TY - JOUR A1 - Kamali, Bahareh A1 - Stella, Tommaso A1 - Berg-Mohnicke, Michael A1 - Pickert, Jürgen A1 - Groh, Jannis A1 - Nendel, Claas T1 - Improving the simulation of permanent grasslands across Germany by using multi-objective uncertainty-based calibration of plant-water dynamics JF - European journal of agronomy N2 - The dynamics of grassland ecosystems are highly complex due to multifaceted interactions among their soil, water, and vegetation components. Precise simulations of grassland productivity therefore rely on accurately estimating a variety of parameters that characterize different processes of these systems. This study applied three calibration schemes - a Single-Objective (SO-SUFI2), a Multi-Objective Pareto (MO-Pareto), and, a novel Uncertainty-Based Multi-Objective (MO-SUFI2) - to estimate the parameters of MONICA (Model for Nitrogen and Carbon Simulation) agro-ecosystem model in grassland ecosystems across Germany. The MO-Pareto model is based on a traditional Pareto optimality concept, while the MO-SUFI2 optimizes multiple target variables considering their level of prediction uncertainty. We used measurements of leaf area index, aboveground biomass, and soil moisture from experimental data at five sites with different intensities of cutting regimes (from two to five cutting events per season) to evaluate model performance. Both MO-Pareto and MO-SUFI2 outperformed SO-SUFI2 during calibration and validation. The comparison of the two MO approaches shows that they do not necessarily conflict with each other, but MO-SUFI2 provides complementary information for better estimations of model parameter uncertainty. We used the obtained parameter ranges to simulate grassland productivity across Germany under different cutting regimes and quantified the uncertainty associated with estimated productivity across regions. The results showed higher uncertainty in intensively managed grasslands compared to extensively managed grasslands, partially due to a lack of high-resolution input information concerning cutting dates. Furthermore, the additional information on the quantified uncertainty provided by our proposed MO-SUFI2 method adds deeper insights on confidence levels of estimated productivity. Benefiting from additional management data collected at high resolution and ground measurements on the composition of grassland species mixtures appear to be promising solutions to reduce uncertainty and increase model reliability. KW - intensively managed grasslands KW - extensively managed grasslands KW - grassland productivity KW - pareto optimality Y1 - 2022 U6 - https://doi.org/10.1016/j.eja.2022.126464 SN - 1161-0301 SN - 1873-7331 VL - 134 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Pohanková, Eva A1 - Hlavinka, Petr A1 - Kersebaum, Kurt-Christian A1 - Rodríguez, Alfredo A1 - Balek, Jan A1 - Bednařík, Martin A1 - Dubrovský, Martin A1 - Gobin, Anne A1 - Hoogenboom, Gerrit A1 - Moriondo, Marco A1 - Nendel, Claas A1 - Olesen, Jørgen E. E. A1 - Rötter, Reimund Paul A1 - Ruiz-Ramos, Margarita A1 - Shelia, Vakhtang A1 - Stella, Tommaso A1 - Hoffmann, Munir Paul A1 - Takáč, Jozef A1 - Eitzinger, Josef A1 - Dibari, Camilla A1 - Ferrise, Roberto A1 - Bláhová, Monika A1 - Trnka, Miroslav T1 - Expected effects of climate change on the production and water use of crop rotation management reproduced by crop model ensemble for Czech Republic sites JF - European journal of agronomy N2 - Crop rotation, fertilization and residue management affect the water balance and crop production and can lead to different sensitivities to climate change. To assess the impacts of climate change on crop rotations (CRs), the crop model ensemble (APSIM,AQUACROP, CROPSYST, DAISY, DSSAT, HERMES, MONICA) was used. The yields and water balance of two CRs with the same set of crops (winter wheat, silage maize, spring barley and winter rape) in a continuous transient run from 1961 to 2080 were simulated. CR1 was without cover crops and without manure application. Straw after the harvest was exported from the fields. CR2 included cover crops, manure application and crop residue retention left on field. Simulations were performed using two soil types (Chernozem, Cambisol) within three sites in the Czech Republic, which represent temperature and precipitation gradients for crops in Central