Guangyu Li

Soil pollution with cadmium (Cd) poses a significant threat to the global natural environment, negatively impacting soil health and food security, particularly in China. Cd pollution influences bacterial communities directly and indirectly by altering soil physicochemical properties, including pH, soil particle size (SPS), moisture content (MC), organic matter (OM), available phosphorus (AP), available potassium (AK), total nitrogen (TN), catalase activity (SC), phosphatase activity (SP), urease activity (SU), and concentrations of heavy metals such as copper (Cu), cadmium (Cd), lead (Pb), chromium (Cr), arsenic (As), mercury (Hg), nickel (Ni), and zinc (Zn). In this study, 50 farmlands were randomly selected in J County, eastern China. High-throughput 16S rRNA sequencing was employed to analyze the soil bacterial community structure and its relationship with various environmental factors across different levels of Cd pollution. The results indicated: (1) Sobs and Chao (bacterial community richness indexes), along with Shannon and Invsimpson (bacterial diversity indexes), were significantly higher in severely Cd-polluted soil compared to moderately polluted soil. (2) In moderately polluted cultivated land, nine bacterial phyla exhibited strong transfer and absorption functions for Ni and Hg, while three genera were positively correlated with Cr and Ni. Conversely, in severely polluted soil samples, the relative abundances of 11 bacterial phyla and four genera showed significant positive correlations with Cr, Cu, Pb, and Zn. (3) The functional abundance of bacterial communities in severely Cd-polluted environments was significantly greater than that in moderately polluted ones, at a significance level of p<0.05. These results indicate the presence of heavy metal-tolerant bacteria in Cd-polluted soils.

Farmland use regulation strictly regulates the conversion of agricultural land for other agricultural purposes and the construction of agricultural facilities, thereby optimizing the land use pattern in rural areas. However, different measures and intensities of farmland use regulation can affect the overall performance of green and low-carbon development in rural areas. This study utilizes system dynamics modeling and simulation to conduct a case study based on current land use data from 10 towns in Liyang City, China. The empirical results indicate the following: (1) Based on comprehensive measurements of green and low carbon development performance, Liyang City exhibits a pattern of higher indices in the south and lower indices in the north. Towns such as Tianmu Lake, Daibu, and Shezhu show relatively high average comprehensive indices of 0.31, 0.30, and 0.28, significantly higher than other towns. (2) Simulation of farmland use regulation’s impact on green and low carbon development performance reveals that Scenario One, involving additional construction land occupying farmland, achieves a comprehensive index of only 0.23, significantly lower than the other scenarios. (3) Based on calculations and field surveys, Liyang City’s villages are categorized into four types, with the largest number being industry-integrated villages (94 villages). Accordingly, policies for farmland use regulation are designed for different village types. Therefore, future farmland use regulation should be tailored with differentiated institutional designs according to the development needs of different villages. This study’s findings provide insights into green and low-carbon development in rural areas.

Human trajectories, reflecting people's travel patterns and the range of activities, are crucial for the applications like urban planning and epidemic control. However, the real-world human trajectory data tends to be limited by user privacy or device acquisition issues, leading to its insufficient quality to support the above applications. Hence, generating human trajectory data is a crucial but challenging task, which suffers from the following two critical challenges: 1) how to capture the user distribution in human trajectories (group view), and 2) how to model the complex mobility patterns of each user trajectory (individual view). In this paper, we propose a novel human trajectories generator (named VOLUNTEER), consisting of a user VAE and a trajectory VAE, to address the above challenges. Specifically, in the user VAE, we propose to learn the user distribution with all human trajectories from a group view. In the trajectory VAE, from the individual view, we model the complex mobility patterns by decoupling travel time and dwell time to accurately simulate individual trajectories. Extensive experiments on two real-world datasets show the superiority of our model over the state-of-the-art baselines. Further application analysis in the industrial system also demonstrates the effectiveness of our model.

Fallowing is regarded as an effective method for the self-recovery management of farmland and is generally used in cultivated land management. Studies have shown that long-term fallow has many ecological and environmental benefits. However, the long-term fallowing of farmland has also caused a decline in the grain production of farmland for a period of time. Short-term fallow can reduce the risk of food insecurity, but there are few studies on short-term fallow, especially on the comparation of different fallowing management methods and their relationship with soil microbial ecology. Our study has focused on seven treatments. Firstly, the traditional farming method was set as the control group. Native vegetation and crop-pasture vegetation were set as the fallowing vegetation. There were three irrigation–fertilization levels for each vegetation. The effects of the sampling times showed that the impact of fallow management on the soil properties became gradually stronger with time. The interactions between the sampling times and treatments showed a significant impact on organic carbon and total nitrogen. There was a significant impact of fallow management on the inorganic carbon accumulation and ammonia nitrogen consumption. Microbial biomass carbon was significantly increased by fallowing. Fallowing with irrigation could enhance the soil microbial nitrogen transformation. Some genera associated with assisting diseases were significantly increased by the native vegetation fallow and grass fallow with farmyard manure. The fallow with native vegetation showed more advantageous ecological benefits than the crop-pasture vegetation fallow. Although the crop-pasture vegetation followed the principle of ecological intensification, it failed to show better ecological benefits in the short fallow period. In irrigation management, the benefits of native vegetation and crop-pasture vegetation are similar. However, considering the lower cost of crop-pasture vegetation, crop-pasture vegetation fallow with irrigation could be a better choice. If it is difficult to implement conservation measures during the fallowing process, native vegetation fallowing without management may be the only fallowing choice.