Phytoremediation, which involves the use of plants to accumulate and translocate metals and metalloids, represents a promising strategy for environmental remediation. The efficiency of phytoremediation is influenced by many factors such as metal/metalloid types, soil properties, and plant traits. It remains unclear how these factors modulate the efficiency of phytoremediation. We synthesized 547 data pairs from 82 studies to comprehensively evaluate the ability of hyperaccumulating plants to accumulate and translocate metals/metalloids under varying environmental conditions. The results show that cadmium (Cd), the most frequently investigated heavy metal, has the highest average bioaccumulation factor (BF) (10.0 ± 1.3) but a relatively low average translocation factor (TF) (1.8 ± 0.1). Aboveground biomass (AGB) of Cd hyperaccumulators is negatively correlated with BF but positively correlated with TF. Cd hyperaccumulating plants exhibit the highest accumulation capacity (maximal BF = 191), with roots outperforming aerial parts. The lower TF is mainly due to the lower AGB of Cd hyperaccumulating plants. In contrast, nickel (Ni) hyperaccumulators exhibit the highest TF, particularly in leaves and stems, indicating that Ni primarily accumulates in the aboveground parts. As soil pH increases, the BF of Cd and Zinc (Zn) decrease, whereas the BF of lead (Pb) increases, likely due to their distinct chemical behaviors under different pH conditions. Threshold concentrations were also identified for several for metals/metalloids (e.g., Cd: 214.8 mg kg^-1; Pb: 31352.3 mg kg^-1), beyond which BF falls below 1.0, indicating diminished accumulation efficiency due to toxicity constraints. In sum, these findings provide insights for optimizing phytoremediation strategies, aiding in plant selection and remediation condition optimization for improved efficiency and sustainability.

Urbanization has not only promoted economic development, but also significantly changed land use and development strategy. The environmental problems brought by urbanization threaten ecological security directly. Therefore, it is necessary to introduce changes in land use when constructing an ecological security pattern. This study takes the Yangtze River Delta urban agglomeration, one of the most economically developed regions in China, as the research area. Based on its land use status, the Cellular Automata–Markov model was used to predict the quantitative change and transfer of land-use types in 2025, and three types of land-use patterns were simulated under different scenarios. Combined with the pressure–state–response model, the Entropy TOPSIS comprehensive evaluation model is used to evaluate the three phases in the years of 2005, 2010, and 2015, and the results indicated that the safety level dropped from 85.45% to 82.94%. Five spatial associations were obtained from the spatial autocorrelation analysis using GeoDA, and the clustering distribution of the three phases was roughly the same. Based on the requirements of “Natural Growth” scenario, “Urban Sprawl” scenario, and “Ecological Protection” scenario, the transfer matrix of the various land-use types were modified rationally. The results of scenario simulations illustrated that the level of urbanization was inversely proportional to the level of ecological security. The surrounding cities in the northern part of Taihu Lake were developing rapidly, with low levels of ecological security. The hilly cities in the southern part, in contrast, developed slowly and had a high level of ecological security. Based on the temporal and spatial changes in the ecosystem, an ecosystem optimization model was proposed to determine the ecological functional areas. The nature of each functional area provided the basis to formulate urban construction and management plans and achieve sustainable urban development.

Sichuan Province is an important ecological barrier in the upper reaches of the Yangtze River. Therefore, it is critical to investigate the temporal and spatial changes, as well as the driving factors, of ecosystem service values (ESVs) in Sichuan Province. This paper used land use data from 2000, 2005, 2010, 2015, and 2020 to quantify the spatiotemporal changes in the ESVs in Sichuan Province. Correlation coefficients and bivariate spatial autocorrelation methods were used to analyze the trade-offs and synergies of ESVs in the city (autonomous prefecture) and grid scales. At the same time, we used a Geographical Detector model (GDM) to explore the synergies between nine factors and ESVs. The results revealed that: (1) In Sichuan Province, the ESVs increased by 0.77% from 729.26 × 10⁹ CNY in 2000 to 741.69 × 10⁹ CNY in 2020 (unit: CNY = Chinese Yuan). Furthermore, ecosystem services had a dynamic degree of 0.13%. Among them, the ESVs of forestland were the highest, accounting for about 60.59% of the total value. Among the individual ecosystem services, only food production, environmental purification, and soil conservation decreased in value, while the values of other ecosystem services increased. (2) The ESVs increased with elevation, showing a spatial distribution pattern of first rising and then decreasing. The high-value areas of ESVs per unit area were primarily distributed in the forestland of the transition area between the basin and plateau; The low-value areas were distributed in the northwest, or the urban areas with frequent human activities in the Sichuan Basin. (3) The tradeoffs and synergies between multi-scale ecosystems showed that ecosystem services were synergies-dominated. As the scale of research increased, the tradeoffs between ecosystems gradually transformed into synergies. (4) The main driving factors for the spatial differentiation of ESVs in Sichuan Province were average annual precipitation, average annual temperature, and gross domestic product (GDP); the interaction between normalized difference vegetation index (NDVI) and GDP had the strongest driving effect on ESVs, generally up to 30%. As a result, the distribution of ESVs in Sichuan Province was influenced by both the natural environment and the social economy. The present study not only identified the temporal and spatial variation characteristics and driving factors of ESVs in Sichuan Province, but also provided a reference for the establishment of land use planning and ecological environmental protection mechanisms in this region.

Abandoned cropland may lead to a series of issues regarding the environment, ecology, and food security. In hilly areas, cropland is prone to be abandoned due to scattered planting, relatively fewer sunlight hours, and a lower agricultural input–output ratio. Furthermore, the impact of abandoned rainfed cropland differs from abandoned irrigated cropland; thus, the corresponding land strategies vary accordingly. Unfortunately, monitoring abandoned cropland is still an enormous challenge in hilly areas. In this study, a new approach was proposed by (1) improving the availability of Sentinel-1 and Sentinel-2 images by a series of processes, (2) obtaining training samples from multisource data overlay analysis and timeseries viewer tool, (3) mapping annual land cover from all available Sentinel-1 and Sentinel-2 images, training samples, and the random forest classifier, and (4) mapping the spatiotemporal distribution of abandoned rainfed cropland and irrigated cropland in hilly areas by assessing land-cover trajectories along with time. The result showed that rainfed cropland had lower F1 scores (0.759 to 0.8) compared to that irrigated cropland (0.836 to 0.879). High overall accuracies of around 0.90 were achieved, with the kappa values ranging from 0.851 to 0.862, which outperformed the existing products in accuracy and spatial detail. Our study provides a reference for extracting the spatiotemporal distribution of abandoned rainfed cropland and irrigated cropland in hilly areas.