Applicability of common stomatal conductance models in maize under varying soil moisture conditions

Divergent impacts of VPD and SWC on ecosystem carbon-water coupling under different dryness conditions

Ecosystem water use efficiency (WUE) is an indicator of carbon-water interactions and is defined as the ratio of gross primary productivity (GPP) to evapotranspiration (ET). However, it is currently unclear how WUE responds to atmospheric and soil drought events in terrestrial ecosystems with different dryness conditions. Additionally, the contributions of GPP and ET to the WUE response remain poorly understood. Based on measurements from 26 flux tower sites distributed worldwide, the binning method and random forest model were employed to separate the sensitivities of daily ecosystem WUE, GPP, and ET to vapor pressure deficit (VPD) and soil water content (SWC) under different dryness conditions (dryness index = potential evapotranspiration/precipitation, DI). Results showed that the sensitivity of WUE to VPD was negative at humid sites (DI < 1), while the sensitivity of WUE to SWC was positive at arid sites (DI > 2). Furthermore, the contribution of GPP to VPD-induced WUE variability was 63 % at humid sites, and the contribution of ET to SWC-induced WUE variability was 68 % when SWC was less than the 60th percentile at arid sites. Consequently, one increasing VPD-induced decrease in GPP was generally linked to a decrease in WUE at humid sites, and one drying soil moisture-caused decrease in ET was linked to a WUE increase under low SWC conditions at arid sites. Finally, VPD had a stronger effect on WUE than SWC when VPD was less than the 90th percentile or SWC was greater than the 50th percentile. Our findings underscore the importance of considering ecosystem dryness when investigating the impacts of VPD and SWC on ecosystem carbon-water coupling.

Salinity-specific stomatal conductance model parameters are reduced by stomatal saturation conductance and area via leaf nitrogen

Modeling stomatal behavior is necessary for accurate stomatal simulation and predicting the terrestrial water‑carbon cycle. Although the Ball-Berry and Medlyn stomatal conductance (g_s) models have been widely used, variations and the drivers of their key slope parameters (m and g₁) remain poorly understood under salinity stress. We measured leaf gas exchange, physiological and biochemical traits, soil water content and electrical conductivity of saturation extract (EC_e), and fitted slope parameters of two genotypes of maize growing in two water and two salinity levels. We found m was different between the genotypes, but no difference in g₁. Salinity stress reduced m and g₁, saturated stomatal conductance (g_sat), the fraction of leaf epidermis area allocation to stomata (f_s), and leaf nitrogen (N) content, and increased EC_e, but no marked decrease in slope parameters under drought. Both m and g₁ were positively correlated with g_sat, f_s, and leaf N content, and negatively correlated with EC_e in the same fashion among the two genotypes. Salinity stress altered m and g₁ by modulating g_sat and f_s via leaf N content. The prediction accuracy of g_s was improved using salinity-specific slope parameters, with root mean square error (RMSE) being decreased from 0.056 to 0.046 and 0.066 to 0.025 mol m^-2 s^-1 for the Ball-Berry and Medlyn models, respectively. This study provides a modeling approach to improving the simulation of stomatal conductance under salinity.

Dynamic Characteristics of Canopy and Vegetation Water Content during an Entire Maize Growing Season in Relation to Spectral-Based Indices

