103 results on '"Mayrose, I."'
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2. TRY plant trait database – enhanced coverage and open access
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Kattge, J., Bonisch, G., Diaz, S., Lavorel, S., Prentice, I. C., Leadley, P., Tautenhahn, S., Werner, G. D. A., Aakala, T., Abedi, M., Acosta, A. T. R., Adamidis, G. C., Adamson, K., Aiba, M., Albert, C. H., Alcantara, J. M., Alcazar, C C., Aleixo, I., Ali, H., Amiaud, B., Ammer, C., Amoroso, M. M., Anand, M., Anderson, C., Anten, N., Antos, J., Apgaua, D. M. G., Ashman, T. L., Asmara, D. H., Asner, G. P., Aspinwall, M., Atkin, O., Aubin, I., Baastrup-Spohr, L., Bahalkeh, K., Bahn, M., Baker, T., Baker, W. J., Bakker, J. P., Baldocchi, D., Baltzer, J., Banerjee, A., Baranger, A., Barlow, J., Barneche, D. R., Baruch, Z., Bastianelli, D., Battles, J., Bauerle, W., Bauters, M., Bazzato, E., Beckmann, M., Beeckman, H., Beierkuhnlein, C., Bekker, R., Belfry, G., Belluau, M., Beloiu, M., Benavides, R., Benomar, L., Berdugo-Lattke, M. L., Berenguer, E., Bergamin, R., Bergmann, J., Bergmann Carlucci, M., Berner, L., Bernhardt Romermann, M., Bigler, C., Bjorkman, A. D., Blackman, C., Blanco, C., Blonder, B., Blumenthal, D., Bocanegra Gonzalez, K. T., Boeckx, P., Bohlman, S., Bohning Gaese, K., Boisvert Marsh, L., Bond, W., Bond-Lamberty, B., Boom, A., Boonman, C. C. F., Bordin, K., Boughton, E. H., Boukili, V., Bowman, D. M. J. S., Bravo, S., Brende, l M. R., Broadley, M. R., Brown, K. A., Bruelheide, H., Brumnich, F., Bruun, H. H., Bruy, D., Buchanan, S. W., Bucher, S. F., Buchmann, N., Buitenwerf, R., Bunker, D. E., Burge, r J., Burrascano, S., Burslem, D. F. R. P., Butterfield, B. J., Byun, C., Marques, M., Scalon, M. C., Caccianiga, M., Cadotte, M., Cailleret, M., Camac, J., Camarero, J. J., Campany, C., Campetella, G., Campos, J. A., Cano Arboleda, L., Canullo, R., Carbognani, M., Carvalho, F., Casanoves, F., Castagneyrol, B., Catford, J. A., Cavender Bares, J., Cerabolini, B. E. L., Cervellini, M., Chacon Madrigal, E., Chapin, K., Chapin, F. S., Chelli, S., Chen, S. C., Chen, A., Cherubini, P., Chianucci, F., Choat, B., Chung, K. S., Chytry, M., Ciccarelli, D., Coll, L., Collins, C. G., Conti, L., Coomes, D., Cornelissen, J. H. C., Cornwell, W. K., Corona, P., Coyea, M., Craine, J., Craven, D., Cromsigt, J. P. G. M., Csecserits, A., Cufar, K., Cuntz, M., da Silva, A. C., Dahlin, K. M., Dainese, M., Dalke, I., Dalle Fratte, M., Dang Le, A. T., Danihelka, J., Dannoura, M., Dawson, S., de Beer, A. J., De Frutos, A., De Long, J. R., Dechant, B., Delagrange, S., Delpierre, N., Derroire, G., Dias, A. S., Diaz Toribio, M. H., Dimitrakopoulos, P. G., Dobrowolski, M., Doktor, D., Drevojan, P., Dong, N., Dransfield, J., Dressler, S., Duarte, L., Ducouret, E., Dullinger, S., Durka, W., Duursma, R., Dymova, O., E- Vojtko, A., Eckstein, R. L., Ejtehadi, H., Elser, J., Emilio, T., Engemann, K., Erfanian, M. B., Erfmeier, A., Esquivel Muelbert, A., Esser, G., Estiarte, M., Domingues, T. F., Fagan, W. F., Fagundez, J., Falster, D. S., Fan, Y., Fang, J., Farris, E., Fazlioglu, F., Feng, Y., Fernandez, Mendez, Ferrara, C., Ferreira, J., Fidelis, A., Finegan, B., Firn, J., Flowers, T. J., Flynn, D. F. B., Fontana, V., Forey, E., Forgiarini, C., Francois, L., Frangipani, M., Frank, D., Frenette Dussault, C., Freschet, G. T., Fry, E. L., Fyllas, N. M., Mazzochini, G. G., Gachet, S., Gallagher, R., Ganade, G., Ganga, F., Garcia Palacios, P., Gargaglione, V., Garnier, E., Garrido, J. L., de Gasper, A. L., Gea Izquierdo, G., Gibson, D., Gillison, A. N., Giroldo, A., Glasenhardt, M. C., Gleason, S., Gliesch, M., Goldberg, E., Goldel, B., Gonzalez Akre, E., Gonzalez Andujar, J. L., Gonzalez Melo, A., Gonzalez Robles, A., Graae, B. J., Granda, E., Graves, S., Green, W. A., Gregor, T., Gross, N., Guerin, G. R., Gunther, A., Gutierrez, A. G., Haddock, L., Haines, A., Hall, J., Hambuckers, A., Han, W., Harrison, S. P., Hattingh, W., Hawes, J. E., He, T., He, P., Heberling, J. M., Helm, A., Hempel, S., Hentschel, J., Herault, B., Heres, A. M., Herz, K., Heuertz, M., Hickler, T., Hietz, P., Higuchi, P., Hipp, A. L., Hirons, A., Hock, M., Hogan, J. A., Holl, K., Honnay, O., Hornstein, D., Hou, E., Hough Snee, N., Hovstad, K. A., Ichie, T., Igic, B., Illa, E., Isaac, M., Ishihara, M., Ivanov, L., Ivanova, L., Iversen, C. M., Izquierdo, J., Jackson, R. B., Jackson, B., Jactel, H., Jagodzinsk, A. M., Jandt, U., Jansen, S., Jenkins, T., Jentsch, A., Jespersen, J. R. P., Jiang, G. F., Johansen, J. L., Johnson, D., Jokela, E. J., Joly, C. A., Jordan, G. J., Joseph, G. S., Junaedi, D., Junker, R. R., Justes, E., Kabzems, R., Kane, J., Kaplan, Z., Kattenborn, T., Kavelenova, L., Kearsley, E., Kempel, A., Kenzo, T., Kerkhoff, A., Khalil, M. I., Kinlock, N. L., Kissling, W. D., Kitajima, K., Kitzberger, T., Kjoller, R., Klein, T., Kleyer, M., Klimesova, J., Klipel, J., Kloeppel, B., Klotz, S., Knops, J. M. H., Kohyama, T., Koike, F., Kollmann, J., Komac, B., Komatsu, K., Konig, C., Kraft, N. J. B., Kramer, K., Kreft, H., Kuhn, I., Kumarathune, D., Kuppler, J., Kurokawa, H., Kurosawa, Y., Kuyah, S., Laclau, J. P., Lafleur, B., Lallai, E., Lamb, E., Lamprecht, A., Larkin, D. J., Laughlin, D., Le Bagousse Pinguet, Y., le Maire, G., le Roux, P. C., le Roux, E., Lee, T., Lens, F., Lewis, S. L., Lhotsky, B., Li, Y., Li, X., Lichstein, J. W., Liebergesell, M., Lim, J. Y., Lin, Y. S., Linares, Y. C., Liu, C., Liu, D., Liu, U., Livingstone, S., Llusia, J., Lohbeck, M., Lopez Garcia, A., Lopez Gonzalez, G., Lososov, a Z., Louault, F., Lukacs, B. A., Lukes, P., Luo, Y., Lussu, M., Ma, S., Maciel Rabelo Pereira, C., Mack, M., Maire, V., Makela, A., Makinen, H., Malhado, A. C. M., Mallik, A., Manning, P., Manzoni, S., Marchetti, Z., Marchino, L., Marcilio Silva, V., Marcon, E., Marignani, M., Markesteijn, L., Martin, A., Martinez Garza, C., Martinez Vilalta, J., Maskova, T., Mason, K., Mason, N., Massad, T. J., Masse, J., Mayrose, I., Mccarthy, J., Mccormack, M. L., Mcculloh, K., Mcfadden, I., Mcgill, B. J., Mcpartland, M. Y., Medeiros, J., Medlyn, B., Meerts, P., Mehrabi, Z., Meir, P., Melo, F., P. L., Mencuccini, M., Meredieu, C., Messier, J., Meszaros, I., Metsaranta, J., Michaletz, S. T., Michelaki, C., Migalina, S., Milla, R., Miller, J., E. D., Minden, V., Ming, R., Mokany, K., Moles, A. T., Molnar, A., Molofsky, J., Molz, M., Montgomery, R. A., Monty, A., Moravcova, L., Moreno Martinez, A., Moretti, M., Mori, A. S., Mori, S., Morris, D., Morrison, J., Mucina, L., Mueller, S., Muir, C. D., Muller, S. C., Munoz, F., Myers Smith, I. H., Myster, R. W., Nagano, M., Naidu, S., Narayanan, A., Natesan, B., Negoita, L., Nelson, A. S., Neuschulz, E. L., Ni, J., Niedrist, G., Nieto, J., Niinemets, U., Nolan, R., Nottebrock, H., Nouvellon, Y., Novakovskiy, A., Nystuen, K. O., O'Grady, A., O'Hara, K., O'Reilly Nugent, A., Oakley, S., Oberhuber, W., Ohtsuka, T., Oliveira, R., Ollerer, K., Olson, M. E., Onipchenko, V., Onoda, Y., Onstein, R. E., Ordonez, J. C., Osada, N., Ostonen, I., Ottaviani, G., Otto, S., Overbeck, G. E., Ozinga, W. A., Pahl, A. T., Paine, C. E. T., Pakeman, R. J., Papageorgiou, A. C., Parfionova, E., Partel, M., Patacca, M., Paula, S., Paule, J., Pauli, H., Pausas, J., Peco, B., Penuelas, J., Perea, A., Peri, P. L., Petisco Souza, A. C., Petraglia, A., Petritan, A. M., Phillips, O. L., Pierce, S., Pillar, V. D., Pisek, J., Pomogaybin, A., Poorter, H., Portsmuth, A., Poschlod, P., Potvin, C., Pounds, D., Powell, A., Power, S. A., Prinzing, A., Puglielli, G., Pysek, P., Raevel, V., Rammig, A., Ransijn, J., Ray, C. A., Reich, P. B., Reichstein, M., Reid, D. E. B., Rejou Mechain, M., de Dios, V. R., Ribeiro, S., Richardson, S., Riibak, K., Rillig, M. C., Riviera, F., Robert, E. M. R., Roberts, S., Robroek, B., Roddy, A., Rodrigues, A. V., Rogers, A., Rollinson, E., Rolo, V., Romermann, C., Ronzhina, D., Roscher, C., Rosell, J. A., Rosenfield, M. F., Rossi, C., Roy, D. B., Royer Tardif, S., Ruger, N., Ruiz Peinado, R., Rumpf, S. B., Rusch, G. M., Ryo, M., Sack, L., Saldana, A., Salgado Negret, B., Salguero Gomez, R., Santa Regina, I., Santacruz Garcia, A. C., Santos, J., Sardans, J., Schamp, B., Scherer Lorenzen, M., Schleuning, M., Schmid, B., Schmidt, M., Schmitt, S., Schneider, J. V., Schowanek, S. D., Schrader, J., Schrodt, F., Schuldt, B., Schurr, F., Selaya Garvizu, G., Semchenko, M., Seymour, C., Sfair, J. C., Sharpe, J. M., Sheppard, C. S., Sheremetiev, S., Shiodera, S., Shipley, B., Shovon, T. A., Siebenkas, A., Sierra, C., Silva, V., Silva, M., Sitzia, T., Sjoman, H., Slot, M., Smith, N. G., Sodhi, D., Soltis, P., Soltis, D., Somers, B., Sonnier, G., Sorensen, M. V., Sosinski, E. E., Soudzilovskaia, N. A., Souza, A. F., Spasojevic, M., Sperandii, M. G., Stan, A. B., Stegen, J., Steinbauer, K., Stephan, J. G., Sterck, F., Stojanovic, D. B., Strydom, T., Suarez, M. L., Svenning, J. C., Svitkova, I., Svitok, M., Svoboda, M., Swaine, E., Swenson, N., Tabarelli, M., Takagi, K., Tappeiner, U., Tarifa, R., Tauugourdeau, S., Tavsanoglu, C., te Beest, M., Tedersoo, L., Thiffault, N., Thom, D., Thomas, E., Thompson, K., Thornton, P. E., Thuiller, W., Tichy, L., Tissue, D., Tjoelker, M. G., Tng, D. Y. P., Tobias, J., Torok, P., Tarin, T., Torres Ruiz, J. M., Tothmeresz, B., Treurnicht, M., Trivellone, V., Trolliet, F., Trotsiuk, V., Tsakalos, J. L., Tsiripidis, I., Tysklind, N., Umehara, T., Usoltsev, V., Vadeboncoeur, M., Vaezi, J., Valladares, F., Vamosi, J., van Bodegom, P. M., van Breugel, M., Van Cleemput, E., van de Weg, M., van der Merwe, S., van der Plas, F., van der Sande, M. T., van Kleunen, M., Van Meerbeek, K., Vanderwel, M., Vanselow, K. A., Varhammar, A., Varone, L., Vasquez Valderrama, M. Y., Vassilev, K., Vellend, M., Veneklaas, E. J., Verbeeck, H., Verheyen, K., Vibrans, A., Vieira, I., Villacis, J., Violle, C., Vivek, P., Wagner, K., Waldram, M., Waldron, A., Walker, A . P., Waller, M., Walther, G., Wang, H., Wang, F., Wang, W., Watkins, H., Watkins, J., Weber, U., Weedon, J. T., Wei, L., Weigelt, P., Weiher, E., Wells, A. W., Wellstein, C., Wenk, E., Westoby, M., Westwood, A., White, P. J., Whitten, M., Williams, M., Winkler, D. E., Winter, K., Womack, C., Wright, I. J., Wright, S. J., Wright, J., Pinho, B. X., Ximenes, F., Yamada, T., Yamaji, K., Yanai, R., Yankov, N., Yguel, B., Zanini, K. J., Zanne, A. E., Zeleny, D., Zhao, Y. P., Zheng, J., Zieminska, K., Zirbel, C. R., Zizka, G., Zo Bi, I. C., Zotz, G., Wirth, C., Systèmes d'élevage méditerranéens et tropicaux (UMR SELMET), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-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), Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant - Clermont Auvergne (PIAF), Université Clermont Auvergne (UCA)-Institut National de la Recherche Agronomique (INRA), Botanique et Modélisation de l'Architecture des Plantes et des Végétations (UMR AMAP), 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), Biodiversité, Gènes & Communautés (BioGeCo), Institut National de la Recherche Agronomique (INRA)-Université de Bordeaux (UB), SILVA (SILVA), AgroParisTech-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Ecologie des forêts de Guyane (UMR ECOFOG), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de la Recherche Agronomique (INRA)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA), 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), Ecologie fonctionnelle et biogéochimie des sols et des agro-écosystèmes (UMR Eco&Sols), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Unité Expérimentale Forêt Pierroton (UEFP), Institut National de la Recherche Agronomique (INRA), Max Planck Institute for Biogeochemistry Max Planck SocietyFoundation CELLEX German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig International Programme of Biodiversity Science (DIVERSITAS) International Geosphere-Biosphere Programme (IGBP) French Foundation for Biodiversity Research (FRB) GIS 'Climat, Environnement et Societe' France AXA Research Fund NERC Natural Environment Research Council Future Earth, Max Planck Institute for Biogeochemistry (MPI-BGC), Max-Planck-Gesellschaft, German Centre for Integrative Biodiversity Research (iDiv), Instituto Multidisciplinario de Biología Vegetal [Córdoba] (IMBIV), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Facultad de Ciencias Exactas, Físicas y Naturales [Córdoba], Universidad Nacional de Córdoba [Argentina]-Universidad Nacional de Córdoba [Argentina], Laboratoire d'Ecologie Alpine (LECA ), Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Centre National de la Recherche Scientifique (CNRS)-Université Grenoble Alpes (UGA), Imperial College London, Ecologie Systématique et Evolution (ESE), AgroParisTech-Université Paris-Saclay-Centre National de la Recherche Scientifique (CNRS), Department of Zoology [Oxford], University of Oxford, Balliol College, Helsingin yliopisto = Helsingfors universitet = University of Helsinki, Tarbiat Modares University [Tehran], Università degli Studi Roma Tre = Roma Tre University (ROMA TRE), Department of Environment [Aegean], University of the Aegean, Institute of Ecology and Evolution [Bern, Switzerland], University of Bern, University of Tartu, Tohoku University [Sendai], 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), Universidad de Jaén (UJA), Instituto Alexander Von Humboldt, Bogota, Colombia, National Institute of Amazonian Research (INPA), Manaus, Brazil, Botany Department, Faculty of Science, Suez Canal University, Ismailia, Egypt, Laboratoire Agronomie et Environnement - Antenne Colmar (LAE-Colmar ), Laboratoire Agronomie et Environnement (LAE), Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Université de Lorraine (UL)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Forest Sciences, University of Göttingen, Göttingen, Germany, Centre for Biodiversity and Sustainable Land-use [University of Göttingen] (CBL), Georg-August-University = Georg-August-Universität Göttingen, Instituto de Investigaciones en Recursos Naturales, Agroecología y Desarrollo Rural (IRNAD), Universidad Nacional de Río Negro, El Bolsón, Argentina, Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET), School of Environmental Sciences, University of Guelph, Pacific Northwest National Laboratory, Richland, WA, USA, University of Massachusetts [Amherst] (UMass Amherst), University of Massachusetts System (UMASS), Centre for Crop Systems Analysis, Wageningen University and Research [Wageningen] (WUR), University of Victoria [Canada] (UVIC), College of Science & Engineering, James Cook University, Smithfield, Qld, Australia, University of Pittsburgh, Pittsburgh, PA, USA, Centre for Forest Research, Institute for Integrative Systems Biology, Université Laval, Quebec, QC, Canada, Arizona State University, Tempe, AZ, USA, University of North Florida [Jacksonville] (UNF), Australian National University (ANU), Great Lakes Forestry Centre, Canadian Forest Service, Natural Resources Canada, Sault Ste. Marie, ON, Canada, Department of Biology [Copenhagen], Faculty of Science [Copenhagen], University of Copenhagen = Københavns Universitet (UCPH)-University of Copenhagen = Københavns Universitet (UCPH), Department of Ecology [Innsbruck], Leopold Franzens Universität Innsbruck - University of Innsbruck, University of Leeds, Royal Botanic Gardens Kew, Richmond, UK, Conservation Ecology, Groningen Institute for Evolutionary Life Sciences (GELIFES), University of Groningen, Groningen, The Netherlands, Lawrence Berkeley National Laboratory [Berkeley] (LBNL), Biology Department, Wilfrid Laurier University, Waterloo, ON, Canada, Department of Forest Resources, University of Minnesota, St. Paul, MN, USA, AgroParisTech, Lancaster Environment Centre, Lancaster University, University of Exeter, University of Adelaide, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Département Environnements et Sociétés (Cirad-ES), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), University of California [Berkeley] (UC Berkeley), University of California (UC), Department of Horticulture and Landscape Architecture, Colorado State University, Fort Collins, CO, USA, Universiteit Gent = Ghent University (UGENT), Università degli Studi di Cagliari = University of Cagliari (UniCa), Helmholtz Zentrum für Umweltforschung = Helmholtz Centre for Environmental Research (UFZ), Royal Museum for Central Africa, Tervuren, Belgium, Bayreuth Center of Ecology and Environmental Research (BayCEER), Groningen Institute of Archaeology (GIA), University of Groningen, Groningen, The Netherlands, Department of Biological Sciences, University of Tennessee, Knoxville, TN, USA, Rocky Mountain Biological Laboratory, Crested Butte, CO, USA, Département des Science, Université du Québec À Montréal, Montreal, QC, Canada, Department of Biogeography, University of Bayreuth, Bayreuth, Germany, Museo Nacional de Ciencias Naturales [Madrid] (MNCN), Consejo Superior de Investigaciones Científicas [Madrid] (CSIC), Université Laval, Quebec, QC, Canada, Instituto de Ciencias Naturales, Universidad Nacional de Colombia, Bogota, Colombia, Fundación Natura, Bogota, Colombia, Environmental Change Institute, Laboratório de Estudos em Vegetação Campestre (LEVCamp), Programa de Pós-Graduação em Botânica, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil, Freie Universität Berlin, Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Berlin, Germany, Laboratório de Ecologia Funcional de Comunidades (LABEF), Departamento de Botânica, Universidade Federal do Paraná, Curitiba, Brazil, School of Informatics, Computing, and Cyber Systems (SICCS), Northern Arizona University [Flagstaff], Institute of Ecology and Evolution, Friedrich Schiller University Jena, Jena, Germany, ETH Zurich, Universitatstrasse 16, 8092 Zurich, Switzerland, University of Gothenburg (GU), Laboratoire de Physique et Physiologie Intégratives de l’Arbre en environnement Fluctuant (PIAF), Université Clermont Auvergne [2017-2020] (UCA [2017-2020])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Universidade Federal do Rio Grande do Sul [Porto Alegre] (UFRGS), School of Life Sciences, Arizona State University, Tempe, AZ, USA, USDA-ARS Rangeland Resources & Systems Research Unit, Fort Collins, CO, USA, Grupo de Investigación en Biodiversidad y Dinámica de Ecosistémas Tropicales - Universidad del Tolima, Ibagué, Colombia, Laboratory of Applied Physical Chemistry - ISOFYS (Gent, Belgium), School of Forest Resources and Conservation [Gainesville] (UF|IFAS|FFGS), Institute of Food and Agricultural Sciences [Gainesville] (UF|IFAS), University of Florida [Gainesville] (UF)-University of Florida [Gainesville] (UF), Senckenberg Biodiversity and Climate Research Centre, Frankfurt am Main, Germany, Department of Biological Sciences, Goethe Universität Frankfurt, Frankfurt am Main, Germany, Department of Biological Sciences, University of Cape Town, Cape Town, South Africa, SAEON Fynbos Node, Claremont, South Africa, Pacific Northwest National Laboratory, College Park, MD, USA, University of Leicester, Department of Environmental Science, Institute for Water and Wetland Research, Radboud University, Nijmegen, The Netherlands, Laboratório de Ecologia Vegetal (LEVEG), Programa de Pós-Graduação em Ecologia, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil, Archbold Biological Station’s Buck Island Ranch, FL, Lake Placid, USA, Department of Ecology and Evolutionary Biology, University of Connecticut, Storrs, CT, USA, University of Tasmania [Hobart, Australia] (UTAS), Facultad de Ciencias Forestales, Universidad Nacional de Santiago del Estero, Santiago del Estero, Argentina, Universität Hohenheim, School of Geography, University of Nottingham, Nottingham, UK, Department of Geography and Geology, Kingston University, Kingston upon Thames, UK, Martin-Luther-Universität Halle Wittenberg (MLU), Facultad de Ingeniería y Ciencias Hídricas, Universidad Nacional del Litoral (FICH-UNL), Santa Fe, Argentina, 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), Institut de Recherche pour le Développement (IRD [Nouvelle-Calédonie]), University of Toronto at Scarborough, Friedrich-Schiller-Universität = Friedrich Schiller University Jena [Jena, Germany], Section for Ecoinformatics and Biodiversity, Department of