@misc{TougmaVandeBroekSixetal., author = {Tougma, In{\`e}s Astrid and Van de Broek, Marijn and Six, Johan and Gaiser, Thomas and Holz, Maire and Zentgraf, Isabel and Webber, Heidi}, title = {AMPSOM: A measureable pool soil organic carbon and nitrogen model for arable cropping systems}, series = {Environmental Modelling \& Software}, volume = {185}, journal = {Environmental Modelling \& Software}, publisher = {Elsevier BV}, issn = {1364-8152}, doi = {10.1016/j.envsoft.2024.106291}, pages = {13}, abstract = {Most cropping system models simulate conceptual soil organic matter (SOM) pools, such as active, passive and slow pools that cannot be measured, complicating model calibration. In reality, SOM can be described in terms of quantifiable pools of particulate organic matter (POM) and mineral-associated organic matter (MAOM) which respond differently to management and climate. We present the AMPSOM model, integrated in a cropping system modelling framework (SIMPLACE). AMPSOM simulates carbon and nitrogen dynamics in MAOM and POM in response to crop growth and management, as well as soil texture, water and nitrogen content and temperature. It also simulates the radiocarbon isotope (14C) of soil organic carbon (SOC) to constrain the turnover time of slowly cycling SOC pools. Model calibration and evaluation were performed for thirty six sandy and loamy arable soils in Brandenburg, Germany. Results show that AMPSOM can reproduce observed patterns of SOC and nitrogen stocks in POM and MAOM along depth profiles across different soil types.}, language = {en} } @misc{NoiaJuniorMartreDeswarteetal., author = {N{\´o}ia-J{\´u}nior, Rog{\´e}rio de S. and Martre, Pierre and Deswarte, Jean-Charles and Cohan, Jean-Pierre and Van der Velde, Marijn and Webber, Heidi and Ewert, Frank and Ruane, Alex C. and Ben-Ari, Tamara and Asseng, Senthold}, title = {Past and future wheat yield losses in France's breadbasket}, series = {Field Crops Research}, volume = {322}, journal = {Field Crops Research}, publisher = {Elsevier BV}, issn = {0378-4290}, doi = {10.1016/j.fcr.2024.109703}, pages = {11}, abstract = {Context or problem: In recent decades, compounding weather extremes and plant diseases have increased wheat yield variability in France, the largest wheat producer in the European Union. Objective or research question: How these extremes might affect future wheat production remains unclear. Methods: Based on department level wheat yields, disease, and climate indices from 1980 to 2019 in France, we combined an existing disease model with machine learning algorithms to estimate future grain yields. Results: This approach explains about 59\% of historical yield variability. Projections from five CMIP6 climate models suggest that extreme low wheat yields, which used to occur once every 20 years, could occur every decade by the end of this century, but elevated CO2 levels might lessen these events. Conclusions: Heatwave-related yield losses are expected to double, while flooding-related yield losses will potentially decline by one third, depending on the representative concentration pathway. Ear blight disease is projected to contribute to 20\% of the expected 400 kg ha-1 average yield losses by the end of the century, compared with 12\% in the historical baseline period. These projections depend on the timing of anthesis, currently between late May and early June in most departments. Anthesis advancing to early May would shift losses primarily to heavy rainfall and low solar radiation. Implications or significance: French wheat production must adapt to these emerging threats, such as heat stress, which until recently had little impact but may become the primary cause of future yield losses.}, language = {en} } @misc{BagagnanBerreWebberetal., author = {Bagagnan, Abdoul Rasmane and Berre, David and Webber, Heidi and Lairez, Juliette and Sawadogo, Hamado and Descheemaeker, Katrien}, title = {From typology to criteria considered by farmers: what explains agroecological practice implementation in North-Sudanian Burkina Faso?}, series = {Frontiers in Sustainable Food Systems}, volume = {8}, journal = {Frontiers in Sustainable Food Systems}, publisher = {Frontiers Media SA}, issn = {2571-581X}, doi = {10.3389/fsufs.2024.1386143}, pages = {15}, abstract = {Cropping systems in the North-Sudanian zone of Burkina Faso face significant challenges related to poor yields, declining soil fertility and harsh climatic conditions. Together these necessitate a shift toward more sustainable farming practices. Agroecology aims to enhance yields while minimizing environmental harm through the use of ecological functions and has been promoted by researchers and farmers' organizations as a solution. However, its implementation remains limited. This study investigated the criteria farmers