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Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions.

ABSTRACT: The distribution of leaf nitrogen among photosynthetic proteins (i.e. chlorophyll, the electron transport system, Rubisco, and other soluble proteins) responds to environmental changes. We hypothesize that this response may underlie the biochemical aspect of leaf acclimation to the growth environment, and describe an analytical method to solve optimum nitrogen partitioning for maximized photosynthesis in C3 leaves. The method predicts a high investment of nitrogen in Rubisco under conditions leading to excessive energy supply relative to metabolic demand (e.g. low temperature, high light, low nitrogen, or low CO2). Conversely, more nitrogen is invested in chlorophyll when the energy supply is limiting. Overall, our optimization results are qualitatively consistent with literature reports. Commonly reported changes in photosynthetic parameters with growth temperature were emergent properties of the optimum nitrogen partitioning. The method was used to simulate dynamic acclimation under varying environmental conditions, using first-order kinetics. Simulated diurnal patterns of leaf photosynthetic rates as a result of acclimation differed greatly from those without acclimation (Awithout). However, differences in predicted photosynthesis integrated over a day or over the growing season from Awithout depended on the value of the kinetic time constant (?), suggesting that ? is a critical parameter determining the overall impact of nitrogen distribution on acclimated photosynthesis.

SUBMITTER: Yin X

PROVIDER: S-EPMC6519419 | biostudies-literature | 2019 Apr

REPOSITORIES: biostudies-literature

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Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions.

Yin Xinyou X Schapendonk Ad H C M AHCM Struik Paul C PC

Journal of experimental botany 20190401 9

The distribution of leaf nitrogen among photosynthetic proteins (i.e. chlorophyll, the electron transport system, Rubisco, and other soluble proteins) responds to environmental changes. We hypothesize that this response may underlie the biochemical aspect of leaf acclimation to the growth environment, and describe an analytical method to solve optimum nitrogen partitioning for maximized photosynthesis in C3 leaves. The method predicts a high investment of nitrogen in Rubisco under conditions lea ...[more]

PMID: 30053195

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Project description:Photosynthetic capacity is one of the most sensitive parameters in vegetation models and its relationship to leaf nitrogen content links the carbon and nitrogen cycles. Process understanding for reliably predicting photosynthetic capacity is still missing. To advance this understanding we have tested across C(3) plant species the coordination hypothesis, which assumes nitrogen allocation to photosynthetic processes such that photosynthesis tends to be co-limited by ribulose-1,5-bisphosphate (RuBP) carboxylation and regeneration. The coordination hypothesis yields an analytical solution to predict photosynthetic capacity and calculate area-based leaf nitrogen content (N(a)). The resulting model linking leaf photosynthesis, stomata conductance and nitrogen investment provides testable hypotheses about the physiological regulation of these processes. Based on a dataset of 293 observations for 31 species grown under a range of environmental conditions, we confirm the coordination hypothesis: under mean environmental conditions experienced by leaves during the preceding month, RuBP carboxylation equals RuBP regeneration. We identify three key parameters for photosynthetic coordination: specific leaf area and two photosynthetic traits (k(3), which modulates N investment and is the ratio of RuBP carboxylation/oxygenation capacity (V(Cmax)) to leaf photosynthetic N content (N(pa)); and J(fac), which modulates photosynthesis for a given k(3) and is the ratio of RuBP regeneration capacity (J(max)) to V(Cmax)). With species-specific parameter values of SLA, k(3) and J(fac), our leaf photosynthesis coordination model accounts for 93% of the total variance in N(a) across species and environmental conditions. A calibration by plant functional type of k(3) and J(fac) still leads to accurate model prediction of N(a), while SLA calibration is essentially required at species level. Observed variations in k(3) and J(fac) are partly explained by environmental and phylogenetic constraints, while SLA variation is partly explained by phylogeny. These results open a new avenue for predicting photosynthetic capacity and leaf nitrogen content in vegetation models.

Dataset Information

Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions.

Publications

Exploring the optimum nitrogen partitioning to predict the acclimation of C3 leaf photosynthesis to varying growth conditions.

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