TY  - JOUR
A1  - Maynard, Daniel S.
A1  - Bialic-Murphy, Lalasia
A1  - Zohner, Constantin
A1  - Averill, Colin
A1  - Hoogen, Johan van den
A1  - Ma, Haozhi
A1  - Mo, Lidong
A1  - Smith, Gabriel Reuben
A1  - Acosta, Alicia T. R.
A1  - Aubin, Isabelle
A1  - Berenguer, Erika
A1  - Boonman, Coline C. F.
A1  - Catford, Jane A.
A1  - Cerabolini, Bruno E. L.
A1  - Dias, Arildo S.
A1  - González-Melo, Andrés
A1  - Hietz, Peter
A1  - Lusk, Christopher H.
A1  - Mori, Akira S.
A1  - Niinemets, Ülo
A1  - Pillar, Valério D.
A1  - Pinho, Bruno X.
A1  - Rosell, Julieta A.
A1  - Schurr, Frank
A1  - Sheremetev, Serge N.
A1  - Silva, Ana Carolina Feldenheimer da
A1  - Sosinski, Ênio
A1  - Bodegom, Peter M. van
A1  - Weiher, Evan
A1  - Bönisch, Gerhard
A1  - Kattge, Jens
A1  - Crowther, Thomas Ward
T1  - Global relationships in tree functional traits
T2  - Nature Communications
N2  - 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.
KW  - Biogeography
KW  - Ecology
KW  - Ecophysiology
Y1  - 2022
UR  - http://publikationen.ub.uni-frankfurt.de/frontdoor/index/index/docId/63271
UR  - https://nbn-resolving.org/urn:nbn:de:hebis:30:3-632719
SN  - 2041-1723
N1  - The imputed trait data used in this study have been deposited in a dedicated GitHub repository with https://doi.org/10.5281/zenodo.6564051 (https://github.com/dsmaynard/tree_traits), along with the cleaned phylogenetic eigenvectors from the seed plant phylogeny of Smith & Brown (2018) and corresponding tree species names matched using BGCI GlobalTreeSearch database v1.3. The raw TRY trait data are not available due to data privacy and sharing restrictions, but can be obtained by making a data request to the TRY Plant Trait Database (https://www.try-db.org/TryWeb/).
N1  - The code for replicating the central findings of this paper is available at https://github.com/dsmaynard/tree_traits (https://doi.org/10.5281/zenodo.6564051).
VL  - 13
IS  - art. 3185
SP  - 1
EP  - 12
PB  - Nature Publishing Group UK
CY  - [London]
ER  -