Time lag characteristics of sap flow in seed-maize and their implications for modeling transpiration in an arid region of Northwest China

Abstract

Plant capacity for water storage leads to time lags between basal stem sap flow and transpiration in various woody plants. Internal water storage depends on the sizes of woody plants. However, the changes and its influencing factors in time lags of basal stem flow during the development of herbaceous plants including crops remain unclear. A field experiment was conducted in an arid region of Northwest China to examine the time lag characteristics of sap flow in seed-maize and to calibrate the transpiration modeling. Cross-correlation analysis was used to estimate the time lags between stem sap flow and meteorological driving factors including solar radiation (Rs) and vapor pressure deficit of the air (VPDair). Results indicate that the changes in seed-maize stem sap flow consistently lagged behind the changes in Rs and preceded the changes in VPDair both on hourly and daily scales, suggesting that light-mediated stomatal closures drove sap flow responses. The time lag in the maize's sap flow differed significantly during different growth stages and the difference was potentially due to developmental changes in capacitance tissue and/or xylem during ontogenesis. The time lags between stem sap flow and Rs in both female plants and male plants corresponded to plant use of stored water and were independent of total plant water use. Time lags of sap flow were always longer in male plants than in female plants. Theoretically, dry soil may decrease the speed by which sap flow adjusts ahead of shifts in VPDair in comparison with wet soil and also increase the speed by which sap flow adjusts to Rs. However, sap flow lags that were associated with Rs before irrigation and after irrigation in female plants did not shift. Time series analysis method provided better results for simulating seed-maize sap flow with advantages of allowing for fewer variables to be included. This approach would be helpful in improving the accuracy of estimation for canopy transpiration and conductance using meteorological measurements.

Transpiration Dynamics in Co-Located Maize, Sorghum, and Soybean Closed Canopies and Their Environmental Controls

“…Among the three radiative energy variables included in this research (R s , R n , PAR), we found that PAR had the maximum correlation with T LAI -1 across all crops, which was substantially greater than R s and R n (table 2). In the literature, maize transpiration has been shown to be driven by R s (Bo et al, 2017;Rousseaux et al, 2009), but PAR showed the most energy driving effect. PAR represents the visible portion (400-700 nm) electromagnetic spectrum that is useful for plant growth and development and thus is a better predictor of T LAI -1 than R s .…”

Time-Lag Effect Between Sap Flow and Environmental Factors of Larix principis-rupprechtii Mayr

“…Prior studies have noted the importance of both soil moisture and meteorological demands in controlling time lags [22,40,41]. However, most studies in the field have only focused on the influence of VPD on time lags while neglecting the effects of comprehensive meteorological factors, such as ET ref , that directly reflect evapotranspiration demand.…”

“…For instance, Zeppel et al [22] pointed out that declines in soil moisture along with declines in soil-root conductance could lead to larger hysteresis on drier days; however, Wullschleger et al [23] reported that hysteresis was more evident in wet soils. Bo et al [41] noted that the effects of dry soil on lag times in sap flow may not be straightforward since the soil moisture deficit generally affects plant stem flow at different temporal scales than the main environmental factors of stem flow. Zhang et al [12] noted that the shape of the hysteresis loop was primarily controlled by the time lag between radiation and VPD at high soil moisture levels and that the soil moisture content affected J s -VPD hysteresis under water stress, which was defined as θ < 0.175.…”

Improvement of reference evapotranspiration by considering time lag effect in back propagation neural network model

“…In addition, many papers have reported the existence of periodic and seasonal delays between evapotranspiration and meteorological factors. Bo studied the time-lag characteristics of seed-maize liquid flow and believed that the time-lag of maize liquid flow was significantly different in different growth stages [28] .…”