ALBERT

Description: Understanding, modeling, and predicting the impact of global change on ecosystem functioning across biogeographical gradients can benefit from enhanced capacity to represent biota as a continuous distribution of traits. However, this is a challenge for the field of biogeography historically grounded on the species concept. Here we focus on the...

Description: [1]  We present the concept of the Carbon Cycle Data Assimilation System and describe its evolution over the last two decades from an assimilation system around a simple diagnostic model of the terrestrial biosphere to a system for the calibration and initialization of the land component of a comprehensive earth system model. We critically review the capability of this modeling framework to integrate multiple data streams, to assess their mutual consistency and with the model, to reduce uncertainties in the simulation of the terrestrial carbon cycle, to provide, in a traceable manner, reanalysis products with documented uncertainty, and to assist the design of the observational network. We highlight some of the challenges we met and experience we gained, give recommendations for operating the system and suggest directions for future development.

Description: Feedbacks between the terrestrial carbon cycle and the atmosphere have the potential to greatly modify expected rates of future climate change. This makes it all the more urgent to exploit all existing data for the purpose of accurate modelling of the underlying processes. Here we use a Bayesian random sampling method to constrain parameters of the Farquhar model of leaf photosynthesis and a model of leaf respiration against a comprehensive set of plant trait data at the leaf level. The resulting probability density function (PDF) of model parameters is contrasted with a PDF derived using a conventional “expert knowledge” approach. When running the Biosphere Energy Transfer Hydrology (BETHY) scheme with a 1000- member sub-sample of each of the two PDFs for present climate and a climate scenario, we find that the use of plant trait data is able to reduce the uncertainty range of simulated net leaf assimilation (NLA) by more than a factor of two. Most of the remaining variability is caused by only four parameters, associated with the acclimation of photosynthesis to plant growth temperature and to how leaf stomata react to atmospheric CO2 concentration. We suggest that this method should be used extensively to parameterize Earth system models, given that data bases on plant traits are increasingly being made available to the modelling community.

Description: Functional diversity is critical for ecosystem dynamics, stability and productivity. However, dynamic global vegetation models (DGVMs) which are increasingly used to simulate ecosystem functions under global change, condense functional diversity to Plant Functional Types (PFTs) with constant parameters. Here, we develop an individual- and trait-based version of the dynamic global vegetation model (DGVM) LPJmL (Lund-Potsdam-Jena managed Land) called LPJmL-FIT (LPJmL with Flexible Individual Traits) which we apply to generate plant trait maps for the Amazon basin. LPJmL-FIT incorporates empirical ranges of five traits of tropical trees extracted from the TRY global plant trait database, namely specific leaf area ( SLA ), leaf longevity ( LL ), leaf nitrogen content ( N area ), the maximum carboxylation rate of RUBISCO per leaf area ( Vcmax area ), and wood density ( WD ). To scale the individual growth performance of trees, the leaf traits are linked by trade-offs based on the leaf economics spectrum, whereas wood density is linked to tree mortality. No pre-selection of growth strategies is taking place, because individuals with unique trait combinations are uniformly distributed at tree establishment. We validate the modeled trait distributions by empirical trait data and the modeled biomass by a remote sensing product along a climatic gradient. Including trait variability and trade-offs successfully predicts natural trait distributions and achieves a more realistic representation of functional diversity at the local to regional scale. As sites of high climatic variability, the fringes of the Amazon promote trait divergence and the coexistence of multiple tree growth strategies, whilst lower plant trait diversity is found in the species-rich center of the region with relatively low climatic variability. LPJmL-FIT enables to test hypotheses on the effects of functional biodiversity on ecosystem functioning and to apply the DGVM to current challenges in ecosystem management from local to global scales, i.e. deforestation and climate change effects. This article is protected by copyright. All rights reserved.

