Heavy metal (HM) accumulation in farmland soil can be transferred to the human body through the food chain, posing a serious threat to human health. Exploring the environmental risk and safe utilization zoning of soil HMs in farmland can provide the basis for the formulation of effective control strategies. Soil samples from typical subtropical farmland were collected in Jinhua City and analyzed for HMs (As, Cd, Cr, Cu, Hg, Ni, Pb, and Zn). The objective of this study was to explore the spatial distribution and environmental risk of soil HMs, and then divide the safe utilization area of soil HMs of farmland in Jinhua City. The results showed that the mean concentrations of soil HMs were, in descending order: Zn (76.05 mg kg⁻¹) > Cr (36.73 mg kg⁻¹) > Pb (32.48 mg kg⁻¹) > Cu (18.60 mg kg⁻¹) > Ni (11.95 mg kg⁻¹) > As (6.37 mg kg⁻¹) > Cd (0.18 mg kg⁻¹) > Hg (0.11 mg kg⁻¹), and all determined soil HMs did not exceed the risk screening values for soil contamination of agricultural land of China. The fitted semi-variogram showed that the spatial autocorrelation of Cd, Hg, Pb, and Zn was weak, with island-shaped distribution, while As, Cr, Cu, and Ni had medium spatial autocorrelation, with strip-shaped and island-shaped distribution. The hot spot analysis and environmental risk probability showed that the environmental risks of As, Cd, Cu, Pb, Zn, and Cu were relatively high, whereas those of Cr, Hg, and Ni were relatively low. Safe utilization zones and basic safe utilization zones accounted for 89.35% and 8.58% of the total farmland area in Jinhua, respectively, and only a small part of the farmland soil was at risk of use.

Unreasonable human activities may cause the accumulation of heavy metals (HMs) in the agricultural soil, which will ultimately threaten the quality of soil environment, the safety of agricultural products, and human health. Therefore, the accumulation characteristics, potential sources, and health risks of HMs in agricultural soils in China’s subtropical regions were investigated. The mean Hg, Cu, Zn, Pb, and Cd concentrations of agricultural soil in Jinhua City have exceeded the corresponding background values of Zhejiang Province, while the mean concentrations of determined 8 HMs were less than their corresponding risk-screening values for soil contamination of agricultural land in China. The spatial distribution of As, Cr, Ni, Cu, and Pb were generally distributed in large patches, and Hg, Zn, and Cd were generally sporadically distributed. A positive definite matrix factor analysis (PMF) model had better performance than an absolute principal component–multiple linear regression (APCS-MLR) model in the identification of major sources of soil HMs, as it revealed higher R² value (0.81–0.99) and lower prediction error (−0.93–0.25%). The noncarcinogenic risks (HI) of the 8 HMs to adults and children were within the acceptable range, while the carcinogenic risk (RI) of children has exceeded the safety threshold, which needs to be addressed by relevant departments. The PMF based human health risk assessment model indicated that industrial sources contributed the highest risk to HI (32.92% and 30.47%) and RI (60.74% and 61.5%) for adults and children, followed by agricultural sources (21.34%, 29.31% and 32.94% 33.19%). Therefore, integrated environmental management should be implemented to control and reduce the accumulation of soil HMs from agricultural and industrial sources.

The multi-function characteristics of cultivated land have been widely recognized by researchers in China and globally, and it is important to provide a theoretical basis and practical reference for future research on the evaluation and zoning of cultivated land quality based on a space–function–environment perspective. Spearman rank correlation analysis and cluster analysis were used to categorize cultivated land by its quality. This study developed a theoretical evaluation framework of the space–function–environment quality for cultivated land and constructed a total of 23 indicators of cultivated land quality in three dimensions. The framework was applied to a case study that evaluated and zoned cultivated land quality based on a space–function–environment perspective. The results showed that the synergies and tradeoffs among spatial quality, functional quality and environmental quality, and the influences of the three on cultivated land quality are mutually restricted and act together. The cultivated land in Qujiang District can be divided into five types of areas according to the cold and hot spot analysis results of the secondary indexes of cultivated land spatial quality, functional quality and environmental quality. Based on these results, different protection schemes are proposed for different cultivated land qualities.

