The Dongting Lake area (China) is a climate change-sensitive and ecologically fragile area and plays a crucial role in the regulation of the regional climate. In recent decades, rapid social and economic development has led to increased land use/land cover (LULC) changes in the Dongting Lake area, which affect the surface energy balance and hydrological processes. Its contemporary variability under climate change remains highly uncertain. Therefore, we retrieved the Land surface temperature (LST) from the Landsat 7 data and explored its relationship with the LULC types. The results showed that LST is significantly affected by surface type. LST varied significantly across LULC types, with higher LSTs in built-up land, reed beach land, forest land, and paddy fields than in water bodies, mud beaches, marshlands, and riparian forests. Water bodies play an important regulatory role in reducing LST and mitigating thermal effects on the ground. The winter LST in the study area increased by approximately 3.5 °C, which may be related to the decrease in the area of Dongting Lake water bodies, water fields and reed flats after the Three Gorges Reservoir was impounded. Compared with the relationship between the NDVI, DEM, and distance from the water body, the negative correlation between the NDMI and LST was stronger and more stable and had the greatest effect on LST. These insights improve the understanding of the land change consequences on the temporal dynamics of LST.

Understanding the impact of changes in cultivated land in terms of structure, distribution, and quantity on grain production potential (GPP) is essential for a sustainable land utilization strategy and food security. Cultivated land balance (CLB), as a critical policy aiming at protecting farmland in China, has greatly restricted the loss of cultivated land. However, changes in cultivated land were largely generated due to the land-use activities led by the CLB policy. To clarify how the spatiotemporal dynamics of cultivated land led by the CLB policy affects the GPP, this work discusses the impact mechanism of cultivated land changes on GPP and provides an empirical analysis in Hunan Province, China. This study shows that the activities that merely aim at restricting the loss of cultivated land under CLB cannot stop the decline in GPP in China, since it requires the government to reclaim a certain amount of cultivated land that is equal to that occupied for non-cultivated land use. Furthermore, the distribution of cultivated land changed after the implementation of CLB and, as a result, contributed to the decrease in the quality of cultivated land and GPP. Quantity, productivity, and other elements that may potentially facilitate cultivated land protection are greatly advocated to be considered to enrich the connotation of the CLB policy in China. It also found that less developed regions located in central and western Hunan Province, among other areas, observed a higher sensitivity of GPP to cultivated land change. More attention should be paid to protecting cultivated land in these regions and addressing issues such as the abandonment of high-quality cultivated land.

Understanding the dynamics of the grain yield gap (YGAP) and its causative factors is essential for optimizing the layout of grain production and addressing the food crisis, especially in countries with a huge population and less cultivated land, such as China. In the study, a spatial analysis- and machine learning-based framework for YGAP analysis was developed, taking Hunan Province, China, as an application. The results showed that the average YGAP in Hunan Province gradually narrowed from 1990 to 2018, and the YGAPs narrowed in 116 counties. Of which, 26 counties narrowed by more than 4 t ha⁻¹, 58 counties narrowed from 2–4 t ha⁻¹, and 32 counties narrowed within 2 t ha⁻¹. Additionally, we found that the GDP per capita (GDPPC), sunshine hours (SH), per capita annual net income of farmers (PCAI), and rural electricity consumption (REC) play a key role in YGAP change, and the importance of human investment to the YGAP decreased, while socioeconomic environment became the dominant factor that influenced grain production. Comprehensively, the relatively great potential for grain yield growth was generated in sixty-four counties, which are mainly located in the northern, central, and southern Hunan. The findings suggest that it is necessary to consider the trends of economic development in rural areas and population migration in agricultural management. This work provides insights into yield gap dynamics and may contribute to sustainable agricultural management in Hunan Province, China, and other similar regions.

Selenium (Se) is essential for human health, but it interacts with cadmium (Cd). However, there has been little focus on developing soil health evaluation models based on the interaction between Se and heavy metals, or the transport of Se and Cd in oilseed rape. Through detection, it was found that the soil in Yuanzhou District is mostly Se-rich (average 0.62 mg kg⁻¹). Correlation analysis of the soil showed a positive correlation between Se content with Cd (r = 0.62, p < 0.01) and organic matter (r = 0.60, p < 0.01). A soil health score model was developed and performed well, indicating that the model can be used to estimate relevant soil health scores. Furthermore, the natural Se content of rice ranges from 0.07 to 0.28 mg kg⁻¹, and the overall enrichment ability of Se and Cd in oilseed rape is stronger than it is in rice. According to the correlation analysis, the Cd content in the soil was significantly correlated with the stems of oilseed rape (r = 0.49, p < 0.01) and rice (r = 0.37, p < 0.05). As a result, this study suggests using the rice/oilseed rape intercropping model of farming to transfer Cd into oilseed rape to reduce the Cd content in rice.