EGU2020-4984, updated on 07 Dec 2024
https://doi.org/10.5194/egusphere-egu2020-4984
EGU General Assembly 2020
© Author(s) 2024. This work is distributed under
the Creative Commons Attribution 4.0 License.

Understanding and quantifying carbon cycling in managed grasslands through model-data fusion

Vasileios Myrgiotis1, Rob Clement1, Stephanie K. Jones2, Ben Keane4, Mark Lee2, Peter E. Levy3, Robert M. Rees2, Ute M. Skiba3, Luke T. Smallman1, Sylvia Toet4, Mathew Williams1, and Emanuel Blei1
Vasileios Myrgiotis et al.
  • 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.

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