Description: Earth system models demonstrate large uncertainty in projected changes in terrestrial carbon budgets. The lack of inclusion of adaptive responses of vegetation communities to the environment has been suggested to hamper the ability of modeled vegetation to adequately respond to environmental change. In this study, variation in functional responses of vegetation has been added to an Earth System Model (ESM) based on ecological principles. The restriction of viable mean trait values of vegetation communities by the environment, called ‘habitat filtering’, is an important ecological assembly rule and allows for determination of global scale trait-environment relationships. These relationships were applied to model trait variation for different plant functional types (PFTs). For three leaf traits (specific leaf area, maximum carboxylation rate at 25 °C, and maximum electron transport rate at 25 °C) relationships with multiple environmental drivers, like precipitation, temperature, radiation and CO 2 , were determined for the PFTs within the Max Planck Institute ESM. With these relationships, spatiotemporal variation in these formerly fixed traits in PFTs was modeled in global change projections (IPCC RCP8.5 scenario). Inclusion of this environment-driven trait variation resulted in a strong reduction of the global carbon sink by at least 33% (2.1 Pg C yr −1 ) from the 2 nd quarter of the 21 st century onward compared to the default model with fixed traits. In addition, the mid and high latitudes became a stronger carbon sink and the tropics a stronger carbon source, caused by trait-induced differences in productivity and relative respirational costs. These results point towards a reduction of the global carbon sink when including a more realistic representation of functional vegetation responses, implying more carbon will stay airborne, which could fuel further climate change. This article is protected by copyright. All rights reserved.

Description: Phenotypic traits and their associated trade-offs have been shown to have globally consistent effects on individual plant physiological functions, but how these effects scale up to influence competition, a key driver of community assembly in terrestrial vegetation, has remained unclear. Here we use growth data from more than 3 million trees in over 140,000 plots across the world to show how three key functional traits--wood density, specific leaf area and maximum height--consistently influence competitive interactions. Fast maximum growth of a species was correlated negatively with its wood density in all biomes, and positively with its specific leaf area in most biomes. Low wood density was also correlated with a low ability to tolerate competition and a low competitive effect on neighbours, while high specific leaf area was correlated with a low competitive effect. Thus, traits generate trade-offs between performance with competition versus performance without competition, a fundamental ingredient in the classical hypothesis that the coexistence of plant species is enabled via differentiation in their successional strategies. Competition within species was stronger than between species, but an increase in trait dissimilarity between species had little influence in weakening competition. No benefit of dissimilarity was detected for specific leaf area or wood density, and only a weak benefit for maximum height. Our trait-based approach to modelling competition makes generalization possible across the forest ecosystems of the world and their highly diverse species composition.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Kunstler, Georges -- Falster, Daniel -- Coomes, David A -- Hui, Francis -- Kooyman, Robert M -- Laughlin, Daniel C -- Poorter, Lourens -- Vanderwel, Mark -- Vieilledent, Ghislain -- Wright, S Joseph -- Aiba, Masahiro -- Baraloto, Christopher -- Caspersen, John -- Cornelissen, J Hans C -- Gourlet-Fleury, Sylvie -- Hanewinkel, Marc -- Herault, Bruno -- Kattge, Jens -- Kurokawa, Hiroko -- Onoda, Yusuke -- Penuelas, Josep -- Poorter, Hendrik -- Uriarte, Maria -- Richardson, Sarah -- Ruiz-Benito, Paloma -- Sun, I-Fang -- Stahl, Goran -- Swenson, Nathan G -- Thompson, Jill -- Westerlund, Bertil -- Wirth, Christian -- Zavala, Miguel A -- Zeng, Hongcheng -- Zimmerman, Jess K -- Zimmermann, Niklaus E -- Westoby, Mark -- England -- Nature. 2016 Jan 14;529(7585):204-7. doi: 10.1038/nature16476. Epub 2015 Dec 23.