EGU2020-12097
https://doi.org/10.5194/egusphere-egu2020-12097
EGU General Assembly 2020
© Author(s) 2020. This work is distributed under
the Creative Commons Attribution 4.0 License.

Leaf nitrogen distribution within canopies is (also) optimal

Han Wang1, Colin Prentice2, Trevor Keenan3, Ülo Niinemets4, and Nils Stenseth5
Han Wang et al.
  • 1Tsinghua University, Department of Earth System Science, Beijing, China (wanghan_sci@yahoo.com)
  • 2Imperial College London, UK
  • 3University of California, Berkeley, US
  • 4Estonian University of Life Sciences, Estonia
  • 5University of Oslo, Norway

The distribution of leaf nitrogen (NL) within canopies has been discussed for decades in relation to the optimality hypothesis that predicts coordination of carboxylation capacity with absorbed light. Although an optimal (that is, proportional) response of both carboxylation capacity and NLto light is extensively supported by field observations of variation among sites, the observed saturation curve of NLwithin canopies seems to challenge the generality of that response. By considering dynamic light regimes, we propose an optimality-based theory that successfully reconciles the apparent conflict of observed NLdistribution within and between canopies. This theory proposes that due to the highly uneven temporal distribution of sun flecks, the light level to which understory leaves acclimate is much higher than the average light level. This proposition leads to a saturation curve for the vertical distribution of NL. Our within-canopy data analysis supports this theory. Understorey leaves require significantly less NLto achieve photosynthetic capacity as an acclimation to sun flecks. The contribution of structural and photosynthetic components to NLpredicted by the theory is quantitatively and consistently supported by global datasets of variation both within and between canopies.

How to cite: Wang, H., Prentice, C., Keenan, T., Niinemets, Ü., and Stenseth, N.: Leaf nitrogen distribution within canopies is (also) optimal, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-12097, https://doi.org/10.5194/egusphere-egu2020-12097, 2020

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