Bioscience, Aarhus University, Aarhus, Denmark, Center for Biodiversity Dynamics in a Changing World (BIOCHANGE), Department of Bioscience, Aarhus University, Aarhus, Denmark, New Jersey Institute of Technology [Newark] (NJIT), University of Rostock, Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome] (UNIROMA), School of Biological Sciences, University of Aberdeen, Aberdeen, UK, Center for Ecosystem Science and Society, Northern Arizona University, Flagstaff, AZ, USA, School of Civil and Environmental Engineering, Yonsei University, Seoul, Korea, Departamento de Botânica, SCB, UFPR – Federal University of Parana, Curitiba, Brazil, Centro Politécnico, Universidade Federal do Paraná, Curitiba, Brazil, Università degli Studi di Milano = University of Milan (UNIMI), Risques, Ecosystèmes, Vulnérabilité, Environnement, Résilience (RECOVER), Aix Marseille Université (AMU)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Environmental Systems Science, ETH Zürich, Zürich, Switzerland, Swiss Federal Institute for Forest, Snow and Landscape Research WSL, Centre of Excellence for Bioscurity Risk Analysis, The University of Melbourne, Melbourne, Vic., Australia, Centro de Investigaciones Biológicas (CSIC), Colgate University, Hamilton, NY, USA, School of Biosciences and Veterinary Medicine, Plant Diversity and Ecosystems Management Unit, University of Camerino, Camerino, Italy, University of the Basque Country/Euskal Herriko Unibertsitatea (UPV/EHU), Departamento de Geociencias y Medio Ambiente, Universidad Nacional de Colombia, Medellin, Colombia, Università degli studi di Parma = University of Parma (UNIPR), Centro Agronómico Tropical de Investigación y Enseñanza - Tropical Agricultural Research and Higher Education Center (CATIE), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Geography, King’s College London, London, UK, University of Minnesota [Twin Cities] (UMN), University of Minnesota System, Universitá degli Studi dell’Insubria = University of Insubria [Varese] (Uninsubria), Alma Mater Studiorum Università di Bologna [Bologna] (UNIBO), Universidad de Costa Rica (UCR), University of Arizona, Institute of Arctic Biology, University of Alaska [Fairbanks] (UAF), Royal Botanic Gardens [Kew], Department of Biology [Fort Collins], Colorado State University [Fort Collins] (CSU), WSL Swiss Federal Research Institute, Birmensdorf, Switzerland, Faculty of Forestry, University of British Columbia, Vancouver, BC, Canada, CREA – Research Centre for Forestry and Wood, Arezzo, Italy, Western Sydney University, ungwon University, Goesan, Chungbuk, Korea, Department of Botany and Zoology [Brno] (SCI / MUNI), Faculty of Science [Brno] (SCI / MUNI), Masaryk University [Brno] (MUNI)-Masaryk University [Brno] (MUNI), University of Pisa - Università di Pisa, Department of Agriculture and Forest Engineering (EAGROF), University of Lleida, Lleida, Spain, Joint Research Unit CTFC – AGROTECNIO, Solsona, Spain, University of California Riverside, Riverside, CA, USA, Faculty of Environmental Sciences, University of Life Sciences Prague, Institute of Botany of the Czech Academy of Sciences (IB / CAS), Czech Academy of Sciences [Prague] (CAS), University of Cambridge [UK] (CAM), Systems Ecology, Department of Ecological Science, Vrije Universiteit, Amsterdam, The Netherlands, School of Biological, Earth and Environmental Sciences, UNSW Sydney, Sydney, NSW, Australia, Faculté de foresterie, de géographie et de géomatique, Université Laval, Quebec, QC, Canada, Jonah Ventures, Boulder, CO, USA, Centro de Modelación y Monitoreo de Ecosistemas, Universidad Mayor, Santiago, Chile, Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences (SLU), Centre for African Conservation Ecology, Department of Zoology, Nelson Mandela University, Port Elizabeth, South Africa, MTA Centre for Ecological Research [Tihany], Hungarian Academy of Sciences (MTA), University of Ljubljana, Santa Catarina State University, Lages, SC, Brazil, Department of Geography, Environment, and Spatial Sciences, Michigan State University, East Lansing, MI, USA, Eurac Research, Institute for Alpine Environment, Bozen-Bolzano, Italy, Institute of Biology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences, Syktyvkar, Komi Republic, Russia, University of Science – Vietnam National University Ho Chi Minh City, Ho Chi Minh City, Vietnam, Graduate School of Agriculture, Kyoto University, Kyoto, Japan, Graduate School of Global Environmental Studies, Kyoto University, Kyoto, Japan, Swedish Species Information Centre, University of Pretoria [South Africa], Helmholtz Centre for Environmental Research – UFZ, Leipzig, Germany, Department of Terrestrial Ecology, Netherlands Institute of Ecology, Wageningen, The Netherlands, Department Computational Landscape Ecology [UFZ Leipsig], Department Computational Hydrosystems, UFZ – Helmholtz Centre for Environmental Research, Leipzig, Germany, Seoul National University [Seoul] (SNU), Institute of Temperate Forest Sciences (ISFORT), Ripon, QC, Canada, UQO, Department of Natural Sciences, Ripon, QC, Canada, Université Paris-Sud - Paris 11 (UP11)-AgroParisTech-Centre National de la Recherche Scientifique (CNRS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-AgroParisTech-Université de Guyane (UG)-Centre National de la Recherche Scientifique (CNRS)-Université des Antilles (UA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Goethe-Universität Frankfurt am Main, University of Florida [Gainesville] (UF), The University of Western Australia (UWA), School of Biological Sciences, The University of Western Australia, Department of Biological Sciences, Macquarie University, Department of Botany and Molecular Evolution, Senckenberg Research Institute and Natural History Museum, Universität Wien, Karlstad University [Sweden], Ferdowsi University of Mashhad (FUM), Flathead Lake Biological Station, University of Montana, School of Sustainability, Arizona State University, Programa Nacional de Pós-Doutorado (PNPD), Programa de Pós Graduação em Ecologia, Institute of Biology, University of Campinas UNICAMP, Institute for Ecosystem Research/Geobotany, Kiel University, School of Geography, Earth and Environmental Sciences [Birmingham], University of Birmingham [Birmingham], Justus-Liebig-Universität Gießen = Justus Liebig University (JLU), Global Ecology Unit CREAF-CEAB-CSIC, Universitat Autònoma de Barcelona (UAB), FFCLRP-USP, Department of Biology [USA], University of Maryland [College Park], University of Maryland System-University of Maryland System, University of A Coruña (UDC), School of Physics [UNSW Sydney] (UNSW), University of New South Wales [Sydney] (UNSW), Icahn School of Medicine at Mount Sinai [New York] (MSSM), University of Peking, Peking University [Beijing], Università degli Studi di Sassari = University of Sassari [Sassari] (UNISS), Ordu University - Ordu Üniversitesi, Lanzhou University, Universidad del Tolima, Research Centre for Forestry and Wood, Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria = Council for Agricultural Research and Economics (CREA), Brazilian Agricultural Research Corporation (Embrapa), Universidade de São Paulo = University of São Paulo (USP), Centro Agronomico Tropical de Investigacion y Ensenanza (CATIE), Queensland University of Technology [Brisbane] (QUT), University of Sussex, Harvard University, Institute for Alpine Environment, European Academy of Bozen-Bolzano (EURAC), Étude et compréhension de la biodiversité (ECODIV), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Laboratoire de Physique Atmosphérique et Planétaire (LPAP), Université de Liège, Université de Sherbrooke (UdeS), Station d'écologie théorique et expérimentale (SETE), Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Observatoire Midi-Pyrénées (OMP), Institut de Recherche pour le Développement (IRD)-Université Toulouse III - Paul Sabatier (UT3), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), 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, University of Manchester [Manchester], Universidade Estadual de Campinas = University of Campinas (UNICAMP), Macquarie University, Universidade Federal do Rio Grande do Norte [Natal] (UFRN), Universidad Rey Juan Carlos [Madrid] (URJC), Universidad Nacional de la Patagonia Austral (UNPA), Universidade Regional de Blumenau (FURB), INIA-CIFOR, Southern Illinois University [Carbondale] (SIU), Center for Biodiversity Management, Instituto Federal de Educação Ciência e Tecnologia do Cearà, The Morton Arboretum, United States Department of Agriculture (USDA), Swiss Federal Institute of Technology, Aarhus University [Aarhus], Smithsonian Conservation Biology Institute, Centre Supérieur de la Recherche Scientifique (CSIC), Centre Supérieur de la Recherche Scientifique, Universidad del Rosario [Bogota], Norwegian University of Science and Technology [Trondheim] (NTNU), Norwegian University of Science and Technology (NTNU), Université Paris Sud (Paris 11), Senckenberg Research Institutes and Natural History Museums, Universidad de Chile = University of Chile [Santiago] (UCHILE), Joint Global Change Research Institute, Pacific Northwest National Laboratory (PNNL)-University of Maryland [College Park], Smithsonian Tropical Research Institute, University of Liege, Université de Liège - Gembloux, Institut Pasteur de Shanghai, Académie des Sciences de Chine - Chinese Academy of Sciences (IPS-CAS), Réseau International des Instituts Pasteur (RIIP), University of Bristol [Bristol], University of the Witwatersrand [Johannesburg] (WITS), Norwegian University of Life Sciences (NMBU), Murdoch University, Carnegie Museum of Natural History [Pittsburgh], Transilvania University of Brasov, Martin-Luther-University Halle-Wittenberg, Senckenberg Biodiversity and Climate Research Centre (SBiK-F), Goethe-Universität Frankfurt am Main-Senckenberg – Leibniz Institution for Biodiversity and Earth System Research - Senckenberg Gesellschaft für Naturforschung, Leibniz Association-Leibniz Association, Universität für Bodenkultur Wien = University of Natural Resources and Life [Vienne, Autriche] (BOKU), Santa Catarina State University (UDESC), University Centre Myerscough, Kiel University, Florida International University [Miami] (FIU), Division of Plant Ststematic and Ecology, Biology department, Université Catholique de Louvain = Catholic University of Louvain (UCL), University of Applied Sciences of Weihenstephan, Four Peaks Environmental Science and Data Solutions, Norsk institutt for bioøkonomi=Norwegian Institute of Bioeconomy Research (NIBIO), Kochi University of Technology (KUT), University of Illinois [Chicago] (UIC), University of Illinois System, Universitat de Barcelona (UB), Kyoto University, Tyumen State University, Oak Ridge National Laboratory [Oak Ridge] (ORNL), UT-Battelle, LLC, Universitat Politècnica de Catalunya [Barcelona] (UPC), Stanford University, University of Edinburgh, Polish Academy of Sciences (PAN), Philips Research Europe - Hamburg, Sector Medical Imaging Systems, Philips Research, Institute for Systematic Botany and Ecology, Universität Ulm - Ulm University [Ulm, Allemagne], Ecosystèmes, biodiversité, évolution [Rennes] (ECOBIO), Université de Rennes (UR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR), Université de Rennes (UR)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut national des sciences de l'Univers (INSU - CNRS)-Université de Rennes 2 (UR2)-Centre National de la Recherche Scientifique (CNRS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre National de la Recherche Scientifique (CNRS), Universität Bayreuth, University of Copenhagen = Københavns Universitet (UCPH), Guangxi Normal University, University College of London [London] (UCL), Hobart - Tasmania 7001, University of Venda [South Africa] (UNIVEN), University of Melbourne, Philipps Universität Marburg = Philipps University of Marburg, Agrosystèmes Cultivés et Herbagers (ARCHE), Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse (ENSAT), Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT)-Institut National Polytechnique (Toulouse) (Toulouse INP), Université de Toulouse (UT)-Université de Toulouse (UT), Natural Resource Operations and Rural Development, Humboldt State University (HSU), Charles University [Prague] (CU), Karlsruhe Institute of Technology (KIT), Samara National Research University, Institute of Plant Sciences, Forestry and Forest Products Research Institute (FFPRI), Kenyon College, University of Garmian, State University of New York (SUNY), Institute for Biodiversity and Ecosystem Dynamics (IBED), University of Amsterdam [Amsterdam] (UvA), Universidad Nacional del Comahue [Neuquén] (UNCOMA), IT University of Copenhagen (ITU), Agricultural Research Organization, Landscape Ecology Group, University of Oldenburg, Western Carolina University, Xi'an Jiaotong-Liverpool University [Suzhou], Hokkaido University [Sapporo, Japan], Yokohama National University, Technische Universität Munchen - Université Technique de Munich [Munich, Allemagne] (TUM), Institut d Estudis Andorrans, Smithsonian Environmental Research Center (SERC), Humboldt University Of Berlin, University of California [Los Angeles] (UCLA), Department of Biodiversity, Macroecology and Biogeography, Yamagata University, Jomo Kenyatta University of Agriculture and Technology (JKUAT), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro - Montpellier SupAgro, Université du Québec en Abitibi-Témiscamingue (UQAT), University of Saskatchewan [Saskatoon] (U of S), University of Natural Resources and Life Sciences, Institute of Mountain Risk Engineering - Vienna, Austria, University of Wyoming (UW), Département Performances des systèmes de production et de transformation tropicaux (Cirad-PERSYST), Nelson Mandela University [Port Elizabeth], University of Wisconsin - Eau Claire, Naturalis Biodiversity Center [Leiden], Département de biologie [Sherbrooke] (UdeS), Faculté des sciences [Sherbrooke] (UdeS), Université de Sherbrooke (UdeS)-Université de Sherbrooke (UdeS), Yangzhou University, Leipzig University, University Pablo de Olavide, Shanghai Jiao Tong University [Shanghai], Royal Botanical Gardens, Masaryk University [Brno] (MUNI), Department of Physiology, University of Debrecen Egyetem [Debrecen]-Research Centre for Molecular Medicine-Medical and Health Science Centre, Global Change Research Centre (CzechGlobe), Université du Québec à Trois-Rivières (UQTR), Natural Resources Institute Finland (LUKE), Universidade Federal de Alagoas = Federal University of Alagoas (UFAL), Lakehead University, Stockholm University, Universidad Nacional del Litoral [Santa Fe] (UNL), Universidade Federal do Paraná (UFPR), Bangor University, Universidad Autonoma del Estado de Morelos (UAEM), Manaaki Whenua – Landcare Research [Lincoln], Gorongosa National Park, Université de Montréal (UdeM), Tel Aviv University (TAU), University of Queensland [Brisbane], University of Wisconsin-Madison, University of Maine, Holden Arboretum, Hawkesbury Institute for he Environment, Laboratoire d'Ecologie Végétale et Biogéochimie, Université libre de Bruxelles (ULB), University of British Columbia (UBC), Research School of Biology, Universidade Federal de Pernambuco [Recife] (UFPE), School of Geosciences [Edinburgh], Ecology and Evolutionary Biology [Tucson] (EEB), University of Debrecen, Northern Forestry Centre, Canadian Forest Service - CFS (CANADA), University of Illinois at Urbana-Champaign [Urbana], Data61 [Canberra] (CSIRO), Australian National University (ANU)-Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of Debrecen Egyetem [Debrecen], University of Vermont [Burlington], Fundação Zoobotânica do Rio Grande do Sul, University of Montana, Institut de RadioAstronomie Millimétrique (IRAM), Centre National de la Recherche Scientifique (CNRS), University of Freiburg [Freiburg], University of Hawaii, Institut Français de Pondichéry (IFP), Ministère de l'Europe et des Affaires étrangères (MEAE)-Centre National de la Recherche Scientifique (CNRS), Oklahoma State University [Stillwater] (OSU), Osaka City University, Charles Darwin Research Station (CDRS), Charles Darwin Foundation, Los Alamos National Laboratory (LANL), Zhejiang Normal University, European Academy of Bolzano, Universidad Distrital Francisco Jose de Caldas [Bogota], University of Bayreuth, Institute of Biology of Komi Scientific Centre of the Ural Branch of the Russian Academy of Sciences, Russian Academy of Sciences [Moscow] (RAS), CSIRO Land and Water, Commonwealth Scientific and Industrial Research Organisation [Canberra] (CSIRO), University of Canberra, CEH, Department of Systems and Science, Graduate School of Informatics, Kyoto University-Kyoto University, Departamento de Telemática, Faculdade de Engenharia Elétrica e de Computação (DT/FEEC), Universidad Nacional Autónoma de México = National Autonomous University of Mexico (UNAM), Moscow State University, Vrije Universiteit Amsterdam [Amsterdam] (VU), Meijo University, Institute of Ecology and Earth Sciences [Tartu], Astronomical Institute of the Czech Academy of Sciences (ASU / CAS), University of Nijmegen, University of New England (UNE), The James Hutton Institute, Democritus University of Thrace (DUTH), Institute of Ecology and Earth Sciences, University of Tartu, Spanish National Research Council (CSIC), Senckenberg Research Institute and Natural History Museum, University of Vienna [Vienna], Center for Desertification Research (CIDE), Universitat de València (UV), Universidad Autónoma de Madrid (UAM), Université de Jaén, National Institute for Research and Development in Forestry, Department of Plant Production (University of Milan), Tartu Observatory, Botanical Garden of the Samara University, Forschungszentrum Jülich GmbH, Tallinn University, Universität Regensburg (REGENSBURG), Universität Regensburg, School of Social Sciences [Cardiff], Cardiff University, Estonian University of Life Sciences (EMU), Sch Life Sci Weihenstephan, Arizona State University [Tempe] (ASU), Department of Forest Resources, University of Minnesota System-University of Minnesota System, Research Institute for Networks and Communications Engineering (RINCE), Dublin City University [Dublin] (DCU)-Science Foundation Ireland-Enterprise Ireland-Higher Education Authority-School of Electronic Engineering, Southwest University of Science and Technology [Mianyang] (SWUST), Universidade Federal do Acre (UFAC), Berlin-Brandenburg Institute of Advanced Biodiversity Research (BBIB), Centre méditérannéen de médecine moléculaire (C3M), Université Nice Sophia Antipolis (1965 - 2019) (UNS), COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-COMUE Université Côte d'Azur (2015-2019) (COMUE UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Mississippi State University [Mississippi], University of Southampton, Yale University [New Haven], Brookhaven National Laboratory [Upton, NY] (BNL), UT-Battelle, LLC-Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY)-U.S. Department of Energy [Washington] (DOE), East Stroudsburg University, INDEHESA, Forestry School, Universidad de Extremadura - University of Extremadura (UEX), Institute of Physical Geography [Frankfurt am Main], Universität Zürich [Zürich] = University of Zurich (UZH), Lake Ecosystems Group [Lancaster, U.K.] (Centre for Ecology & Hydrology), Lancaster Environment Centre [Lancaster, U.K.], University of Valladolid, Norwegian Institute for Nature Research (NINA), Universidad Nacional de Colombia [Bogotà] (UNAL), Instituto de Recursos Naturales y Agrobiología de Salamanca (IRNASA), Universidade de Coimbra [Coimbra], Algoma University, Senckenberg biodiversität und klima forschungszentrum (BIK-F), Forschungsinstitut Senckenberg (SGN), University of Nottingham, UK (UON), University of Würzburg = Universität Würzburg, Agence Française de Sécurité Sanitaire des Aliments (AFSSA), Herencia, Kirstenbosch Research Centre, South African National Biodiversity Institute, Federal University of Pernambuco [Recife], Sharplex Services, University of Hohenheim, Komarov Botanical Institute RAS, Center for Sustainability Science, Hokkaido, Département de Biologie, University of Regina (UR), Technische Universität Ilmenau (TU ), Universidade de Lisboa = University of Lisbon (ULISBOA), Universidade Federal de Lavras = Federal University of Lavras (UFLA), Università degli Studi di Padova = University of Padua (Unipd), Gothenburg Global Biodiversity Centre, Department of Biology [Gainesville] (UF|Biology), Texas Tech University [Lubbock] (TTU), Florida Museum of Natural History [Gainesville], KU Leuven, Embrapa Recursos Genéticos e Biotecnologia [Brasília], Universiteit Leiden, University of California [Riverside] (UC Riverside), Pacific Northwest National Laboratory (PNNL), University of Natural Resources and Applied Life Sciences, Vienna, (BOKU) and Competence Centre Wood K plus, University of Novi Sad, Instituto Nacional de Investigaciones en Biodiversidad y Medioambiente [Bariloche] (INIBIOMA-CONICET), Consejo Nacional de Investigaciones Científicas y Técnicas [Buenos Aires] (CONICET)-Universidad Nacional del Comahue [Neuquén] (UNCOMA), Slovak Academy of Sciences (SAS), Technical University in Zvolen (TUZVO), Faculty of Forestry and Wood Sciences, Czech University of Life Sciences Prague (CZU), University of Aberdeen, University of Maryland System, Universität Innsbruck [Innsbruck], Estacion Experimental de Zonas Aridas, Hacettepe University = Hacettepe Üniversitesi, Centre for Forest Research (CFR), Université du Québec à Montréal = University of Québec in Montréal (UQAM), Bioversity International [Montpellier], Bioversity International [Rome], Consultative Group on International Agricultural Research [CGIAR] (CGIAR)-Consultative Group on International Agricultural Research [CGIAR] (CGIAR), Department of Animal and Plant Sciences [Sheffield], University of Sheffield [Sheffield], The School for Field Studies, Quantum Optics and Laser Science, Blackett Laboratory, Blackett Laboratory, Imperial College London-Imperial College London, University of Delaware [Newark], Université Clermont Auvergne [2017-2020] (UCA [2017-2020]), Biodiversity and Ecosystem Services Research Group, Stellenbosch University, Czech University of Life Science, Aristotle University of Thessaloniki, Osaka Natural History Center, Ural State Forest Engineering University, University of New Hampshire (UNH), University of Calgary, Catholic University of Leuven - Katholieke Universiteit Leuven (KU Leuven), Hawkesbury Institute for the Environment [Richmond] (HIE), Computational & Applied Vegetation Ecology (CAVElab), Dept Forest & Water Management, Lab Forestry, Museu Paraense Emílio Goeldi, Federal University of Para - Universidade Federal do Pará - UFPA [Belém, Brazil] (UFPA), State Key Laboratory of Natural and Biomimetic Drugs, Fudan University [Shanghai], Department of Ecological Science [Amsterdam], Vrije Universiteit Brussel (VUB), Laboratoire de Biologie des Ligneux et des Grandes Cultures (LBLGC), Université d'Orléans (UO)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Department of Biology, Free University of Bozen-Bolzano, Dpt Biological Sciences, Macquarie University, Duke University [Durham], IFP Energies nouvelles (IFPEN), Department of Primary Industries, Graduate School of Integrated Arts and Sciences, Hiroshima University, Université de Tsukuba = University of Tsukuba, SUNY College of Environmental Science and Forestry (SUNY-ESF), Biological Sciences Department (BIOLOGICAL SCIENCES DEPARTMENT), Nanjing University (NJU), National Taiwan University [Taiwan] (NTU), Zhejiang University, Beijing Forestry University, Institut National Polytechnique Félix Houphouët-Boigny, Universität Leipzig, Max Planck Fellow Program for Christian Wirth, the International Programme of Biodiversity Science (DIVERSITAS), the International Geosphere‐Biosphere Programme (IGBP), Future Earth, the French Foundation for Biodiversity Research (FRB), and GIS ‘Climat, Environnement et Société’ France, JENS KATTGE, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, GERMANY, ELLEN L. FRY, UNIVERSITY OF LIÈGE, BELGIUM, NIKOLAOS M. FYLLAS, UNIVERSITY OF THE AEGEAN, GREECE, GERHARD BÖNISCH, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, GERMANY, SUSANNE TAUTENHAHN, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, JENA, GERMANY, GIJSBERT D. A. WERNER, UNIVERSITY OF OXFORD, OXFORD, UK, TUOMAS AAKALA, UNIVERSITY OF HELSINKI, FINLAND, MEHDI ABEDI, TARBIAT MODARES UNIVERSITY, IRAN, ALICIA T. R. ACOSTA, UNIVERSITY OF ROMA TRE, ITALY, GEORGE C. ADAMIDIS, UNIVERSITY OF BERN, SWITZERLAND, KAIRI ADAMSON, UNIVERSITY OF TARTU, ESTONIA, MASAHIRO AIBA, TOHOKU UNIVERSITY, JAPAN., CÉCILE H. ALBERT, AIX MARSEILLE UNIV, UNIV AVIGNON, FRANCE., JULIO M. ALCÁNTARA, UNIVERSIDAD DE JAÉN, SPAIN, CAROLINA ALCÁZAR C, Instituto Alexander Von Humboldt, Colombia., HAMADA ALI, SUEZ CANAL UNIVERSITY, EGYPT, BERNARD AMIAUD, UNIVERSITÉ DE LORRAINE, FRANCE., CHRISTIAN AMMER, UNIVERSITY OF GÖTTINGEN, GERMANY, MARIANO M. AMOROSO, UNIVERSIDAD NACIONAL DE RÍO NEGRO, ARGENTINA, MADHUR ANAND, UNIVERSITY OF GUELPH, CANADA., MARIJN BAUTERS, GHENT UNIVERSITY, BELGIUM., ERIKA BAZZATO, UNIVERSITY OF CAGLIARI, ITALY., MICHAEL BECKMANN, Helmholtz Centre for Environmental Research, Germany., HANS BEECKMAN, ROYAL MUSEUM FOR CENTRAL AFRICA, BELGIUM., CARL BEIERKUHNLEIN, UNIVERSITY OF BAYREUTH, GERMANY., RENEE BEKKER, UNIVERSITY OF GRONINGEN, THE NETHERLANDS., JOANA BERGMANN, FREIE UNIVERSITÄT BERLIN, GERMANY., MARCOS BERGMANN CARLUCCI, UFPC, LOGAN BERNER, NORTHERN ARIZONA UNIVERSITY, USA., MARKUS BERNHARDT-RÖMERMANN, FRIEDRICH SCHILLER UNIVERSITY JENA, GERMANY., CHRISTOF BIGLER, ETH ZURICH, SWITZERLAND., FEDERICO BRUMNICH, UNIVERSIDAD NACIONAL DEL LITORAL (FICH-UNL), ARGENTINA, HANS HENRIK BRUUN, UNIVERSITY OF COPENHAGEN, DENMARK, DAVID BRUY, UNIVERSITÉ DE MONTPELLIER, FRANCE, SERRA W. BUCHANAN, UNIVERSITY OF TORONTO SCARBOROUGH, CANADA, ROBERT BUITENWERF, AARHUS UNIVERSITY, DENMARK, DANIEL E. BUNKER, NEW JERSEY INSTITUTE OF TECHNOLOGY, USA, JANA BÜRGER, UNIVERSITY OF ROSTOCK, GERMANY, SABINA BURRASCANO, SAPIENZA UNIVERSITY OF ROME, ITALY, DAVID F. R. P. BURSLEM, UNIVERSITY OF ABERDEEN, UK, BRADLEY J. BUTTERFIELD, NORTHERN ARIZONA UNIVERSITY, USA, CHAEHO BYUN, YONSEI UNIVERSITY, KOREA, MARINA C. SCALON, UFP, MARCO CACCIANIGA, UNIVERSITÀ DEGLI STUDI DI MILANO, ITALY, MARC CADOTTE, UNIVERSITY OF TORONTO SCARBOROUGH, CANADA, MAXIME CAILLERET, AIX?MARSEILLE UNIVERSITY, FRANCE, JAMES CAMAC, THE UNIVERSITY OF MELBOURNE, AUSTRALIA, JESÚS JULIO CAMARERO, INSTITUTO PIRENAICO DE ECOLOGÍA (IPE?CSIC), SPAIN, COURTNEY CAMPANY, COLGATE UNIVERSITY, USA, GIANDIEGO CAMPETELLA, UNIVERSITY OF CAMERINO, ITALY, JUAN ANTONIO CAMPOS, UNIVERSITY OF THE BASQUE COUNTRY UPV/EHU, SPAIN, LAURA CANO-ARBOLEDA, UNIVERSIDAD NACIONAL DE COLOMBIA, COLOMBIA, ROBERTO CANULLO, UNIVERSITY OF CAMERINO, ITALY, MICHELE CARBOGNANI, UNIVERSITY OF PARMA, ITALY, FABIO CARVALHO, LANCASTER UNIVERSITY, UK, BASTIEN CASTAGNEYROL, UNIV. BORDEAUX, FRANCE, JANE A. CATFORD, KING'S COLLEGE LONDON, UK, JEANNINE CAVENDER-BARES, UNIVERSITY OF MINNESOTA, USA, BRUNO E. L. CERABOLINI, UNIVERSITY OF INSUBRIA, ITALY, MARCO CERVELLINI, UNIVERSITY OF BOLOGNA, ITALY, EDUARDO CHACÓN-MADRIGAL, UNIVERSIDAD DE COSTA RICA, COSTA RICA, KENNETH CHAPIN, THE UNIVERSITY OF ARIZONA, USA, SAMANTHA DAWSON, SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES, AREND JACOBUS DE BEER, UNIVERSITY OF PRETORIA, SOUTH AFRICA, ANGEL DE FRUTOS, HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH, GERMANY, LEANDRO DUARTE, UFRGS, EMILIE DUCOURET, UMR ECOFOG (AGROPARISTECH, CNRS, INRA, UNIVERSITÉ DES ANTILLES, UNIVERSITÉ DE LA GUYANE), FRANCE, STEFAN DULLINGER, UNIVERSITY OF VIENNA, AUSTRIA, DAN F. B. FLYNN, ARNOLD ARBORETUM OF HARVARD UNIVERSITY, USA, VERONIKA FONTANA, INSTITUTE FOR ALPINE ENVIRONMENT, ITALY, KYONG-SOOK CHUNG, JUNGWON UNIVERSITY, KOREA, MILAN CHYTRÝ, MASARYK UNIVERSITY, CZECH REPUBLIC, DANIELA CICCARELLI, UNIVERSITY OF PISA, ITALY, LLUÍS COLL, UNIVERSITY OF LLEIDA, SPAIN, COURTNEY G. COLLINS, UNIVERSITY OF CALIFORNIA RIVERSIDE, USA, LUISA CONTI, UNIVERSITY OF LIFE SCIENCES PRAGUE, CZECH REPUBLIC, DAVID COOMES, UNIVERSITY OF CAMBRIDGE, UK, JOHANNES H. C. CORNELISSEN, VRIJE UNIVERSITEIT, THE NETHERLANDS, WILLIAM K. CORNWELL, EARTH AND ENVIRONMENTAL SCIENCES, AUSTRALIA, PIERMARIA CORONA, CREA – RESEARCH CENTRE FOR FORESTRY AND WOOD, ITALY, MARIE COYEA, UNIVERSITÉ LAVAL, CANADA, JOSEPH CRAINE, JONAH VENTURES, USA, DYLAN CRAVEN, UNIVERSIDAD MAYOR, CHILE, JORIS P. G. M. CROMSIGT, SWEDISH UNIVERSITY OF AGRICULTURAL SCIENCES, SWEDEN, ANIKÓ CSECSERITS, MTA CENTRE FOR ECOLOGICAL RESEARCH, HUNGARY, KATARINA CUFAR, UNIVERSITY OF LJUBLJANA, SLOVENIA, MATTHIAS CUNTZ, UNIVERSITÉ DE LORRAINE, FRANCE, ANA CAROLINA DA SILVA, SANTA CATARINA STATE UNIVERSITY, BRAZIL, KYLA M. DAHLIN, MICHIGAN STATE UNIVERSITY, USA, MATTEO DAINESE, INSTITUTE FOR ALPINE ENVIRONMENT, ITALY, IGOR DALKE, INSTITUTE OF BIOLOGY OF KOMI SCIENCE CENTRE OF THE URAL BRANCH OF THE RUSSIAN ACADEMY OF SCIENCES, RUSSIA, MICHELE DALLE FRATTE, UNIVERSITY OF INSUBRIA, ITALY, ANH TUAN DANG-LE, UNIVERSITY HO CHI MINH CITY, VIETNAM, JIRÍ DANIHELKA, MASARYK UNIVERSITY, CZECH REPUBLIC, MASAKO DANNOURA, KYOTO UNIVERSITY, JAPAN, JONATHAN R. DE LONG, NETHERLANDS INSTITUTE OF ECOLOGY, THE NETHERLANDS, BENJAMIN DECHANT, SEOUL NATIONAL UNIVERSITY, REPUBLIC OF KOREA, SYLVAIN DELAGRANGE, INSTITUTE OF TEMPERATE FOREST SCIENCES (ISFORT), CANADA, NICOLAS DELPIERRE, UNIVERSITY OF PARIS?SUD, FRANCE, GÉRALDINE DERROIRE, UNIVERSITÉ DES ANTILLES, FRANCE, ARILDO S. DIAS, UNIVERSITÄT FRANKFURT, GERMANY, MILTON HUGO DIAZ-TORIBIO, UNIVERSITY OF FLORIDA, USA, PANAYIOTIS G. DIMITRAKOPOULOS, UNIVERSITY OF THE AEGEAN, GREECE, MARK DOBROWOLSKI, THE UNIVERSITY OF WESTERN AUSTRALIA, AUSTRALIA, DANIEL DOKTOR, HELMHOLTZ CENTRE FOR ENVIRONMENTAL RESEARCH – UFZ, GERMANY, PAVEL DREVOJAN, MASARYK UNIVERSITY, CZECH REPUBLIC, NING DONG, MACQUARIE UNIVERSITY, AUSTRALIA, JOHN DRANSFIELD, ROYAL BOTANIC GARDENS KEW, UK, STEFAN DRESSLER, DEPARTMENT OF BOTANY AND MOLECULAR EVOLUTION, GERMANY, WALTER DURKA, GERMAN CENTER FOR INTEGRATIVE BIODIVERSITY RESEARCH (IDIV) HALLE?JENA?LEIPZIG, GERMANY, REMKO DUURSMA, WESTERN SYDNEY UNIVERSITY, AUSTRALIA, OLGA DYMOVA, KOMI REPUBLIC, RUSSIA, E-VOJTKÓ, A., UNIVERSITY OF SOUTH BOHEMIA, CZECH REPUBLIC, ROLF LUTZ ECKSTEIN, KARLSTAD UNIVERSITY, SWEDEN, HAMID EJTEHADI, FERDOWSI UNIVERSITY OF MASHHAD, IRAN, JAMES ELSER, UNIVERSITY OF MONTANA, USA, THAISE EMILIO, UNIVERSITY OF CAMPINAS UNICAMP, BRAZIL, KRISTINE ENGEMANN, AARHUS UNIVERSITY, DENMARK, MOHAMMAD BAGHER ERFANIAN, FERDOWSI UNIVERSITY OF MASHHAD, IRAN, ALEXANDRA ERFMEIER, KIEL UNIVERSITY, KIEL, GERMANY, ADRIANE ESQUIVEL-MUELBERT, EARTH AND ENVIRONMENTAL SCIENCES, AUSTRALIA, GERD ESSER, JUSTUS LIEBIG UNIVERSITY, GERMANY, MARC ESTIARTE, SPANISH NATIONAL RESEARCH COUNCIL – CSIC, SPAIN, TOMAS F. DOMINGUES, DEPARTMENT OF BIOLOGY – FFCLRP/USP, BRAZIL, WILLIAM F. FAGAN, UNIVERSITY OF MARYLAND, USA, JAIME FAGÚNDEZ, UNIVERSITY OF A CORUÑA, SPAIN, DANIEL S. FALSTER, EVOLUTION & ECOLOGY RESEARCH CENTRE, AUSTRALIA, YING FAN, RUTGERS UNIVERSITY, USA, JINGYUN FANG, PEKING UNIVERSITY, CHINA, EMMANUELE FARRIS, UNIVERSITY OF SASSARI, ITALY, FATIH FAZLIOGLU, ORDU UNIVERSITY, TURKEY, YANHAO FENG, LANZHOU UNIVERSITY, CHINA, FERNANDO FERNANDEZ-MENDEZ, UNIVERSIDAD DEL TOLIMA, COLOMBIA, CARLOTTA FERRARA, CREA – RESEARCH CENTRE FOR FORESTRY AND WOOD, ITALY, JOICE NUNES FERREIRA, CPATU, ALESSANDRA FIDELIS, (UNESP), RIO CLARO, BRAZIL, BRYAN FINEGAN, CATIE-CENTRO AGRONÓMICO TROPICAL DE INVESTIGACIÓN Y ENSEÑANZA, COSTA RICA, JENNIFER FIRN, QUEENSLAND UNIVERSITY OF TECHNOLOGY (QUT), AUSTRALIA, TIMOTHY J. FLOWERS, UNIVERSITY OF SUSSEX, UK, ESTELLE FOREY, UNIVERSITÉ DE ROUEN, FRANCE, CRISTIANE FORGIARINI, UFRGS, BRAZIL., LOUIS FRANÇOIS, UNIVERSITY OF LIÈGE, BELGIUM., MARCELO FRANGIPANI, UFRGS, BRAZIL, DOROTHEA FRANK, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, GERMANY, CEDRIC FRENETTE-DUSSAULT, GÉOPOLE DE L'UNIVERSITÉ DE SHERBROOKE, CANADA, GRÉGOIRE T. FRESCHET, PAUL SABATIER UNIVERSITY TOULOUSE, FRANCE, PAUL LEADLEY, UNIVERSITY OF PARIS-SUD, UNIVERSITÉ PARIS-SACLAY, ORSAY, FRANCE, IZABELA ALEIXO, NATIONAL INSTITUTE OF AMAZONIAN RESEARCH (INPA), BRAZIL, SANDRA DÍAZ, UNIVERSIDAD NACIONAL DE CÓRDOBA, ARGENTINA, SANDRA LAVOREL, UNIV. SAVOIE MONT BLANC, LECA, GRENOBLE, FRANCE, IAIN COLIN PRENTICE, IMPERIAL COLLEGE, UK., CAROLYN ANDERSON, UNIVERSITY OF MASSACHUSETTS AMHERST, USA, NIELS ANTEN, WAGENINGEN UNIVERSITY, THE NETHERLANDS, JOSEPH ANTOS, UNIVERSITY OF VICTORIA, CANADA, DEBORAH MATTOS GUIMARÃES APGAUA, JAMES COOK UNIVERSITY, AUSTRALIA, TIA-LYNN ASHMAN, UNIVERSITY OF PITTSBURGH, USA, DEGI HARJA ASMARA, UNIVERSITÉ LAVAL, CANADA, GREGORY P. ASNER, ARIZONA STATE UNIVERSITY, USA., MICHAEL ASPINWALL, UNIVERSITY OF NORTH FLORIDA, USA., OWEN ATKIN, AUSTRALIAN NATIONAL UNIVERSITY, AUSTRALIA., ISABELLE AUBIN, NATURAL RESOURCES CANADA, LARS BAASTRUP-SPOHR, UNIVERSITY OF COPENHAGEN, DENMARK., KHADIJEH BAHALKEH, TARBIAT MODARES UNIVERSITY, IRAN., MICHAEL BAHN, UNIVERSITY OF INNSBRUCK, AUSTRIA., TIMOTHY BAKER, UNIVERSITY OF LEEDS, LEEDS, UK., WILLIAM J. BAKER, ROYAL BOTANIC GARDENS KEW, UK., JAN P. BAKKER, UNIVERSITY OF GRONINGEN, THE NETHERLANDS., DENNIS BALDOCCHI, UNIVERSITY OF CALIFORNIA BERKELEY, USA., JENNIFER BALTZER, WILFRID LAURIER UNIVERSITY, CANADA, ARINDAM BANERJEE, UNIVERSITY OF MINNESOTA, USA., ANNE BARANGER, AGROPARISTECH, FRANCE., JOS BARLOW, LANCASTER UNIVERSITY, UK., DIEGO R. BARNECHE, UNIVERSITY OF EXETER, UK., ZDRAVKO BARUCH, THE UNIVERSITY OF ADELAIDE, AUSTRALIA., DENIS BASTIANELLI, UNIV MONTPELLIER, FRANCE., JOHN BATTLES, UNIVERSITY OF CALIFORNIA AT BERKELEY, USA, WILLIAM BAUERLE, COLORADO STATE UNIVERSITY, USA, SOLVEIG FRANZISKA BUCHER, FRIEDRICH?SCHILLER?UNIVERSITÄT JENA, GERMANY, GAVIN BELFRY, UNIVERSITY OF TENNESSEE, USA., MICHAEL BELLUAU, UNIVERSITÉ DU QUÉBEC À MONTRÉAL, CANADA., MIRELA BELOIU, UNIVERSITY OF BAYREUTH, GERMANY., RAQUEL BENAVIDES, MUSEO NACIONAL DE CIENCIAS NATURALES-CSIC, SPAIN., LAHCEN BENOMAR, UNIVERSITÉ LAVAL, CANADA., MARY LEE BERDUGO-LATTKE, UNIVERSIDAD NACIONAL DE COLOMBIA, COLOMBIA., ERIKA BERENGUER, UNIVERSITY OF OXFORD, UK., RODRIGO BERGAMIN, UFRS, NINA BUCHMANN, ETH ZURICH, ZURICH, SWITZERLAND, ANNE D. BJORKMAN, UNIVERSITY OF GOTHENBURG, SWEDEN., CHRIS BLACKMAN, UNIVERSITÉ CLERMONT-AUVERGNE, FRANCE., CAROLINA BLANCO, UFRGS, BENJAMIN BLONDER, ARIZONA STATE UNIVERSITY, USA., DANA BLUMENTHAL, USDA-ARS RANGELAND RESOURCES & SYSTEMS RESEARCH UNIT, USA., KELLY T. BOCANEGRA-GONZÁLEZ, UNIVERSIDAD DEL TOLIMA, COLOMBIA., PASCAL BOECKX, GHENT UNIVERSITY, BELGIUM., STEPHANIE BOHLMAN, UNIVERSITY OF FLORIDA, USA., KATRIN BÖHNING-GAESE, UNIVERSITÄT FRANKFURT, GERMANY., LAURA BOISVERT-MARSH, UNIVERSITÄT FRANKFURT, GERMANY., WILLIAM BOND, UNIVERSITY OF CAPE TOWN, SOUTH AFRICA., BEN BOND-LAMBERTY, COLLEGE PARK, USA., ARNOUD BOOM, UNIVERSITY OF LEICESTER, UK., COLINE C. F. BOONMAN, RADBOUD UNIVERSITY, THE NETHERLANDS., KAUANE BORDIN, UFRGS, ELIZABETH H. BOUGHTON, ARCHBOLD BIOLOGICAL STATION'S BUCK ISLAND RANCH, USA., VANESSA BOUKILI, UNIVERSITY OF CONNECTICUT, USA, DAVID M. J. S. BOWMAN, UNIVERSITY OF TASMANIA, AUSTRALIA., SANDRA BRAVO, UNIVERSIDAD NACIONAL DE SANTIAGO DEL ESTERO, MARCO RICHARD BRENDEL, UNIVERSITY OF HOHENHEIM, MARTIN R. BROADLEY, UNIVERSITY OF NOTTINGHAM, UK, KERRY A. BROWN, KINGSTON UNIVERSITY, UK., HELGE BRUELHEIDE, MARTIN LUTHER UNIVERSITY HALLE?WITTENBERG, GERMANY, FERNANDO CASANOVES, CATIE-CENTRO AGRONÓMICO TROPICAL DE INVESTIGACIÓN Y ENSEÑANZA, COSTA RICA, F. STUART CHAPIN, UNIVERSITY OF ALASKA FAIRBANKS, USA, STEFANO CHELLI, UNIVERSITY OF CAMERINO, ITALY, SI?CHONG CHEN, ROYAL BOTANIC GARDENS, UK, ANPING CHEN, COLORADO STATE UNIVERSITY, USA, PAOLO CHERUBINI, UNIVERSITY OF BRITISH COLUMBIA, CANADA, FRANCESCO CHIANUCCI, CREA – RESEARCH CENTRE FOR FORESTRY AND WOOD, ITALY, BRENDAN CHOAT, WESTERN SYDNEY UNIVERSITY, AUSTRALIA, GUILHERME G. MAZZOCHINI, UNIVERSITY OF CAMPINAS, CAMPINAS, BRAZIL, SOPHIE GACHET, UNIV AVIGNON, FRANCE, RACHAEL GALLAGHER, MACQUARIE UNIVERSITY, AUSTRALIA, GISLENE GANADE, UFRN, BRAZIL., MARY-CLAIRE GLASENHARDT, THE MORTON ARBORETUM, USA, ALAIN HAMBUCKERS, UNIVERSITY OF LIÈGE, BELGIUM, MASAE ISHIHARA, KYOTO UNIVERSITY, JAPAN, LEONID IVANOV, TYUMEN STATE UNIVERSITY, RUSSIA, LARISSA IVANOVA, TYUMEN STATE UNIVERSITY, RUSSIA., COLLEEN M. IVERSEN, OAK RIDGE NATIONAL LABORATORY, USA, JORDI IZQUIERDO, Universitat Politècnica de Catalunya, Spain, ROBERT B. JACKSON, STANFORD UNIVERSITY, USA, FRANCESCA GANGA, UNIVERSITY OF CAGLIARI, ITALY, PABLO GARCÍA-PALACIOS, UNIVERSIDAD REY JUAN CARLOS, SPAIN, VERÓNICA GARGAGLIONE, UNIVERSIDAD NACIONAL DE LA PATAGONIA AUSTRAL, ARGENTINA, ERIC GARNIER, UNIV. MONTPELLIER, FRANCE, JOSE LUIS GARRIDO, ESTACIÓN EXPERIMENTAL DEL ZAIDÍN, SPAIN, ANDRÉ LUÍS DE GASPER, UNIVERSIDADE REGIONAL DE BLUMENAU, BRAZIL, GUILLERMO GEAIZQUIERDO, INIA?CIFOR, SPAIN, DAVID GIBSON, SOUTHERN ILLINOIS UNIVERSITY CARBONDALE, USA, ANDREW N. GILLISON, CENTER FOR BIODIVERSITY MANAGEMENT, AUSTRALIA, AELTON GIROLDO, INSTITUTO FEDERAL DE EDUCAÇÃO CIÊNCIA E TECNOLOGIA DO CEARÁ, BRAZIL, SEAN GLEASON, WATER MANAGEMENT AND SYSTEMS RESEARCH UNIT, USA, MARIANA GLIESCH, INSTITUTE OF INTEGRATIVE BIOLOGY, SWITZERLAND, EMMA GOLDBERG, UNIVERSITY OF MINNESOTA, USA, BASTIAN GÖLDEL, AARHUS UNIVERSITY, DENMARK, ERIKA GONZALEZ-AKRE, NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY NTNU, NORWAY, JOSE L. GONZALEZ-ANDUJAR, CSIC-INSTITUTE FOR SUSTAINABLE AGRICULTURE (IAS), SPAIN, ANDRÉS GONZÁLEZ-MELO, UNIVERSIDAD DEL ROSARIO, COLOMBIA, ANA GONZÁLEZ-ROBLES, UNIVERSIDAD DE JAÉN, SPAIN, BENTE JESSEN GRAAE, NORWEGIAN UNIVERSITY OF SCIENCE AND TECHNOLOGY NTNU, NORWAY, ELENA GRANDA, UNIVERSITY OF ALCALÁ, SPAIN, SARAH GRAVES, UNIVERSITY OF FLORIDA, USA, WALTON A. GREEN, HARVARD UNIVERSITY, USA, THOMAS GREGOR, SENCKENBERG RESEARCH INSTITUTE AND NATURAL HISTORY MUSEUM, GERMANY, NICOLAS GROSS, UNIVERSIDAD REY JUAN CARLOS, SPAIN, GREG R. GUERIN, THE UNIVERSITY OF ADELAIDE, AUSTRALIA, ANGELA GÜNTHER, MAX PLANCK INSTITUTE FOR BIOGEOCHEMISTRY, GERMANY, ALVARO G. GUTIÉRREZ, UNIVERSIDAD DE CHILE, CHILE, LILLIE HADDOCK, COLLEGE PARK, USA, ANNA HAINES, THE UNIVERSITY OF MANCHESTER, UK, JEFFERSON HALL, SMITHSONIAN TROPICAL RESEARCH INSTITUTE, REPUBLIC OF PANAMA, WENXUAN HAN, CHINA AGRICULTURAL UNIVERSITY, CHINA, SANDY P. HARRISON, UNIVERSITY OF READING, UK, WESLEY HATTINGH, UNIVERSITY OF THE WITWATERSRAND, SOUTH AFRICA, JOSEPH E. HAWES, ANGLIA RUSKIN UNIVERSITY, UK, TIANHUA HE, CURTIN UNIVERSITY, AUSTRALIA, PENGCHENG HE, CHINESE ACADEMY OF SCIENCES, CHINA, JACOB MASON HEBERLING, CARNEGIE MUSEUM OF NATURAL HISTORY, USA, AVELIINA HELM, UNIVERSITY OF TARTU, ESTONIA, STEFAN HEMPEL, FREIE UNIVERSITÄT BERLIN, GERMANY, JÖRN HENTSCHEL, FRIEDRICH-SCHILLER-UNIVERSITÄT JENA, GERMANY, BRUNO HÉRAULT, UNIVERSITÉ DE MONTPELLIER, FRANCE, ANA-MARIA HERE, TRANSILVANIA UNIVERSITY OF BRASOV, ROMANIA, KATHARINA HERZ, MARTIN LUTHER UNIVERSITY HALLE?WITTENBERG, GERMANY, MYRIAM HEUERTZ, UNIV. BORDEAUX, FRANCE, THOMAS HICKLER, GOETHE UNIVERSITY, GERMANY, PETER HIETZ, UNIVERSITY OF NATURAL RESOURCES AND LIFE SCIENCES, AUSTRIA, PEDRO HIGUCHI, SANTA CATARINA STATE UNIVERSITY, BRAZIL, ANDREW L. HIPP, THE MORTON ARBORETUM, USA, ANDREW HIRONS, UNIVERSITY CENTRE MYERSCOUGH, UK, MARIA HOCK, INSTITUTE FOR ECOSYSTEM RESEARCH/GEOBOTANY, GERMANY, JAMES AARON HOGAN, FLORIDA INTERNATIONAL UNIVERSITY, USA, KAREN HOLL, UNIVERSITY OF CALIFORNIA, USA, OLIVIER HONNAY, PLANT CONSERVATION AND POPULATION BIOLOGY, BELGIUM, KNUT ANDERS HOVSTAD, DEPARTMENT OF LANDSCAPE AND BIODIVERSITY, NORWAY, TOMOAKI ICHIE, KOCHI UNIVERSITY, JAPAN, BORIS IGIC, UNIVERSITY OF ILLINOIS AT CHICAGO, USA, ESTELA ILLA, UNIVERSITAT DE BARCELONA, SPAIN, MARNEY ISAAC, UNIVERSITY OF TORONTO, CANADA, BENJAMIN JACKSON, UNIVERSITY OF EDINBURGH, SCOTLAND, HERVÉ JACTEL, UNIV. BORDEAUX, FRANCE, ANDRZEJ M. JAGODZINSKI, UNIVERSITY OF LIFE SCIENCES, POLAND, UTE JANDT, MARTIN LUTHER UNIVERSITY HALLE-WITTENBERG, GERMANY, STEVEN JANSEN, ULM UNIVERSITY, GERMANY, THOMAS, University of Oxford [Oxford], University of Helsinki, Tarbiat Modaras University, Roma Tre University, Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL), Centre for Biodiversity and Sustainable Land-use, University of Göttingen, Göttingen, Germany, Department of Biology, University of North Florida, Jacksonville, FL, USA, University of Copenhagen = Københavns Universitet (KU)-University of Copenhagen = Københavns Universitet (KU), Department of Range Management, Faculty of Natural Resources