Spatial Patterns of Carbon Exchange Seasonality in Amazonian Forest

Monday, 15 December 2014
Liang Xu1, Sassan S Saatchi1,2, Yan Yang1,3, Ranga Myneni3, Christian Frankenberg2 and Diya Chowdhury1, (1)University of California Los Angeles, Los Angeles, CA, United States, (2)NASA Jet Propulsion Laboratory, Pasadena, CA, United States, (3)Boston University, Boston, MA, United States
The terrestrial gross primary production (GPP) is considered the largest CO2 flux (123±8 petagrams) and responsible for driving several ecosystem functions globally. However, estimates of magnitude and regional variations of this flux remain uncertain in humid tropical forests, particularly in Amazonia where limited ground data have caused gross assumptions about seasonality and heterogeneity of these forests. Empirical upscaling of the in situ observations or refined process-based modeling using remote sensing inputs have improved estimates of carbon exchange, but the seasonal variation of this exchange in Amazonia remains a challenge and has been the subject of recent scientific debates. Here, we used satellite observations of canopy structure, skin temperature, water content, and optical properties over 10 years (2000-2009) to quantify spatial patterns of seasonality of Amazonian forests. We found 9 pheno-regions with distinct seasonal cycles in Amazonia, among them 3 regions showing strong seasonal variations with maximized GPP in the wet season; another 3 exhibiting rising GPP in the dry season; and the remaining 3 with low seasonality. These patterns were verified by direct measurements of photosynthetic activity using florescence from GOSAT satellite. Our results suggest that water and radiation represented by canopy water content and skin temperature regulate photosynthetic activities over Amazonia that can be captured by spatial variations of Near Infrared Reflectance. Our detection of patterns of seasonality in Amazonia will improve modeling global exchange of carbon and predicting future impacts of climate change on tropical forests.