Search

China's National Key Ecological Function Zones (NKEFZs) currently represent the largest and most extensive ecological conservation policy in China, with one of the core objectives of this policy being to improve eco-environmental quality (EEQ). This study regards the establishment of NKEFZs as a quasi-natural experiment. Based on panel data from 130 counties in Sichuan Province from 2001 to 2021, a multi-period difference-in-differences (DID) model was employed to evaluate the impact of NKEFZ establishment on EEQ. The findings indicate the following: ① The establishment of NKEFZs can significantly enhance the EEQ of the covered areas, albeit as a gradual long-term process. This conclusion not only meets the parallel-trends assumption but also holds true in a series of robustness tests such as placebo tests. ② Mechanism analysis reveals that NKEFZs can enhance EEQ through the effects of optimizing land spatial allocation and upgrading industrial structure. ③ Heterogeneity analysis demonstrates that the beneficial effect of NKEFZs on EEQ varies across different functional zone types, geographic spaces and ethnic regions. Our study not only contributes to the accumulation of empirical evidence and institutional refinement in the sustainable implementation of ecological policies in China but also offers valuable insights and references for other countries in formulating policies for eco-environmental protection. [ABSTRACT FROM AUTHOR]

Scientific assessment of the coupled coordination degree between urbanization and food security (CDUFS) revealed regional differences and sources. Dynamic evolution and trends are important references for achieving a coordinated interaction between high-quality urbanization and ensuring food security. Specifically, the CDUFS was measured using prefectural panel data in China from 2000 to 2019 and the coupling coordination degree model, which revealed its spatial correlation and differentiation. On this basis, in order to examine the spatiotemporal differences and evolution of the CDUFS, the Dagum–Gini coefficient and Kernel density estimation were innovatively used to analyze its regional differences and evolution distribution. The spatial Markov chain was further employed to examine the evolution trend of the CDUFS. The study found that the CDUFS showed a downward trend in fluctuation within the low coordination interval. There was a positive spatial correlation, with a more stable distribution pattern of high–high and low–low clusters. The regional differences in the CDUFS were obvious and the overall difference has expanded. The main source of regional differences among different food functional areas was inter-regional differences, followed by intra-regional differences. The regional difference between food main producing areas and food main marketing areas was the highest. The CDUFS shows a single-peak distribution; the imbalance between regions was still prominent with a left trailing phenomenon and no convergence. The CDUFS has the stability of maintaining the original state, and the probability of leapfrogging evolution is low in the short term. Finally, the geospatial effect plays an important role in the dynamic evolution of the CDUFS. [ABSTRACT FROM AUTHOR]

Heavy metal pollution in soil is threatening the ecological environment and human health. However, field measurement of heavy metal content in soil entails significant costs. Therefore, this study explores the estimation method of soil heavy metals based on remote sensing images and machine learning. To accurately estimate the heavy metal content, we propose a hybrid artificial intelligence model integrating least absolute shrinkage and selection operator (LASSO), genetic algorithm (GA) and error back propagation neural network (BPNN), namely the LASSO-GA-BPNN model. Meanwhile, this study compares the accuracy of the LASSO-GA-BPNN model, SVR (Support Vector Regression), RF (Random Forest) and spatial interpolation methods with Huanghua city as an example. Furthermore, the study uses the LASSO-GA-BPNN model to estimate the content of eight heavy metals (including Ni, Pb, Cr, Hg, Cd, As, Cu, and Zn) in Huanghua and visualize the results in high resolution. In addition, we calculate the Nemerow index based on the estimation results. The results denote that, the simultaneous optimization of BPNN by LASSO and GA can greatly improve the estimation accuracy and generalization ability. The LASSO-GA-BPNN model is a more accurate model for the estimate heavy metal content in soil compared to SVR, RF and spatial interpolation. Moreover, the comprehensive pollution level in Huanghua is mainly low pollution. The overall spatial distribution law of each heavy metal content is very similar, and the local spatial distribution of each heavy metal is different. The results are of great significance for soil pollution estimation. [ABSTRACT FROM AUTHOR]

