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Spatial (Mis)Matches Between Biodiversity and Habitat Quality Under Multi-Scenarios: A Case Study in Shandong Province, Eastern China

Author

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  • Xiaoyin Sun

    (Key Laboratory of Nansihu Lake Wetland Ecological Conservation & Environmental Protection (Shandong Province), College of Geography and Tourism, Qufu Normal University, Rizhao 276826, China)

  • Ruifeng Shan

    (Key Laboratory of Nansihu Lake Wetland Ecological Conservation & Environmental Protection (Shandong Province), College of Geography and Tourism, Qufu Normal University, Rizhao 276826, China)

  • Qingxin Luan

    (Key Laboratory of Nansihu Lake Wetland Ecological Conservation & Environmental Protection (Shandong Province), College of Geography and Tourism, Qufu Normal University, Rizhao 276826, China)

  • Yuee Zhang

    (Key Laboratory of Nansihu Lake Wetland Ecological Conservation & Environmental Protection (Shandong Province), College of Geography and Tourism, Qufu Normal University, Rizhao 276826, China)

  • Zhicong Chen

    (Jining Planning and Design Institute, Jining 272100, China)

Abstract

Despite declines in biodiversity and habitat quality (HQ) at a global scale, our understanding of the HQ and matches between HQ and biodiversity under management scenarios is incomplete. To address this deficiency, the study examined trends in HQ and (mis)matches between biodiversity and HQ over four decades in Shandong province, China, identified the key drivers, and assessed the effectiveness of ecological policies, including Ecological Redlines (ERLs) and the Grain for Green (GG) program. During the 40-year period, HQ and matching degrees (indicated by related coefficients) between biodiversity and HQ decreased obviously. Correlation analysis showed that related coefficients between HQ and four biodiversity indices (vertebrate, vascular plant, and vegetation formation type richness, and comprehensive biodiversity index) were all significant ( p < 0.01), and coefficients were highest for the biodiversity composite index. An analysis of relative importance by the random forest algorithm indicated significant variation in driving factors for spatial distribution of HQ, biodiversity, and matches between them. The key determinants of biodiversity distribution were biophysical factors, such as NDVI (normalized difference vegetation index), DEM (digital elevation model), and temperature. However, the main drivers of HQ distribution were social factors, such as the accessibility of anthropogenic activities, urbanization, and population density. Ecological policy scenarios, ERLs and GG, are clearly effective and could improve HQ and the matching degree between HQ and biodiversity significantly. Furthermore, the improvement in HQ under ERLs was less than that under GG, while the increase in the matching degree was opposite. The results of this study can be integrated by ecological managers and planners for biodiversity conservation.

Suggested Citation

  • Xiaoyin Sun & Ruifeng Shan & Qingxin Luan & Yuee Zhang & Zhicong Chen, 2024. "Spatial (Mis)Matches Between Biodiversity and Habitat Quality Under Multi-Scenarios: A Case Study in Shandong Province, Eastern China," Land, MDPI, vol. 13(12), pages 1-13, December.
  • Handle: RePEc:gam:jlands:v:13:y:2024:i:12:p:2215-:d:1546339
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    References listed on IDEAS

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    1. Upadhaya, Suraj & Dwivedi, Puneet, 2019. "Conversion of forestlands to blueberries: Assessing implications for habitat quality in Alabaha river watershed in Southeastern Georgia, United States," Land Use Policy, Elsevier, vol. 89(C).
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