Jucker, T., van der Plas, F., Scherer-Lorenzen, M., Verheyen, K., Allan, E., Benavides, R., Bruelheide, H., Ohse, B., Paquette, A., Ampoorter, E., Bastias, C.C., Bauhus, J., Bonal, D., Bouriaud, O., Bussotti, F., Carnol, M., Castagneyrol, B., Chećko, E., Dawud, S.M., De Wandeler, H., Domisch, T., Finer, L., Fischer, M., Fotelli, M., Gessler, A., Granier, A., Grossiord, C., Guyot, V., Haase, J., Hättenschwiler, S., Jactel, H., Jaroszewicz, B., Joly, F.-X., Kambach, Stephan, Kolb, S., Koricheva, J., Liebersgesell, M., Milligan, H., Müller, S., Muys, B., Nguyen, D., Nock, C., Pollastrini, M., Purschke, O., Radoglou, K., Raulund-Rasmussen, K., Roger, F., Ruiz-Benito, P., Seidl, R., Selvi, F., Seiferling, I., Stenlid, J., Valladares, F., Vesterdal, L., and Baeten, L.
Abstract: The importance of biodiversity in supporting ecosystem functioning is generally well accepted. However, most evidence comes from small-scale studies, and scaling-up patterns of biodiversity–ecosystem functioning (B-EF) remains challenging, in part because the importance of environmental factors in shaping B-EF relations is poorly understood. Using a forest research platform in which 26 ecosystem functions were measured along gradients of tree species richness in six regions across Europe, we investigated the extent and the potential drivers of context dependency of B-EF relations. Despite considerable variation in species richness effects across the continent, we found a tendency for stronger B-EF relations in drier climates as well as in areas with longer growing seasons and more functionally diverse tree species. The importance of water availability in driving context dependency suggests that as water limitation increases under climate change, biodiversity may become even more important to support high levels of functioning in European forests.
Published: 2017

18. A guide to phylogenetic metrics for conservation, community ecology and macroecology

Author: Tucker, C, Cadotte, M, Carvalho, S, Davies, T, Ferrier, S, Fritz, S, Grenyer, R, Helmus, M, Jin, L, Mooers, A, Pavoine, S, Purschke, O, Redding, D, Rosauer, D, Winter, M, and Mazel, F
Subjects: diversity metrics, Conservation of Natural Resources, Ecology, conservation, Original Articles, prioritization, Biodiversity, Biological Evolution, ddc:570, community assembly, phylogenetic diversity, Original Article, range size, biogeography, evolutionary history, biodiversity hotspots, Phylogeny
Abstract: The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub-disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub-disciplines hampers potential meta-analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo-diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information. Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo-diversity metrics based on their mathematical form within these three dimensions and identify ‘anchor’ representatives: for α-diversity metrics these are PD (Faith’s phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices.
Published: 2016

19. The Evolutionary Legacy of Diversification Predicts Ecosystem Function

Author: Yguel, B., Jactel, H., Pearse, I.S., Moen, D., Winter, M., Hortal, J., Helmus, M.R., Kuhn, I., Pavoine, S., Purschke, O., Weiher, E., Violle, C., Ozinga, W.A., Brandle, M., Bartish, I., Prinzing, A., Yguel, B., Jactel, H., Pearse, I.S., Moen, D., Winter, M., Hortal, J., Helmus, M.R., Kuhn, I., Pavoine, S., Purschke, O., Weiher, E., Violle, C., Ozinga, W.A., Brandle, M., Bartish, I., and Prinzing, A.
Abstract: Contains fulltext : 161858.pdf (publisher's version ) (Open Access)
Published: 2016

20. Tree phylogenetic diversity promotes host–parasitoid interactions

Author: Staab, M., Bruelheide, H., Durka, Walter, Michalski, Stefan, Purschke, O., Zhu, C.-D., Klein, A.-M., Staab, M., Bruelheide, H., Durka, Walter, Michalski, Stefan, Purschke, O., Zhu, C.-D., and Klein, A.-M.
Abstract: Evidence from grassland experiments suggests that a plant community's phylogenetic diversity (PD) is a strong predictor of ecosystem processes, even stronger than species richness per se. This has, however, never been extended to species-rich forests and host–parasitoid interactions. We used cavity-nesting Hymenoptera and their parasitoids collected in a subtropical forest as a model system to test whether hosts, parasitoids, and their interactions are influenced by tree PD and a comprehensive set of environmental variables, including tree species richness. Parasitism rate and parasitoid abundance were positively correlated with tree PD. All variables describing parasitoids decreased with elevation, and were, except parasitism rate, dependent on host abundance. Quantitative descriptors of host–parasitoid networks were independent of the environment. Our study indicates that host–parasitoid interactions in species-rich forests are related to the PD of the tree community, which influences parasitism rates through parasitoid abundance. We show that effects of tree community PD are much stronger than effects of tree species richness, can cascade to high trophic levels, and promote trophic interactions. As during habitat modification phylogenetic information is usually lost non-randomly, even species-rich habitats may not be able to continuously provide the ecosystem process parasitism if the evolutionarily most distinct plant lineages vanish.
Published: 2016

21. Soil and tree species traits both shape soil microbial communities during early growth of Chinese subtropical forests

Author: Pei, Z., Eichenberg, D., Bruelheide, H., Kröber, W., Kühn, P., Li, Y., von Oheimb, G., Purschke, O., Scholten, T., Buscot, Francois, Gutknecht, Jessica, Pei, Z., Eichenberg, D., Bruelheide, H., Kröber, W., Kühn, P., Li, Y., von Oheimb, G., Purschke, O., Scholten, T., Buscot, Francois, and Gutknecht, Jessica
Abstract: A better understanding of the linkages between aboveground and belowground biotic communities is needed for more accurate predictions about how ecosystems may be altered by climate change, land management, or biodiversity loss. Soil microbes are strongly affected by multiple factors including local abiotic environmental conditions and plant characteristics. To find out how soil microbial communities respond to multiple facets of the local soil and plant environment, we analysed soil lipid profiles associated with three-year-old monocultures of 29 tree species. These species are native of the diverse subtropical forests of southeast China and greatly vary in functional traits, growth or biomass characteristics, and phylogenetic relatedness. Along with the traits of each tree species, we also determined the soil and plot characteristics in each monoculture plot and tested for phylogenetic signals in tree species-specific microbial indicators. Microbial community structure and biomass were influenced by both soil properties and plant functional traits, but were not related to the phylogenetic distances of tree species. Specifically, total microbial biomass, indicators for fungi, bacteria, and actinomycetes were positively correlated with soil pH, soil organic nitrogen, and soil moisture. Our results also indicate that leaf dry matter content and the leaf carbon to nitrogen ratio influence multivariate soil microbial community structure, and that these factors and tree growth traits (height, crown or basal diameter) positively promote the abundances of specific microbial functional groups. At the same time, a negative correlation between leaf nitrogen content and Gram positive bacterial abundance was detected, indicating plant–microbial competition for nitrogen in our system. In conclusion, even at early stages of tree growth, soil microbial community abundance and structure can be significantly influenced by plant traits, in combination with local soil characteristics.
Published: 2016

22. Tree species traits but not diversity mitigate stem breakage in a subtropical forest following a rare and extreme ice storm

Author: Nadrowski, K., Pietsch, K., Baruffol, M., Both, S., Gutknecht, Jessica, Bruelheide, H., Heklau, H., Kahl, A., Kahl, T., Niklaus, P., Kröber, W., Liu, X., Mi, X., Michalski, Stefan, von Oheimb, G., Purschke, O., Schmid, B., Fang, T., Welk, E., Wirth, C., Nadrowski, K., Pietsch, K., Baruffol, M., Both, S., Gutknecht, Jessica, Bruelheide, H., Heklau, H., Kahl, A., Kahl, T., Niklaus, P., Kröber, W., Liu, X., Mi, X., Michalski, Stefan, von Oheimb, G., Purschke, O., Schmid, B., Fang, T., Welk, E., and Wirth, C.
Abstract: Future climates are likely to include extreme events, which in turn have great impacts on ecological systems. In this study, we investigated possible effects that could mitigate stem breakage caused by a rare and extreme ice storm in a Chinese subtropical forest across a gradient of forest diversity. We used Bayesian modeling to correct stem breakage for tree size and variance components analysis to quantify the influence of taxon, leaf and wood functional traits, and stand level properties on the probability of stem breakage. We show that the taxon explained four times more variance in individual stem breakage than did stand level properties; trees with higher specific leaf area (SLA) were less susceptible to breakage. However, a large part of the variation at the taxon scale remained unexplained, implying that unmeasured or undefined traits could be used to predict damage caused by ice storms. When aggregated at the plot level, functional diversity and wood density increased after the ice storm. We suggest that for the adaption of forest management to climate change, much can still be learned from looking at functional traits at the taxon level.
Published: 2014

23. Functional and phylogenetic diversity of woody plants drive herbivory in highly diverse forests

Author: Schuldt, A., Assmann, T., Bruelheide, B., Durka, Walter, Eichenberg, D., Härdtle, W., Kröber, W., Michalski, Stefan, Purschke, O., Schuldt, A., Assmann, T., Bruelheide, B., Durka, Walter, Eichenberg, D., Härdtle, W., Kröber, W., Michalski, Stefan, and Purschke, O.
Abstract: Biodiversity loss may alter ecosystem processes, such as herbivory, a key driver of ecological functions in species-rich (sub)tropical forests. However, the mechanisms underlying such biodiversity effects remain poorly explored, as mostly effects of species richness – a very basic biodiversity measure – have been studied. Here, we analyze to what extent the functional and phylogenetic diversity of woody plant communities affect herbivory along a diversity gradient in a subtropical forest.We assessed the relative effects of morphological and chemical leaf traits and of plant phylogenetic diversity on individual-level variation in herbivory of dominant woody plant species across 27 forest stands in south-east China.Individual-level variation in herbivory was best explained by multivariate, community-level diversity of leaf chemical traits, in combination with community-weighted means of single traits and species-specific phylodiversity measures. These findings deviate from those based solely on trait variation within individual species.Our results indicate a strong impact of generalist herbivores and highlight the need to assess food-web specialization to determine the direction of biodiversity effects. With increasing plant species loss, but particularly with the concomitant loss of functional and phylogenetic diversity in these forests, the impact of herbivores will probably decrease – with consequences for the herbivore-mediated regulation of ecosystem functions.
Published: 2014

24. Contrasting changes in taxonomic, phylogenetic and functional diversity during a long-term succession: insights into assembly processes

