QIN Hui-yan, LIU Ting-ting, HUANG Ying-li. Evaluation and Sensitivity Analysis of Forest Ecosystem Resilience at Provincial Scale in China[J]. Journal of Ecology and Rural Environment, 2022, 38(3): 281-288. DOI: 10.19741/j.issn.1673-4831.2021.0465
    Citation: QIN Hui-yan, LIU Ting-ting, HUANG Ying-li. Evaluation and Sensitivity Analysis of Forest Ecosystem Resilience at Provincial Scale in China[J]. Journal of Ecology and Rural Environment, 2022, 38(3): 281-288. DOI: 10.19741/j.issn.1673-4831.2021.0465

    Evaluation and Sensitivity Analysis of Forest Ecosystem Resilience at Provincial Scale in China

    • Studying the resilience of forest ecosystems at the provincial scale in China and quantifying the impact of each index weight on resilience could provide a decision-making foundation for sustainable forest management at the macroscale. This paper constructed a provincial-scale forest ecological resilience evaluation index system based on the ecological pressure-state-response model from the two aspects of vulnerability and adaptive capacity and adopted the OAT (one-at-a-time) method to quantify the weight of each index's impact on the assessment results of forest ecosystem resilience. The results show that the average values of the vulnerability, adaptive capacity and resilience index of the forest ecosystem were 0.309, 0.323 and 0.320, respectively; the impact of forest ecosystem response capacity on forest ecosystem resilience was higher than that of forest ecosystem vulnerability, with coefficients of 0.720 and 0.280, respectively. Accumulation per unit area, the control rate of rodent damage and the restoration area of degraded forests were the most sensitive factors to forest ecosystem resilience, while fire prevention investment, the area of closed hills for afforestation and investment in forest management were less sensitive. Overall, the resilience level of the provincial forest ecosystem was relatively low, and the evaluation results of forest ecosystem resilience were generally and relatively stable, which indicates that the weights initially determined by the entropy method are reasonable.
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