A variety of spectral vegetation indices (SVIs) have been constructed to monitor crop water stress. However, their abilities to reflect dynamic canopy water content (CWC) and vegetation water content (VWC) during the growing season have not been concurrently examined, and the underlying mechanisms remain unclear, especially in relation to soil drying. In this study, a field experiment was conducted and designed with various irrigation regimes applied during two consecutive growing seasons of maize. The results showed that CWC, VWC, and the SVIs exhibited obvious trends of first increasing and then decreasing within a growing season. In addition, VWC was allometrically related to CWC across the two growing seasons. A linear relationship between the five SVIs and CWC occurred within a certain CWC range (0.01–0.41 kg m−2), while the relationship between these SVIs and VWC was nonlinear. Furthermore, the five SVIs indicated critical values for VWC, and these values were 1.12 and 1.15 kg m−2 for the water index (WI) and normalized difference water index (NDWI), respectively; however, the normalized difference infrared index (NDII), normalized difference vegetation index (NDVI), and optimal soil-adjusted vegetation index (OSAVI) had the same critical value of 0.55 kg m−2. Therefore, in comparison to the NDII, NDVI, and OSAVI, the WI and NDWI better reflected the crop water content based on their sensitives to CWC and VWC. Moreover, CWC was the most important direct biotic driver of the dynamics of SVIs, while leaf area index (LAI) was the most important indirect biotic driver. VWC was a critical indirect regulator of WI, NDWI, NDII, and OSAVI dynamics, whereas vegetation dry mass (VDM) was the critical indirect regulator of NDVI dynamics. These findings may provide additional information for estimating agricultural drought and insights on the impact mechanism of soil water deficits on SVIs.

Assessment of effective LAI and water use efficiency using Eddy Covariance data

Globally, maize (Zea mays, a C4-plant) and alfalfa (Medicago sativa, a C3-plant) are common and economically important crops. Predicting the response of their water use efficiency, WUE, to changing hydrologic and climatic conditions is vital in helping farmers adapt to a changing climate. In this study, we assessed the effective leaf area index (eLAI - the leaf area most involved in CO₂ and H₂O exchange) and stomatal conductance in canopy scale in maize and alfalfa fields. In the process we used a theoretically-based photosynthesis C3-C4 model (C3C4PM) and carbon and water vapour fluxes measured by Eddy Covariance towers at our study sites. We found that in our study sites the eLAI was in the range of 25-32% of the observed total LAI in these crops. WUEs were in range of 8-9 mmol/mol. C3C4PM can be used in predictions of stomatal conductance and eLAI responses in C3 and C4 agricultural crops to elevated CO₂ concentration and changes in precipitation and temperature under future climate scenarios.

The Interrelationship Between Water Use Efficiency and Radiation Use Efficiency Under Progressive Soil Drying in Maize

The maximizing of water use efficiency (WUE) and radiation use efficiency (RUE) is vital to improving crop production in dryland farming systems. However, the fundamental question as to the association of WUE with RUE and its underlying mechanism under limited-water availability remains contentious. Here, a two-year field trial for maize designed with five progressive soil drying regimes applied at two different growth stages (three-leaf stage and seven-leaf stage) was conducted during the 2013-2014 growing seasons. Both environmental variables and maize growth traits at the leaf and canopy levels were measured during the soil drying process. The results showed that leaf WUE increased with irrigation reduction at the early stage, while it decreased with irrigation reduction at the later stage. Leaf RUE thoroughly decreased with irrigation reduction during the progressive soil drying process. Aboveground biomass (AGB), leaf area index (LAI), a fraction of absorbed photosynthetically active radiation (fAPAR), and light extinction coefficient (k) of the maize canopy were significantly decreased by water deficits regardless of the growth stages when soil drying applied. The interrelationships between WUE and RUE were linear across the leaf and canopy scales under different soil drying patterns. Specifically, a positive linear relationship between WUE and RUE are unexpectedly found when soil drying was applied at the three-leaf stage, while it turned out to be negative when soil drying was applied at the seven-leaf stage. Moreover, the interaction between canopy WUE and RUE was more regulated by fAPAR than LAI under soil drying. Our findings suggest that more attention must be paid to fAPAR in evaluating the effect of drought on crops and may bring new insights into the interrelationships of water and radiation use processes in dryland agricultural ecosystems.

