Russell Doughty

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.

Global atmospheric carbon dioxide concentrations are largely driven by 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, and climate data to investigate the seasonality and synchrony 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. In Central Africa, we find a continental-scale bimodal seasonality in SIF, the minimum of which is synchronous with precipitation, but its maximum is likely less related to environmental drivers.

Global atmospheric carbon dioxide concentrations are largely driven by 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, and climate data to investigate the seasonality and synchrony 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. In Central Africa, we find a continental-scale bimodal seasonality in SIF, the minimum of which is synchronous with precipitation, but its maximum is likely less related to environmental drivers.

Global atmospheric carbon dioxide concentrations are largely driven by 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, and climate data to investigate the seasonality and synchrony 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. In Central Africa, we find a continental-scale bimodal seasonality in SIF, the minimum of which is synchronous with precipitation, but its maximum is likely less related to environmental drivers.

The seasonal timing and magnitude of photosynthesis in evergreen needleleaf forests (ENFs) has major implications for the carbon cycle and is increasingly sensitive to changing climate. Earlier spring photosynthesis can increase carbon uptake over the growing season or cause early water reserve depletion that leads to premature cessation and increased carbon loss. Determining the start and the end of the growing season in ENFs is challenging due to a lack of field measurements and difficulty in interpreting satellite data, which are impacted by snow and cloud cover, and the pervasive “greenness” of these systems. We combine continuous needle‐scale chlorophyll fluorescence measurements with tower‐based remote sensing and gross primary productivity (GPP) estimates at three ENF sites across a latitudinal gradient (Colorado, Saskatchewan, Alaska) to link physiological changes with remote sensing signals during transition seasons. We derive a theoretical framework for observations of solar‐induced chlorophyll fluorescence (SIF) and solar intensity‐normalized SIF (SIF_relative) under snow‐covered conditions, and show decreased sensitivity compared with reflectance data (~20% reduction in measured SIF vs. ~60% reduction in near‐infrared vegetation index [NIRv] under 50% snow cover). Needle‐scale fluorescence and photochemistry strongly correlated (r² = 0.74 in Colorado, 0.70 in Alaska) and showed good agreement on the timing and magnitude of seasonal transitions. We demonstrate that this can be scaled to the site level with tower‐based estimates of LUE_P and SIF_relative which were well correlated across all sites (r² = 0.70 in Colorado, 0.53 in Saskatchewan, 0.49 in Alaska). These independent, temporally continuous datasets confirm an increase in physiological activity prior to snowmelt across all three evergreen forests. This suggests that data‐driven and process‐based carbon cycle models which assume negligible physiological activity prior to snowmelt are inherently flawed, and underscores the utility of SIF data for tracking phenological events. Our research probes the spectral biology of evergreen forests and highlights spectral methods that can be applied in other ecosystems.

Global atmospheric carbon dioxide concentrations are largely driven by 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, and climate data to investigate the seasonality and synchrony 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. In Central Africa, we find a continental-scale bimodal seasonality in SIF, the minimum of which is synchronous with precipitation, but its maximum is likely less related to environmental drivers.

Fires were historically rare in tropical forests of West and Central Africa, where dense vegetation, rapid decomposition, and high moisture limit available fuels. However, increasing heat and drought combined with forest degradation and fragmentation are making these areas more susceptible to wildfires. We evaluated historical patterns of Moderate Resolution Imaging Spectroradiometer active fires in African tropical forests from 2003 to 2021. Trends were mostly positive, particularly in the northeastern and southern Congo Basin, and were concentrated in areas with high deforestation. Year‐to‐year variation of fires was synchronized with increasing temperature and vapor pressure deficit. There was anomalously high fire activity across the region during the 2015–2016 El Niño. These results contrast with the drier African woodlands and savannas, where fire has been decreasing. Further attention to fires in African tropical forests is needed to understand their global impacts on carbon dynamics and their local implications for biodiversity and human livelihoods.

Space-based vegetation indices have been used to model global photosynthesis for more than two decades. However, vegetation indices are linked to leaf optical properties rather than leaf physiology, which limits their utility in regions where changes in photosynthesis are driven by leaf development and demography. Conversely, solar-induced chlorophyll fluorescence contains information on leaf physiology and has been shown to be synchronous with photosynthetic activity. Here we present a novel model of global photosynthesis, ChloFluo, which uses spaceborne chlorophyll fluorescence to estimate the amount of photosynthetically active radiation (PAR) absorbed by chlorophyll (APAR_chl). ChloFluo is unique in that instead of estimating APAR_chl as a function of a vegetation index and an ancillary PAR product, we model APAR_chl using its empirical relationship with SIF and the proportion of APAR_chl that is reemitted as SIF, or ΦF. Potential uses of our model are to advance our understanding of the timing and magnitude of photosynthesis, its effect on atmospheric carbon dioxide fluxes, and vegetation response to climate events and change.