Search Results (151)

Cultivated land quality is a key factor in ensuring sustainable agricultural development. Exploring differences in cultivated land quality under distinct cropping systems is essential for developing targeted improvement strategies. This study takes place in Shenyang City—located in the typical black soil region of Northeast China—as a case area to construct a cultivated land quality evaluation system comprising 13 indicators, including organic matter, effective soil layer thickness, and texture configuration. A minimum data set (MDS) was separately extracted for paddy and upland fields using principal component analysis (PCA) to conduct a comprehensive evaluation of cultivated land quality. Additionally, an obstacle degree model was employed to identify the limiting factors and quantify their impact. The results indicated the following. (1) Both MDSs consisted of seven indicators, among which five were common: ≥10 °C accumulated temperature, available phosphorus, arable layer thickness, irrigation capacity, and organic matter. Parent material and effective soil layer thickness were unique to paddy fields, while landform type and soil texture were unique to upland fields. (2) The cultivated land quality index (CQI) values at the sampling point level showed no significant difference between paddy (0.603) and upland (0.608) fields. However, their spatial distributions diverged significantly; paddy fields were dominated by high-grade land (Grades I and II) clustered in southern areas, whereas uplands were primarily of medium quality (Grades III and IV), with broader spatial coverage. (3) Major constraint factors for paddy fields were effective soil layer thickness (21.07%) and arable layer thickness (22.29%). For upland fields, the dominant constraints were arable layer thickness (27.57%), organic matter (25.40%), and ≥10 °C accumulated temperature (23.28%). Available phosphorus and ≥10 °C accumulated temperature were identified as shared constraint factors affecting quality classification in both systems. In summary, cultivated land quality under different cropping systems is influenced by distinct limiting factors. The construction of cropping-system-specific MDSs effectively improves the efficiency and accuracy of cultivated land quality assessment, offering theoretical and methodological support for land resource management in the black soil regions of China. Full article

The Kundulun River Basin is the most prominent branch of the Yellow River system within the jurisdiction of Baotou City. As an important water source and ecological barrier, its ecological quality is directly related to the ecological security and sustainable development of the surrounding areas. This study selected the Kundulun River Basin in Baotou City as the research area. On the basis of collecting relevant information, a field investigation was conducted on the ecological and geological conditions of the atmospheric surface subsurface Earth system, using the watershed as the survey scope and water as the carrier for the transfer and conversion of materials and energy in the watershed. This study selected the main factors that affect the ecological geological quality of the watershed and established an evaluation model using the analytic hierarchy process, the coefficient of variation method, and the comprehensive analysis method. We have established an ecological geological quality evaluation index system for the Kundulun River Basin. We conducted quantitative evaluation and comprehensive analysis of regional ecological and geological environment quality. The results indicate that ecological environment indicators contribute the most to the ecological quality of the study area, while the impact of human activities on ecological quality is relatively small. From the perspective of evaluation indicators, grassland has the highest weight, followed by precipitation, groundwater depth, forest land, and cultivated land. Approximately 30.26% of the land in the research area is in a state of high or relatively high ecological and geological–environmental quality risk. It can be seen that the overall quality of the ecological geological environment is not optimistic and needs further protection. Full article

Humic substances affect both soil fertility and carbon sequestration. This study aimed to evaluate the effect of straw return on the quality of soil organic matter on arable land commonly farmed by private farmers at 65 different sites between 2012 and 2022 in the Czech Republic (central Europe). In this study, most of the carbon supply was applied in straw (67% of the carbon input on average). No significant correlation between the total carbon input and both parameters of soil organic matter quality and soil organic carbon content was found. The ratio of optical absorbance at 465 to 665 nm (E4/E6) and humification index correlated most significantly with organic fertilization. However, the E4/E6 ratio was more significantly affected by the altitude of the experimental site compared to the organic fertilization. When the weighted mean C/N ratio of organic fertilizers applied exceeded the value of ca. 65, there was a decrease in the E4/E6 ratio in fluvisols and luvisols and an increase in the humification index in loamy soils, sandy loamy soils, and silt loamy soils compared to the C/N ratio ≤ 50. Leguminous cultivation revealed no significant effect on soil organic matter quality. Full article

