The ability of a naturally established forest on cutaway peatland to sequester carbon
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Date
2025
Authors
Mealy, Hannah
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Publisher
University College Cork
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Abstract
This study aimed to quantify the atmospheric greenhouse gas (GHG) fluxes of CO₂ and CH₄ from a naturally regenerated mixed woodland established on a cutaway peatland. Both CO₂ and CH₄ are critical contributors to climate change. CO₂ is responsible for long-term warming because it remains in the atmosphere for centuries, gradually accumulating and exerting a warming effect. In contrast CH₄ has a shorter lifespan, but it is far more effective at trapping heat in the short term, making it a potent driver of near-term climate warming. By monitoring these emissions, this research sought to estimate the net ecosystem exchange (NEE) (CO₂) and CH₄ to assess the peatland’s role as a carbon sink or source, providing crucial insights to inform climate change mitigation strategies for degraded peatland ecosystems.
Continuous measurements were collected over a 12-month period using two open-path gas analysers and a 3-D sonic anemometer mounted on an eddy covariance (EC) tower. These recorded raw atmospheric CO₂ and CH₄ concentrations and 3-D wind speeds at 10 Hz and averaged flux data over half-hour intervals. These high-frequency measurements allowed for a detailed temporal analysis of gas fluxes and contributed to calculating the ecosystem’s annual carbon balance. A closed transparent chamber was designed and built and used with a portable gas analyser to examine the below canopy contribution to the overall CO₂ fluxes. Results revealing that the below canopy habitat made a substantial contribution to overall CO₂ emissions, while the whole ecosystem still maintained a net carbon sink status.
A comparison of gap-filling methods for flux data was conducted, with the random forest (RF) machine learning model outperforming other methods such as marginal distribution sampling (MDS) in terms of accuracy and reliability. This approach was crucial in addressing data gaps and modelling the fluxes.
The gap-filled dataset, simulated using the random forest method, showed that CO₂ was the primary contributor to the total atmospheric carbon balance, with an estimated flux of –28.9 t CO₂ ha⁻¹ yr⁻¹ (±0.07 SE). The model demonstrated strong predictive performance, with a correlation coefficient of 77% and a low root mean square error (RMSE) of the prediction of 3.95 μmol m⁻² s⁻¹ between the unseen and modeled data points. In contrast, CH₄ emissions were much lower, contributing only 0.01 t CH₄ ha⁻¹ yr⁻¹ (±0.0002 SE), with a weak
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correlation between the unseen and modeled data points of 20% and a low RMSE of 0.0113 μmol m⁻² s⁻¹. The uncertainty in both flux estimates was low, indicating a high level of confidence in the gap-filled time series produced by the random forest model. These results provide robust assurance of the model's ability to accurately predict GHG fluxes from this peatland ecosystem.
After incorporating default GHG emissions for N₂O and DOC from IPCC (2013) values to estimate the total emission factor for the Lullymore site, the study revealed that the site remained as a significant carbon sink, with a total GHG emission factor of –26.4 t CO₂-eq ha⁻¹ yr⁻¹. This contrasts with emission factors reported for drained forests and rewetted peatlands. Methane emissions contributed very little to the overall emissions factor, estimated at 0.28 t CO₂-eq ha⁻¹ yr⁻¹ (including global warming potential).
However, the study faced limitations, including data covering only one year and the absence of a below-canopy photosynthetically active radiation (PAR) sensor, which may have led to a slight overestimation of positive NEE values below the canopy. The study's findings emphasise the potential of low-maintenance, naturally regenerated mixed woodlands on degraded peatlands as an effective carbon mitigation strategy, supporting the need for this land-use category to be recognised separately from conventional forestry in GHG reporting.
Future research should focus on multi-year monitoring to account for interannual variability, and adjustments in measurement infrastructure will be necessary as the woodland matures. Overall, this research highlights the substantial carbon sequestration potential of mixed woodlands on cutaway peatlands and provides critical insights for policy makers aiming to improve carbon accounting and enhance climate mitigation efforts.
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Keywords
Peatlands , Bogs , Greenhouse gases , Woodlands , Carbon dioxide , Methane , Eddy covariance , Chamber
Citation
Mealy, H. 2025. The ability of a naturally established forest on cutaway peatland to sequester carbon. PhD Thesis, University College Cork. The ability of a naturally established forest on cutaway peatland to sequester carbon