and Marine Sciences, Tarbiat Modares University, Noor, Iran, University of Innsbruck, School of Geography, University of Leeds, Leeds, UK, Centre for Ecology and Conservation, College of Life and Environmental Sciences, University of Exeter, Penryn, UK., School of Biological Sciences, The University of Adelaide, Adelaide, SA, Australia, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-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 National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), University of California at Berkeley, Berkeley, CA, USA, Department of Green Chemistry and Technology, Ghent University, Gent, Belgium, Department of Environment, Ghent University, Gent, Belgium, Department of Life and Environmental Sciences, Botany Division, University of Cagliari, Cagliari, Italy, Museo Nacional de Ciencias Naturales-CSIC, Madrid, Spain, Environmental Change Institute, University of Oxford, Oxford, UK, Institut für Biologie, Freie Universität Berlin, Berlin, Germany, Department of Biological and Environmental Sciences, University of Gothenburg, Gothenburg, Sweden, Universidade Federal do Rio Grande do Sul, Porto Alegre, Brazil, Universiteit Gent = Ghent University [Belgium] (UGENT), School of Geography, Geology and Environment, University of Leicester, Leicester, UK, Institute of Landscape and Plant Ecology, University of Hohenheim, Stuttgart, Germany, Institute of Biology/Geobotany and Botanical Garden, Martin Luther University Halle-Wittenberg, Halle, Germany, German Center for Integrative Biodiversity Research (iDiv) Halle-Jena- Leipzig, Leipzig, Germany, University of Toronto [Scarborough, Canada], Faculty of Agricultural and Environmental Sciences, University of Rostock, Rostock, Germany, Università degli Studi di Roma 'La Sapienza' = Sapienza University [Rome], Dipartimento di Bioscienze, Università degli Studi di Milano, Milano, Italy, Department of Plant Biology and Ecology, University of the Basque Country UPV/ EHU, Bilbao, Spain, Department of Chemistry, Life Sciences and Environmental Sustainability, University of Parma, Parma, Italy, Department of Biotechnology and Life Sciences, University of Insubria, Varese, Italy, BIGEA, Department of Biological, Geological and Environmental Sciences, Alma Mater Studiorum – University of Bologna, Bologna, Italy, Escuela de Biología, Universidad de Costa Rica, San José, Costa Rica, The University of Arizona, Tucson, AZ, USA, University of Alaska [Anchorage], Royal Botanic Gardens, Kew, Department of Biology, University of Pisa, Pisa, Italy, Department of Plant Sciences, University of Cambridge, Cambridge, UK, Biotechnical Faculty, University of Ljubljana, Ljubljana, Slovenia, Institut National de la Recherche Agronomique (INRA)-Université de Lorraine (UL)-AgroParisTech, Department of Plant and Soil Sciences, University of Pretoria, Pretoria, South Africa, Department of Landscape Architecture and Rural Systems Engineering, Seoul National University, Seoul, Republic of Korea, Department of Botany and Biodiversity Research, University of Vienna, Department of Environmental and Life Sciences – Biology, Karlstad University, Quantitative Plant Ecology and Biodiversity Research Laboratory, Department of Biology, Faculty of Science, Ferdowsi University of Mashhad, Justus Liebig University, Justus-Liebig-Universität Gießen (JLU), University of Sassari, Consiglio per la Ricerca in Agricoltura e l’analisi dell’economia agraria (CREA), Universidade de São Paulo (USP), Harvard University [Cambridge], Federal University of Rio Grande do Sul, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Observatoire Midi-Pyrénées (OMP), Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Université Fédérale Toulouse Midi-Pyrénées-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD)-Météo France-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Institut de Recherche pour le Développement (IRD), 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), University of Campinas [Campinas] (UNICAMP), University of Cagliari, Universidad de Chile, University of Natural Resources and Life Sciences (BOKU), University of California, Norwegian Institute of Bioeconomy Research (NIBIO), Kyoto University [Kyoto], Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES), University of Copenhagen = Københavns Universitet (KU), University of Venda, Philipps University of Marburg, Institut National de la Recherche Agronomique (INRA)-École nationale supérieure agronomique de Toulouse [ENSAT]-Institut National Polytechnique (Toulouse) (Toulouse INP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées, State University of New York, Stonybrook, IT University of Copenhagen, Smithsonian Environmental Research Center, Humboldt University of Berlin, Georg-August-University [Göttingen], Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro), Nelson Mandela Metropolitan University [Port Elizabeth, South Africa], Netherlands Centre for Biodiversity Naturalis, University of Leipzig [Leipzig, Allemagne], Unité d'Agronomie, University of Debrecen-Research Centre for Molecular Medicine-Medical and Health Science Centre, Global Change Research Institute, University of California [Berkeley], Natural resources institute Finland, Universita degli Studi di Cagliari [Cagliari], Tel Aviv University [Tel Aviv], Oklahoma State University [Stillwater], Kyoto University [Kyoto]-Kyoto University [Kyoto], Universidade Estadual de Campinas (UNICAMP), Universidad Nacional Autónoma de México (UNAM), Vrije universiteit = Free university of Amsterdam [Amsterdam] (VU), Universidad Autonoma de Madrid (UAM), University of Parma = Università degli studi di Parma [Parme, Italie], University of Milan, Forschungszentrum Juelich, Université Nice Sophia Antipolis (... - 2019) (UNS), U.S. Department of Energy [Washington] (DOE)-UT-Battelle, LLC-Stony Brook University [SUNY] (SBU), State University of New York (SUNY)-State University of New York (SUNY), University of Extremadura, University of Göttingen - Georg-August-Universität Göttingen, Universidade de Lisboa (ULISBOA), Federal University of Lavras, Universita degli Studi di Padova, Leiden University, University of California [Riverside] (UCR), Ferdowsi University of Mashhad, Museo Nacional de Ciencias Naturales (MNCN), Departments of Botany and Zoology, Federal University of Para - Universidade Federal do Para [Belem - Brésil], Institut National de la Recherche Agronomique (INRA)-Université d'Orléans (UO), Institut national polytechnique Félix Houphouët-Boigny, Universität Leipzig [Leipzig], Institut National de la Recherche Agronomique (INRA)-Université Clermont Auvergne (UCA), 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)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Institut National de la Recherche Agronomique (INRA), Consejo Nacional de Investigaciones Científicas y Técnicas, Instituto Multidisciplinario de Biología Vegetal (IMBIV), and Factulad de Ciencias Exactas, Físicas y Naturales, Universidad Nacional de Córdoba, Córdoba, Argentina, Laboratoire d'Ecologie Alpine (LECA), Centre National de la Recherche Scientifique (CNRS)-Université Savoie Mont Blanc (USMB [Université de Savoie] [Université de Chambéry])-Université Joseph Fourier - Grenoble 1 (UJF)-Université Grenoble Alpes (UGA), Imperial College London, London SW7 2AZ, UK., Department of Zoology, University of Oxford, Oxford, UK, Balliol College, University of Oxford, Oxford, UK, University of Roma Tre, Rome, Italy, Biodiversity Conservation Laboratory, Department of Environment, University of the Aegean, Mytilene, Greece, Institute of Ecology and Evolution, University of Bern, Bern, Switzerland, Tartu Observatory, University of Tartu, Tartumaa, Estonia, Graduate School of Life Sciences, Tohoku University, Sendai, Japan, Centre National de la Recherche Scientifique (CNRS)-Institut de recherche pour le développement [IRD] : UMR237-Aix Marseille Université (AMU)-Avignon Université (AU), Universidad de Jaén, Jaén, Spain, UMR Nancy-Université- INRA Agronomie et Environnement Nancy-Colmar, Nancy Université, Conicet-Consejo Nacional de Investigaciones Científicas y Técnicas, Buenos Aires, Argentina, Environmental Sciences, Guelph, University of Massachusetts Amherst, Amherst, MA, USA, Wageningen University and Research Center (WUR), University of Victoria, Victoria, BC, Canada, Department of Ecology, University of Innsbruck, Innsbruck, Austria, Department of Biological Sciences-Lancaster University, Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Helmholtz Centre for Environmental Research (UFZ), School of Informatics, Computing, and Cyber Systems, Northern Arizona University, Flagstaff, AZ, USA, Université Clermont Auvergne (UCA)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Universiteit Gent [Ghent], School of Forest Resources and Conservation, University of Florida, Gainesville, FL, USA, University of Tasmania, Hobart, Tas., Australia, AMAP, IRD, Herbier de Nouvelle-Calédonie, Nouméa, New Caledonia, Université de Montpellier (UM)-Centre National de la Recherche Scientifique (CNRS)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD [France-Sud])-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Friedrich-Schiller-Universität Jena, Jena, Germany, Università degli Studi di Roma 'La Sapienza' [Rome], wiss Federal Institute for Forest, Snow and Landscape Research WSL, Birmensdorf, Switzerland, Consejo Superior de Investigaciones Científicas [Spain] (CSIC), Tropical Agricultural Centre for Research and Higher Education (CATIE), Tropical Agricultural Centre for Research and Higher Education, Univ. Bordeaux, INRAE, BIOGECO, Cestas, France, Department of Ecology, Evolution, and Behavior, University of Minnesota, St. Paul, MN, USA, Royal Botanic Gardens, Kew, West Sussex, UK, Department of Biology, Colorado State University, Fort Collins, CO, USA, Hawkesbury Institute for the Environment, Western Sydney University, Sydney, NSW, Australia, Department of Botany and Zoology, Masaryk University, Brno, Czech Republic, Faculty of Environmental Sciences, University of Life Sciences Prague, Praha-Suchdol, Czech Republic, Institute of Botany, Czech Academy of Sciences, Třeboň, Czech Republic, Department of Wildlife, Fish and Environmental Studies, Swedish University of Agricultural Sciences, Umeå, Sweden, MTA Centre for Ecological Research, Tihany, Hungary, Swedish Species Information Centre, Swedish University of Agricultural Sciences, Uppsala, Sweden, Université des Antilles (UA)-Centre National de la Recherche Scientifique (CNRS)-Université de Guyane (UG)-AgroParisTech-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad), University of Florida [Gainesville], UFZ - Helmholtz Centre for Environmental Research, School of Geography, Earth and Environmental Sciences – University of Birmingham, Universitat Autònoma de Barcelona [Barcelona] (UAB), University of Ordu, Council for Agricultural Research and Economics (CREA), Université de Sherbrooke [Sherbrooke], 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), United States Department of Agriculture - USDA (USA), Smithsonian Institution, Carnegie Museum of Natural History, Friedrich-Schiller-Universität Jena, Biodiversité, Gènes et Communautés, Goethe-Universität Frankfurt am Main-Senckenberg Gesellschaft für Naturforschung, University of Natural Resources and Applied Life Sciences (BOKU), Florida International University (FIU), Université Catholique de Louvain (UCL), Stanford University [Stanford], Université de Rennes 1 (UR1), Université de Rennes (UNIV-RENNES)-Université de Rennes (UNIV-RENNES)-Institut Ecologie et Environnement (INEE), Centre National de la Recherche Scientifique (CNRS)-Centre National de la Recherche Scientifique (CNRS)-Observatoire des Sciences de l'Univers de Rennes (OSUR)-Centre National de la Recherche Scientifique (CNRS), University of Tasmania (UTAS), Institut National de la Recherche Agronomique (INRA)-Ecole Nationale Supérieure Agronomique de Toulouse-Institut National Polytechnique (Toulouse) (Toulouse INP), Charles University [Prague], Ghent University [Belgium] (UGENT), Helmholtz Zentrum für Umweltforschung (UFZ), Hokkaido University, Technical University of Munich (TUM), Wageningen University and Research Centre [Wageningen] (WUR), Georg-August-Universität Göttingen, Western Sydney University (UWS), Centre de Coopération Internationale en Recherche Agronomique pour le Développement (Cirad)-Institut de Recherche pour le Développement (IRD)-Centre international d'études supérieures en sciences agronomiques (Montpellier SupAgro)-Institut national d’études supérieures agronomiques de Montpellier (Montpellier SupAgro)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Département de Biologie, Université de Sherbrooke, Sherbrooke, QC, Canada, Université de Sherbrooke, Masaryk University, Czech Academy of Sciences [Prague] (ASCR), Natural Resources Institute Finland, Landcare Research [Lincoln], Université de Montréal [Montréal], Université Libre de Bruxelles [Bruxelles] (ULB), Centre National de la Recherche Scientifique (CNRS)-Ministère de l'Europe et des Affaires étrangères (MEAE), French Institute of Pondicherry (IFP), Normal Zhejiang University, Estonian University of Life Sciences, Institute of Biology Bucharest, Romanian Academy, VU University Amsterdam, Astronomical Institute of the Czech Academy of Sciences, Technische Universität München [München] (TUM), University of Parma, Cardiff School of Social Sciences, University of Cardiff, University of Minnesota [Twin Cities], Manaaki Whenua Landcare Research, Université Côte d'Azur (UCA)-Université Côte d'Azur (UCA)-Institut National de la Santé et de la Recherche Médicale (INSERM), Brookhaven National Laboratory [Upton] (BNL), Stony Brook University [SUNY] (SBU), University of Zürich [Zürich] (UZH), Algoma University [Canada], University of Goettingen, University of Wuerzburg, University of Würzburg, AFSSA, Sherbrooke University, University of Lisbon, Department of Biology (University of Florida), Florida Museum of Natural History, Technical University in Zvolen, University of Zvolen, Fac Forestry & Wood Sci, Université du Québec à Montréal (UQAM), Bioversity International, Consultative Group on International Agricultural Research [CGIAR], Université Clermont Auvergne (UCA), Vrije Universiteit [Brussels] (VUB), University of Tsukuba, Kattge, Jen, Bönisch, Gerhard, Díaz, Sandra, Lavorel, Sandra, Prentice, Iain Colin, Leadley, Paul, Tautenhahn, Susanne, Werner, Gijsbert D A, Aakala, Tuoma, Abedi, Mehdi, Acosta, Alicia Teresa Rosario, Adamidis, George C, Adamson, Kairi, Aiba, Masahiro, Albert, Cécile H, Alcántara, Julio M, Alcázar C, Carolina, Aleixo, Izabela, Ali, Hamada, Amiaud, Bernard, Ammer, Christian, Amoroso, Mariano M, Anand, Madhur, Anderson, Carolyn, Anten, Niel, Antos, Joseph, Apgaua, Deborah Mattos Guimarãe, Ashman, Tia-Lynn, Asmara, Degi Harja, Asner, Gregory P, Aspinwall, Michael, Atkin, Owen, Aubin, Isabelle, Baastrup-Spohr, Lar, Bahalkeh, Khadijeh, Bahn, Michael, Baker, Timothy, Baker, William J, Bakker, Jan P, Baldocchi, Denni, Baltzer, Jennifer, Banerjee, Arindam, Baranger, Anne, Barlow, Jo, Barneche, Diego R, Baruch, Zdravko, Bastianelli, Deni, Battles, John, Bauerle, William, Bauters, Marijn, Bazzato, Erika, Beckmann, Michael, Beeckman, Han, Beierkuhnlein, Carl, Bekker, Renee, Belfry, Gavin, Belluau, Michael, Beloiu, Mirela, Benavides, Raquel, Benomar, Lahcen, Berdugo-Lattke, Mary Lee, Berenguer, Erika, Bergamin, Rodrigo, Bergmann, Joana, Bergmann Carlucci, Marco, Berner, Logan, Bernhardt-Römermann, Marku, Bigler, Christof, Bjorkman, Anne D, Blackman, Chri, Blanco, Carolina, Blonder, Benjamin, Blumenthal, Dana, Bocanegra-González, Kelly T, Boeckx, Pascal, Bohlman, Stephanie, Böhning-Gaese, Katrin, Boisvert-Marsh, Laura, Bond, William, Bond-Lamberty, Ben, Boom, Arnoud, Boonman, Coline C F, Bordin, Kauane, Boughton, Elizabeth H, Boukili, Vanessa, Bowman, David M J S, Bravo, Sandra, Brendel, Marco Richard, Broadley, Martin R, Brown, Kerry A, Bruelheide, Helge, Brumnich, Federico, Bruun, Hans Henrik, Bruy, David, Buchanan, Serra W, Bucher, Solveig Franziska, Buchmann, Nina, Buitenwerf, Robert, Bunker, Daniel E, Bürger, Jana, Burrascano, Sabina, Burslem, David F R P, Butterfield, Bradley J, Byun, Chaeho, Marques, Marcia, Scalon, Marina C, Caccianiga, Marco, Cadotte, Marc, Cailleret, Maxime, Camac, Jame, Camarero, Jesús Julio, Campany, Courtney, Campetella, Giandiego, Campos, Juan Antonio, Cano-Arboleda, Laura, Canullo, Roberto, Carbognani, Michele, Carvalho, Fabio, Casanoves, Fernando, Castagneyrol, Bastien, Catford, Jane A, Cavender-Bares, Jeannine, Cerabolini, Bruno E L, Cervellini, Marco, Chacón-Madrigal, Eduardo, Chapin, Kenneth, Chapin, F Stuart, Chelli, Stefano, Chen, Si-Chong, Chen, Anping, Cherubini, Paolo, Chianucci, Francesco, Choat, Brendan, Chung, Kyong-Sook, Chytrý, Milan, Ciccarelli, Daniela, Coll, Lluí, Collins, Courtney G, Conti, Luisa, Coomes, David, Cornelissen, Johannes H C, Cornwell, William K, Corona, Piermaria, Coyea, Marie, Craine, Joseph, Craven, Dylan, Cromsigt, Joris P G M, Csecserits, Anikó, Cufar, Katarina, Cuntz, Matthia, da Silva, Ana Carolina, Dahlin, Kyla M, Dainese, Matteo, Dalke, Igor, Dalle Fratte, Michele, Dang-Le, Anh Tuan, Danihelka, Jirí, Dannoura, Masako, Dawson, Samantha, de Beer, Arend Jacobu, De Frutos, Angel, De Long, Jonathan R, Dechant, Benjamin, Delagrange, Sylvain, Delpierre, Nicola, Derroire, Géraldine, Dias, Arildo S, Diaz-Toribio, Milton Hugo, Dimitrakopoulos, Panayiotis G, Dobrowolski, Mark, Doktor, Daniel, Dřevojan, Pavel, Dong, Ning, Dransfield, John, Dressler, Stefan, Duarte, Leandro, Ducouret, Emilie, Dullinger, Stefan, Durka, Walter, Duursma, Remko, Dymova, Olga, E-Vojtkó, Anna, Eckstein, Rolf Lutz, Ejtehadi, Hamid, Elser, Jame, Emilio, Thaise, Engemann, Kristine, Erfanian, Mohammad Bagher, Erfmeier, Alexandra, Esquivel-Muelbert, Adriane, Esser, Gerd, Estiarte, Marc, Domingues, Tomas F, Fagan, William F, Fagúndez, Jaime, Falster, Daniel S, Fan, Ying, Fang, Jingyun, Farris, Emmanuele, Fazlioglu, Fatih, Feng, Yanhao, Fernandez-Mendez, Fernando, Ferrara, Carlotta, Ferreira, Joice, Fidelis, Alessandra, Finegan, Bryan, Firn, Jennifer, Flowers, Timothy J, Flynn, Dan F B, Fontana, Veronika, Forey, Estelle, Forgiarini, Cristiane, François, Loui, Frangipani, Marcelo, Frank, Dorothea, Frenette-Dussault, Cedric, Freschet, Grégoire T, Fry, Ellen L, Fyllas, Nikolaos M, Mazzochini, Guilherme G, Gachet, Sophie, Gallagher, Rachael, Ganade, Gislene, Ganga, Francesca, García-Palacios, Pablo, Gargaglione, Verónica, Garnier, Eric, Garrido, Jose Lui, de Gasper, André Luí, Gea-Izquierdo, Guillermo, Gibson, David, Gillison, Andrew N, Giroldo, Aelton, Glasenhardt, Mary-Claire, Gleason, Sean, Gliesch, Mariana, Goldberg, Emma, Göldel, Bastian, Gonzalez-Akre, Erika, Gonzalez-Andujar, Jose L, González-Melo, André, González-Robles, Ana, Graae, Bente Jessen, Granda, Elena, Graves, Sarah, Green, Walton A, Gregor, Thoma, Gross, Nicola, Guerin, Greg R, Günther, Angela, Gutiérrez, Alvaro G, Haddock, Lillie, Haines, Anna, Hall, Jefferson, Hambuckers, Alain, Han, Wenxuan, Harrison, Sandy P, Hattingh, Wesley, Hawes, Joseph E, He, Tianhua, He, Pengcheng, Heberling, Jacob Mason, Helm, Aveliina, Hempel, Stefan, Hentschel, Jörn, Hérault, Bruno, Hereş, Ana-Maria, Herz, Katharina, Heuertz, Myriam, Hickler, Thoma, Hietz, Peter, Higuchi, Pedro, Hipp, Andrew L, Hirons, Andrew, Hock, Maria, Hogan, James Aaron, Holl, Karen, Honnay, Olivier, Hornstein, Daniel, Hou, Enqing, Hough-Snee, Nate, Hovstad, Knut Ander, Ichie, Tomoaki, Igić, Bori, Illa, Estela, Isaac, Marney, Ishihara, Masae, Ivanov, Leonid, Ivanova, Larissa, Iversen, Colleen M, Izquierdo, Jordi, Jackson, Robert B, Jackson, Benjamin, Jactel, Hervé, Jagodzinski, Andrzej M, Jandt, Ute, Jansen, Steven, Jenkins, Thoma, Jentsch, Anke, Jespersen, Jens Rasmus Plantener, Jiang, Guo-Feng, Johansen, Jesper Liengaard, Johnson, David, Jokela, Eric J, Joly, Carlos Alfredo, Jordan, Gregory J, Joseph, Grant Stuart, Junaedi, Decky, Junker, Robert R, Justes, Eric, Kabzems, Richard, Kane, Jeffrey, Kaplan, Zdenek, Kattenborn, Teja, Kavelenova, Lyudmila, Kearsley, Elizabeth, Kempel, Anne, Kenzo, Tanaka, Kerkhoff, Andrew, Khalil, Mohammed I, Kinlock, Nicole L, Kissling, Wilm