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Quantitative identification of altitudinal natural zones of mountain vegetation based on ecosystem multi-stable states — A case study of Bogda Mountain in Xinjiang

  • role： First author第一作者
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100049, China

    Shandong Agricultural University, Tai’an 271018, China

  • Email：wanhong@aircas.ac.cn
  • Introduction：万红， 研究方向为山地生态遥感。E-mail： wanhong@aircas.ac.cn
WAN Hong123,  
  • Affiliation：

    Shandong Agricultural University, Tai’an 271018, China

GUO Peng3,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Centre on Space Technologies for Natural and Cultural Heritage under the Auspices of UNESCO, Beijing 100094, China

LUO Lei14,  
  • Affiliation：

    Henan University of Technology, Zhengzhou 450001, China

ZHAO Yanchuang5,  
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    University of Chinese Academy of Sciences, Beijing 100049, China

ZHAO Yan12,  
  • role： Corresponding author通信作者
  • Affiliation：

    Aerospace Information Research Institute, Chinese Academy of Sciences, Beijing 100094, China

    International Centre on Space Technologies for Natural and Cultural Heritage under the Auspices of UNESCO, Beijing 100094, China

  • Email：wangxy@aircas.ac.cn
  • Introduction：王心源， 研究方向为空间考古、数字自然与文化遗产。E-mail： wangxy@aircas.ac.cn
WANG Xinyuan14*

Resümee

The distribution of altitudinal natural zones is closely related to the natural characteristics and service functions of mountain ecosystems. Quantitative identification of its elevation range can efficiently capture the results of the interaction between climate change and vegetation. Digital extraction and extensive analysis in such a critical elevation range is often restricted by the suitability of the experimental model and the spatial-temporal continuity of the data. In this study, temperate deserts, montane steppes, montane coniferous forests, alpine meadows and alpine cushion vegetation were considered as the stable state of the ecosystem. The land surface temperature was derived from the Landsat 8 Thermal Infrared Sensor data using the mono-window algorithm. Latent class analysis was conducted to test whether the remotely sensed indicator exhibited a multi-peak mode and to evaluate the number of states in an actual ecosystem. The potential energy of two adjacent states of the altitudinal natural zone was estimated by the potential energy analysis model, and the ecological transition range and demarcation elevation on the northern slope of Bogda Mountain were identified. The results showed that the frequency distribution of LST was bimodal, indicating the presence of distinct alternative modes. Moreover, the number of system modes changed from 1 to 2, and the AIC rapidly decreased. Both states revealed the existence of different ecosystem states. Second, potential energy analysis was used to identify the ecological transition area and demarcation elevation between adjacent altitudinal natural zones along the elevation gradient, temperate desert-montane steppes (transition range: 1062—1093 m, demarcation elevation: 1066 m), montane steppes-montane coniferous forests (transition range: 1689—1764 m, demarcation elevation: 1707 m), montane coniferous forests-alpine meadows (transition range: 2690—2744 m, demarcation elevation: 2714 m), and alpine meadows-alpine cushion vegetation (transition range: 3251—3263 m, demarcation elevation: 3257 m). Finally, the reliability of the results was verified by field survey data in July 2018, the overall RMSE was 17.19 m. In this study, the remotely sensed indicator and the principle of ecological stable states in combination with the potential energy analysis method provide a reference basis for quickly and accurately extracting the ecological transition range and demarcation elevation of the altitudinal natural zones.

Schlüsselwort

Vegetation altitudinal natural zones;ecosystem states;critical transitions;potential energy analysis;Bogda Mountain

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