The Forestry Ecological Restoration Program (FERP) aims to restore the world's degraded forest landscapes to restore biodiversity and mitigate climate change. Scientific evaluation of eco-efficiency of forestry restoration programs (EEoFERPs) is the basis for developing and implementing inclusive and sustainable development policy measures. We take the world's largest FERP—China's Sloping Land Conversion Program (SLCP)—as an example. Using 314 county-level panel data in the Loess Plateau, the core area for the implementation of the SLCP, during 2002–2015, this study aims to evaluate the eco-efficiency of the Sloping Land Conversion Program (EEoSLCP) based on a DEA model and to measure the eco-efficiency dynamic changes through a Malmquist index model. The results show that: (1) The overall EEoSLCP of the Loess Plateau is at a low level, with an average efficiency of only 0.357 from 2002 to 2015. EEoSLCP is on an overall upward trend, mainly influenced by technical efficiency. (2) There are significant spatial differences in EEoSLCP among counties on the Loess Plateau, with an overall decreasing distribution trend from south to north and from southeast to northwest. (3) The Malmquist index of the EEoSLCP grew at an average annual rate of 17.7%, with technical efficiency changes being the most important factor driving its growth. Our results suggest that in the future, when implementing or designing FERPs, it is necessary not only to select the appropriate restoration plan precisely while respecting the laws of nature, but also to improve the management and technical level of FERPs accordingly. [ABSTRACT FROM AUTHOR]

The flow and reallocation of agricultural production factors induced by urbanization play an important role in the changes of the grain production pattern (GPP). Using provincial panel data from 1996 to 2018 in China as the research sample, the center of gravity transfer–standard deviation ellipse model was applied to understand the change characteristics of GPP. Next, a dynamic spatial panel econometric model was established to test the impact of urbanization on GPP, and a spatial mediated effect model was used to identify the mediated transmission paths played by cropland utilization, planting structure adjustment, and agricultural technology progress in this impact process. The main conclusions showed that (1) the grain production COG of China transferred to the northeast, gradually resulting in a spatial pattern from the northeast to the southwest; (2) the urbanization process has a significant negative impact on the GPP, with each unit increase in urbanization resulting in a 0.30% decrease in the grain production concentration index; (3) cropland utilization, planting structural adjustment, and agricultural technology progress play significant mediating roles in the impact of urbanization on the GPP, and their mediating effects can weaken the direct negative impact of urbanization, among which the mediating effect of planting structure adjustment is the highest (13.9%). The study findings provide a new perspective for further understanding the relationship between urbanization and grain production pattern and also provide theoretical references and practical insights for improving the allocation efficiency of agricultural production factors and formulating scientific regional planning policies for grain production in the high-quality transformation of urbanization. [ABSTRACT FROM AUTHOR]

China has witnessed accelerated urbanization since the reforms and open policies which began in 1978. This eventually resulted in increased residential water requirements and worsening water shortages, particularly in the current century. In the context of resource and environmental constraints, improving agricultural water use efficiency (AWUE) is a crucial issue to ensure food security, improve the ecological environment, and meet the needs of sustainable agricultural development. Based on the panel data of 30 provinces in China from 1999 to 2018, the article uses the Super-SBM model to measure the AWUE. Moreover, the study uses the entropy method to establish the urbanization evaluation index system from the dimensions of population, land, economy, measures the comprehensive level of urbanization development, and further constructs a dynamic spatial econometric model. We use the unconditional maximum likelihood estimation method to evaluate the impact of urbanization development on AWUE and its heterogeneity. The findings reveal that the AWUE considering undesired outcomes has generally shown a steady improvement, but there is ample space for resource conservation and environmental protection, and there are noticeable differences among regions. The decomposition of spatial effects shows that urbanization development in each region has a short-term positive effect on AWUE in the region and neighboring regions, and a long-term effect exists only in the western region. The impact of urbanization in different dimensions has been found that both land urbanization and economic urbanization contribute to the improvement of AWUE, while population urbanization helps to improve AWUE by improving the awareness level of the farmers. [ABSTRACT FROM AUTHOR]