Daniel, Kitajima, Kaoru, Kitzberger, Thoma, Kjøller, Rasmu, Klein, Tamir, Kleyer, Michael, Klimešová, Jitka, Klipel, Joice, Kloeppel, Brian, Klotz, Stefan, Knops, Johannes M H, Kohyama, Takashi, Koike, Fumito, Kollmann, Johanne, Komac, Benjamin, Komatsu, Kimberly, König, Christian, Kraft, Nathan J B, Kramer, Koen, Kreft, Holger, Kühn, Ingolf, Kumarathunge, Dushan, Kuppler, Jona, Kurokawa, Hiroko, Kurosawa, Yoko, Kuyah, Shem, Laclau, Jean-Paul, Lafleur, Benoit, Lallai, Erik, Lamb, Eric, Lamprecht, Andrea, Larkin, Daniel J, Laughlin, Daniel, Le Bagousse-Pinguet, Yoann, le Maire, Guerric, le Roux, Peter C, le Roux, Elizabeth, Lee, Tali, Lens, Frederic, Lewis, Simon L, Lhotsky, Barbara, Li, Yuanzhi, Li, Xine, Lichstein, Jeremy W, Liebergesell, Mario, Lim, Jun Ying, Lin, Yan-Shih, Linares, Juan Carlo, Liu, Chunjiang, Liu, Daijun, Liu, Udayangani, Livingstone, Stuart, Llusià, Joan, Lohbeck, Madelon, López-García, Álvaro, Lopez-Gonzalez, Gabriela, Lososová, Zdeňka, Louault, Frédérique, Lukács, Balázs A, Lukeš, Petr, Luo, Yunjian, Lussu, Michele, Ma, Siyan, Maciel Rabelo Pereira, Camilla, Mack, Michelle, Maire, Vincent, Mäkelä, Annikki, Mäkinen, Harri, Malhado, Ana Claudia Mende, Mallik, Azim, Manning, Peter, Manzoni, Stefano, Marchetti, Zuleica, Marchino, Luca, Marcilio-Silva, Viniciu, Marcon, Eric, Marignani, Michela, Markesteijn, Lar, Martin, Adam, Martínez-Garza, Cristina, Martínez-Vilalta, Jordi, Mašková, Tereza, Mason, Kelly, Mason, Norman, Massad, Tara Joy, Masse, Jacynthe, Mayrose, Itay, Mccarthy, Jame, Mccormack, M Luke, Mcculloh, Katherine, Mcfadden, Ian R, Mcgill, Brian J, Mcpartland, Mara Y, Medeiros, Juliana S, Medlyn, Belinda, Meerts, Pierre, Mehrabi, Zia, Meir, Patrick, Melo, Felipe P L, Mencuccini, Maurizio, Meredieu, Céline, Messier, Julie, Mészáros, Ilona, Metsaranta, Juha, Michaletz, Sean T, Michelaki, Chrysanthi, Migalina, Svetlana, Milla, Ruben, Miller, Jesse E D, Minden, Vanessa, Ming, Ray, Mokany, Karel, Moles, Angela T, Molnár, Attila, Molofsky, Jane, Molz, Martin, Montgomery, Rebecca A, Monty, Arnaud, Moravcová, Lenka, Moreno-Martínez, Alvaro, Moretti, Marco, Mori, Akira S, Mori, Shigeta, Morris, Dave, Morrison, Jane, Mucina, Ladislav, Mueller, Sandra, Muir, Christopher D, Müller, Sandra Cristina, Munoz, Françoi, Myers-Smith, Isla H, Myster, Randall W, Nagano, Masahiro, Naidu, Shawna, Narayanan, Ayyappan, Natesan, Balachandran, Negoita, Luka, Nelson, Andrew S, Neuschulz, Eike Lena, Ni, Jian, Niedrist, Georg, Nieto, Jhon, Niinemets, Ülo, Nolan, Rachael, Nottebrock, Henning, Nouvellon, Yann, Novakovskiy, Alexander, Nystuen, Kristin Odden, O'Grady, Anthony, O'Hara, Kevin, O'Reilly-Nugent, Andrew, Oakley, Simon, Oberhuber, Walter, Ohtsuka, Toshiyuki, Oliveira, Ricardo, Öllerer, Kinga, Olson, Mark E, Onipchenko, Vladimir, Onoda, Yusuke, Onstein, Renske E, Ordonez, Jenny C, Osada, Noriyuki, Ostonen, Ivika, Ottaviani, Gianluigi, Otto, Sarah, Overbeck, Gerhard E, Ozinga, Wim A, Pahl, Anna T, Paine, C E Timothy, Pakeman, Robin J, Papageorgiou, Aristotelis C, Parfionova, Evgeniya, Pärtel, Meeli, Patacca, Marco, Paula, Susana, Paule, Juraj, Pauli, Harald, Pausas, Juli G, Peco, Begoña, Penuelas, Josep, Perea, Antonio, Peri, Pablo Lui, Petisco-Souza, Ana Carolina, Petraglia, Alessandro, Petritan, Any Mary, Phillips, Oliver L, Pierce, Simon, Pillar, Valério D, Pisek, Jan, Pomogaybin, Alexandr, Poorter, Hendrik, Portsmuth, Angelika, Poschlod, Peter, Potvin, Catherine, Pounds, Devon, Powell, A Shafer, Power, Sally A, Prinzing, Andrea, Puglielli, Giacomo, Pyšek, Petr, Raevel, Valerie, Rammig, Anja, Ransijn, Johanne, Ray, Courtenay A, Reich, Peter B, Reichstein, Marku, Reid, Douglas E B, Réjou-Méchain, Maxime, de Dios, Victor Resco, Ribeiro, Sabina, Richardson, Sarah, Riibak, Kersti, Rillig, Matthias C, Riviera, Fiamma, Robert, Elisabeth M R, Roberts, Scott, Robroek, Bjorn, Roddy, Adam, Rodrigues, Arthur Viniciu, Rogers, Alistair, Rollinson, Emily, Rolo, Victor, Römermann, Christine, Ronzhina, Dina, Roscher, Christiane, Rosell, Julieta A, Rosenfield, Milena Fermina, Rossi, Christian, Roy, David B, Royer-Tardif, Samuel, Rüger, Nadja, Ruiz-Peinado, Ricardo, Rumpf, Sabine B, Rusch, Graciela M, Ryo, Masahiro, Sack, Lawren, Saldaña, Angela, Salgado-Negret, Beatriz, Salguero-Gomez, Roberto, Santa-Regina, Ignacio, Santacruz-García, Ana Carolina, Santos, Joaquim, Sardans, Jordi, Schamp, Brandon, Scherer-Lorenzen, Michael, Schleuning, Matthia, Schmid, Bernhard, Schmidt, Marco, Schmitt, Sylvain, Schneider, Julio V, Schowanek, Simon D, Schrader, Julian, Schrodt, Franziska, Schuldt, Bernhard, Schurr, Frank, Selaya Garvizu, Galia, Semchenko, Marina, Seymour, Colleen, Sfair, Julia C, Sharpe, Joanne M, Sheppard, Christine S, Sheremetiev, Serge, Shiodera, Satomi, Shipley, Bill, Shovon, Tanvir Ahmed, Siebenkäs, Alrun, Sierra, Carlo, Silva, Vasco, Silva, Mateu, Sitzia, Tommaso, Sjöman, Henrik, Slot, Martijn, Smith, Nicholas G, Sodhi, Darwin, Soltis, Pamela, Soltis, Dougla, Somers, Ben, Sonnier, Grégory, Sørensen, Mia Vedel, Sosinski, Enio Egon, Soudzilovskaia, Nadejda A, Souza, Alexandre F, Spasojevic, Marko, Sperandii, Marta Gaia, Stan, Amanda B, Stegen, Jame, Steinbauer, Klau, Stephan, Jörg G, Sterck, Frank, Stojanovic, Dejan B, Strydom, Tanya, Suarez, Maria Laura, Svenning, Jens-Christian, Svitková, Ivana, Svitok, Marek, Svoboda, Miroslav, Swaine, Emily, Swenson, Nathan, Tabarelli, Marcelo, Takagi, Kentaro, Tappeiner, Ulrike, Tarifa, Rubén, Tauugourdeau, Simon, Tavsanoglu, Cagatay, Te Beest, Mariska, Tedersoo, Leho, Thiffault, Nelson, Thom, Dominik, Thomas, Evert, Thompson, Ken, Thornton, Peter E, Thuiller, Wilfried, Tichý, Lubomír, Tissue, David, Tjoelker, Mark G, Tng, David Yue Phin, Tobias, Joseph, Török, Péter, Tarin, Tonantzin, Torres-Ruiz, José M, Tóthmérész, Béla, Treurnicht, Martina, Trivellone, Valeria, Trolliet, Franck, Trotsiuk, Volodymyr, Tsakalos, James L, Tsiripidis, Ioanni, Tysklind, Nikla, Umehara, Toru, Usoltsev, Vladimir, Vadeboncoeur, Matthew, Vaezi, Jamil, Valladares, Fernando, Vamosi, Jana, van Bodegom, Peter M, van Breugel, Michiel, Van Cleemput, Elisa, van de Weg, Martine, van der Merwe, Stephni, van der Plas, Fon, van der Sande, Masha T, van Kleunen, Mark, Van Meerbeek, Koenraad, Vanderwel, Mark, Vanselow, Kim André, Vårhammar, Angelica, Varone, Laura, Vasquez Valderrama, Maribel Yesenia, Vassilev, Kiril, Vellend, Mark, Veneklaas, Erik J, Verbeeck, Han, Verheyen, Kri, Vibrans, Alexander, Vieira, Ima, Villacís, Jaime, Violle, Cyrille, Vivek, Pandi, Wagner, Katrin, Waldram, Matthew, Waldron, Anthony, Walker, Anthony P, Waller, Martyn, Walther, Gabriel, Wang, Han, Wang, Feng, Wang, Weiqi, Watkins, Harry, Watkins, Jame, Weber, Ulrich, Weedon, James T, Wei, Liping, Weigelt, Patrick, Weiher, Evan, Wells, Aidan W, Wellstein, Camilla, Wenk, Elizabeth, Westoby, Mark, Westwood, Alana, White, Philip John, Whitten, Mark, Williams, Mathew, Winkler, Daniel E, Winter, Klau, Womack, Chevonne, Wright, Ian J, Wright, S Joseph, Wright, Justin, Pinho, Bruno X, Ximenes, Fabiano, Yamada, Toshihiro, Yamaji, Keiko, Yanai, Ruth, Yankov, Nikolay, Yguel, Benjamin, Zanini, Kátia Janaina, Zanne, Amy E, Zelený, David, Zhao, Yun-Peng, Zheng, Jingming, Zheng, Ji, Ziemińska, Kasia, Zirbel, Chad R, Zizka, Georg, Zo-Bi, Irié Casimir, Zotz, Gerhard, Wirth, Christian, AXA Research Fund, Commission of the European Communities, Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Observatoire Midi-Pyrénées (OMP), Université Fédérale Toulouse Midi-Pyrénées-Université Fédérale Toulouse Midi-Pyrénées-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Institut de Recherche pour le Développement (IRD)-Institut national des sciences de l'Univers (INSU - CNRS)-Centre National d'Études Spatiales [Toulouse] (CNES)-Centre National de la Recherche Scientifique (CNRS)-Météo-France -Centre National de la Recherche Scientifique (CNRS), Université Paul-Valéry - Montpellier 3 (UPVM)-École pratique des hautes études (EPHE), Leydet, Michelle, Max Planck Institute for Biogeochemistry, German Center for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Universidad Nacional de Córdoba, LECA, Imperial College, Université Paris-Saclay, Tarbiat Modares University, University of Roma Tre, Tohoku University, IMBE, Universidad de Jaén, Instituto Alexander Von Humboldt, National Institute of Amazonian Research (INPA), Suez Canal University, Université de Lorraine, University of Göttingen, Universidad Nacional de Río Negro, Conicet-Consejo Nacional de Investigaciones Científicas y Técnicas, Pacific Northwest National Laboratory, University of Massachusetts Amherst, Wageningen University, University of Victoria, James Cook University, University of Pittsburgh, Université Laval, Arizona State University, University of North Florida, Australian National University, Natural Resources Canada, University of Copenhagen, Royal Botanic Gardens Kew, University of Groningen, University of California Berkeley, Wilfrid Laurier University, University of Minnesota, The University of Adelaide, UMR SELMET, Univ Montpellier, University of California at Berkeley, Colorado State University, Ghent University, Helmholtz Centre for Environmental Research – UFZ, Royal Museum for Central Africa, University of Tennessee, Rocky Mountain Biological Laboratory, Université du Québec À Montréal, Museo Nacional de Ciencias Naturales-CSIC, Universidad Nacional de Colombia, Fundación Natura, Universidade Federal do Rio Grande do Sul, Northern Arizona University, Friedrich Schiller University Jena, ETH Zurich, University of 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de Ecología (IPE-CSIC), Colgate University, University of Camerino, University of the Basque Country UPV/EHU, CATIE-Centro Agronómico Tropical de Investigación y Enseñanza, BIOGECO, King's College London, University of Insubria, Alma Mater Studiorum – University of Bologna, Universidad de Costa Rica, The University of Arizona, University of Alaska Fairbanks, Royal Botanic Gardens, WSL Swiss Federal Research Institute, University of British Columbia, CREA – Research Centre for Forestry and Wood, Jungwon University, University of Pisa, University of Lleida, Joint Research Unit CTFC – AGROTECNIO, University of California Riverside, University of Life Sciences Prague, Czech Academy of Sciences, University of Cambridge, Vrije Universiteit, UNSW Sydney, Jonah Ventures, Universidad Mayor, Swedish University of Agricultural Sciences, Nelson Mandela University, MTA Centre for Ecological Research, UMR Silva, Santa Catarina State University, Michigan State University, Institute of Biology of Komi Science Centre of the Ural Branch of the Russian Academy of Sciences, University of Science – Vietnam National University Ho Chi Minh City, University of Pretoria, Netherlands Institute of Ecology, UFZ – Helmholtz Centre for Environmental Research, Seoul National University, Institute of Temperate Forest Sciences (ISFORT), UQO, Université de la Guyane), Goethe-Universität Frankfurt, Iluka Resources, The University of Western Australia, University of Vienna, University of South Bohemia, Karlstad University, Earth and Environmental Sciences – University of Birmingham, Spanish National Research Council – CSIC, CREAF, University of Maryland, University of A Coruña, Rutgers University, Peking University, Ordu University, Empresa Brasileira de Pesquisa Agropecuária (EMBRAPA), Universidade Estadual Paulista (Unesp), Queensland University of Technology (QUT), Arnold Arboretum of Harvard University, Université de Rouen, University of Liège, Géopole de l'Université de Sherbrooke, Paul Sabatier University Toulouse, University of Manchester, Universidade Federal do Rio Grande do Norte – UFRN, Universidad Rey Juan Carlos, Universidad Nacional de La Patagonia Austral, Univ. Paul Valéry, Consejo Superior de Investigaciones Científicas, Universidade Regional de Blumenau, Southern Illinois University Carbondale, Instituto Federal de Educação Ciência e Tecnologia do Ceará, Agricultural Research Service, ETH Zürich (Swiss Federal Institute of Technology), CSIC – Institute for Sustainable Agriculture (IAS), Universidad del Rosario, Norwegian University of Science and Technology NTNU, University of Alcalá, UMR Ecosystème Prairial, The University of Manchester, China Agricultural University, Chinese Academy of Sciences, University of Reading, University of the Witwatersrand, Anglia Ruskin University, Norwegian University of Life Sciences, Curtin University, INP-HB, Scientific Campus of the University of the Basque Country, Goethe University, University of Natural Resources and Life Sciences, The Field Museum, Florida International University, US Department of Energy, Santa Cruz, Evolution and Biodiversity Conservation, Kochi University, University of Illinois at Chicago, Universitat de Barcelona, University of Toronto, Ural Branch of the Russian Academy of Sciences, Oak Ridge National Laboratory, Universitat Politècnica de Catalunya, Polish Academy of Sciences, Poznan University of Life Sciences, Ulm University, Guangxi University, Jl. Kebun Raya Cibodas, Philipps-University Marburg, University Salzburg, CIRAD, Humboldt State University, The Czech Academy of Sciences, Charles University, Karlsruhe Institute of Technology, Forestry and Forest Products Research Institute, State University of New York at Stony Brook, University of Amsterdam, CONICET, Universidad Nacional del Comahue, Weizmann Institute of Science, Helmholtz Centre for Environmental Research-UFZ, Xi'an Jiaotong Liverpool University, Technical University of Munich, Wageningen University & Research, Land Life Company, Coconut Research Institute of Sri Lanka, UMR Eco&Sols, University of Montpellier, Université du Québec en Abitibi-Témiscamingue, University of Saskatchewan, University of Natural Resources and Life Sciences Vienna, University of Wyoming, University of Wisconsin Eau Claire, Naturalis Biodiversity Center, University College London, Sun Yat-sen University, University of Leipzig, Shanghai Jiao Tong University, National Forestry and Grassland Administration, Universitat Autònoma de Barcelona, Wageningen University and Research, World Agroforestry (ICRAF), University of Jaén, DRI, Global Change Research Institute AS CR, Université du Québec à Trois-Rivières, Federal University of Alagoas, Bolin Centre for Climate Research, Universidad Autónoma del Estado de Morelos, Manaaki Whenua - Landcare Research, Institut de recherche en biologie végétale, Université de Montréal, Tel Aviv University, The University of Queensland, CSIRO, Manaaki Whenua – Landcare Research, Université Libre de Bruxelles, The Australian National University, The University of Edinburgh, Universidade Federal de Pernambuco (UFPE), ICREA, UEFP, University of Waterloo, Tulipan s/n, Vrije Universiteit Brussel, University of Illinois at Urbana-Champaign, University of Vermont, Centre for Northern Forest Ecosystem Research, Matieland, University of Freiburg, University of Hawai'i, Université Grenoble-Alpes, French Institute of Pondicherry, Oklahoma State University, Charles Darwin Research Station, University of Idaho, Instituto de Investigación de Recursos Biológicos Alexander von Humboldt, Universidad Distrital Francisco José de Caldas, NORD University, NTNU, Gifu University, Romanian Academy, Tercer Circuito s/n de Ciudad Universitaria, Universidad Nacional Autónoma de México, Moscow Lomonosov State University, Universidad de las Américas, Wageningen Environmental Research, Technische Universität München, University of New England, Democritus University of Thrace, Universidad Austral de Chile, Desertification Research Center (CIDE-CSIC), Universidad Autónoma de Madrid, Instituto Nacional de Tecnología Agropecuaria (INTA), National Institute for Research-Development in Forestry, University of Regensburg, McGill University, Morton Arboretum, Université Rennes 1/CNRS, Université Paul Valéry, Southwest University of Science and Technology, Universitat de Lleida, Universidade Federal do Acre, Manaaki Whenua-Landcare Research, Centre for Ecological Research and Forestry Applications (CREAF), Royal Museum for Central-Africa (RMCA), Mississippi State University, Radboud University Nijmegen, Yale University, Brookhaven National Laboratory, Ciudad Universitaria, University of Zurich, Chastè Planta-Wildenberg, Centre for Ecology & Hydrology (CEH), Canadian Forest Service, University of Valladolid-INIA, University of Lausanne, Norwegian Institute for Nature Research, Oxford University, Instituto de Recursos Naturales y Agrobiología de Salamanca (IRNASA-CSIC), Universidade de Coimbra, Senckenberg Biodiversität und Klima Forschungszentrum (SBiK-F), Palmengarten der Stadt Frankfurt am Main, Research Institute for Humanity and Nature, University of Regina, Technische Universität Ilmenau, Università degli Studi di Padova, Gothenburg Botanical Garden, Texas Tech University, Archbold Biological Station, Universidade Federal do Rio Grande do Norte, Slovak Academy of Sciences, Czech University of Life Sciences, Estación Experimental de Zonas Áridas (CSIC), CIRAD-UMR SELMET-PZZS, Hacettepe University, Utrecht University, Canadian Wood Fibre Centre, University of Sheffield, Silwood Park, MTA-DE Lendület Functional and Restoration Ecology Research Group, University of Delaware, UMR PIAF, MTA-TKI Biodiversity and Ecosystem Services Research Group, University of Illinois, Botanical Garden of Ural Branch of Russian Academy of Sciences, University of New Hampshire, National University of Singapore, Edinburgh University, Florida Institute of Technology, University of Konstanz, Taizhou University, University of Erlangen-Nuremberg, Universidad de Concepcion, Bulgarian Academy of Sciences, Museu Paraense Emilio Goeldi, Universidad de las Fuerzas Armadas (ESPE), Goa University, Pondicherry University, Carl von Ossietzky University of Oldenburg, Cambridge Conservation Initiative, Tsinghua University, Chinese Academy of Forestry, Fujian Normal University, Vrije Universiteit Amsterdam, Maritime and Science Technology Academy, University of Winnipeg, King Saud University, University of California – Irvine, U. S. Geological Survey, Duke University, NSW Department of Primary Industries, SUNY-College of Environmental Science and Forestry, Sorbonne-Université, Laboratório de Ecologia Vegetal (LEVEG), George Washington University, National Taiwan University, Institut National Polytechnique Félix Houphouët-Boigny (INP-HB), University Oldenburg, and Biyoloji
- Subjects
[SDE] Environmental Sciences ,LIFE-HISTORY ,Geography & travel ,WOOD DENSITY ,plant trait ,Biodiversity & Conservation ,05 Environmental Sciences ,Growth ,580 Plants (Botany) ,COMMUNITY COMPOSITION ,ROOT TRAITS ,Biologiska vetenskaper ,Ecological modeling ,data coverage ,data integration ,data representativeness ,functional diversity ,plant traits ,TRY plant trait database ,Biodiversity ,Ecology ,Plants ,Access to Information ,Ecosystem ,data representativene ,ddc:910 ,General Environmental Science ,Global and Planetary Change ,GLOBAL PATTERNS ,food and beverages ,LEAF PHOTOSYNTHETIC TRAITS ,Biological Sciences ,CAVElab ,Data processing ,ddc:580 ,[SDE]Environmental Sciences ,Biodiversity Conservation ,Life Sciences & Biomedicine ,INCLINATION ANGLE DISTRIBUTION ,Environmental Sciences & Ecology ,Ecology and Environment ,Database ,LITTER DECOMPOSITION ,ddc:570 ,Datenintegration ,Environmental Chemistry ,DDC 004 / Data processing & computer science ,Intraspecific competition ,Data integration (Computer science) ,Science & Technology ,Biology and Life Sciences ,Plant ,06 Biological Sciences ,Environmental factor ,Nutrient Network ,Biology and Microbiology ,FUNCTIONAL TRAITS ,DDC 580 / Botanical sciences ,Earth and Environmental Sciences ,ddc:004 ,[SDE.BE]Environmental Sciences/Biodiversity and Ecology ,Environmental Sciences ,RELATIVE GROWTH-RATE - Abstract
Plant traits—the morphological, anatomical, physiological, biochemical and phenological characteristics of plants—determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits—almost complete coverage for ‘plant growth form’. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait–environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives., publishedVersion
- Published
- 2020
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3. Sex determination: why so many ways of doing it?
