Abstract

Abstract. The carbon cycle of tropical terrestrial vegetation plays a vital role in the storage and exchange of atmospheric CO2. But large uncertainties surround the impacts of land-use change emissions, climate warming, the frequency of droughts, and CO2 fertilization. This culminates in poorly quantified carbon stocks and carbon fluxes even for the major ecosystems of Africa (savannas and tropical evergreen forests). Contributors to this uncertainty are the sparsity of (micro-)meteorological observations across Africa's vast land area, a lack of sufficient ground-based observation networks and validation data for CO2, and incomplete representation of important processes in numerical models. In this study, we therefore turn to two remotely sensed vegetation products that have been shown to correlate highly with gross primary production (GPP): sun-induced fluorescence (SIF) and near-infrared reflectance of vegetation (NIRv). The former is available from an updated product that we recently published (Sun-Induced Fluorescence of Terrestrial Ecosystems Retrieval – SIFTER v2), which specifically improves retrievals in tropical environments. A comparison against flux tower observations of daytime-partitioned net ecosystem exchange from six major biomes in Africa shows that SIF and NIRv reproduce the seasonal patterns of GPP well, resulting in correlation coefficients of >0.9 (N=12 months, four sites) over savannas in the Northern and Southern hemispheres. These coefficients are slightly higher than for the widely used Max Planck Institute for Biogeochemistry (MPI-BGC) GPP products and enhanced vegetation index (EVI). Similarly to SIF signals in the neighboring Amazon, peak productivity occurs in the wet season coinciding with peak soil moisture and is followed by an initial decline during the early dry season, which reverses when light availability peaks. This suggests similar leaf dynamics are at play. Spatially, SIF and NIRv show a strong linear relation (R>0.9; N≥250 pixels) with multi-year MPI-BGC GPP even within single biomes. Both MPI-BGC GPP and the EVI show saturation relative to peak NIRv and SIF signals during high-productivity months, which suggests that GPP in the most productive regions of Africa might be larger than suggested.

Highlights

  • Gross primary production (GPP) is the carbon dioxide (CO2) flux between the terrestrial biosphere and the atmosphere by terrestrial plants via plant photosynthesis, and it is the largest CO2 flux on the planet (Beer et al, 2010)

  • Spatial patterns in climatological near-infrared reflectance of vegetation (NIRv), sun-induced fluorescence (SIF), and Max Planck Institute for Biogeochemistry (MPI-BGC) GPP are very similar across large scales, with maximum annual mean productivity in tropical broadleaf forests

  • Guanter et al (2014) found that the MPI-BGC GPP underestimated the global crop production by 50 %–70 % compared to SIF GPP obtained by a fitting to flux-tower-based GPP from US and European croplands and grasslands; in African grassland we found SIF GPP to be relatively lower than MIP-BGC GPP

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Summary

Introduction

Gross primary production (GPP) is the carbon dioxide (CO2) flux between the terrestrial biosphere and the atmosphere by terrestrial plants via plant photosynthesis, and it is the largest CO2 flux on the planet (Beer et al, 2010). In determining African net ecosystem exchange (NEE), GPP was more important than total ecosystem respiration (TER) (Ciais et al, 2011; Ardö, 2015). It dominates the interannual variability in the terrestrial ecosystem carbon uptake, and as a consequence of fertilization, it is likely to continue its substantial increase and play an important role in carbon–climate coupling (Vermote et al, 1997; Friedlingstein et al, 2019). Quantification of the spatiotemporal variations in GPP is important to assess biogeochemical cycling in the terrestrial biosphere, ecosystem functioning, carbon budgets, and food production in the context of global climate change. We can only crudely describe the carbon balance of these regions in the current and future climate

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