Albi-boric argosols, mainly distributed in the Sanjiang Plain of Heilongjiang Province, China, accounting for over 80% of the total cultivated land area, is characterized by a nutrient-deficient layer beneath black soil. This study addresses the challenges of modern agriculture by investigating the impact of straw incorporation on soil dissolved organic carbon (DOC) and its structures in albi-boric argosols, profiles, using fluorescence excitation–emission spectroscopy and parallel factor analysis (PARAFAC). Three treatments were applied: undisturbed albi-boric argosols (C), mixed albic and illuvium layers (M), and mixed albic and illuvium layers with straw (MS). Results showed that the yield of M and MS increased by 9.9% and 13.0%, respectively. There was a significant increase in DOC content, particularly in the MS treatment. Fluorescence index (FI) values ranged from 1.65 to 1.86, biological index (BIX) values were less than 1, and humification index (HIX) values were below 0.75, indicating a mix of plant and microbial sources for DOC, autochthonous characteristics, and weaker humification degree. PARAFAC identified two/three individual fluorophore moieties that were attributed to fulvic acid substances, soluble microbial products, and tyrosine-like substances, with microbial products as the dominant component. This study demonstrates the effect of improving barrier soil and maintaining sustainable agriculture by enhancing soil quality. Full article

The ecological impacts of dam and reservoir construction necessitate systematic environmental quality evaluation (EEQ) to reconcile ecological protection with sustainable development. To address this need, we integrated the Remote Sensing Ecological Index (RSEI)—a comprehensive metric synthesizing greenness, humidity, heat, and dryness—with a Land Use Change Ecological Response (LUCER) model to quantify the long-term EEQ dynamics in reservoir-affected regions. This study utilized Landsat and Sentinel-2 remote sensing imagery with a 10 m resolution from the years 2000, 2005, 2010, 2015, and 2020 to compute the RSEI for the Qianping Reservoir area in Henan Province, investigating the spatiotemporal variations in EEQ. Key findings reveal: (1) Temporal trend: EEQ showed fluctuating improvement, with RSEI projected to rise gradually until 2030. (2) Spatial pattern: A lower ecological quality in central reservoir zones contrasts with higher quality in surrounding mountainous areas. (3) Mechanism: The Land Use Change Ecological Response (LUCER) model reveals that the conversion of cultivated land to forestland and grassland drives significant EEQ improvements, counterbalancing the negative impacts of hydrological fragmentation caused by reservoir construction and urbanization. This study advances RSEI applications in reservoir ecology by establishing a coupled monitoring–prediction framework, providing actionable insights for dam-related ecological restoration and governance. Full article

In recent years, China’s “greening” trend has drawn great attention. However, does this truly represent ecological improvement? This study aims to figure it out on the mountain–oasis–desert ecosystem in the rid region of Northwest China. By first exploring the vegetation changes and the influence of climate factors and human activities on these changes, we then assessed the regional ecological quality using a combination of the Remote Sensing Ecological Index (RSEI) and the InVEST Habitat Quality Model. The results revealed that the NDVI was indeed increased, but the increase was primarily driven by cropland expansion, with significant NDVI and RSEI growth confined to oases. When croplands were excluded, RSEI values dropped substantially, and 20.9% of the region shows noticeable ecological quality deterioration. Remarkably, 75% of areas with improved RSEI ratings are cultivated lands, which concealed the degradation of natural ecosystems. The InVEST model highlights intensified regional degradation, with habitat quality declining and 9.1% of grasslands converted into croplands. Hurst index projections show 47.5% of vegetation faces sustained degradation. Thus, the observed “greening” primarily reflects cropland expansion rather than ecological improvement. Natural ecosystems in mountainous and desert areas face ongoing severe degradation. This research emphasizes the urgent need for arid regions to balance agricultural expansion with ecological conservation. Full article

Cultivated land (CL), as the foundation of agricultural production, possesses multifunctionality, and its utilization mode directly influences the agricultural modernization process. This study systematically analyzed the coupled and coordinated development characteristics and driving mechanisms of cultivated land multifunction (CLM) and agricultural mechanization (AM) using data from 31 Chinese provinces between 2011 and 2021, aiming to reveal the complexity of regional agricultural modernization and provide scientific evidence for differentiated agricultural development strategies. Key research findings: (1) From 2011 to 2021, the levels of CLM utilization, AM development index, and their coupling coordination consistently increased, but regional development disparities were prominent. The CLM level in western regions was significantly lower than in eastern and central regions, with regional differences in AM development gradually expanding. (2) Driving factors of coupled and coordinated development varied significantly across regions: eastern regions were primarily driven by technological innovation, central regions were influenced by production efficiency and social security, and western regions were mainly constrained by ecological functions. (3) Natural conditions such as cultivated land area, quality, and land flatness significantly impact the coordinated development of AM and CLM. This study innovatively constructed an evaluation index system for CLM and AM coupling coordination, integrating socio-economic and remote sensing data. By employing entropy weight TOPSIS and coupling coordination models, it conducted an in-depth analysis of long-term temporal changes and revealed the internal mechanisms of regional coordinated development through spatial econometric methods. The research results not only provide theoretical support for regional agricultural modernization but also offer scientific references for formulating differentiated agricultural development policies, promoting synergistic development of agricultural modernization and ecological civilization construction, and exploring more precise and sustainable regional agricultural development paths. Full article

