Global climate models predict decreases in leaf stomatal conductance and transpiration due to increases in atmospheric CO₂. The consequences of these reductions are increases in soil moisture availability and continental scale run-off at decadal time-scales. Thus, a theory explaining the differential sensitivity of stomata to changing atmospheric CO₂ and other environmental conditions must be identified. Here, these responses are investigated using optimality theory applied to stomatal conductance. An analytical model for stomatal conductance is proposed based on: (a) Fickian mass transfer of CO₂ and H₂O through stomata; (b) a biochemical photosynthesis model that relates intercellular CO₂ to net photosynthesis; and (c) a stomatal model based on optimization for maximizing carbon gains when water losses represent a cost. Comparisons between the optimization-based model and empirical relationships widely used in climate models were made using an extensive gas exchange dataset collected in a maturing pine (Pinus taeda) forest under ambient and enriched atmospheric CO₂. In this interpretation, it is proposed that an individual leaf optimally and autonomously regulates stomatal opening on short-term (approx. 10-min time-scale) rather than on daily or longer time-scales. The derived equations are analytical with explicit expressions for conductance, photosynthesis and intercellular CO₂, thereby making the approach useful for climate models. Using a gas exchange dataset collected in a pine forest, it is shown that (a) the cost of unit water loss λ (a measure of marginal water-use efficiency) increases with atmospheric CO₂; (b) the new formulation correctly predicts the condition under which CO₂-enriched atmosphere will cause increasing assimilation and decreasing stomatal conductance.

The partitioning among carbon (C) pools of the extra C captured under elevated atmospheric CO₂concentration ([CO₂]) determines the enhancement in C sequestration, yet no clear partitioning rules exist. Here, we used first principles and published data from four free-air CO₂enrichment (FACE) experiments on forest tree species to conceptualize the total allocation of C to below ground (TBCA) under current [CO₂] and to predict the likely effect of elevated [CO₂]. We show that at a FACE site where leaf area index (L) ofPinus taedaL. was altered through nitrogen fertilization, ice-storm damage, and droughts, changes inL, reflecting the aboveground sink for net primary productivity, were accompanied by opposite changes in TBCA. A similar pattern emerged when data were combined from the four FACE experiments, using leaf area duration (L_D) to account for differences in growing-season length. Moreover, elevated [CO₂]-induced enhancement of TBCA in the combined data decreased from ≈50% (700 g C m⁻²y⁻¹) at the lowestL_Dto ≈30% (200 g C m⁻²y⁻¹) at the highestL_D. The consistency of the trend in TBCA withLand its response to [CO₂] across the sites provides a norm for predictions of ecosystem C cycling, and is particularly useful for models that useLto estimate components of the terrestrial C balance.

We estimated long‐term annual evapotranspiration (ET_Q) at the watershed scale by combining continuous daily streamflow (Q) records, a simplified watershed water balance, and a nonlinear reservoir model. Our analysis used Q measured from 11 watersheds (area ranged from 12 to 1386 km²) from the uppermost section of the Neuse River Basin in North Carolina, USA. In this area, forests and agriculture dominate the land cover and the spatial variation in climatic drivers is small. About 30% of the interannual variation in the basin‐averaged ET_Q was explained by the variation in precipitation (P), while ET_Q showed a minor inverse correlation with pan evaporation. The sum of annual Q and ET_Q was consistent with the independently measured P. Our analysis shows that records of Q can provide approximate, continuous estimates of long‐term ET and, thereby, bounds for modeling regional fluxes of water and of other closely coupled elements, such as carbon.

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 CO₂ 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 CO₂ concentration (c_a). 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 CO₂ 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 CO₂ Enrichment experiment (North Carolina, USA). 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. 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.