Jianlong Wang's research while affiliated with Northwest A & F University and other places

Global climate change is increasing the frequency and intensity of drought and salt stress worldwide, with profound impacts on tree growth and survival. However, the response of plant hydraulic transport and carbon balance to combined drought and salt stress remains unclear. This study investigated the leaf physiological traits, stem xylem hydraulic traits, and nonstructural carbohydrate concentration of Robinia pseudoacacia seedlings under normal irrigation treatment (CK, freshwater at 80–100% FC); salt stress treatment (SS, 0.3% soil salinity with freshwater); drought stress treatment (DS, withholding irrigation); and combined drought and salt treatments (SDS, 0.3% soil salinity withholding irrigation). Our results showed that the leaf physiological traits responded differently to different treatments. DS and SDS treatment significantly decreased leaf water potential and stomatal conductance, while SS treatment did not. DS treatment increased stomatal density but decreased stomatal area to adapt to water deficit, while SS and SDS treatment decreased stomatal length or width. In terms of xylem hydraulic traits, SS, DS and SDS significantly decreased xylem specific hydraulic conductivity by 47%, 42% and 49%, while percent loss of conductivity (PLC) significantly increased by 81% and 62% in DS and SDS, but the PLC of SS was not increased significantly. Additionally, net photosynthetic rate and transpiration rate significantly decreased in SS, DS and SDS, while leaf water use efficiency significantly increased. The chlorophyll content index and maximum light quantum efficiency of photosystem II were also decreased. For nonstructural carbohydrate, the soluble sugars, starch and total non-structural carbohydrate were significantly decreased in DS in specific tissues, showing reductions of 42%, 68%, and 56% in leaves, 69%, 61%, and 62% in stem, and 30%, 59%, and 57% in root. Our findings provide evidence that salt addition alleviated drought stress by improving hydraulic traits and carbohydrate reserves, which is expected to contribute to predicting future vegetation dynamics under climate change.

Precipitation isoscapes have provided supporting data for numerous studies of water stable isotopes, alleviating the lack of observation data. However, the applicability of simulation data from global models to specific regional contexts remains a subject requiring further investigation, particularly concerning d-excess—an aspect often overlooked by prediction models. To bridge this gap, this study evaluates the performance of three mainstream precipitation isoscapes (OIPC3.2, RCWIP1, and RCWIP2) for the prediction of average annual δ2H, δ18O, and d-excess based on observations from the CHNIP database. The results show that while all three models can accurately reproduce δ2H and δ18O values, none are able to accurately match d-excess values. This disparity can be attributed to the absence of water-vapor source information in the models’ input variables, a key determinant influencing d-excess outcomes. Additionally, it is noteworthy that OIPC3.2 stands out as the optimal choice for δ2H and δ18O estimations, while RCWIP2 exhibits progressive enhancements over RCWIP1 in d-excess estimations. This highlights the significance of selecting highly pluralistic information variables and recognizing the impact of error propagation in such models. As a result, the advancement of isoscapes in accurately and precisely depicting precipitation isotopes, particularly d-excess, necessitates further refinement. Future avenues for improvement might involve the incorporation of water-vapor source-clustering methodologies, the selection of information-rich variables, and the autonomous construction of a dedicated d-excess simulation. This research provides valuable insights for the further refining of isoscape modeling in the future.