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Experimental vs. modeled water use in mature Norway spruce (Picea abies) exposed to elevated CO(2).

Leuzinger S, Bader MK - Front Plant Sci (2012)

Bottom Line: Rising levels of atmospheric CO(2) have often been reported to reduce plant water use.Here, we provide first results from a free air CO(2) enrichment (FACE) experiment with naturally growing, mature (35 m) Picea abies (L.) (Norway spruce) and compare them to simulations by the DGVM LPJ-GUESS.Using LPJ-GUESS, we simulated this experiment using climate data from a nearby weather station.

View Article: PubMed Central - PubMed

Affiliation: School of Applied Sciences, Auckland University of Technology Auckland, New Zealand ; Forest Ecology, ETH Zurich Zurich, Switzerland ; Institute of Botany, University of Basel Basel, Switzerland.

ABSTRACT
Rising levels of atmospheric CO(2) have often been reported to reduce plant water use. Such behavior is also predicted by standard equations relating photosynthesis, stomatal conductance, and atmospheric CO(2) concentration, which form the core of dynamic global vegetation models (DGVMs). Here, we provide first results from a free air CO(2) enrichment (FACE) experiment with naturally growing, mature (35 m) Picea abies (L.) (Norway spruce) and compare them to simulations by the DGVM LPJ-GUESS. We monitored sap flow, stem water deficit, stomatal conductance, leaf water potential, and soil moisture in five 35-40 m tall CO(2)-treated (550 ppm) trees over two seasons. Using LPJ-GUESS, we simulated this experiment using climate data from a nearby weather station. While the model predicted a stable reduction of transpiration of between 9% and 18% (at concentrations of 550-700 ppm atmospheric CO(2)), the combined evidence from various methods characterizing water use in our experimental trees suggest no changes in response to future CO(2) concentrations. The discrepancy between the modeled and the experimental results may be a scaling issue: while dynamic vegetation models correctly predict leaf-level responses, they may not sufficiently account for the processes involved at the canopy and ecosystem scale, which could offset the first-order stomatal response.

No MeSH data available.


Related in: MedlinePlus

Relationship between soil moisture (mean across ambient and CO2-treated area) and stem water deficit in per mille for P. abies under ambient (open symbols) and elevated CO2-conditions (filled symbols). Periods between day of year 175 and 250 were considered. AIC, Akaike Information Criterion; CPE, nonlinear model with common parameter estimates; VPE, nonlinear model with varying parameter estimates for each treatment. Soil moisture explained 77%, 82%, and 65% of the variation in stem water deficit during the pre-treatment period and the 2009 and 2010 CO2 enrichment periods, respectively. The gray-shaded area around the regression line indicates the 95% confidence interval.
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Figure 4: Relationship between soil moisture (mean across ambient and CO2-treated area) and stem water deficit in per mille for P. abies under ambient (open symbols) and elevated CO2-conditions (filled symbols). Periods between day of year 175 and 250 were considered. AIC, Akaike Information Criterion; CPE, nonlinear model with common parameter estimates; VPE, nonlinear model with varying parameter estimates for each treatment. Soil moisture explained 77%, 82%, and 65% of the variation in stem water deficit during the pre-treatment period and the 2009 and 2010 CO2 enrichment periods, respectively. The gray-shaded area around the regression line indicates the 95% confidence interval.

Mentions: Generally, we tested statistically significant differences between treatments by fitting models with common parameter estimates and varying parameter estimates for each treatment, followed by a comparison of the two models (Figures 2, 4, and 5). The CO2-treatment was considered to affect the variable of interest statistically significantly, if the Akaike information criterion (AIC) was significantly lower in the more complex model (i.e., ΔAIC > 2). To determine the envelope curves for the sap flow-VPD relationships, we calculated the 95th percentiles of relative sap flow (SF95) for every 2 kPa VPDVPD bin and fitted the polynomial model SF95 = a × CO2 + b × VPD + c × VPD2 + d × VPD3, since all other attempts to fit a non-linear model failed. The factor CO2 is the CO2-treatment with the levels 1 (elevated) and 0 (ambient). The interaction term VPD × CO2 was not significant and was therefore dropped. All analyzes were carried out using R version 2.13.0 (R Development Core Team, 2011).


Experimental vs. modeled water use in mature Norway spruce (Picea abies) exposed to elevated CO(2).

