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Quantifying Degradation Classifications on Alpine Grassland in the Lhasa River Basin, Qinghai-Tibetan Plateau

Author

Listed:
  • Wangya Han

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Huiting Lu

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Guohua Liu

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

  • Jingsheng Wang

    (Key Laboratory of Ecosystem Network Observation and Modeling, Institute of Geographic Sciences and Natural Resources Research, Chinese Academy of Sciences, Beijing 100101, China)

  • Xukun Su

    (State Key Laboratory of Urban and Regional Ecology, Research Center for Eco-Environmental Sciences, Chinese Academy of Sciences, Beijing 100085, China
    College of Resources and Environment, University of Chinese Academy of Sciences, Beijing 100049, China)

Abstract

The Qinghai-Tibetan Plateau (QTP) has the world’s largest alpine grassland ecosystem. The QTP ecosystem is extremely fragile and suffers continuous degradation. An accurate determination of the status of alpine grassland is the first crucial step in monitoring its degradation. A novel method combining field survey with remote sensing information based on ecological indicators is proposed. The degradation classification of alpine grassland was identified by multivariate hierarchical analysis based on 270 field plots. The spatial pattern of alpine grassland degradation was mapped by determining remote sensing variables that corresponded to field indicators of the degradation classification system. The results showed that clustering analysis divided the degradation classification of alpine grassland into five classes: Non-Degraded (ND), Slightly Degraded (SLD), Moderately Degraded (MD), Severely Degraded (SD), and Extremely Degraded (ED). The most significant factors for alpine grassland degradation included the dominance of Cyperaceae plants, soil total nitrogen content, soil organic carbon content, soil total carbon content, soil bulk density, soil pH, dominance of miscellaneous plants, and elevation among all 17 variables. The assessment and mapping of alpine grassland degradation provide an important basis for alpine grassland protection and management, particularly at a large scale.

Suggested Citation

  • Wangya Han & Huiting Lu & Guohua Liu & Jingsheng Wang & Xukun Su, 2019. "Quantifying Degradation Classifications on Alpine Grassland in the Lhasa River Basin, Qinghai-Tibetan Plateau," Sustainability, MDPI, vol. 11(24), pages 1-14, December.
    • Handle: RePEc:gam:jsusta:v:11:y:2019:i:24:p:7067-:d:296279
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    References listed on IDEAS

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    1. Gellrich, Mario & Baur, Priska & Robinson, Brett Harvey & Bebi, Peter, 2008. "Combining classification tree analyses with interviews to study why sub-alpine grasslands sometimes revert to forest: A case study from the Swiss Alps," Agricultural Systems, Elsevier, vol. 96(1-3), pages 124-138, March.
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    Cited by:

    1. Sishi Wang & Xin Tan & Fenglei Fan, 2023. "Changes in Impervious Surfaces in Lhasa City, a Historical City on the Qinghai–Tibet Plateau," Sustainability, MDPI, vol. 15(6), pages 1-16, March.

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