Leaf-level coordination principles propagate to the ecosystem scale

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Gomarasca, Ulisse | Migliavacca, Mirco | Kattge, Jens | Nelson, Jacob A. | Niinemets, Ülo | Wirth, Christian | Cescatti, Alessandro | Bahn, Michael | Nair, Richard | Acosta, Alicia T. R. | Arain, M. Altaf | Beloiu, Mirela | Black, T. Andrew | Bruun, Hans Henrik | Bucher, Solveig Franziska | Buchmann, Nina | Byun, Chaeho | Carrara, Arnaud | Conte, Adriano | da Silva, Ana C. | Duveiller, Gregory | Fares, Silvano | Ibrom, Andreas | Knohl, Alexander | Komac, Benjamin | Limousin, Jean-Marc | Lusk, Christopher H. | Mahecha, Miguel D. | Martini, David | Minden, Vanessa | Montagnani, Leonardo | Mori, Akira S. | Onoda, Yusuke | Peñuelas, Josep | Perez-Priego, Oscar | Poschlod, Peter | Powell, Thomas L. | Reich, Peter B. | Šigut, Ladislav | van Bodegom, Peter M. | Walther, Sophia | Wohlfahrt, Georg | Wright, Ian J. | Reichstein, Markus

Edité par CCSD ; Nature Publishing Group -

International audience. Fundamental axes of variation in plant traits result from trade-offs between costs and benefits of resource-use strategies at the leaf scale. However, it is unclear whether similar trade-offs propagate to the ecosystem level. Here, we test whether trait correlation patterns predicted by three well-known leaf- and plant-level coordination theories – the leaf economics spectrum, the global spectrum of plant form and function, and the least-cost hypothesis – are also observed between community mean traits and ecosystem processes. We combined ecosystem functional properties from FLUXNET sites, vegetation properties, and community mean plant traits into three corresponding principal component analyses. We find that the leaf economics spectrum (90 sites), the global spectrum of plant form and function (89 sites), and the least-cost hypothesis (82 sites) all propagate at the ecosystem level. However, we also find evidence of additional scale-emergent properties. Evaluating the coordination of ecosystem functional properties may aid the development of more realistic global dynamic vegetation models with critical empirical data, reducing the uncertainty of climate change projections.

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