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

Author

Kattge, J, Bönisch, G, Díaz, S, Lavorel, S, Prentice, IC, Leadley, P, Tautenhahn, A, Werner, GDA, Aakala, T, Abedi, M, Acosta, ATR, Adamidis, GC, K, Adamson., Aiba, M, Albert, CH, Alcántara, JM, Alcázar, 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, Salguero-Gomez, R, and Terrestrial Ecology (TE)

Subjects
Access to Information, Ecology, Plan_S-Compliant-TA, international, food and beverages, Biodiversity, Plants, 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.

Published
2020

2. TRY plant trait database enhanced coverage and open access

Author

Kattge, J., Bönisch, G., Díaz, 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., Alcántara, J.M., Alcázar, 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-Römermann, M., Bigler, C., Bjorkman, A.D., Blackman, C., Blanco, C., Blonder, B., Blumenthal, D., Bocanegra-González, K.T., Boeckx, P., Bohlman, S., Böhning-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., Brendel, 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., Bürger, J., Burrascano, Sabina, 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 Prieto, Juan Antonio, Cano-Arboleda, L., Canullo, R., Carbognani, M., Carvalho, F., Casanoves, F., Castagneyrol, B., Catford, J.A., Cavender-Bares, J., Cerabolini, Bruno E. L., Cervellini, M., Chacón-Madrigal, E., Chapin, K., Chapin, F.S., Chelli, S., Chen, S.-C., Chen, A., Cherubini, P., Chianucci, F., Choat, B., Chung, K.-S., Chytrý, Milan, 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., and da, Silva, A.C

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 and Sons Ltd

Published
2020

3. The bouquets of ecosystem services rendered by permanent hay meadows

Author

Elise Tasset, Morvan-Bertrand, A., Amiaud, B., J-B, Cliquet, Frédérique Louault, Katja Klumpp, Vecrin, R., Mischler, P., Husse, S., Servane Lemauviel-Lavenant, Ecophysiologie Végétale, Agronomie et Nutritions (EVA), Université de Caen Normandie (UNICAEN), Normandie Université (NU)-Normandie Université (NU)-Institut National de la Recherche Agronomique (INRA), Normandie Université (NU), 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), Chambre d’Agriculture de l'Orne (CA 61), Institut de l'Elevage, and PNR Lorraine

Subjects
stockage du carbone, fourrage, pratique de gestion des prairies, [SDE.MCG]Environmental Sciences/Global Changes, agroécologie, forage, permanent pastures, prairie permanente, biodiversité, fertilisation, pâturage permanent, gestion des prairies, fertilization, Agroecology
Abstract

Permanent grasslands produce high-quality forage and host very diverse plant communities. They also play a key role in carbon storage. However, we still understand little about how pedoclimatic conditions and plant community management or functioning help generate ecosystem services. This study analysed 32 grasslands in Normandy, Lorraine, and Auvergne that offer different ecosystem services. Certain grasslands had high values for service indicators. However, no synergies among services were observed, which suggests that determinant factors were different. A functional traits approach showed that plant community functioning directly affected forage quality. Plant diversity was tied to agricultural management and is also likely related to grassland history and landscape structure. Carbon storage levels were related to the clay content of soils.