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Irstea, UR EMGR, 2 rue de la Papeterie BP-76, F-38402, St-Martin-d'Heres, France. ; Univ. Grenoble Alpes, F-38402 Grenoble, France. ; Department of Biological Sciences, Macquarie University, New South Wales 2109, Australia. ; Forest Ecology and Conservation Group, Department of Plant Sciences, University of Cambridge, Cambridge CB2 3EA, UK. ; Mathematical Sciences Institute, The Australian National University, Canberra 0200, Australia. ; National Herbarium of New South Wales, Royal Botanic Gardens and Domain Trust, Sydney 2000, New South Wales, Australia. ; Environmental Research Institute, School of Science, University of Waikato, Hamilton 3240, New Zealand. ; Forest Ecology and Forest Management Group, Wageningen University, 6708 PB Wageningen, The Netherlands. ; Department of Biology, University of Regina, 3737 Wascana Pkwy, Regina SK S4S 0A2, Canada. ; Cirad, UPR BSEF, F-34398 Montpellier, France. ; Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Republic of Panama. ; Graduate School of Life Sciences, Tohoku University, Sendai 980-8578, Japan. ; INRA, UMR Ecologie des Forets de Guyane, BP 709, 97387 Kourou Cedex, France. ; International Center for Tropical Botany, Department of Biological Sciences, Florida International University, Miami, Florida 33199, USA. ; Faculty of Forestry, University of Toronto, 33 Willcocks Street, Toronto, Ontario M5S 3B3, Canada. ; Swiss Federal Research Institute WSL, Landscape Dynamics Unit, CH-8903 Birmensdorf, Switzerland. ; Systems Ecology, Department of Ecological Science, Vrije Universiteit, Amsterdam 1081 HV, The Netherlands. ; Swiss Federal Research Institute WSL, Forest Resources and Management Unit, CH-8903 Birmensdorf, Switzerland. ; University of Freiburg, Chair of Forestry Economics and Planning, D-79106 Freiburg, Germany. ; Cirad, UMR Ecologie des Forets de Guyane, Campus Agronomique, BP 701, 97387 Kourou, France. ; Max Planck Institute for Biogeochemistry, Hans Knoll Str. 10, 07745 Jena, Germany. ; German Centre for Integrative Biodiversity Research (iDiv), Halle-Jena-Leipzig, Deutscher Platz 5e 04103 Leipzig, Germany. ; Graduate School of Agriculture, Kyoto University, Kyoto, 606-8502 Japan. ; CSIC, Global Ecology Unit CREAF-CSIC-UAB, Cerdanyola del Valles 08193, Catalonia, Spain. ; CREAF, Cerdanyola del Valles, 08193 Barcelona, Catalonia, Spain. ; Plant Sciences (IBG-2), Forschungszentrum Julich GmbH, D-52425 Julich, Germany. ; Department of Ecology, Evolution and Environmental Biology, Columbia University, New York, New York 10027, USA. ; Landcare Research, PO Box 40, Lincoln 7640, New Zealand. ; Biological and Environmental Sciences, School of Natural Sciences, University of Stirling, Stirling FK9 4LA, UK. ; Forest Ecology and Restoration Group, Department of Life Sciences, Science Building, University of Alcala, Campus Universitario, 28805 Alcala de Henares (Madrid), Spain. ; Department of Natural Resources and Environmental Studies, National Dong Hwa University, Hualien 97401, Taiwan. ; Department of Forest Resource Management, Swedish University of Agricultural Sciences (SLU), Skogsmarksgrand, 901 83 Umea, Sweden. ; Department of Biology, University of Maryland, College Park, Maryland 20742, USA. ; Centre for Ecology and Hydrology, Bush Estate, Penicuik, Midlothian EH26 0QB, UK. ; Department of Environmental Sciences, University of Puerto Rico, Rio Piedras Campus PO Box 70377 San Juan, Puerto Rico 00936-8377, USA. ; Institute for Systematic, Botany and Functional Biodiversity, University of Leipzig, Johannisallee 21 04103 Leipzig, Germany.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26700807" target="_blank"〉PubMed〈/a〉

Description: Earth is home to a remarkable diversity of plant forms and life histories, yet comparatively few essential trait combinations have proved evolutionarily viable in today's terrestrial biosphere. By analysing worldwide variation in six major traits critical to growth, survival and reproduction within the largest sample of vascular plant species ever compiled, we found that occupancy of six-dimensional trait space is strongly concentrated, indicating coordination and trade-offs. Three-quarters of trait variation is captured in a two-dimensional global spectrum of plant form and function. One major dimension within this plane reflects the size of whole plants and their parts; the other represents the leaf economics spectrum, which balances leaf construction costs against growth potential. The global plant trait spectrum provides a backdrop for elucidating constraints on evolution, for functionally qualifying species and ecosystems, and for improving models that predict future vegetation based on continuous variation in plant form and function.