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• Answered the question of " Whether the ecological benefits will continue to improve as usual under the background of continuous ecological water convey?" • Answered the question of " How wide is the impact of ecological water convey on groundwater and the vegetation in riparian zone?" • Answered the question of " Where ecological water has been consumed at different times?" In arid regions, ecological water replenishment benefits in desert riparian forests are typically evaluated by assessing changes in hydrology (water area and groundwater depth) and vegetation growth before and after it is implemented. While continuous ecological water delivery may enhance ecological benefits, its trajectory remains uncertain. Under the backdrop of ongoing ecological water delivery, this study examines whether ecological benefits continue to improve and identifies strategies for optimal control and efficient utilization of ecological water. Based on an analysis of groundwater level changes and vegetation changes during early, middle, and late stages of ecological water conveyance in the Tarim River, China (2000–2021), ecological water consumption distribution was revealed. A notable observation is that a wide eco-water conveyance did not significantly impact forest growth indicators, such as tree ring density, crown width, and tree ring size, in Populus euphratica trees. Compared to a century ago, there were significant variations in the growth of P. euphratica tree rings over the 20-year ecological water transfer period. The vegetation coverage on riverbanks increased significantly in the early to mid-stages of ecological water conveyance (2000–2015), but then plateaued in the subsequent years (post-2015). There was a significant upward trend in plant diversity on riverbanks and tail lakes during the early stage (2000–2006), but it declined sharply thereafter (post-2006). A recommendation includes constraining the tail lake's water area and using ecological sluice gates and levees to disperse eco-water away from the river to enhance the efficiency of ecological water utilization. As a result of these findings, rational management systems can be developed in similar arid environments. [ABSTRACT FROM AUTHOR]

Reservoirs play important roles in the drinking water supply for urban residents, agricultural water provision, and the maintenance of ecosystem health. Satellite optical remote sensing of water quality variables in medium and micro-sized inland waters under oligotrophic and mesotrophic status is challenging in terms of the spatio-temporal resolution, weather conditions and frequent nutrient status changes in reservoirs, etc., especially when quantifying non-optically active components (non-OACs). This study was based on the surface reflectance products of unmanned aerial vehicle (UAV) multispectral images, Sentinel-2B Multispectral instrument (MSI) images and Landsat 7 Enhanced Thematic Mapper Plus (ETM+) by utilizing fuzzy C-means (FCM) clustering algorithm was combined with band combination (BC) model to construct the FCM-BC empirical model, and used mixed density network (MDN), extreme gradient boosting (XGBoost), deep neural network (DNN) and support vector regression (SVR) machine learning (ML) models to invert 12 kinds of optically active components (OACs) and non-OACs. Compared with the unclustered BC (UC) model, the mean coefficient of determination (MR) of the FCM-BC models was improved by at least 46.9%. MDN model showed best accuracy (R2 in the range of 0.60–0.98) and stability (R2 decreased by up to 13.2%). The accuracy of UAV was relatively higher in both empirical methods and machine learning methods. Additionally, the spatio-temporal distribution maps of four water quality variables were mapped based on the MDN model and UAV images, all platforms showed good consistency. An inversion strategy of water quality variables in various monitoring frequencies and weather conditions were proposed finally. The purpose of introducing the UAV platform was to cooperate with the satellite to improve the monitoring response ability of OACs and non-OACs in small and micro-sized oligotrophic and mesotrophic water bodies. [Display omitted] • Estimation of optically inactive and non-optically inactive components. • Clustering algorithm effectively improved the accuracy of the empirical models. • The mixture density network model had the best regression results. • Spatial distribution of four water quality variables map was generated. [ABSTRACT FROM AUTHOR]

Studies on the interactions between urban landscape patterns and land surface temperatures are the key to urban heat island (UHI) mitigation. However, the landscape pattern indices used in previous studies were inconsistent in type and number. Furthermore, few studies combined the composition and configuration indices into one integrated indicator. The description of landscape pattern is thus a great yet rewarding challenge. In this study, we used the integrated location weighted landscape index (LWLI) proposed by Chen et al. (2009) and revised it to indicate potential UHIs. Fifty-six circular landscape samples along four transects were created and the LWLI was derived based on the theory of the GINI index. The LWLI considers the type, composition and configuration of different land covers inside a landscape, where configuration is treated as location weights. The potential UHI was represented by the land surface temperature (LST) of each circle landscape center. The correlation analysis results showed that the LWLI was significantly positively correlated with summer potential UHIs, with a Pearson R equaling 0.736, and barely correlated with winter potential UHI. Moreover, the LWLI was slightly more strongly correlated with potential UHI than composition alone. These correlations weakened as the landscapes grew larger. The linear regression results further revealed that the LWLI explained about 53% of the summer potential UHI, which was slightly better than composition alone (49%). This indicated that the LWLI was as effective in predicting the potential UHI as the combination of several pattern indicators, echoing Tobler’s first law of geography, which states that “all things are related, but nearby things are more related than distant things.” This study also leaves room for improvement of the index by integrating more environmental/ecological parameters as weights, and for further application of the index in other fields. [ABSTRACT FROM AUTHOR]