Europe. For the description of future climatic conditions, seven climate scenarios were used. Six of them had increasing CO & nbsp;concentrations according RCP 8.5, one had no CO2 increase in the future. The output of an ensemble expected higher productivity by 0.82 t/ha/year and 2.04 t/ha/year for yields and aboveground biomass in the future (2051-2080). However, if the direct effect of a CO2 increase is not considered, the average yields for lowlands will be lower. Compared to CR1, CR2 showed higher average yields of 1.26 t/ha/year for current climatic conditions and 1.41 t/ha/year for future climatic conditions. For the majority of climate change scenarios, the crop model ensemble agrees on the projected yield increase in C3 crops in the future for CR2 but not for CR1. Higher agreement for future yield increases was found for Chernozem, while for Cambisol, lower yields under dry climate scenarios are expected. For silage maize, changes in simulated yields depend on locality. If the same hybrid will be used in the future, then yield reductions should be expected within lower altitudes. The results indicate the potential for higher biomass production from cover crops, but CR2 is associated with almost 120 mm higher evapotranspiration compared to that of CR1 over a 5-year cycle for lowland stations in the future, which in the case of the rainfed agriculture could affect the long-term soil water balance. This could affect groundwater replenishment, especially for locations with fine textured soils, although the findings of this study highlight the potential for the soil water-holding capacity to buffer against the adverse weather conditions. KW - Yields KW - Evapotranspiration KW - Winter wheat KW - Silage maize KW - Spring barley KW - Winter oilseed rape Y1 - 2022 U6 - https://doi.org/10.1016/j.eja.2021.126446 SN - 1161-0301 SN - 1873-7331 VL - 134 PB - Elsevier CY - Amsterdam ER - TY - JOUR A1 - Nendel, Claas A1 - Reckling, Moritz A1 - Debaeke, Philippe A1 - Schulz, Susanne A1 - Berg-Mohnicke, Michael A1 - Constantin, Julie A1 - Fronzek, Stefan A1 - Hoffmann, Munir A1 - Jakšić, Snežana A1 - Kersebaum, Kurt-Christian A1 - Klimek-Kopyra, Agnieszka A1 - Raynal, Hélène A1 - Schoving, Céline A1 - Stella, Tommaso A1 - Battisti, Rafael T1 - Future area expansion outweighs increasing drought risk for soybean in Europe JF - Global change biology N2 - The European Union is highly dependent on soybean imports from overseas to meet its protein demands. Individual Member States have been quick to declare self-sufficiency targets for plant-based proteins, but detailed strategies are still lacking. Rising global temperatures have painted an image of a bright future for soybean production in Europe, but emerging climatic risks such as drought have so far not been included in any of those outlooks. Here, we present simulations of future soybean production and the most prominent risk factors across Europe using an ensemble of climate and soybean growth models. Projections suggest a substantial increase in potential soybean production area and productivity in Central Europe, while southern European production would become increasingly dependent on supplementary irrigation. Average productivity would rise by 8.3% (RCP 4.5) to 8.7% (RCP 8.5) as a result of improved growing conditions (plant physiology benefiting from rising temperature and CO2 levels) and farmers adapting to them by using cultivars with longer phenological cycles. Suitable production area would rise by 31.4% (RCP 4.5) to 37.7% (RCP 8.5) by the mid-century, contributing considerably more than productivity increase to the production potential for closing the protein gap in Europe. While wet conditions at harvest and incidental cold spells are the current key challenges for extending soybean production, the models and climate data analysis anticipate that drought and heat will become the dominant limitations in the future. Breeding for heat-tolerant and water-efficient genotypes is needed to further improve soybean adaptation to changing climatic conditions. KW - genotypes KW - legumes KW - maturity groups KW - protein crops KW - protein transition KW - resilience Y1 - 2022 U6 - https://doi.org/10.1111/gcb.16562 SN - 1354-1013 SN - 1365-2486 VL - 29 IS - 5 SP - 1340 EP - 1358 PB - Wiley-Blackwell CY - Ocford [u.a] ER -