Background
Future climate uncertainties highlight the need to develop biogeochemical-hydrological models to identify, evaluate, and predict the major controls on carbon and nutrient cycling in peatland soils under anthropogenic disturbances.
In this project activity, we aim to improve our conceptual and quantitative understanding of the function of soil biogeochemical processes that regulate the changes in carbon and nutrient driven by variations in anthropogenic disturbances. We mainly focus on regional scale evaluation of carbon stocks and reactivity sub-models that can be incorporated into the Canadian Model for Peatlands (CaMP) (and eventually the Carbon Budget Model of the Canadian Forest Sector) by greenhouse gas emission-related data in the models. The data (e.g., aboveground biomass, belowground biomass, litter, dead wood and soil organic carbon) from the compilation of peatland datasets for selected regional scale peatland catchments, coupled to the past and ongoing data, will be integrated into a coupled biogeochemistry-hydrology model, which will yield a better representation of soil carbon stocks. This will be achieved by:
Activity Outline
- Providing regional scale process-level knowledge and data to be scaled up using modeling approaches, including Machine Learning algorithms, to forecast possible future trajectories of peatlands greenhouse gas emissions under various scenarios of environmental change
- Validating the model parameters with key environmental drivers through a peat incubation study