Implications of the steady-state assumption for the global vegetation carbon turnover

Research output: Contribution to journalResearch articleContributedpeer-review

Contributors

  • Fan Naixin - , Junior Professorship in Environmental Remote Sensing, Max Planck Institute for Biogeochemistry (Author)
  • Maurizio Santoro - , GAMMA Remote Sensing Research and Consulting AG (Author)
  • Simon Besnard - , Helmholtz Centre Potsdam - German Research Centre for Geosciences (Author)
  • Oliver Cartus - , GAMMA Remote Sensing Research and Consulting AG (Author)
  • Sujan Koirala - , Max Planck Institute for Biogeochemistry (Author)
  • Nuno Carvalhais - , Max Planck Institute for Biogeochemistry, NOVA University Lisbon, European Laboratory for Learning and Intelligent Systems (Author)

Abstract

Vegetation carbon turnover time (τ) is a central ecosystem property to quantify the global vegetation carbon dynamics. However, our understanding of vegetation dynamics is hampered by the lack of long-term observations of the changes in vegetation biomass. Here we challenge the steady state assumption of τ by using annual changes in vegetation biomass that derived from remote-sensing observations. We evaluate the changes in magnitude, spatial patterns, and uncertainties in vegetation carbon turnover times from 1992 to 2016. We found the robustness in the steady state assumption for forest ecosystems at large spatial scales, contrasting with local larger differences at the grid cell level between τ under steady state and τ under non-steady state conditions. The observation that terrestrial ecosystems are not in a steady state locally is deemed crucial when studying vegetation dynamics and the potential response of biomass to disturbance and climatic changes.

Details

Original languageEnglish
Article number104036
JournalEnvironmental research letters
Volume18
Issue number10
Publication statusPublished - 1 Oct 2023
Peer-reviewedYes

Keywords

Research priority areas of TU Dresden

DFG Classification of Subject Areas according to Review Boards

Keywords

  • remote sensing, steady state assumption, vegetation carbon stock, vegetation carbon turnover time