Climate change and farmland environmental pollution have put greater pressure on the sustainability of agricultural production. Based on the provincial panel data of mainland China from 1978 to 2018, climate variables such as precipitation, temperature, and sunshine hours are included into the input indicators, and agricultural non-point source pollution and carbon emissions are taken as undesirable outputs, the agricultural production efficiency (APE) under the dual constraints of climate change and the resource environment was estimated by the super slacks-based measure (SBM)-undesirable model. On the basis of the trajectory of the imbalanced spatiotemporal evolution of APE shown by Kernel density estimation and the standard deviational ellipse (SDE)–center of gravity (COG) transfer model, the spatial convergence model was used to test the convergence and differentiation characteristics of APE. Under the dual constraints, APE presents a "bimodal" distribution with a stable increase in fluctuation, but it is still at a generally low level and does not show polarization, among which the APE in the northeast region is the highest. The COG of APE tends to transfer towards the northeast, and the coverage of the SDE is shrinking, so the overall spatial pattern is characterized by a tendency of clustering towards the north in the north-south direction and a tendency of imbalance in the east-west direction. APE has significant spatial convergence, and there is a trend of "latecomer catching-up" in low-efficiency regions. The introduction of spatial correlation accelerates the convergence rate and shortens the convergence period. The convergence rate is the highest in the central and western regions, followed by that in the northeastern region, and the convergence rate is the lowest in the eastern region. In addition, the convergence rate in different time periods has a phase change. The process of improving the quality and efficiency of agricultural production requires enhancing the adaptability of climate change, balancing the carrying capacity of the resource environment, and strengthening inter-regional cooperation and linkage in the field of agriculture. [ABSTRACT FROM AUTHOR]

The allocation efficiency of China's agricultural science and technology resources (ASTR) varies in different regions and has a complicated spatial distribution pattern. To visually study whether there are correlations and mutual influences between the allocation efficiency of different regions, we use social network analysis methods (SNA). The study found that: (i) China's allocation efficiency of ASTR has significant spatial correlation and spillover effects. The overall network density is declining. (ii) The spatial correlation network has significant regional heterogeneity. Some eastern provinces play "intermediaries" and "bridges" in the network. (iii) Geographical proximity, differences in economic development levels, industrial structure levels, and differences in urbanization have a significant impact on the formation of spatial association networks. [ABSTRACT FROM AUTHOR]

Improving agricultural water use efficiency (AWUE) is an important way to solve the shortage of water resources in arid and semi-arid regions. This study used the Super-DEA (data envelopment analysis) to measure the AWUE of 52 cities in Northwest China from 2000 to 2018. Based on spatial and temporal perspectives, it applied Exploratory Spatial Data Analysis (ESDA) to explore the dynamic evolution and regional differences of AWUE. A spatial econometric model was then used to analyze the main factors that influence the AWUE in Northwest China. The results showed firstly that the overall AWUE in Northwest China from 2000 to 2018 presented a steady upward trend. However, only a few cities achieved effective agricultural water usage by 2018, and the differences among cities were obvious. Secondly, AWUE showed an obvious spatial autocorrelation in Northwest China and showed significant high–high and low–low agglomeration characteristics. Thirdly, economic growth, urbanization development, and effective irrigation have significant, positive effects on AWUE, while per capita water resource has a significant, negative influence. Finally, when improving the AWUE in arid and semi-arid regions, plans should be formulated according to local conditions. The results of this study can provide new ideas on the study of AWUE in arid and semi-arid regions and provide references for the formulation of regional agricultural water resource utilization policies as well. [ABSTRACT FROM AUTHOR]

In the present work, the ultrasonic-assisted extraction (UAE) of total flavonoids (TF) from Pteris cretica L. was optimized by response surface methodology (RSM) on the basis of a single-factor experiment. The optimized UAE parameters were as follows: Ethanol concentration 56.74%, extraction time 45.94 min, extraction temperature 74.27 °C, and liquid/solid ratio 33.69 mL/g. Under the optimized conditions, the total flavonoids yield (TFY) was 4.71 ± 0.04%, which was higher than that obtained by heat reflux extraction (HRE). The extracts were further analyzed by HPLC, and five major flavonoids, including rutin, quercitrin, luteolin, apigenin, and luteolin-7-O-glucoside, were identified and quantified. Furthermore, the results of the antioxidant test showed that the TF extract obtained under optimized UAE conditions exhibited good 2,2-diphenyl-1-picrylhydrazyl radical (DPPH•) and 2,2-azino-bis(3-ethylbenzothiazoline-6-sulfonic acid) radical (ABTS+•), nitric oxide radical (NO•) scavenging activities, and ferrous ion (Fe2+) chelating capacity, with IC50 values of 74.49, 82.92, 89.12, and 713.41 µg/mL, respectively. Results indicated that the UAE technique developed in this work was an efficient, rapid, and simple approach for the extraction of flavonoids with antioxidant activity from P. cretica. [ABSTRACT FROM AUTHOR]

