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Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land–climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles. ; TRY initiative on plant traits German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. European Union's Horizon 2020 project BACI 640176 University of Zurich University Research Priority Program on Global Change and Biodiversity National Science Foundation (NSF) 20-508 NOMIS grant of Remotely Sensing Ecological Genomics Max Planck Society via its fellowship programme German Research Foundation (DFG) RU 1536/3-1 project Resilient Forests of the Dutch Ministry of Economic Affairs KB-29-009-003 EU-FP7-KBBE project: BACCARA-Biodiversity and climate change, a risk analysis 226299 Australian Research Council DP170103410 European Research Council (ERC) ERC-SyG-2013-610028 IMBALANCE-P VIDI by the Netherlands Organization of Scientific Research 016.161.318 II. Oldenburgischer Deichband Wasserverbandstag e.V. NWS 10/05 Conselho Nacional de Desenvolvimento Cientifico e Tecnologico (CNPQ) 369617/2017-2 307689/2014-0 National Research Foundation of Korea (NRF) - Korea government (MSIT) 2018R1C1B6005351 Comision Nacional de Investigacion Cientifica y Tecnologica (CONICYT) CONICYT FONDECYT 11150835 1200468 Russian Science Foundation (RSF) 19-14-00038 Future Earth ; Versión publicada - versión final del editor

The authors investigate the broad-scale climatological and soil properties that co-vary with major axes of plant functional traits. They find that variation in plant size is attributed to latitudinal gradients in water or energy limitation, while variation in leaf economics traits is attributed to both climate and soil fertility including their interaction. Plant functional traits can predict community assembly and ecosystem functioning and are thus widely used in global models of vegetation dynamics and land-climate feedbacks. Still, we lack a global understanding of how land and climate affect plant traits. A previous global analysis of six traits observed two main axes of variation: (1) size variation at the organ and plant level and (2) leaf economics balancing leaf persistence against plant growth potential. The orthogonality of these two axes suggests they are differently influenced by environmental drivers. We find that these axes persist in a global dataset of 17 traits across more than 20,000 species. We find a dominant joint effect of climate and soil on trait variation. Additional independent climate effects are also observed across most traits, whereas independent soil effects are almost exclusively observed for economics traits. Variation in size traits correlates well with a latitudinal gradient related to water or energy limitation. In contrast, variation in economics traits is better explained by interactions of climate with soil fertility. These findings have the potential to improve our understanding of biodiversity patterns and our predictions of climate change impacts on biogeochemical cycles. ; The study was supported by the TRY initiative on plant traits (http://www.try-db. org). The TRY database is hosted at the Max Planck Institute for Biogeochemistry (MPI BGC, Germany) and supported by Future Earth and the German Centre for Integrative Biodiversity Research (iDiv) Halle-Jena-Leipzig. We would like to thank all PIs contributing to the TRY database, whose efforts allowed this analysis. In detail, we thank: J.H.C. Cornelissen, R. Milla, W. Cornwell, K. Kramer, S. Gachet, Ingolf Kühn, P. Poschlod, M. Scherer, J. Pausas, B. Sandal, K. Verheyen, J. Penuelas, N. Soudzilovskaia, P. Reich, J. Fang, S. Harrison, R. Gallagher, B. Hawkins, B. Finegan, J. Powers, F. Lenti, S. Higgins, B. Medlyn, H. Ford, V. Pillar, M. Bahn, E. Sosinski, T. He, B. Cerabolini, J. Cavender-Bares, I. J. Wright, F. Louault, B. Amiaud, G. Gonzalez-Melo, P. Adler, F. Schurr, J. Craine, Y. Niinemets, A. Zanne, H. Jactel, M. Harze, R. Montgomery, C. Römermann, T. Hickler, A. Pahl, M. Dainese, D. Kirkup, J. Dickie, W. Hattingh, P. Higuchi, T. Domingues, A. Araujo, M. Williams, C. Price, B. Shipley, L. Sack, B. Schamp, W. Han, Y. Onoda, K. Fleischer, J.P. Wright, G. Guerin, F. de Vries, D.D. Baldocchi, J. Kattge, B. Blonder, K. Brown, D. Campetella, G. Frechet, Q. Read, N. G. Swenson, V. Lanta, E. Weiher, M. Leishman, A. Siefert, M. Spasojevic, R. Jackson, J. Messier, S. J. Wright, D. Craven, J. Molofsky, P. Meir, E. Forey, A. Totte, C. Frenette Dussault, O. Atkin, F. Koike, D. Laughlin, S. Burrascano, K. Ollerer, N. Gross, A. Madhur, P. Begonna, B. Bond-Lamberty, B. von Holle, W. Green, B. Yguel, A. C. Malhado, P. Manning, G. Zotz, E. Lamb, J. Fagundez, Z. Wang, S. Diaz, C. Byun, W. Bond, B. Enquist, C. Baraloto, P. Manning, M. Kleyer, W. Ozinga, J. Ordonez, J. Lloyd, H. Poorter, E. Garnier, F. Valladares, C. Pladevall, G. Freschet, M. Moretti, H. Kurokawa, V. Minden, A. Demey, F. Férnandez-Méndez, J. Butterfield, T. Domingu, E. Swaine, L. Poorter, S. Shiodera, T. Chapin, M. Beckmann, J.A. Gutierrez, M. Mencuccini, S. Jansen, and N. J. B. Kraft. We appreciate the discussions at the MPI BGC. We thank F. Fazayeli for preparing the gap-filled trait data. We thank F. Gans and U. Weber for preparing ancillary data and B. Ahrens for pointing out some soil data availability. We acknowledge Environmental Systems Research Institute (ESRI) and its licensor(s) for the Geodata product of the Missions Database 'ArcWorld Supplement' (GMI), published by Global Mapping International and originated from Global Mapping International for producing Extended Data Fig. 1 and Supplementary Fig. 7 and available in ArcGIS software by ESRI. ArcGIS and ArcMap are the intellectual property of ESRI and are used herein under license. For more information about ESRI software, please visit www.esri.com. The authors affiliated with the MPI BGC acknowledge funding by the European Union's Horizon 2020 project BACI under grant agreement no. 640176. We are thankful to the data providers for the SoilGrids, hosted by ISRIC. J.S.J. acknowledges the International Max Planck Research School for global biogeochemical cycles. J.S.J., M.E.S. and M.C.S. acknowledge support from the University of Zurich University Research Priority Program on Global Change and Biodiversity. P.B.R., M.E.S. and M.C.S. acknowledge membership in the US NSF 20-508 BII-Implementation project, 'The causes and consequences of plant biodiversity across scales in a rapidly changing world'. M.E.S. acknowledges the NOMIS grant of Remotely Sensing Ecological Genomics that funds J.S.J. and M.C.S. C.W. acknowledges the support of the Max Planck Society via its fellowship programme. N.R. was funded by a research grant from Deutsche Forschungsgemeinschaft DFG (RU 1536/3-1). K.K. was supported by the project Resilient Forests (KB-29-009-003) of the Dutch Ministry of Economic Affairs. The trait data supplied were co-funded by the EU-FP7-KBBE project: BACCARA—Biodiversity and climate change, a risk analysis (project ID 226299). I.W. acknowledges support from the Australian Research Council (DP170103410). J.P. acknowledges financial support from the European Research Council Synergy grant ERC-SyG-2013-610028 IMBALANCE-P. N.A.S. is financed by a VIDI grant (016.161.318) issued by the Netherlands Organization of Scientific Research. The data V.M. provided were funded by II. Oldenburgischer Deichband and the Wasserverbandstag e.V. (NWS 10/05). We thank M. Kleyer for his critical input. P.H. and V.D.P. have been supported by CNPq (grant nos 369617/2017-2 and 307689/2014-0, respectively). C.B. was supported by the National Research Foundation of Korea (NRF) grant funded by the Korea government (MSIT) (2018R1C1B6005351). A.G.G. was funded by FONDECYT grant nos 11150835 and 1200468. V.O. thanks Russian science foundation (RSF, 19-14-00038) for financial support.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles-open data, open source and open methods-is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

