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Soil respiration partitioning in afforested temperate peatlands

2018-09-12, Jovani-Sancho, A. Jonay, Cummins, Thomas, Byrne, Kenneth A.

Understanding and quantifying soil respiration and its component fluxes are necessary to model global carbon cycling in a changing climate as small changes in soil CO2 fluxes could have important implications for future climatic conditions. A soil respiration partitioning study was conducted in eight afforested peatland sites in south-west Ireland. Using trenched points, annual soil CO2 emissions, and the contributions of root and heterotrophic respiration as components of total soil respiration, were estimated. Nonlinear regression models were evaluated to determine the best predictive soil respiration model for each component flux, using soil temperature and water table level as explanatory variables. Temporal variation in soil CO2 efflux was driven by soil temperature at 10 cm depth, with all treatment points also affected by water table level fluctuations. The effect of water table level on soil respiration was best accounted for by incorporating a water level Gaussian function into the soil-temperature–soil-respiration model. Mean root respiration was 44% of mean total soil respiration, varying between 1100 and 2049 g CO2 m−2 year−1. Heterotrophic respiration was divided between peat respiration and litter respiration, which accounted for 35 and 21% of total soil respiration, respectively. While peat respiration varied between 774 and 1492 g CO2 m−2 year−1, litter respiration varied between 514 and 1013 g CO2 m−2 year−1. Although the extrapolation of these results to other sites should be done with caution, the empirical models developed for the entire dataset in this study are a useful tool to predict and simulate CO2 emissions in similar afforested peatlands (e.g. pine and spruce plantations) in temperate maritime climate conditions.

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Peatland Properties Influencing Greenhouse Gas Emissions and Removal

2022-01, Renou-Wilson, Florence, Byrne, Kenneth A., Flynn, Raymond, Premrov, Alina, Riondato, Emily, Saunders, Matthew, Walz, Kilian, Wilson, David

A nationwide peatland survey was conducted across 50 ombrotrophic peatlands (bogs) in Ireland to ascertain a wide range of peat properties. In addition to natural (relatively intact) sites, we surveyed the most prevalent peatland land use categories (LUCs): grassland, forestry and peat extraction (both industrial and domestic), as well as management options (deep drained; shallow drained; rewetting). Furthermore, the entirety of the peat profile (down to the sub-peat mineral soil/bedrock) was sampled. Our results demonstrate that Irish bogs have been drastically altered by human activities and that the sampled peat properties reflect the nature and magnitude of the impact of the land use and management.

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Modeling relevant factors and covariates of carbon stock changes in peatlands using a hierarchical linear mixed modeling approach

2020-05-08, Walz, Kilian, Byrne, Kenneth A., Wilson, David, Renou-Wilson, Florence

While peatlands constitute the largest soil carbon stock in Ireland with 75% of soil carbon stored in an area covering an estimated 20% of the land surface, carbon stocks of peatlands are affected by past and present disturbances related to various land uses. Afforestation, grazing and peat extraction for energy and horticultural use often are major drivers of peatland soil degradation. A comparative assessment of the impact of land disturbance on peatland soil carbon stocks on a national scale has been lacking so far. Current research, funded by the Irish Environmental Protection Agency (EPA), addresses this issue with the goal to fill various gaps related to mapping and modeling changes of soil carbon stock in Irish peatlands. Data from the first nationwide peatland survey forms the basis for this study, in which the influence of different factors and covariates on soil carbon distribution in peatlands is examined. After data exploratory analysis, a mixed linear modeling approach is tested for its suitability to explain peatland soil carbon distribution within the Republic of Ireland. Parameters are identified which are responsible for changes across the country. In addition, model performance to map peat soil carbon stock within a three-dimensional space is evaluated.