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Spatial heterogeneity analysis of matching degree between endangered plant diversity and ecosystem services in **shuangbanna

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Abstract

Biodiversity and ecosystem services (ESs) are closely linked. Human activities have caused critical damage to the habitat and ecosystem function of organisms, leading to decline in global biodiversity and ecosystem services. To ensure sustainable development of local ecological environments, it is critical to analyze the spatial matching degree of biodiversity and ESs and identify ecologically vulnerable areas. Taking **shuangbanna, southern China, as an example, we constructed a pixel-scale matching degree index to analyze the spatial matching degree of endangered plant diversity (EPD) and four ESs and classified the matching degree into low-low, low-high, high-low, and high-high four types. The results revealed a mismatch relationship of EPD and ESs in more than 70% of areas. Under the influence of altitude and land use/land cover (LULC) type, the matching degree of EPD and ESs showed obvious spatial heterogeneity. In low-altitude areas in the south of **shuangbanna, EPD and ESs mainly showed mismatch, while high-altitude areas in the west had a better match. Natural forest was the main land cover in which EPD and ESs showed high-high match and its areal proportion was much larger than that of rubber plantation, tea plantation, and cropland. Our findings also stress the need to concentrate conservation efforts on areas exhibiting a low-low match relationship, indicative of potential ecological vulnerability. The pixel-scale spatial matching degree analysis framework developed in this study for EPD and ESs provides high-resolution maps with 30 m × 30 m pixel size, which can support the implementation of ecological protection measures and policy formulation, and has a wide range of applicability. This study provides valuable insights for the sustainable management of biodiversity and ESs, contributing to the strengthening of local ecological environment protection.

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Data availability

The datasets used and/or analyzed during the current study are available from the corresponding author on reasonable request.

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Funding

This research was supported by the Key Research Program of Frontier Sciences, CAS (Grant No. ZDBS-LY-7011), Key Program of National Social Science Foundation of China (Grant No. 17AZZ008), and International Cooperation and Exchange of the National Natural Science Foundation of China (Grant No. 51861125101).

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Authors and Affiliations

  1. Research Institute of Management Science, Business School, Hohai University, Nan**g, 211100, China

    Fan Zhang, Huimin Wang, Zhou Fang, Yang Yang, Yanling Zhi & Shiliang Yang

  2. Center for Integrative Conservation & Yunnan Key Laboratory for Conservation of Tropical Rainforests and Asian Elephants, **shuangbanna Tropical Botanical Garden, Chinese Academy of Sciences, Mengla, 666303, Yunnan, China

    Fan Zhang & Yang Bai

  3. State Key Laboratory of Hydrology Water Resource and Hydraulic Engineering, Hohai University, Nan**g, 210098, China

    Fan Zhang, Huimin Wang, Zhou Fang, Yanling Zhi & Shiliang Yang

  4. Environmental Science Center, Qatar University, P.O.Box: 2713, Doha, Qatar

    Juha M. Alatalo

  5. Yunnan International Joint Laboratory of Southeast Asia Biodiversity Conservation, Menglun, 666303, China

    Yang Bai

  6. Department of Economics and Management, Tian** University, Tian**, 300072, China

    Gang Liu

Authors
  1. Fan Zhang
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Contributions

Fan Zhang: conceptualization, writing—original draft preparation, methodology. Huimin Wang: conceptualization, writing—original draft preparation. Juha M. Alatalo: methodology. Yang Bai: conceptualization, writing—original draft preparation. Zhou Fang: methodology, software. Gang Liu: methodology. Yang Yang: visualization. Yanling Zhi: investigation. Shiliang Yang: data curation.

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Correspondence to Yang Bai.

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Zhang, ., Wang, H., Alatalo, J.M. et al. Spatial heterogeneity analysis of matching degree between endangered plant diversity and ecosystem services in **shuangbanna. Environ Sci Pollut Res 30, 96891–96905 (2023). https://doi.org/10.1007/s11356-023-29172-7

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