Climate forcing due to optimization of maximal leaf conductance in subtropical vegetation under rising CO2

Abstract

Plant physiological adaptation to the global rise in atmospheric CO(2) concentration (CO(2)) is identified as a crucial climatic forcing. To optimize functioning under rising CO(2), plants reduce the diffusive stomatal conductance of their leaves (g(s)) dynamically by closing stomata and structurally by growing leaves with altered stomatal densities and pore sizes. The structural adaptations reduce maximal stomatal conductance (g(smax)) and constrain the dynamic responses of g(s). Here, we develop and validate models that simulate structural stomatal adaptations based on diffusion of CO(2) and water vapor through stomata, photosynthesis, and optimization of carbon gain under the constraint of a plant physiological cost of water loss. We propose that the ongoing optimization of g(smax) is eventually limited by species-specific limits to phenotypic plasticity. Our model reproduces observed structural stomatal adaptations and predicts that adaptation will continue beyond double CO(2). Owing to their distinct stomatal dimensions, angiosperms reach their phenotypic response limits on average at 740 ppm and conifers on average at 1,250 ppm CO(2). Further, our simulations predict that doubling today's CO(2) will decrease the annual transpiration flux of subtropical vegetation in Florida by ≈60 W·m(-2). We conclude that plant adaptation to rising CO(2) is altering the freshwater cycle and climate and will continue to do so throughout this century.

Fig. 1.

An overview of observed relationships among stomatal density (D), pore size at maximal stomatal opening (a_max), and the resulting maximal stomatal conductance (g_smax) and leaf surface area allocated to stomatal pores at a_max (A_%). (A) Power law relationship between D and a_max are plotted together with lines of equal g_smax (solid lines) and A_% (dashed lines). See Eq. 1 and Table S1 for calculations of g_smax. Note that logarithmic axes are used. (B) Cumulative probability of A_% for woody angiosperm and conifer species fitted to a lognormal distribution. The value of 0.6 indicates the estimated lower bound (5% probability) on A_% defined here as A_%low. Note that a logarithmic x axis is used. (C) Species-specific strategies to adapt g_smax linearly with A_%. The dashed line denotes A_%low. Lines of linear least squares regressions are indicated per species and used to determine the intersect with A_%low to predict the lowest attainable g_smax for each species, defined as g_low. The r² values are: 0. 97 (Ar), 0.96 (Ic), 0.86 (Mc), 0.96 (Ql), 0.91 (Qn), 0.85 (Pe), 0.98 (Pt), and 0.94 (Td) with P < 0.001 for all. Data FB09 are from ref. , others from ref. . Species names and their abbreviations are defined in the legend.

Fig. 2.

Modeled structural adaptations of g_smax to CO₂ for each species (solid colored lines), compared with measured g_smax averaged at each measured CO₂. Inset shows a direct comparison between modeled and measured g_smax averaged over CO₂ quartiles of the data. Error bars indicate SDs of modeled (vertical) and measured (horizontal) g_smax in each quartile.

Fig. 3.

Modeled daily average gas exchange at the leaf level for ensembles with dynamic stomatal adaptation only (GfixMod), with structural and dynamic adaptation (GoptMod) and with CO₂ response limits included (GlimMod). (A) Simulated stomatal conductance (g_s). (B) Transpiration (E). (C) Assimilation (A) and C_i/C_a-ratio at maximum photosynthesis. (D) Water use efficiency (WUE) expressed in [mmol (CO₂)·mol (H₂O)^-1].

Fig. 4.

Changes in annual canopy transpiration [ΔLE (W·m⁻²)] among preindustrial, present, and double CO₂ for ensembles with dynamic stomatal adaptation only (GfixMod), with structural and dynamic adaptation (GoptMod), and with CO₂ response limits included (GlimMod). Error bars for individual species denote SDs in daily average transpiration for preindustrial and double CO₂; error bars for mean values denote SDs between species averages.