Sustainable irrigation based on co-regulation of soil water supply and atmospheric evaporative demand.

Irrigation is an important adaptation to reduce crop yield loss due to water stress from both soil water deficit (low soil moisture) and atmospheric aridity (high vapor pressure deficit, VPD). Traditionally, irrigation has primarily focused on soil water deficit. Observational evidence demonstrates that stomatal conductance is co-regulated by soil moisture and VPD from water supply and demand aspects. Here we use a validated hydraulically-driven ecosystem model to reproduce the co-regulation pattern. Specifically, we propose a plant-centric irrigation scheme considering water supply-demand dynamics (SDD), and compare it with soil-moisture-based irrigation scheme (management allowable depletion, MAD) for continuous maize cropping systems in Nebraska, United States. We find that, under current climate conditions, the plant-centric SDD irrigation scheme combining soil moisture and VPD, could significantly reduce irrigation water use (-24.0%) while maintaining crop yields, and increase economic profits (+11.2%) and irrigation water productivity (+25.2%) compared with MAD, thus SDD could significantly improve water sustainability.

Seasonal responses of photosynthetic parameters in maize and sunflower and their relationship with leaf functional traits.

Estimates of seasonal variation in photosynthetic capacity (Pc ) are critical for modeling the time course of carbon fluxes. Given the time-intensive nature of calculating Pc parameters via gas exchange, it is appealing to calculate parameter variation via changes in chlorophyll (Chl) and nitrogen (N) content by assuming that Pc scales with these variables. Although seasonal changes in Pc and the relationships between N and Pc have been evaluated in forest canopies, there is limited data on seasonal parameter values in crops, nor is it clear if seasonal changes in Pc can be estimated from leaf traits under the high N fertility of managed systems. We characterized the seasonal variability of the maximum rates of carboxylation (Vcmax ) and electron transport (Jmax ) under well-fertilized conditions for maize (Zea mays L.) and sunflower (Helianthus annuus L.) and coupled these data with measurements of Chl, N, and leaf mass per unit area (LMA). The seasonal Chl-N relationship was significant in maize, but not in sunflower. Area-based N-Vcmax relationships were not significant for either crop. Mass-based N-Vcmax relationships were weak in sunflower, but highly significant in maize. Our results suggest that Pc can be seasonally adjusted in maize with reliable estimates of changes in LMA.

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.