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    Multimodel Evaluation of Nitrous Oxide Emissions From an Intensively Managed Grassland
    (Hoboken, NJ : Wiley, 2020) Fuchs, Kathrin; Merbold, Lutz; Buchmann, Nina; Bretscher, Daniel; Brilli, Lorenzo; Fitton, Nuala; Topp, Cairistiona F.E.; Klumpp, Katja; Lieffering, Mark; Martin, Raphaël; Newton, Paul C.D.; Rees, Robert M.; Rolinski, Susanne; Smith, Pete; Snow, Val
    Process-based models are useful for assessing the impact of changing management practices and climate on yields and greenhouse gas (GHG) emissions from agricultural systems such as grasslands. They can be used to construct national GHG inventories using a Tier 3 approach. However, accurate simulations of nitrous oxide (N2O) fluxes remain challenging. Models are limited by our understanding of soil-plant-microbe interactions and the impact of uncertainty in measured input parameters on simulated outputs. To improve model performance, thorough evaluations against in situ measurements are needed. Experimental data of N2O emissions under two management practices (control with typical fertilization versus increased clover and no fertilization) were acquired in a Swiss field experiment. We conducted a multimodel evaluation with three commonly used biogeochemical models (DayCent in two variants, PaSim, APSIM in two variants) comparing four years of data. DayCent was the most accurate model for simulating N2O fluxes on annual timescales, while APSIM was most accurate for daily N2O fluxes. The multimodel ensemble average reduced the error in estimated annual fluxes by 41% compared to an estimate using the Intergovernmental Panel on Climate Change (IPCC)-derived method for the Swiss agricultural GHG inventory (IPCC-Swiss), but individual models were not systematically more accurate than IPCC-Swiss. The model ensemble overestimated the N2O mitigation effect of the clover-based treatment (measured: 39–45%; ensemble: 52–57%) but was more accurate than IPCC-Swiss (IPCC-Swiss: 72–81%). These results suggest that multimodel ensembles are valuable for estimating the impact of climate and management on N2O emissions. ©2019. The Authors.
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    Silicon Isotopes in an EMIC's Ocean: Sensitivity to Runoff, Iron Supply, and Climate
    (Hoboken, NJ : Wiley, 2020) Dietze, H.; Löptien, U.; Hordoir, R.; Heinemann, M.; Huiskamp, W.; Schneider, B.
    The isotopic composition of Si in biogenic silica (BSi), such as opal buried in the oceans' sediments, has changed over time. Paleorecords suggest that the isotopic composition, described in terms of d30Si, was generally much lower during glacial times than today. There is consensus that this variability is attributable to differing environmental conditions at the respective time of BSi production and sedimentation. The detailed links between environmental conditions and the isotopic composition of BSi in the sediments remain, however, poorly constrained. In this study, we explore the effects of a suite of offset boundary conditions during the Last Glacial Maximum (LGM) on the isotopic composition of BSi archived in sediments in an Earth System Model of intermediate complexity (EMIC). Our model results suggest that a change in the isotopic composition of Si supply to the glacial ocean is sufficient to explain the observed overall low(er) glacial d30Si in BSi. All other processes explored trigger model responses of either wrong sign or magnitude or are inconsistent with a recent estimate of bottom water oxygenation in the Atlantic Sector of the Southern Ocean. Caveats, mainly associated with generic uncertainties in today's pelagic biogeochemical modules, remain. © 2020. The Authors.