Publications by authors named "Kurt-Christian Kersebaum"

Article Synopsis
  • Lack of nitrogen in poor countries hampers food production, while excess nitrogen in industrialized nations breaches environmental limits.
  • A global crop model study shows that redistributing nitrogen inputs can potentially double cereal production in food-insecure areas and boost global output by 12% without major regional losses.
  • The research outlines strategies to redistribute nitrogen use effectively, aiming to improve food security while maintaining ecological balance.
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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.

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Winter cover crops are sown in between main spring crops (e.g. cash and forage crops) to provide a range of benefits, including the reduction of nitrogen (N) leaching losses to groundwater.

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Smallholder farmers in sub-Saharan Africa (SSA) currently grow rainfed maize with limited inputs including fertilizer. Climate change may exacerbate current production constraints. Crop models can help quantify the potential impact of climate change on maize yields, but a comprehensive multimodel assessment of simulation accuracy and uncertainty in these low-input systems is currently lacking.

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Yield development of agricultural crops over time is not merely the result of genetic and agronomic factors, but also the outcome of a complex interaction between climatic and site-specific soil conditions. However, the influence of past climatic changes on yield trends remains unclear, particularly under consideration of different soil conditions. In this study, we determine the effects of single agrometeorological factors on the evolution of German winter wheat yields between 1958 and 2015 from 298 published nitrogen (N)-fertilization experiments.

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Global warming is expected to increase the frequency and intensity of severe water scarcity (SWS) events, which negatively affect rain-fed crops such as wheat, a key source of calories and protein for humans. Here, we develop a method to simultaneously quantify SWS over the world's entire wheat-growing area and calculate the probabilities of multiple/sequential SWS events for baseline and future climates. Our projections show that, without climate change mitigation (representative concentration pathway 8.

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The impact of climate change could undermine the future grain production as a consequence of increased temperature and drought condition or improve the crop performance owing to the increased CO in the atmosphere. Wheat water demand and yield are strictly related to climate conditions of the area where the plants are cropped. In this study, we assessed the future trends of grain yield and water consumption in two European regions, Germany (Continental region) and Italy (Mediterranean region) in the light of the multiple sources of uncertainty related to climate and yield forecasts.

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Food security relies on the resilience of staple food crops to climatic variability and extremes, but the climate resilience of European wheat is unknown. A diversity of responses to disturbance is considered a key determinant of resilience. The capacity of a sole crop genotype to perform well under climatic variability is limited; therefore, a set of cultivars with diverse responses to weather conditions critical to crop yield is required.

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Article Synopsis
  • Wheat grain protein concentration is crucial for nutrition but often overlooked in crop production improvements.
  • A study using a multi-model ensemble predicts that while increased CO levels might initially boost wheat yields, rising temperatures and altered rainfall patterns will likely negate these benefits, especially in low-rainfall areas.
  • Adapting wheat genotypes to warmer conditions could increase overall yields but may lead to a decrease in grain protein concentration, highlighting the challenge of balancing quantity and quality in wheat production amid climate change.
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Understanding the drivers of yield levels under climate change is required to support adaptation planning and respond to changing production risks. This study uses an ensemble of crop models applied on a spatial grid to quantify the contributions of various climatic drivers to past yield variability in grain maize and winter wheat of European cropping systems (1984-2009) and drivers of climate change impacts to 2050. Results reveal that for the current genotypes and mix of irrigated and rainfed production, climate change would lead to yield losses for grain maize and gains for winter wheat.

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Article Synopsis
  • Climate change impact assessments often face uncertainties from various sources, including climate projections and inadequacies in model parameters.
  • A new study developed a triple-ensemble probabilistic assessment using seven crop models, multiple parameters, and eight climate projections to evaluate the impact on barley growth and yield in Finland and Spain for the 2050s.
  • The results showed varied effects on yield, with a median change of -4% in Finland and +16% in Spain, highlighting that crop model structure contributed most to the uncertainty in outcomes, offering insights for model users on where to focus their efforts.
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We show the error in water-limited yields simulated by crop models which is associated with spatially aggregated soil and climate input data. Crop simulations at large scales (regional, national, continental) frequently use input data of low resolution. Therefore, climate and soil data are often generated via averaging and sampling by area majority.

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Crop models of crop growth are increasingly used to quantify the impact of global changes due to climate or crop management. Therefore, accuracy of simulation results is a major concern. Studies with ensembles of crop models can give valuable information about model accuracy and uncertainty, but such studies are difficult to organize and have only recently begun.

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