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云南省县域农业生态效率时空分异及其影响因素

SPATIAL-TEMPORAL DIFFERENTIATION AND INFLUENCING FACTORS OF AGRICULTURAL ECOLOGICAL EFFICIENCY IN COUNTIES OF YUNNAN PROVINCE
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摘要 [目的]云南省地形起伏度大,立体气候资源丰富,高原特色农业优势明显,测度其农业生态效率,并从农业生产条件、社会经济和自然生态环境3个维度选取10个驱动因子分析其对农业生态效率的影响程度。[方法]文章运用超效率的SBM模型,基于2008—2018年云南省129个县(市、区)农业面板数据,测度县域农业生态效率,结合空间自相关模型和地理探测器模型,对云南省县域农业生态效率的时空演变、空间异质性及其影响因素进行实证研究。[结果](1)云南省县域农业生态效率整体处于中等效率水平,但呈波动下降趋势;空间上呈东西部、南北部相对高、中部低的“U”型分布格局,且东西差异大于南北差异。(2)从全局空间自相关来看,云南省县域农业生效率正相关和波动性空间集聚特征显著;从局部空间自相关来看,农业生态效率空间正相关的县域数量在逐年递减,集聚性呈下降趋势。农业生态效率高高(HH)集聚主要分布在云南省西北部及南部,向邻接县域扩散的趋势明显;低低(LL)集聚主要分布在云南省中部和东南部。(3)从影响因素看,社会经济因素仍是目前农业生态效率主要影响因素,但其作用强度不断下降,自然环境因素特别是地形起伏度解释力不断上升,不同驱动因子对其空间分异的影响差异明显,且驱动因子交互作用会增强农业生态效率空间分异。[结论]云南省县域农业生态效率时空分异显著,社会经济因素是农业生态效率空间分异的主要影响因素,但地形起伏度、降水等自然生态环境因素对农业生态效率影响程度明显提升。 The terrain of Yunnan province is rugged,rich in three-dimensional climate resources,and has obvious advantages in plateau characteristic agriculture.In this paper,the agricultural ecological efficiency of Yunnan province is measured using the super efficiency SBM model,and ten driving factors are selected from three dimensions:agricultural production conditions,socio-economics,and natural ecological environment to analyze their impact on agricultural ecological efficiency.Based on panel data of 129 counties(cities,districts)in Yunnan province from 2008 to 2018,combining spatial autocorrelation models and geographic detectors,this paper conducted an empirical study on spatial-temporal evolution,spatial heterogeneity and influencing factors of agricultural ecological efficiency in counties of Yunnan province.The results were listed as follows.(1)The overall agricultural ecological efficiency of counties in Yunnan province was at a medium level with a downward trend,and presented a"U"-shaped distribution pattern with relatively high efficiency in the eastern,western,and northern parts,and low efficiency in the central part,with greater differences between east-west than north-south.(2)From the perspective of global spatial autocorrelation,there were significant positive correlations and spatial clustering of fluctuation in agricultural ecological efficiency among counties in Yunnan province.From the perspective of local spatial autocorrelation,the number of counties with positive correlation of agricultural ecological efficiency was gradually decreasing,and the aggregation was decreasing.The High-High(HH)aggregation of agricultural ecological efficiency was mainly distributed in the northwest and south of Yunnan province,and showed an obvious trend of spreading to adjacent counties;the Low-Low(LL)aggregation was mainly distributed in the central and southeast parts of Yunnan province.(3)In terms of influencing factors,socio-economic factors were still the main influencing factors of agricultural ecological efficiency,but their impact was continuously decreasing,while the explanatory power of natural ecological environment factors,especially terrain ruggedness,was increasing.In summary,The impact of different driving factors on spatial differentiation is significant,and the interaction of driving factors can enhance the spatial differentiation of agricultural ecological efficiency.The spatial-temporal differentiation of agricultural ecological efficiency in counties of Yunnan province is significant,and socioeconomic factors are the main driving factors for spatial differentiation.However,natural ecological environment factors,such as terrain ruggedness and precipitation,have a more significant impact on agricultural ecological efficiency.
作者 宁发金 鲁茸拉木 杜发春 Ning Fajin;Lu Ronglamu;Du Fachun(Markism College of Yunnan Agricultural University,Kunming 650500,Yunnan,China;Institute of New Rural Development of Yunnan Agricultural University,Kunming 650500,Yunnan,China;Training Department of Yunnan Academy of Social Sciences,Kunming 650034,Yunnan,China)
出处 《中国农业资源与区划》 CSCD 北大核心 2024年第2期49-61,共13页 Chinese Journal of Agricultural Resources and Regional Planning
基金 国家社科基金一般项目“中缅边境抵边村寨治理中的境内外影响及对策研究”(21BMZ109)。
关键词 农业生态效率 超效率SBM模型 地理探测器 时空分异 影响因素 agricultural ecological efficiency super-efficient SBM model geodetector spatiotemporal differenti⁃ation influencing factors
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