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应用生态学报 ›› 2024, Vol. 35 ›› Issue (3): 769-779.doi: 10.13287/j.1001-9332.202403.022

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吉林省生态系统服务价值与景观生态风险关联性及其空间分异

梁仕豪1, 李文1*, 高宇2, 刘保住1   

  1. 1东北林业大学园林学院, 哈尔滨 150040;
    2黑龙江省森林保护研究所, 哈尔滨 150040
  • 收稿日期:2023-09-20 修回日期:2024-01-15 出版日期:2024-03-18 发布日期:2024-06-18
  • 通讯作者: *E-mail: liwen@nefu.edu.cn
  • 作者简介:梁仕豪, 男, 1997年生, 硕士研究生。主要从事生态系统服务与景观格局研究。E-mail: liangshihao1997@163.com
  • 基金资助:
    黑龙江省自然科学基金联合引导性项目(LH2022E001)

Correlations between ecosystem service value and landscape ecological risk and its spatial heterogeneity in Jilin Province, China

LIANG Shihao1, LI Wen1*, GAO Yu2, LIU Baozhu1   

  1. 1College of Landscape Architecture, Northeast Forestry University, Harbin 150040, China;
    2Heilongjiang Forest Protection Research Institute, Harbin 150040, China
  • Received:2023-09-20 Revised:2024-01-15 Online:2024-03-18 Published:2024-06-18

摘要: 探究生态系统服务价值与景观生态风险之间的相关性及其空间分异的驱动因子,有助于维护区域生态安全的稳定并促进人类福祉的持续创造。本研究以吉林省为例,基于5 km×5 km的评价单元,对2000、2005、2010、2015、2020年土地利用数据进行网格化和重采样,定量评价研究区的景观生态风险和生态系统服务价值,揭示其时空变化特征,并采用双变量空间自相关分析方法和地理探测器模型揭示二者的相关性及其空间分异的驱动因子。结果表明: 2000—2020年间,研究区生态系统服务价值总量由3858.95亿元下降至3782.11亿元。研究区东部以极低风险区、中风险区和低风险区为主,西部以极高风险区和高风险区为主。吉林省景观生态风险与生态系统服务价值间呈现出显著的负相关性以及显著的空间负相关性。土地利用类型和人为影响指数是促使研究区生态系统服务价值和景观生态风险产生空间分异的重要驱动因子。未来应通过合理规范土地利用和合理控制人为活动强度对吉林省进行生态环境优化。

关键词: 生态系统服务价值, 景观生态风险, 空间自相关, 吉林省

Abstract: Exploring the correlations between ecosystem service value (ESV) and landscape ecological risk and the driving factors of their spatial variations is crucial for maintaining regional ecological security and promoting sustainable human well-being. We carried out a grid resampling size of 5 km×5 km assessment units of Jilin Pro-vince based on the remote sensing monitoring data of land use in 2000, 2005, 2010, 2015, and 2020. We quantitatively evaluated the landscape ecological risk and ESV, and analyzed their spatial-temporal variations. Employing bivariate spatial autocorrelation analysis and the geographical detector models, we examined the correlation between the landscape ecological risk and ESV and explored the driving factors for their spatial variations. The results showed that ESV in Jilin Province decreased from 385.895 billion yuan to 378.211 billion yuan during 2000-2020. The eastern region was dominated by extremely low risk, medium risk, and low risk areas. In contrast, the western region was mainly composed of extremely high risk and high risk areas. There was a significant negative correlation and spatial negative correlation between landscape ecological risk and ESV in Jilin Province. Human activity and land use type were the important driving factors for spatial differentiation in both landscape ecological risk and ESV. Our findings suggested that scientific land use regulation and appropriate control of human activities are critically needed to optimize Jilin Province’s ecological environment.

Key words: ecosystem service value, landscape ecological risk, spatial autocorrelation, Jilin Province