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| 东北粮食主产区农业绿色发展水平时空演化及其影响因素 | |
| 引用本文： | 盖美,杨苘菲,何亚宁.东北粮食主产区农业绿色发展水平时空演化及其影响因素[J].资源科学,2022,44(5):927-942. |
| 作者姓名： | 盖美 杨苘菲 何亚宁 |
| 作者单位： | 1.辽宁师范大学海洋可持续发展研究院,大连 116029 2.辽宁省“海洋经济高质量发展”高校协同创新中心,大连 116029 |
| 基金项目： | 辽宁省社会科学规划基金重点项目(L20ATJ001) |
| 摘 要： | 厘清东北粮食主产区农业绿色发展水平的时空演化特征及影响因素,可为推进区域农业绿色发展提供参考依据。本文基于2010—2019年中国东北粮食主产区37个地级市数据,采用可变模糊识别模型、核密度估计模型以及空间杜宾模型对东北粮食主产区农业绿色发展水平进行测度,并探究其时空演化特征及影响因素。结果表明：①总体来看,农业绿色发展水平整体呈上升趋势,但仍处于中等水平。空间上存在一定的分级现象,较高水平地级市相对较多,且主要集中于黑龙江省。②分维度来看,时间上,2010—2019年各维度均呈不同程度的上升趋势,其中农业经济活力增长幅度最大,达到35.63%;农业科技创新增长幅度最小,仅达到0.61%。空间上,农业科技创新的基尼系数和变异系数呈下降趋势,其他维度空间异质性显著,发展不均衡。③经济发展、国际贸易和信息沟通对东北粮食主产区农业绿色发展存在显著的促进作用,而工业化水平对其存在显著的抑制作用。此外,人口密度和工业化水平存在显著的空间负溢出效应。最后,根据研究结论并结合各区域农业绿色发展现状,针对性地提出了政策建议。 |
| 关 键 词： | 农业绿色发展 影响因素 可变模糊识别模型 空间杜宾模型 东北粮食主产区 |
| 收稿时间： | 2021-10-12 |
| 修稿时间： | 2022-01-10 |
Spatiotemporal changes and influencing factors of agricultural green development level in main grain-producing areas in Northeast China |
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| GAI Mei,YANG Qingfei,HE Yaning.Spatiotemporal changes and influencing factors of agricultural green development level in main grain-producing areas in Northeast China[J].Resources Science,2022,44(5):927-942. | |
| Authors: | GAI Mei YANG Qingfei HE Yaning |
| Institution: | 1. Institute of Marine Sustainable Development, Liaoning Normal University, Dalian 116029, China 2. University Collaborative Innovation Center of Marine Economy High-Quality Development of Liaoning Province, Dalian 116029, China |
| Abstract: | Clarifying the spatial and temporal change characteristics and factors that influence the level of agricultural green development in the main grain-producing regions of Northeast China can provide a reference basis for promoting regional agricultural green development. Based on the data of 37 cities in the main grain-producing areas in Northeast China from 2010 to 2019, this study used variable fuzzy recognition model, kernel density estimation model, and spatial Durbin model to measure the level of agricultural green development in the region. The temporal and spatial change characteristics and influencing factors were also explored. The results show that: (1) Temporally, the agricultural green development level showed an overall upward trend, but it is still at a medium development level. Spatially, there is a certain differentiation across the region. There are many cities with relatively high-level development, and they are mainly found in Heilongjiang Province. (2) Each dimension of agricultural green development has shown an upward trend to varying degrees from 2010 to 2019, among them, agricultural economic vitality grew the most, reaching 35.63%; agricultural science and technology innovation grew the least, reaching only 0.61%. The Gini index and coefficient of variation of agricultural technological innovation across the region showed a downward trend, the spatial heterogeneity of other dimensions is significant, and the development is uneven across space. (3) There is a significant contribution of economic development, international trade and information communication to the agricultural green development in the main grain-producing regions of Northeast China, while there is a significant inhibitory effect of industrialization level. In addition, there is a significant negative spatial spillover effect of population density and industrialization level. Finally, based on the research findings and combined with the current situation of agricultural green development in each subregion, targeted policy recommendations were proposed. |
| Keywords: | agricultural green development influencing factors variable fuzzy recognition model spatial Durbin model main grain-producing areas in Northeast China |
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