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Effects of climate change and anthropogenic activity on the vegetation greening in the Liaohe River Basin of northeastern China

归一化差异植被指数 植被(病理学) 环境科学 植树造林 绿化 自然地理学 城市化 气候变化 降水 生态学 地理 农林复合经营 医学 生物 病理 气象学
作者
Liya Zhu,Shuang Sun,Yang Li,Xingbao Liu,Ke Hu
出处
期刊:Ecological Indicators [Elsevier BV]
卷期号:148: 110105-110105 被引量:75
标识
DOI:10.1016/j.ecolind.2023.110105
摘要

Elucidating the response mechanism of variation in vegetation trend to determinant is of great value to environmental resource management, particularly significant in the ecologically fragile area. The Liaohe River Basin (LRB) is a key part of eco-security in China, which has experienced apparent climatic variations and intensified human activities in recent decades. Yet, it still remains not clear about drivers in shaping the spatio-temporal patterns of vegetation growth. Here, the normalized difference vegetation index (NDVI) was utilized to investigate the spatio-temporal variation of vegetation coverage from 2000 to 2019. Then, we incorporated partial derivatives analysis to conduct attribution analyses of vegetation greening in light of the meteorological data. The prime findings are as follows: (1) The vegetation coverage in the LRB presented a growing state in the recent 20 years at a rate of 0.0031/a, with significant spatial and temporal heterogeneity due to its slope; (2) The attribution results showed that the average contribution of precipitation, temperature, and solar radiation to the NDVI changes in the LRB was 0.00205/a, 0.00008/a, and −0.00028/a, respectively. (3) The climatic change played the most dominant role in influencing vegetation activities as a result of the relative contributions of 59.68% of NDVI changes (40.32% contributed by anthropogenic activities); (4) LULC dynamics were characterized by an increase in forest land and large-scale ecological afforestation projects, which increase vegetation coverage. Conversely, urbanization adversely affected vegetation variations. Understanding the findings of this study is expected to offer further scientific support and practical implications for monitoring the local vegetation status.
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