Zhou Zhaoqiang, Liu Suning, Ding Yibo, Fu Qiang, Wang Yao, Cai Hejiang, Shi Haiyun
State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China.
State Environmental Protection Key Laboratory of Integrated Surface Water-Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Guangdong Provincial Key Laboratory of Soil and Groundwater Pollution Control, School of Environmental Science and Engineering, Southern University of Science and Technology, Shenzhen, Guangdong, China; Center for Climate Physics, Institute for Basic Science, Busan, Republic of Korea.
J Environ Manage. 2022 Jun 1;311:114879. doi: 10.1016/j.jenvman.2022.114879. Epub 2022 Mar 15.
The increase in drought frequency in recent years is considered as an important factor affecting vegetation diversity. Understanding the responses of vegetation dynamics to drought is helpful to reveal the behavioral mechanisms of terrestrial ecosystems and propose effective drought control measures. In this study, long time series of Normalized Difference Vegetation Index (NDVI) and Solar-induced chlorophyll fluorescence (SIF) were used to analyze the vegetation dynamics in the Pearl River Basin (PRB). The relationship between vegetation and meteorological drought was evaluated, and the corresponding differences among different vegetation types were revealed. Based on an improved partial wavelet coherence (PWC) analysis, the influences of teleconnection factors (i.e., large-scale climate patterns and solar activity) on the response relationship between meteorological drought and vegetation were quantitatively analyzed to determine the roles of factors. The results indicate that (a) vegetation in the PRB showed an increasing trend from 2001 to 2019, and the SIF increased more than that of NDVI; (b) the vegetation response time (VRT) based on NDVI (VRT) was typically 4-6 months, while the VRT based on SIF (VRT) was typically 2-4 months. The VRT was shortest in the woody savannas and longest in the evergreen broadleaf forests. (c) The relationship between the SIF and meteorological drought was more significant than that between the NDVI and meteorological drought. (d) There was a significant positive correlation between meteorological drought and vegetation in the period of 8-20 years. The El Niño Southern Oscillation (ENSO), Pacific Decadal Oscillation (PDO) and sunspots were important driving factors affecting the response relationship between drought and vegetation. Specifically, the PDO had the greatest impacts among these factors.
近年来干旱频率的增加被认为是影响植被多样性的一个重要因素。了解植被动态对干旱的响应有助于揭示陆地生态系统的行为机制,并提出有效的干旱控制措施。在本研究中,利用长时间序列的归一化植被指数(NDVI)和太阳诱导叶绿素荧光(SIF)来分析珠江流域(PRB)的植被动态。评估了植被与气象干旱之间的关系,并揭示了不同植被类型之间的相应差异。基于改进的偏小波相干(PWC)分析,定量分析了遥相关因子(即大尺度气候模式和太阳活动)对气象干旱与植被响应关系的影响,以确定各因子的作用。结果表明:(a)珠江流域的植被在2001年至2019年呈增加趋势,且SIF的增加幅度大于NDVI;(b)基于NDVI的植被响应时间(VRT)通常为4-6个月,而基于SIF的VRT通常为2-4个月。VRT在木本稀树草原中最短,在常绿阔叶林中最长。(c)SIF与气象干旱之间的关系比NDVI与气象干旱之间的关系更显著。(d)在8-20年期间,气象干旱与植被之间存在显著正相关。厄尔尼诺-南方涛动(ENSO)、太平洋年代际振荡(PDO)和太阳黑子是影响干旱与植被响应关系的重要驱动因素。具体而言,PDO在这些因素中影响最大。