Published
2019

4. Mapping local and global variability in plant trait distributions

Author

BUTLER, E. E., DATTA, A., FLORES-MORENO, H., CHEN, M., WYTHERS, K. R., FAZAYELI, F., BANERJEE, A., ATKIN, O. K., KATTGE, J., AMIAUD, B., BLONDER, B., BOENISCH, G., BOND-LAMBERTY, B., BROWN, K. A., BYUN, C., CAMPETELLA, G., CERABOLINI, B. E. L., CORNELISSEN, J. H. C., CRAINE, J. M., CRAVEN, D., DE VRIES, F. T., DIAZ, S., DOMINGUES, T. F., FOREY, E., GONZALEZ-MELO, A., GROSS, N., HAN, W., HATTINGH, W. N., HICKLER, T., JANSEN, S., SOSINSKI JUNIOR, E. E., KRAMER, K., ETHAN E. BUTLER, ABHIRUP DATTA, HABACUC FLORES-MORENO, MING CHEN, KIRK R. WYTHERS, FARIDEH FAZAYELI, ARINDAM BANERJEE, OWEN K. ATKIN, JENS KATTGE, BERNARD AMIAUD, BENJAMIN BLONDER, GERHARD BOENISCH, BEN BOND-LAMBERTY, KERRY A. BROWN, CHAEHO BYUN, GIANDIEGO CAMPETELLA, BRUNO E. L. CERABOLINI, JOHANNES H. C. CORNELISSEN, JOSEPH M. CRAINE, DYLAN CRAVEN, FRANCISKA T. DE VRIES, SANDRA DIAZ, TOMAS F. DOMINGUES, ESTELLE FOREY, ANDR?ES GONZALEZ-MELO, NICOLAS GROSS, WENXUAN HAN, WESLEY N. HATTINGH, THOMAS HICKLER, STEVEN JANSEN, ENIO EGON SOSINSKI JUNIOR, CPACT, and KOEN KRAMER.

Subjects
Clima
Abstract

Made available in DSpace on 2018-01-16T23:25:14Z (GMT). No. of bitstreams: 1 Enio2017PNAS2017ButlerE1093746.pdf: 2780433 bytes, checksum: 6961da4bb1493e231123f5627751b471 (MD5) Previous issue date: 2018-01-16

Published
2017

5. Functional diversity-area relationship in permanent grassland

Author

Simon Taugourdeau, Schneider, M., Domenicone, C., Sempe, L., Amiaud, B., Huguenin-Elie, O., and Plantureux, S.

Subjects
L02 - Alimentation animale, F40 - Écologie végétale, F08 - Systèmes et modes de culture, F70 - Taxonomie végétale et phytogéographie, U30 - Méthodes de recherche, human activities
Abstract

The target of a multi-functional, sustainable use of grasslands requires deeper understanding of the relationships between grassland management and plant diversity and its consequences on ecosystem functioning. Some of these relationships are well known for specific pedo-climatic conditions. One option to extend our knowledge to a broader range of conditions is to aggregate different studies by performing a meta-analysis. Nevertheless, differences in sampling area between studies is a major challenge. For taxonomic diversity, species-area curves have been established for different habitats but references for functional diversity are scarce. We aimed at assessing the possibility of using functional diversity-area curves to correct for differing sampling area between studies before merging data for overall analysis on functional diversity. We measured diversity in 9 nested areas of increasing size (from 0.01 m² to 100 m²) in 16 grasslands with different management (grazing, mowing).We analyzed the effect of area on specific richness, functional richness, functional divergence and community weighed mean value of several functional traits (SLA, LDMC) and on the percentage of legumes. We conclude that correction for differing sampling area is possible for functional richness and community weighted mean values.

Published
2012

6. Effects of cropping practice dynamics on permanent grassland vegetation during the conversion to organic farming

Author

GAUJOUR, E., AMIAUD, B., FIORELLI, J.-L., MIGNOLET, C., COQUIL, X., BELLON, S., DIOLEZ, A., HUYGHE, C., PENVERN, S., and SAVINI, I.

Subjects
Pasture and forage crops, Biodiversity and ecosystem services
Abstract

The aim of this work was to identify the impact of farming practices on permanent grassland vegetation during the conversion from conventional to organic farming. We considered functional and species diversities in order to compare the different grassland categories based on the farming practices used over a period of six years - five years before conversion and one year after. We identified three categories of grasslands: those generally cut twice a year, those intensely grazed, and those that were used under diversified practices. We showed that grasslands characterised by cutting and low fertilization level have the highest species richness compared to the other two categories (23.2, 16.9 and 17 species, respectively), and the lowest pastoral index (45.9, 66.8 and 68.6, respectively). These cut paddocks also presented the highest functional diversity (i.e., richness of functional property attributes) for two of the properties studied: means of dispersal and establishment strategy as defined by Grime. Grasslands with diversified practices (grazing, cutting and nitrogen supply) were not characterised by any single or combined functional property attribute, to the contrary of the two other categories. Finally, farming practices alone do not explain all of the differences in vegetation. We therefore hypothesize that, first, the dynamics of permanent grassland vegetation following conversion to organic farming is only initiated by agricultural practices and, second, other key factors such as landscape characteristics affect these dynamics.