Agricultural land reclamation of coastal tidal land (CTL) with organic amendments may modulate the soil properties, and therefore promote crop growth. However, the linkages between soil nutrient contents, pools, stoichiometry, and crop growth under the supplement of organic amendments in CTL is limited. In this study, six treatments including the control (CK), organic manure (OM), polyacrylamide plus organic manure (PAM + OM), straw mulching plus organic manure (SM + OM), buried straw plus organic manure (BS + OM), and bio-organic manure plus organic manure (BM + OM) were conducted to explore these linkages in newly reclaimed CTL in Jiangsu Province, eastern China. The results showed that the application of different soil reclamation treatments increased soil nutrient contents, pools, and modulated their stoichiometric ratio, which thus promoted the growth of oat. Soil under all reclamation treatments increased the contents of surface soil organic carbon (SOC), total nitrogen (TN), and total phosphorus (TP), and the BM + OM treatment had the highest increase, which increased by 11.7–182.4%, 24.3–85.7%, 3.2–29.4%, respectively. The highest soil C pools were observed in the oat heading stage (36.67–41.34 Mg C ha⁻¹), whereas the soil N and P pools were more stable during the oat growth period. Similarly, the highest surface soil C/N and C/P were observed in the oat heading stage (11.23–14.67 and 8.97–14.21), whereas the N/P in surface soil increased compared with the CK treatment during the oat growth period, with the exception of the filling stage. Land reclamation treatments significantly promoted oat growth by changing soil C, N, and P contents, pools, and stoichiometry, among which soil SOC, TN, TP, C/P, and N/P are more closely related to oat growth (p < 0.05).

Accurately mapping the spatial distribution and variation of soil organic matter (SOM) is of great significance for guiding regional soil management. However, the applicability and prediction performance of machine learning techniques in dryland agroecosystems still needs to be further studied. In this study, we collected a total of 733 topsoil samples from the farmland in Xiao County, Anhui Province, which is a typical dryland agroecosystem in the Huang-Huai-Hai Plain. Then, the environmental covariates were selected, and the ordinary kriging (OK), multiple linear stepwise regression (MLR), regression kriging (RK), radial basis function neural network (RBFNN), and random forest (RF) models were conducted to map the SOM content, and the optimal model was ascertained. The results demonstrated that the alkali-hydrolyzable nitrogen (26.11%), available potassium (17.73%), mean annual precipitation (13.26%), and pH (11.80%) were the main controlling factors affecting the spatial distribution of SOM in the study area. Meanwhile, the introduction of environmental covariates can effectively improve the SOM prediction accuracy, and the RF model (R² = 0.48, MAE = 2.38 g kg⁻¹, MRE = 12.99%, RMSE = 3.14 g kg⁻¹) has a better performance than the RFBNN, MLR, RK, and OK methods. Although there are local differences in the spatial distribution of SOM predicted by the five methods, the overall spatial distribution of SOM was characterized by the low concentration area (13.44–20.00 g kg⁻¹) distributed in the central and northwest of study area, and the high concentration area (24.00–28.95 g kg⁻¹) distributed in the southeast. Overall, our study demonstrated that machine learning-based models could accurately predict the SOM content in dryland agroecosystem, and the produced maps function as baseline maps for sustainable agricultural management.

Rural depression is a global issue in the process of worldwide urbanization. Compared with rural economic institution reform, rural land institution reform is more thorough in realizing rural revitalization. In this paper, polycentric governance theory is used to introduce marketization reform of collective profit-oriented land (MRCPL). MRCPL aims to allow rural collective profit-oriented construction land to be sold and leased with the same rights and at the same price as state-owned construction land. In the process of MRCPL, we suppose that the key subject is the central government, and the multiple auxiliary subjects include local governments, markets, villagers, and village collectives. Herein, Deqing County was selected as the research area and its achievements, conflicts, and potential risks in the process of MRCPL were studied. This study found that in Deqing County, a unified urban–rural construction land market has been preliminarily established, the rural revenue allocation mechanism has been updated, and the rural land finance mechanism has been developed. However, MRCPL may have conflicts with existing land requisition institutions and land banking institutions, and may also have conflicts within different subjects (farmers, village collective, local government, and central government). These conflicts may lead to potential risks, such as rent-seeking risk, land-financing risk, and real-estate-bubble risk. In general, the MRCPL aims to allow rural collective profit-oriented construction land to be sold and leased with the same rights and at the same prices as state-owned construction land. This reform can protect farmers’ land rights and promote the construction of urban and rural integration.