Author: Purschke, O., Schmid, B.C., Sykes, M.T., Poschlod, P., Michalski, Stefan, Durka, Walter, Kühn, Ingolf, Winter, Marten, Prentice, H.C., Purschke, O., Schmid, B.C., Sykes, M.T., Poschlod, P., Michalski, Stefan, Durka, Walter, Kühn, Ingolf, Winter, Marten, and Prentice, H.C.
Abstract: Theory predicts that the processes generating biodiversity after disturbance will change during succession. Comparisons of phylogenetic and functional (alpha and beta) diversity with taxonomic diversity can provide insights into the extent to which community assembly is driven by deterministic or stochastic processes, but comparative approaches have yet to be applied to successional systems.We characterized taxonomic, phylogenetic and functional plant (alpha and beta) diversity within and between four successional stages in a > 270-year-long arable-to-grassland chronosequence. Null models were used to test whether functional and phylogenetic turnover differed from random expectations, given the levels of species diversity.The three facets of diversity showed different patterns of change during succession. Between early and early-mid succession, species richness increased but there was no increase in functional or phylogenetic diversity. Higher than predicted levels of functional similarity between species within the early and early-mid successional stages, indicate that abiotic filters have selected for sets of functionally similar species within sites. Between late-mid and late succession, there was no further increase in species richness, but a significant increase in functional alpha diversity, suggesting that functionally redundant species were replaced by functionally more dissimilar species. Functional turnover between stages was higher than predicted, and higher than within-stage turnover, indicating that different assembly processes act at different successional stages.Synthesis. Analysis of spatial and temporal turnover in different facets of diversity suggests that deterministic processes generate biodiversity during post-disturbance ecosystem development and that the relative importance of assembly processes has changed over time. Trait-mediated abiotic filtering appears to play an important role in community assembly during the early and early-mid
Published: 2013

25. Components of uncertainty in species distribution analysis: a case study of the great grey shrike

Author: Dormann, Carsten, Purschke, O., García Márquez, J.R., Lautenbach, Sven, Schröder, B., Dormann, Carsten, Purschke, O., García Márquez, J.R., Lautenbach, Sven, and Schröder, B.
Abstract: Sophisticated statistical analyses are common in ecological research, particularly in species distribution modeling. The effects of sometimes arbitrary decisions during the modeling procedure on the final outcome are difficult to assess, and to date are largely unexplored. We conducted an analysis quantifying the contribution of uncertainty in each step during the model‐building sequence to variation in model validity and climate change projection uncertainty. Our study system was the distribution of the Great Grey Shrike in the German federal state of Saxony. For each of four steps (data quality, collinearity method, model type, and variable selection), we ran three different options in a factorial experiment, leading to 81 different model approaches. Each was subjected to a fivefold cross‐validation, measuring area under curve (AUC) to assess model quality. Next, we used three climate change scenarios times three precipitation realizations to project future distributions from each model, yielding 729 projections. Again, we analyzed which step introduced most variability (the four model‐building steps plus the two scenario steps) into predicted species prevalences by the year 2050. Predicted prevalences ranged from a factor of 0.2 to a factor of 10 of present prevalence, with the majority of predictions between 1.1 and 4.2 (inter‐quartile range). We found that model type and data quality dominated this analysis. In particular, artificial neural networks yielded low cross‐validation robustness and gave very conservative climate change predictions. Generalized linear and additive models were very similar in quality and predictions, and superior to neural networks. Variations in scenarios and realizations had very little effect, due to the small spatial extent of the study region and its relatively small range of climatic conditions. We conclude that, for climate projections, model type and data quality were the most influential factors. Since comparison of model type
Published: 2008

26. Functional responses of plant communities to management, landscape and historical factors in semi-natural grasslands

Author: Vandewalle, M., primary, Purschke, O., additional, de Bello, F., additional, Reitalu, T., additional, Prentice, H.C., additional, Lavorel, S., additional, Johansson, L.J., additional, and Sykes, M.T., additional
Published: 2013
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27. sPlot – A new tool for global vegetation analyses

Author: Bruelheide H., Dengler J., Jiménez-Alfaro B., Purschke O., Hennekens S., Chytrý M., Pillar V., Jansen F., Kattge J., Sandel B., Aubin I., Biurrun I., Field R., Haider S., Jandt U., Lenoir J., Peet R., Peyre G., Sabatini F., Schmidt M., Schrodt F., Winter M., Aćić S., Agrillo E., Alvarez M., Ambarlı D., Angelini P., Apostolova I., Arfin Khan M., Arnst E., Attorre F., Baraloto C., Beckmann M., Berg C., Bergeron Y., Bergmeier E., Bjorkman A., Bondareva V., Borchardt P., Botta-Dukát Z., Boyle B., Breen A., Brisse H., Byun C., Cabido M., Casella L., Cayuela L., Černý T., Chepinoga V., Csiky J., Curran M., Ćušterevska R., Dajić Stevanović Z., De Bie E., de Ruffray P., De Sanctis M., Dimopoulos P., Dressler S., Ejrnæs R., El-Sheikh M., Enquist B., Ewald J., Fagúndez J., Finckh M., Font X., Forey E., Fotiadis G., García-Mijangos I., de Gasper A., Golub V., Gutierrez A., Hatim M., He T., Higuchi P., Holubová D., Hölzel N., Homeier J., Indreica A., Işık Gürsoy D., Jansen S., Janssen J., Jedrzejek B., Jiroušek M., Jürgens N., Kącki Z., Kavgacı A., Kearsley E., Kessler M., Knollová I., Kolomiychuk V., Korolyuk A., Kozhevnikova M., Kozub Ł., Krstonošić D., Kühl H., Kühn I., Kuzemko A., Küzmič F., Landucci F., Lee M., Bruelheide H., Dengler J., Jiménez-Alfaro B., Purschke O., Hennekens S., Chytrý M., Pillar V., Jansen F., Kattge J., Sandel B., Aubin I., Biurrun I., Field R., Haider S., Jandt U., Lenoir J., Peet R., Peyre G., Sabatini F., Schmidt M., Schrodt F., Winter M., Aćić S., Agrillo E., Alvarez M., Ambarlı D., Angelini P., Apostolova I., Arfin Khan M., Arnst E., Attorre F., Baraloto C., Beckmann M., Berg C., Bergeron Y., Bergmeier E., Bjorkman A., Bondareva V., Borchardt P., Botta-Dukát Z., Boyle B., Breen A., Brisse H., Byun C., Cabido M., Casella L., Cayuela L., Černý T., Chepinoga V., Csiky J., Curran M., Ćušterevska R., Dajić Stevanović Z., De Bie E., de Ruffray P., De Sanctis M., Dimopoulos P., Dressler S., Ejrnæs R., El-Sheikh M., Enquist B., Ewald J., Fagúndez J., Finckh M., Font X., Forey E., Fotiadis G., García-Mijangos I., de Gasper A., Golub V., Gutierrez A., Hatim M., He T., Higuchi P., Holubová D., Hölzel N., Homeier J., Indreica A., Işık Gürsoy D., Jansen S., Janssen J., Jedrzejek B., Jiroušek M., Jürgens N., Kącki Z., Kavgacı A., Kearsley E., Kessler M., Knollová I., Kolomiychuk V., Korolyuk A., Kozhevnikova M., Kozub Ł., Krstonošić D., Kühl H., Kühn I., Kuzemko A., Küzmič F., Landucci F., and Lee M.
Abstract: © 2019 International Association for Vegetation Science Aims: Vegetation-plot records provide information on the presence and cover or abundance of plants co-occurring in the same community. Vegetation-plot data are spread across research groups, environmental agencies and biodiversity research centers and, thus, are rarely accessible at continental or global scales. Here we present the sPlot database, which collates vegetation plots worldwide to allow for the exploration of global patterns in taxonomic, functional and phylogenetic diversity at the plant community level. Results: sPlot version 2.1 contains records from 1,121,244 vegetation plots, which comprise 23,586,216 records of plant species and their relative cover or abundance in plots collected worldwide between 1885 and 2015. We complemented the information for each plot by retrieving climate and soil conditions and the biogeographic context (e.g., biomes) from external sources, and by calculating community-weighted means and variances of traits using gap-filled data from the global plant trait database TRY. Moreover, we created a phylogenetic tree for 50,167 out of the 54,519 species identified in the plots. We present the first maps of global patterns of community richness and community-weighted means of key traits. Conclusions: The availability of vegetation plot data in sPlot offers new avenues for vegetation analysis at the global scale.