- Author
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Bachtrog, D., Mank, J.E., Peichel, C.L., Kirkpatrick, M., Otto, S.P., Ashman, T.L., Hahn, M.W., Kitano, J., Mayrose, I., Ming, R., Perrin, N., Ross, L., Valenzuela, N., Vamosi, J.C., and Tree of Sex Consortium
- Abstract
Sexual reproduction is an ancient feature of life on earth, and the familiar X and Y chromosomes in humans and other model species have led to the impression that sex determination mechanisms are old and conserved. In fact, males and females are determined by diverse mechanisms that evolve rapidly in many taxa. Yet this diversity in primary sex-determining signals is coupled with conserved molecular pathways that trigger male or female development. Conflicting selection on different parts of the genome and on the two sexes may drive many of these transitions, but few systems with rapid turnover of sex determination mechanisms have been rigorously studied. Here we survey our current understanding of how and why sex determination evolves in animals and plants and identify important gaps in our knowledge that present exciting research opportunities to characterize the evolutionary forces and molecular pathways underlying the evolution of sex determination.
- Published
- 2014
4. Sex Determination: Why So Many Ways of Doing It?
- Author
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Bachtrog, D, Mank, JE, Peichel, CL, Kirkpatrick, M, Otto, SP, Ashman, TL, Hahn, MW, Kitano, J, Mayrose, I, Ming, R, Perrin, N, Ross, L, Valenzuela, N, Vamosi, JC, Blackmon, H, Goldberg, EE, Pennell, MW, Bachtrog, D, Mank, JE, Peichel, CL, Kirkpatrick, M, Otto, SP, Ashman, TL, Hahn, MW, Kitano, J, Mayrose, I, Ming, R, Perrin, N, Ross, L, Valenzuela, N, Vamosi, JC, Blackmon, H, Goldberg, EE, and Pennell, MW
- Abstract
Sexual reproduction is an ancient feature of life on earth, and the familiar X and Y chromosomes in humans and other model species have led to the impression that sex determination mechanisms are old and conserved. In fact, males and females are determined by diverse mechanisms that evolve rapidly in many taxa. Yet this diversity in primary sex-determining signals is coupled with conserved molecular pathways that trigger male or female development. Conflicting selection on different parts of the genome and on the two sexes may drive many of these transitions, but few systems with rapid turnover of sex determination mechanisms have been rigorously studied. Here we survey our current understanding of how and why sex determination evolves in animals and plants and identify important gaps in our knowledge that present exciting research opportunities to characterize the evolutionary forces and molecular pathways underlying the evolution of sex determination. © 2014 Bachtrog et al.
- Published
- 2014
5. Evolutionary Models Accounting for Layers of Selection in Protein-Coding Genes and their Impact on the Inference of Positive Selection
- Author
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Rubinstein, N. D., primary, Doron-Faigenboim, A., additional, Mayrose, I., additional, and Pupko, T., additional
- Published
- 2011
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6. Pepitope: epitope mapping from affinity-selected peptides
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Mayrose, I., primary, Penn, O., additional, Erez, E., additional, Rubinstein, N. D., additional, Shlomi, T., additional, Freund, N. T., additional, Bublil, E. M., additional, Ruppin, E., additional, Sharan, R., additional, Gershoni, J. M., additional, Martz, E., additional, and Pupko, T., additional
- Published
- 2007
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7. A Gamma mixture model better accounts for among site rate heterogeneity
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Mayrose, I., primary, Friedman, N., additional, and Pupko, T., additional
- Published
- 2005
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8. ConSurf 2005: the projection of evolutionary conservation scores of residues on protein structures
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Landau, M., primary, Mayrose, I., additional, Rosenberg, Y., additional, Glaser, F., additional, Martz, E., additional, Pupko, T., additional, and Ben-Tal, N., additional
- Published
- 2005
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9. Selecton: a server for detecting evolutionary forces at a single amino-acid site
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Doron-Faigenboim, A., primary, Stern, A., additional, Mayrose, I., additional, Bacharach, E., additional, and Pupko, T., additional
- Published
- 2005
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10. Comparison of Site-Specific Rate-Inference Methods for Protein Sequences: Empirical Bayesian Methods Are Superior
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Mayrose, I., primary
- Published
- 2004
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11. Rate4Site: an algorithmic tool for the identification of functional regions in proteins by surface mapping of evolutionary determinants within their homologues
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Pupko, T., Bell, R.E., Mayrose, I., Glaser, F., and Ben-Tal, N.
- Abstract
Motivation: A number of proteins of known three-dimensional (3D) structure exist, with yet unknown function. In light of the recent progress in structure determination methodology, this number is likely to increase rapidly. A novel method is presented here: 'Rate4Site', which maps the rate of evolution among homologous proteins onto the molecular surface of one of the homologues whose 3D-structure is known. Functionally important regions often correspond to surface patches of slowly evolving residues. Results: Rate4Site estimates the rate of evolution of amino acid sites using the maximum likelihood (ML) principle. The ML estimate of the rates considers the topology and branch lengths of the phylogenetic tree, as well as the underlying stochastic process. To demonstrate its potency, we study the Src SH2 domain. Like previously established methods, Rate4Site detected the SH2 peptide-binding groove. Interestingly, it also detected inter-domain interactions between the SH2 domain and the rest of the Src protein that other methods failed to detect. Availability: Rate4Site can be downloaded at: http://ashtoret.tau.ac.il/ It is implemented as a web server at: bioinfo.tau.ac.il/ConSurfContact: tal@ism.ac.jp rebell@ashtoret.tau.ac.il fabian@ashtoret.tau.ac.il bental@ashtoret.tau.ac.il Supplementary Information: Multiple sequence alignment of homologous SH2 domains, the corresponding phylogenetic tree and additional examples are available at http://ashtoret.tau.ac.il/~rebell Keywords: rate variation among sites; evolutionary conservation; protein evolution; maximum likelihood; SH2 domains.
- Published
- 2002
12. Tree of Sex: A database of sexual systems
- Author
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The Tree of Sex Consortium, Ashman, T.-L., Bachtrog, D., Blackmon, H., Goldberg, E.E., Hahn, M.W., Kirkpatrick, M., Kitano, J., Mank, J.E., Mayrose, I., Ming, R., Otto, S.P., Peichel, C.L., Pennell, M.W., Perrin, N., Ross, L., Valenzuela, N., and Vamosi, J.C.
- Abstract
The vast majority of eukaryotic organisms reproduce sexually, yet the nature of the sexual system and the mechanism of sex determination often vary remarkably, even among closely related species. Some species of animals and plants change sex across their lifespan, some contain hermaphrodites as well as males and females, some determine sex with highly differentiated chromosomes, while others determine sex according to their environment. Testing evolutionary hypotheses regarding the causes and consequences of this diversity requires interspecific data placed in a phylogenetic context. Such comparative studies have been hampered by the lack of accessible data listing sexual systems and sex determination mechanisms across the eukaryotic tree of life. Here, we describe a database developed to facilitate access to sexual system and sex chromosome information, with data on sexual systems from 11,038 plant, 705 fish, 173 amphibian, 593 non-avian reptilian, 195 avian, 479 mammalian, and 11,556 invertebrate species.
- Published
- 2014
13. A machine-learning-based alternative to phylogenetic bootstrap.
- Author
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Ecker N, Huchon D, Mansour Y, Mayrose I, and Pupko T
- Subjects
- Sequence Alignment methods, Computational Biology methods, Likelihood Functions, Phylogeny, Machine Learning, Software, Algorithms
- Abstract
Motivation: Currently used methods for estimating branch support in phylogenetic analyses often rely on the classic Felsenstein's bootstrap, parametric tests, or their approximations. As these branch support scores are widely used in phylogenetic analyses, having accurate, fast, and interpretable scores is of high importance., Results: Here, we employed a data-driven approach to estimate branch support values with a probabilistic interpretation. To this end, we simulated thousands of realistic phylogenetic trees and the corresponding multiple sequence alignments. Each of the obtained alignments was used to infer the phylogeny using state-of-the-art phylogenetic inference software, which was then compared to the true tree. Using these extensive data, we trained machine-learning algorithms to estimate branch support values for each bipartition within the maximum-likelihood trees obtained by each software. Our results demonstrate that our model provides fast and more accurate probability-based branch support values than commonly used procedures. We demonstrate the applicability of our approach on empirical datasets., Availability and Implementation: The data supporting this work are available in the Figshare repository at https://doi.org/10.6084/m9.figshare.25050554.v1, and the underlying code is accessible via GitHub at https://github.com/noaeker/bootstrap_repo., (© The Author(s) 2024. Published by Oxford University Press.)
- Published
- 2024
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14. The Tree Reconstruction Game: Phylogenetic Reconstruction Using Reinforcement Learning.
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Azouri D, Granit O, Alburquerque M, Mansour Y, Pupko T, and Mayrose I
- Subjects
- Likelihood Functions, Models, Genetic, Computational Biology methods, Software, Phylogeny, Algorithms
- Abstract
The computational search for the maximum-likelihood phylogenetic tree is an NP-hard problem. As such, current tree search algorithms might result in a tree that is the local optima, not the global one. Here, we introduce a paradigm shift for predicting the maximum-likelihood tree, by approximating long-term gains of likelihood rather than maximizing likelihood gain at each step of the search. Our proposed approach harnesses the power of reinforcement learning to learn an optimal search strategy, aiming at the global optimum of the search space. We show that when analyzing empirical data containing dozens of sequences, the log-likelihood improvement from the starting tree obtained by the reinforcement learning-based agent was 0.969 or higher compared to that achieved by current state-of-the-art techniques. Notably, this performance is attained without the need to perform costly likelihood optimizations apart from the training process, thus potentially allowing for an exponential increase in runtime. We exemplify this for data sets containing 15 sequences of length 18,000 bp and demonstrate that the reinforcement learning-based method is roughly three times faster than the state-of-the-art software. This study illustrates the potential of reinforcement learning in addressing the challenges of phylogenetic tree reconstruction., (© The Author(s) 2024. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)
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- 2024
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15. Publisher Correction: Revising the global biogeography of annual and perennial plants.
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Poppenwimer T, Mayrose I, and DeMalach N
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- 2024
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16. Statistical framework to determine indel-length distribution.
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Wygoda E, Loewenthal G, Moshe A, Alburquerque M, Mayrose I, and Pupko T
- Subjects
- Bayes Theorem, Sequence Alignment, INDEL Mutation, Evolution, Molecular, Software, Algorithms
- Abstract
Motivation: Insertions and deletions (indels) of short DNA segments, along with substitutions, are the most frequent molecular evolutionary events. Indels were shown to affect numerous macro-evolutionary processes. Because indels may span multiple positions, their impact is a product of both their rate and their length distribution. An accurate inference of indel-length distribution is important for multiple evolutionary and bioinformatics applications, most notably for alignment software. Previous studies counted the number of continuous gap characters in alignments to determine the best-fitting length distribution. However, gap-counting methods are not statistically rigorous, as gap blocks are not synonymous with indels. Furthermore, such methods rely on alignments that regularly contain errors and are biased due to the assumption of alignment methods that indels lengths follow a geometric distribution., Results: We aimed to determine which indel-length distribution best characterizes alignments using statistical rigorous methodologies. To this end, we reduced the alignment bias using a machine-learning algorithm and applied an Approximate Bayesian Computation methodology for model selection. Moreover, we developed a novel method to test if current indel models provide an adequate representation of the evolutionary process. We found that the best-fitting model varies among alignments, with a Zipf length distribution fitting the vast majority of them., Availability and Implementation: The data underlying this article are available in Github, at https://github.com/elyawy/SpartaSim and https://github.com/elyawy/SpartaPipeline., (© The Author(s) 2024. Published by Oxford University Press.)
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- 2024
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17. Revising the global biogeography of annual and perennial plants.
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Poppenwimer T, Mayrose I, and DeMalach N
- Subjects
- Acclimatization, Biological Evolution, Climate Change statistics & numerical data, Databases, Factual, Desert Climate, Human Activities, Mediterranean Region, Rain, Temperature, Ecosystem, Geographic Mapping, Phylogeography, Plant Physiological Phenomena, Plants classification
- Abstract
There are two main life cycles in plants-annual and perennial
1,2 . These life cycles are associated with different traits that determine ecosystem function3,4 . Although life cycles are textbook examples of plant adaptation to different environments, we lack comprehensive knowledge regarding their global distributional patterns. Here we assembled an extensive database of plant life cycle assignments of 235,000 plant species coupled with millions of georeferenced datapoints to map the worldwide biogeography of these plant species. We found that annual plants are half as common as initially thought5-8 , accounting for only 6% of plant species. Our analyses indicate that annuals are favoured in hot and dry regions. However, a more accurate model shows that the prevalence of annual species is driven by temperature and precipitation in the driest quarter (rather than yearly means), explaining, for example, why some Mediterranean systems have more annuals than desert systems. Furthermore, this pattern remains consistent among different families, indicating convergent evolution. Finally, we demonstrate that increasing climate variability and anthropogenic disturbance increase annual favourability. Considering future climate change, we predict an increase in annual prevalence for 69% of the world's ecoregions by 2060. Overall, our analyses raise concerns for ecosystem services provided by perennial plants, as ongoing changes are leading to a higher proportion of annual plants globally., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)- Published
- 2023
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18. PloiDB: the plant ploidy database.
- Author
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Halabi K, Shafir A, and Mayrose I
- Subjects
- Polyploidy, Genome, Plant, Ploidies, Plants genetics
- Published
- 2023
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19. The Effect of Methodological Considerations on the Construction of Gene-Based Plant Pan-genomes.
- Author
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Glick L and Mayrose I
- Subjects
- Genome, Plant, Sequence Analysis, DNA, Molecular Sequence Annotation, Plants genetics, Genomics methods, Arabidopsis genetics
- Abstract
Pan-genomics is an emerging approach for studying the genetic diversity within plant populations. In contrast to common resequencing studies that compare whole genome sequencing data with a single reference genome, the construction of a pan-genome (PG) involves the direct comparison of multiple genomes to one another, thereby enabling the detection of genomic sequences and genes not present in the reference, as well as the analysis of gene content diversity. Although multiple studies describing PGs of various plant species have been published in recent years, a better understanding regarding the effect of the computational procedures used for PG construction could guide researchers in making more informed methodological decisions. Here, we examine the effect of several key methodological factors on the obtained gene pool and on gene presence-absence detections by constructing and comparing multiple PGs of Arabidopsis thaliana and cultivated soybean, as well as conducting a meta-analysis on published PGs. These factors include the construction method, the sequencing depth, and the extent of input data used for gene annotation. We observe substantial differences between PGs constructed using three common procedures (de novo assembly and annotation, map-to-pan, and iterative assembly) and that results are dependent on the extent of the input data. Specifically, we report low agreement between the gene content inferred using different procedures and input data. Our results should increase the awareness of the community to the consequences of methodological decisions made during the process of PG construction and emphasize the need for further investigation of commonly applied methodologies., (© The Author(s) 2023. Published by Oxford University Press on behalf of Society for Molecular Biology and Evolution.)
- Published
- 2023
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20. A non-homogeneous model of chromosome-number evolution to reveal shifts in the transition patterns across the phylogeny.
- Author
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Shafir A, Halabi K, Escudero M, and Mayrose I
- Subjects
- Phylogeny, Polyploidy, Plants genetics, Evolution, Molecular, Chromosomes, Cyperaceae genetics
- Abstract
Changes in chromosome numbers, including polyploidy and dysploidy events, play a key role in eukaryote evolution as they could expediate reproductive isolation and have the potential to foster phenotypic diversification. Deciphering the pattern of chromosome-number change within a phylogeny currently relies on probabilistic evolutionary models. All currently available models assume time homogeneity, such that the transition rates are identical throughout the phylogeny. Here, we develop heterogeneous models of chromosome-number evolution that allow multiple transition regimes to operate in distinct parts of the phylogeny. The partition of the phylogeny to distinct transition regimes may be specified by the researcher or, alternatively, identified using a sequential testing approach. Once the number and locations of shifts in the transition pattern are determined, a second search phase identifies regimes with similar transition dynamics, which could indicate on convergent evolution. Using simulations, we study the performance of the developed model to detect shifts in patterns of chromosome-number evolution and demonstrate its applicability by analyzing the evolution of chromosome numbers within the Cyperaceae plant family. The developed model extends the capabilities of probabilistic models of chromosome-number evolution and should be particularly helpful for the analyses of large phylogenies that include multiple distinct subclades., (© 2023 The Authors. New Phytologist © 2023 New Phytologist Foundation.)
- Published
- 2023
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21. Multi-Knock-a multi-targeted genome-scale CRISPR toolbox to overcome functional redundancy in plants.
- Author
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Hu Y, Patra P, Pisanty O, Shafir A, Belew ZM, Binenbaum J, Ben Yaakov S, Shi B, Charrier L, Hyams G, Zhang Y, Trabulsky M, Caldararu O, Weiss D, Crocoll C, Avni A, Vernoux T, Geisler M, Nour-Eldin HH, Mayrose I, and Shani E
- Subjects
- Plant Breeding, Plants genetics, Genome, Plant, CRISPR-Cas Systems, Plants, Genetically Modified genetics, Gene Editing, Clustered Regularly Interspaced Short Palindromic Repeats genetics, Arabidopsis genetics
- Abstract
Plant genomes are characterized by large and complex gene families that often result in similar and partially overlapping functions. This genetic redundancy severely hampers current efforts to uncover novel phenotypes, delaying basic genetic research and breeding programmes. Here we describe the development and validation of Multi-Knock, a genome-scale clustered regularly interspaced short palindromic repeat toolbox that overcomes functional redundancy in Arabidopsis by simultaneously targeting multiple gene-family members, thus identifying genetically hidden components. We computationally designed 59,129 optimal single-guide RNAs that each target two to ten genes within a family at once. Furthermore, partitioning the library into ten sublibraries directed towards a different functional group allows flexible and targeted genetic screens. From the 5,635 single-guide RNAs targeting the plant transportome, we generated over 3,500 independent Arabidopsis lines that allowed us to identify and characterize the first known cytokinin tonoplast-localized transporters in plants. With the ability to overcome functional redundancy in plants at the genome-scale level, the developed strategy can be readily deployed by scientists and breeders for basic research and to expedite breeding efforts., (© 2023. The Author(s), under exclusive licence to Springer Nature Limited.)
- Published
- 2023
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22. Using evolutionary data to make sense of macromolecules with a "face-lifted" ConSurf.
- Author
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Yariv B, Yariv E, Kessel A, Masrati G, Chorin AB, Martz E, Mayrose I, Pupko T, and Ben-Tal N
- Subjects
- Protein Conformation, Conserved Sequence genetics, Proteins chemistry, Software, Evolution, Molecular, Biological Evolution
- Abstract
The ConSurf web-sever for the analysis of proteins, RNA, and DNA provides a quick and accurate estimate of the per-site evolutionary rate among homologues. The analysis reveals functionally important regions, such as catalytic and ligand-binding sites, which often evolve slowly. Since the last report in 2016, ConSurf has been improved in multiple ways. It now has a user-friendly interface that makes it easier to perform the analysis and to visualize the results. Evolutionary rates are calculated based on a set of homologous sequences, collected using hidden Markov model-based search tools, recently embedded in the pipeline. Using these, and following the removal of redundancy, ConSurf assembles a representative set of effective homologues for protein and nucleic acid queries to enable informative analysis of the evolutionary patterns. The analysis is particularly insightful when the evolutionary rates are mapped on the macromolecule structure. In this respect, the availability of AlphaFold model structures of essentially all UniProt proteins makes ConSurf particularly relevant to the research community. The UniProt ID of a query protein with an available AlphaFold model can now be used to start a calculation. Another important improvement is the Python re-implementation of the entire computational pipeline, making it easier to maintain. This Python pipeline is now available for download as a standalone version. We demonstrate some of ConSurf's key capabilities by the analysis of caveolin-1, the main protein of membrane invaginations called caveolae., (© 2023 The Authors. Protein Science published by Wiley Periodicals LLC on behalf of The Protein Society.)
- Published
- 2023
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23. The Chromosome Counts Database (CCDB).
- Author
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Rice A and Mayrose I
- Subjects
- Phylogeny, Databases, Factual, Genomics, Information Storage and Retrieval, Documentation
- Abstract
For decades, plant biologists have been interested in the determination and documentation of chromosome numbers for extant taxa. This central cytological character has been used as an important phylogenetic marker and as an indicator for major genomic events such as polyploidy and dysploidy. Due to their significance and the relative ease by which chromosome numbers can be obtained, chromosome numbers have been extensively recorded across the plant kingdom and documented in a wide variety of resources. This makes the collection process a wearing task, often leading to partial data retrieval. In 2015, the Chromosome Counts Database (CCDB) was assembled, being an online unified community resource. This database compiles dozens of different chromosome counts sources, of which a significant portion had been unavailable before in a digitized, searchable format. The vast amount of data assembled in CCDB has already enabled a large number of analyses to examine the evolution of different plant hierarchies, as well as the application of various follow-up analyses, such as ploidy-level inference using chromEvol. CCDB ( http://ccdb.tau.ac.il/ ) encourages data sharing among the botanical community and is expected to continue expanding as additional chromosome numbers are recorded., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)
- Published
- 2023
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- View/download PDF
24. Inferring Chromosome Number Changes Along a Phylogeny Using chromEvol.
- Author
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Rice A and Mayrose I
- Subjects
- Humans, Phylogeny, Ploidies, Polyploidy, Genomics, Models, Statistical
- Abstract
Chromosome numbers have long been used for the identification of key genomic events such as polyploidy and dysploidy. These inferences are often challenging, particularly when applied to large phylogenies, or clades in which more than a few chromosome number transitions had occurred. Here we describe the chromEvol computational framework that infers shifts in chromosome numbers along a phylogeny using probabilistic models of chromosome number change. Given chromosome count data and an associated phylogeny, chromEvol identifies such patterns by fitting probabilistic models of chromosome number evolution to the data. We describe the chromEvol workflow using available online tools, including the specification of the desired models, the examination of model fit to the data, and the inference of ploidy levels. The pipeline can be used by the wide scientific community and requires no previous computational or programming skills., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)
- Published
- 2023
- Full Text
- View/download PDF
25. Using ChromEvol to Determine the Mode of Chromosomal Evolution.
- Author
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Escudero M, Maguilla E, Márquez-Corro JI, Martín-Bravo S, Mayrose I, Shafir A, Tan L, Tribble C, and Zenil-Ferguson R
- Subjects
- Humans, Likelihood Functions, Phylogeny, Polyploidy, Evolution, Molecular, Chromosomes genetics
- Abstract
The ChromEvol software was the first to implement a likelihood-based approach, using probabilistic models that depict the pattern of chromosome number change along a specified phylogeny. The initial models have been completed and expanded during the last years. New parameters that model polyploid chromosome evolution have been implemented in ChromEvol v.2. In recent years, new and more complex models have been developed. The BiChrom model is able to implement two distinct chromosome models for the two possible trait states of a binary character of interest. ChromoSSE jointly implements chromosome evolution, speciation, and extinction. In the near future, we will be able to study chromosome evolution with increasingly complex models., (© 2023. The Author(s), under exclusive license to Springer Science+Business Media, LLC, part of Springer Nature.)
- Published
- 2023
- Full Text
- View/download PDF
26. The evolutionary dynamics that retain long neutral genomic sequences in face of indel deletion bias: a model and its application to human introns.
