Satellite observation of tropical forest seasonality: spatial patterns of carbon exchange in Amazonia

摘要

Determining the seasonality of terrestrial carbon exchange with the atmosphere remains a challenge in tropical forests because of the heterogeneity of ecosystem and climate. The magnitude and spatial variability of this flux are unknown, particularly in Amazonia where empirical upscaling approaches from spatially sparse in situ measurements and simulations from process-based models have been challenged in recent scientific literature. Here, we use satellite proxy observations of canopy structure, skin temperature, water content, and optical properties over a period of 10 years (2000–2009) to constrain and quantify the spatial pattern and seasonality of carbon exchange of Amazonian forests. We identify nine regions through an optimized cluster approach with distinct leaf phenology synchronized with either water or light availability and corresponding seasonal cycles of gross primary production (GPP), covering more than 600 million ha of remaining old growth forests of Amazonia. We find South and Southwestern regions show strong seasonality of GPP with a peak in the wet season; while from Central Western to Northeastern Amazonia cover three regions with rising GPP in the dry season. The remaining four regions have significant but weak seasonality. These patterns agree with satellite florescence observations, a better proxy for photosynthetic activity. Our results suggest that only one-third of the patterns can be explained by the spatial autocorrelation caused by intra-annual variability of climate over Amazonia. The remaining two-thirds of variations are due to biogeography of the Amazon basin driven by forest composition, structure, and nutrients. These patterns, for the first time, provide a complex picture of seasonal changes of tropical forests related to photosynthesis and influenced by water, light, and stomatal responses of trees that can improve modeling of regional carbon cycle and future prediction of impacts of climate change.