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An optimality-based model explains seasonal variation in C3 plant photosynthetic capacity.
- Source :
-
Global change biology [Glob Chang Biol] 2020 Nov; Vol. 26 (11), pp. 6493-6510. Date of Electronic Publication: 2020 Sep 12. - Publication Year :
- 2020
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Abstract
- The maximum rate of carboxylation (V <subscript>cmax</subscript> ) is an essential leaf trait determining the photosynthetic capacity of plants. Existing approaches for estimating V <subscript>cmax</subscript> at large scale mainly rely on empirical relationships with proxies such as leaf nitrogen/chlorophyll content or hyperspectral reflectance, or on complicated inverse models from gross primary production or solar-induced fluorescence. A novel mechanistic approach based on the assumption that plants optimize resource investment coordinating with environment and growth has been shown to accurately predict C3 plant V <subscript>cmax</subscript> based on mean growing season environmental conditions. However, the ability of optimality theory to explain seasonal variation in V <subscript>cmax</subscript> has not been fully investigated. Here, we adapt an optimality-based model to simulate daily V <subscript>cmax,25C</subscript> (V <subscript>cmax</subscript> at a standardized temperature of 25°C) by incorporating the effects of antecedent environment, which affects current plant functioning, and dynamic light absorption, which coordinates with plant functioning. We then use seasonal V <subscript>cmax,25C</subscript> field measurements from 10 sites across diverse ecosystems to evaluate model performance. Overall, the model explains about 83% of the seasonal variation in C3 plant V <subscript>cmax,25C</subscript> across the 10 sites, with a medium root mean square error of 12.3 μmol m <superscript>-2</superscript>  s <superscript>-1</superscript> , which suggests that seasonal changes in V <subscript>cmax,25C</subscript> are consistent with optimal plant function. We show that failing to account for acclimation to antecedent environment or coordination with dynamic light absorption dramatically decreases estimation accuracy. Our results show that optimality-based approach can accurately reproduce seasonal variation in canopy photosynthetic potential, and suggest that incorporating such theory into next-generation trait-based terrestrial biosphere models would improve predictions of global photosynthesis.<br /> (© 2020 John Wiley & Sons Ltd.)
- Subjects :
- Chlorophyll
Climate
Plant Leaves
Seasons
Ecosystem
Photosynthesis
Subjects
Details
- Language :
- English
- ISSN :
- 1365-2486
- Volume :
- 26
- Issue :
- 11
- Database :
- MEDLINE
- Journal :
- Global change biology
- Publication Type :
- Academic Journal
- Accession number :
- 32654330
- Full Text :
- https://doi.org/10.1111/gcb.15276