10.5061/DRYAD.SV2J191
Kong, Deliang
Shenyang Agricultural University
Wang, Junjian
Southern University of Science and Technology
Wu, Huifang
Henan University
Valverde-Barrantes, Oscar J.
Florida International University
Wang, Ruili
North West Agriculture and Forestry University
Zeng, Hui
Peking University
Kardol, Paul
Swedish University of Agricultural Sciences
Zhang, Haiyan
Shenyang Agricultural University
Feng, Yulong
Shenyang Agricultural University
Data from: Nonlinearity of root trait relationships and the root economics
spectrum
Dryad
dataset
2019
Plant roots
Plant roots
2019-05-17T16:49:14Z
2019-05-17T16:49:14Z
en
https://doi.org/10.1038/s41467-019-10245-6
13400 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
The root economics spectrum (RES), a common hypothesis postulating a
tradeoff between resource acquisition and conservation traits, is being
challenged by conflicting relationships between root diameter, tissue
density (RTD) and root nitrogen concentration (RN). Here, we analyze a
global trait dataset of absorptive roots for over 800 plant species. For
woody species (but not for non-woody species), we find nonlinear
relationships between root diameter and RTD and RN, which stem from the
allometric relationship between stele and cortical tissues. These
nonlinear relationships explain how sampling bias from different ends of
the nonlinear curves can result in conflicting trait relationships.
Further, the shape of the relationships varies depending on evolutionary
context and mycorrhizal affiliation. Importantly, the observed nonlinear
trait relationships do not support the RES predictions. Allometry-based
nonlinearity of root trait relationships improves our understanding of the
ecology, physiology and evolution of absorptive roots.
Average mass for the first order rootsThis dataset includes average dry
mass for the first order roots of 96 woody species. These species are the
same as those in our previous published paper, i.e., Kong et al. (2014)
Leading dimensions in absorptive root trait variation across 96
subtropical forest species. New Phytologist 203: 863-872.Source Data.xlsx
global
Global