Search

The depth‐wise distribution of root water uptake is typically inferred through linear mixing models that utilize knowledge of stable water isotopes in soil and plants. However, these existing models often represent the water uptake profile in discrete segments, potentially introducing significant uncertainty and bias into results. In this study, we introduced a novel root water uptake mixing model that combines a Bayesian linear mixing framework with a continuous root water uptake pattern, named CrisPy. To evaluate the performance of CrisPy, we conducted virtual and field‐based tests under several types of prior information. CrisPy showed accurate and robust reconstruction of the true root water uptake profile under various prior information settings in the virtual test. By contrast, the discrete mixing model, MixSIAR was greatly influenced by the prior information and deviated from the true profile. The root mean squared error of the uptake proportions from CrisPy ranged from 3.6% to 7.4%, while MixSIAR exhibited values of 6.3%–15.2%. Furthermore, posterior predictive checking indicated that CrisPy effectively reconstructed the mean and standard deviations of plant water isotopic compositions in both virtual and field‐based tests. MixSIAR, however, underestimated the mean and overestimated the standard deviation of these compositions. These findings collectively support the enhanced accuracy, greater robustness, and reduced uncertainty of CrisPy in comparison to MixSIAR. Therefore, CrisPy provides a powerful tool for partitioning plant water sources. Plain Language Summary: Root water uptake mixing models are essential to study root water uptake patterns. MixSIAR is widely used for this purpose but it requires soil segmentation, which results in limited accuracy and spatial resolution of the root water uptake patterns. In this study, we introduced a novel model named CrisPy. It describes root water uptake in a continuous pattern, instead of dividing the soil profile into segments. The virtual and field tests illustrated CrisPy had fewer errors associated with root water uptake profiles than MixSIAR. Moreover, CrisPy generated plant water isotopic distributions that are closer to observations than that from MixSIAR. These differences illustrate that CrisPy is more accurate than MixSIAR. Key Points: A continuous root water uptake isotope mixing model, named CrisPy, was developedCrisPy is less sensitive to the prior information and more accurate than MixSIARCrisPy is a robust and open‐source tool for plant water partitioning [ABSTRACT FROM AUTHOR]

Compared to traditional biochar (BC), nano-biochar (NBC) boasts superior physicochemical properties, promising extensive applications in agriculture, ecological environments, and beyond. Due to its strong adsorption and migration properties, NBC may carry nutrients or pollutants to deeper soil layers or even groundwater, causing serious environmental risks. Nevertheless, the migration rules and mechanisms of NBC in soil are still unclear. Therefore, this study employed soil column migration experiments to systematically explore the migration rules and mechanisms of NBC under various flow rates, initial soil water contents, soil depths, and soil textures. The results showed that regulated by smaller particle size differences and greater surface charges, NBC exhibited a stronger migration ability compared with traditional BC. As the soil texture transitioned from fine to coarse, the migration capability of NBC significantly improved, driven by both pore structure and interaction forces as described by the DLVO theory. The migration ability of NBC was also greatly boosted as the soil transitioned from saturated to unsaturated conditions, primarily because of preferential flow. When the flow rate increased from 70% KS to 100% KS and 130% KS, the migration ability of NBC also increased accordingly, as changes in injection flow rates altered the velocity distribution of pore water. NBC in 25 cm soil columns was more prone to shallow retention compared with 10 cm soil columns, resulting in weaker overall migration ability. In addition, through fitting of the two-site kinetic model and related parameters, the penetration curves of NBC under various variable conditions were effectively characterized. These findings could offer valuable insights for NBC's future efficient, rational, and sustainable utilization, facilitating the evaluation and mitigation of its potential environmental risks. [ABSTRACT FROM AUTHOR]

Partitioning soil water balance (SWB) is an effective approach for deciphering the impacts of vegetation change on soil hydrological processes. Growing apple trees on the Loess Plateau, China, leads to a substantial deep soil water deficit, posing a serious threat to the sustainable development of apple production. However, the impact of deep-rooted apple trees on SWB remains poorly understood. In this study, we conducted a "Paired Plot" experiment to achieve this objective by decoupling SWB components using water stable isotopes, tritium, and soil water contents from deep soil cores (up to 25 m) under apple orchards with a stand age gradient of 8–23 years. The results showed that deep soil water storage under apple orchards was notably reduced compared to nearby farmland, showing a stand age-related pattern of deep soil water deficit (R2 = 0.91). By analyzing the changing patterns of SWB components, we found that the main factor driving this deficit is the water uptake process controlled by the deep root system. This process is triggered by the increased transpiration demand of apple trees and short-term water scarcity. These findings have implications for understanding soil water dynamics, sustainable agroforestry management, and soil water resources' protection in this region and other similar water-limited areas. [ABSTRACT FROM AUTHOR]

Nanobiochar exhibits promising applications across a spectrum of fields due to its exceptional physicochemical properties. Ball milling, a prominent nanobiochar synthesis method, is influenced by process factors and biochar pretreatments, yet dominant controls still remain uncertain. In this study, the apple branch bulk biochar (pyrolyzed under 350 ∘ C) was ball milled under different milling speeds, ball-to-powder mass ratios, and milling durations to investigate the optimal process parameter combinations for ball milling method. Then, we evaluated the impact of pyrolysis temperature and pretreatment temperature of bulk biochar on ball milling effect using optimized parameter combinations. Subsequently, the physicochemical properties of the bulk biochar and nanobiochar were measured. The results showed that high speed with low ball-to-powder mass ratio, low speed with high ball-to-powder mass ratio, and high pyrolysis temperature could significantly decrease the particle sizes of nanobiochar. Ball milling duration and pretreatment temperature had no significant effect on the particle sizes of biochar. The optimal combination of the rotational speed, ball-to-powder mass ratio and milling duration was 400 RPM, 100:1, 2 h and 700 RPM, 20:1, 2 h. The bulk biochar pyrolyzed at 550 ∘ C could be milled into biochar nanoparticles with an average particle size smaller than 100 nm via above parameters. Nanobiochar shows improved properties such as specific surface area, cation exchange capacity, and surface functional groups over bulk biochar. This study provides a scientific basis for the widespread application of ball milling in the field of preparing nanobiochar. We successfully synthesized biochar nanoparticles from apple branches by optimizing key parameters in the ball milling process, including biochar pyrolysis temperature, milling speed, duration, and ball-to-powder ratio. The resulting biochar nanoparticles exhibited significantly enhanced physicochemical properties, such as increased specific surface area, cation exchange capacity, and surface functional groups, in comparison to the native biochar. This study provides a scientific basis for the widespread application of ball milling in the field of preparing nano-biochar. [ABSTRACT FROM AUTHOR]

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. [ABSTRACT FROM AUTHOR]