- Author
-
Loewenthal G, Wygoda E, Nagar N, Glick L, Mayrose I, and Pupko T
- Subjects
- Humans, Introns, Genome, Genomics, Evolution, Molecular, INDEL Mutation
- Abstract
Insertions and deletions (indels) of short DNA segments are common evolutionary events. Numerous studies showed that deletions occur more often than insertions in both prokaryotes and eukaryotes. It raises the question why neutral sequences are not eradicated from the genome. We suggest that this is due to a phenomenon we term border-induced selection . Accordingly, a neutral sequence is bordered between conserved regions. Deletions occurring near the borders occasionally protrude to the conserved region and are thereby subject to strong purifying selection. Thus, for short neutral sequences, an insertion bias is expected. Here, we develop a set of increasingly complex models of indel dynamics that incorporate border-induced selection. Furthermore, we show that short conserved sequences within the neutrally evolving sequence help explain: (i) the presence of very long sequences; (ii) the high variance of sequence lengths; and (iii) the possible emergence of multimodality in sequence length distributions. Finally, we fitted our models to the human intron length distribution, as introns are thought to be mostly neutral and bordered by conserved exons. We show that when accounting for the occurrence of short conserved sequences within introns, we reproduce the main features, including the presence of long introns and the multimodality of intron distribution.
- Published
- 2022
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27. A LASSO-based approach to sample sites for phylogenetic tree search.
- Author
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Ecker N, Azouri D, Bettisworth B, Stamatakis A, Mansour Y, Mayrose I, and Pupko T
- Subjects
- Likelihood Functions, Phylogeny, Artificial Intelligence, Software
- Abstract
Motivation: In recent years, full-genome sequences have become increasingly available and as a result many modern phylogenetic analyses are based on very long sequences, often with over 100 000 sites. Phylogenetic reconstructions of large-scale alignments are challenging for likelihood-based phylogenetic inference programs and usually require using a powerful computer cluster. Current tools for alignment trimming prior to phylogenetic analysis do not promise a significant reduction in the alignment size and are claimed to have a negative effect on the accuracy of the obtained tree., Results: Here, we propose an artificial-intelligence-based approach, which provides means to select the optimal subset of sites and a formula by which one can compute the log-likelihood of the entire data based on this subset. Our approach is based on training a regularized Lasso-regression model that optimizes the log-likelihood prediction accuracy while putting a constraint on the number of sites used for the approximation. We show that computing the likelihood based on 5% of the sites already provides accurate approximation of the tree likelihood based on the entire data. Furthermore, we show that using this Lasso-based approximation during a tree search decreased running-time substantially while retaining the same tree-search performance., Availability and Implementation: The code was implemented in Python version 3.8 and is available through GitHub (https://github.com/noaeker/lasso_positions_sampling). The datasets used in this paper were retrieved from Zhou et al. (2018) as described in section 3., Supplementary Information: Supplementary data are available at Bioinformatics online., (© The Author(s) 2022. Published by Oxford University Press.)
- Published
- 2022
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28. A Probabilistic Model for Indel Evolution: Differentiating Insertions from Deletions.
- Author
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Loewenthal G, Rapoport D, Avram O, Moshe A, Wygoda E, Itzkovitch A, Israeli O, Azouri D, Cartwright RA, Mayrose I, and Pupko T
- Subjects
- Bayes Theorem, Models, Statistical, Phylogeny, Evolution, Molecular, INDEL Mutation
- Abstract
Insertions and deletions (indels) are common molecular evolutionary events. However, probabilistic models for indel evolution are under-developed due to their computational complexity. Here, we introduce several improvements to indel modeling: 1) While previous models for indel evolution assumed that the rates and length distributions of insertions and deletions are equal, here we propose a richer model that explicitly distinguishes between the two; 2) we introduce numerous summary statistics that allow approximate Bayesian computation-based parameter estimation; 3) we develop a method to correct for biases introduced by alignment programs, when inferring indel parameters from empirical data sets; and 4) using a model-selection scheme, we test whether the richer model better fits biological data compared with the simpler model. Our analyses suggest that both our inference scheme and the model-selection procedure achieve high accuracy on simulated data. We further demonstrate that our proposed richer model better fits a large number of empirical data sets and that, for the majority of these data sets, the deletion rate is higher than the insertion rate., (© The Author(s) 2021. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)
- Published
- 2021
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29. Bee flowers drive macroevolutionary diversification in long-horned bees.
- Author
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Dorchin A, Shafir A, Neumann FH, Langgut D, Vereecken NJ, and Mayrose I
- Subjects
- Animals, Bees, Biological Evolution, Phylogeny, Pollen, Flowers, Pollination
- Abstract
The role of plant-pollinator interactions in the rapid radiation of the angiosperms have long fascinated evolutionary biologists. Studies have brought evidence for pollinator-driven diversification of various plant lineages, particularly plants with specialized flowers and concealed rewards. By contrast, little is known about how this crucial interaction has shaped macroevolutionary patterns of floral visitors. In particular, there is currently no empirical evidence that floral host association has increased diversification in bees, the most prominent group of floral visitors that essentially rely on angiosperm pollen. In this study, we examine how floral host preference influenced diversification in eucerine bees (Apidae, Eucerini), which exhibit large variations in their floral associations. We combine quantitative pollen analyses with a recently proposed phylogenetic hypothesis, and use a state speciation and extinction probabilistic approach. Using this framework, we provide the first evidence that multiple evolutionary transitions from host plants with accessible pollen to restricted pollen from 'bee-flowers' have significantly increased the diversification of a bee clade. We suggest that exploiting host plants with restricted pollen has allowed the exploitation of a new ecological niche for eucerine bees and contributed both to their colonization of vast regions of the world and their rapid diversification.
- Published
- 2021
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30. Mechanisms Underlying Host Range Variation in Flavivirus: From Empirical Knowledge to Predictive Models.
- Author
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Halabi K and Mayrose I
- Subjects
- Animals, Host Specificity, Humans, Mosquito Vectors genetics, Phylogeny, Culicidae genetics, Flavivirus genetics
- Abstract
Preventing and controlling epidemics caused by vector-borne viruses are particularly challenging due to their diverse pool of hosts and highly adaptive nature. Many vector-borne viruses belong to the Flavivirus genus, whose members vary greatly in host range and specificity. Members of the Flavivirus genus can be categorized to four main groups: insect-specific viruses that are maintained solely in arthropod populations, mosquito-borne viruses and tick-borne viruses that are transmitted to vertebrate hosts by mosquitoes or ticks via blood feeding, and those with no-known vector. The mosquito-borne group encompasses the yellow fever, dengue, and West Nile viruses, all of which are globally spread and cause severe morbidity in humans. The Flavivirus genus is genetically diverse, and its members are subject to different host-specific and vector-specific selective constraints, which do not always align. Thus, understanding the underlying genetic differences that led to the diversity in host range within this genus is an important aspect in deciphering the mechanisms that drive host compatibility and can aid in the constant arms-race against viral threats. Here, we review the phylogenetic relationships between members of the genus, their infection bottlenecks, and phenotypic and genomic differences. We further discuss methods that utilize these differences for prediction of host shifts in flaviviruses and can contribute to viral surveillance efforts.
- Published
- 2021
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31. Panoramic: A package for constructing eukaryotic pan-genomes.
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Glick L and Mayrose I
- Subjects
- Reproducibility of Results, Eukaryota genetics, Genome, Genomics, Software
- Abstract
The study of intraspecific genomic variation in eukaryotic species has been the focus of numerous genome resequencing projects in recent years. One emerging approach for the analysis of intraspecific diversity uses the concept of a pan-genome, which theoretically represents the full set of genomic sequences and coding genes from all individuals of a given species. This approach has many advantages over reference-based methods and has been successfully applied to study both prokaryotic and eukaryotic species. However, the process of pan-genome construction still presents considerable scientific and technical challenges, especially for eukaryotic species with large and complex genomes. Although general approaches for the construction of pan-genomes have been devised, currently available software tools implement only certain modules of the entire computational procedure. Therefore, each pan-genome project requires the development of tailored analysis pipelines, thus complicating and prolonging the process and impairing research reproducibility and comparison across studies. Here, we present Panoramic, a software package for the automatic construction of eukaryotic pan-genomes. Panoramic takes raw sequencing reads as input and applies two alternative approaches for pan-genome construction. Panoramic makes pan-genome construction a considerably easier task by providing simple user interface and efficient data processing algorithms. We demonstrate the use of Panoramic by constructing the pan-genome of the model plant species Arabidopsis thaliana from sequencing data of 20 diverse ecotypes., (© 2021 John Wiley & Sons Ltd.)
- Published
- 2021
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32. A Codon Model for Associating Phenotypic Traits with Altered Selective Patterns of Sequence Evolution.
- Author
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Halabi K, Karin EL, Guéguen L, and Mayrose I
- Subjects
- Animals, Codon, Models, Genetic, Phylogeny, Primates genetics, Evolution, Molecular, Phenotype, Selection, Genetic
- Abstract
Detecting the signature of selection in coding sequences and associating it with shifts in phenotypic states can unveil genes underlying complex traits. Of the various signatures of selection exhibited at the molecular level, changes in the pattern of selection at protein-coding genes have been of main interest. To this end, phylogenetic branch-site codon models are routinely applied to detect changes in selective patterns along specific branches of the phylogeny. Many of these methods rely on a prespecified partition of the phylogeny to branch categories, thus treating the course of trait evolution as fully resolved and assuming that phenotypic transitions have occurred only at speciation events. Here, we present TraitRELAX, a new phylogenetic model that alleviates these strong assumptions by explicitly accounting for the uncertainty in the evolution of both trait and coding sequences. This joint statistical framework enables the detection of changes in selection intensity upon repeated trait transitions. We evaluated the performance of TraitRELAX using simulations and then applied it to two case studies. Using TraitRELAX, we found an intensification of selection in the primate SEMG2 gene in polygynandrous species compared to species of other mating forms, as well as changes in the intensity of purifying selection operating on sixteen bacterial genes upon transitioning from a free-living to an endosymbiotic lifestyle.[Evolutionary selection; intensification; $\gamma $-proteobacteria; genotype-phenotype; relaxation; SEMG2.]., (© The Author(s) 2020. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For permissions, please email: journals.permissions@oup.com.)
- Published
- 2021
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33. Harnessing machine learning to guide phylogenetic-tree search algorithms.
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Azouri D, Abadi S, Mansour Y, Mayrose I, and Pupko T
- Subjects
- Animals, Databases, Genetic statistics & numerical data, Databases, Protein statistics & numerical data, Humans, Models, Genetic, Algorithms, Evolution, Molecular, Machine Learning, Phylogeny
- Abstract
Inferring a phylogenetic tree is a fundamental challenge in evolutionary studies. Current paradigms for phylogenetic tree reconstruction rely on performing costly likelihood optimizations. With the aim of making tree inference feasible for problems involving more than a handful of sequences, inference under the maximum-likelihood paradigm integrates heuristic approaches to evaluate only a subset of all potential trees. Consequently, existing methods suffer from the known tradeoff between accuracy and running time. In this proof-of-concept study, we train a machine-learning algorithm over an extensive cohort of empirical data to predict the neighboring trees that increase the likelihood, without actually computing their likelihood. This provides means to safely discard a large set of the search space, thus potentially accelerating heuristic tree searches without losing accuracy. Our analyses suggest that machine learning can guide tree-search methodologies towards the most promising candidate trees.
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- 2021
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34. Model adequacy tests for probabilistic models of chromosome-number evolution.
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Rice A and Mayrose I
- Subjects
- Chromosomes, Models, Genetic, Models, Statistical, Phylogeny, Evolution, Molecular, Magnoliopsida
- Abstract
Chromosome number is a central feature of eukaryote genomes. Deciphering patterns of chromosome-number change along a phylogeny is central to the inference of whole genome duplications and ancestral chromosome numbers. ChromEvol is a probabilistic inference tool that allows the evaluation of several models of chromosome-number evolution and their fit to the data. However, fitting a model does not necessarily mean that the model describes the empirical data adequately. This vulnerability may lead to incorrect conclusions when model assumptions are not met by real data. Here, we present a model adequacy test for likelihood models of chromosome-number evolution. The procedure allows us to determine whether the model can generate data with similar characteristics as those found in the observed ones. We demonstrate that using inadequate models can lead to inflated errors in several inference tasks. Applying the developed method to 200 angiosperm genera, we find that in many of these, the best-fitting model provides poor fit to the data. The inadequacy rate increases in large clades or in those in which hybridizations are present. The developed model adequacy test can help researchers to identify phylogenies whose underlying evolutionary patterns deviate substantially from current modelling assumptions and should guide future methods development., (© 2020 The Authors New Phytologist © 2020 New Phytologist Foundation.)
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- 2021
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35. The Evolution of Chromosome Numbers: Mechanistic Models and Experimental Approaches.
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Mayrose I and Lysak MA
- Subjects
- Chromosome Painting, Genome, Plant, Genomics, Polyploidy, Chromosomes, Plant, Evolution, Molecular, Models, Genetic
- Abstract
Chromosome numbers have been widely used to describe the most fundamental genomic attribute of an organism or a lineage. Although providing strong phylogenetic signal, chromosome numbers vary remarkably among eukaryotes at all levels of taxonomic resolution. Changes in chromosome numbers regularly serve as indication of major genomic events, most notably polyploidy and dysploidy. Here, we review recent advancements in our ability to make inferences regarding historical events that led to alterations in the number of chromosomes of a lineage. We first describe the mechanistic processes underlying changes in chromosome numbers, focusing on structural chromosomal rearrangements. Then, we focus on experimental procedures, encompassing comparative cytogenomics and genomics approaches, and on computational methodologies that are based on explicit models of chromosome-number evolution. Together, these tools offer valuable predictions regarding historical events that have changed chromosome numbers and genome structures, as well as their phylogenetic and temporal placements., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution.)
- Published
- 2021
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36. COVID-19 pandemic-related lockdown: response time is more important than its strictness.
- Author
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Loewenthal G, Abadi S, Avram O, Halabi K, Ecker N, Nagar N, Mayrose I, and Pupko T
- Subjects
- COVID-19 epidemiology, COVID-19 mortality, COVID-19 virology, Humans, Pandemics, Physical Distancing, SARS-CoV-2 isolation & purification, Survival Rate, Time Factors, COVID-19 pathology, Quarantine
- Abstract
The rapid spread of SARS-CoV-2 and its threat to health systems worldwide have led governments to take acute actions to enforce social distancing. Previous studies used complex epidemiological models to quantify the effect of lockdown policies on infection rates. However, these rely on prior assumptions or on official regulations. Here, we use country-specific reports of daily mobility from people cellular usage to model social distancing. Our data-driven model enabled the extraction of lockdown characteristics which were crossed with observed mortality rates to show that: (i) the time at which social distancing was initiated is highly correlated with the number of deaths, r
2 = 0.64, while the lockdown strictness or its duration is not as informative; (ii) a delay of 7.49 days in initiating social distancing would double the number of deaths; and (iii) the immediate response has a prolonged effect on COVID-19 death toll., (© 2020 The Authors. Published under the terms of the CC BY 4.0 license.)- Published
- 2020
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37. ModelTeller: Model Selection for Optimal Phylogenetic Reconstruction Using Machine Learning.
- Author
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Abadi S, Avram O, Rosset S, Pupko T, and Mayrose I
- Subjects
- Machine Learning, Models, Genetic, Phylogeny
- Abstract
Statistical criteria have long been the standard for selecting the best model for phylogenetic reconstruction and downstream statistical inference. Although model selection is regarded as a fundamental step in phylogenetics, existing methods for this task consume computational resources for long processing time, they are not always feasible, and sometimes depend on preliminary assumptions which do not hold for sequence data. Moreover, although these methods are dedicated to revealing the processes that underlie the sequence data, they do not always produce the most accurate trees. Notably, phylogeny reconstruction consists of two related tasks, topology reconstruction and branch-length estimation. It was previously shown that in many cases the most complex model, GTR+I+G, leads to topologies that are as accurate as using existing model selection criteria, but overestimates branch lengths. Here, we present ModelTeller, a computational methodology for phylogenetic model selection, devised within the machine-learning framework, optimized to predict the most accurate nucleotide substitution model for branch-length estimation. We demonstrate that ModelTeller leads to more accurate branch-length inference than current model selection criteria on data sets simulated under realistic processes. ModelTeller relies on a readily implemented machine-learning model and thus the prediction according to features extracted from the sequence data results in a substantial decrease in running time compared with existing strategies. By harnessing the machine-learning framework, we distinguish between features that mostly contribute to branch-length optimization, concerning the extent of sequence divergence, and features that are related to estimates of the model parameters that are important for the selection made by current criteria., (© The Author(s) 2020. Published by Oxford University Press on behalf of the Society for Molecular Biology and Evolution. All rights reserved. For permissions, please e-mail: journals.permissions@oup.com.)
- Published
- 2020
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- View/download PDF
38. Heterogeneity in the rate of molecular sequence evolution substantially impacts the accuracy of detecting shifts in diversification rates.
- Author
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Shafir A, Azouri D, Goldberg EE, and Mayrose I
- Subjects
- Computer Simulation, Biological Evolution, Models, Genetic
- Abstract
As species richness varies along the tree of life, there is a great interest in identifying factors that affect the rates by which lineages speciate or go extinct. To this end, theoretical biologists have developed a suite of phylogenetic comparative methods that aim to identify where shifts in diversification rates had occurred along a phylogeny and whether they are associated with some traits. Using these methods, numerous studies have predicted that speciation and extinction rates vary across the tree of life. In this study, we show that asymmetric rates of sequence evolution lead to systematic biases in the inferred phylogeny, which in turn lead to erroneous inferences regarding lineage diversification patterns. The results demonstrate that as the asymmetry in sequence evolution rates increases, so does the tendency to select more complicated models that include the possibility of diversification rate shifts. These results thus suggest that any inference regarding shifts in diversification pattern should be treated with great caution, at least until any biases regarding the molecular substitution rate have been ruled out., (© 2020 The Authors. Evolution © 2020 The Society for the Study of Evolution.)
- Published
- 2020
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39. TRY plant trait database - enhanced coverage and open access.