consider when implementing agroecological practices at the farm level and how these criteria and their implementation are influenced by farm characteristics. Data collection methods included the serious game TAKIT, together with baseline and complementary household surveys (108 farmers each). Farm diversity was analyzed using a statistical typology. The influence of farm types, farm structural variables and the village location on (1) whether or not agroecological practices were implemented and (2) the criteria considered by farmers was explored. Four distinct farm types were identified: low resource endowed farms relying on off-farm income, low resource endowed farms relying on livestock income, medium resource endowed farms relying on agricultural and livestock income, and high resource endowed farms with diverse sources of income. There were no significant differences in the implementation of agroecological practices across farm types. Crop rotations were the most frequently implemented practice (by 91\% of the study farmers), while the 2-by-2 line intercropping of sorghum-cowpea was the least implemented (9\% of farmers). Implementation of zai pits varied significantly between villages, with farmers in Nagreonkoudogo more likely to use them than those in Tanvousse, due to differing soil characteristics. Farmers considered several criteria when deciding whether to implement agroecological practices, including the ability to improve yield and preserve soil. Constraints to their implementation included a lack of knowledge and their high labor requirements. These criteria did not differ across farm types, likely because they stem from shared environmental constraints or conditions. The study highlights the complexity of agroecological transitions in sub-Saharan Africa, and illustrates the need to adequately consider contextual conditions. The co-design of new practices, and the redesign of existing ones, should align with criteria considered by farmers.}, language = {en} } @misc{SchallerWebberEwertetal., author = {Schaller, J{\"o}rg and Webber, Heidi and Ewert, Frank and Stein, Mathias and Puppe, Daniel}, title = {The transformation of agriculture towards a silicon improved sustainable and resilient crop production}, series = {npj Sustainable Agriculture}, volume = {2}, journal = {npj Sustainable Agriculture}, number = {1}, publisher = {Springer Science and Business Media LLC}, issn = {2731-9202}, doi = {10.1038/s44264-024-00035-z}, pages = {9}, abstract = {Sustainable and resilient crop production is facing many challenges. The restoration of natural reactive silicon cycles offers an opportunity to improve sustainability through reducing phosphorus fertilizer use and to increase crops' resilience to drought stress and pests. We therefore call upon farmers, agri-food-researchers, and policymakers to pave the road for transforming agriculture to a silicon-improved sustainable crop production, which represents a promising approach to achieve food security under global change.}, language = {en} } @misc{KimWebber, author = {Kim, Yean-Uk and Webber, Heidi}, title = {Contrasting responses of spring and aummer potato to climate change in South Korea}, series = {Potato Research}, volume = {67}, journal = {Potato Research}, number = {4}, publisher = {Springer Science and Business Media LLC}, issn = {0014-3065}, doi = {10.1007/s11540-024-09691-7}, pages = {1265 -- 1286}, abstract = {This paper assessed the effects of climate change and planting date adjustment on spring and summer potato in South Korea for the period 2061-2090. The study applied the SUBSTOR-Potato model and outputs of 24 general circulation models to capture future variability in climate conditions for four shared socioeconomic pathway-representative concentration pathway scenarios. Without planting date adjustment, tuber yield was projected to increase by approximately 20\% for spring and summer potato, indicating that the CO2 fertilization effect would offset the adverse effect of rising temperature. The effect of planting date adjustment was significant only for spring potato, where overall climate change impact with the optimized planting date was approximately  +60\%. For spring potato, the effects of rising temperature were bidirectional: temperature increases early in the year extended the growing season, whereas the higher temperature increases in June under the most severe climate change condition accelerated leaf senescence and reduced tuber bulking rate. Based on these results, different adaptation strategies could be established for spring potato for different climate change conditions. For example, developing frost-tolerant cultivars would continue to be recommended to plant earlier under the mild climate change conditions, whereas breeding mid-late maturity cultivars with high-temperature tolerance would be needed to delay senescence and enhance late tuber growth under the severe climate change conditions. Unlike spring potato, the breeding goal for summer potato of increasing high-temperature tolerance holds across all climate change conditions. Finally, these optimistic results should be interpreted with caution as the current model does not fully capture the effect of high-temperature episodes and the interactive effect between CO2 and temperature, which may reduce beneficial projected climate change impacts.