Determine potential for greenhouse gas emission reductions through best management practices for peatland development


Avoided peatland conversion will protect ecosystem carbon stocks and greenhouse gas uptake, while restoration can protect residual carbon and reinstate greenhouse gas sink function. In addition to these actions, best management practices (BMPs) during land-use that results in peatland disturbance can mitigate greenhouse gas emissions. Examples of BMPs could include application of low-impact forest harvest or geological exploration practices in peatland (e.g., winter access, low-impact seismic lines), reduced hydrologic impact of roads (e.g., culverts, permeable fill). To determine the potential for best management practices to lead to greenhouse gas emission reductions, data on the response of peatlands to disturbance under “business-as-usual” disturbance activities and under best management practices are required. These can then be compared to undisturbed peatlands to determine induced emissions and emission reductions associated with BMPs. Understanding how BMPs affect drivers of carbon storage and greenhouse gas exchange, such as plant community composition, water table position, and water chemistry, will enable empirical modelling of potential for BMPs to reduce greenhouse gas emissions as well as the incorporation of these actions into site to national scale peatland models.

Activity Outline

  • Compile data on carbon stocks and fluxes from peatlands affected by a variety of disturbance types
  • Compare compiled data to natural reference peatland carbon stocks and fluxes when available in the original source, or to regionally representative peatlands using data in the Can-Peat data repository to determine the impact of disturbances
  • Evaluate and assign each study to high and low-impact classes for each disturbance type
  • Compare between these classes to assess the potential to mitigate emissions
  • Evaluate controls on greenhouse gas emissions and incorporate significant variables into empirical models to predict disturbance effects
  • Use these simple models in scenarios to further evaluate the potential to mitigate induced emissions by limiting changes in environmental drivers