In order to find an efficient way for broccoli to increase the phenolic content, this study intended primarily to elucidate the effect of methyl jasmonate (MeJA) treatment on the phenolic accumulation in broccoli. The optimum concentration of MeJA was studied first, and 10 μM MeJA was chosen as the most effective concentration to improve the phenolic content in wounded broccoli. Furthermore, in order to elucidate the effect of methyl jasmonate (MeJA) treatment on phenolic biosynthesis in broccoli, the key enzyme activities of phenylpropanoid metabolism, the total phenolic content (TPC), individual phenolic compounds (PC), antioxidant activity (AOX) and antioxidant metabolism-associated enzyme activities were investigated. Results show that MeJA treatment stimulated phenylalanine ammonia-lyase (PAL), cinnamate 4-hydroxylase (C4H), and 4-coumarin coenzyme A ligase (4CL) enzymes activities in phenylpropanoid metabolism, and inhibited the activity of polyphenol oxidase (PPO), and further accelerated the accumulation of the wound-induced rutin, caffeic acid, and cinnamic acid accumulation, which contributed to the result of the total phenolic content increasing by 34.8% and ferric reducing antioxidant power increasing by 154.9% in broccoli. These results demonstrate that MeJA in combination with wounding stress can induce phenylpropanoid metabolism for the wound-induced phenolic accumulation in broccoli. [ABSTRACT FROM AUTHOR]

For the full development and utilization of Sophora tonkinensis Gagnep., this study was primarily intended to established a simple and efficient approach for the preparative purification of total flavonoids from S. tonkinensis by macroporous resin column chromatography (MRCC). The adsorption and desorption characteristics of the total flavonoids on ten macroporous resins were first studied, and AB-8 resin was chosen as the most suitable, and the adsorption data were best fitted to the pseudo-second-order kinetics model and Langmuir isotherm model. Furthermore, the technological parameters for the purification of the total flavonoids were optimized using column chromatography. After a sample one-step purification procedure, the content of the total flavonoids increased by about 4.76-fold from 12.14% to 57.82%, with a recovery yield of 84.93%. In addition, the comparative analysis of the flavonoid extracts before and after purification was performed by high-performance liquid chromatography coupled with photodiode-array detection (HPLC-PAD). The results showed that the contents of six major flavonoids in the purified product were all higher than before the purification. Therefore, the AB-8 MRCC established in this work was a promising method for the industrial-scale purification of the total flavonoids from S. tonkinensis. [ABSTRACT FROM AUTHOR]

The objective of this study was to develop an ultrasonic-assisted procedure for the extraction of total phenolics from Citrus aurantium L. blossoms (CAB) and evaluate the free radical scavenging activity and anti-HMG-CoA reductase activity of the total phenolics. In this work, a Box– Behnken design based on single-factor experiments was used to explore the optimum extraction process. Under the optimum conditions (extraction solvent 70.31% ethanol, extraction temperature 61.94 °C, extraction time 51.73 min, and liquid-to-solid ratio 35.63 mL/g), the extraction yield of total phenolics was 95.84 mg gallic acid equivalents (GAE)/g dry matter (DM), which was highly consistent with the theoretical value (96.12 mg GAE/g DM). The higher contents of total phenolics and five main phenolic compounds obtained from the optimized ultrasonic-assisted extraction (UAE) proved its efficiency when compared with conventional heat reflux extraction (HRE). The total phenolic extract showed excellent free radical scavenging properties against 1,1-diphenyl-2-picrylhydrazyl radical (DPPH·), 2,2′-azino-bis-(3-ethylbenzthiazoline-6-sulphonic acid) radical (ABTS+·), hydroxyl radical (·OH) and superoxide anion radical (·O2−), with IC50 values of 197.007, 83.878, 218.643, and 158.885 μg/mL, respectively; the extracts also showed good inhibition of β-hydroxy-β-methylglutaryl-CoA reductase (HMG-CoA reductase) activity, with an IC50 value of 117.165 μg/mL. Total phenolics from CAB could be a potential source of natural free radical scavenger and HMG-CoA reductase inhibitor. [ABSTRACT FROM AUTHOR]