}, language = {en} } @misc{Noia JuniorDeswarteCohanetal., author = {N{\´o}ia J{\´u}nior, Rog{\´e}rio de S. and Deswarte, Jean-Charles and Cohan, Jean-Pierre and Martre, Pierre and van der Velde, Marijn and Lecerf, Remi and Webber, Heidi and Ewert, Frank and Ruane, Alex C. and Slafer, Gustavo A. and Asseng, Senthold}, title = {The extreme 2016 wheat yield failure in France}, series = {Global Change Biology}, volume = {29}, journal = {Global Change Biology}, number = {11}, publisher = {Wiley}, issn = {1354-1013}, doi = {10.1111/gcb.16662}, pages = {3130 -- 3146}, abstract = {France suffered, in 2016, the most extreme wheat yield decline in recent history, with some districts losing 55\% yield. To attribute causes, we combined the largest coherent detailed wheat field experimental dataset with statistical and crop model techniques, climate information, and yield physiology. The 2016 yield was composed of up to 40\% fewer grains that were up to 30\% lighter than expected across eight research stations in France. The flowering stage was affected by prolonged cloud cover and heavy rainfall when 31\% of the loss in grain yield was incurred from reduced solar radiation and 19\% from floret damage. Grain filling was also affected as 26\% of grain yield loss was caused by soil anoxia, 11\% by fungal foliar diseases, and 10\% by ear blight. Compounding climate effects caused the extreme yield decline. The likelihood of these compound factors recurring under future climate change is estimated to change with a higher frequency of extremely low wheat yields.}, language = {en} } @misc{DiancoumbaMacCarthyWebberetal., author = {Diancoumba, M. and MacCarthy, Dilys Sefakor and Webber, Heidi and Akinseye, Folorunso M. and Faye, Babacar and Noul{\`e}koun, Florent and Whitbread, Anthony Michael and Corbeels, Marc and Worou, Nadine O.}, title = {Scientific agenda for climate risk and impact assessment of West African cropping systems}, series = {Global Food Security}, volume = {38}, journal = {Global Food Security}, publisher = {Elsevier BV}, issn = {2211-9124}, doi = {10.1016/j.gfs.2023.100710}, pages = {4}, abstract = {Rainfed agriculture is at the centre of many West African economies and a key livelihood strategy in the region. Highly variable rainfall patterns lead to a situation in which farmers' investments to increase productivity are very risky and will become more risky with climate change. Process-based cropping system models are a key tool to assess the impact of weather variability and climate change, as well as the effect of crop management options on crop yields, soil fertility and farming system resilience and widely used by the West African scientific community. Challenges to use are related to their consideration of the prevailing systems and conditions of West African farms, as well as limited data availability for calibration. We outline here a number of factors need to be considered if they are to contribute to the scientific basis underlying transformation of farming systems towards sustainability. These include: capacity building, improved models, FAIR data, research partnerships and using models in co-development settings.}, language = {en} } @misc{RezaeiFayeEwertetal., author = {Rezaei, Ehsan Eyshi and Faye, Babacar and Ewert, Frank and Asseng, Senthold and Martre, Pierre and Webber, Heidi}, title = {Impact of coupled input data source-resolution and aggregation on contributions of high-yielding traits to simulated wheat yield}, series = {Scientific Reports}, volume = {14}, journal = {Scientific Reports}, number = {1}, publisher = {Springer Science and Business Media LLC}, issn = {2045-2322}, doi = {10.1038/s41598-024-74309-4}, pages = {11}, abstract = {High-yielding traits can potentially improve yield performance under climate change. However, data for these traits are limited to specific field sites. Despite this limitation, field-scale calibrated crop models for high-yielding traits are being applied over large scales using gridded weather and soil datasets. This study investigates the implications of this practice. The SIMPLACE modeling platform was applied using field, 1 km, 25 km, and 50 km input data resolution and sources, with 1881 combinations of three traits [radiation use