Dr. Xuefei Li has been recently granted the Academy of Finland Postdoctoral funding for her project: Belowground Methane Turnover at a Boreal Peatland: Quantifying the Processes with in-situ Stable Isotope Methods (MIso). This project will be running from Sep 2020 to August 2023.
Boreal peatlands emit substantial amount of methane (CH4), a potent greenhouse gas, to the atmosphere. The lack of field experiment studying CH4 turnover processes is a key bottle neck in the development of peatland CH4 modelling. In this project, Xuefei proposes the first systematic study quantifying in situ major CH4 turnover processes (production, oxidation and transport) and their responses to the change in environmental conditions along a peat profile with high temporal resolution in a typical boreal peatland (Siikaneva fen) in Southern Finland.
A cavity ring-down spectrometer will be utilized to capture the dynamics of belowground dissolved CH4 and carbon dioxide concentrations and their δ13C natural abundance signatures at different peat depth. This novel approach continuously monitors the real-time CH4 turnover processes of the steady-state conditions along a vertical profile. Additionally, a complementary 13C pulse labelling experiment will be performed in situ to trace the processes which cannot be separated by the isotope natural abundance approach alone. Besides, environmental parameters will be monitored throughout the study period to examine the dependence of CH4 turnover processes on the environment. With the new insight gained from the measurements, a mechanistic CH4 model HIMMELI (HelsinkI Model of MEthane buiLd-up and emIssion for peatlands) will be modified by including vertical dependency of the process rates and new parameterization to multiple process descriptions, and it will be tested against ecosystem-scale CH4 flux observations using eddy covariance technique.
This project has potential to profoundly renew our knowledge on belowground CH4 dynamics especially in the less-studied winter and shoulder seasons when emission are most variable. The cutting-edge results to be obtained from the experiments will provide an unprecedented dataset for the optimization and validation of mechanistic CH4 models.