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

Author: Ben Sparrow, V. B. Martynenko, Jonathan Lenoir, Eszter Ruprecht, Idoia Biurrun, Luzmila Arroyo, Borja Jiménez-Alfaro, Aníbal Pauchard, Roberto Venanzoni, Stephan M. Hennekens, Mohamed Z. Hatim, Cyrus Samimi, Arkadiusz Nowak, Gerhard E. Overbeck, Petr Sklenář, Renata Ćušterevska, Valentin Golub, Eduardo Vélez-Martin, Gwendolyn Peyre, Inger Greve Alsos, Ioannis Tsiripidis, Tarek Hattab, Andrey Yu. Korolyuk, Jutta Kapfer, Jörg Ewald, Donald M. Waller, Ute Jandt, Tetiana Dziuba, Marco Schmidt, Alvaro G. Gutiérrez, Thomas Wohlgemuth, Adrian Indreica, Zygmunt Kącki, Jürgen Dengler, Željko Škvorc, Dirk Nikolaus Karger, Panayotis Dimopoulos, Viktor Onyshchenko, Hanhuai Shan, John Janssen, Hua Feng Wang, Holger Kreft, Jérôme Munzinger, Brian J. Enquist, Frederic Lens, Wannes Hubau, Birgit Jedrzejek, Alexander Christian Vibrans, Miguel D. Mahecha, Emmanuel Garbolino, Sophie Gachet, Abel Monteagudo Mendoza, Josep Peñuelas, Melisa A. Giorgis, Svetlana Aćić, Débora Vanessa Lingner, Victor V. Chepinoga, Richard Field, Ladislav Mucina, Michele De Sanctis, Mohamed A. El-Sheikh, Isabelle Aubin, Hamid Gholizadeh, Fahmida Sultana, Fabio Attorre, Valerijus Rašomavičius, Cindy Q. Tang, Tomáš Černý, Gonzalo Rivas-Torres, Donald A. Walker, Alicia Teresa Rosario Acosta, Timothy J. Killeen, Francesco Maria Sabatini, Susan K. Wiser, Urban Šilc, Andraž Čarni, Florian Jansen, Valério D. Pillar, Jonas V. Müller, Aaron Pérez-Haase, Els De Bie, Antonio Galán-de-Mera, Zhiyao Tang, Anne D. Bjorkman, Sylvia Haider, Kiril Vassilev, Risto Virtanen, Henrik von Wehrden, Hjalmar S. Kühl, Manfred Finckh, Zvjezdana Stančić, Pavel Shirokikh, Elizabeth Kearsley, Petr Petřík, Yves Bergeron, Iva Apostolova, Emiliano Agrillo, Jozef Šibík, Norbert Jürgens, Marta Gaia Sperandii, Anna Kuzemko, Jens-Christian Svenning, Timothy J. S. Whitfeld, Michael Kessler, Bruno Hérault, John-Arvid Grytnes, Laura Casella, Tomáš Peterka, Miguel Alvarez, Tsipe Aavik, Gregory Richard Guerin, André Luis de Gasper, Corrado Marcenò, Luis Cayuela, Brody Sandel, Cyrille Violle, Jens Kattge, Guillermo Hinojos Mendoza, Anke Jentsch, Arindam Banerjee, Jesper Erenskjold Moeslund, Mohammed Abu Sayed Arfin Khan, Patrice de Ruffray, Milan Chytrý, S. M. Yamalov, Tatiana Lysenko, Meelis Pärtel, Viktoria Bondareva, Helge Bruelheide, John S. Rodwell, Jiri Dolezal, Oliver L. Phillips, Rasmus Revermann, Larisa Khanina, Erwin Bergmeier, Robert K. Peet, Jörg Brunet, Solvita Rūsiņa, Oliver Purschke, Gianmaria Bonari, Jürgen Homeier, Martin Zobel, János Csiky, Marijn Bauters, Jalil Noroozi, Karsten Wesche, Kim André Vanselow, Norbert Hölzel, Flavia Landucci, Farideh Fazayeli, Wolfgang Willner, Viktoria Wagner, Alireza Naqinezhad, Aurora Levesley, Vadim Prokhorov, Hongyan Liu, Ali Kavgaci, Rodolfo Vásquez Martínez, Franziska Schrodt, Attila Lengyel, Elise A. Arnst, Sabatini F.M., Lenoir J., Hattab T., Arnst E.A., Chytry M., Dengler J., De Ruffray P., Hennekens S.M., Jandt U., Jansen F., Jimenez-Alfaro B., Kattge J., Levesley A., Pillar V.D., Purschke O., Sandel B., Sultana F., Aavik T., Acic S., Acosta A.T.R., Agrillo E., Alvarez M., Apostolova I., Arfin Khan M.A.S., Arroyo L., Attorre F., Aubin I., Banerjee A., Bauters M., Bergeron Y., Bergmeier E., Biurrun I., Bjorkman A.D., Bonari G., Bondareva V., Brunet J., Carni A., Casella L., Cayuela L., Cerny T., Chepinoga V., Csiky J., Custerevska R., De Bie E., de Gasper A.L., De Sanctis M., Dimopoulos P., Dolezal J., Dziuba T., El-Sheikh M.A.E.-R.M., Enquist B., Ewald J., Fazayeli F., Field R., Finckh M., Gachet S., Galan-de-Mera A., Garbolino E., Gholizadeh H., Giorgis M., Golub V., Alsos I.G., Grytnes J.-A., Guerin G.R., Gutierrez A.G., Haider S., Hatim M.Z., Herault B., Hinojos Mendoza G., Holzel N., Homeier J., Hubau W., Indreica A., Janssen J.A.M., Jedrzejek B., Jentsch A., Jurgens N., Kacki Z., Kapfer J., Karger D.N., Kavgaci A., Kearsley E., Kessler M., Khanina L., Killeen T., Korolyuk A., Kreft H., Kuhl H.S., Kuzemko A., Landucci F., Lengyel A., Lens F., Lingner D.V., Liu H., Lysenko T., Mahecha M.D., Marceno C., Martynenko V., Moeslund J.E., Monteagudo Mendoza A., Mucina L., Muller J.V., Munzinger J., Naqinezhad A., Noroozi J., Nowak A., Onyshchenko V., Overbeck G.E., Partel M., Pauchard A., Peet R.K., Penuelas J., Perez-Haase A., Peterka T., Petrik P., Peyre G., Phillips O.L., Prokhorov V., Rasomavicius V., Revermann R., Rivas-Torres G., Rodwell J.S., Ruprecht E., Rusina S., Samimi C., Schmidt M., Schrodt F., Shan H., Shirokikh P., Sibik J., Silc U., Sklenar P., Skvorc Z., Sparrow B., Sperandii M.G., Stancic Z., Svenning J.-C., Tang Z., Tang C.Q., Tsiripidis I., Vanselow K.A., Vasquez Martinez R., Vassilev K., Velez-Martin E., Venanzoni R., Vibrans A.C., Violle C., Virtanen R., von Wehrden H., Wagner V., Walker D.A., Waller D.M., Wang H.-F., Wesche K., Whitfeld T.J.S., Willner W., Wiser S.K., Wohlgemuth T., Yamalov S., Zobel M., Bruelheide H., Sabatini, Fm, Lenoir, J, Hattab, T, Arnst, Ea, Chytry, M, Dengler, J, De Ruffray, P, Hennekens, Sm, Jandt, U, Jansen, F, Jimenez-Alfaro, B, Kattge, J, Levesley, A, Pillar, Vd, Purschke, O, Sandel, B, Sultana, F, Aavik, T, Acic, S, Acosta, Atr, Agrillo, E, Alvarez, M, Apostolova, I, Khan, Masa, Arroyo, L, Attorre, F, Aubin, I, Banerjee, A, Bauters, M, Bergeron, Y, Bergmeier, E, Biurrun, I, Bjorkman, Ad, Bonari, G, Bondareva, V, Brunet, J, Carni, A, Casella, L, Cayuela, L, Cerny, T, Chepinoga, V, Csiky, J, Custerevska, R, De Bie, E, de Gasper, Al, De Sanctis, M, Dimopoulos, P, Dolezal, J, Dziuba, T, El-Sheikh, Mam, Enquist, B, Ewald, J, Fazayeli, F, Field, R, Finckh, M, Gachet, S, Galan-de-Mera, A, Garbolino, E, Gholizadeh, H, Giorgis, M, Golub, V, Alsos, Ig, Grytnes, Ja, Guerin, Gr, Gutierrez, Ag, Haider, S, Hatim, Mz, Herault, B, Mendoza, Gh, Holzel, N, Homeier, J, Hubau, W, Indreica, A, Janssen, Jam, Jedrzejek, B, Jentsch, A, Jurgens, N, Kacki, Z, Kapfer, J, Karger, Dn, Kavgaci, A, Kearsley, E, Kessler, M, Khanina, L, Killeen, T, Korolyuk, A, Kreft, H, Kuhl, H, Kuzemko, A, Landucci, F, Lengyel, A, Lens, F, Lingner, Dv, Liu, Hy, Lysenko, T, Mahecha, Md, Marceno, C, Martynenko, V, Moeslund, Je, Mendoza, Am, Mucina, L, Muller, Jv, Munzinger, Jm, Naqinezhad, A, Noroozi, J, Nowak, A, Onyshchenko, V, Overbeck, Ge, Partel, M, Pauchard, A, Peet, Rk, Penuelas, J, Perez-Haase, A, Peterka, T, Petrik, P, Peyre, G, Phillips, Ol, Prokhorov, V, Rasomavicius, V, Revermann, R, Rivas-Torres, G, Rodwell, J, Ruprecht, E, Rusina, S, Samimi, C, Schmidt, M, Schrodt, F, Shan, Hh, Shirokikh, P, Sibik, J, Silc, U, Sklenar, P, Skvorc, Z, Sparrow, B, Sperandii, Mg, Stancic, Z, Svenning, Jc, Tang, Zy, Tang, Cq, Tsiripidis, I, Vanselow, Ka, Martinez, Rv, Vassilev, K, Velez-Martin, E, Venanzoni, R, Vibrans, Ac, Violle, C, Virtanen, R, von Wehrden, H, Wagner, V, Walker, Da, Waller, Dm, Wang, Hf, Wesche, K, Whitfeld, Tj, Willner, W, Wiser, Sk, Wohlgemuth, T, Yamalov, S, Zobel, M, Bruelheide, H, Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), MARine Biodiversity Exploitation and Conservation (UMR MARBEC), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Institut méditerranéen de biodiversité et d'écologie marine et continentale (IMBE), Avignon Université (AU)-Aix Marseille Université (AMU)-Institut de recherche pour le développement [IRD] : UMR237-Centre National de la Recherche Scientifique (CNRS), Centre de recherche sur les Risques et les Crises (CRC), Mines Paris - PSL (École nationale supérieure des mines de Paris), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UPVM)-École Pratique des Hautes Études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), ANR-07-BDIV-0006,BIONEOCAL,L'endémisme en Nouvelle-Calédonie : étude phylogénétique et populationnelle des son émergence.(2007), ANR-07-BDIV-0008,INC,Incendies et biodiversité de écosystèmes en Nouvelle-Calédonie.(2007), ANR-07-BDIV-0010,ULTRABIO,Biodiversité et stratégies adaptatives végétales et microbiennes des écosystèmes ultramafiques en Nouvelle-Calédonie.(2007), European Project: 610028,EC:FP7:ERC,ERC-2013-SyG,IMBALANCE-P(2014), European Project: 291585,EC:FP7:ERC,ERC-2011-ADG_20110209,T-FORCES(2012), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Institut de Recherche pour le Développement (IRD), MINES ParisTech - École nationale supérieure des mines de Paris, Université Paul-Valéry - Montpellier 3 (UPVM)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), and Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)
Subjects: 0106 biological sciences, Biome, Bos- en Landschapsecologie, Biodiversity, DIVERSITY, FOREST VEGETATION, 01 natural sciences, purl.org/becyt/ford/1 [https], Abundance (ecology), big data, Vegetation type, PHYTOSOCIOLOGICAL DATABASE, parcelle, Forest and Landscape Ecology, functional traits, vascular plants, biodiversity, biogeography, database, macroecology, vegetation plots, Macroecology, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, Global and Planetary Change, Ecology, vascular plant, Vegetation, F70 - Taxonomie végétale et phytogéographie, PE&RC, Vegetation plot, Geography, 580: Pflanzen (Botanik), Ecosystems Research, Diffusion de l'information, Plantenecologie en Natuurbeheer, Vegetatie, Bos- en Landschapsecologie, Biodiversité, ARCHIVE, Communauté végétale, Evolution, [SDE.MCG]Environmental Sciences/Global Changes, Biogéographie, GRASSLAND VEGETATION, Plant Ecology and Nature Conservation, [SDV.BID]Life Sciences [q-bio]/Biodiversity, 010603 evolutionary biology, Behavior and Systematics, Couverture végétale, 577: Ökologie, PLANT, purl.org/becyt/ford/1.6 [https], functional trait, Biology, Ecology, Evolution, Behavior and Systematics, Vegetatie, 010604 marine biology & hydrobiology, Impact sur l'environnement, DRY GRASSLANDS, Plant community, 15. Life on land, Végétation, WETLAND VEGETATION, Earth and Environmental Sciences, UNIVERSITY, Physical geography, Vegetation, Forest and Landscape Ecology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, données ouvertes
Abstract: Datos disponibles en https://github.com/fmsabatini/sPlotOpen_Code, EU H2020 project BACI, Grant No. 640176 (...), 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., Levesley, A., Pillar, V.D., Purschke, O., Sandel, B., Sultana, F., Aavik, T., Aćić, S., Acosta, A.T.R., Agrillo, E., Alvarez, M., Apostolova, I., Arfin Khan, M.A.S., Arroyo, L., Attorre, F., Aubin, I., Banerjee, A., Bauters, M., Bergeron, Y., Bergmeier, E., Biurrun, I., Bjorkman, A.D., Bonari, G., Bondareva, V., Brunet, J., Čarni, A., Casella, L., Cayuela, L., Černý, T., Chepinoga, V., Csiky, J., Ćušterevska, R., De Bie, E., de Gasper, A.L., De Sanctis, M., Dimopoulos, P., Dolezal, J., Dziuba, T., El-Sheikh, M.A.E.-R.M., Enquist, B., Ewald, J., Fazayeli, F., Field, R., Finckh, M., Gachet, S., Galán-de-Mera, A., Garbolino, E., Gholizadeh, H., Giorgis, M., Golub, V., Alsos, I.G., Grytnes, J.-A., Guerin, G.R., Gutiérrez, A.G., Haider, S., Hatim, M.Z., Hérault, B., Hinojos Mendoza, G., Hölzel, N., Homeier, J., Hubau, W., Indreica, A., Janssen, J.A.M., Jedrzejek, B., Jentsch, A., Jürgens, N., Kącki, Z., Kapfer, J., Karger, D.N., Kavgacı, A., Kearsley, E., Kessler, M., Khanina, L., Killeen, T., Korolyuk, A., Kreft, H., Kühl, H.S., Kuzemko, A., Landucci, F., Lengyel, A., Lens, F., Lingner, D.V., Liu, H., Lysenko, T., Mahecha, M.D., Marcenò, C., Martynenko, V., Moeslund, J.E., Monteagudo Mendoza, A., Mucina, L., Müller, J.V., Munzinger, J., Naqinezhad, A., Noroozi, J., Nowak, A., Onyshchenko, V., Overbeck, G.E., Pärtel, M., Pauchard, A., Peet, R.K., Peñuelas, J., Pérez-Haase, A., Peterka, T., Petřík, P., Peyre, G., Phillips, O.L., Prokhorov, V., Rašomavičius, V., Revermann, R., Rivas-Torres, G., Rodwell, J.S., Ruprecht, E., Rūsiņa, S., Samimi, C., Schmidt, M., Schrodt, F., Shan, H., Shirokikh, P., Šibík, J., Šilc, U., Sklenář, P., Škvorc, Ž., Sparrow, B., Sperandii, M.G., Stančić, Z., Svenning, J.-C., Tang, Z., Tang, C.Q., Tsiripidis, I., Vanselow, K.A., Vásquez Martínez, R., Vassilev, K., Vélez-Martin, E., Venanzoni, R., Vibrans, A.C., Violle, C., Virtanen, R., von Wehrden, H., Wagner, V., Walker, D.A., Waller, D.M., Wang, H.-F., Wesche, K., Whitfeld, T.J.S., Willner, W., Wiser, S.K., Wohlgemuth, T., Yamalov, S., Zobel, M., Bruelheide, H.
Published: 2021

