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Sun-induced fluorescence and near-infrared reflectance of vegetation track the seasonal dynamics of gross primary production over Africa

  • Anteneh Getachew Mengistu*
  • , Gizaw Mengistu Tsidu
  • , Gerbrand Koren
  • , Maurits L. Kooreman
  • , K. Folkert Boersma
  • , Torbern Tagesson
  • , Jonas Ardö
  • , Yann Nouvellon
  • , Wouter Peters
  • *Corresponding author for this work

Research output: Contribution to journalArticleAcademicpeer-review

Abstract

The carbon cycle of tropical terrestrial vegetation plays a vital role in the storage and exchange of atmospheric CO<span classCombining double low line"inline-formula">2</span>. But large uncertainties surround the impacts of land-use change emissions, climate warming, the frequency of droughts, and CO<span classCombining double low line"inline-formula">2</span> 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 CO<span classCombining double low line"inline-formula">2</span>, 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 <span classCombining double low line"inline-formula"0.9</span> (<span classCombining double low line"inline-formula">NCombining double low line12</span> 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 (<span classCombining double low line"inline-formula">R</i0.9</span>; <span classCombining double low line"inline-formula">N≥250</span> 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.

Original languageEnglish
Pages (from-to)2843-2857
Number of pages15
JournalBiogeosciences
Volume18
Issue number9
DOIs
Publication statusPublished - 10 May 2021
Externally publishedYes

Bibliographical note

Funding Information:
Financial support. This research has been supported by the Euro-

Funding Information:
Acknowledgements. The authors acknowledge the NOAA Earth System Research Laboratories, Met Office Hadley Centre, Global Precipitation Climatology Centre, Global Land Data Assimilation System, MODIS dataset, and ECMWF for the data products. We would also like to acknowledge the FLUXNET data principal investigators of the GH-Ank (Ghana), ZA-Kru (South Africa), ZM-Mon (Zambia), and BR-Sa1 (Brazil) sites. The first author also acknowledges Addis Ababa University, Addis Ababa Science and Technology University, the Coimbra Group Scholarship Programme, and the University of Groningen for their support through fellowship and access to research facilities. Data were processed on Cartesius (SURFsara) using a grant for computing time (SH-312-14) from the Dutch Research Council (NWO). Jonas Ardö was supported by Lund University. We would like to thank the associate editor David Bowling and the anonymous reviewers for their constructive and thoughtful comments and suggestions that significantly improved the paper.

Publisher Copyright:
© 2021 Copernicus GmbH. All rights reserved.

UN SDGs

This output contributes to the following UN Sustainable Development Goals (SDGs)

  1. SDG 13 - Climate Action
    SDG 13 Climate Action
  2. SDG 15 - Life on Land
    SDG 15 Life on Land

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