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

Publikation: Beitrag in FachzeitschriftForschungsartikelBeigetragenBegutachtung

Beitragende

  • Fan Naixin - , Juniorprofessur für Umweltfernerkundung, Max Planck Institute for Biogeochemistry (Autor:in)
  • Maurizio Santoro - , GAMMA Remote Sensing Research and Consulting AG (Autor:in)
  • Simon Besnard - , Helmholtz-Zentrum Potsdam – Deutsches GeoForschungsZentrum (Autor:in)
  • Oliver Cartus - , GAMMA Remote Sensing Research and Consulting AG (Autor:in)
  • Sujan Koirala - , Max Planck Institute for Biogeochemistry (Autor:in)
  • Nuno Carvalhais - , Max Planck Institute for Biogeochemistry, Universidade NOVA de Lisboa, European Laboratory for Learning and Intelligent Systems Unit Jena (Autor:in)

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

OriginalspracheEnglisch
Aufsatznummer104036
Seitenumfang8
FachzeitschriftEnvironmental research letters
Jahrgang18
Ausgabenummer10
PublikationsstatusVeröffentlicht - 9 Okt. 2023
Peer-Review-StatusJa

Schlagworte

Forschungsprofillinien der TU Dresden

Schlagwörter

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