29. Global trait–environment relationships of plant communities

Author: Esteban Álvarez-Dávila, Maurizio Mencuccini, Zhiyao Tang, Norbert Jürgens, Christopher Baraloto, Robert K. Peet, Jérôme Munzinger, Josep Peñuelas, Peter M. van Bodegom, Erwin Bergmeier, Wim A. Ozinga, Isabelle Aubin, Yadvinder Malhi, Michele De Sanctis, William Farfan-Rios, Marten Winter, Benjamin Blonder, Jordi Sardans, Christian Wirth, Valério D. Pillar, Nicole J. Fenton, Ilona Knollová, Jiří Doležal, Miguel D. Mahecha, Jens Kattge, Marijn Bauters, Zoltán Botta-Dukát, Francesco Maria Sabatini, Jonathan Lenoir, Peter B. Reich, Florian Jansen, Jorcely Barroso, Frédérique Louault, Anne D. Bjorkman, Alvaro G. Gutiérrez, Michael Kleyer, Matteo Dainese, Dylan Craven, Andraž Čarni, Anita K. Smyth, Gunnar Seidler, Idoia Biurrun, Ted R. Feldpausch, Javier Silva Espejo, Helge Bruelheide, Risto Virtanen, Tarek Hattab, Franziska Schrodt, Greg R. Guerin, Sandra Díaz, Anke Jentsch, Jürgen Dengler, Borja Jiménez-Alfaro, J. Hans C. Cornelissen, Kate H. Orwin, Bruno Hérault, Tomáš Černý, Stephan M. Hennekens, Erik Welk, Frederic Lens, Mohammed Abu Sayed Arfin Khan, Jacqueline Loos, Kiril Vassilev, Milan Chytrý, Jonas V. Müller, Christine Römermann, Sylvia Haider, Géraldine Derroire, Marcos Silveira, Greg H. R. Henry, Petr Petřík, Ülo Niinemets, Zygmunt Kącki, Isla H. Myers-Smith, Michael Kessler, Dirk Nikolaus Karger, Evan Weiher, Andrey Yu. Korolyuk, Richard Field, Raquel Thomas, Eric Garnier, Luis Cayuela, Brody Sandel, Cyrille Violle, Jens-Christian Svenning, Corrado Marcenò, Aaron Pérez-Haase, Daniel C. Laughlin, Pedro Higuchi, Jürgen Homeier, Ute Jandt, Fabio Attorre, Karsten Wesche, Norbert Hölzel, Oliver L. Phillips, Ingolf Kühn, Marco Schmidt, Meelis Pärtel, David A. Neill, Maria Sporbert, Mariyana Lyubenova, Oliver Purschke, Arthur Vinicius Rodrigues, Ioannis Tsiripidis, Jan Altman, Institute of Biology/Geobotany and Botanical Garden, Martin-Luther-Universität Halle Wittenberg (MLU), Universität Bayreuth, German Centre for Integrative Biodiversity Research (iDiv), UR Ecol & Dynam Syst Anthropises EDYSAN, UMR CNRS 7058, Université de Picardie Jules Verne (UPJV), Department of Botany and Zoology, Masaryk University, ALTERRA Wageningen, ALTERRA, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, Universidade Federal do Rio Grande do Norte [Natal] (UFRN), Universiteit Leiden [Leiden], Fundación Con-Vida, Ecologie des forêts de Guyane (ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université des Antilles et de la Guyane (UAG)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Universidade Federal do Acre (UFAC), Ecology and Evolutionary Biology [Tucson] (EEB), University of Arizona, National Institute of Biology [Ljubljana], Universidad Rey Juan Carlos [Madrid] (URJC), Vrije Universiteit Amsterdam [Amsterdam] (VU), Royal Institute of Technology (KTH), Department of Microelectronics and Information Technology, Kista Photonics Research Center (KPRC) (KTH), Royal Institute of Technology [Stockholm] (KTH ), AgroParisTech, Centre d’Ecologie Fonctionnelle et Evolutive (CEFE), Université Paul-Valéry - Montpellier 3 (UM3)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-École pratique des hautes études (EPHE)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Ecosystèmes et Ressources Aquatiques (UR03AGRO1), Institut National Agronomique de Tunisie, Westfälische Wilhelms-Universität Münster (WWU), Georg-August-Universität Göttingen, Bayreuth Center of Ecology and Environmental Research (BayCEER), University of Zurich, Landscape Ecology Group, University of Oldenburg, Helmholtz Zentrum für Umweltforschung (UFZ), Netherlands Centre for Biodiversity Naturalis, Institute of Ecology, Leuphana University, Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), Institut National de la Recherche Agronomique (INRA)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS), Environmental Change Institute, University of Oxford [Oxford], School of Geosciences [Edinburgh], University of Edinburgh, Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD [France-Sud]), Universidad Estatal Amazonica, Estonian University of Life Sciences, University of Nijmegen, Global Ecology Unit CREAF-CEAB-CSIC, Universitat Autònoma de Barcelona [Barcelona] (UAB), Institute of Ecology and Earth Sciences, University of Tartu, University of Tartu, Department of Forest Resources, University of Minnesota [Twin Cities], University of Minnesota System-University of Minnesota System, Universität Regensburg (REGENSBURG), Universität Regensburg, Centre de Recerca Ecològica i Aplicacions Forestals (CREAF), Dept Biol Sci, Ecoinformat & Biodivers Grp, Aarhus University [Aarhus], Aristotle University of Thessaloniki, Dept Biol, University of Oulu, University of Wisconsin-Eau Claire, Department of Botany, Senckenberg Natural History Museum, Synthesis Centre for Biodiversity Sciences, German Centre for Integrative Biodiversity Research, Universität Leipzig [Leipzig], Philips Research Europe - Hamburg, Sector Medical Imaging Systems, Philips Research, Ecologie et Dynamique des Systèmes Anthropisés - UMR CNRS 7058 (EDYSAN), Université de Picardie Jules Verne (UPJV)-Centre National de la Recherche Scientifique (CNRS), Masaryk University [Brno] (MUNI), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-École pratique des hautes études (EPHE), Université Paris sciences et lettres (PSL)-Université Paris sciences et lettres (PSL)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut National de la Recherche Agronomique (INRA)-Université Paul-Valéry - Montpellier 3 (UPVM)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut de Recherche pour le Développement (IRD [France-Sud]), MARine Biodiversity Exploitation and Conservation (UMR MARBEC), Institut de Recherche pour le Développement (IRD)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS), Georg-August-University [Göttingen], Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Centre National de la Recherche Scientifique (CNRS)-Université de Montpellier (UM)-Institut National de la Recherche Agronomique (INRA)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud]), Universitat Autònoma de Barcelona (UAB), University of Minnesota [Twin Cities] (UMN), Martin-Luther-University Halle-Wittenberg, Ecologie et Dynamique des Systèmes Anthropisés (EDYSAN), Wageningen University and Research Centre [Wageningen] (WUR), Chercheur indépendant, Department of Ecological Modelling [UFZ Leipzig], Helmholtz Centre for Environmental Research (UFZ), Laboratoire des Sciences de l'Environnement Marin (LEMAR) (LEMAR), Institut de Recherche pour le Développement (IRD)-Institut Universitaire Européen de la Mer (IUEM), Institut de Recherche pour le Développement (IRD)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS)-Institut Français de Recherche pour l'Exploitation de la Mer (IFREMER)-Université de Brest (UBO)-Centre National de la Recherche Scientifique (CNRS), Hawkesbury Institute for the Environment [Richmond] (HIE), Western Sydney University (UWS), Bruelheide H., Dengler J., Purschke O., Lenoir J., Jimenez-Alfaro B., Hennekens S.M., Botta-Dukat Z., Chytry M., Field R., Jansen F., Kattge J., Pillar V.D., Schrodt F., Mahecha M.D., Peet R.K., Sandel B., van Bodegom P., Altman J., Alvarez-Davila E., Arfin Khan M.A.S., Attorre F., Aubin I., Baraloto C., Barroso J.G., Bauters M., Bergmeier E., Biurrun I., Bjorkman A.D., Blonder B., Carni A., Cayuela L., Cerny T., Cornelissen J.H.C., Craven D., Dainese M., Derroire G., De Sanctis M., Diaz S., Dolezal J., Farfan-Rios W., Feldpausch T.R., Fenton N.J., Garnier E., Guerin G.R., Gutierrez A.G., Haider S., Hattab T., Henry G., Herault B., Higuchi P., Holzel N., Homeier J., Jentsch A., Jurgens N., Kacki Z., Karger D.N., Kessler M., Kleyer M., Knollova I., Korolyuk A.Y., Kuhn I., Laughlin D.C., Lens F., Loos J., Louault F., Lyubenova M.I., Malhi Y., Marceno C., Mencuccini M., Muller J.V., Munzinger J., Myers-Smith I.H., Neill D.A., Niinemets U., Orwin K.H., Ozinga W.A., Penuelas J., Perez-Haase A., Petrik P., Phillips O.L., Partel M., Reich P.B., Romermann C., Rodrigues A.V., Sabatini F.M., Sardans J., Schmidt M., Seidler G., Silva Espejo J.E., Silveira M., Smyth A., Sporbert M., Svenning J.-C., Tang Z., Thomas R., Tsiripidis I., Vassilev K., Violle C., Virtanen R., Weiher E., Welk E., Wesche K., Winter M., Wirth C., Jandt U., Systems Ecology, Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro)-Institut national d'enseignement supérieur pour l'agriculture, l'alimentation et l'environnement (Institut Agro), and Institut de Recherche pour le Développement (IRD [France-Sud])-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)
Subjects: 0106 biological sciences, [SDV]Life Sciences [q-bio], Bos- en Landschapsecologie, 01 natural sciences, Ecosystem services, forests, grassland, life history traits, plant dispersal, plants, Forest and Landscape Ecology, Environmental planning, OT PB Vredepeel, [SDV.EE]Life Sciences [q-bio]/Ecology, environment, diversité fonctionnelle, Ecology, Vegetation, Plants, Grassland, économie foliaire, Biogeography, Community Ecology, Ecosystems Research, [SDE]Environmental Sciences, Trait, Vegetatie, Bos- en Landschapsecologie, F40 - Écologie végétale, F60 - Physiologie et biochimie végétale, [SDE.MCG]Environmental Sciences/Global Changes, education, [SDV.BID]Life Sciences [q-bio]/Biodiversity, Life History Trait, Biology, Sustainability Science, 010603 evolutionary biology, température, Life Science, prédiction, Ecosystem, Forest, 577: Ökologie, Vegetatie, Ecology, Evolution, Behavior and Systematics, climat, Plant Dispersal, Niche differentiation, Plant community, 15. Life on land, Disturbance (ecology), Vegetation, Forest and Landscape Ecology, [SDE.BE]Environmental Sciences/Biodiversity and Ecology, Scale (map), 010606 plant biology & botany
Abstract: International audience; Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait-environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.
Published: 2018