Abstract: Fertilization (CK, N, P, K, NP, NK, PK, NPK) and watering (CK, rain, snow) were applied to a desert grassland of northwest Xinjiang, China. Results showed that: (1) After nutrient and water additions for one year, the plant community structure changed, the individual number of Graminoids increased significantly, while the individual number of Cruciferaes decreased sharply. The total species number was 16 before the treatment and 10 after the treatment, reduced by 37.5%. (2) The vegetation coverage above ground and the plant density increased significantly under the additions of NP and NPK (p < 0.05), while the other nutrient additions had no significant effects on the vegetation coverage and density. Neither additional snow addition nor rain had significant effects. (3) Compared with the control (CK), the additions of N, P and PK increased the diversity indexes (D &H′) and Evenness (J); the additions of K, NP, NK and NPK decreased the diversity indexes (D &H′) and evenness (J). However, neither of the treatments has significant effect on the diversity indexes and Evenness based on the ANOVA (p < 0.05). (4) Snow significantly decreased the plant species richness (p < 0.05). However, neither the rain nor the nutrient addition has significant effect on the species richness. (5) The inter-annual variation trend of the diversity indexes (D &H′) and Evenness (J) showed an increasing trend during 2009–2012. [Copyright &y& Elsevier]

Abstract: A receptor affinity chromatographic selection method was developed for screening the bioactive compounds binding to β 2-adrenoceptor (β 2-AR) in Coptidis rhizome. The bioactive compounds were analyzed by molecular recognition with a β 2-AR affinity column. The retention compounds eluted from the β 2-AR column were separated online with reverse-phase high-performance liquid chromatography by column switching technology, and identified by a coupled ion-trap mass spectrometer. Four compounds were screened as the bioactive compounds of Coptidis rhizome and identified as 2,9,10-trimethoxy-3-hydroxyl-protoberberine (jateorhizine), 2,3-methylenedioxy-9-methoxy-protoberberine, 2,3,9,10-tetramethoxy-protoberberine (palmatine) and 2,3-methylenedioxy-9,10-dimethoxy-protoberberine (berberine). The association constants of jatrorrhizine, palmatine and berberine to the β 2-AR were determined by the zonal elution method with standards. Berberine and palmatine had only one type of binding site on the immobilized β 2-AR. Their association constants were (2.28±0.11)×104/M and (3.00±0.10)×104/M, respectively. Jatrorrhizine had at least two type of binding sites on the immobilized β 2-AR, and the corresponding association constants were (2.20±0.09)×10−4/M and (6.78±0.001)×105/M. [Copyright &y& Elsevier]

Abstract: Investigation of the interaction between drugs and receptors is very important in revealing the biologic basis and mechanism of the drug, and designing new bioactive compounds. The β 2-adrenoceptor (β 2-AR) was purified from rabbit lung tissues and immobilized on the surface of macro-pore silica gel through covalent bonds to prepare the stationary phase. Binding isotherms of terbutaline and salbutamol were determined by frontal analysis and the perturbation method, respectively. On the basis of the model of binding isotherm assumed, zonal elution was used to investigate the binding interaction of the receptor with terbutaline and salbutamol. The two drugs had one type of common binding site on immobilized β 2-AR. Salbutamol had at least one other major binding region. The association constant for terbutaline was (9.76±0.67)×104/M, and the concentration of the binding sites was (9.37±1.32)×10−6 M. Under identical conditions, association constants for salbutamol at the two types of binding site were (1.11±0.08)×104/M and (1.34±0.13)×103/M, and the concentration of the binding sites was (5.46±0.35)×10−6 M. Entropy increase was the main driving force for terbutaline and salbutamol to bind with β 2-AR. The associating reaction of terbutaline and β 2-AR was an exothermal process primarily from electrostatic interactions; hydrophobic force was the major factor contributing to the process for salbutamol. [Copyright &y& Elsevier]