Limits...
Using an optimality model to understand medium and long-term responses of vegetation water use to elevated atmospheric CO2 concentrations.

Schymanski SJ, Roderick ML, Sivapalan M - AoB Plants (2015)

Bottom Line: Examples include stomatal conductance at short time scale (minutes), leaf area index and fine root distributions at longer time scales (days-months) and species composition and dominant growth forms at very long time scales (years-decades-centuries).As a result, the overall response of evapotranspiration to changes in environmental forcing may also change at different time scales.Without any model tuning or calibration, the model reproduced general trends deduced from FACE experiments, but, contrary to the widespread expectation that eCO2 would generally decrease water use due to its leaf-scale effect on stomatal conductance, our results suggest that eCO2 may lead to unchanged or even increased vegetation water use in water-limited climates, accompanied by an increase in perennial vegetation cover.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental Systems Science, Swiss Federal Institute of Technology Zurich, Universitätstrasse 16, 8092 Zurich, Switzerland Formerly at: Max Planck Institute for Biogeochemistry, Jena, Germany stan.schymanski@env.ethz.ch.

No MeSH data available.


Related in: MedlinePlus

Simulated mean annual evapotranspiration rates for different atmospheric CO2 concentrations (Ca). ‘Medium-term’ refers to simulations where constant vegetation properties (see Table 1) were optimized for Ca = 317 ppm, while dynamic vegetation properties were optimized for the respective Ca. ‘Long-term’ refers to simulations where all vegetation properties were optimized for the respective Ca. The horizontal black dashed lines are a visual guide to see the change relative to the ET rates at 317 ppm Ca.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
getmorefigures.php?uid=PMC4497478&req=5

PLV060F2: Simulated mean annual evapotranspiration rates for different atmospheric CO2 concentrations (Ca). ‘Medium-term’ refers to simulations where constant vegetation properties (see Table 1) were optimized for Ca = 317 ppm, while dynamic vegetation properties were optimized for the respective Ca. ‘Long-term’ refers to simulations where all vegetation properties were optimized for the respective Ca. The horizontal black dashed lines are a visual guide to see the change relative to the ET rates at 317 ppm Ca.

Mentions: Simulated responses to increasing atmospheric CO2 concentrations (Ca). First column in each block gives the actual values (for Ca = 317 ppm), while subsequent columns contain deviations (in %) from these values. Negative differences marked in red font. ‘Medium-term response’, constant vegetation properties (see Table 1) were optimized for Ca = 317 ppm; ‘Long-term adaptation’, all vegetation properties were optimized for the respective Ca. P, precipitation; Q, drainage and runoff; ET, evapotranspiration (transpiration + soil evaporation)1; Et, transpiration1; Es, soil evaporation1; Gs, big-leaf CO2 stomatal conductance2; WUE, water-use efficiency (total Ag/total Et); iWUE, intrinsic WUE [average (Ag/Gs)]; MA, fractional cover of big leaf; Ag, CO2 uptake rate1; Jmax25, leaf electron transport capacity2; λp and λs, median of ∂Et/∂Ag; RAI, root area index (fine root surface area per ground area); Θ1, soil saturation degree in top soil layer; Av(Θ), average saturation degree within the rooting zone of perennial vegetation. All magnitudes given as averages (λp and λs: median values) over last 5 years of simulation. Note that at steady-state, total P = total Q + total ET. However, in the simulations for VIR, soil water storage (saturated + unsaturated) varies by up to 1000 mm on a decadal scale, and in fact decreased in the last 5 years of the simulation by roughly 500 mm, explaining the mean annual imbalance of 100 mm at this site (see Fig. 2 in the SI). 1Per m2 ground area; 2per m2 projected leaf area.


Using an optimality model to understand medium and long-term responses of vegetation water use to elevated atmospheric CO2 concentrations.

Schymanski SJ, Roderick ML, Sivapalan M - AoB Plants (2015)

Simulated mean annual evapotranspiration rates for different atmospheric CO2 concentrations (Ca). ‘Medium-term’ refers to simulations where constant vegetation properties (see Table 1) were optimized for Ca = 317 ppm, while dynamic vegetation properties were optimized for the respective Ca. ‘Long-term’ refers to simulations where all vegetation properties were optimized for the respective Ca. The horizontal black dashed lines are a visual guide to see the change relative to the ET rates at 317 ppm Ca.
© Copyright Policy - creative-commons
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC4497478&req=5

PLV060F2: Simulated mean annual evapotranspiration rates for different atmospheric CO2 concentrations (Ca). ‘Medium-term’ refers to simulations where constant vegetation properties (see Table 1) were optimized for Ca = 317 ppm, while dynamic vegetation properties were optimized for the respective Ca. ‘Long-term’ refers to simulations where all vegetation properties were optimized for the respective Ca. The horizontal black dashed lines are a visual guide to see the change relative to the ET rates at 317 ppm Ca.
Mentions: Simulated responses to increasing atmospheric CO2 concentrations (Ca). First column in each block gives the actual values (for Ca = 317 ppm), while subsequent columns contain deviations (in %) from these values. Negative differences marked in red font. ‘Medium-term response’, constant vegetation properties (see Table 1) were optimized for Ca = 317 ppm; ‘Long-term adaptation’, all vegetation properties were optimized for the respective Ca. P, precipitation; Q, drainage and runoff; ET, evapotranspiration (transpiration + soil evaporation)1; Et, transpiration1; Es, soil evaporation1; Gs, big-leaf CO2 stomatal conductance2; WUE, water-use efficiency (total Ag/total Et); iWUE, intrinsic WUE [average (Ag/Gs)]; MA, fractional cover of big leaf; Ag, CO2 uptake rate1; Jmax25, leaf electron transport capacity2; λp and λs, median of ∂Et/∂Ag; RAI, root area index (fine root surface area per ground area); Θ1, soil saturation degree in top soil layer; Av(Θ), average saturation degree within the rooting zone of perennial vegetation. All magnitudes given as averages (λp and λs: median values) over last 5 years of simulation. Note that at steady-state, total P = total Q + total ET. However, in the simulations for VIR, soil water storage (saturated + unsaturated) varies by up to 1000 mm on a decadal scale, and in fact decreased in the last 5 years of the simulation by roughly 500 mm, explaining the mean annual imbalance of 100 mm at this site (see Fig. 2 in the SI). 1Per m2 ground area; 2per m2 projected leaf area.

Bottom Line: Examples include stomatal conductance at short time scale (minutes), leaf area index and fine root distributions at longer time scales (days-months) and species composition and dominant growth forms at very long time scales (years-decades-centuries).As a result, the overall response of evapotranspiration to changes in environmental forcing may also change at different time scales.Without any model tuning or calibration, the model reproduced general trends deduced from FACE experiments, but, contrary to the widespread expectation that eCO2 would generally decrease water use due to its leaf-scale effect on stomatal conductance, our results suggest that eCO2 may lead to unchanged or even increased vegetation water use in water-limited climates, accompanied by an increase in perennial vegetation cover.

View Article: PubMed Central - PubMed

Affiliation: Department of Environmental Systems Science, Swiss Federal Institute of Technology Zurich, Universitätstrasse 16, 8092 Zurich, Switzerland Formerly at: Max Planck Institute for Biogeochemistry, Jena, Germany stan.schymanski@env.ethz.ch.

No MeSH data available.


Related in: MedlinePlus