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Arid Land Geography >

2023 , Vol. 46 >Issue 4: 614 - 624

DOI: https://doi.org/10.12118/j.issn.1000-6060.2022.302

Plant Ecology

Vegetation dynamic and its driving force and multi-scenario prediction in Otindag Sandy Land

  • Jiayan LUO ,
  • Jing ZHANG ,
  • Mengran XU ,
  • Yu MO ,
  • Liga TONG
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  • 1. College of Environment and Resources, Dalian Minzu University, Dalian 116600, Liaoning, China
    2. College of Architecture, Dalian Minzu University, Dalian 116650, Liaoning, China

Received date: 2022-06-21

  Revised date: 2022-08-15

  Online published: 2023-04-28

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Abstract

In the context of future global warming, the vegetation in arid and semi-arid regions in China is more sensitive, and the balance between economic development and environmental protection remains challenging. Therefore, it is essential to conduct dynamic monitoring and driving factors assessment of vegetation in those areas. In this study, the spatiotemporal variation of NDVI in Otindag Sandy Land from 2000 to 2020 was first analyzed using Theil-Sen median trend analysis; next, the driving mechanism of NDVI change was analyzed using the Geodetector model. Finally, multiscenario analysis was used to reveal the future change trajectories of vegetation in the area. The results showed that the NDVI of Otindag Sandy Land exhibited upward fluctuation trends within 20 years, and grazing is the main factor affecting the changes in NDVI in Otindag Sandy Land; however, the effect of grazing to NDVI dynamics in the Otindag Sandy Land gradually weakened. In addition, the multiscenario prediction results show that, although the vegetation of Otindag Sandy Land is developing toward restoration, its fragile ecological environment and the vegetation status were still threatened by human activities and climate change. This study provides a theoretical basis for the Otindag Sandy Land ecological construction and restoration, as well as relevant countermeasures and suggestions according to the actual situation.

Key words： trend analysis; geodetector; multi-scenario prediction; NDVI; Otindag Sandy Land

Cite this article

Jiayan LUO , Jing ZHANG , Mengran XU , Yu MO , Liga TONG . Vegetation dynamic and its driving force and multi-scenario prediction in Otindag Sandy Land[J]. Arid Land Geography, 2023 , 46(4) : 614 -624 . DOI: 10.12118/j.issn.1000-6060.2022.302

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