Temporal and spatial variation characteristics of vegetation coverage and quantitative analysis of its potential driving forces in the Qilian Mountains, China, 2000–2020

植被(病理学) 归一化差异植被指数 驱动因素 环境科学 自然地理学 仰角(弹道) 地形地貌 日照时长 中国 气候变化 生态学 地理 气象学 降水 病理 考古 生物 医学 数学 几何学 地图学
作者
Yafan Zuo,Yuanhang Li,Kangning He,Yusheng Wen
出处
期刊:Ecological Indicators [Elsevier BV]
卷期号:143: 109429-109429 被引量:59
标识
DOI:10.1016/j.ecolind.2022.109429
摘要

Vegetation is an important indicator reflecting ecological environment stability, and monitoring vegetation change and understanding its potential driving force have important guiding significance for the adjustment and implementation of ecological restoration measures. As an ecological security barrier in northwest China, the Qilian Mountains (QLMs) play an important role in promoting the green development of social and economic development. Currently, the comprehensive driving effects of natural and anthropogenic factors on vegetation change in the QLMs are not clear. Based on the normalized difference vegetation index (NDVI), the spatiotemporal characteristics and trend changes in vegetation in the QLMs were systematically analyzed from 2000 to 2020 in this paper. The effects of natural and anthropogenic driving factors on vegetation change were explored using a geographic detector (GeoDetector). The results showed that the vegetation has improved continuously in the past 21 years, but the overall vegetation coverage was still low. The vegetation distribution was highly clustered, with a decreasing trend from east to west. Annual sunshine duration (q statistic = 0.3347) and distance to the rivers (q statistic = 0.2649) had the greatest explanatory power for vegetation change, while slope, aspect, and landform type had the least explanatory power. The interaction between elevation and sunshine duration, temperature and precipitation, temperature and sunshine duration, elevation and precipitation had the most explanatory power for vegetation change. Finally, we determined the ranges or categories of driving factors that were most suitable for vegetation growth by using a risk detector. The results of this study can help us further understand the potential driving mechanism of vegetation coverage variation in the QLMs and provide theoretical guidance for relevant managers to formulate ecological restoration measures and land management policies in the next step. It is of great significance to maintain the stability of the fragile ecological environment and prevent land degradation in arid and semiarid areas of Northwest China.
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