Abstract: Simulation of the biogeochemical cycles of extensively and intensively managed grasslands and croplands are of particular interest due to the strong connection between ecosystem production, animal husbandry and food security. In the frame of MACSUR LiveM activities, we conducted a series of „blind tests” (i.e. uncalibrated model simulations with previously optimized model) on differently managed grasslands within Europe and Israel. We used the latest version of Biome-BGC MuSo model, the modified version of the widely used biogeochemical Biome-BGC model. Biome-BGC MuSo contains structural improvements, development of management modules, and the extension of the model to simulate herbaceouos ecosystem carbon and water cycles more faithfully. The studied ecosystems were meadows and pastures located in a variety of climate zones from the Atlantic sector to Central Europe, including Mediterranean sites. Managements were intensive and extensive grazing or mowing with or without different kind of fertilizers. Under similar options we simulated ecosystem variables, e.g. Gross Primary Production (GPP) and Net Ecosystem Exchange (NEE). Our experiences show that different sites have different sensitivity to the parameters (maximum root depth, soil parameters, etc.), but overall the model provided realistic fluxes. Experiences gained during the blind tests led us to further improve the model. Biome-BGC MuSo is available as a standalone model in personal computers, but also through virtual laboratory environment and Biome-BGC Projects database (http://ecos.okologia.mta.hu/bbgcdb) developed within the BioVeL project (http://www.biovel.eu). Scientific workflow management, web service and desktop grid technology can support model optimization in the so-called „calibrated runs” within MACSUR.

Abstract: Two independently developed simulation models – the grassland-specific PaSim and the biome-generic Biome-BGC MuSo (BBGC MuSo) – linking climate, soil, vegetation and management to ecosystem biogeochemical cycles were compared in a simulation of carbon (C) and water fluxes. The results were assessed against eddy-covariance flux data from five observational grassland sites representing a range of conditions in Europe: Grillenburg in Germany, Laqueuille in France with both extensive and intensive management, Monte Bondone in Italy and Oensingen in Switzerland. Model comparison (after calibration) gave substantial agreement, the performances being marginal to acceptable for weekly-aggregated gross primary production and ecosystem respiration (R-2 similar to 0.66 – 0.91), weekly evapotranspiration (R-2 similar to 0.78 – 0.94), soil water content in the topsoil (R-2 similar to 0.1 -0.7) and soil temperature (R-2 similar to 0.88 – 0.96). The bias was limited to the range -13 to 9 g C m(-2) week(-1) for C fluxes (-11 to 8 g C m(-2) week(-1) in case of BBGC MuSo, and -13 to 9 g C m(-2) week(-1) in case of PaSim) and -4 to 6 mm week for water fluxes (with BBGC MuSo providing somewhat higher estimates than PaSim), but some higher relative root mean square errors indicate low accuracy for prediction, especially for net ecosystem exchange The sensitivity of simulated outputs to changes in atmospheric carbon dioxide concentration ([CO2]), temperature and precipitation indicate, with certain agreement between the two models, that C outcomes are dominated by [CO2] and temperature gradients, and are less due to precipitation. ET rates decrease with increasing [CO2] in PaSim (consistent with experimental knowledge), while lack of appropriate stomatal response could be a limit in BBGC MuSo responsiveness. Results of the study indicate that some of the errors might be related to the improper representation of soil water content and soil temperature. Improvement is needed in the model representations of soil processes (especially soil water balance) that strongly influence the biogeochemical cycles of managed and unmanaged grasslands. (C) 2015 Elsevier B.V. All rights reserved.