Climatic and soil factors explain the two-dimensional spectrum of global plant trait variation

Julia S. Joswig, Christian Wirth, Meredith C. Schuman, Jens Kattge, Björn Reu, Ian J. Wright, Sebastian D. Sippel, Nadja Rüger, Ronny Richter, Michael E. Schaepman, Peter M. van Bodegom, J. H.C. Cornelissen, Sandra Díaz, Wesley N. Hattingh, Koen Kramer, Frederic Lens, Ülo Niinemets, Peter B. Reich, Markus Reichstein, Christine RömermannFranziska Schrodt, Madhur Anand, Michael Bahn, Chaeho Byun, Giandiego Campetella, Bruno E.L. Cerabolini, Joseph M. Craine, Andres Gonzalez-Melo, Alvaro G. Gutiérrez, Tianhua He, Pedro Higuchi, Hervé Jactel, Nathan J.B. Kraft, Vanessa Minden, Vladimir Onipchenko, Josep Peñuelas, Valério D. Pillar, Ênio Sosinski, Nadejda A. Soudzilovskaia, Evan Weiher, Miguel D. Mahecha

Research output: Contribution to journalArticlepeer-review

103 Scopus citations

Abstract

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.

Original languageEnglish (US)
Pages (from-to)36-50
Number of pages15
JournalNature Ecology and Evolution
Volume6
Issue number1
DOIs
StatePublished - Jan 2022

Bibliographical note

Funding Information:
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.

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© 2021, The Author(s).

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  • Journal Article
  • Research Support, Non-U.S. Gov't

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