Revisiting dry season vegetation dynamics in the Amazon rainforest using different satellite vegetation datasets

Abstract

There has been a debate regarding whether the Amazon rainforest is greening during the dry season. This is partially because of the great uncertainty associated with the ability of different vegetation indices to accurately assess tropical vegetation status. This paper, revisit this issue by comprehensively examining the seasonal variations in vegetation recorded in various satellite-based vegetation datasets, namely, the leaf area index (LAI), contiguous solar-induced fluorescence (CSIF), enhanced vegetation index (EVI), and vegetation optical depth (VOD). All four of these vegetation datasets show an increase in vegetation during the dry season in most parts of the Amazon; however, the vegetation changes are not only spatially variable, but also differ among the datasets. This may be attributable in part to the different physical characteristics captured by each of the datasets. For example, the seasonal maximum value occurs first in the LAI, followed by the CSIF, EVI, and VOD, in that order. The seasonal cycle of the LAI agrees reasonably well with in-situ observations of leaf flush and leaf fall. As new leaf production offsets senescence and abscission, the dry-season vegetation increases in most parts of the Amazon rainforest. Partial correlation analysis was used to further investigate the potential climatic cues (i.e., precipitation, temperature and radiation) associated with the seasonal changes recorded in the vegetation data. We found that precipitation and radiation were the dominant potential cues for seasonal VOD (48%) and LAI (59%) changes, respectively. However, CSIF appears to be associated more closely with temperature and precipitation, with significant correlations observed across ∼x223C 37% of the Amazon rainforest area for both with CSIF. Finally, variations in the EVI showed similar sensitivity to all three climatic variables considered. The findings presented here will greatly improve our understanding of vegetation dynamics and the carbon cycle in the Amazon rainforest ecosystem.