BACKGROUND AND AIMS: Water and nitrogen (N) are two limiting resources for biomass production of terrestrial vegetation. Water losses in transpiration (E) can be decreased by reducing leaf stomatal conductance (g(s)) at the expense of lowering CO(2) uptake (A), resulting in increased water-use efficiency. However, with more N available, higher allocation of N to photosynthetic proteins improves A so that N-use efficiency is reduced when g(s) declines. Hence, a trade-off is expected between these two resource-use efficiencies. In this study it is hypothesized that when foliar concentration (N) varies on time scales much longer than g(s), an explicit complementary relationship between the marginal water- and N-use efficiency emerges. Furthermore, a shift in this relationship is anticipated with increasing atmospheric CO(2) concentration (c(a)). METHODS: Optimization theory is employed to quantify interactions between resource-use efficiencies under elevated c(a) and soil N amendments. The analyses are based on marginal water- and N-use efficiencies, λ = (∂A/∂g(s))/(∂E/∂g(s)) and η = ∂A/∂N, respectively. The relationship between the two efficiencies and related variation in intercellular CO(2) concentration (c(i)) were examined using A/c(i) curves and foliar N measured on Pinus taeda needles collected at various canopy locations at the Duke Forest Free Air CO(2) Enrichment experiment (North Carolina, USA). KEY RESULTS: Optimality theory allowed the definition of a novel, explicit relationship between two intrinsic leaf-scale properties where η is complementary to the square-root of λ. The data support the model predictions that elevated c(a) increased η and λ, and at given c(a) and needle age-class, the two quantities varied among needles in an approximately complementary manner. CONCLUSIONS: The derived analytical expressions can be employed in scaling-up carbon, water and N fluxes from leaf to ecosystem, but also to derive transpiration estimates from those of η, and assist in predicting how increasing c(a) influences ecosystem water use.
BACKGROUND AND AIMS: Water and nitrogen (N) are two limiting resources for biomass production of terrestrial vegetation. Water losses in transpiration (E) can be decreased by reducing leaf stomatal conductance (g(s)) at the expense of lowering CO(2) uptake (A), resulting in increased water-use efficiency. However, with more N available, higher allocation of N to photosynthetic proteins improves A so that N-use efficiency is reduced when g(s) declines. Hence, a trade-off is expected between these two resource-use efficiencies. In this study it is hypothesized that when foliar concentration (N) varies on time scales much longer than g(s), an explicit complementary relationship between the marginal water- and N-use efficiency emerges. Furthermore, a shift in this relationship is anticipated with increasing atmospheric CO(2) concentration (c(a)). METHODS: Optimization theory is employed to quantify interactions between resource-use efficiencies under elevated c(a) and soil N amendments. The analyses are based on marginal water- and N-use efficiencies, λ = (∂A/∂g(s))/(∂E/∂g(s)) and η = ∂A/∂N, respectively. The relationship between the two efficiencies and related variation in intercellular CO(2) concentration (c(i)) were examined using A/c(i) curves and foliar N measured on Pinus taeda needles collected at various canopy locations at the Duke Forest Free Air CO(2) Enrichment experiment (North Carolina, USA). KEY RESULTS: Optimality theory allowed the definition of a novel, explicit relationship between two intrinsic leaf-scale properties where η is complementary to the square-root of λ. The data support the model predictions that elevated c(a) increased η and λ, and at given c(a) and needle age-class, the two quantities varied among needles in an approximately complementary manner. CONCLUSIONS: The derived analytical expressions can be employed in scaling-up carbon, water and N fluxes from leaf to ecosystem, but also to derive transpiration estimates from those of η, and assist in predicting how increasing c(a) influences ecosystem water use.