Ball-Berry Model Research Articles

The response of mesophyll conductance to short-term CO2 variation is related to stomatal conductance.

The response of mesophyll conductance (gm) to CO2 plays a key role in photosynthesis and ecosystem carbon cycles under climate change. Despite numerous studies, there is still debate about how gm responds to short-term CO2 variations. Here we used multiple methods and looked at the relationship between stomatal conductance to CO2 (gsc) and gm to address this aspect. We measured chlorophyll fluorescence parameters and online carbon isotope discrimination (Δ) at different CO2 mole fractions in sunflower (Helianthus annuus L.), cowpea (Vigna unguiculata L.), and wheat (Triticum aestivum L.) leaves. The variable J and Δ based methods showed that gm decreased with an increase in CO2 mole fraction, and so did stomatal conductance. There were linear relationships between gm and gsc across CO2 mole fractions. gm obtained from A-Ci curve fitting method was higher than that from the variable J method and was not representative of gm under the growth CO2 concentration. gm could be estimated by empirical models analogous to the Ball-Berry model and the USO model for stomatal conductance. Our results suggest that gm and gsc respond in a coordinated manner to short-term variations in CO2, providing new insight into the role of gm in photosynthesis modelling.

Improvement of transpiration estimation based on a two-leaf conductance-photosynthesis model with seasonal parameters for temperate deciduous forests.

Conductance-photosynthesis (Gs-A) models, accompanying with light use efficiency (LUE) models for calculating carbon assimilation, are widely used for estimating canopy stomatal conductance (Gs) and transpiration (Tc) under the two-leaf (TL) scheme. However, the key parameters of photosynthetic rate sensitivity (gsu and gsh) and maximum LUE (ϵmsu and ϵmsh) are typically set to temporally constant values for sunlit and shaded leaves, respectively. This may result in Tc estimation errors, as it contradicts field observations. In this study, the measured flux data from three temperate deciduous broadleaved forests (DBF) FLUXNET sites were adopted, and the key parameters of LUE and Ball-Berry models for sunlit and shaded leaves were calibrated within the entire growing season and each season, respectively. Then, the estimations of gross primary production (GPP) and Tc were compared between the two schemes of parameterization: (1) entire growing season-based fixed parameters (EGS) and (2) season-specific dynamic parameters (SEA). Our results show a cyclical variability of ϵmsu across the sites, with the highest value during the summer and the lowest during the spring. A similar pattern was found for gsu and gsh, which showed a decrease in summer and a slight increase in both spring and autumn. Furthermore, the SEA model (i.e., the dynamic parameterization) better simulated GPP, with a reduction in root mean square error (RMSE) of about 8.0 ± 1.1% and an improvement in correlation coefficient (r) of 3.7 ± 1.5%, relative to the EGS model. Meanwhile, the SEA scheme reduced Tc simulation errors in terms of RMSE by 3.7 ± 4.4%. These findings provide a greater understanding of the seasonality of plant functional traits, and help to improve simulations of seasonal carbon and water fluxes in temperate forests.

Photosynthetic resource-use efficiency trade-offs triggered by vapour pressure deficit and nitrogen supply in a C4 species

Trade-offs in resource-use efficiency (including water-, nitrogen-, and light-use efficiency, i.e., WUE, NUE, and LUE) are an important acclimation strategy of plants to environmental stresses. C4 photosynthesis, featured by a CO2 concentrating mechanism, is believed to be more efficient in using resources compared to C3 photosynthesis. However, response of photosynthetic resource-use efficiency trade-offs in C4 plants to vapour pressure deficit (VPD) and N supply has rarely been studied. Here, we studied the photosynthetic acclimation of Cleistogenes squarrosa, a perennial C4 grass, to controlled growth conditions with high or low VPD and N supply. High VPD increased WUE by 12% and decreased NUE by 16%, the ratio of net photosynthetic rate (A) to electron transport rate (J) (A/J) by 7% and the apparent quantum yield by 6%. High N supply tended to reduce NUE and increased maximum phosphoenol pyruvate carboxylation rate by 71% and slightly increased WUE. Stomatal conductance showed acclimation to VPD according to the Ball-Berry model, while a balanced cost of carboxylation and transpiration capacity was found across VPD and N treatments based on the least-cost model. WUE correlated negatively with NUE and LUE indicating that there was a trade-off between them, which is likely associated with acclimations in stomatal conductance and CO2 concentrating mechanisms.