Published
2009

9. The global spectrum of plant form and function: enhanced species-level trait dataset

Author

Sandra Díaz, Jens Kattge, Johannes H. C. Cornelissen, Ian J. Wright, Sandra Lavorel, Stéphane Dray, Björn Reu, Michael Kleyer, Christian Wirth, I. Colin Prentice, Eric Garnier, Gerhard Bönisch, Mark Westoby, Hendrik Poorter, Peter B. Reich, Angela T. Moles, John Dickie, Amy E. Zanne, Jérôme Chave, S. Joseph Wright, Serge N. Sheremetiev, Hervé Jactel, Christopher Baraloto, Bruno E. L. Cerabolini, Simon Pierce, Bill Shipley, Fernando Casanoves, Julia S. Joswig, Angela Günther, Valeria Falczuk, Nadja Rüger, Miguel D. Mahecha, Lucas D. Gorné, Bernard Amiaud, Owen K. Atkin, Michael Bahn, Dennis Baldocchi, Michael Beckmann, Benjamin Blonder, William Bond, Ben Bond-Lamberty, Kerry Brown, Sabina Burrascano, Chaeho Byun, Giandiego Campetella, Jeannine Cavender-Bares, F. Stuart Chapin, Brendan Choat, David Anthony Coomes, William K. Cornwell, Joseph Craine, Dylan Craven, Matteo Dainese, Alessandro Carioca de Araujo, Franciska T. de Vries, Tomas Ferreira Domingues, Brian J. Enquist, Jaime Fagúndez, Jingyun Fang, Fernando Fernández-Méndez, Maria T. Fernandez-Piedade, Henry Ford, Estelle Forey, Gregoire T. Freschet, Sophie Gachet, Rachael Gallagher, Walton Green, Greg R. Guerin, Alvaro G. Gutiérrez, Sandy P. Harrison, Wesley Neil Hattingh, Tianhua He, Thomas Hickler, Steven I. Higgins, Pedro Higuchi, Jugo Ilic, Robert B. Jackson, Adel Jalili, Steven Jansen, Fumito Koike, Christian König, Nathan Kraft, Koen Kramer, Holger Kreft, Ingolf Kühn, Hiroko Kurokawa, Eric G. Lamb, Daniel C. Laughlin, Michelle Leishman, Simon Lewis, Frédérique Louault, Ana C. M. Malhado, Peter Manning, Patrick Meir, Maurizio Mencuccini, Julie Messier, Regis Miller, Vanessa Minden, Jane Molofsky, Rebecca Montgomery, Gabriel Montserrat-Martí, Marco Moretti, Sandra Müller, Ülo Niinemets, Romà Ogaya, Kinga Öllerer, Vladimir Onipchenko, Yusuke Onoda, Wim A. Ozinga, Juli G. Pausas, Begoña Peco, Josep Penuelas, Valério D. Pillar, Clara Pladevall, Christine Römermann, Lawren Sack, Norma Salinas, Brody Sandel, Jordi Sardans, Brandon Schamp, Michael Scherer-Lorenzen, Ernst-Detlef Schulze, Fritz Schweingruber, Satomi Shiodera, Ênio Sosinski, Nadejda Soudzilovskaia, Marko J. Spasojevic, Emily Swaine, Nathan Swenson, Susanne Tautenhahn, Ken Thompson, Alexia Totte, Rocío Urrutia-Jalabert, Fernando Valladares, Peter van Bodegom, François Vasseur, Kris Verheyen, Denis Vile, Cyrille Violle, Betsy von Holle, Patrick Weigelt, Evan Weiher, Michael C. Wiemann, Mathew Williams, Justin Wright, Gerhard Zotz, Biology, General Botany and Nature Management, 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], Universidad Nacional de Córdoba [Argentina], Ecologie quantitative et évolutive des communautés, Département écologie évolutive [LBBE], Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Université Claude Bernard Lyon 1 (UCBL), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Centre National de la Recherche Scientifique (CNRS)-Laboratoire de Biométrie et Biologie Evolutive - UMR 5558 (LBBE), Université de Lyon-Université de Lyon-Institut National de Recherche en Informatique et en Automatique (Inria)-VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-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)-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, 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)-Université de Montpellier (UM), Biodiversité, Gènes & Communautés (BioGeCo), Université de Bordeaux (UB)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), Écophysiologie des Plantes sous Stress environnementaux (LEPSE), Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE)-Institut Agro Montpellier, 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), Etude et Compréhension de la biodiversité (ECODIV), Université de Rouen Normandie (UNIROUEN), Normandie Université (NU)-Normandie Université (NU), Unité Mixte de Recherche sur l'Ecosystème Prairial - UMR (UREP), VetAgro Sup - Institut national d'enseignement supérieur et de recherche en alimentation, santé animale, sciences agronomiques et de l'environnement (VAS)-Institut National de Recherche pour l’Agriculture, l’Alimentation et l’Environnement (INRAE), TRY initiative on plant traits (https://www.try-db.org).TRY is an initiative of the Max Planck Institute for Biogeochemistry, bioDISCOVERY/Future Earth (ICSU), the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and Nucleo DiverSus (CONICET-Universidad Nacional de Cordoba, Argentina)., The Global Spectrum of Plant Form and Function study has been supported by the European BACI project (Towards a Biosphere Atmosphere change Index, EU grant ID 640176), FONCyT, CONICET, Universidad Nacional de Cordoba, the Inter-American Institute for Global Change Research, and The Newton Fund (NERC UK -CONICET ARG), Díaz, Sandra [0000-0003-0012-4612], Kattge, Jens [0000-0002-1022-8469], Wright, Ian J [0000-0001-8338-9143], Lavorel, Sandra [0000-0002-7300-2811], Dray, Stéphane [0000-0003-0153-1105], Wirth, Christian [0000-0003-2604-8056], Garnier, Eric [0000-0002-9392-5154], Westoby, Mark [0000-0001-7690-4530], Reich, Peter B [0000-0003-4424-662X], Moles, Angela T [0000-0003-2041-7762], Zanne, Amy E [0000-0001-6379-9452], Chave, Jérôme [0000-0002-7766-1347], Wright, S Joseph [0000-0003-4260-5676], Sheremetiev, Serge N [0000-0002-0318-6766], Baraloto, Christopher [0000-0001-7322-8581], Cerabolini, Bruno EL [0000-0002-3793-0733], Casanoves, Fernando [0000-0001-8765-9382], Joswig, Julia S [0000-0002-7786-1728], Mahecha, Miguel D [0000-0003-3031-613X], Atkin, Owen K [0000-0003-1041-5202], Bahn, Michael [0000-0001-7482-9776], Bond, William [0000-0002-3441-2084], Bond-Lamberty, Ben [0000-0001-9525-4633], Byun, Chaeho [0000-0003-3209-3275], Campetella, Giandiego [0000-0001-6126-522X], Cavender-Bares, Jeannine [0000-0003-3375-9630], Chapin, F Stuart [0000-0002-2558-9910], Choat, Brendan [0000-0002-9105-640X], Coomes, David Anthony [0000-0002-8261-2582], Cornwell, William K [0000-0003-4080-4073], Craine, Joseph [0000-0001-6561-3244], Craven, Dylan [0000-0003-3940-833X], Dainese, Matteo [0000-0001-7052-5572], Domingues, Tomas Ferreira [0000-0003-2857-9838], Enquist, Brian J [0000-0002-6124-7096], Gallagher, Rachael [0000-0002-4680-8115], Harrison, Sandy P [0000-0001-5687-1903], Hattingh, Wesley Neil [0000-0002-3626-5137], He, Tianhua [0000-0002-0924-3637], Higuchi, Pedro [0000-0002-3855-555X], Jackson, Robert B [0000-0001-8846-7147], Jansen, Steven [0000-0002-4476-5334], Kreft, Holger [0000-0003-4471-8236], Kühn, Ingolf [0000-0003-1691-8249], Kurokawa, Hiroko [0000-0001-8778-8045], Laughlin, Daniel C [0000-0002-9651-5732], Manning, Peter [0000-0002-7940-2023], Mencuccini, Maurizio [0000-0003-0840-1477], Müller, Sandra [0000-0003-4289-755X], Pausas, Juli G [0000-0003-3533-5786], Penuelas, Josep [0000-0002-7215-0150], Pillar, Valério D [0000-0001-6408-2891], Sack, Lawren [0000-0002-7009-7202], Salinas, Norma [0000-0001-9941-2109], Sardans, Jordi [0000-0003-2478-0219], Scherer-Lorenzen, Michael [0000-0001-9566-590X], Sosinski, Ênio [0000-0001-6310-9474], Spasojevic, Marko J [0000-0003-1808-0048], Weigelt, Patrick [0000-0002-2485-3708], Williams, Mathew [0000-0001-6117-5208], Zotz, Gerhard [0000-0002-6823-2268], Apollo - University of Cambridge Repository, 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), Diaz, S, Kattge, J, Cornelissen, JHC, Wright, IJ, Lavorel, S, Dray, S, Reu, B, Kleyer, M, Wirth, C, Prentice, IC, Garnier, E, Bonisch, G, Westoby, M, Poorter, H, Reich, PB, Moles, AT, Dickie, J, Zanne, AE, Chave, J, Wright, SJ, Sheremetiev, SN, Jactel, H, Baraloto, C, Cerabolini, BEL, Pierce, S, Shipley, B, Casanoves, F, Joswig, JS, Gunther, A, Falczuk, V, Ruger, N, Mahecha, MD, Gorne, LD, Amiaud, B, Atkin, OK, Bahn, M, Baldocchi, D, Beckmann, M, Blonder, B, Bond, W, Bond-Lamberty, B, Brown, K, Burrascano, S, Byun, C, Campetella, G, Cavender-Bares, J, Chapin, FS, Choat, B, Coomes, DA, Cornwell, WK, Craine, J, Craven, D, Dainese, M, de Araujo, AC, de Vries, FT, Domingues, TF, Enquist, BJ, Fagundez, J, Fang, J, Fernandez-Mendez, F, Fernandez-Piedade, MT, Ford, H, Forey, E, Freschet, GT, Gachet, S, Gallagher, R, Green, W, Guerin, GR, Gutierrez, AG, Harrison, SP, Hattingh, WN, He, T, Hickler, T, Higgins, SI, Higuchi, P, Ilic, J, Jackson, RB, Jalili, A, Jansen, S, Koike, F, Konig, C, Kraft, N, Kramer, K, Kreft, H, Kuhn, I, Kurokawa, H, Lamb, EG, Laughlin, DC, Leishman, M, Lewis, S, Louault, F, Malhado, ACM, Manning, P, Meir, P, Mencuccini, M, Messier, J, Miller, R, Minden, V, Molofsky, J, Montgomery, R, Montserrat-Marti, G, Moretti, M., Muller, S, Niinemets, U, Ogaya, R, Ollerer, K, Onipchenko, V, Onoda, Y, Ozinga, WA, Pausas, JG, Peco, B, Penuelas, J, Pillar, VD, Pladevall, C, Romermann, C, Sack, L, Salinas, N, Sandel, B, Sardans, J, Schamp, B, Scherer-Lorenzen, M, Schulze, ED, Schweingruber, F, Shiodera, S, Sosinski, E, SOUDZILOVSKAIA, Nadia, Spasojevic, MJ, Swaine, E, Swenson, N, Tautenhahn, S, Thompson, K, Totte, A, Urrutia-Jalabert, R, Valladares, F, van Bodegom, P, Vasseur, F, Verheyen, K, Vile, D, Violle, C, von Holle, B, Weigelt, P, Weiher, E, Wiemann, MC, Williams, M, Wright, J, Zotz, G, and Systems Ecology