Diffuse agricultural pollution is a leading contributor to surface water degradation, particularly in regions undergoing rapid land use change and agricultural intensification. In many developing countries, conventional assessment approaches fall short of capturing the spatial complexity and cumulative nature of multiple environmental drivers that influence surface water vulnerability. This study addresses this gap by introducing the Integral Index of Vulnerability to Diffuse Contamination (IIVDC), a spatially explicit, multi-criteria framework that combines the Analytical Hierarchy Process (AHP) with Geographic Information Systems (GIS). The IIVDC integrates six key indicators—slope, soil erodibility, land use, runoff potential, hydrological connectivity, and observed water quality—weighted through expert elicitation and mapped at high spatial resolution. The methodology was applied to the Guachal River watershed in Valle del Cauca, Colombia, where agricultural pressures are pronounced. Results indicate that 33.0% of the watershed exhibits high vulnerability and 4.3% very high vulnerability, with critical zones aligned with steep slopes, limited vegetation cover, and strong hydrological connectivity to cultivated areas. By accounting for both biophysical attributes and pollutant transport pathways, the IIVDC offers a replicable tool for prioritizing land management interventions. Beyond its technical application, the IIVDC contributes to sustainability by enabling evidence-based decision-making for water resource protection and land use planning. It supports integrated, spatially targeted actions that can reduce long-term contamination risks, guide sustainable agricultural practices, and improve institutional capacity for watershed governance. The approach is particularly suited for contexts where data are limited but spatial planning is essential. Future refinement should consider dynamic water quality monitoring and validation across contrasting hydro-climatic regions to enhance transferability. Full article

As an important ecological barrier and economic belt in China, the sustainable development of the Yellow River Basin (YRB) is of great significance to national ecological security and regional economic balance. Based on the coupled and coordinated development analysis of the water–soil–energy–carbon (W-L-E-C) system in the provinces of the Yellow River Basin from 2002 to 2022, this study systematically analyzed the interaction relationship among the various factors through WLECNI index assessment, factor identification, and driving factor exploration. Thus, it fully reveals the spatiotemporal evolution law of regional coordinated development and its internal driving mechanism. It is found that the coordinated development of the W-L-E-C system in different provinces of the Yellow River Basin presents significant spatiotemporal differentiation, and its evolution process is influenced by multiple factors. It is found that the coordination of the YRB presents a significant spatial difference, and Inner Mongolia and Shaanxi, as high coordination areas, have achieved significant improvement in coordination, through ecological restoration and clean energy replacement, arable land intensification, and industrial water-saving technology, respectively. Shandong, Henan, and Shanxi in the middle coordination zone have made some achievements in industrial greening and water-saving technology promotion, but they are still restricted by industrial carbon emissions and land resource pressure. The Ningxia and Gansu regions with low coordination are slow to improve their coordination due to water resource overload and inefficient energy utilization. Barrier factor analysis shows that the water resources utilization rate (W4), impervious area (L4), energy consumption per unit GDP (E1), and carbon emissions from energy consumption (C3) are the core factors restricting coordination. Among them, the water quality compliance rate (W5) of Shanxi and Henan is very low, and the impervious area (L4) of Shandong is a prominent problem. The interaction analysis of the driving factors showed that there were significant interactions between water resource use and ecological protection (W-E), land resource and energy use (L-E), and carbon emissions and ecosystem (C-E). Inner Mongolia, Shaanxi, and Shandong achieved coordinated improvement through “scenic energy + ecological restoration”, cultivated land protection, and industrial greening. Shanxi, Henan, and Ningxia are constrained by the “W-L-E-C” complex obstacles. In the future, the Yellow River Basin should implement the following zoning control strategy: for the areas with high coordination, it should focus on consolidating the synergistic advantages of ecological protection and energy development; water-saving technology and energy consumption reduction measures should be promoted in the middle coordination area. In the low coordination area, efforts should be made to solve the problem of resource overload, and the current situation of low resource utilization efficiency should be improved by improving the utilization rate of recycled water and applying photovoltaic sand control technology. This differentiated governance plan will effectively enhance the level of coordinated development across the basin. The research results provide a decision-making framework of “zoning regulation, system optimization and dynamic monitoring” for the sustainable development of the YRB, and provide a scientific basis for achieving high-quality development of the basin. Full article