30. Post-COVID recovery is faster after an infection with the SARS-CoV-2 Omicron variant: a population-based cohort study.

Author: Pfrommer LR, Diexer S, Klee B, Massag J, Gottschick C, Purschke O, Binder M, Frese T, Girndt M, Sedding D, Rosendahl J, Hoell JI, Moor I, Gekle M, Allwang C, Junne F, and Mikolajczyk R
Abstract: Purpose: Post-COVID-19 condition (PCC) poses a substantial burden to affected individuals, health care systems, and society as a whole. We examined factors associated with recovery from PCC, focusing on the vaccination status prior to infection and the virus variant., Methods: Our analyses are based on the population-based cohort study for digital health research in Germany (DigiHero). Respondents who reported a SARS-CoV-2 infection and COVID-related symptoms ≥ 12 weeks post-infection were classified as having PCC. Those with ongoing PCC were followed-up in six-month intervals based on their date of infection. We used a Cox model for interval-censored data to analyze PCC recovery., Results: Among the 4,529 respondents with PCC included in our analyses, about 26%, 19%, 36%, and 44% of those infected during dominance of the SARS-CoV-2 wildtype, Alpha, Delta, and Omicron variant had recovered one year after infection, respectively. When stratifying by virus variant, vaccination was not associated with a faster recovery. Conversely, those infected with Omicron (HR = 2.20; 95%CI: 1.96-2.48) or Delta (HR = 1.69; 95%CI: 1.43-2.01) recovered faster than those infected with the SARS-CoV-2 wildtype or Alpha strain., Conclusion: Although the recovery from PCC is faster for the newer virus variants, still a substantial fraction of those who developed PCC after an infection with the Omicron variant report prolonged persistence of symptoms., Competing Interests: Declarations Ethics approval and consent to participate The responsible Ethics Committee of the Martin Luther University Halle-Wittenverg provided ethical approval (Registration number 2020-076). Informed consent was obtained from all participants. Competing interests The authors declare no competing interests., (© 2024. The Author(s).)
Published: 2024
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31. Likelihood of Post-COVID Condition in people with hybrid immunity; data from the German National Cohort (NAKO).

Author: Mikolajczyk R, Diexer S, Klee B, Pfrommer L, Purschke O, Fricke J, Ahnert P, Gabrysch S, Gottschick C, Bohn B, Brenner H, Buck C, Castell S, Gastell S, Greiser KH, Harth V, Heise JK, Holleczek B, Kaaks R, Keil T, Krist L, Leitzmann M, Lieb W, Meinke-Franze C, Michels KB, Velásquez IM, Obi N, Panreck L, Peters A, Pischon T, Schikowski T, Schmidt B, Standl M, Stang A, Völzke H, Weber A, Zeeb H, and Karch A
Subjects: Humans, Germany epidemiology, Male, Female, Middle Aged, Adult, Risk Factors, Aged, Cohort Studies, Post-Acute COVID-19 Syndrome, Vaccination statistics & numerical data, Young Adult, COVID-19 Vaccines immunology, COVID-19 Vaccines administration & dosage, COVID-19 epidemiology, COVID-19 immunology, SARS-CoV-2 immunology
Abstract: Objectives: The risk of Post-COVID-19 condition (PCC) under hybrid immunity remains unclear., Methods: Using data from the German National Cohort (NAKO Gesundheitsstudie), we investigated risk factors for self-reported post-infection symptoms (any PCC is defined as having at least one symptom, and high symptom burden PCC as having nine or more symptoms)., Results: Sixty percent of 109,707 participants reported at least one previous SARS-CoV-2 infection; 35% reported having had any symptoms 4-12 months after infection; among them 23% reported nine or more symptoms. Individuals, who did not develop PCC after their first infection, had a strongly reduced risk for PCC after their second infection (50%) and a temporary risk reduction, which waned over 9 months after the preceding infection. The risk of developing PCC strongly depended on the virus variant. Within variants, there was no effect of the number of preceding vaccinations, apart from a strong protection by the fourth vaccination compared to three vaccinations for the Omicron variant (odds ratio = 0.52; 95% confidence interval 0.45-0.61)., Conclusions: Previous infections without PCC and a fourth vaccination were associated with a lower risk of PCC after a new infection, indicating diminished risk under hybrid immunity. The two components of risk reduction after a preceding infection suggest different immunological mechanisms., Competing Interests: Declaration of Competing Interest None., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Published: 2024
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32. The contribution of SARS-CoV-2 to the burden of acute respiratory infections in winter season 2022/2023: results from the DigiHero study.

Author: Glaser N, Diexer S, Klee B, Purschke O, Binder M, Frese T, Girndt M, Höll J, Moor I, Rosendahl J, Gekle M, Sedding D, Mikolajczyk R, and Gottschick C
Subjects: Humans, Germany epidemiology, Adult, Middle Aged, Male, Female, Incidence, Aged, Adolescent, Young Adult, Child, Child, Preschool, Infant, Aged, 80 and over, Infant, Newborn, Acute Disease epidemiology, COVID-19 epidemiology, Seasons, Respiratory Tract Infections epidemiology, Respiratory Tract Infections virology, SARS-CoV-2
Abstract: Objectives: In winter of 2022/2023 SARS-CoV-2 had developed into one of many seasonal respiratory pathogens, causing an additional burden of acute respiratory infections (ARIs). Although testing was still widely used, many positive tests were not reported for the official statistics. Using data from a population-based cohort, we aimed to investigate the contribution of SARS-CoV-2 to the burden of ARI., Methods: Over 70,000 participants of the German population-based DigiHero study were invited to a questionnaire about the number and time point of ARI and SARS-CoV-2 test results in winter 2022/2023. We calculated the incidence of non-severe acute respiratory syndrome (SARS) ARI, the additional contribution of SARS-CoV-2, and extrapolated the age-specific estimates to obtain the total burden of SARS-CoV-2 in Germany., Results: For the winter of 2022/2023, 37,708 participants reported 54,813 ARIs, including 9358 SARS-CoV-2 infections. This translated into a cumulative incidence of 145 infections/100 persons for all ARIs, 120 infections/100 persons for non-SARS ARI, and 25 infections/100 persons for SARS ARI (+21%)., Conclusions: Our estimate for ARI related to SARS-CoV-2 is consistent with the difference in all ARI between pre-pandemic years and 2022/2023. This additional burden should be considered, particularly, with respect to the implications for the work force., Competing Interests: Declarations of competing interest The authors have no competing interest to declare., (Copyright © 2024 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Published: 2024
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33. Insights into early recovery from Long COVID-results from the German DigiHero Cohort.

