Preprints
https://doi.org/10.5194/gmd-2022-143
https://doi.org/10.5194/gmd-2022-143
Submitted as: model description paper
26 Jul 2022
Submitted as: model description paper | 26 Jul 2022
Status: this preprint is currently under review for the journal GMD.

PVN 1.0: using dynamic PFTs and restoration scenarios to model CO2 and CH4 emissions in peatlands

Tanya Juliette Rebecca Lippmann1, Monique Heijmans2, Han Dolman3,4, Ype van der Velde1, Dimmie Hendriks5, and Ko van Huissteden1,6 Tanya Juliette Rebecca Lippmann et al.
  • 1Vrije Universiteit Amsterdam, Amsterdam, the Netherlands
  • 2Wageningen University and Research, Wageningen, the Netherlands
  • 3Royal Netherlands Institute for Sea Research, Texel, the Netherlands
  • 4Netherlands Earth System Science Center, Utrecht, the Netherlands
  • 5Deltares Research Institute, Utrecht, the Netherlands
  • 6VOF Kytalyk Carbon Cycle Research, Utrecht, the Netherlands

Abstract. Peatlands are the world’s largest terrestrial carbon store. Despite covering only 3 % of the planet’s land surface, peatlands store 30 % of the planet’s terrestrially available carbon. The Dutch government's 2019 National Climate Agreement committed to reduce the contribution of peatlands to total national Dutch greenhouse gas (GHG) emissions, by 1 Mton CO2 per year (20 %) until 2030. Countries with similarly degraded peatlands are likely to face similar commitments in the coming years. Restoration (or rewetting) is a proposed solution to reduce land subsidence and increase carbon sequestration in agricultural peatlands but is often accompanied by large CH4 emissions.

Whilst, previous studies have investigated whether singular plant types impact the GHG emissions of peatlands, few (or no) studies have investigated the impact of plant composition on GHG emissions in peatlands. To assess the impact of dynamic vegetation on subsequent GHG fluxes in peatlands, we developed a new model, Peatland-VU-NUCOM (PVN). This is the second process-based model to date, capable of simulating dynamic vegetation, CO2, and CH4 emissions in peatlands.

The new PVN model simulates CH4 and CO2 fluxes in relation to the plant community composition. The PVN model includes plant competition, CH4 diffusion, ebullition, root, shoot, litter exudate production, below-ground decomposition, and aboveground moss development, under changing water table and climatic conditions. The model was compared against observational data collected at two sites in the Netherlands.

These results showed that plant communities impact net GHG emissions. This is the first time that a peatland emissions model is able to investigate the role of re-introducing peat forming vegetation on subsequent GHG emissions. We also found that the initial plant community influenced the potential for harvest events to reduce GHG emissions. These results indicated that plant community restoration is a critical component of peatland restoration.

Tanya Juliette Rebecca Lippmann et al.

Status: open (until 20 Sep 2022)

Comment types: AC – author | RC – referee | CC – community | EC – editor | CEC – chief editor | : Report abuse

Tanya Juliette Rebecca Lippmann et al.

Data sets

PVN model code and input data Tanya J. R. Lippmann https://bitbucket.org/tlippmann/pvn_public

Model code and software

PVN 1.0 model source code Tanya J. R. Lippmann https://doi.org/10.5281/zenodo.6802102

Tanya Juliette Rebecca Lippmann et al.

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Short summary
To assess the impact of vegetation on GHG fluxes in peatlands, we developed a new model, Peatland-VU-NUCOM (PVN). These results showed that plant communities impact GHG emissions, indicating that plant community re-establishment is a critical component of peatland restoration. This is the first time that a peatland emissions model investigated the role of re-introducing peat forming vegetation on GHG emissions.