Fallow is a practice in which the soil is left uncultivated for a period of time and is used less due to the pressure on agricultural land, which impairs soil regeneration. The cultivation of legumes, such as peanuts, is a viable alternative that leads to an improvement in the soil chemistry and grain capacity. Despite their importance, there are gaps regarding the use of peanuts for land reclamation and their importance for enzymatic activity in the soil. Therefore, the aim of this study was to evaluate the effects of straw incorporation and peanut cultivation in fallow land on the soil’s chemical and biological quality and to determine whether the introduction of these elements contributes to an improvement in the soil fertility parameters and enzymatic activity. To achieve these objectives, experimental plots were established in fallow soils with different amounts of straw (0; 5 and 10 t ha⁻¹), with and without herbicide application and with peanut incorporation. The soil chemistry and enzymatic activity, plant biometrics and productivity were evaluated. The results showed that the straw treatment resulted in better plant development and increased productivity by up to 80%. The pH, soil organic matter, soil organic carbon, P, K, sum of bases and cation exchange capacity variables increased significantly with the presence of the plant and the incorporation of straw compared to uncovered soil, by 10%, 86%, 80%, 68%, 42%, 38% and 27%, respectively. For the enzymatic activity, the values showed that straw and peanut management affects the higher activity of β-glucosidase and arylsulfatase, with differences of 75 and 74% compared to the control. The incorporation of straw and peanuts in fallow land improves the chemical and biological quality of the soil. The use of herbicides has no effect on the soil dynamics or peanut development in the presence of straw and the presence of peanuts provides a better soil quality index and increases the β-glucosidase and arylsulfatase activity in the soil. Full article

The Mediterranean Diet is a highly sustainable diet, and legumes are among the products that best characterize this concept. This study evaluates the environmental sustainability of the Protected Geographical Indication (PGI) legume Phaseolus vulgaris L. cultivated in the Asturias region, Spain. Employing a multi-indicator approach, the study aims to define and measure certain biodiversity indicators useful for assessing the ecological quality and sustainability of the agroecosystems under consideration. Spatial analyses were conducted with GIS-based methodologies, integrating the Analytic Hierarchy Process (AHP) to generate a Sustainability Index (SI). The study found that a significant positive spatial autocorrelation was observed using Moran’s I test (Moran’s I = 0.74555, p < 0.01), indicating that the SI values were not equally distributed but clustered around particular regions. Furthermore, the Getis-Ord Gi* analysis determined statistically significant hotspots, mainly distributed in the western and southwestern areas, including regions near Cangas del Narcea and Tineo. This paper highlights the importance of integrating spatial analysis for environmental assessments to develop sustainability approaches. Soil quality, water use, biodiversity, and land management are some of the factors that affect sustainability outcomes in the region. The results underscore the role of PGI in promoting sustainable agricultural practices by meeting geographical and quality requirements for local production. Full article

The estimation of soil organic matter (SOM) content is essential for understanding the chemical, physical, and biological functions of soil. It is also an important attribute reflecting the quality of black soil. In this study, machine learning algorithms of support vector machine (SVM), neural network (NN), decision tree (DT), random forest (RF), extreme gradient boosting machine (GBM), and generalized linear model (GLM) were used to study the accurate prediction model of SOM in Tieling County, Tieling City, Liaoning Province, China. The models were trained by using 1554 surface soil samples and 19 auxiliary variables. Recursive feature elimination was used as a feature selection method to identify effective variables. The results showed that Normalized Difference Vegetation Index (NDVI) and elevation were key auxiliary variables. Based on 10-fold cross-validation, the RF model had the highest prediction accuracy. In terms of accuracy, the coefficient of determination of RF was 0.77, and the root mean square error was 2.85. The average soil organic matter content was 20.15 g/kg. The spatial distribution of SOM shows that higher content is concentrated in the east and west, while lower content is found in the middle. The SOM content of cultivated land was lower than that of forest land. Full article