Author: Diexer S, Klee B, Gottschick C, Broda A, Purschke O, Binder M, Gekle M, Girndt M, Hoell JI, Moor I, Sedding D, Rosendahl J, and Mikolajczyk R
Subjects: Male, Humans, SARS-CoV-2, Principal Component Analysis, Post-Acute COVID-19 Syndrome, COVID-19
Abstract: 65 million people worldwide are estimated to suffer from long-term symptoms after their SARS-CoV-2 infection (Long COVID). However, there is still little information about the early recovery among those who initially developed Long COVID, i.e. had symptoms 4-12 weeks after infection but no symptoms after 12 weeks. We aimed to identify associated factors with this early recovery. We used data from SARS-CoV-2-infected individuals from the DigiHero study. Participants provided information about their SARS-CoV-2 infections and symptoms at the time of infection, 4-12 weeks, and more than 12 weeks post-infection. We performed multivariable logistic regression to identify factors associated with early recovery from Long COVID and principal component analysis (PCA) to identify groups among symptoms. 5098 participants reported symptoms at 4-12 weeks after their SARS-CoV-2 infection, of which 2441 (48%) reported no symptoms after 12 weeks. Men, younger participants, individuals with mild course of acute infection, individuals infected with the Omicron variant, and individuals who did not seek medical care in the 4-12 week period after infection had a higher chance of early recovery. In the PCA, we identified four distinct symptom groups. Our results indicate differential risk of continuing symptoms among individuals who developed Long COVID. The identified risk factors are similar to those for the development of Long COVID, so people with these characteristics are at higher risk not only for developing Long COVID, but also for longer persistence of symptoms. Those who sought medical help were also more likely to have persistent symptoms., (© 2024. The Author(s).)
Published: 2024
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34. To Remind or Not to Remind During Recruitment? An Analysis of an Online Panel in Germany.

Author: Klee B, Costa D, Frese T, Knoechelmann A, Meyer G, Meyer T, Purschke O, Schildmann J, Steckelberg A, and Mikolajczyk R
Subjects: Humans, Germany, Surveys and Questionnaires
Abstract: Objective: To explore the role of reminders in recruiting and maintaining participation in an online panel. Methods: 50,045 individuals from five German federal states were invited by regular mail to participate in the online study "Health-Related Beliefs and Healthcare Experiences in Germany." Those who did not respond to the first attempt received a postal reminder. Comparisons of sociodemographic characteristics and responses were made between first-attempt respondents and those who enrolled after the second letter. Results: After the initial letter, 2,216 (4.4%, 95%CI: 4.3%-4.6%) registered for the study; after a reminder 1,130 (2.5%, 2.3%-2.6% of those reminded) enrolled. Minor sociodemographic differences were observed between the groups and the content of the responses did not differ. Second-attempt respondents were less likely to participate in subsequent questionnaires: 67.3% of first-attempt vs. 43.3% of second-attempt respondents participated in their fourth survey. Recruitment costs were 79% higher for second-attempt respondents. Conclusion: While reminders increased the number of participants, lower cost-effectiveness and higher attrition of second-attempt respondents support the use of single invitation only for studies with a similar design to ours when the overall participation is low., Competing Interests: The authors declare that they do not have any conflicts of interest., (Copyright © 2024 Klee, Costa, Frese, Knoechelmann, Meyer, Meyer, Purschke, Schildmann, Steckelberg and Mikolajczyk.)
Published: 2024
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35. Association between virus variants, vaccination, previous infections, and post-COVID-19 risk.

Author: Diexer S, Klee B, Gottschick C, Xu C, Broda A, Purschke O, Binder M, Frese T, Girndt M, Hoell JI, Moor I, Gekle M, and Mikolajczyk R
Subjects: Humans, SARS-CoV-2, Odds Ratio, Vaccination, COVID-19 epidemiology, COVID-19 prevention & control
Abstract: Objectives: The SARS-CoV-2 Omicron variant has spread rapidly and has been the dominant variant since 2022. The course of acute infection, in a vaccinated population, with Omicron is milder compared with earlier variants. However, little is known about how the occurrence of long-term symptoms after Omicron infection compared with other variants is modulated by previous infections and/or vaccinations., Methods: Participants of the DigiHero study provided information about their SARS-CoV-2 infections, vaccinations, and symptoms 12 or more weeks after infection (post-COVID-19 condition - PCC)., Results: Participants infected with wildtype SARS-CoV-2 had the highest PCC risk (adjusted odds ratio [aOR] 6.44, 95% confidence interval (CI): 5.49; 7.56), followed by participants infected with Alpha and Delta compared with the reference group (individuals infected with Omicron having received three or more vaccinations). Among those infected with a specific variant, the number of preceding vaccinations was not associated with a risk reduction for PCC, whereas previous infection was strongly associated with a lower PCC risk (aOR 0.14, 95% CI 0.07; 0.25)., Conclusions: While infection with Omicron is less likely to result in PCC compared with previous variants, lack of protection by vaccination suggests a substantial challenge for the healthcare system during the early endemic period. In the midterm, the protective effects of previous infections can reduce the burden of PCC., Competing Interests: Declarations of competing interest The authors have no competing interests to declare., (Copyright © 2023 The Author(s). Published by Elsevier Ltd.. All rights reserved.)
Published: 2023
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36. T cell repertoire breadth is associated with the number of acute respiratory infections in the LoewenKIDS birth cohort.

Author: Paschold L, Gottschick C, Langer S, Klee B, Diexer S, Aksentijevich I, Schultheiß C, Purschke O, Riese P, Trittel S, Haase R, Dressler F, Eberl W, Hübner J, Strowig T, Guzman CA, Mikolajczyk R, and Binder M
Subjects: Infant, Female, Humans, Birth Cohort, Thymus Gland, B-Lymphocytes, T-Lymphocytes, Respiratory Tract Infections
Abstract: We set out to gain insight into peripheral blood B and T cell repertoires from 120 infants of the LoewenKIDS birth cohort to investigate potential determinants of early life respiratory infections. Low antigen-dependent somatic hypermutation of B cell repertoires, as well as low T and B cell repertoire clonality, high diversity, and high richness especially in public T cell clonotypes reflected the immunological naivety at 12 months of age when high thymic and bone marrow output are associated with relatively few prior antigen encounters. Infants with inadequately low T cell repertoire diversity or high clonality showed higher numbers of acute respiratory infections over the first 4 years of life. No correlation of T or B cell repertoire metrics with other parameters such as sex, birth mode, older siblings, pets, the onset of daycare, or duration of breast feeding was noted. Together, this study supports that-regardless of T cell functionality-the breadth of the T cell repertoire is associated with the number of acute respiratory infections in the first 4 years of life. Moreover, this study provides a valuable resource of millions of T and B cell receptor sequences from infants with available metadata for researchers in the field., (© 2023. The Author(s).)
Published: 2023
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37. [BeoNet-Halle-development of a multifunctional database for the automated extraction of healthcare data from general practitioner and specialist practices].

Author: Moser K, Mikolajczyk R, Bauer A, Tiller D, Christoph J, Purschke O, Lückmann SL, and Frese T
Subjects: Humans, Germany, Academic Medical Centers, Delivery of Health Care, General Practitioners, General Practice
Abstract: The Beobachtungspraxennetzwerk Halle (BeoNet-Halle) is an innovative database of outpatient care that has been collecting patient data from participating primary care and specialty practices throughout Germany since 2020 and making it available for research and care. The database is set up and maintained by the Institute of Medical Epidemiology, Biometrics and Informatics and the Institute of General Practice and Family Medicine of the Martin Luther University Halle-Wittenberg. Furthermore, the Data Integration Center of the University Medical Center Halle is involved in the project. In principle, anonymized and pseudonymized patient data from all commercially available practice management systems should flow into the databases.In this article, we describe the structure and methods of the multi-purpose database BeoNet and quantify the current data stock. The workflow of collection, transfer, and storage of broad consents is described and advantages and limitations of the database are discussed.BeoNet-Halle currently contains anonymized data of approximately 73,043 patients from five physician practices. Furthermore, it includes data from more than 2,653,437 ICD-10 diagnoses, 1,403,726 prescriptions, and 1,894,074 laboratory results. Pseudonymized data were successfully exported from 481 patients.BeoNet-Halle enables an almost seamless representation of the care provided in the participating practices. In the future, the database will map patient treatment pathways across practices and provide high-quality care data to contribute to health policy decision-making and optimization of care processes., (© 2023. The Author(s).)
Published: 2023
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38. Anxiety, depressive symptoms, and distress over the course of the war in Ukraine in three federal states in Germany.

Author: Massag J, Diexer S, Klee B, Costa D, Gottschick C, Broda A, Purschke O, Opel N, Binder M, Sedding D, Frese T, Girndt M, Hoell J, Moor I, Rosendahl J, Gekle M, and Mikolajczyk R
Abstract: Introduction: The Russian invasion of Ukraine and the resulting consequences are in the center of political discussions, media, and likely individual thinking of the population in Germany. Yet, the impact of this prolonged exposure on mental health is not known hitherto., Methods: Using the population based cohort study DigiHero from three federal states (Saxony-Anhalt, Saxony, and Bavaria), we assessed anxiety levels (GAD-7), depressive symptoms (PHQ-9), and distress (modified PDI) in the first weeks of war and 6 months later., Results: Of those 19,432, who responded in the first weeks of war, 13,934 (71.1%) responded also 6 months later. While anxiety and emotional distress decreased during the 6 months, their average scores were still elevated, and a substantial fraction of respondents displayed clinically relevant sequelae. Persons from low-income households were especially affected, specifically by fears related to the personal financial situation. Those who reacted with a particularly strong fear in the beginning of war were more likely to have persistent clinically relevant symptoms of depression and anxiety also 6 months later., Discussion: The Russian invasion of Ukraine is accompanied by continuing impairment of mental health in the German population. Fears surrounding the personal financial situation are a strong determinant., Competing Interests: The authors declare that the research was conducted in the absence of any commercial or financial relationships that could be construed as a potential conflict of interest., (Copyright © 2023 Massag, Diexer, Klee, Costa, Gottschick, Broda, Purschke, Opel, Binder, Sedding, Frese, Girndt, Hoell, Moor, Rosendahl, Gekle and Mikolajczyk.)
Published: 2023
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39. Mental health in Germany in the first weeks of the Russo-Ukrainian war.