Subjects
Statistics and Probability, Data Descriptor, [SDV]Life Sciences [q-bio], Bos- en Landschapsecologie, Library and Information Sciences, Education, SIZE-REDUCTION, QUERCUS-ILEX, WIDE-RANGE, Life Science, Forest and Landscape Ecology, Macroecology, Vegetatie, Vegetation, ENVIRONMENT RELATIONSHIPS, 3103 Ecology, Biology and Life Sciences, Biodiversity, 3108 Plant Biology, Computer Science Applications, Biogeography, 631/158/852, FOLIAR NITROGEN ISOTOPES, 631/158/851, [SDE]Environmental Sciences, Vegetatie, Bos- en Landschapsecologie, Vegetation, Forest and Landscape Ecology, LEAF ECONOMICS SPECTRUM, Statistics, Probability and Uncertainty, data-descriptor, ELEVATED CO2, WOODY-PLANTS, PHOTOSYNTHETIC CAPACITY, 631/158/670, RELATIVE GROWTH-RATE, Information Systems, 31 Biological Sciences
Abstract

[Abstract] Here we provide the ‘Global Spectrum of Plant Form and Function Dataset’, containing species mean values for six vascular plant traits. Together, these traits –plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass – define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date. The study has been supported by the TRY initiative on plant traits (https://www.try-db.org). TRY is an initiative of the Max Planck Institute for Biogeochemistry, bioDISCOVERY/Future Earth (ICSU), the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig and Núcleo DiverSus (CONICET- Universidad Nacional de Córdoba, Argentina). The Global Spectrum of Plant Form and Function study has been supported by the European BACI project (Towards a Biosphere Atmosphere change Index, EU grant ID 640176), and grants to SD by FONCyT, CONICET, Universidad Nacional de Córdoba, the Inter-American Institute for Global Change Research, and The Newton Fund (NERC UK – CONICET ARG). VO thanks RSF (#19-14-00038p). Open Access funding enabled and organized by Projekt DEAL

Published
2022

10. The global spectrum of plant form and function: enhanced species-level trait dataset.

Author

Díaz S, Kattge J, Cornelissen JHC, Wright IJ, Lavorel S, Dray S, Reu B, Kleyer M, Wirth C, Prentice IC, Garnier E, Bönisch G, Westoby M, Poorter H, Reich PB, Moles AT, Dickie J, Zanne AE, Chave J, Wright SJ, Sheremetiev SN, Jactel H, Baraloto C, Cerabolini BEL, Pierce S, Shipley B, Casanoves F, Joswig JS, Günther A, Falczuk V, Rüger N, Mahecha MD, Gorné LD, Amiaud B, Atkin OK, Bahn M, Baldocchi D, Beckmann M, Blonder B, Bond W, Bond-Lamberty B, Brown K, Burrascano S, Byun C, Campetella G, Cavender-Bares J, Chapin FS 3rd, Choat B, Coomes DA, Cornwell WK, Craine J, Craven D, Dainese M, de Araujo AC, de Vries FT, Domingues TF, Enquist BJ, Fagúndez J, Fang J, Fernández-Méndez F, Fernandez-Piedade MT, Ford H, Forey E, Freschet GT, Gachet S, Gallagher R, Green W, Guerin GR, Gutiérrez AG, Harrison SP, Hattingh WN, He T, Hickler T, Higgins SI, Higuchi P, Ilic J, Jackson RB, Jalili A, Jansen S, Koike F, König C, Kraft N, Kramer K, Kreft H, Kühn I, Kurokawa H, Lamb EG, Laughlin DC, Leishman M, Lewis S, Louault F, Malhado ACM, Manning P, Meir P, Mencuccini M, Messier J, Miller R, Minden V, Molofsky J, Montgomery R, Montserrat-Martí G, Moretti M, Müller S, Niinemets Ü, Ogaya R, Öllerer K, Onipchenko V, Onoda Y, Ozinga WA, Pausas JG, Peco B, Penuelas J, Pillar VD, Pladevall C, Römermann C, Sack L, Salinas N, Sandel B, Sardans J, Schamp B, Scherer-Lorenzen M, Schulze ED, Schweingruber F, Shiodera S, Sosinski Ê, Soudzilovskaia N, Spasojevic MJ, Swaine E, Swenson N, Tautenhahn S, Thompson K, Totte A, Urrutia-Jalabert R, Valladares F, van Bodegom P, Vasseur F, Verheyen K, Vile D, Violle C, von Holle B, Weigelt P, Weiher E, Wiemann MC, Williams M, Wright J, and Zotz G