- Author
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Kattge J, Bönisch G, Díaz S, Lavorel S, Prentice IC, Leadley P, Tautenhahn S, Werner GDA, Aakala T, Abedi M, Acosta ATR, Adamidis GC, Adamson K, Aiba M, Albert CH, Alcántara JM, Alcázar C C, Aleixo I, Ali H, Amiaud B, Ammer C, Amoroso MM, Anand M, Anderson C, Anten N, Antos J, Apgaua DMG, Ashman TL, Asmara DH, Asner GP, Aspinwall M, Atkin O, Aubin I, Baastrup-Spohr L, Bahalkeh K, Bahn M, Baker T, Baker WJ, Bakker JP, Baldocchi D, Baltzer J, Banerjee A, Baranger A, Barlow J, Barneche DR, Baruch Z, Bastianelli D, Battles J, Bauerle W, Bauters M, Bazzato E, Beckmann M, Beeckman H, Beierkuhnlein C, Bekker R, Belfry G, Belluau M, Beloiu M, Benavides R, Benomar L, Berdugo-Lattke ML, Berenguer E, Bergamin R, Bergmann J, Bergmann Carlucci M, Berner L, Bernhardt-Römermann M, Bigler C, Bjorkman AD, Blackman C, Blanco C, Blonder B, Blumenthal D, Bocanegra-González KT, Boeckx P, Bohlman S, Böhning-Gaese K, Boisvert-Marsh L, Bond W, Bond-Lamberty B, Boom A, Boonman CCF, Bordin K, Boughton EH, Boukili V, Bowman DMJS, Bravo S, Brendel MR, Broadley MR, Brown KA, Bruelheide H, Brumnich F, Bruun HH, Bruy D, Buchanan SW, Bucher SF, Buchmann N, Buitenwerf R, Bunker DE, Bürger J, Burrascano S, Burslem DFRP, Butterfield BJ, Byun C, Marques M, Scalon MC, Caccianiga M, Cadotte M, Cailleret M, Camac J, Camarero JJ, Campany C, Campetella G, Campos JA, Cano-Arboleda L, Canullo R, Carbognani M, Carvalho F, Casanoves F, Castagneyrol B, Catford JA, Cavender-Bares J, Cerabolini BEL, Cervellini M, Chacón-Madrigal E, Chapin K, Chapin FS, Chelli S, Chen SC, Chen A, Cherubini P, Chianucci F, Choat B, Chung KS, Chytrý M, Ciccarelli D, Coll L, Collins CG, Conti L, Coomes D, Cornelissen JHC, Cornwell WK, Corona P, Coyea M, Craine J, Craven D, Cromsigt JPGM, Csecserits A, Cufar K, Cuntz M, da Silva AC, Dahlin KM, Dainese M, Dalke I, Dalle Fratte M, Dang-Le AT, Danihelka J, Dannoura M, Dawson S, de Beer AJ, De Frutos A, De Long JR, Dechant B, Delagrange S, Delpierre N, Derroire G, Dias AS, Diaz-Toribio MH, Dimitrakopoulos PG, Dobrowolski M, Doktor D, Dřevojan P, Dong N, Dransfield J, Dressler S, Duarte L, Ducouret E, Dullinger S, Durka W, Duursma R, Dymova O, E-Vojtkó A, Eckstein RL, Ejtehadi H, Elser J, Emilio T, Engemann K, Erfanian MB, Erfmeier A, Esquivel-Muelbert A, Esser G, Estiarte M, Domingues TF, Fagan WF, Fagúndez J, Falster DS, Fan Y, Fang J, Farris E, Fazlioglu F, Feng Y, Fernandez-Mendez F, Ferrara C, Ferreira J, Fidelis A, Finegan B, Firn J, Flowers TJ, Flynn DFB, Fontana V, Forey E, Forgiarini C, François L, Frangipani M, Frank D, Frenette-Dussault C, Freschet GT, Fry EL, Fyllas NM, Mazzochini GG, Gachet S, Gallagher R, Ganade G, Ganga F, García-Palacios P, Gargaglione V, Garnier E, Garrido JL, de Gasper AL, Gea-Izquierdo G, Gibson D, Gillison AN, Giroldo A, Glasenhardt MC, Gleason S, Gliesch M, Goldberg E, Göldel B, Gonzalez-Akre E, Gonzalez-Andujar JL, González-Melo A, González-Robles A, Graae BJ, Granda E, Graves S, Green WA, Gregor T, Gross N, Guerin GR, Günther A, Gutiérrez AG, Haddock L, Haines A, Hall J, Hambuckers A, Han W, Harrison SP, Hattingh W, Hawes JE, He T, He P, Heberling JM, Helm A, Hempel S, Hentschel J, Hérault B, Hereş AM, Herz K, Heuertz M, Hickler T, Hietz P, Higuchi P, Hipp AL, Hirons A, Hock M, Hogan JA, Holl K, Honnay O, Hornstein D, Hou E, Hough-Snee N, Hovstad KA, Ichie T, Igić B, Illa E, Isaac M, Ishihara M, Ivanov L, Ivanova L, Iversen CM, Izquierdo J, Jackson RB, Jackson B, Jactel H, Jagodzinski AM, Jandt U, Jansen S, Jenkins T, Jentsch A, Jespersen JRP, Jiang GF, Johansen JL, Johnson D, Jokela EJ, Joly CA, Jordan GJ, Joseph GS, Junaedi D, Junker RR, Justes E, Kabzems R, Kane J, Kaplan Z, Kattenborn T, Kavelenova L, Kearsley E, Kempel A, Kenzo T, Kerkhoff A, Khalil MI, Kinlock NL, Kissling WD, Kitajima K, Kitzberger T, Kjøller R, Klein T, Kleyer M, Klimešová J, Klipel J, Kloeppel B, Klotz S, Knops JMH, Kohyama T, Koike F, Kollmann J, Komac B, Komatsu K, König C, Kraft NJB, Kramer K, Kreft H, Kühn I, Kumarathunge D, Kuppler J, Kurokawa H, Kurosawa Y, Kuyah S, Laclau JP, Lafleur B, Lallai E, Lamb E, Lamprecht A, Larkin DJ, Laughlin D, Le Bagousse-Pinguet Y, le Maire G, le Roux PC, le Roux E, Lee T, Lens F, Lewis SL, Lhotsky B, Li Y, Li X, Lichstein JW, Liebergesell M, Lim JY, Lin YS, Linares JC, Liu C, Liu D, Liu U, Livingstone S, Llusià J, Lohbeck M, López-García Á, Lopez-Gonzalez G, Lososová Z, Louault F, Lukács BA, Lukeš P, Luo Y, Lussu M, Ma S, Maciel Rabelo Pereira C, Mack M, Maire V, Mäkelä A, Mäkinen H, Malhado ACM, Mallik A, Manning P, Manzoni S, Marchetti Z, Marchino L, Marcilio-Silva V, Marcon E, Marignani M, Markesteijn L, Martin A, Martínez-Garza C, Martínez-Vilalta J, Mašková T, Mason K, Mason N, Massad TJ, Masse J, Mayrose I, McCarthy J, McCormack ML, McCulloh K, McFadden IR, McGill BJ, McPartland MY, Medeiros JS, Medlyn B, Meerts P, Mehrabi Z, Meir P, Melo FPL, Mencuccini M, Meredieu C, Messier J, Mészáros I, Metsaranta J, Michaletz ST, Michelaki C, Migalina S, Milla R, Miller JED, Minden V, Ming R, Mokany K, Moles AT, Molnár A 5th, Molofsky J, Molz M, Montgomery RA, Monty A, Moravcová L, Moreno-Martínez A, Moretti M, Mori AS, Mori S, Morris D, Morrison J, Mucina L, Mueller S, Muir CD, Müller SC, Munoz F, Myers-Smith IH, Myster RW, Nagano M, Naidu S, Narayanan A, Natesan B, Negoita L, Nelson AS, Neuschulz EL, Ni J, Niedrist G, Nieto J, Niinemets Ü, Nolan R, Nottebrock H, Nouvellon Y, Novakovskiy A, Nystuen KO, O'Grady A, O'Hara K, O'Reilly-Nugent A, Oakley S, Oberhuber W, Ohtsuka T, Oliveira R, Öllerer K, Olson ME, Onipchenko V, Onoda Y, Onstein RE, Ordonez JC, Osada N, Ostonen I, Ottaviani G, Otto S, Overbeck GE, Ozinga WA, Pahl AT, Paine CET, Pakeman RJ, Papageorgiou AC, Parfionova E, Pärtel M, Patacca M, Paula S, Paule J, Pauli H, Pausas JG, Peco B, Penuelas J, Perea A, Peri PL, Petisco-Souza AC, Petraglia A, Petritan AM, Phillips OL, Pierce S, Pillar VD, Pisek J, Pomogaybin A, Poorter H, Portsmuth A, Poschlod P, Potvin C, Pounds D, Powell AS, Power SA, Prinzing A, Puglielli G, Pyšek P, Raevel V, Rammig A, Ransijn J, Ray CA, Reich PB, Reichstein M, Reid DEB, Réjou-Méchain M, de Dios VR, Ribeiro S, Richardson S, Riibak K, Rillig MC, Riviera F, Robert EMR, Roberts S, Robroek B, Roddy A, Rodrigues AV, Rogers A, Rollinson E, Rolo V, Römermann C, Ronzhina D, Roscher C, Rosell JA, Rosenfield MF, Rossi C, Roy DB, Royer-Tardif S, Rüger N, Ruiz-Peinado R, Rumpf SB, Rusch GM, Ryo M, Sack L, Saldaña A, Salgado-Negret B, Salguero-Gomez R, Santa-Regina I, Santacruz-García AC, Santos J, Sardans J, Schamp B, Scherer-Lorenzen M, Schleuning M, Schmid B, Schmidt M, Schmitt S, Schneider JV, Schowanek SD, Schrader J, Schrodt F, Schuldt B, Schurr F, Selaya Garvizu G, Semchenko M, Seymour C, Sfair JC, Sharpe JM, Sheppard CS, Sheremetiev S, Shiodera S, Shipley B, Shovon TA, Siebenkäs A, Sierra C, Silva V, Silva M, Sitzia T, Sjöman H, Slot M, Smith NG, Sodhi D, Soltis P, Soltis D, Somers B, Sonnier G, Sørensen MV, Sosinski EE Jr, Soudzilovskaia NA, Souza AF, Spasojevic M, Sperandii MG, Stan AB, Stegen J, Steinbauer K, Stephan JG, Sterck F, Stojanovic DB, Strydom T, Suarez ML, Svenning JC, Svitková I, Svitok M, Svoboda M, Swaine E, Swenson N, Tabarelli M, Takagi K, Tappeiner U, Tarifa R, Tauugourdeau S, Tavsanoglu C, Te Beest M, Tedersoo L, Thiffault N, Thom D, Thomas E, Thompson K, Thornton PE, Thuiller W, Tichý L, Tissue D, Tjoelker MG, Tng DYP, Tobias J, Török P, Tarin T, Torres-Ruiz JM, Tóthmérész B, Treurnicht M, Trivellone V, Trolliet F, Trotsiuk V, Tsakalos JL, Tsiripidis I, Tysklind N, Umehara T, Usoltsev V, Vadeboncoeur M, Vaezi J, Valladares F, Vamosi J, van Bodegom PM, van Breugel M, Van Cleemput E, van de Weg M, van der Merwe S, van der Plas F, van der Sande MT, van Kleunen M, Van Meerbeek K, Vanderwel M, Vanselow KA, Vårhammar A, Varone L, Vasquez Valderrama MY, Vassilev K, Vellend M, Veneklaas EJ, Verbeeck H, Verheyen K, Vibrans A, Vieira I, Villacís J, Violle C, Vivek P, Wagner K, Waldram M, Waldron A, Walker AP, Waller M, Walther G, Wang H, Wang F, Wang W, Watkins H, Watkins J, Weber U, Weedon JT, Wei L, Weigelt P, Weiher E, Wells AW, Wellstein C, Wenk E, Westoby M, Westwood A, White PJ, Whitten M, Williams M, Winkler DE, Winter K, Womack C, Wright IJ, Wright SJ, Wright J, Pinho BX, Ximenes F, Yamada T, Yamaji K, Yanai R, Yankov N, Yguel B, Zanini KJ, Zanne AE, Zelený D, Zhao YP, Zheng J, Zheng J, Ziemińska K, Zirbel CR, Zizka G, Zo-Bi IC, Zotz G, and Wirth C
- Subjects
- Biodiversity, Ecology, Plants, Access to Information, Ecosystem
- Abstract
Plant traits-the morphological, anatomical, physiological, biochemical and phenological characteristics of plants-determine how plants respond to environmental factors, affect other trophic levels, and influence ecosystem properties and their benefits and detriments to people. Plant trait data thus represent the basis for a vast area of research spanning from evolutionary biology, community and functional ecology, to biodiversity conservation, ecosystem and landscape management, restoration, biogeography and earth system modelling. Since its foundation in 2007, the TRY database of plant traits has grown continuously. It now provides unprecedented data coverage under an open access data policy and is the main plant trait database used by the research community worldwide. Increasingly, the TRY database also supports new frontiers of trait-based plant research, including the identification of data gaps and the subsequent mobilization or measurement of new data. To support this development, in this article we evaluate the extent of the trait data compiled in TRY and analyse emerging patterns of data coverage and representativeness. Best species coverage is achieved for categorical traits-almost complete coverage for 'plant growth form'. However, most traits relevant for ecology and vegetation modelling are characterized by continuous intraspecific variation and trait-environmental relationships. These traits have to be measured on individual plants in their respective environment. Despite unprecedented data coverage, we observe a humbling lack of completeness and representativeness of these continuous traits in many aspects. We, therefore, conclude that reducing data gaps and biases in the TRY database remains a key challenge and requires a coordinated approach to data mobilization and trait measurements. This can only be achieved in collaboration with other initiatives., (© 2019 The Authors. Global Change Biology published by John Wiley & Sons Ltd.)
- Published
- 2020
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40. Interaction among ploidy, breeding system and lineage diversification.
- Author
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Zenil-Ferguson R, Burleigh JG, Freyman WA, Igić B, Mayrose I, and Goldberg EE
- Subjects
- Bayes Theorem, Models, Biological, Polyploidy, Quantitative Trait, Heritable, Biodiversity, Phylogeny, Plant Breeding, Ploidies
- Abstract
If particular traits consistently affect rates of speciation and extinction, broad macroevolutionary patterns can be interpreted as consequences of selection at high levels of the biological hierarchy. Identifying traits associated with diversification rates is difficult because of the wide variety of characters under consideration and the statistical challenges of testing for associations from comparative phylogenetic data. Ploidy (diploid vs polyploid states) and breeding system (self-incompatible vs self-compatible states) are both thought to be drivers of differential diversification in angiosperms. We fit 29 diversification models to extensive trait and phylogenetic data in Solanaceae and investigate how speciation and extinction rate differences are associated with ploidy, breeding system, and the interaction between these traits. We show that diversification patterns in Solanaceae are better explained by breeding system and an additional unobserved factor, rather than by ploidy. We also find that the most common evolutionary pathway to polyploidy in Solanaceae occurs via direct breakdown of self-incompatibility by whole genome duplication, rather than indirectly via breakdown followed by polyploidization. Comparing multiple stochastic diversification models that include complex trait interactions alongside hidden states enhances our understanding of the macroevolutionary patterns in plant phylogenies., (© 2019 The Authors. New Phytologist © 2019 New Phytologist Trust.)
- Published
- 2019
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41. Meiotic drive shapes rates of karyotype evolution in mammals.
- Author
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Blackmon H, Justison J, Mayrose I, and Goldberg EE
- Subjects
- Animals, Female, Models, Genetic, Biological Evolution, Karyotype, Mammals genetics, Meiosis
- Abstract
Chromosome number is perhaps the most basic characteristic of a genome, yet generalizations that can explain the evolution of this trait across large clades have remained elusive. Using karyotype data from over 1000 mammals, we developed and applied a phylogenetic model of chromosome evolution that links chromosome number changes with karyotype morphology. Using our model, we infer that rates of chromosome number evolution are significantly lower in species with karyotypes that consist of either all bibrachial or all monobrachial chromosomes than in species with a mix of both types of morphologies. We suggest that species with homogeneous karyotypes may represent cases where meiotic drive acts to stabilize the karyotype, favoring the chromosome morphologies already present in the genome. In contrast, rapid bouts of chromosome number evolution in taxa with mixed karyotypes may indicate that a switch in the polarity of female meiotic drive favors changes in chromosome number. We do not find any evidence that karyotype morphology affects rates of speciation or extinction. Furthermore, we document that switches in meiotic drive polarity are likely common and have occurred in most major clades of mammals, and that rapid remodeling of karyotypes may be more common than once thought., (2019 The Authors Evolution published by Wiley Periodicals, Inc. on behalf of The Society for the Study of Evolution.)
- Published
- 2019
- Full Text
- View/download PDF
42. Model selection may not be a mandatory step for phylogeny reconstruction.
- Author
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Abadi S, Azouri D, Pupko T, and Mayrose I
- Subjects
- Evolution, Molecular, Models, Genetic, Phylogeny
- Abstract
Determining the most suitable model for phylogeny reconstruction constitutes a fundamental step in numerous evolutionary studies. Over the years, various criteria for model selection have been proposed, leading to debate over which criterion is preferable. However, the necessity of this procedure has not been questioned to date. Here, we demonstrate that although incongruency regarding the selected model is frequent over empirical and simulated data, all criteria lead to very similar inferences. When topologies and ancestral sequence reconstruction are the desired output, choosing one criterion over another is not crucial. Moreover, skipping model selection and using instead the most parameter-rich model, GTR+I+G, leads to similar inferences, thus rendering this time-consuming step nonessential, at least under current strategies of model selection.
- Published
- 2019
- Full Text
- View/download PDF
43. The global biogeography of polyploid plants.
- Author
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Rice A, Šmarda P, Novosolov M, Drori M, Glick L, Sabath N, Meiri S, Belmaker J, and Mayrose I
- Subjects
- Forests, Biological Evolution, Phylogeography, Plants genetics, Polyploidy
- Abstract
Deciphering the global distribution of polyploid plants is fundamental for understanding plant evolution and ecology. Many factors have been hypothesized to affect the uneven distribution of polyploid plants across the globe. Nevertheless, the lack of large comparative datasets has restricted such studies to local floras and to narrow taxonomical scopes, limiting our understanding of the underlying drivers of polyploid plant distribution. We present a map portraying the worldwide polyploid frequencies, based on extensive spatial data coupled with phylogeny-based polyploidy inference for tens of thousands of species. This allowed us to assess the potential global drivers affecting polyploid distribution. Our data reveal a clear latitudinal trend, with polyploid frequency increasing away from the equator. Climate, especially temperature, appears to be the most influential predictor of polyploid distribution. However, we find this effect to be mostly indirect, mediated predominantly by variation in plant lifeforms and, to a lesser extent, by taxonomical composition and species richness. Thus, our study presents an emerging view of polyploid distribution that highlights attributes that facilitate the establishment of new polyploid lineages by providing polyploids with sufficient time (that is, perenniality) and space (low species richness) to compete with pre-adapted diploid relatives.
- Published
- 2019
- Full Text
- View/download PDF
44. OneTwoTree: An online tool for phylogeny reconstruction.
- Author
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Drori M, Rice A, Einhorn M, Chay O, Glick L, and Mayrose I
- Subjects
- Internet, Plantaginaceae classification, Plantaginaceae genetics, Computational Biology methods, Phylogeny
- Abstract
Phylogeny reconstruction is a key instrument in numerous biological analyses, ranging from evolutionary and ecology research, to conservation and systems biology. The increasing accumulation of genomic data makes it possible to reconstruct phylogenies with both high accuracy and at increasingly finer resolution. Yet, taking advantage of the enormous amount of sequence data available requires the use of computational tools for efficient data retrieval and processing, or else the process could quickly become an error-prone endeavour. Here, we present OneTwoTree (http://onetwotree.tau.ac.il/), a Web-based tool for tree reconstruction based on the supermatrix paradigm. Given a list of taxa names of interest as the sole input requirement, OneTwoTree retrieves all available sequence data from NCBI GenBank, clusters these into orthology groups, identifies the most informative set of markers, searches for an appropriate outgroup, and assembles a partitioned sequence matrix that is then used for the final phylogeny reconstruction step. OneTwoTree further allows users to control various steps of the process, such as the merging of sequences from similar clusters, or phylogeny reconstruction based on markers from a specific genome type. By comparing the performance of OneTwoTree to a manually reconstructed phylogeny of the Antirrhineae tribe, we show that the use of OneTwoTree resulted in substantially higher data coverage in terms of both taxon sampling and the number of informative markers assembled. OneTwoTree provides a flexible online tool for species-tree reconstruction, aimed to assist researchers ranging in their level of prior expertise in the task of phylogeny reconstruction., (© 2018 John Wiley & Sons Ltd.)
- Published
- 2018
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45. Broad phylogenetic analysis of cation/proton antiporters reveals transport determinants.
- Author
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Masrati G, Dwivedi M, Rimon A, Gluck-Margolin Y, Kessel A, Ashkenazy H, Mayrose I, Padan E, and Ben-Tal N
- Subjects
- Amino Acids metabolism, Binding Sites, Cations, Humans, Models, Molecular, Mutation genetics, Protein Transport drug effects, Sodium pharmacology, Valinomycin pharmacology, Antiporters classification, Phylogeny, Protons
- Abstract
Cation/proton antiporters (CPAs) play a major role in maintaining living cells' homeostasis. CPAs are commonly divided into two main groups, CPA1 and CPA2, and are further characterized by two main phenotypes: ion selectivity and electrogenicity. However, tracing the evolutionary relationships of these transporters is challenging because of the high diversity within CPAs. Here, we conduct comprehensive evolutionary analysis of 6537 representative CPAs, describing the full complexity of their phylogeny, and revealing a sequence motif that appears to determine central phenotypic characteristics. In contrast to previous suggestions, we show that the CPA1/CPA2 division only partially correlates with electrogenicity. Our analysis further indicates two acidic residues in the binding site that carry the protons in electrogenic CPAs, and a polar residue in the unwound transmembrane helix 4 that determines ion selectivity. A rationally designed triple mutant successfully converted the electrogenic CPA, EcNhaA, to be electroneutral.
- Published
- 2018
- Full Text
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46. CRISPys: Optimal sgRNA Design for Editing Multiple Members of a Gene Family Using the CRISPR System.
- Author
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Hyams G, Abadi S, Lahav S, Avni A, Halperin E, Shani E, and Mayrose I
- Subjects
- Algorithms, Base Sequence, Computer Simulation, Gene Knockout Techniques, Genes, Plant genetics, Genome, Plant genetics, Solanum lycopersicum genetics, Models, Genetic, RNA, Guide, CRISPR-Cas Systems metabolism, CRISPR-Cas Systems, Gene Editing methods, Genomics methods, RNA, Guide, CRISPR-Cas Systems genetics
- Abstract
The development of the CRISPR-Cas9 system in recent years has made eukaryotic genome editing, and specifically gene knockout for reverse genetics, a simple and effective task. The system is directed to a genomic target site by a programmed single-guide RNA (sgRNA) that base-pairs with it, subsequently leading to site-specific modifications. However, many gene families in eukaryotic genomes exhibit partially overlapping functions, and thus, the knockout of one gene might be concealed by the function of the other. In such cases, the reduced specificity of the CRISPR-Cas9 system, which may lead to the modification of genomic sites that are not identical to the sgRNA, can be harnessed for the simultaneous knockout of multiple homologous genes. We introduce CRISPys, an algorithm for the optimal design of sgRNAs that would potentially target multiple members of a given gene family. CRISPys first clusters all the potential targets in the input sequences into a hierarchical tree structure that specifies the similarity among them. Then, sgRNAs are proposed in the internal nodes of the tree by embedding mismatches where needed, such that the efficiency to edit the induced targets is maximized. We suggest several approaches for designing the optimal individual sgRNA and an approach to compute the optimal set of sgRNAs for cases when the experimental platform allows for more than one. The latter may optionally account for the homologous relationships among gene-family members. We further show that CRISPys outperforms simpler alignment-based techniques by in silico examination over all gene families in the Solanum lycopersicum genome., (Copyright © 2018 Elsevier Ltd. All rights reserved.)
- Published
- 2018
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47. Macroevolutionary Patterns of Flowering Plant Speciation and Extinction.
- Author
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Vamosi JC, Magallón S, Mayrose I, Otto SP, and Sauquet H
- Subjects
- Biodiversity, Magnoliopsida genetics, Phylogeny, Biological Evolution, Extinction, Biological, Genetic Speciation, Magnoliopsida physiology
- Abstract
Species diversity is remarkably unevenly distributed among flowering plant lineages. Despite a growing toolbox of research methods, the reasons underlying this patchy pattern have continued to perplex plant biologists for the past two decades. In this review, we examine the present understanding of transitions in flowering plant evolution that have been proposed to influence speciation and extinction. In particular, ploidy changes, transitions between tropical and nontropical biomes, and shifts in floral form have received attention and have offered some surprises in terms of which factors influence speciation and extinction rates. Mating systems and dispersal characteristics once predominated as determining factors, yet recent evidence suggests that these changes are not as influential as previously thought or are important only when paired with range shifts. Although range extent is an important correlate of speciation, it also influences extinction and brings an applied focus to diversification research. Recent studies that find that past diversification can predict present-day extinction risk open an exciting avenue for future research to help guide conservation prioritization.
- Published
- 2018
- Full Text
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48. Multispeed genome diploidization and diversification after an ancient allopolyploidization.
- Author
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Mandáková T, Pouch M, Harmanová K, Zhan SH, Mayrose I, and Lysak MA
- Subjects
- Australia, Brassicaceae genetics, Chromosome Painting, DNA, Plant genetics, Gene Rearrangement, Genome, Plant, New Zealand, Phylogeny, Biological Evolution, Brassicaceae classification, Hybridization, Genetic, Polyploidy
- Abstract
Hybridization and genome doubling (allopolyploidy) have led to evolutionary novelties as well as to the origin of new clades and species. Despite the importance of allopolyploidization, the dynamics of postpolyploid diploidization (PPD) at the genome level has been only sparsely studied. The Microlepidieae (MICR) is a crucifer tribe of 17 genera and c. 56 species endemic to Australia and New Zealand. Our phylogenetic and cytogenomic analyses revealed that MICR originated via an intertribal hybridization between ancestors of Crucihimalayeae (n = 8; maternal genome) and Smelowskieae (n = 7; paternal genome), both native to the Northern Hemisphere. The reconstructed ancestral allopolyploid genome (n = 15) originated probably in northeastern Asia or western North America during the Late Miocene (c. 10.6-7 million years ago) and reached the Australian mainland via long-distance dispersal. In Australia, the allotetraploid genome diverged into at least three main subclades exhibiting different levels of PPD and diversity: 1.25-fold descending dysploidy (DD) of n = 15 → n = 12 (autopolyploidy → 24) in perennial Arabidella (3 species), 1.5-fold DD of n = 15 → n = 10 in the perennial Pachycladon (11 spp.) and 2.1-3.75-fold DD of n = 15 → n = 7-4 in the largely annual crown-group genera (42 spp. in 15 genera). These results are among the first to demonstrate multispeed genome evolution in taxa descending from a common allopolyploid ancestor. It is suggested that clade-specific PPD can operate at different rates and efficacies and can be tentatively linked to life histories and the extent of taxonomic diversity., (© 2017 John Wiley & Sons Ltd.)
- Published
- 2017
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49. An Integrated Model of Phenotypic Trait Changes and Site-Specific Sequence Evolution.
- Author
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Levy Karin E, Wicke S, Pupko T, and Mayrose I
- Subjects
- Computer Simulation, Genome, Plastid genetics, Phenotype, Classification methods, Evolution, Molecular, Genome, Plant genetics, Models, Genetic
- Abstract
Recent years have seen a constant rise in the availability of trait data, including morphological features, ecological preferences, and life history characteristics. These phenotypic data provide means to associate genomic regions with phenotypic attributes, thus allowing the identification of phenotypic traits associated with the rate of genome and sequence evolution. However, inference methodologies that analyze sequence and phenotypic data in a unified statistical framework are still scarce. Here, we present TraitRateProp, a probabilistic method that allows testing whether the rate of sequence evolution is associated with a binary phenotypic character trait. The method further allows the detection of specific sequence sites whose evolutionary rate is most noticeably affected following the character transition, suggesting a shift in functional/structural constraints. TraitRateProp is first evaluated in simulations and then applied to study the evolutionary process of plastid plant genomes upon a transition to a heterotrophic lifestyle. To this end, we analyze 20 plastid genes across 85 orchid species, spanning different lifestyles and representing different genera in this large family of flowering plants. Our results indicate higher evolutionary rates following repeated transitions to a heterotrophic lifestyle in all but four of the loci analyzed. [Evolutionary models; evolutionary rate; genotype-phenotype; orchids; plastome; rate shift.]., (© The Author(s) 2017. Published by Oxford University Press, on behalf of the Society of Systematic Biologists. All rights reserved. For Permissions, please email: journals.permissions@oup.com.)
- Published
- 2017
- Full Text
- View/download PDF
50. A machine learning approach for predicting CRISPR-Cas9 cleavage efficiencies and patterns underlying its mechanism of action.
- Author
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Abadi S, Yan WX, Amar D, and Mayrose I
- Subjects
- Algorithms, Humans, RNA, Guide, CRISPR-Cas Systems genetics, ROC Curve, CRISPR-Cas Systems genetics, Computational Biology methods, Gene Editing methods, Machine Learning
- Abstract
The adaptation of the CRISPR-Cas9 system as a genome editing technique has generated much excitement in recent years owing to its ability to manipulate targeted genes and genomic regions that are complementary to a programmed single guide RNA (sgRNA). However, the efficacy of a specific sgRNA is not uniquely defined by exact sequence homology to the target site, thus unintended off-targets might additionally be cleaved. Current methods for sgRNA design are mainly concerned with predicting off-targets for a given sgRNA using basic sequence features and employ elementary rules for ranking possible sgRNAs. Here, we introduce CRISTA (CRISPR Target Assessment), a novel algorithm within the machine learning framework that determines the propensity of a genomic site to be cleaved by a given sgRNA. We show that the predictions made with CRISTA are more accurate than other available methodologies. We further demonstrate that the occurrence of bulges is not a rare phenomenon and should be accounted for in the prediction process. Beyond predicting cleavage efficiencies, the learning process provides inferences regarding patterns that underlie the mechanism of action of the CRISPR-Cas9 system. We discover that attributes that describe the spatial structure and rigidity of the entire genomic site as well as those surrounding the PAM region are a major component of the prediction capabilities.
- Published
- 2017
- Full Text
- View/download PDF
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