Search

The excessive use of cultivated land for non-grain production activities is considered a threat to grain security. This study presents an analysis framework on unraveling the causal mechanisms for non-grain production of cultivated land. We apply the analysis framework in Liyang, which is located in the Yangtze River Delta and is also an important "national grain base" county of China. We first determine four non-grain production categories as immediately recoverable (IMR), simple-engineering recoverable (SER), engineering recoverable (ENR), and irrecoverable (IR) based on the effect of non-grain activities on the degree of soil damage of the cultivated land, especially the difficulty of restoring the capacity for grain production. Then, we analyze the spatial pattern features for non-grain production of four given categories at the village scale. Furthermore, we reveal the mechanisms of the four categories using multiple linear regression modeling with geophysical, demographic, economic, and policy variables. The results show that the total non-grain area of cultivated land in Liyang is 28,158.38 hectares, and the non-grain rate is 48.09%, ranging from 10.59% to 96.75% among villages. The IMR, SER, ER, and IR rates are 11.81%, 17.76%, 15.07%, and 3.45%, respectively. There is also a significant neighborhood effect among the four categories, indicating that non-grain production activities have a stimulating effect on the surrounding operators of cultivated land. Farming conditions such as the proportion of irrigated farmland and economic variables such as the tourism scale have stronger effects on non-grain production than demographic variables. Policy variables, especially the cultivated land transfer policy, neither inhibit nor promote non-grain production. Based on these findings, we make policy suggestions for reducing non-grain production activities and protecting cultivated land. This analysis framework contributes to a new perspective for unraveling the causal mechanisms and making categorical governance decisions of non-grain production on cultivated land at the village level. [ABSTRACT FROM AUTHOR]

The rate of vegetation green-up (RVG) indicates the ability of vegetation to respond to changes in climatic conditions. Understanding long-term RVG trends can clarify the changes in how quickly the vegetation grows from dormancy to maturity with time. However, how RVG trends respond to environmental variables and variable interactions remains unknown. We examined the long-term RVG trends (1981–2018) over the northern extratropics and determined the influence of environment variables and interactions between variables on the RVG trends based on the Global Land Surface Satellite leaf area index and a multivariable regression considering interactions between variables (MRCI). Our results showed a persistent increase in RVG at 0.020% (8-day)−1 year−1 over the entire region. Except for shrublands (−0.032% (8-day)−1 year−1), RVG trends increased significantly, particularly in woody savannas (0.095% (8-day)−1 year−1) and mixed forests (0.076% (8-day)−1 year−1). The relative importance of interactive effects (RIIAE) to the RVG trends is roughly 30%. Rising CO2, enhanced vapor pressure deficit (VPD), and warming are the primary factors affecting the RVG trends, both at the pixel and the biome scales. The accelerated RVG is triggered by both rising CO2 and warming but is partially offset by increased VPD. Our findings shed light on the relative contribution of variable interactions and assessed the relationship between environmental factors and RVG trends across different biomes, hence strengthening our knowledge of vegetation spring green-up in response to global change. [ABSTRACT FROM AUTHOR]