Abstract

Here we provide the 'Global Spectrum of Plant Form and Function Dataset', containing species mean values for six vascular plant traits. Together, these traits -plant height, stem specific density, leaf area, leaf mass per area, leaf nitrogen content per dry mass, and diaspore (seed or spore) mass - define the primary axes of variation in plant form and function. The dataset is based on ca. 1 million trait records received via the TRY database (representing ca. 2,500 original publications) and additional unpublished data. It provides 92,159 species mean values for the six traits, covering 46,047 species. The data are complemented by higher-level taxonomic classification and six categorical traits (woodiness, growth form, succulence, adaptation to terrestrial or aquatic habitats, nutrition type and leaf type). Data quality management is based on a probabilistic approach combined with comprehensive validation against expert knowledge and external information. Intense data acquisition and thorough quality control produced the largest and, to our knowledge, most accurate compilation of empirically observed vascular plant species mean traits to date., (© 2022. The Author(s).)

Published
2022
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11. Mapping local and global variability in plant trait distributions.

Author

Butler EE, Datta A, Flores-Moreno H, Chen M, Wythers KR, Fazayeli F, Banerjee A, Atkin OK, Kattge J, Amiaud B, Blonder B, Boenisch G, Bond-Lamberty B, Brown KA, Byun C, Campetella G, Cerabolini BEL, Cornelissen JHC, Craine JM, Craven D, de Vries FT, Díaz S, Domingues TF, Forey E, González-Melo A, Gross N, Han W, Hattingh WN, Hickler T, Jansen S, Kramer K, Kraft NJB, Kurokawa H, Laughlin DC, Meir P, Minden V, Niinemets Ü, Onoda Y, Peñuelas J, Read Q, Sack L, Schamp B, Soudzilovskaia NA, Spasojevic MJ, Sosinski E, Thornton PE, Valladares F, van Bodegom PM, Williams M, Wirth C, and Reich PB

Subjects
Environment, Geography, Models, Statistical, Plant Dispersal, Spatial Analysis, Ecosystem, Plants, Quantitative Trait, Heritable
Abstract

Our ability to understand and predict the response of ecosystems to a changing environment depends on quantifying vegetation functional diversity. However, representing this diversity at the global scale is challenging. Typically, in Earth system models, characterization of plant diversity has been limited to grouping related species into plant functional types (PFTs), with all trait variation in a PFT collapsed into a single mean value that is applied globally. Using the largest global plant trait database and state of the art Bayesian modeling, we created fine-grained global maps of plant trait distributions that can be applied to Earth system models. Focusing on a set of plant traits closely coupled to photosynthesis and foliar respiration-specific leaf area (SLA) and dry mass-based concentrations of leaf nitrogen ([Formula: see text]) and phosphorus ([Formula: see text]), we characterize how traits vary within and among over 50,000 [Formula: see text]-km cells across the entire vegetated land surface. We do this in several ways-without defining the PFT of each grid cell and using 4 or 14 PFTs; each model's predictions are evaluated against out-of-sample data. This endeavor advances prior trait mapping by generating global maps that preserve variability across scales by using modern Bayesian spatial statistical modeling in combination with a database over three times larger than that in previous analyses. Our maps reveal that the most diverse grid cells possess trait variability close to the range of global PFT means., Competing Interests: The authors declare no conflict of interest.

