Seasonality and synchrony of photosynthesis in African forests inferred from spaceborne chlorophyll fluorescence and vegetation indices

Abstract. Global atmospheric carbon dioxide concentrations are largely driven by changes in fossil fuel emissions and terrestrial photosynthesis, of which tropical forests account for one-third. Relative to other tropical regions, less is known about the seasonality of African tropical forest productivity and its synchrony with environmental factors due to a lack of in situ carbon flux data. To help fill this knowledge gap, we use spaceborne solar-induced chlorophyll fluorescence (SIF), vegetation indices – including the enhanced vegetation index (EVI), the normalized difference vegetation index (NDVI), and the land surface water index (LSWI) – and climate data to investigate the seasonality and synchrony of indicators of photosynthesis in Africa's tropical forest ecoregions. We find West African SIF to increase during the dry season and peak prior to precipitation, as has been observed in the Amazon. However, NDVI and EVI do not mimic the strong double-peak seasonality observed in SIF; instead, they often plateau until substantial decreases occur in the dry season. In central Africa, we find a continental-scale bimodal seasonality in SIF and EVI, the minimum of which is synchronous with precipitation, but its maximum is likely less related to environmental drivers. Our findings highlight the complex relationships between SIF, vegetation indices, and environmental factors, underscoring the importance of using multiple remote sensing measures to monitor tropical forest productivity.

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Publication Details

Journal
Biogeosciences
Published
2025-04-24
DOI
https://doi.org/10.5194/bg-22-1985-2025
Citations
2
Primary Topic
Remote Sensing in Agriculture
Type
article
Field-Weighted Citation Impact
3.43
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article

Seasonality and synchrony of photosynthesis in African forests inferred from spaceborne chlorophyll fluorescence and vegetation indices

Michael C. Wimberly, Russell Doughty, Moses Azong Cho, Hélène Peiro et al.
2 citations
Biogeosciences
Remote Sensing in Agriculture
3.43
article

Seasonality and synchrony of photosynthesis in African forests inferred from spaceborne chlorophyll fluorescence and vegetation indices

Michael C. Wimberly, Russell Doughty, Moses Azong Cho, Hélène Peiro, Sean Crowell, Nicholas Cody Parazoo, Dan Wanyama
article en
2 citations

Abstract

Abstract. Global atmospheric carbon dioxide concentrations are largely driven by changes in fossil fuel emissions and terrestrial photosynthesis, of which tropical forests account for one-third. Relative to other tropical regions, less is known about the seasonality of African tropical forest productivity and its synchrony with environmental factors due to a lack of in situ carbon flux data. To help fill this knowledge gap, we use spaceborne solar-induced chlorophyll fluorescence (SIF), vegetation indices – including the enhanced vegetation index (EVI), the normalized difference vegetation index (NDVI), and the land surface water index (LSWI) – and climate data to investigate the seasonality and synchrony of indicators of photosynthesis in Africa's tropical forest ecoregions. We find West African SIF to increase during the dry season and peak prior to precipitation, as has been observed in the Amazon. However, NDVI and EVI do not mimic the strong double-peak seasonality observed in SIF; instead, they often plateau until substantial decreases occur in the dry season. In central Africa, we find a continental-scale bimodal seasonality in SIF and EVI, the minimum of which is synchronous with precipitation, but its maximum is likely less related to environmental drivers. Our findings highlight the complex relationships between SIF, vegetation indices, and environmental factors, underscoring the importance of using multiple remote sensing measures to monitor tropical forest productivity.

BiogeosciencesVol. 22(8)
Jet Propulsion Laboratory (US), Scientific Solutions (United States) (US), Space Research Organisation Netherlands (NL), University of Oklahoma (US)
Openalex Percentile: Top 9%
Remote Sensing in Agriculture
3.43
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