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林业科学 ›› 2025, Vol. 61 ›› Issue (4): 196-214.doi: 10.11707/j.1001-7488.LYKX20240287

• 研究论文 • 上一篇    

中国林业经济韧性非均衡性及其影响因素

徐彩瑶1,2, 王朝勇2, 穆亚丽3, 孔凡斌3, 廖文梅4   

  1. 1. 浙江农林大学浙江省乡村振兴研究院/“千万工程”研究院 杭州311300;
    2. 浙江农林大学经济管理学院 杭州 311300;
    3. 南京林业大学数字林业与绿色发展研究院/经济管理学院 南京2100371;
    4. 江西农业大学“三农”问题研究中心/经济管理学院 南昌 330045
  • 收稿日期:2024-05-19 修回日期:2024-12-14 发布日期:2025-04-21
  • 通讯作者: 孔凡斌为通信作者。E-mail:kongfanbin@aliyun.com。
  • 基金资助:
    国家自然科学基金项目(42301328,42371294,42071283,72263017)。

Non-Equilibrium of China’s Forestry Economic Resilience and Its Influencing Factors

Xu Caiyao1,2, Wang Chaoyong2, Mu Yali3, Kong Fanbin3, Liao Wenmei4   

  1. 1. Rural Revitalization Academy of Zhejiang Province/Green Rural Revival Program Academy, Zhejiang A & F University Hangzhou 311300;
    2. College of Economics and Management, Zhejiang A & F University Hangzhou 311300;
    3. Institute of Digital Forestry and Green Development/College of Economics and Management, Nanjing Forestry University Nanjing 210037;
    4. Research Centre for Three Rural Issues/College of Economics and Management, Jiangxi Agricultural University Nanchang 330045
  • Received:2024-05-19 Revised:2024-12-14 Published:2025-04-21

摘要: 目的 在建设产业韧性强的林业强国背景下,探究中国林业经济韧性非均衡性特征及其影响因素,为林业高质量发展提供参考。方法 基于2011—2020年中国30个省域单元面板数据,构建林业经济韧性水平评价指标体系测度林业经济韧性水平,采用熵权法、空间自相关分析法、Dagum基尼系数分解法、Kernel密度估计法、空间收敛模型、地理探测器等方法探究中国林业经济韧性非均衡性特征及其影响因素。结果 1) 2011—2020年中国林业经济韧性水平总体呈增长态势,由2011年的3.19增至2020年的4.53,呈东南高、西北低的空间特征,空间集聚特征主要呈显著的高-高聚集、高-低聚集和低-高聚集。2) 2011—2020年中国林业经济韧性水平非均衡性逐渐扩大,Dagum基尼系数由2011年的0.306 5增至2020年的0.325 9。3) 基于东中西部分区的结果表明,超变密度和地区间差异是中国林业经济韧性非均衡性的主要影响因素;基于胡焕庸线分区的结果表明,地区内差异和地区间差异是中国林业经济韧性非均衡性的主要影响因素。4) 2011—2020年中国林业经济韧性水平不存在σ收敛特征,存在绝对β收敛和条件β收敛特征。基于东中西部分区的结果表明,中国及各地区林业经济韧性水平的条件β收敛速度快于绝对β收敛速度,且中部地区的条件β收敛速度最快;基于胡焕庸线分区的结果表明,胡焕庸线以西地区的收敛速度高于中国和胡焕庸线以东地区。5) 适应力、可持续性、产业协作性以及林业农药使用量、林下经济产值、林业旅游与休闲产业带动产值等是中国林业经济韧性水平变化的重要影响因素。结论 要大力发展绿色、生态和智慧林业,推动林业生态链、产业链和价值链提质增效,完善森林资源高水平保护和培育机制,提高林业适应不确定性风险的能力,科学发展森林旅游、森林康养和林下经济新业态,实现林业三产融合发展,积极服务区域经济,推动林业经济与区域经济协同发展。

关键词: 林业经济韧性, 非均衡性, 空间收敛, 地理探测器, 胡焕庸线

Abstract: Objective In the context of building a forestry power with strong industrial resilience, the characteristics of the non-equilibrium of forestry economic resilience in China and its influencing factors are explored to provide a scientific basis for the high-quality development of forestry.Method Based on the panel data of 30 provincial units in China from 2011 to 2020, the evaluation index system of forestry economic resilience level is constructed to measure the level of forestry economy resilience, and entropy weight method, spatial autocorrelation analysis, Dagum Gini coefficient decomposition method, Kernel density estimation method, spatial convergence model, and geographic detector are adopted to analysis the non-equilibrium characteristics of and its influencing factors of the forestry economy resilience in China.Result 1) The forestry economic resilience of China from 2011 to 2020 shows an overall growth trend, increasing from 3.19 in 2011 to 4.53 in 2020, with spatial characteristics of high in the southeast and low in the northwest. The spatial agglomeration characteristics mainly present significant high-high agglomeration, high-low agglomeration, and low-high agglomeration. 2) The forestry economic resilience of China gradually expanded from 2011 to 2020, and the Dagum Gini coefficient increased from 0.306 5 in 2011 to 0.325 9 in 2020. 3) The result based on the east-central-west zoning indicates that hypervariable density and inter-regional differences are the main influencing factors on the non-equilibrium of the forestry economic resilience of China. The result based on the Hu Huanyong line zoning shows that intra-regional and inter-regional differences are the main influencing factors of the non-equilibrium of the forestry economic resilience of China. 4) There is no σ-convergence feature, and there are absolute β-convergence and conditional β-convergence features in the forestry economic resilience of China from 2011 to 2020. The result based on the east-central-west zoning indicates the conditional β convergence of the forestry economic resilience of China. The conditional β convergence of each region is faster than the absolute β convergence, and the central region has the quickest rate of conditional β convergence. The result based on the Hu Huanyong line zoning shows the convergence speed of the west region of the Hu Huanyong line is higher than that of China and the eastern region of the Hu Huanyong line. 5) Adaptive capacity, sustainability, industrial multi-collaborative, forestry pesticide use, value of non-timber forest-based economy output, forestry tourism, and leisure industry driven output value are important influencing factors for the forestry economic resilience of China. Conclusion It is necessary to vigorously develop green, ecological, and intelligent forestry, promote the enhancement of the quality and efficiency of the forestry ecological chain, industrial chain, and value chain, improve the mechanism for high-level protection and cultivation of forest resources, improve the ability of forestry to adapt to the risk of uncertainty, scientifically develop new forms of forest tourism, forest recreation and non-timber forest-based economy, realize the integrated development of the three industries of forestry, actively serve the regional economy, and promote synergistic development of the forestry economy and the regional economy.

Key words: forestry economic resilience, non-equilibrium, spatial convergence, geographical detector, Hu Huanyong line

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