Published
2017
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12. Integrating Agricultural and Ecological Goals into the Management of Species-Rich Grasslands: Learning from the Flowering Meadows Competition in France.

Author

Magda D, de Sainte Marie C, Plantureux S, Agreil C, Amiaud B, Mestelan P, and Mihout S

Subjects
Animals, France, Livestock, Agriculture methods, Biodiversity, Conservation of Natural Resources methods, Grassland
Abstract

Current agri-environmental schemes for reconciling agricultural production with biodiversity conservation are proving ineffective Europe-wide, increasing interest in results-based schemes (RBSs). We describe here the French "Flowering Meadows" competition, rewarding the "best agroecological balance" in semi-natural grasslands managed by livestock farmers. This competition, which was entered by about a thousand farmers in 50 regional nature parks between 2007 and 2014, explicitly promotes a new style of agri-environmental scheme focusing on an ability to reach the desired outcome rather than adherence to prescriptive management rules. Building on our experience in the design and monitoring of the competition, we argue that the cornerstone of successful RBSs is a collective learning process in which the reconciliation of agriculture and environment is reconsidered in terms of synergistic relationships between agricultural and ecological functioning. We present the interactive, iterative process by which we defined an original method for assessing species-rich grasslands in agroecological terms. This approach was based on the integration of new criteria, such as flexibility, feeding value, and consistency of use, into the assessment of forage production performance and the consideration of biodiversity conservation through its functional role within the grassland ecosystem, rather than simply noting the presence or abundance of species. We describe the adaptation of this methodology on the basis of competition feedback, to bring about a significant shift in the conventional working methods of agronomists and conservationists (including researchers).The potential and efficacy of RBSs for promoting ecologically sound livestock systems are discussed in the concluding remarks, and they relate to the ecological intensification debate.

Published
2015
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13. Filling the gap in functional trait databases: use of ecological hypotheses to replace missing data.

Author

Taugourdeau S, Villerd J, Plantureux S, Huguenin-Elie O, and Amiaud B

Abstract

Functional trait databases are powerful tools in ecology, though most of them contain large amounts of missing values. The goal of this study was to test the effect of imputation methods on the evaluation of trait values at species level and on the subsequent calculation of functional diversity indices at community level using functional trait databases. Two simple imputation methods (average and median), two methods based on ecological hypotheses, and one multiple imputation method were tested using a large plant trait database, together with the influence of the percentage of missing data and differences between functional traits. At community level, the complete-case approach and three functional diversity indices calculated from grassland plant communities were included. At the species level, one of the methods based on ecological hypothesis was for all traits more accurate than imputation with average or median values, but the multiple imputation method was superior for most of the traits. The method based on functional proximity between species was the best method for traits with an unbalanced distribution, while the method based on the existence of relationships between traits was the best for traits with a balanced distribution. The ranking of the grassland communities for their functional diversity indices was not robust with the complete-case approach, even for low percentages of missing data. With the imputation methods based on ecological hypotheses, functional diversity indices could be computed with a maximum of 30% of missing data, without affecting the ranking between grassland communities. The multiple imputation method performed well, but not better than single imputation based on ecological hypothesis and adapted to the distribution of the trait values for the functional identity and range of the communities. Ecological studies using functional trait databases have to deal with missing data using imputation methods corresponding to their specific needs and making the most out of the information available in the databases. Within this framework, this study indicates the possibilities and limits of single imputation methods based on ecological hypothesis and concludes that they could be useful when studying the ranking of communities for their functional diversity indices.

Published
2014
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