A canopy conductance model with temporal physiological and environmental factors

Canopy conductance, one of the key variables in simulating evapotranspiration, is strongly influenced by the physiological status of a plant and environmental factors, including photosynthetically active radiation, vapor pressure deficit, air temperature, soil moisture and so on. However, the restrictive functions used to represent these factors rarely consider the dynamics of physiological and environmental factors. This study proposed an improved canopy conductance model by regarding radiation and vapor pressure deficit as the two main influencing factors, quantifying the temporal variation in stomatal responses to radiation that notably adjust stomatal behavior, parameterizing maximum stomatal conductance with plant type-specific functions and proposing a new restrictive function for the VPD. The improved canopy conductance model was incorporated in a surface conductance model for estimating surface conductance and evapotranspiration at 8 flux stations at the Heihe River Basin and the Haihe River Basin. The estimated results were the most accurate when comparing to two other models. Furthermore, the model performance was acceptable when most of the parameters were assumed to be constant across the sites except the reference canopy conductance G_{c, ref} and the soil evaporation parameter α_s, which suggests that the improved canopy conductance model could be used as a parsimony model for improving canopy conductance predictions and water use efficiency over typical climate zones and underlying surface types in North of China.

A process-based coupled model of stomatal conductance-photosynthesis-transpiration during leaf ontogeny for water-saving irrigated rice

Process-based coupled model of stomatal conductance-photosynthesis-transpiration was developed to estimate simultaneously stomatal conductance g_sw, photosynthetic rate P_n, and transpiration rate T_r during leaf ontogeny. The modified Jarvis model was constructed by superposing the influence of leaf age LA on g_sw in traditional Jarvis model. And the modified Farquhar model was constructed by incorporating the relationships of the LA with parameters in Farquhar model into traditional Farquhar model. The average and leaf-age-based coupled models were constructed, respectively, by combining traditional Farquhar and Penman-Monteith models with traditional Jarvis, and combining modified Farquhar and Penman-Monteith models with modified Jarvis. The results showed that the g_sw, the maximum rate of carboxylation, maximum rate of electron transport, rate of triose phosphates utilization, and mitochondrial respiration rate varied in a positive skew pattern, while the mesophyll diffusion conductance decreased linearly with increase in LA. The average coupled model underestimated g_sw, P_n, and T_r for young leaves and overestimated g_sw, P_n, and T_r for old leaves. And the leaf-age-based coupled model generally perfected well in estimating g_sw, P_n, and T_r for all leaves during leaf ontogeny. The study will provide basic information for either modeling leaf g_sw, P_n, and T_r continuously, or upscaling them from leaf to canopy scale by considering the variation of LA within canopy.

Hyperspectral and Thermal Sensing of Stomatal Conductance, Transpiration, and Photosynthesis for Soybean and Maize under Drought

During water stress, crops undertake adjustments in functional, structural, and biochemical traits. Hyperspectral data and machine learning techniques (PLS-R) can be used to assess water stress responses in plant physiology. In this study, we investigated the potential of hyperspectral optical (VNIR) measurements supplemented with thermal remote sensing and canopy height (hc) to detect changes in leaf physiology of soybean (C3) and maize (C4) plants under three levels of soil moisture in controlled environmental conditions. We measured canopy evapotranspiration (ET), leaf transpiration (Tr), leaf stomatal conductance (gs), leaf photosynthesis (A), leaf chlorophyll content and morphological properties (hc and LAI), as well as vegetation cover reflectance and radiometric temperature (TL,Rad). Our results showed that water stress caused significant ET decreases in both crops. This reduction was linked to tighter stomatal control for soybean plants, whereas LAI changes were the primary control on maize ET. Spectral vegetation indices (VIs) and TL,Rad were able to track these different responses to drought, but only after controlling for confounding changes in phenology. PLS-R modeling of gs, Tr, and A using hyperspectral data was more accurate when pooling data from both crops together rather than individually. Nonetheless, separated PLS-R crop models are useful to identify the most relevant variables in each crop such as TL,Rad for soybean and hc for maize under our experimental conditions. Interestingly, the most important spectral bands sensitive to drought, derived from PLS-R analysis, were not exactly centered at the same wavelengths of the studied VIs sensitive to drought, highlighting the benefit of having contiguous narrow spectral bands to predict leaf physiology and suggesting different wavelength combinations based on crop type. Our results are only a first but a promising step towards larger scale remote sensing applications (e.g., airborne and satellite). PLS-R estimates of leaf physiology could help to parameterize canopy level GPP or ET models and to identify different photosynthetic paths or the degree of stomatal closure in response to drought.