@misc{MartreDueriBrownetal., author = {Martre, Pierre and Dueri, Sibylle and Brown, Hamish and Asseng, Senthold and Ewert, Frank and Webber, Heidi and George, Mike and Craigie, Rob and Guarin, Jose Rafael and Pequeno, Diego and Stella, Tommaso and Ahmed, Mukhtar and Alderman, Phillip and Basso, Bruno and Berger, Andres and Bracho Mujica, Gennady and Cammarano, Davide and Chen, Yi and Dumont, Benjamin and Rezaei, Ehsan Eyshi and Fereres, Elias and Ferrise, Roberto and Gaiser, Thomas and Gao, Yujing and Garcia-Vila, Margarita and Gayler, Sebastian and Hochman, Zvi and Hoogenboom, Gerrit and Kersebaum, Kurt C. and Nendel, Claas and Olesen, J{\o}rgen and Padovan, Gloria and Palosuo, Taru and Priesack, Eckart and Pullens, Johannes and Rodr{\´i}guez, Alfredo and R{\"o}tter, Reimund P. and Ruiz Ramos, Margarita and Semenov, Mikhail and Senapati, Nimai and Siebert, Stefan and Srivastava, Amit Kumar and St{\"o}ckle, Claudio and Supit, Iwan and Tao, Fulu and Thorburn, Peter and Wang, Enli and Weber, Tobias and Xiao, Liujun and Zhao, Chuang and Zhao, Jin and Zhao, Zhigan and Zhu, Yan}, title = {Winter wheat experiments to optimize sowing dates and densities in a high-yielding environment in New Zealand: field experiments and AgMIP-Wheat multi-model simulations}, series = {Open Data Journal for Agricultural Research}, volume = {10}, journal = {Open Data Journal for Agricultural Research}, publisher = {Wageningen University and Research}, issn = {2352-6378}, doi = {10.18174/odjar.v10i0.18442}, pages = {14 -- 21}, abstract = {This paper describes the data set that was used to test the accuracy of twenty-nine crop models in simulating the effect of changing sowing dates and sowing densities on wheat productivity for a high-yielding environment in New Zealand. The data includes one winter wheat cultivar (Wakanui) grown during six consecutive years, from 2012-2013 to 2017-2018, at two farms located in Leeston and Wakanui in Canterbury, New Zealand. The simulations were carried out in the framework of the Agricultural Model Intercomparison and Improvement Project for wheat (AgMIP-Wheat). Data include local daily weather data, soil profile characteristics and initial conditions, crop measurements at maturity (grain, stem, chaff and leaf dry weight, ear number and grain number, grain unit dry weight), and at stem elongation and anthesis (total above ground dry biomass, leaf number per stem and leaf area index). Several in-season measurements of the normalized difference vegetation index (NDVI) and the fraction of intercepted photosynthetically active radiation (FIPAR) are also available. The crop model simulations include both daily in-season and end-of-season results from twenty-nine wheat models.}, language = {en} } @misc{CouedelFalconnierAdametal., author = {Cou{\"e}del, Antoine and Falconnier, Gatien N. and Adam, Myriam and Cardinael, R{\´e}mi and Boote, Kenneth and Justes, Eric and Smith, Ward N. and Whitbread, Anthony Michael and Affholder, Fran{\c{c}}ois and Balkovic, Juraj and Basso, Bruno and Bhatia, Arti and Chakrabarti, Bidisha and Chikowo, Regis and Christina, Mathias and Faye, Babacar and Ferchaud, Fabien and Folberth, Christian and Akinseye, Folorunso M. and Gaiser, Thomas and Galdos, Marcelo V. and Gayler, Sebastian and Gorooei, Aram and Grant, Brian and Guibert, Herv{\´e} and Hoogenboom, Gerrit and Kamali, Bahareh and Laub, Moritz and Maureira, Fidel and Mequanint, Fasil and Nendel, Claas and Porter, Cheryl H. and Ripoche, Dominique and Ruane, Alex C. and Rusinamhodzi, Leonard and Sharma, Shikha and Singh, Upendra and Six, Johan and Srivastava, Amit Kumar and Vanlauwe, Bernard and Versini, Antoine and Vianna, Murilo and Webber, Heidi and Weber, Tobias K. D. and Zhang, Congmu and Corbeels, Marc}, title = {Long-term soil organic carbon and crop yield feedbacks differ between 16 soil-crop models in sub-Saharan Africa}, series = {European Journal of Agronomy}, volume = {155}, journal = {European Journal of Agronomy}, publisher = {Elsevier BV}, issn = {1161-0301}, doi = {10.1016/j.eja.2024.127109}, pages = {16}, abstract = {Food insecurity in sub-Saharan Africa is partly due to low staple crop yields, resulting from poor soil fertility and low nutrient inputs. Integrated soil fertility management (ISFM), which includes the combined use of mineral and organic fertilizers, can contribute to increasing yields and sustaining soil organic carbon (SOC) in the long term. Soil-crop simulation models can help assess the performance and trade-offs of a range of crop management practices including ISFM, under current and future climate. Yet, uncertainty in model simulations can be high, resulting from poor model calibration and/or inadequate model structure. Multi-model simulations have been shown to be more robust than those with single models and help understand and reduce modelling uncertainty. In this study, we aim to perform the first multi-model comparison for long-term simulations of crop yield and SOC and their feedbacks in SSA. We evaluated the performance of 16 soil-crop models using data from four long-term maize experiments at sites in SSA with contrasting climates and soils. Each experiment had four treatments: i) no exogenous inputs, ii) addition of mineral nitrogen (N) fertilizer, iii) use of organic amendments, and iv) combined use of mineral and organic inputs. We assessed model performance in two steps: through blind calibration involving a minimum level of experimental data provided to the modeling teams, and subsequently through full calibration, which included a more extensive set of observational data. Model ensemble accuracy was greater with full calibration than blind calibration. Improvement in model accuracy was larger for maize yields (nRMSE 48 vs 18\%) than for topsoil SOC (nRMSE 22 vs 14\%). Model ensemble uncertainty (defined as the coefficient of variation across the 16 models) increased over the duration of the long-term experiments. Uncertainty of SOC simulations increased when organic amendments were used, whilst uncertainty of yield predictions was largest when no inputs were applied. Our study revealed large discrepancies among the models in simulating i) crop-to-soil feedbacks due to uncertainties in simulated carbon coming from roots, and ii) soil-to-crop feedbacks due to large uncertainties in simulated crop N supply from soil organic matter decomposition. These discrepancies were largest when organic amendments were applied. The results highlight the need for long-term experiments in which root and soil N dynamics are monitored. This will provide the corresponding data to improve and calibrate soil-crop models, which will lead to more robust and reliable simulations of SOC and crop productivity, and their interactions.}, language = {en} }