Author
Listed:
- Jing Lin
(Northwest A&F University)
- Wenhao Bo
(Northwest A&F University)
- Xinping Dong
(Northwest A&F University)
- Ruiwan Zhang
(Northwest A&F University)
- Junping Yan
(Long County Agricultural Technology Promotion Center)
- Tao Chen
(Northwest A&F University
Ministry of Agriculture and Rural Affairs)
Abstract
Studying the vegetation dynamics and driving mechanisms in ecologically fragile areas is crucial for understanding the process of ecosystem evolution and achieving sustainable development. This study focused on the entire Mu Us Sandy Land (MUSL) and utilized the variation coefficient, trend analysis, and Hurst index to investigate the spatio-temporal variation in fractional vegetation cover (FVC) and its sustainability characteristic from 2000 to 2020. Meanwhile, residual analysis was employed to separate the impact of climatic factors such as temperature and precipitation, as well as anthropogenic factors, on FVC change. The results showed that FVC of MUSL was lower in the northwest and higher in the southeast. Over the past 21 years, the average annual FVC value increased from a low of 0.3486 in 2000 to a high of 0.6186 in 2018, with a growth rate of 0.0996/10a. Overall, the vegetation condition of MUSL has improved, with about 70.10% of the region having a significant increase in FVC, mainly concentrated in the southeast, while FVC decrease mainly occurred in the northwest. However, the majority of these FVC changes exhibited an anti-persistence characteristic, indicating that future FVC growth in many regions was fraught with uncertainty. Human activities accounted for 70.71% of FVC change, while climate factors contributed only 29.29%, indicating that the former dominated this ecological process. In this arid and fragile area, precipitation had a greater impact on FVC than temperature. This study illustrates the dominant role of ecological engineering in vegetation greening in MUSL, while also pointing out the unsustainable risk of the restoration mode, which provides a theoretical basis for adjusting and optimizing future management strategies.
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