Effects of Warming and Drought Stress on the Coupling of Photosynthesis and Transpiration in Winter Wheat (Triticum aestivum L.)

The coupling of photosynthesis and transpiration in plant leaves forms the basis of carbon–water coupling in terrestrial ecosystems. Previous studies have attributed the coupling of leaf photosynthesis and transpiration to joint stomata control, but they lack analyses of the coupling mechanism. In this study, winter wheat (Triticum aestivum L.) was selected as a plant material on the North China Plain. Under the conditions of warming and drought stress, the photosynthetic rate (An), transpiration rate (Tr), water pressure saturation (VPD), and leaf temperature (T1) of wheat were recorded on clear days at the jointing, flowering, and grain-filling stages from 9:00 to 12:00 a.m. Then, the measured values were fitted to the simulated values obtained using the Ball–Berry and Penman–Monteith models. The results showed that the stomatal size, stomatal conductance, An, and Tr of winter wheat leaves were decreased by warming, drought stress, and their synergistic effects. Based on the Ball–Berry model, different fitting effects were observed in the treatments of adequate water supply with warming (R-g), water deficit with warming (R-d), adequate water supply without warming (N-g), and water deficit without warming (N-d). The R2 values of the R-g, R-d, N-g, and N-d treatments were 0.962, 0.958, 0.964, and 0.943, respectively. The Tr values were fitted based on the Penman–Monteith model. In the R-g, R-d, N-g, and N-d treatments, the R2 values of the R-g, R-d, N-g, and N-d treatments were 0.923, 0.849, 0.934, and 0.919, respectively. In conclusion, both warming and water deficit reduce stomatal conductance, An, Tr, and the coupling effect of photosynthesis and transpiration.

A comparative study of three stomatal conductance models for estimating evapotranspiration in a dune ecosystem in a semi-arid region

The accurate simulation of stomatal conductance is crucial for not only revealing the carbon and water cycle processes of an ecosystem, but also to improve the accuracy of simulations of evapotranspiration (ET). This study coupled three stomatal conductance models, i.e. the Stannard (ST), Jarvis-Stewart (JS), and Ball-Berry (BB) models, with the Shuttleworth-Wallace (SW) model to estimate ET for a mobile dune ecosystem in the Horqin Sandy Land, North China. These models were calibrated and validated using eddy covariance (EC) measurements taken during the growing season between 2013 and 2018. The results indicated that the SW-BB model showed better performance in comparison to the SW-JS and SW-ST models at half-hourly and daily timescales. The stomatal conductance models incorporating soil moisture (SM) content generally showed better performance during the extreme drought period, with the rank of the three models according to performance being: SW-BB > SW-JS > SW-ST. The models showed the highest sensitivity to SM when incorporating the effect of SM on stomatal conductance, indicating that SM has an important effect on stomatal conductance and ET. The results of this study indicate that of the models assessed, the Ball-Berry stomatal conductance model coupled with the SW model is optimal for estimating ET in dune ecosystems with sparse vegetation.

Evaluating ecohydrological modelling framework to link atmospheric CO2 and stomatal conductance

AbstractThe establishment of an accurate stomatal conductance (gs) model in responding to CO2 enrichment under diverse environmental conditions remains an important issue as gs is the key to understand the plant–water–atmosphere interactions. A better representation of gs is important to reduce uncertainties in predicting the climate change impacts on various ecosystem functions. In this study, we evaluated three most commonly used gs formulations for the estimation of the stomatal response to environmental factors using in situ measurements under different environmental conditions. The three gs models were Leuning's modified Ball–Berry model and two specific cases of the optimization models (i.e., Rubisco limitation model and RuBP regeneration limitation model). On the basis of an analysis of 234 data points obtained from experiments under instantaneous, semicontrolled, and the free‐air CO2 experiment conditions, we found that Leuning's modified Ball–Berry model and RuBP‐limited optimization model showed similar performance, and both performed better than Rubisco limitation model. Functional groups (e.g., C3 vs. C4 species) and life form (e.g., annual vs. perennial species) play an important role in determining the gs model performance and thus pose a challenge for gs predictions in mixed vegetation communities.

On the minimum leaf conductance: its role in models of plant water use, and ecological and environmental controls.

