干旱区地理2026，Vol.49Issue(7)：1470-1480,11.DOI:10.12118/j.issn.1000-6060.2025.625
中国农业韧性空间关联网络特征及驱动因素识别
Characteristics of agricultural resilience spatial correlation network and identification of driving factors in China
摘要
Abstract
Based on panel data from 30 provinces,autonomous regions,and municipalities in China from 2014 to 2023,this study employs the entropy weight method,social network analysis,and exponential random graph mod-els to systematically examine the structural characteristics and driving factors of the spatial correlation network of agricultural resilience in China.The results indicate that(1)Agricultural resilience shows a steady upward trend,although development across dimensions remains uneven.Economic and social resilience perform relatively well,whereas production and ecological resilience lag behind.(2)The spatial correlation network of agricultural resilience exhibits a flat development trend.Although the overall network remains highly accessible,close corre-lations have not yet formed,and most provinces,autonomous regions,and municipalities maintain one-way corre-lations.(3)The spatial correlation follows a"west-central-east"radiation path.Net spillover sectors are mainly concentrated in the central and western regions,whereas net benefit sectors are primarily distributed in the central and eastern regions,and the broker sector still requires substantial improvement.(4)The formation of spatially correlated networks of agricultural resilience in China results from the interplay of endogenous structures,actor attributes,and external environments.Endogenous structures such as reciprocity and circularity promote the for-mation of the agricultural resilience network.Economic level,production conditions,industrial structure,and ex-treme heavy rainfall are the core driving forces for the formation of the agricultural resilience network,while geo-graphical proximity and trade are important external driving forces.关键词
农业韧性/空间关联网络/社会网络分析法/指数随机图模型Key words
agricultural resilience/spatial correlation network/social network analysis/exponential random graph model引用本文复制引用
芦风英,滕圣钰,邓光耀..中国农业韧性空间关联网络特征及驱动因素识别[J].干旱区地理,2026,49(7):1470-1480,11.基金项目
国家自然科学基金项目(72363021) （72363021）
甘肃省基础研究计划-软科学专项一般项目(26JRZA085) （26JRZA085）
甘肃省高校教师创新基金项目(2026B-107) （2026B-107）
兰州财经大学校级科研项目(Lzufe2024C-009)资助 （Lzufe2024C-009）
