Modelling Carbon Dynamics and Restoration Strategies across Peatlands in Scotland

Peatlands, covering just 3% of Earth's surface, hold 15-30% of global soil carbon stocks. However, land use and drainage contribute 5-10% of human-driven CO₂ emissions, depleting long-stored carbon. In the UK, peatlands span 12% of land, emitting 23,100 kt CO₂e annually. Scotland, where peatlands cover 20-25%, has a net-zero by 2045 targets, and aims to counter current estimated peatland emissions of 8.8-9.7 Mt CO₂ annually via restoration efforts. Peatland carbon dynamics under varying drainage and rewetting conditions as well as under different future climate change scenarios (Representative Concentration Pathway (RCP) scenarios—RCP 2.6 and RCP 8.5) were therefore explored using the ecosystem model Wetland-DNDC across two contrasting sites. One site, located at Cross Lochs in Forsinard (UK-CLS), represents a near-natural blanket bog that currently serves as a robust carbon sink, whereas the other, an eroding oceanic blanket bog in the Cairngorms (UK-BAM), acts as a net source of carbon dioxide emissions. Prior to hydrological simulation, Wetland-DNDC runs across each of the two sites were validated against eddy covariance derived net ecosystem exchange (NEE), gross primary productivity (GPP), ecosystem respiration (ER) and evapotranspiration data (ET).Compared to baseline scenario of no drainage, continuous drainage at 5 cm from 1861 till 2020 and then rewetting to 5 cm from 2020 to 2100 induced different rates of recovery for the three dominant vectors of carbon exchange. For example, increase in the sequestration capacity (NEE) by 84% across UK-BAL compared to 21% across UK-CLS at the end of simulation period was triggered by corresponding increase in GPP. However, neither the undrained baseline scenario at Balmoral nor the drained state at CrossLochs can be validated, which introduces a degree of uncertainty in interpreting these simulated outcomes.Ongoing efforts aim to evaluate the combined effects of peatland management practices (e.g., drainage at varying depths) and climate change (including extreme events) on GHG flux dynamics. Using Wetland-DNDC and its simplified stochastic (random forest) meta-model framework, these analyses will improve the reliability of carbon audit tools in assessing the benefits of peatland restoration under future climate scenarios. This approach will also enable spatial modelling of CO₂ emissions across Scotland's peatlands and support the development of more accurate Tier 2 emission factors for the UK, aligning with national and global climate mitigation goals.