In the past 20 years, the global economy has undergone tremendous changes with rapid industrialization and urbanization. Cultivated land is an important spatial carrier for human production and life, and its use pattern also changes with socioeconomic development. Natural, economic, social, and policy factors jointly drive the cultivated land use transition (CLUT). However, the spatiotemporal pattern and evolution characteristics of the CLUT at the national scale have not yet been clarified in China. Factors that play a leading role in the transition are also unclear. To this end, this paper explores the spatiotemporal evolution characteristics of the CLUT at a national scale and analyzes the main drivers and spatial differentiation rules of the transition based on relevant data from 31 provincial units on the Chinese mainland from 2000 to 2019. The results show that: (1) The CLUT in China from 2000 to 2019 had obvious stage characteristics. (2) The coordination degree of the CLUT was enhanced overall. Areas with a higher degree of coordination presented a spatial distribution pattern of small agglomeration and large dispersion, while low-level areas were distributed in spots. (3) Different drivers had various effects on the CLUT. The topography played an inhibitory role in the transition, and its influence showed obvious differences between the east and west regions. The effect of the construction land demand index shifted from inhibition to promotion, while the effects of the gross agricultural economic output and the total power of agricultural machinery in the transition were insignificant.

It is of great significance for scientific land use planning and ecological security protection to clarify the impacts of land use changes on an ecosystem’s health. Based on the dynamic evolution of land use and ecosystem health on the Northern Slope of Tianshan Mountain (NSTM) from 2000 to 2020, this study utilized the patch-generating land use simulation (PLUS) model, the Vitality–Organization–Resilience–Services (VORS) model, and the elasticity approach to assess the impacts of land use changes on ecosystem health under four different scenarios: Natural Development Scenario (ND), Farmland Conservation Priority Scenario (FP), Ecological Conservation Priority Scenario (EP), and Urban Development Priority Scenario (UD). The results indicate that (1) land use on the NSTM from 2000 to 2020 was predominantly characterized by barren land and grassland. (2) The overall level of ecosystem health on the NSTM was poor from 2000 to 2020 but showed a gradual improvement trend. (3) Ecosystem health levels vary greatly across scenarios. In general, ecosystem health improves under FP and EP scenarios but deteriorates significantly under ND and UD scenarios. The resilience of ecosystem health varies significantly across different land categories. In the future, optimizing the current land use pattern and refining the ecological protection policy are essential to enhance ecosystem health and services in the NSTM.

To amplify grain production capacity, a global trend is emerging in which many regions are transitioning from dependence on rainfall to irrigated agriculture. An illustrative example of this form of land consolidation is the conversion from dryland to paddy fields, which has changed the ecological environment of farmlands, resulting in significant effects on carbon fixation and emissions. However, there currently exists a deficiency in essential understanding regarding the short-term effects of dryland-to-paddy conversion on ecological processes tied to soil carbon-fixation bacteria and carbon emission efficiency (CEE). Therefore, field monitoring and high-throughput sequencing were carried out to monitor the changes in soil carbon emission efficiency and carbon-fixation bacteria before and after the conversion. Our results indicate that while conversion from dryland to paddy fields can boost grain yield, it also results in an increase in soil carbon emissions and a consequent decrease of 25.78% in carbon emission efficiency. This transition has resulted in an increased soil carbon-fixing bacterial alpha diversity index and enhanced network complexity. The structural equation model indicates that changes in soil environmental factors, especially soil moisture, soil organic carbon (SOC), readily oxidizable carbon (ROC), and carbon-fixing bacteria, are the primary drivers of CEE variation (p < 0.05). Given the critical role that the soil carbon cycle plays in global climate change, there is a pressing need for increased global attention towards the carbon emissions triggered by the transition from rainfed to irrigated agriculture.