Dr Nicolas Puche1, Dr Nimai Senapati2, Dr Chris Flechard3, Dr Katja Klumpp4, Dr Miko Kirschbaum5, Dr Abad Chabbi6
1INRA, UMR ECOSYS, Thiverval-grignon, France, 2Rothamsted Research, Department of Plant Sciences, West Common/Harpenden, United Kingdom, 3INRA, UMR 1069 SAS, Rennes, France, 4INRA, VetAgro Sup, UMR 874 Ecosystème Prairial, Clermont Ferrand, France, 5Manaaki Whenua – Landcare Research, Palmerston North 4442, New Zealand, 6INRA, URP3F, Lusignan, France
The CenW ecosystem model simulates carbon, water, and nitrogen cycles following ecophysiological processes and management practices on a daily basis. In the first part of the study, we tested and evaluated the model using five years eddy covariance measurements from two adjacent but differently managed grasslands in France. The data were used to parameterize CenW for the two grassland sites until good agreements, i.e., high model efficiencies and correlations, between observed and modeled fluxes were achieved. The CenW model captured day-to-day, seasonal, and interannual variability observed in measured CO₂ and water fluxes. We also showed that following mowing and grazing, carbon gain was severely curtailed through a sharp and severe reduction in photosynthesizing biomass. We also identified large model/data discrepancies for carbon fluxes during grazing events caused by the noncapture by the eddy covariance system of large respiratory losses of C from dairy cows when they were present in the paddocks. The missing component of cows’ respiration in the net carbon budget of the grazed grassland can turn sites from being C sinks to being neutral or C sources, highlighting that extra care is needed in the processing of eddy covariance data from grazed grasslands to correctly calculate their annual CO₂ balances and carbon budgets. In the second part of the study, the calibrated CenW model was used to get a better understanding on how grasslands ecosystems and their soil carbon stocks will respond to future climate and to changes in management practices. We used 3 different sets of meteorological variables corresponding to possible future conditions at the study site according to RCP 2.6, 4.5 and 8.5 to run the model for long term. We showed that the long-term grassland productivity, milk production, carbon and water fluxes and soil carbon stocks were strongly modified by climate alteration.