Leaf carbon and nitrogen stoichiometric variation along
environmental gradients
environmental gradients
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Published version
Author(s)
Xu, Huiying
Wang, Han
Prentice, Iain Colin
Harrison, Sandy P
Type
Journal Article
Abstract
Leaf stoichiometric traits are central to ecosystem function and biogeochemical cycling, yet no accepted theory predicts their variation along environmental gradients. Using data in the China Plant Trait Database version 2, we aimed to characterize variation in leaf carbon and nitrogen per unit mass (Cmass, Nmass) and their ratio, and to test an eco-evolutionary optimality model for Nmass. Community-mean trait values were related to climate variables by multiple linear regression. Climatic optima and tolerances of major genera were estimated; Pagel’s λ was used to quantify phylogenetic controls, and Bayesian phylogenetic linear mixed models to assess the contributions of climate, species identity and phylogeny. Optimality-based predictions of community-mean Nmass were compared to observed values. All traits showed strong phylogenetic signals. Climate explained only 18 % of C : N ratio variation among species but 45 % among communities, highlighting the role of taxonomic replacement in mediating community-level responses. Geographic distributions of deciduous taxa separated primarily by moisture, evergreens by temperature. Cmass increased with irradiance, but decreased with moisture and temperature. Nmass declined with all three variables. C : N ratio variations were dominated by Nmass. The coefficients relating Nmass to the ratio of maximum carboxylation capacity at 25 °C (Vcmax25) and leaf mass per area (Ma) were influenced by leaf area index. The optimality model captured 68 % and 53 % of variation between communities for Vcmax25 and Ma respectively, and 30 % for Nmass. We conclude that stoichiometric variations along climate gradients are achieved largely by environmental selection among species and clades with different characteristic trait values. Variations in leaf C : N ratio are mainly determined by Nmass, and optimality-based modelling shows useful predictive ability for community-mean Nmass. These findings should help to improve the representation of C : N coupling in ecosystem models.
Date Issued
2023-11-17
Date Acceptance
2023-10-06
Citation
Biogeosciences, 2023, 20 (22), pp.4511-4525
ISSN
1726-4170
Publisher
Copernicus Publications
Start Page
4511
End Page
4525
Journal / Book Title
Biogeosciences
Volume
20
Issue
22
Copyright Statement
© Author(s) 2023. This work is distributed under
the Creative Commons Attribution 4.0 License.
the Creative Commons Attribution 4.0 License.
License URL
Identifier
https://bg.copernicus.org/articles/20/4511/2023/
Publication Status
Published
Date Publish Online
2023-11-17