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Spatial Multiobjective Optimization of Agricultural Conservation Practices using a SWAT Model and an Evolutionary Algorithm
Published on: December 9, 2012
[Spatial Network Analysis of Inter-provincial Straw Return Coupled with Agricultural Green and Low-carbon Production
Lan-Lan Zhao1, Ming-Liang Li2, Xian-Dong Li1
1College of Economics and Management, Xinjiang Agricultural University, Urumqi 830052, China.
Abstract:
The systematic characterization of the coupled and coordinated spatial correlation network characteristics and driving mechanism of straw return technology promotion and agricultural green and low-carbon production efficiency provides empirical reference for guaranteeing food security and promoting sustainable agricultural development. The study comprehensively applies the coupled coordination degree model, modified gravity model, social network analysis method, and QAP method to outline the coordination level and spatial correlation network evolution characteristics of straw return to fields and agricultural green and low-carbon production efficiency in 30 provinces of China from 2000 to 2021 and to explore their influencing factors. The study found that: ① During the study period, China's agricultural green and low-carbon production efficiency showed a small fluctuation and growth trend, with significant regional differences and an overall development trend of eastern region > central region > western region. ② The overall coupling and coordination degree between straw return and agricultural green low-carbon production efficiency in 30 provinces in China was on the rise, with a significant spatial clustering effect. The provinces with high coupling and coordination degree gradually converged to the eastern region, and the coupling and coordination degree of the western region was gradual, with a lag in the spreading speed and the overall performance of the "east is flourishing and west is declining" development pattern. ③ In 2021, the intensity of the spatial connection of coupling coordination will be larger than that in 2000, showing a complex pattern of center-periphery type with dense east and sparse west, multi-flow direction, and intertwining. ④ The overall network density and association degree of coupling coordination of 30 provinces in China were relatively stable, the network hierarchy degree and network efficiency have increased, the core-edge structure was characterized significantly, and the scope of the core area in the eastern region was significantly larger than that in the central and western regions. ⑤ Agricultural technology progress, economic development level, geographic proximity, agricultural industry agglomeration, and human capital level had a significant positive effect on the spatial association network.
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