EGU24-7100, updated on 08 Mar 2024
EGU General Assembly 2024
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Modelling sub-grid peatland vegetation dynamics in the ORCHIDEE-PEAT land surface model

Chunjing Qiu1 and Philippe Ciais2
Chunjing Qiu and Philippe Ciais
  • 1Research Center for Global Change and Complex Ecosystems, School of Ecological and Environmental Sciences, East China Normal University, Shanghai, China
  • 2Laboratoire des Sciences du Climat et de l’Environnement (LSCE), CEA–CNRS– UVSQ, IPSL, Université Paris-Saclay, 91191 Gif-sur-Yvette, France

Peatlands store about one-third of global soil organic carbon. The carbon dynamics and storage of peatlands depend on the balance between plants’ carbon uptake and microbial carbon decomposition. As a result of global warming and climate-driven ecohydrological changes, the plant community composition of peatlands is projected to change, affecting the carbon sequestration and storage capacity of these ecosystems both directly and indirectly by modulating water flows. However, while there has been a notable focus on studying the variation in the water table position of peatlands and its consequential influence on the dynamics of peatland soil carbon, the impacts of peatland plant community composition have been largely overlooked. To accurately predict peatland carbon dynamics, land surface models need to account for the diversity of peatlands plant types and the competitive interactions among them. We incorporated six plant functional types (PFT) into the ORCHIDEE-PEAT model to represent mosses, grasses, shrubs, and trees growing in peatlands. Areas covered by each PFT are functions of the bioclimatic limitations, mortality, and establishment of each PFT, as well as competitions among PFTs. The model will be employed to assess the effect of climate change on peatland vegetation dynamics and carbon fluxes.

How to cite: Qiu, C. and Ciais, P.: Modelling sub-grid peatland vegetation dynamics in the ORCHIDEE-PEAT land surface model, EGU General Assembly 2024, Vienna, Austria, 14–19 Apr 2024, EGU24-7100,, 2024.