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The coordination of leaf photosynthesis links C and N fluxes in C3 plant species.

Maire V, Martre P, Kattge J, Gastal F, Esser G, Fontaine S, Soussana JF - PLoS ONE (2012)

Bottom Line: The resulting model linking leaf photosynthesis, stomata conductance and nitrogen investment provides testable hypotheses about the physiological regulation of these processes.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.

View Article: PubMed Central - PubMed

Affiliation: INRA, UR874 UREP, Clermont-Ferrand, France. vmaire24@gmail.com

ABSTRACT
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.

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Tests of the coordination hypothesis using values of leaf photosynthetic traits predicted from environmental growth conditions.A) Relationship between the predicted rates of RuBP carboxylation/oxygenation (Wc) and RuBP regeneration (Wj) under plant growth conditions. B) Relationship between predicted (Nac) and observed (Na) leaf N content. The insert in Fig. 2B shows the same relationship without the very high observed Na values for the PFT1. Symbols are as for Fig. 1.
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pone-0038345-g002: Tests of the coordination hypothesis using values of leaf photosynthetic traits predicted from environmental growth conditions.A) Relationship between the predicted rates of RuBP carboxylation/oxygenation (Wc) and RuBP regeneration (Wj) under plant growth conditions. B) Relationship between predicted (Nac) and observed (Na) leaf N content. The insert in Fig. 2B shows the same relationship without the very high observed Na values for the PFT1. Symbols are as for Fig. 1.

Mentions: Once the multiple regression models were established for each leaf photosynthetic parameter, we tested by bootstrap analysis if their prediction was robust enough to satisfy the coordination hypothesis. All random datasets generated by bootstrap (n = 220) gave significant regression models (Tables S5–S6). The parameters values of these regression models were used with the remainder of the data (n = 293–220 = 70) to predict leaf photosynthetic parameters values. Photosynthetic parameters values were then used to predict Wc, Wj and Nac. We found that Wc matched Wj (Fig. 2A) and Nac matched Na (Fig. 2B, RRMSE  = 0.2), whatever the random dataset to which it was applied (Tables S5–S6).


The coordination of leaf photosynthesis links C and N fluxes in C3 plant species.

Maire V, Martre P, Kattge J, Gastal F, Esser G, Fontaine S, Soussana JF - PLoS ONE (2012)

Tests of the coordination hypothesis using values of leaf photosynthetic traits predicted from environmental growth conditions.A) Relationship between the predicted rates of RuBP carboxylation/oxygenation (Wc) and RuBP regeneration (Wj) under plant growth conditions. B) Relationship between predicted (Nac) and observed (Na) leaf N content. The insert in Fig. 2B shows the same relationship without the very high observed Na values for the PFT1. Symbols are as for Fig. 1.
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Related In: Results  -  Collection

Show All Figures
getmorefigures.php?uid=PMC3369925&req=5

pone-0038345-g002: Tests of the coordination hypothesis using values of leaf photosynthetic traits predicted from environmental growth conditions.A) Relationship between the predicted rates of RuBP carboxylation/oxygenation (Wc) and RuBP regeneration (Wj) under plant growth conditions. B) Relationship between predicted (Nac) and observed (Na) leaf N content. The insert in Fig. 2B shows the same relationship without the very high observed Na values for the PFT1. Symbols are as for Fig. 1.
Mentions: Once the multiple regression models were established for each leaf photosynthetic parameter, we tested by bootstrap analysis if their prediction was robust enough to satisfy the coordination hypothesis. All random datasets generated by bootstrap (n = 220) gave significant regression models (Tables S5–S6). The parameters values of these regression models were used with the remainder of the data (n = 293–220 = 70) to predict leaf photosynthetic parameters values. Photosynthetic parameters values were then used to predict Wc, Wj and Nac. We found that Wc matched Wj (Fig. 2A) and Nac matched Na (Fig. 2B, RRMSE  = 0.2), whatever the random dataset to which it was applied (Tables S5–S6).

Bottom Line: The resulting model linking leaf photosynthesis, stomata conductance and nitrogen investment provides testable hypotheses about the physiological regulation of these processes.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.

View Article: PubMed Central - PubMed

Affiliation: INRA, UR874 UREP, Clermont-Ferrand, France. vmaire24@gmail.com

ABSTRACT
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.

Show MeSH
Related in: MedlinePlus