Leuzinger S, Bader MK - Front Plant Sci (2012)

Relationship between soil moisture (mean across ambient and CO2-treated area) and stem water deficit in per mille for P. abies under ambient (open symbols) and elevated CO2-conditions (filled symbols). Periods between day of year 175 and 250 were considered. AIC, Akaike Information Criterion; CPE, nonlinear model with common parameter estimates; VPE, nonlinear model with varying parameter estimates for each treatment. Soil moisture explained 77%, 82%, and 65% of the variation in stem water deficit during the pre-treatment period and the 2009 and 2010 CO2 enrichment periods, respectively. The gray-shaded area around the regression line indicates the 95% confidence interval.
© Copyright Policy - open-access
Related In: Results  -  Collection

License
Show All Figures
getmorefigures.php?uid=PMC3472548&req=5

Figure 4: Relationship between soil moisture (mean across ambient and CO2-treated area) and stem water deficit in per mille for P. abies under ambient (open symbols) and elevated CO2-conditions (filled symbols). Periods between day of year 175 and 250 were considered. AIC, Akaike Information Criterion; CPE, nonlinear model with common parameter estimates; VPE, nonlinear model with varying parameter estimates for each treatment. Soil moisture explained 77%, 82%, and 65% of the variation in stem water deficit during the pre-treatment period and the 2009 and 2010 CO2 enrichment periods, respectively. The gray-shaded area around the regression line indicates the 95% confidence interval.
Mentions: Generally, we tested statistically significant differences between treatments by fitting models with common parameter estimates and varying parameter estimates for each treatment, followed by a comparison of the two models (Figures 2, 4, and 5). The CO2-treatment was considered to affect the variable of interest statistically significantly, if the Akaike information criterion (AIC) was significantly lower in the more complex model (i.e., ΔAIC > 2). To determine the envelope curves for the sap flow-VPD relationships, we calculated the 95th percentiles of relative sap flow (SF95) for every 2 kPa VPDVPD bin and fitted the polynomial model SF95 = a × CO2 + b × VPD + c × VPD2 + d × VPD3, since all other attempts to fit a non-linear model failed. The factor CO2 is the CO2-treatment with the levels 1 (elevated) and 0 (ambient). The interaction term VPD × CO2 was not significant and was therefore dropped. All analyzes were carried out using R version 2.13.0 (R Development Core Team, 2011).

Bottom Line: Rising levels of atmospheric CO(2) have often been reported to reduce plant water use.Here, we provide first results from a free air CO(2) enrichment (FACE) experiment with naturally growing, mature (35 m) Picea abies (L.) (Norway spruce) and compare them to simulations by the DGVM LPJ-GUESS.Using LPJ-GUESS, we simulated this experiment using climate data from a nearby weather station.

View Article: PubMed Central - PubMed

Affiliation: School of Applied Sciences, Auckland University of Technology Auckland, New Zealand ; Forest Ecology, ETH Zurich Zurich, Switzerland ; Institute of Botany, University of Basel Basel, Switzerland.

ABSTRACT
Rising levels of atmospheric CO(2) have often been reported to reduce plant water use. Such behavior is also predicted by standard equations relating photosynthesis, stomatal conductance, and atmospheric CO(2) concentration, which form the core of dynamic global vegetation models (DGVMs). Here, we provide first results from a free air CO(2) enrichment (FACE) experiment with naturally growing, mature (35 m) Picea abies (L.) (Norway spruce) and compare them to simulations by the DGVM LPJ-GUESS. We monitored sap flow, stem water deficit, stomatal conductance, leaf water potential, and soil moisture in five 35-40 m tall CO(2)-treated (550 ppm) trees over two seasons. Using LPJ-GUESS, we simulated this experiment using climate data from a nearby weather station. While the model predicted a stable reduction of transpiration of between 9% and 18% (at concentrations of 550-700 ppm atmospheric CO(2)), the combined evidence from various methods characterizing water use in our experimental trees suggest no changes in response to future CO(2) concentrations. The discrepancy between the modeled and the experimental results may be a scaling issue: while dynamic vegetation models correctly predict leaf-level responses, they may not sufficiently account for the processes involved at the canopy and ecosystem scale, which could offset the first-order stomatal response.

No MeSH data available.


Related in: MedlinePlus