Contents Summary 693 I. Introduction 693 II. Comparison of various definitions and measurement techniques of minimum conductance 694 III. Cuticular conductance 695 IV. Contribution of stomata 696 V. Environmental and ecological variation in minimum conductance 696 VI. Use of minimum conductance in models 698 VII. Conclusions 703 Acknowledgements 703 References 703 SUMMARY: When the rate of photosynthesis is greatly diminished, such as during severe drought, extreme temperature or low light, it seems advantageous for plants to close stomata and completely halt water loss. However, water loss continues through the cuticle and incompletely closed stomata, together constituting the leaf minimum conductance (gmin ). In this review, we critically evaluate the sources of variation in gmin , quantitatively compare various methods for its estimation, and illustrate the role of gmin in models of leaf gas exchange. A literature compilation of gmin as measured by the weight loss of detached leaves is presented, which shows much variation in this trait, which is not clearly related to species groups, climate of origin or leaf type. Much evidence points to the idea that gmin is highly responsive to the growing conditions of the plant, including soil water availability, temperature and air humidity - as we further demonstrate with two case studies. We pay special attention to the role of the minimum conductance in the Ball-Berry model of stomatal conductance, and caution against the usual regression-based method for its estimation. The synthesis presented here provides guidelines for the use of gmin in ecosystem models, and points to clear research gaps for this drought tolerance trait.

Acclimation to Fluctuating Light Impacts the Rapidity of Response and Diurnal Rhythm of Stomatal Conductance.

Plant acclimation to growth light environment has been studied extensively; however, the majority of these studies have focused on light intensity and photo-acclimation, with few studies exploring the impact of dynamic growth light on stomatal acclimation and behavior. To assess the impact of growth light regime on stomatal acclimation, we grew Arabidopsis (Arabidopsis thaliana) plants in three different lighting regimes (with the same average daily intensity), fluctuating with a fixed pattern of light, fluctuating with a randomized pattern of light (sinusoidal), and nonfluctuating (square wave), to assess the effect of light regime dynamics on gas exchange. We demonstrated that gs (stomatal conductance to water vapor) acclimation is influenced by both intensity and light pattern, modifying the stomatal kinetics at different times of the day and resulting in differences in the rapidity and magnitude of the gs response. We also describe and quantify the response to an internal signal that uncouples variation in A and gs over the majority of the diurnal period and represents 25% of the total diurnal gs This gs response can be characterized by a Gaussian element and when incorporated into the widely used Ball-Berry model greatly improved the prediction of gs in a dynamic environment. From these findings, we conclude that acclimation of gs to growth light could be an important strategy for maintaining carbon fixation and overall plant water status and should be considered when inferring responses in the field from laboratory-based experiments.

Seasonal variability of the parameters of the Ball-Berry model of stomatal conductance in maize (Zea mays L.) and sunflower (Helianthus annuus L.) under well-watered and water-stressed conditions.

The Ball-Berry (BB) model of stomatal conductance (gs ) is frequently coupled with a model of assimilation to estimate water and carbon exchanges in plant canopies. The empirical slope (m) and 'residual' gs (g0 ) parameters of the BB model influence transpiration estimates, but the time-intensive nature of measurement limits species-specific data on seasonal and stress responses. We measured m and g0 seasonally and under different water availability for maize and sunflower. The statistical method used to estimate parameters impacted values nominally when inter-plant variability was low, but had substantial impact with larger inter-plant variability. Values for maize (m=4.53±0.65; g0 =0.017±0.016 mol m-2 s-1 ) were 40% higher than other published values. In maize, we found no seasonal changes in m or g0 , supporting the use of constant seasonal values, but water stress reduced both parameters. In sunflower, inter-plant variability of m and g0 was large (m=8.84±3.77; g0 =0.354±0.226 mol m-2 s-1 ), presenting a challenge to clear interpretation of seasonal and water stress responses - m values were stable seasonally, even as g0 values trended downward, and m values trended downward with water stress while g0 values declined substantially.

Estimating the sensitivity of stomatal conductance to photosynthesis: a review.

