Interannual Variability in African Regional Ecosystem Carbon Fluxes and Their Drivers Revealed by Satellite Observations
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2025
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Source Global Biogeochemical Cycles, 39(7)
Details
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Journal Title:Global Biogeochemical Cycles
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Personal Author:
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NOAA Program & Office:
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Description:The sparseness of ground‐based observations hinders our ability to understand the processes driving the interannual variability (IAV) of the African ecosystem carbon cycle. This study explores the regional pattern of the IAV in net biosphere exchange (NBE), defined as the sum of gross primary production (GPP), respiration, and biomass burning emissions, across Africa and its climate drivers from 2015 to 2021, by integrating satellite‐derived carbon flux estimates. Our analysis reveals that moisture‐driven IAV of GPP determines the IAV of total NBE in Africa, but the magnitude of NBE IAV is not uniformly proportional to the GPP IAV across regions. Though IAV of NBE in eastern and southern grasslands is comparable, the IAV of GPP in the east is 29% ± 9% greater, offset by respiration with higher moisture sensitivity. By contrast, the IAV of NBE in northern forests is around twice that of southern forests, despite a smaller IAV of GPP. The larger NBE IAV is attributed to the higher moisture sensitivity of biomass burning emissions and the stronger temperature sensitivity of respiration in northern forests, which prevents respiration from declining despite significant GPP reductions under dry and warm conditions (e.g., the 2016 El Niño year). We also find that in northern grasslands, unlike other regions, IAV of NBE is primarily determined by respiration, which responds strongly to soil rewetting in the late dry season. Our results underscore the potential of satellite observations in uncovering the drivers of the IAV in the African ecosystem carbon cycle at regional as well as continental scales.
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Source:Global Biogeochemical Cycles, 39(7)
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DOI:
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ISSN:0886-6236 ; 1944-9224
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Rights Information:Other
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Compliance:Library
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Main Document Checksum:urn:sha-512:03ac29434154bc6dc0b57c078b99c37fe89222795a465805b27905c0f3e76824d48ed99ab7c4c03f26b685bbdef43e86e72fc4a03293c2d1fad590c27d20f52c
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