Soil nitrogen mineralisation simulated by crop models across different environments and the consequences for model improvement Claas Nendel , P Thorburn , Michael Melzer , Carlos Eduardo P Cerri , L Claessens , PK Aggarwal , Myriam Adam , C Angulo , Senthold Asseng , Christian Baron , Bruno Basso , Simona Bassu , Patrick Bertuzzi , Christian Biernath , Hendrik Boogaard , Kenneth J Boote , Nadine Brisson , Davide Cammarano , Sjaak Conjin , Marc Corbeels , Delphine Deryng , Giacomo De Sanctis , J Doltra , Jean-Louis Durand , Franck Ewert , Sebastian Gayler , Richard Goldberg , RF Grant , Patricio Grassini , L Heng , Steven B Hoek , J Hooker , LA Hunt , J Ingwersen , Cesar Izaurralde , Raymond Jongschaap , Armen Kemanian , KC Kersebaum , Jon Lizaso , David Makowski , Pierre Martre , Christoph Müller , Soo-Hyung Kim , Sora Naresh Kumar , GJ O'Leary , Jørgen E Olesen , TM Osborne , T Palosuo , Maria Virginia Pravia , Eckart Priesack , Dominique Ripoche , R Rötter , Federico Sau , MA Semenov , Iurii Shcherbak , P Steduto , C Stöckle , P Stratonovitch , T Streck , Iwan Supit , F Tao , Edmar Teixeira , Dennis Timlin , M Travasso , K Waha , Daniel Wallach , Jeffrey W White , Joost Wolf user-5f1692da4c775ed682f59262（2016）
摘要
Crop models are the state-of-the-art tool to predict crop yields in the context of climate change and food security. The uncertainty associated with their use can be partly overcome by using multi-model ensembles (mme), though model improvement
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