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 (
gs) 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
gs 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
gs, 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 (
ca).
Methods
Optimization theory is employed to quantify interactions between resource-use efficiencies under elevated
ca and soil N amendments. The analyses are based on marginal water- and N-use efficiencies, λ = (∂
A/∂
gs)/(∂
E/∂
gs) and η = ∂
A/∂
N, respectively. The relationship between the two efficiencies and related variation in intercellular CO
2 concentration (
ci) were examined using
A/
ci 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
ca increased η and λ, and at given
ca 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
ca influences ecosystem water use.
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