Author: Gottschick C, Diexer S, Massag J, Klee B, Broda A, Purschke O, Binder M, Sedding D, Frese T, Girndt M, Hoell JI, Michl P, Gekle M, and Mikolajczyk R
Abstract: Background: In the connected world, although societies are not directly involved in a military conflict, they are exposed to media reports of violence., Aims: We assessed the effects of such exposures on mental health in Germany during the military conflict in Ukraine., Method: We used the German population-based cohort for digital health research, DigiHero, launching a survey on the eighth day of the Russo-Ukrainian war. Of the 27 509 cohort participants from the general population, 19 444 (70.7%) responded within 17 days. We measured mental health and fear of the impact of war compared with other fears (natural disasters or health-related)., Results: In a subsample of 4441 participants assessed twice, anxiety in the population (measured by the Generalised Anxiety Disorder-7 screener) was higher in the first weeks of war than during the strongest COVID-19 restrictions. Anxiety was elevated across the whole age spectrum, and the mean was above the cut-off for mild anxiety. Over 95% of participants expressed various degrees of fear of the impact of war, whereas the percentage for other investigated fears was 0.47-0.82. A one-point difference in the fear of the impact of war was associated with a 2.5 point (95% CI 2.42-2.58) increase in anxiety (11.9% of the maximum anxiety score). For emotional distress, the increase was 0.67 points (0.66-0.68) (16.75% of the maximum score)., Conclusions: The population in Germany reacted to the Russo-Ukrainian war with substantial distress, exceeding reactions during the strongest restrictions in the COVID-19 pandemic. Fear of the impact of war was associated with worse mental health.
Published: 2023
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40. Symptom Burden and Factors Associated with Acute Respiratory Infections in the First Two Years of Life-Results from the LoewenKIDS Cohort.

Author: Langer S, Horn J, Gottschick C, Klee B, Purschke O, Caputo M, Dorendorf E, Meyer-Schlinkmann KM, Raupach-Rosin H, Karch A, Rübsamen N, Aydogdu M, Buhles M, Dressler F, Eberl W, Koch FEV, Frambach T, Franz H, Guthmann F, Guzman CA, Haase R, Hansen G, Heselich V, Hübner J, Koch HG, Oberhoff C, Riese P, Schild R, Seeger S, Tchirikov M, Trittel S, von Kaisenberg C, and Mikolajczyk R
Abstract: Acute respiratory infections (ARIs) are the most common childhood illnesses worldwide whereby the reported frequency varies widely, often depending on type of assessment. Symptom diaries are a powerful tool to counteract possible under-reporting, particularly of milder infections, and thus offer the possibility to assess the full burden of ARIs. The following analyses are based on symptom diaries from participants of the German birth cohort study LoewenKIDS. Primary analyses included frequencies of ARIs and specific symptoms. Factors, which might be associated with an increased number of ARIs, were identified using the Poisson regression. A subsample of two hundred eighty-eight participants were included. On average, 13.7 ARIs (SD: 5.2 median: 14.0 IQR: 10-17) were reported in the first two years of life with an average duration of 11 days per episode (SD: 5.8, median: 9.7, IQR: 7-14). The median age for the first ARI episode was 91 days (IQR: 57-128, mean: 107, SD: 84.5). Childcare attendance and having siblings were associated with an increased frequency of ARIs, while exclusive breastfeeding for the first three months was associated with less ARIs, compared to exclusive breastfeeding for a longer period. This study provides detailed insight into the symptom burden of ARIs in German infants.
Published: 2022
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41. Disturbed habitats locally reduce the signal of deep evolutionary history in functional traits of plants.

Author: Prinzing A, Pavoine S, Jactel H, Hortal J, Hennekens SM, Ozinga WA, Bartish IV, Helmus MR, Kühn I, Moen DS, Weiher E, Brändle M, Winter M, Violle C, Venail P, Purschke O, and Yguel B
Subjects: Biodiversity, Phenotype, Phylogeny, Plants genetics, Biological Evolution, Ecosystem
Abstract: The functioning of present ecosystems reflects deep evolutionary history of locally cooccurring species if their functional traits show high phylogenetic signal (PS). However, we do not understand what drives local PS. We hypothesize that local PS is high in undisturbed and stressful habitats, either due to ongoing local assembly of species that maintained ancestral traits, or to past evolutionary maintenance of ancestral traits within habitat species-pools, or to both. We quantified PS and diversity of 10 traits within 6704 local plant communities across 38 Dutch habitat types differing in disturbance or stress. Mean local PS varied 50-fold among habitat types, often independently of phylogenetic or trait diversity. Mean local PS decreased with disturbance but showed no consistent relationship to stress. Mean local PS exceeded species-pool PS, reflecting nonrandom subsampling from the pool. Disturbance or stress related more strongly to mean local than to species-pool PS. Disturbed habitats harbour species with evolutionary divergent trait values, probably driven by ongoing, local assembly of species: environmental fluctuations might maintain different trait values within lineages through an evolutionary storage effect. If functional traits do not reflect phylogeny, ecosystem functioning might not be contingent on the presence of particular lineages, and lineages might establish evolutionarily novel interactions., (© 2021 The Authors. New Phytologist © 2021 New Phytologist Foundation.)
Published: 2021
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42. The risk of indoor sports and culture events for the transmission of COVID-19.

Author: Moritz S, Gottschick C, Horn J, Popp M, Langer S, Klee B, Purschke O, Gekle M, Ihling A, Zimmermann FDL, and Mikolajczyk R
Subjects: Aerosols, COVID-19 diagnosis, COVID-19 virology, Computer Simulation, Disease Transmission, Infectious prevention & control, Humans, SARS-CoV-2 genetics, SARS-CoV-2 isolation & purification, Air Pollution, Indoor prevention & control, COVID-19 transmission, Hygiene standards, SARS-CoV-2 pathogenicity, Ventilation methods
Abstract: Nearly all mass gathering events worldwide were banned at the beginning of the COVID-19 pandemic, as they were suspected of presenting a considerable risk for the transmission of SARS-CoV-2. We investigated the risk of transmitting SARS-CoV-2 by droplets and aerosols during an experimental indoor mass gathering event under three different hygiene practices, and used the data in a simulation study to estimate the resulting burden of disease under conditions of controlled epidemics. Our results show that the mean number of measured direct contacts per visitor was nine persons and this can be reduced substantially by appropriate hygiene practices. A comparison of two versions of ventilation with different air exchange rates and different airflows found that the system which performed worst allowed a ten-fold increase in the number of individuals exposed to infectious aerosols. The overall burden of infections resulting from indoor mass gatherings depends largely on the quality of the ventilation system and the hygiene practices. Presuming an effective ventilation system, indoor mass gathering events with suitable hygiene practices have a very small, if any, effect on epidemic spread., (© 2021. The Author(s).)
Published: 2021
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43. Author Correction: A global database for metacommunity ecology, integrating species, traits, environment and space.

Author: Jeliazkov A, Mijatovic D, Chantepie S, Andrew N, Arlettaz R, Barbaro L, Barsoum N, Bartonova A, Belskaya E, Bonada N, Brind'Amour A, Carvalho R, Castro H, Chmura D, Choler P, Chong-Seng K, Cleary D, Cormont A, Cornwell W, de Campos R, de Voogd N, Doledec S, Drew J, Dziock F, Eallonardo A, Edgar MJ, Farneda F, Hernandez DF, Frenette-Dussault C, Fried G, Gallardo B, Gibb H, Gonçalves-Souza T, Higuti J, Humbert JY, Krasnov BR, Saux EL, Lindo Z, Lopez-Baucells A, Lowe E, Marteinsdottir B, Martens K, Meffert P, Mellado-Díaz A, Menz MHM, Meyer CFJ, Miranda JR, Mouillot D, Ossola A, Pakeman R, Pavoine S, Pekin B, Pino J, Pocheville A, Pomati F, Poschlod P, Prentice HC, Purschke O, Raevel V, Reitalu T, Renema W, Ribera I, Robinson N, Robroek B, Rocha R, Shieh SH, Spake R, Staniaszek-Kik M, Stanko M, Tejerina-Garro FL, Braak CT, Urban MC, Klink RV, Villéger S, Wegman R, Westgate MJ, Wolff J, Żarnowiec J, Zolotarev M, and Chase JM
Abstract: An amendment to this paper has been published and can be accessed via a link at the top of the paper.
Published: 2020
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44. Similar factors underlie tree abundance in forests in native and alien ranges.

Author: van der Sande MT, 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 GR, Gutiérrez AG, Jandt U, Jansen F, Jiménez-Alfaro B, Kattge J, Kearsley E, Klotz S, Kramer K, Moretti M, Niinemets Ü, Peet RK, Penuelas J, Petřík P, Reich PB, Sandel B, Schmidt M, Sibikova M, Violle C, Whitfeld TJS, Wohlgemuth T, and Knight TM
Abstract: Aim: Alien 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., Location: Global., Time Period: Recent., Major Taxa Studied: Trees., Methods: We 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., Results: In 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 Conclusions: Our 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., (© 2019 The Authors. Global Ecology and Biogeography published by John Wiley & Sons Ltd.)
Published: 2020
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45. A global database for metacommunity ecology, integrating species, traits, environment and space.

Author: Jeliazkov A, Mijatovic D, Chantepie S, Andrew N, Arlettaz R, Barbaro L, Barsoum N, Bartonova A, Belskaya E, Bonada N, Brind'Amour A, Carvalho R, Castro H, Chmura D, Choler P, Chong-Seng K, Cleary D, Cormont A, Cornwell W, de Campos R, de Voogd N, Doledec S, Drew J, Dziock F, Eallonardo A, Edgar MJ, Farneda F, Hernandez DF, Frenette-Dussault C, Fried G, Gallardo B, Gibb H, Gonçalves-Souza T, Higuti J, Humbert JY, Krasnov BR, Saux EL, Lindo Z, Lopez-Baucells A, Lowe E, Marteinsdottir B, Martens K, Meffert P, Mellado-Díaz A, Menz MHM, Meyer CFJ, Miranda JR, Mouillot D, Ossola A, Pakeman R, Pavoine S, Pekin B, Pino J, Pocheville A, Pomati F, Poschlod P, Prentice HC, Purschke O, Raevel V, Reitalu T, Renema W, Ribera I, Robinson N, Robroek B, Rocha R, Shieh SH, Spake R, Staniaszek-Kik M, Stanko M, Tejerina-Garro FL, Braak CT, Urban MC, Klink RV, Villéger S, Wegman R, Westgate MJ, Wolff J, Żarnowiec J, Zolotarev M, and Chase JM
Subjects: Animals, Biodiversity, Ecology, Plants, Biota
Abstract: The use of functional information in the form of species traits plays an important role in explaining biodiversity patterns and responses to environmental changes. Although relationships between species composition, their traits, and the environment have been extensively studied on a case-by-case basis, results are variable, and it remains unclear how generalizable these relationships are across ecosystems, taxa and spatial scales. To address this gap, we collated 80 datasets from trait-based studies into a global database for metaCommunity Ecology: Species, Traits, Environment and Space; "CESTES". Each dataset includes four matrices: species community abundances or presences/absences across multiple sites, species trait information, environmental variables and spatial coordinates of the sampling sites. The CESTES database is a live database: it will be maintained and expanded in the future as new datasets become available. By its harmonized structure, and the diversity of ecosystem types, taxonomic groups, and spatial scales it covers, the CESTES database provides an important opportunity for synthetic trait-based research in community ecology.
Published: 2020
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46. Global trait-environment relationships of plant communities.

