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ABSTRACT Photosynthesis is the largest flux of carbon between the atmosphere and Earth's surface and is driven by enzymes that require nitrogen, namely, ribulose‐1,5‐bisphosphate (RuBisCO). Thus, photosynthesis is a key link between the terrestrial carbon and nitrogen cycle, and the representation of this link is critical for coupled carbon‐nitrogen land surface models. Models and observations suggest that soil nitrogen availability can limit plant productivity increases under elevated CO2. Plants acclimate to elevated CO2by downregulating RuBisCO and thus nitrogen in leaves, but this acclimation response is not currently included in land surface models. Acclimation of photosynthesis to CO2can be simulated by the photosynthetic optimality theory in a way that matches observations. Here, we incorporated this theory into the land surface component of the Energy Exascale Earth System Model (ELM). We simulated land surface carbon and nitrogen processes under future elevated CO2conditions to 2100 using the RCP8.5 high emission scenario. Our simulations showed that when photosynthetic acclimation is considered, photosynthesis increases under future conditions, but maximum RuBisCO carboxylation and thus photosynthetic nitrogen demand decline. We analyzed two simulations that differed as to whether the saved nitrogen could be used in other parts of the plant. The allocation of saved leaf nitrogen to other parts of the plant led to (1) a direct alleviation of plant nitrogen limitation through reduced leaf nitrogen requirements and (2) an indirect reduction in plant nitrogen limitation through an enhancement of root growth that led to increased plant nitrogen uptake. As a result, reallocation of saved leaf nitrogen increased ecosystem carbon stocks by 50.3% in 2100 as compared to a simulation without reallocation of saved leaf nitrogen. These results suggest that land surface models may overestimate future ecosystem nitrogen limitation if they do not incorporate leaf nitrogen savings resulting from photosynthetic acclimation to elevated CO2.
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Nitrogen demand, availability, and acquisition strategy control plant responses to elevated CO2
Abstract Plants respond to increasing atmospheric CO2 concentrations by reducing leaf nitrogen content and photosynthetic capacity—patterns that correspond with increased net photosynthesis and growth. Despite the longstanding notion that nitrogen availability regulates these responses, eco-evolutionary optimality theory posits that leaf-level responses to elevated CO2 are driven by leaf nitrogen demand for building and maintaining photosynthetic enzymes and are independent of nitrogen availability. In this study, we examined leaf and whole-plant responses of Glycine max L. (Merr) subjected to full-factorial combinations of two CO2, two inoculation, and nine nitrogen fertilization treatments. Nitrogen fertilization and inoculation did not alter leaf photosynthetic responses to elevated CO2. Instead, elevated CO2 decreased the maximum rate of ribulose-1,5-bisophosphate oxygenase/carboxylase (Rubisco) carboxylation more strongly than it decreased the maximum rate of electron transport for ribulose-1,5-bisphosphate (RuBP) regeneration, increasing net photosynthesis by allowing rate-limiting steps to approach optimal coordination. Increasing fertilization enhanced positive whole-plant responses to elevated CO2 due to increased below-ground carbon allocation and nitrogen uptake. Inoculation with nitrogen-fixing bacteria did not influence plant responses to elevated CO2. These results reconcile the role of nitrogen availability in plant responses to elevated CO2, showing that leaf photosynthetic responses are regulated by leaf nitrogen demand while whole-plant responses are constrained by nitrogen availability.
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- Award ID(s):
- 2045968
- PAR ID:
- 10612536
- Publisher / Repository:
- Oxford University Press
- Date Published:
- Journal Name:
- Journal of Experimental Botany
- Volume:
- 76
- Issue:
- 10
- ISSN:
- 0022-0957
- Format(s):
- Medium: X Size: p. 2908-2923
- Size(s):
- p. 2908-2923
- Sponsoring Org:
- National Science Foundation
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