Temporal-spatial pattern and driving factors of cultivated land use transition at country level in Shaanxi province, China.

The county-level Cultivated Land Use Form index (CLUF) in Shaanxi province in 2000, 2005, 2010, and 2015 was measured with the entropy method and the linear combination method. Then, the spatial differentiation characteristics and driving mechanism of CLUF were characterized and identified through exploratory spatial data analysis, standard deviation ellipse model, kernel density estimation, multiple linear, and spatial regression analysis. The conclusions drawn from empirical results were as follows. First, the CLUF presented a spatial differentiation pattern of high in the middle and low in the north and south, and the CLUF had a strong positive spatial correlation. The local spatial patterns were mainly the high-high agglomeration and low-low agglomeration. Second, the gravity center of CLUF moves from northeast to southwest, but it is always located in the central part of Shaanxi province. The CLUF showed a trend from expansion and decentralization to contraction and centralization in geographical space, with an obvious spatial spillover effect. Third, the results of nuclear density estimation showed that the difference in the CLUF between counties displayed a trend of first shrinking and then expanding. Fourth, the cultivated land use transition was promoted by the combination of the natural environment, economic growth, and urbanization development, and factors of the driving mechanism of the cultivated land use transition are complicated. Finally, policy recommendations to promote the rationalization and cultivated land use transition were put forward, such as strengthening infrastructure construction, formulating differentiated policies, and giving play to the role of neighboring demonstrations.

Socioeconomic status, ambidextrous learning, and farmers' adoption of biological control technology: evidence from 650 kiwifruit growers in China.

BACKGROUND: Rural China is characterized as having different rates of economic growth. The resource and socioeconomic statuses of farm households greatly affect their productivity and the activities they engage in. The main objective in this study was to explore the mechanisms concerning how socioeconomic status of kiwifruit growers affects their adoption of biological control technology (BCT). To achieve this objective, field survey data from 650 kiwifruit farmers in specific kiwifruit growing areas of Shaanxi and Sichuan provinces in China were investigated. The binary probit model and Bootstrap dual mediated utility models served to assess socioeconomic status's effect on farmers' BCT adoption. RESULTS: This study discovered a significant positive correlation between socioeconomic status and the adoption rate of biological control technology. Farmers of various socioeconomic status have significant differences in the rate of BCT adoption. This study's empirical analysis found that exploratory learning and exploitative learning under dual learning had a significant mediating effect on farmers' socioeconomic status when it came to BCT acceptance. CONCLUSION: Results show that the rate of BCT adoption is related to farmers' socioeconomic status and dual learning mode, which provides new insights for understanding how farmers implement new technology. This study will help agricultural extension departments increase their awareness of BCT adoption by farmers, and the development of diverse learning approaches in response to differences in socioeconomic status of farmers may significantly increase their likelihood to implement BCT. © 2021 Society of Chemical Industry.

Measurement and spatial convergence analysis of China's agricultural green development index.

Based on the comprehensive evaluation system of agricultural green development index (AGDI), this paper uses entropy weight method and linear weighted sum method to measure the agricultural green development level of 31 provinces in China from 2013 to 2018. We then incorporate spatial correlation into the traditional convergence test model, study the spatial convergence of AGDI, and explore the reasons for regional differences in AGDI. The results show that the level of AGDI in China showed an overall growth trend during the sample survey period, but there were significant differences in the rate of AGDI among different regions, mainly manifested as "eastern > western > central." The AGDI shows a significant positive spatial correlation on the whole, and its overall spatial distribution is characterized by high-high agglomeration and low-low agglomeration. The provinces with higher and lower level of AGDI still maintain the original relatively concentrated distribution in geographical space. On this basis, the study examines the regional differences of AGDI and its evolution by Dagum Gini coefficient decomposition and spatial convergence. The results showed that the overall difference of AGDI showed a fluctuating downward trend. The intra-regional difference of AGDI in the western region was the largest, and that in the eastern region was the smallest. The contribution rate of intensity of transvariation among regions was the main source of the relative difference of AGDI. Meanwhile, the AGDI of the overall, eastern, central, and western regions present significant σ convergence and conditional ß convergence. Except for the central region, the overall, eastern, and western regions present significant absolute ß convergence. The low-level areas of AGDI have significant "catch-up effect" on the areas with high-level AGDI. Based on the above results, this paper also puts forward some policy suggestions from the perspective of cross-regional collaborative governance to improve China's agricultural green development mode and narrow the regional differences of China's agricultural green development.