Comprehensive evaluation of vegetation responses to meteorological drought from both linear and nonlinear perspectives

Abstract

The frequent occurrence of drought events in recent years has caused significant changes in plant biodiversity. Understanding vegetation dynamics and their responses to climate change is of great significance to reveal the behaviour mechanism of terrestrial ecosystems. In this study, NDVI and SIF were used to evaluate the dynamic changes of vegetation in the Pearl River Basin (PRB). The relationship between vegetation and meteorological drought in the PRB was evaluated from both linear and nonlinear perspectives, and the difference of vegetation response to meteorological drought in different land types was revealed. Cross wavelet analysis was used to explore the teleconnection factors (e.g., large-scale climate patterns and solar activity) that may affect the relationship between meteorological drought and vegetation dynamics. The results show that 1) from 2001 to 2019, the vegetation cover and photosynthetic capacity of the PRB both showed increasing trends, with changing rates of 0.055/10a and 0.036/10a, respectively; 2) compared with NDVI, the relationship between SIF and meteorological drought was closer; 3) the vegetation response time (VRT) obtained based on NDVI was mainly 4–5 months, which was slightly longer than that based on SIF (mainly 3–4 months); 4) the VRT of woody vegetation (mainly 3–4 months) was longer than that of herbaceous vegetation (mainly 4–5 months); and 5) vegetation had significant positive correlations with the El Niño Southern Oscillation (ENSO) and sunspots but a significant negative correlation with the Pacific Decadal Oscillation (PDO). Compared with sunspots, the ENSO and the PDO were more closely related to the response relationship between meteorological drought and vegetation. The outcomes of this study can help reveal the relationship between vegetation dynamics and climate change under the background of global warming and provide a new perspective for studying the relationship between drought and vegetation.

Assessment of Spatiotemporal Patterns and the Effect of the Relationship between Meteorological Drought and Vegetation Dynamics in the Yangtze River Basin Based on Remotely Sensed Data

“…The NDVI data and land cover data used in this study were acquired from the Model Resolution Imaging Spectrometer (MODIS) [3]. The MODIS NDVI datasets (MOD13C2) offer a temporal resolution of 1 month and a spatial resolution of 0.05 • [11].…”

“…However, PWC is limited to excluding a single variable [40]. The improved PWC analysis enables the examination of wavelet coherence in the time-frequency domain after removing the effect of other factors [3]. For a more detailed description and calculation process of the improved PWC, please refer to the study conducted by Hu and Si [40].…”

“…In the context of global warming, the frequency and intensity of droughts have significantly increased [1][2][3]. Generally, droughts occur based on a decreasing rate of regional precipitation or an increasing rate of evaporation caused by rising temperatures [4][5][6], which have crucial negative impacts on agricultural production, water resources, ecosystems, and socioeconomic development [7][8][9].…”

“…Currently, there is an increasing interest in exploring teleconnection factors and their remote relationship to drought and vegetation. Many studies have utilized wavelet coherence (WTC) and cross-wavelet coherence methods to investigate the influence of large-scale climate patterns and solar activity on drought or vegetation [3,[37][38][39]. However, these expositions are unsatisfactory because they barely mention the effects of teleconnection factors on the interaction of drought and vegetation.…”

Investigating Drought Propagation Time, Relationship, and Drivers in Perennial River Basins of China

“…Because human activities and land cover could have complex mechanisms impacting drought propagation [61,70], we were not able to sufficiently analyze human activities and land cover in this study. Previous studies have shown that if more variables, such as temperature, evaporation, and soil moisture are taken into account when calculating the drought index, the drought characteristics will change [71,72]. In this study, the SPI, with the characteristics of multiple timescales and easy calculations, was selected to represent meteorological drought.…”