A common approach for estimating fluxes of CO2 and water in canopy models is to couple a model of photosynthesis (An ) to a semi-empirical model of stomatal conductance (gs ) such as the widely validated and utilized Ball-Berry (BB) model. This coupling provides an effective way of predicting transpiration at multiple scales. However, the designated value of the slope parameter (m) in the BB model impacts transpiration estimates. There is a lack of consensus regarding how m varies among species or plant functional types (PFTs) or in response to growth conditions. Literature values are highly variable, with inter-species and intra-species variations of >100%, and comparisons are made more difficult because of differences in collection techniques. This paper reviews the various methods used to estimate m and highlights how variations in measurement techniques or the data utilized can influence the resultant m. Additionally, this review summarizes the reported responses of m to [CO2 ] and water stress, collates literature values by PFT and compiles nearly three decades of values into a useful compendium.

Suitability of four stomatal conductance models in agro-pastoral ecotone in North China: A case study for potato and oil sunflower.

The suitability of four popular empirical and semi-empirical stomatal conductance models (Jarvis model, Ball-Berry model, Leuning model and Medlyn model) was evaluated based on para-llel observation data of leaf stomatal conductance, leaf net photosynthetic rate and meteorological factors during the vigorous growing period of potato and oil sunflower at Wuchuan experimental station in agro-pastoral ecotone in North China. It was found that there was a significant linear relationship between leaf stomatal conductance and leaf net photosynthetic rate for potato, whereas the linear relationship appeared weaker for oil sunflower. The results of model evaluation showed that Ball-Berry model performed best in simulating leaf stomatal conductance of potato, followed by Leuning model and Medlyn model, while Jarvis model was the last in the performance rating. The root-mean-square error (RMSE) was 0.0331, 0.0371, 0.0456 and 0.0794 mol·m-2·s-1, the normalized root-mean-square error (NRMSE) was 26.8%, 30.0%, 36.9% and 64.3%, and R-squared (R2) was 0.96, 0.61, 0.91 and 0.88 between simulated and observed leaf stomatal conductance of potato for Ball-Berry model, Leuning model, Medlyn model and Jarvis model, respectively. For leaf stomatal conductance of oil sunflower, Jarvis model performed slightly better than Leuning model, Ball-Berry model and Medlyn model. RMSE was 0.2221, 0.2534, 0.2547 and 0.2758 mol·m-2·s-1, NRMSE was 40.3%, 46.0%, 46.2% and 50.1%, and R2 was 0.38, 0.22, 0.23 and 0.20 between simulated and observed leaf stomatal conductance of oil sunflower for Jarvis model, Leuning model, Ball-Berry model and Medlyn model, respectively. The path analysis was conducted to identify effects of specific meteorological factors on leaf stomatal conductance. The diurnal variation of leaf stomatal conductance was principally affected by vapour pressure saturation deficit for both potato and oil sunflower. The model evaluation suggested that the stomatal conductance models for oil sunflower are to be improved in further research.

Plantecophys--An R Package for Analysing and Modelling Leaf Gas Exchange Data.

Here I present the R package 'plantecophys', a toolkit to analyse and model leaf gas exchange data. Measurements of leaf photosynthesis and transpiration are routinely collected with portable gas exchange instruments, and analysed with a few key models. These models include the Farquhar-von Caemmerer-Berry (FvCB) model of leaf photosynthesis, the Ball-Berry models of stomatal conductance, and the coupled leaf gas exchange model which combines the supply and demand functions for CO2 in the leaf. The 'plantecophys' R package includes functions for fitting these models to measurements, as well as simulating from the fitted models to aid in interpreting experimental data. Here I describe the functionality and implementation of the new package, and give some examples of its use. I briefly describe functions for fitting the FvCB model of photosynthesis to measurements of photosynthesis-CO2 response curves ('A-Ci curves'), fitting Ball-Berry type models, modelling C3 photosynthesis with the coupled photosynthesis-stomatal conductance model, modelling C4 photosynthesis, numerical solution of optimal stomatal behaviour, and energy balance calculations using the Penman-Monteith equation. This open-source package makes technically challenging calculations easily accessible for many users and is freely available on CRAN.