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Diaz, Sandra -- Kattge, Jens -- Cornelissen, Johannes H C -- Wright, Ian J -- Lavorel, Sandra -- Dray, Stephane -- Reu, Bjorn -- Kleyer, Michael -- Wirth, Christian -- Prentice, I Colin -- Garnier, Eric -- Bonisch, Gerhard -- Westoby, Mark -- Poorter, Hendrik -- Reich, Peter B -- Moles, Angela T -- Dickie, John -- Gillison, Andrew N -- Zanne, Amy E -- Chave, Jerome -- Wright, S Joseph -- Sheremet'ev, Serge N -- Jactel, Herve -- Baraloto, Christopher -- Cerabolini, Bruno -- Pierce, Simon -- Shipley, Bill -- Kirkup, Donald -- Casanoves, Fernando -- Joswig, Julia S -- Gunther, Angela -- Falczuk, Valeria -- Ruger, Nadja -- Mahecha, Miguel D -- Gorne, Lucas D -- England -- Nature. 2016 Jan 14;529(7585):167-71. doi: 10.1038/nature16489. Epub 2015 Dec 23.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉Instituto Multidisciplinario de Biologia Vegetal (IMBIV), CONICET and FCEFyN, Universidad Nacional de Cordoba, Casilla de Correo 495, 5000 Cordoba, Argentina. ; Max Planck Institute for Biogeochemistry, Hans-Knoll-Strasse 10, 07745 Jena, Germany. ; German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany. ; Systems Ecology, Department of Ecological Science, Vrije Universiteit, De Boelelaan 1085, 1081 HV Amsterdam, The Netherlands. ; Department of Biological Sciences, Macquarie University, Sydney, New South Wales 2109, Australia. ; Laboratoire d'Ecologie Alpine, UMR 5553, CNRS - Universite Grenoble Alpes, 38041 Grenoble Cedex 9, France. ; Laboratoire de Biometrie et Biologie Evolutive, UMR5558, Universite Lyon 1, CNRS, F-69622 Villeurbanne, France. ; Institute of Biology, University of Leipzig, Johannisallee 21, 04103 Leipzig, Germany. ; Escuela de Biologia, Universidad Industrial de Santander, Cra. 27 Calle 9, 680002 Bucaramanga, Colombia. ; Landscape Ecology Group, Institute of Biology and Environmental Sciences, University of Oldenburg, D-26111 Oldenburg, Germany. ; Department of Systematic Botany and Functional Biodiversity, University of Leipzig, Johannisallee 21, 04103 Leipzig, Germany. ; AXA Chair in Biosphere and Climate Impacts, Grand Challenges in Ecosystems and the Environment and Grantham Institute - Climate Change and the Environment, Department of Life Sciences, Imperial College London, Silwood Park Campus, Buckhurst Road, Ascot SL5 7PY, UK. ; Centre d'Ecologie Fonctionnelle et Evolutive (UMR 5175), CNRS-Universite de Montpellier - Universite Paul-Valery Montpellier - EPHE, 34293 Montpellier Cedex 5, France. ; Plant Sciences (IBG-2), Forschungszentrum Julich GmbH, D-52425 Julich, Germany. ; Department of Forest Resources, University of Minnesota, St Paul, Minnesota 55108, USA. ; Hawkesbury Institute for the Environment, University of Western Sydney, Penrith New South Wales 2751, Australia. ; Evolution &Ecology Research Centre, School of Biological, Earth and Environmental Sciences, UNSW Australia, Sydney, New South Wales 2052, Australia. ; Collections , The Royal Botanic Gardens Kew, Wakehurst Place, Ardingly, West Sussex, RH17 6TN, UK. ; Center for Biodiversity Management, P.O. Box 120, Yungaburra, Queensland 4884, Australia. ; Department of Biological Sciences, George Washington University, Washington DC 20052, USA. ; Center for Conservation and Sustainable Development, Missouri Botanical Garden, St Louis, Missouri 63121, USA. ; UMR 5174 Laboratoire Evolution et Diversite Biologique, CNRS &Universite Paul Sabatier, Toulouse 31062, France. ; Smithsonian Tropical Research Institute, Apartado 0843-03092, Balboa, Ancon, Panama. ; Komarov Botanical Institute, Prof. Popov Street 2, St Petersburg 197376, Russia. ; INRA, UMR1202 BIOGECO, F-33610 Cestas, France. ; Universite de Bordeaux, BIOGECO, UMR 1202, F-33600 Pessac, France. ; International Center for Tropical Botany, Department of Biological Sciences, Florida International University, Miami, Florida 33199, USA. ; INRA, UMR Ecologie des Forets de Guyane, 97310 Kourou, French Guiana. ; Department of Theoretical and Applied Sciences, University of Insubria, Via J.H. Dunant 3, I-21100 Varese, Italy. ; Department of Agricultural and Environmental Sciences (DiSAA), University of Milan, Via G. Celoria 2, I-20133 Milan, Italy. ; Departement de biologie, Universite de Sherbrooke, Sherbrooke, Quebec J1K 2R1, Canada. ; Biodiversity Informatics and Spatial Analysis, Jodrell Building, The Royal Botanic Gardens Kew, Richmond TW9 3AB, UK. ; Unidad de Bioestadistica, Centro Agronomico Tropical de Investigacion y Ensenanza (CATIE), 7170 Turrialba, 30501, Costa Rica.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/26700811" target="_blank"〉PubMed〈/a〉