Author: Bruelheide H, Dengler J, Purschke O, Lenoir J, Jiménez-Alfaro B, Hennekens SM, Botta-Dukát Z, Chytrý M, Field R, Jansen F, Kattge J, Pillar VD, Schrodt F, Mahecha MD, Peet RK, Sandel B, van Bodegom P, Altman J, Alvarez-Dávila E, Arfin Khan MAS, Attorre F, Aubin I, Baraloto C, Barroso JG, Bauters M, Bergmeier E, Biurrun I, Bjorkman AD, Blonder B, Čarni A, Cayuela L, Černý T, Cornelissen JHC, Craven D, Dainese M, Derroire G, De Sanctis M, Díaz S, Doležal J, Farfan-Rios W, Feldpausch TR, Fenton NJ, Garnier E, Guerin GR, Gutiérrez AG, Haider S, Hattab T, Henry G, Hérault B, Higuchi P, Hölzel N, Homeier J, Jentsch A, Jürgens N, Kącki Z, Karger DN, Kessler M, Kleyer M, Knollová I, Korolyuk AY, Kühn I, Laughlin DC, Lens F, Loos J, Louault F, Lyubenova MI, Malhi Y, Marcenò C, Mencuccini M, Müller JV, Munzinger J, Myers-Smith IH, Neill DA, Niinemets Ü, Orwin KH, Ozinga WA, Penuelas J, Pérez-Haase A, Petřík P, Phillips OL, Pärtel M, Reich PB, Römermann C, Rodrigues AV, Sabatini FM, Sardans J, Schmidt M, Seidler G, Silva Espejo JE, Silveira M, Smyth A, Sporbert M, Svenning JC, Tang Z, Thomas R, Tsiripidis I, Vassilev K, Violle C, Virtanen R, Weiher E, Welk E, Wesche K, Winter M, Wirth C, and Jandt U
Subjects: Forests, Grassland, Life History Traits, Plant Dispersal, Plants
Abstract: Plant functional traits directly affect ecosystem functions. At the species level, trait combinations depend on trade-offs representing different ecological strategies, but at the community level trait combinations are expected to be decoupled from these trade-offs because different strategies can facilitate co-existence within communities. A key question is to what extent community-level trait composition is globally filtered and how well it is related to global versus local environmental drivers. Here, we perform a global, plot-level analysis of trait-environment relationships, using a database with more than 1.1 million vegetation plots and 26,632 plant species with trait information. Although we found a strong filtering of 17 functional traits, similar climate and soil conditions support communities differing greatly in mean trait values. The two main community trait axes that capture half of the global trait variation (plant stature and resource acquisitiveness) reflect the trade-offs at the species level but are weakly associated with climate and soil conditions at the global scale. Similarly, within-plot trait variation does not vary systematically with macro-environment. Our results indicate that, at fine spatial grain, macro-environmental drivers are much less important for functional trait composition than has been assumed from floristic analyses restricted to co-occurrence in large grid cells. Instead, trait combinations seem to be predominantly filtered by local-scale factors such as disturbance, fine-scale soil conditions, niche partitioning and biotic interactions.
Published: 2018
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47. Embracing scale-dependence to achieve a deeper understanding of biodiversity and its change across communities.

Author: Chase JM, McGill BJ, McGlinn DJ, May F, Blowes SA, Xiao X, Knight TM, Purschke O, and Gotelli NJ
Subjects: Biodiversity, Ecology
Abstract: Because biodiversity is multidimensional and scale-dependent, it is challenging to estimate its change. However, it is unclear (1) how much scale-dependence matters for empirical studies, and (2) if it does matter, how exactly we should quantify biodiversity change. To address the first question, we analysed studies with comparisons among multiple assemblages, and found that rarefaction curves frequently crossed, implying reversals in the ranking of species richness across spatial scales. Moreover, the most frequently measured aspect of diversity - species richness - was poorly correlated with other measures of diversity. Second, we collated studies that included spatial scale in their estimates of biodiversity change in response to ecological drivers and found frequent and strong scale-dependence, including nearly 10% of studies which showed that biodiversity changes switched directions across scales. Having established the complexity of empirical biodiversity comparisons, we describe a synthesis of methods based on rarefaction curves that allow more explicit analyses of spatial and sampling effects on biodiversity comparisons. We use a case study of nutrient additions in experimental ponds to illustrate how this multi-dimensional and multi-scale perspective informs the responses of biodiversity to ecological drivers., (© 2018 John Wiley & Sons Ltd/CNRS.)
Published: 2018
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48. Biodiversity and ecosystem functioning relations in European forests depend on environmental context.

Author: Ratcliffe S, Wirth C, Jucker T, van der Plas F, Scherer-Lorenzen M, Verheyen K, Allan E, Benavides R, Bruelheide H, Ohse B, Paquette A, Ampoorter E, Bastias CC, Bauhus J, Bonal D, Bouriaud O, Bussotti F, Carnol M, Castagneyrol B, Chećko E, Dawud SM, Wandeler H, Domisch T, Finér L, Fischer M, Fotelli M, Gessler A, Granier A, Grossiord C, Guyot V, Haase J, Hättenschwiler S, Jactel H, Jaroszewicz B, Joly FX, Kambach S, Kolb S, Koricheva J, Liebersgesell M, Milligan H, Müller S, Muys B, Nguyen D, Nock C, Pollastrini M, Purschke O, Radoglou K, Raulund-Rasmussen K, Roger F, Ruiz-Benito P, Seidl R, Selvi F, Seiferling I, Stenlid J, Valladares F, Vesterdal L, and Baeten L
Subjects: Climate Change, Europe, Biodiversity, Ecosystem, Forests
Abstract: The importance of biodiversity in supporting ecosystem functioning is generally well accepted. However, most evidence comes from small-scale studies, and scaling-up patterns of biodiversity-ecosystem functioning (B-EF) remains challenging, in part because the importance of environmental factors in shaping B-EF relations is poorly understood. Using a forest research platform in which 26 ecosystem functions were measured along gradients of tree species richness in six regions across Europe, we investigated the extent and the potential drivers of context dependency of B-EF relations. Despite considerable variation in species richness effects across the continent, we found a tendency for stronger B-EF relations in drier climates as well as in areas with longer growing seasons and more functionally diverse tree species. The importance of water availability in driving context dependency suggests that as water limitation increases under climate change, biodiversity may become even more important to support high levels of functioning in European forests., (© 2017 John Wiley & Sons Ltd/CNRS.)
Published: 2017
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49. Climate warming promotes species diversity, but with greater taxonomic redundancy, in complex environments.

Author: Thakur MP, Tilman D, Purschke O, Ciobanu M, Cowles J, Isbell F, Wragg PD, and Eisenhauer N
Subjects: Animals, Biomass, Nematoda, Plants, Soil parasitology, Biodiversity, Climate, DNA Barcoding, Taxonomic, Environment, Global Warming
Abstract: Climate warming is predicted to alter species interactions, which could potentially lead to extinction events. However, there is an ongoing debate whether the effects of warming on biodiversity may be moderated by biodiversity itself. We tested warming effects on soil nematodes, one of the most diverse and abundant metazoans in terrestrial ecosystems, along a gradient of environmental complexity created by a gradient of plant species richness. Warming increased nematode species diversity in complex (16-species mixtures) plant communities (by ~36%) but decreased it in simple (monocultures) plant communities (by ~39%) compared to ambient temperature. Further, warming led to higher levels of taxonomic relatedness in nematode communities across all levels of plant species richness. Our results highlight both the need for maintaining species-rich plant communities to help offset detrimental warming effects and the inability of species-rich plant communities to maintain nematode taxonomic distinctness when warming occur.
Published: 2017
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50. A guide to phylogenetic metrics for conservation, community ecology and macroecology.

Author: Tucker CM, Cadotte MW, Carvalho SB, Davies TJ, Ferrier S, Fritz SA, Grenyer R, Helmus MR, Jin LS, Mooers AO, Pavoine S, Purschke O, Redding DW, Rosauer DF, Winter M, and Mazel F
Subjects: Biodiversity, Biological Evolution, Conservation of Natural Resources methods, Ecology methods, Phylogeny
Abstract: The use of phylogenies in ecology is increasingly common and has broadened our understanding of biological diversity. Ecological sub-disciplines, particularly conservation, community ecology and macroecology, all recognize the value of evolutionary relationships but the resulting development of phylogenetic approaches has led to a proliferation of phylogenetic diversity metrics. The use of many metrics across the sub-disciplines hampers potential meta-analyses, syntheses, and generalizations of existing results. Further, there is no guide for selecting the appropriate metric for a given question, and different metrics are frequently used to address similar questions. To improve the choice, application, and interpretation of phylo-diversity metrics, we organize existing metrics by expanding on a unifying framework for phylogenetic information. Generally, questions about phylogenetic relationships within or between assemblages tend to ask three types of question: how much; how different; or how regular? We show that these questions reflect three dimensions of a phylogenetic tree: richness, divergence, and regularity. We classify 70 existing phylo-diversity metrics based on their mathematical form within these three dimensions and identify 'anchor' representatives: for α-diversity metrics these are PD (Faith's phylogenetic diversity), MPD (mean pairwise distance), and VPD (variation of pairwise distances). By analysing mathematical formulae and using simulations, we use this framework to identify metrics that mix dimensions, and we provide a guide to choosing and using the most appropriate metrics. We show that metric choice requires connecting the research question with the correct dimension of the framework and that there are logical approaches to selecting and interpreting metrics. The guide outlined herein will help researchers navigate the current jungle of indices., (© 2016 The Authors. Biological Reviews published by John Wiley © Sons Ltd on behalf of Cambridge Philosophical Society.)
Published: 2017
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