Search

• A comprehensive assessment of the three major droughts' impacts on Amazon forests. • The 2015/16 drought is the most severe meteorological drought since 2000. • Drought in 2015/16 showed lagging impacts on photosynthesis, greenness, and leaf area. • Photosynthesis, greenness, and leaf area had similar suppression in 2010 and 2015/16. • Canopy water content exhibited more widespread and severe drought impacts in 2015/16. The Amazon forests play an integral role in the global carbon cycle and have a substantial impact on Earth's climate. However, it is increasingly susceptible to the effects of prolonged droughts, exacerbated by climate change and human activities. This vulnerability underscores the importance of understanding the forests' reaction to such environmental stressors. Despite their significance, comprehensive cross-comparisons of the climate and vegetation responses during the 2005, 2010, and 2015/2016 drought episodes are not well-established. Here we utilize a range of gridded vegetation and climate datasets—including leaf area index (LAI), solar-induced chlorophyll fluorescence (SIF), enhanced vegetation index (EVI), vegetation optical depth (VOD), self-calibrating Palmer drought severity index (scPDSI), precipitation (P), land surface temperature (LST), and photosynthetically active radiation (PAR)—to thoroughly assess the climate and vegetation response to these three drought events. Our findings reveal that the extent of drought inhibition in the Amazon forests was 74.7 % in 2015, increasing to 81.3 % in 2016, a significant escalation from 49.6 % in 2005 and 57.7 % in 2010. The effects of these three droughts on vegetation varied in both physiological and structural aspects. The Amazon forests' photosynthetic activity, greenness, and leaf area experienced comparable suppression in 2010 and 2015/2016 droughts. However, canopy water content exhibited more extensive and severe impacts during the 2015/2016 drought. Our findings indicate that varying sensitivities to water deficit and solar radiation lead to diverse spatial patterns and intensities of vegetation response, highlighting the complex dynamics of the Amazon forests under drought stress. [ABSTRACT FROM AUTHOR]

As the most frequent and longest-lasting climate-related disasters, droughts are complex processes caused by hydrological imbalance, and have significant effects on ecosystem function and socioeconomic development. However, most conventional satellite-based drought indices and combined drought indices are mechanically constrained by the fact that they were developed and evaluated for a specific climate or critical ecological region, especially in China. A comprehensive drought index should be developed for extensive application in different climate-hydrology regions. To address this problem, an optimised principal component analysis method (PCA-RF) was proposed to support drought assessment across the transitional area between the humid and arid regions in central China, including the Loess Plateau (LP) and Qinling Mountains (QL). This method eliminated the causal relationships of non-linear changes for multi-aspect parameters such as land surface temperature, precipitation and soil moisture, and was used in developing a new index named "Meteorological drought index by PCA-RF methods (PMDI)". The results showed that PMDI had higher correlations and lower root mean square error than other drought indices (established using the empirical-weights method) with the 1-month standardized precipitation evapotranspiration index (SPEI-1). That means PMDI performed well in meteorological drought monitoring. Additionally, the normalized difference vegetation index (NDVI) and solar-induced chlorophyll fluorescence (SIF) were utilised to evaluate PMDI effectiveness in detecting vegetation response to drought, which represents agricultural drought. The results indicated that correlations between PMDI and vegetation indices (VIs) were stronger when severe or extreme droughts occurred, and that their relationships were affected by the high spatiotemporal heterogeneity in vegetation change over the LP and QL. Overall, PMDI was shown here to be a very suitable index for monitoring meteorological drought (short-term) and has effective action in capturing the response of vegetation signals to agriculture drought events (long-term). Given the excellent performance of PMDI in diverse climate-hydrology conditions of our study regions, we concluded that the PMDI has considerable potential as a drought monitoring methodology on a larger spatial scale. • A new drought index was developed (PMDI), which integrated multiple sources of information describing different aspects. • PMDI performed well in different climate-hydrology regions for short- and long-term drought monitoring. • PMDI has reasonably good potential applicability in drought monitoring on a larger spatial scale. [ABSTRACT FROM AUTHOR]