Saline-alkali soil has the characteristics of high density, high firmness and poor permeability. Aiming at the problems of shallow subsoiling depth, large subsoiling specific resistance and small soil bulkiness in subsoiling operation in saline-alkali soil, this paper establishes a mathematical model of the specific resistance of a broken line subsoiler and uses genetic algorithm and the discrete element method to optimize the structure design of the subsoiler. Firstly, the mathematical model was developed by analyzing the force of the subsoiler in the working process. The genetic algorithm was used to solve the problem, and three geometric models of the broken line subsoilers were fitted. Then, EDEM software was used to simulate this, and the tillage performance was evaluated with draft force, soil disturbance area, subsoiling specific resistance and soil bulkiness as the indexes and verified by field experiment. The results showed that the subsoiling specific resistance of the three broken line subsoilers was significantly lower than that of the standard subsoiler in the simulation test. Compared to the standard subsoiler, the soil disturbance area of the broken line subsoiler-B increased by 12%, the draft force decreased by 19%, the subsoiling specific resistance decreased by 26% and the bulkiness increased by 6%. The field experiment results showed that the broken line subsoiler-B reduced the traction force and improved the tillage efficiency compared to the standard subsoiler, which was consistent with the analysis results of EDEM. The broken line subsoiler can effectively enhance the quality of cultivated land. Full article

Land use patterns significantly influence the quantity and composition of litter in the soil humus layers, thereby affecting the dynamics of soil organic carbon. However, the differences in labile organic carbon fractions and the carbon sequestration index under different land use patterns, as well as their impact on soil carbon storage in the humus layers of mollisols—without migration loss and soil erosion—remain unclear. Labile organic carbon is classified into fractions such as dissolved organic carbon, easily oxidized carbon, particulate organic carbon, and microbial biomass carbon, which are identified through different chemical extraction methods. This study investigates the impact of long-term land use patterns on organic carbon dynamics, organic carbon pools, K_OS, and CPMI in mollisols across five treatments: SC (continuous soybean cultivation), MC (continuous maize cultivation), MSR (maize–soybean rotation), GB (grass belt), and FB (forest belt). It also selects three soil depths (0–20 cm, 20–40 cm, and 40–60 cm) over an 11-year period for analysis. The results indicate that soil organic carbon, labile organic carbon fractions (EOC, POC, DOC, and MBC), and CPMI decrease with soil depth, while K_OS increases. Non-tillage treatments enhance SOC accumulation in the humus layers, with FB exhibiting the highest organic carbon content, surpassing GB, MC, SC, and MSR by 22.88%, 52.35%, 60.64%, and 80.12%, respectively. Non-tillage treatments can enhance the accumulation of labile organic carbon fractions, aligning with the observed trends in soil organic carbon, with the FB treatment identified as optimal. Additionally, these treatments can increase labile organic carbon fractions and CPMI, thereby improving soil stability. To minimize SOC loss, land use patterns should encourage the conversion of farmland to grassland and forest, with the FB treatment recommended as the optimal strategy for the protection of mollisols and the sustainable development of these soils over the long term. This approach is significant for understanding the soil carbon cycle, rationally planning land use strategies, and providing a reference for enhancing soil quality and ecosystem carbon sinks. Full article

In October 2021, China established its first group of national parks, representing a milestone in enhancing the country’s nature reserve system and aligning with global trends in ecological conservation. This study aims to assess habitat quality changes and identify the driving factors in five national parks using multi-temporal land use data from 2000 to 2020. By integrating the land use transfer matrix with the InVEST model, we quantified habitat quality changes, while the geographical detector method was employed to analyze the key natural and socioeconomic drivers. Results showed that grassland and cultivated land were predominantly converted into forestland, leading to improvements in habitat quality in some parks. Specifically, Wuyishan National Park exhibited the highest and most stable habitat quality index, while Three-River-Source National Park experienced significant improvement (+34.10%). However, the Giant Panda, Northeast China Tiger and Leopard, and Hainan Tropical Rainforest National Parks experienced habitat degradation, with decreases of 15.15%, 14.50%, and 13.90%, respectively. Key drivers, such as NDVI, temperature, precipitation, elevation, and population density, were found to significantly influence habitat quality across the parks. This study highlights the ecological benefits of forestland restoration and the risks posed by the conversion of forest to cultivated or construction land, providing valuable insights for optimizing conservation strategies in China’s national parks. Full article