Description: Human activities, especially conversion and degradation of habitats, are causing global biodiversity declines. How local ecological assemblages are responding is less clear--a concern given their importance for many ecosystem functions and services. We analysed a terrestrial assemblage database of unprecedented geographic and taxonomic coverage to quantify local biodiversity responses to land use and related changes. Here we show that in the worst-affected habitats, these pressures reduce within-sample species richness by an average of 76.5%, total abundance by 39.5% and rarefaction-based richness by 40.3%. We estimate that, globally, these pressures have already slightly reduced average within-sample richness (by 13.6%), total abundance (10.7%) and rarefaction-based richness (8.1%), with changes showing marked spatial variation. Rapid further losses are predicted under a business-as-usual land-use scenario; within-sample richness is projected to fall by a further 3.4% globally by 2100, with losses concentrated in biodiverse but economically poor countries. Strong mitigation can deliver much more positive biodiversity changes (up to a 1.9% average increase) that are less strongly related to countries' socioeconomic status.〈br /〉〈span class="detail_caption"〉Notes: 〈/span〉Newbold, Tim -- Hudson, Lawrence N -- Hill, Samantha L L -- Contu, Sara -- Lysenko, Igor -- Senior, Rebecca A -- Borger, Luca -- Bennett, Dominic J -- Choimes, Argyrios -- Collen, Ben -- Day, Julie -- De Palma, Adriana -- Diaz, Sandra -- Echeverria-Londono, Susy -- Edgar, Melanie J -- Feldman, Anat -- Garon, Morgan -- Harrison, Michelle L K -- Alhusseini, Tamera -- Ingram, Daniel J -- Itescu, Yuval -- Kattge, Jens -- Kemp, Victoria -- Kirkpatrick, Lucinda -- Kleyer, Michael -- Correia, David Laginha Pinto -- Martin, Callum D -- Meiri, Shai -- Novosolov, Maria -- Pan, Yuan -- Phillips, Helen R P -- Purves, Drew W -- Robinson, Alexandra -- Simpson, Jake -- Tuck, Sean L -- Weiher, Evan -- White, Hannah J -- Ewers, Robert M -- Mace, Georgina M -- Scharlemann, Jorn P W -- Purvis, Andy -- BB/F017324/1/Biotechnology and Biological Sciences Research Council/United Kingdom -- England -- Nature. 2015 Apr 2;520(7545):45-50. doi: 10.1038/nature14324.〈br /〉〈span class="detail_caption"〉Author address: 〈/span〉1] United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge CB3 0DL, UK. [2] Computational Science Laboratory, Microsoft Research Cambridge, 21 Station Road, Cambridge CB1 2FB, UK. ; Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD, UK. ; 1] United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge CB3 0DL, UK. [2] Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD, UK. ; Department of Life Sciences, Imperial College London, Silwood Park, London SL5 7PY, UK. ; United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge CB3 0DL, UK. ; Department of Biosciences, College of Science, Swansea University, Singleton Park, Swansea SA2 8PP, UK. ; 1] Department of Life Sciences, Natural History Museum, Cromwell Road, London SW7 5BD, UK. [2] Department of Life Sciences, Imperial College London, Silwood Park, London SL5 7PY, UK. ; Department of Genetics, Evolution and Environment, Centre for Biodiversity and Environment Research, University College London, Gower Street, London WC1E 6BT, UK. ; Instituto Multidisciplinario de Biologia Vegetal (CONICET-UNC) and FCEFyN, Universidad Nacional de Cordoba, Casilla de Correo 495, 5000 Cordoba, Argentina. ; Deptartment of Zoology, Faculty of Life Sciences, Tel-Aviv University, 6997801 Tel Aviv, Israel. ; 1] Max Planck Institute for Biogeochemistry, Hans Knoll Strasse 10, 07743 Jena, Germany. [2] German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig, Deutscher Platz 5e, 04103 Leipzig, Germany. ; Landscape Ecology Group, Institute of Biology and Environmental Sciences, University of Oldenburg, D-26111 Oldenburg, Germany. ; Computational Science Laboratory, Microsoft Research Cambridge, 21 Station Road, Cambridge CB1 2FB, UK. ; Department of Plant Sciences, University of Oxford, Oxford OX1 3RB, UK. ; Biology Department, University of Wisconsin-Eau Claire, Eau Claire, Wisconsin 54701, USA. ; 1] United Nations Environment Programme World Conservation Monitoring Centre, 219 Huntingdon Road, Cambridge CB3 0DL, UK. [2] School of Life Sciences, University of Sussex, Brighton BN1 9QG, UK.