efficiency (RUE), light extinction coefficient (K), and fruiting efficiency (FE)] for the period 2001-2010 across Germany. Simulations at the grid level were aggregated to the administrative units, enabling the quantification of the aggregation effect. The simulated yield increased by between 1.4 and 3.1 t ha- 1 with a maximum RUE trait value, compared to a control cultivar. No significant yield improvement (\< 0.4 t ha- 1) was observed with increases in K and FE alone. Utilizing field-scale input data showed the greatest yield improvement per unit increment in RUE. Resolution of water related inputs (soil characteristics and precipitation) had a notably higher impact on simulated yield than of temperature. However, it did not alter the effects of high-yielding traits on yield. Simulated yields were only slightly affected by data aggregation for the different trait combinations. Warm-dry conditions diminished the benefits of high-yielding traits, suggesting that benefits from high-yielding traits depend on environments. The current findings emphasize the critical role of input data resolution and source in quantifying a large-scale impact of high-yielding traits.}, language = {en} } @misc{MartreDueriGuarinetal., author = {Martre, Pierre and Dueri, Sibylle and Guarin, Jose Rafael and Ewert, Frank and Webber, Heidi and Calderini, Daniel and Molero, Gemma and Reynolds, Matthew and Miralles, Daniel and Garcia, Guillermo and Brown, Hamish and George, Mike and Craigie, Rob and Cohan, Jean-Pierre and Deswarte, Jean-Charles and Slafer, Gustavo A. and Giunta, Francesco and Cammarano, Davide and Ferrise, Roberto and Gaiser, Thomas and Gao, Yujing and Hochman, Zvi and Hoogenboom, Gerrit and Hunt, Leslie A. and Kersebaum, Kurt C. and Nendel, Claas and Padovan, Gloria and Ruane, Alex C. and Srivastava, Amit Kumar and Stella, Tommaso and Supit, Iwan and Thorburn, Peter and Wang, Enli and Wolf, Joost and Zhao, Chuang and Zhao, Zhigan and Asseng, Senthold}, title = {Global needs for nitrogen fertilizer to improve wheat yield under climate change}, series = {Nature Plants}, volume = {10}, journal = {Nature Plants}, number = {7}, publisher = {Springer Science and Business Media LLC}, issn = {2055-0278}, doi = {10.1038/s41477-024-01739-3}, pages = {1081 -- 1090}, language = {en} } @misc{KimWebberAdikuetal., author = {Kim, Yean-Uk and Webber, Heidi and Adiku, Samuel G.K. and N{\´o}ia J{\´u}nior, Rog{\´e}rio de S. and Deswarte, Jean-Charles and Asseng, Senthold and Ewert, Frank}, title = {Mechanisms and modelling approaches for excessive rainfall stress on cereals: waterlogging, submergence, lodging, pests and diseases}, series = {Agricultural and Forest Meteorology}, volume = {344}, journal = {Agricultural and Forest Meteorology}, publisher = {Elsevier BV}, issn = {0168-1923}, doi = {10.1016/j.agrformet.2023.109819}, pages = {13}, abstract = {As the intensity and frequency of extreme weather events are projected to increase under climate change, assessing their impact on cropping systems and exploring feasible adaptation options is increasingly critical. Process-based crop models (PBCMs), which are widely used in climate change impact assessments, have improved in simulating the impacts of major extreme weather events such as heatwaves and droughts but still fail to reproduce low crop yields under wet conditions. Here, we provide an overview of yield-loss mechanisms of excessive rainfall in cereals (i.e., waterlogging, submergence, lodging, pests and diseases) and associated modelling approaches with the aim of guiding PBCM improvements. Some PBCMs simulate waterlogging and ponding environments, but few capture aeration stresses on crop growth. Lodging is often neglected by PBCMs; however, some stand-alone mechanistic lodging models exist, which can potentially be incorporated into PBCMs. Some frameworks link process-based epidemic and crop models with consideration of different damage mechanisms. However, the lack of data to calibrate and evaluate these model functions limit the use of such frameworks. In order to generate data for model improvement and close knowledge gaps, targeted experiments on damage mechanisms of waterlogging, submergence, pests and diseases are required. However, consideration of all damage mechanisms in PBCM may result in excessively complex models with a large number of parameters, increasing model uncertainty. Modular frameworks could assist in selecting necessary mechanisms and lead to appropriate model structures and complexity that fit a specific research question. Lastly, there are potential synergies between PBCMs, statistical models, and remotely sensed data that could improve the prediction accuracy and understanding of current PBCMs' shortcomings.}, language = {en} } @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} }