Understanding and quantifying carbon cycling in managed grasslands through model-data fusion
- 1University of Edinburgh, Geosciences, Edinburgh, United Kingdom of Great Britain and Northern Ireland
- 2Scotland's Rural College, Edinburgh, United Kingdom of Great Britain and Northern Ireland
- 3Centre for Ecology and Hydrology, Edinburgh, United Kingdom of Great Britain and Northern Ireland
- 4University of York, Department of Environment and Geography, United Kingdom of Great Britain and Northern Ireland
Managed grasslands are extensive terrestrial ecosystems that provide a range of services. In addition to supporting the world’s various livestock production systems they contain climatically significant amounts of carbon (C). Understanding and quantifying the C dynamics of managed grasslands is complicated yet crucial.This presentation describes a process-model of C dynamics in managed grasslands (DALEC-Grass). DALEC-Grass is a model of intermediate complexity, which calculates primary productivity, dynamicallyallocates C to biomass tissues and describes the impacts of grazing/harvesting activities. The model is integrated into a Bayesian model-data fusion framework (CARDAMOM). CARDAMOM uses observations of ecosystem functioning (e.g. leaf area, biomass, C fluxes) to optimise the model’s parameters while respecting a set of biogeochemical and physiological rules. The model evaluation results presented demonstrate the model’s skill in predicting primary productivity and C allocation patterns in UK grasslands using both ground and satellite based leaf area index (LAI) time series as observational constraints.
How to cite: Myrgiotis, V., Clement, R., Jones, S. K., Keane, B., Lee, M., Levy, P. E., Rees, R. M., Skiba, U. M., Smallman, L. T., Toet, S., Williams, M., and Blei, E.: Understanding and quantifying carbon cycling in managed grasslands through model-data fusion, EGU General Assembly 2020, Online, 4–8 May 2020, EGU2020-4984, https://doi.org/10.5194/egusphere-egu2020-4984, 2020