Modeling stomatal conductance in the earth system: linking leaf water-use efficiency and water transport along the soil–plant–atmosphere continuum

Abstract. The Ball–Berry stomatal conductance model is commonly used in earth system models to simulate biotic regulation of evapotranspiration. However, the dependence of stomatal conductance (gs) on vapor pressure deficit (Ds) and soil moisture must be empirically parameterized. We evaluated the Ball–Berry model used in the Community Land Model version 4.5 (CLM4.5) and an alternative stomatal conductance model that links leaf gas exchange, plant hydraulic constraints, and the soil–plant–atmosphere continuum (SPA). The SPA model simulates stomatal conductance numerically by (1) optimizing photosynthetic carbon gain per unit water loss while (2) constraining stomatal opening to prevent leaf water potential from dropping below a critical minimum. We evaluated two optimization algorithms: intrinsic water-use efficiency (ΔAn /Δgs, the marginal carbon gain of stomatal opening) and water-use efficiency (ΔAn /ΔEl, the marginal carbon gain of transpiration water loss). We implemented the stomatal models in a multi-layer plant canopy model to resolve profiles of gas exchange, leaf water potential, and plant hydraulics within the canopy, and evaluated the simulations using leaf analyses, eddy covariance fluxes at six forest sites, and parameter sensitivity analyses. The primary differences among stomatal models relate to soil moisture stress and vapor pressure deficit responses. Without soil moisture stress, the performance of the SPA stomatal model was comparable to or slightly better than the CLM Ball–Berry model in flux tower simulations, but was significantly better than the CLM Ball–Berry model when there was soil moisture stress. Functional dependence of gs on soil moisture emerged from water flow along the soil-to-leaf pathway rather than being imposed a priori, as in the CLM Ball–Berry model. Similar functional dependence of gs on Ds emerged from the ΔAn/ΔEl optimization, but not the ΔAn /gs optimization. Two parameters (stomatal efficiency and root hydraulic conductivity) minimized errors with the SPA stomatal model. The critical stomatal efficiency for optimization (ι) gave results consistent with relationships between maximum An and gs seen in leaf trait data sets and is related to the slope (g1) of the Ball–Berry model. Root hydraulic conductivity (Rr*) was consistent with estimates from literature surveys. The two central concepts embodied in the SPA stomatal model, that plants account for both water-use efficiency and for hydraulic safety in regulating stomatal conductance, imply a notion of optimal plant strategies and provide testable model hypotheses, rather than empirical descriptions of plant behavior.

Contrasting Water‐Use Efficiency (WUE) Responses of a Potato Mapping Population and Capability of Modified Ball‐Berry Model to Predict Stomatal Conductance and WUE Measured at Different Environmental Conditions

AbstractPotatoes (Solanum tuberosum L.) are drought‐sensitive and more efficient water use, while maintaining high yields is required. Here, water‐use efficiency (WUE) of a mapping population comprising 144 clones from a cross between 90‐HAF‐01 (Solanum tuberosum1) and 90‐HAG‐15 (S. tuberosum2 × S. sparsipilum) was measured on well‐watered plants under controlled‐environment conditions combining three levels of each of the factors: [CO2], temperature, light, and relative humidity in growth chambers. The clones were grouped according to their photosynthetic WUE (pWUE) and whole‐plant WUE (wpWUE) during experiments in 2010. Two offspring groups according to pWUE and wpWUE were identified on the basis of experiments conducted in 2010, which in experiments in 2011 again showed significant differences in pWUE (46 %, P < 0.001) and wpWUE (34 %, P < 0.001). The high‐WUE group had a higher net photosynthesis rate (34 %) and dry matter accumulation (55 %, P < 0.001) rather than leaf‐level transpiration rate (−4 %, no significant difference) or whole‐plant water use (16 %). The pWUE correlated negatively to the ratio between leaf‐internal and leaf‐external [CO2] (R2 = −0.86 in 2010 and R2 = −0.83 in 2011, P < 0.001). The leaf chlorophyll content was lower in the high‐WUE group indicating that the higher net photosynthesis rate was not due to higher leaf‐N status. Less negative value of carbon isotope discrimination (δ13C) in the high‐WUE group was only found in 2011. A modified Ball‐Berry model was fitted to measured stomatal conductance (gs) under the systematically varied environmental conditions to identify parameter differences between the two groups, which could explain their contrasting WUE. Compared to the low‐WUE group, the high‐WUE group showed consistently lower values of the parameter m, which is inversely related to WUE. Differences related specifically to the dependence of gs on humidity and net photosynthesis rate were only found in 2010. The lower ratio between leaf‐internal and leaf‐external [CO2] and higher WUE of the high‐WUE group was consistent over a wide range of air vapour pressure deficits from 0.5 to 3.5 kPa. The mapping population was normally distributed with respect to WUE suggesting a multigenic nature of this trait. The WUE groups identified can be further employed for quantitative trait loci (QTL) analysis by use of gene expression studies or genome resequencing. The differences in population WUE indicate a genetic potential for improvement of this trait.

