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      Global relationships in tree functional traits.

      Maynard, D.S.; Bialic-Murphy, L.; Zohner, C.M.; Averill, C.; van den Hoogen, J.; Ma, H.; Mo, L.; Smith, G.R.; Acosta, A.T.R.; Aubin, I.; Berenguer, E.; Boonman, C.C.F.; Catford, J.A.; Cerabolini, B.E.L.; Dias, A.S.; González-Melo, A.; Hietz, P.; Lusk, Christopher H.; Mori, A.S.; Niinemets, Ü.; Pillar, V.D.; Pinho, B.X.; Rosell, J.A.; Schurr, F.M.; Sheremetev, S.N.; da Silva, A.C.; Sosinski, Ê.; van Bodegom, P.M.; Weiher, E.; Bönisch, G.; Kattge, J.; Crowther, T.W.
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      Maynard_2022_NatComms.pdf
      Published version, 5.992Mb
      DOI
       10.1038/s41467-022-30888-2
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      Permanent link to Research Commons version
      https://hdl.handle.net/10289/14939
      Abstract
      Due to massive energetic investments in woody support structures, trees are subject to unique physiological, mechanical, and ecological pressures not experienced by herbaceous plants. Despite a wealth of studies exploring trait relationships across the entire plant kingdom, the dominant traits underpinning these unique aspects of tree form and function remain unclear. Here, by considering 18 functional traits, encompassing leaf, seed, bark, wood, crown, and root characteristics, we quantify the multidimensional relationships in tree trait expression. We find that nearly half of trait variation is captured by two axes: one reflecting leaf economics, the other reflecting tree size and competition for light. Yet these orthogonal axes reveal strong environmental convergence, exhibiting correlated responses to temperature, moisture, and elevation. By subsequently exploring multidimensional trait relationships, we show that the full dimensionality of trait space is captured by eight distinct clusters, each reflecting a unique aspect of tree form and function. Collectively, this work identifies a core set of traits needed to quantify global patterns in functional biodiversity, and it contributes to our fundamental understanding of the functioning of forests worldwide.
      Date
      2022-06-08
      Type
      Journal Article
      Rights
      This article is licensed under a Creative Commons Attribution 4.0 International License, which permits use, sharing, adaptation, distribution and reproduction in any medium or format, as long as you give appropriate credit to the original author(s) and the source, provide a link to the Creative Commons license, and indicate if changes were made. The images or other third party material in this article are included in the article’s Creative Commons license, unless indicated otherwise in a credit line to the material. If material is not included in the article’s Creative Commons license and your intended use is not permitted by statutory regulation or exceeds the permitted use, you will need to obtain permission directly from the copyright holder. To view a copy of this license, visit http://creativecommons.org/licenses/by/4.0/.

      © The Author(s) 2022
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