Synthesizing trait observations and knowledge across the Tree of Life remains a grand challenge for biodiversity science. Species traits are widely used in ecological and evolutionary science, and new data and methods have proliferated rapidly. Yet accessing and integrating disparate data sources remains a considerable challenge, slowing progress toward a global synthesis to integrate trait data across organisms. Trait science needs a vision for achieving global integration across all organisms. Here, we outline how the adoption of key Open Science principles—open data, open source and open methods—is transforming trait science, increasing transparency, democratizing access and accelerating global synthesis. To enhance widespread adoption of these principles, we introduce the Open Traits Network (OTN), a global, decentralized community welcoming all researchers and institutions pursuing the collaborative goal of standardizing and integrating trait data across organisms. We demonstrate how adherence to Open Science principles is key to the OTN community and outline five activities that can accelerate the synthesis of trait data across the Tree of Life, thereby facilitating rapid advances to address scientific inquiries and environmental issues. Lessons learned along the path to a global synthesis of trait data will provide a framework for addressing similarly complex data science and informatics challenges.

We introduce the AusTraits database - a compilation of values of plant traits for taxa in the Australian flora (hereafter AusTraits). AusTraits synthesises data on 448 traits across 28,640 taxa from field campaigns, published literature, taxonomic monographs, and individual taxon descriptions. Traits vary in scope from physiological measures of performance (e.g. photosynthetic gas exchange, water-use efficiency) to morphological attributes (e.g. leaf area, seed mass, plant height) which link to aspects of ecological variation. AusTraits contains curated and harmonised individual- and species-level measurements coupled to, where available, contextual information on site properties and experimental conditions. This article provides information on version 3.0.2 of AusTraits which contains data for 997,808 trait-by-taxon combinations. We envision AusTraits as an ongoing collaborative initiative for easily archiving and sharing trait data, which also provides a template for other national or regional initiatives globally to fill persistent gaps in trait knowledge. ; Funding Agencies|Australian Research CouncilAustralian Research Council [FT160100113, DE170100208, FT100100910]; National Collaborative Research Infrastructure Strategy (NCRIS)Australian GovernmentDepartment of Industry, Innovation and Science