Response of stomatal conductance to light in tobacco plants

Stomata regulates key plant processes,inluding CO2 assimilation and water use.Although stomatal conductance models evaluate stomatal regulation by plant leaves,model fits have been often different from research and environmental factors.To compare the applicability of stomatal conductance models in tobacco plants,light-response curves of stomatal conductance were measured in this study.The field study was conducted under controlled CO2 concentration and temperature using the Li-6400 photosynthesis determination system.CO2 concentration was maintained at 390 μmol.mol 1 under different temperatures of 20 ℃,25 ℃,30 ℃ and 35 ℃.Stomatal conductance of tobacco across the temperature treatments were fitted with the Ball-Berry model(BB model) and subsequent refinements made by Leuning correction model(BBL model),as well as a mechanism model deduced by Ye Zipiao and Yu Qiang(BBY model).The fitting effects eventually compared.The stomatal conductance model and the emendatory light response model of net photosynthesis were coupled(coupling model) to study the light response characteristics of tobacco stomatal conductance.The results were compared with that from Jarvis model.The fitting results showed that compared with the BB and BBL models,the BBY model better described the relationship between stomatal conductance and net photosynthesis of tobacco across the temperature treatments.Both the coupling and Jarvis models well fitted the response of stomatal conductance to light.However,the fitting effects of the coupling model were better,which directly estimated the maximum stomatal conductance along with the corresponding saturation light intensity.Also the coupling model could be used to study the extent of synchronization of maximum stomatal conductance and net photosynthetic rate.The study showed no synchronization of maximum stomatal conductance and maximum net photosynthetic rate of tobacco across the temperature treatments.At 20 ℃,tobacco stomatal conductance reached the maximum value earlier than net photosynthetic rate.At other temperature treatments,however,tobacco stomatal conductance reached the maximum value later than net photosynthetic rate.

Comparing the performance of different stomatal conductance models using modelled and measured plant carbon isotope ratios (δ13C): implications for assessing physiological forcing

Accurate modelling of long-term changes in plant stomatal functioning is vital to global climate change studies because changes in evapotranspiration influence temperature via physiological forcing of the climate. Various stomatal models are included in land surface schemes, but their robustness over longer timescales is difficult to validate. We compare the performance of three stomatal models, varying in their degree of complexity, and coupled to a land surface model. This is carried out by simulating the carbon isotope ratio of tree leaves (δ(13) Cleaf ) over a period of 53years, and comparing the results with carbon isotope ratios obtained from tree rings (δ(13) Cstem ) measured at six sites in northern Europe. All three stomatal models fail to capture the observed interannual variability in the measured δ(13) Cstem time series. However, the Soil-Plant-Atmosphere (SPA) model performs significantly better than the Ball-Berry (BB) or COX models when tested for goodness-of-fit against measured δ(13) Cstem . The δ(13) Cleaf time series simulated using the SPA model are significantly positively correlated (P<0.05) with measured results over the full time period tested, at all six sites. The SPA model underestimates interannual variability measured in δ(13) Cstem , but is no worse than the BB model and significantly better than the COX model. The inability of current models to adequately replicate changes in stomatal response to rising levels of CO2 concentrations, and thus to quantify the associated physiological forcing, warrants further investigation.

Ozone exposure causes a decoupling of conductance and photosynthesis: implications for the Ball-Berry stomatal conductance model

Industrialization has significantly altered atmospheric chemistry by increasing concentrations of chemicals such as nitrogen oxides (NO( x )) and volatile organic carbon, which react in the presence of sunlight to produce tropospheric ozone (O(3)). Ozone is a powerful oxidant that causes both visual and physiological damage to plants, impairing the ability of the plant to control processes like photosynthesis and transpiration. Damage to photosynthesis and stomatal conductance does not always occur at the same rate, which generates a problem when using the Ball-Berry model to predict stomatal conductance because the calculations directly rely on photosynthesis rates. The goals of this work were to develop a modeling framework to modify Ball-Berry stomatal conductance predictions independently of photosynthesis and to test the framework using experimental data. After exposure to elevated O(3) in open-top chambers, photosynthesis and stomatal conductance in tulip poplar changed at different rates through time. We were able to accurately model observed photosynthetic and stomatal conductance responses to chronic O(3) exposure in a Ball-Berry framework by adjusting stomatal conductance in addition to photosynthesis. This led to a significant improvement in the modeled ability to predict both photosynthesis and stomatal conductance responses to O(3).