〈br /〉〈span class="detail_caption"〉Record origin:〈/span〉 〈a href="http://www.ncbi.nlm.nih.gov/pubmed/25832402" target="_blank"〉PubMed〈/a〉

Description: This dataset provides growth form classifications for 67,413 vascular plant species from North, Central, and South America. The data used to determine growth form were compiled from five major integrated sources and two original publications: the Botanical Information and Ecology Network (BIEN), the Plant Trait Database (TRY), the SALVIAS database, the USDA PLANTS database, Missouri Botanical Garden's Tropicos database, Wright (2010), and Boyle (1996). We defined nine plant growth forms based on woodiness (woody or non-woody), shoot structure (self-supporting or not self-supporting), and root traits (rooted in soil, not rooted in soil, parasitic or aquatic): Epiphyte, Liana, Vine, Herb, Shrub, Tree, Parasite, or Aquatic. Species with multiple growth form classifications were assigned the growth form classification agreed upon by the majority (〉 2/3) of sources. Species with ambiguous or otherwise not interpretable growth form assignments were excluded from the final dataset but are made available with the original data. Comparisons with independent estimates of species richness for the Western hemisphere suggest that our final dataset includes the majority of New World vascular plant species. Coverage is likely more complete for temperate than for tropical species. In addition, aquatic species are likely under-represented. Nonetheless, this dataset represents the largest compilation of plant growth forms published to date, and should contribute to new insights across a broad range of research in systematics, ecology, biogeography, conservation, and global change science. This article is protected by copyright. All rights reserved.

Description: Plant traits \xe2\x80\x93 the morphological, anatomical, physiological, biochemical and phenological characteristics of plants and their organs \xe2\x80\x93 determine how primary producers respond to environmental factors, affect other trophic levels, influence ecosystem processes and services and provide a link from species richness to ecosystem functional diversity. Trait data thus represent the raw material for a wide range of research from evolutionary biology, community and functional ecology to biogeography. Here we present the global database initiative named TRY, which has united a wide range of the plant trait research community worldwide and gained an unprecedented buy-in of trait data: so far 93 trait databases have been contributed. The data repository currently contains almost three million trait entries for 69 000 out of the world\xe2\x80\x99s 300 000 plant species, with a focus on 52 groups of traits characterizing the vegetative and regeneration stages of the plant life cycle, including growth, dispersal, establishment and pepersistence. A first data analysis shows that most plant traits are approximately log-normally distributed, with widely differing ranges of variation across traits. Most trait variation is between species (interspecific), but significant intraspecific variation is also documented, up to 40% of the overall variation. Plant functional types (PFTs), as commonly used in vegetation models, capture a substantial fraction of the observed variation \xe2\x80\x93 but for several traits most variation occurs within PFTs, up to 75% of the overall variation. In the context of vegetation models these traits would better be represented by state variables rather than fixed parameter values. The improved availability of plant trait data in the unified global database is expected to support a paradigm shift from species to trait-based ecology, offer new opportunities for synthetic plant trait research and enable a more realistic and empirically grounded representation of terrestrial vegetation in Earth system models.