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The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen, and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as a base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil-moisture-related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multilayer soil module; in this paper, Biome-BGCMuSo v4.0 is documented).Case studies on a managed forest, cropland, and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance. [ABSTRACT FROM AUTHOR]

The process-based biogeochemical model Biome-BGC was enhanced to improve its ability to simulate carbon, nitrogen and water cycles of various terrestrial ecosystems under contrasting management activities. Biome-BGC version 4.1.1 was used as base model. Improvements included addition of new modules such as the multilayer soil module, implementation of processes related to soil moisture and nitrogen balance, soil moisture related plant senescence, and phenological development. Vegetation management modules with annually varying options were also implemented to simulate management practices of grasslands (mowing, grazing), croplands (ploughing, fertilizer application, planting, harvesting), and forests (thinning). New carbon and nitrogen pools have been defined to simulate yield and soft stem development of herbaceous ecosystems. The model version containing all developments is referred to as Biome-BGCMuSo (Biome-BGC with multi-layer soil module). Case studies on a managed forest, cropland and grassland are presented to demonstrate the effect of model developments on the simulation of plant growth as well as on carbon and water balance. [ABSTRACT FROM AUTHOR]

Climate Services (CS) provide support to decision makers across socio-economic sectors. In the agricultural sector, one of the most important CS applications is to provide timely and accurate yield forecasts based on climate prediction. In this study, the Pasture Simulation model (PaSim) is used to simulate, for the period 1959-2015, the forage production of a mown grassland system (Laqueuille, Massif Central of France) under different management conditions, with meteorological inputs extracted from the SAFRAN atmospheric database. The aim is to generate purely climate-dependent time series of optimal forage production, a variable that is found to maximize the years of brighter and warmer weather conditions at the grassland.In the long term, a remarkable increase in simulated forage yield (>29%) is obtained in all simulations between 1959-1979 and 1995-2015. Such increase seems consistent with observed rising trends in temperature and CO2 and multi-decadal changes in incident solar radiation. At interannual timescales, Sea Surface Temperature anomalies of the Mediterranean (MED), Tropical North Atlantic (TNA), equatorial Pacific (El Niño Southern Oscillation), and the North Atlantic Oscillation (NAO) index, appear robustly correlated with annual forage yield values. Relying on climatic predictors uniquely, a stepwise statistical multi-regression model with leave-one-out cross-validation is developed in this work. Under specific management conditions (e.g., 3 annual cuts) and from 1 to 5 months in advance, the generated model successfully provides a p-value<0.01 in correlation (t test), a root mean square error (RMSE) percentage of 14.6% (1.24 t DM ha-1) and a 71.43% hit rate predicting above/below average years in terms of forage yield collection. These results may help in stimulating the debate about understanding the climate mechanisms at play in European grasslands and provide a useful springboard to implement a grassland seasonal forecasting system in France. [ABSTRACT FROM AUTHOR]