How well do stomatal conductance models perform on closing plant carbon budgets? A test using seedlings grown under current and elevated air temperatures

[1] Future carbon and water fluxes within terrestrial ecosystems will be determined by how stomatal conductance (gs) responds to rising atmospheric CO2 and air temperatures. While both short- and long-term CO2 effects on gs have been repeatedly studied, there are few studies on how gs acclimates to higher air temperatures. Six gs models were parameterized using leaf gas exchange data from black spruce (Picea mariana) seedlings grown from seed at ambient (22/16°C day/night) or elevated (30/24°C) air temperatures. Model performance was independently assessed by how well carbon gain from each model reproduced estimated carbon costs to close the seedlings’ seasonal carbon budgets, a ‘long-term’ indicator of success. A model holding a constant intercellular to ambient CO2 ratio and the Ball-Berry model (based on stomatal responses to relative humidity) could not close the carbon balance for either treatment, while the Jarvis-Oren model (based on stomatal responses to vapor pressure deficit, D) and a model assuming a constant gs each closed the carbon balance for one treatment. Two models, both based on gs responses to D, performed best overall, estimating carbon uptake within 10% of carbon costs for both treatments: the Leuning model and a linear optimization model that maximizes carbon gain per unit water loss. Since gs responses in the optimization model are not a priori assumed, this approach can be used in modeling land-atmosphere exchange of CO2 and water in future climates.

Modeling the impact of drought on canopy carbon and water fluxes for a subtropical evergreen coniferous plantation in southern China through parameter optimization using an ensemble Kalman filter

Abstract. Soil and atmospheric water deficits have significant influences on CO2 and energy exchanges between the atmosphere and terrestrial ecosystems. Model parameterization significantly affects the ability of a model to simulate carbon, water, and energy fluxes. In this study, an ensemble Kalman filter (EnKF) and observations of gross primary productivity (GPP) and latent heat (LE) fluxes were used to optimize model parameters significantly affecting the calculation of these fluxes for a subtropical coniferous plantation in southeastern China. The optimized parameters include the maximum carboxylation rate (Vcmax), the slope in the modified Ball-Berry model (M) and the coefficient determining the sensitivity of stomatal conductance to atmospheric water vapor deficit (D0). Optimized Vcmax and M showed larger variations than D0. Seasonal variations of Vcmax and M were more pronounced than the variations between the two years. Vcmax and M were associated with soil water content (SWC). During dry periods, SWC at the 20 cm depth explained 61% and 64% of variations of Vcmax and M, respectively. EnKF parameter optimization improved the simulations of GPP, LE and SH, mainly during dry periods. After parameter optimization using EnKF, the variations of GPP, LE and SH explained by the model increased by 1% to 4% at half-hourly steps and by 3% to 5% at daily time steps. Further efforts are needed to differentiate the real causes of parameter variations and improve the ability of models to describe the change of stomatal conductance with net photosynthesis rate and the sensitivity of photosynthesis capacity to soil water stress under different environmental conditions.

Diurnal and seasonal variations in stomatal conductance of rice at elevated atmospheric CO2under fully open-air conditions

Understanding of leaf stomatal responses to the atmospheric CO(2) concentration, [CO(2)], is essential for accurate prediction of plant water use under future climates. However, limited information is available for the diurnal and seasonal changes in stomatal conductance (g(s)) under elevated [CO(2)]. We examined the factors responsible for variations in g(s) under elevated [CO(2)] with three rice cultivars grown in an open-field environment under flooded conditions during two growing seasons (a total of 2140 individual measurements). Conductance of all cultivars was generally higher in the morning and around noon than in the afternoon, and elevated [CO(2)] decreased g(s) by up to 64% over the 2 years (significantly on 26 out of 38 measurement days), with a mean g(s) decrease of 23%. We plotted the g(s) variations against three parameters from the Ball-Berry model and two revised versions of the model, and all parameters explained the g(s) variations well at each [CO(2)] in the morning and around noon (R(2) > 0.68), but could not explain these variations in the afternoon (R(2) < 0.33). The present results provide an important basis for modelling future water use in rice production.