四川省大豆生产格局变化及驱动因素研究

Spatiotemporal evolution and driving factors of soybean production in Sichuan Province

  • 摘要: 四川省是我国13个粮食主产区之一, 也是我国大豆种植的新兴地区和西南产区的重要组成, 研究大豆生产格局对四川省落实粮食安全战略、推动西南地区大豆产业发展具有重大意义。文章基于2000—2020年四川省183个区市县的面板数据, 运用空间基尼指数、地理集中度系数、空间转移系数、探索性空间数据分析、最优地理探测器分析了大豆生产的时空格局变化及驱动因素。研究结果发现: 1) 2000—2020年, 四川省大豆产能波动上升, 空间分布极不均衡, 聚集水平逐步上升, 并逐步向川中丘陵区集中; 2)大豆生产存在较强的正向空间相关性, 总体表现为高-高聚集和低-低聚集; 3)资源要素、比较收益、地理气候、经济社会等因素对大豆生产格局变化的影响均高度显著, 且呈现非线性增强、双因子增强的交互效应。资源要素投入、比较收益、海拔高程长期以来对大豆生产格局的影响较为显著且呈波动上升趋势, 气温、乡村家庭规模的影响力提升较快, 交通条件、地区GDP的影响力则总体呈下降趋势, 耕作制度长期以来驱动力最弱。基于此, 四川省大豆生产应着力破解耕地资源细碎化与劳动力短缺等资源环境约束, 大力发展生产性服务业, 全面提升大豆生产机械化水平。通过强化科技创新提升川豆单产, 并进一步优化大豆生产、农机、服务、保险等环节的政策保障。同时, 应重点关注气候变化引发的干旱等自然风险, 健全农业领域自然灾害风险预警与防范机制, 以进一步强化大豆产业的综合风险抵御能力。

     

    Abstract: Sichuan Province is one of the 13 major grain-producing areas in China, as well as an important component of China’s emerging soybean planting area and southwest-producing area. Studies of soybean production patterns are crucial to Sichuan Province’simplementation of food security strategy and soybean industry development in Southwest China. This study analyzes the temporal and spatial evolution characteristics and driving factors of soybean production in China from 2000 to 2020 in Sichuan Province using the Gini coefficient, industrial concentration index, exploring spatial data analysis, and optimal parameters-based geographical detector. The findings were as follows: 1) From 2000 to 2020, soybean production in Sichuan Province fluctuated and increased, the spatial distribution was very uneven, and the agglomeration level increased and gradually concentrated in the hilly areas of central Sichuan. 2) There was a strong positive spatial correlation in soybean production, and the overall manifestations were high-high aggregation and low-low aggregation types. 3) The influences of resource elements, comparative income, geographical climate, and economic and social factors on soybean production pattern change were highly significant, and most of them showed the interaction effect of nonlinear enhancement and double factor interaction enhancement. Among them, the impact of resource input, comparative benefits, and altitude on soybean production pattern was relative high and fluctuating upward trend for a long time. The influence of temperature and rural household size increases rapidly, the influence of transportation conditions and regional GDP decreases, and the driving force of cropping pattern system is the weakest. Based on these results, soybean production in Sichuan Province should focus on breaking the resource and environmental constraints such as cultivated land fragmentation and rural labor shortage, vigorously developing the productive service industry, and comprehensively improving the mechanization level of soybean production. At the same time, it is necessary to strengthen the ability of scientific and technological innovation to improve the yield level of soybeans in Sichuan Province. Additionally, it is critical to further optimize the policy system of soybean production, agricultural machinery, socialized services, insurance, and other links. Finally, we should focus on natural risks, such as drought caused by climate change, and establish and improve the early warning and prevention mechanism of natural disaster risks of soybeans, to further strengthen the comprehensive risk resilience of the soybean industry in Sichuan Province.

     

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