Opposite eco-hydrological processes in flood and drought years caused comparable anomaly in dry-season canopy growth over southern Amazon

Abstract

Abstract While the influences of droughts on Amazon rainforest have been extensively examined, little attention was paid to the extremely wet years characterized by low radiation which may limit the rainforest growth. Here, based on a series of satellite-observed vegetation and hydro-meteorological products, we found a two-stage canopy growth anomaly in the record-breaking wet year 2009, i.e. negative anomalies during April–July followed by positive ones during August–November. Our analysis suggests that, in April–July, low radiation associated with above-average rainfall and cloud cover was the most likely cause for negative anomalies in the canopy growth. In August–November, the rainfall and cloud cover were close to the average, but the solar radiation reaching the land surface was considerably above the average. This was because the atmospheric aerosols were extremely low, resulting from reduced biomass burning activities under the wet conditions. Large-scale positive anomalies in the canopy growth were observed during this 4 month period, mainly driven by the above-average radiation. During the severe drought year 2005, the forest canopy growth also experienced a two-stage process, but in the opposite order from the one in 2009. In April–July, enhanced canopy growth was observed in response to the above-average radiation. With the drought progress and soil water depletion, the canopy senescence was observed during the drought peak in August–November. Interestingly, if we examined the regional canopy growth anomaly during the typical dry season (i.e. July–September), both years showed similarly negative anomalies, but resulting from opposite eco-hydrological processes. This study identifies the explanation for the negative anomalies in the dry-season canopy growth over southern Amazon rainforest in both flood and drought years, and also underscores the necessity to separate different hydro-meteorological stages to better understand vegetation responses to extreme events.