Sensitivity of European wheat to extreme weather

Mäkinen, Hanna; Kaseva, Janne; Trnka, Miroslav; Bálek, Jan; Kersebaum, Kurt Christian; Nendel, Claas; Gobin, Anne; Olesen, Jørgen E.; Bindi, Marco; Ferrise, Roberto; Moriondo, Marco; Rodríguez, Alfredo; Ruiz‐Ramos, Margarita; Takáč, Jozef; Bezak, Pavol; Ventrella, Domenico; Ruget, Françoise; Capellades, Gemma; Kahiluoto, Helena

doi:10.1016/j.fcr.2017.11.008

Cited by 118 publications

(102 citation statements)

References 45 publications

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“…By analysing the characteristic parameters distribution, it is found that the winter wheat vulnerability in Europe is lower to the south, particularly in the surrounding areas of the Mediterranean, which is consistent with Mäkinen's findings based on experimental data on wheat varieties (Mäkinen et al, 2018).…”

Section: Application Of Vulnerability Curvesupporting

confidence: 87%

Establishment and characteristics analysis of a crop-drought vulnerability curve: a case study of European winter wheat

Guo

Zhang

et al. 2019

Preprint

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As an essential component of drought risk, crop-drought vulnerability refers to the degree of 10 the adverse response of a crop to a drought event. Different drought intensities and environments can cause significant differences in crop yield losses. Therefore, quantifying the drought vulnerability and then identifying its spatial distribution pattern will contribute to understanding vulnerability and the development of risk-reduction strategies. We select the European winter wheat growing area as the study area and 0.5°×0.5° grids as the basic assessment units. Winter wheat drought vulnerability curves are 15 established based on the Erosion-Productivity Impact Calculator model simulation. Their loss transmutation and loss extent characteristics are quantitatively analysed by the key points and cumulative loss rate, respectively, and are then synthetically identified VIA K-means clustering. The results show the following. (1) The regional yield loss rate starts to rapidly increase from 0.13 when the drought index reaches 0.18 and then converts to a relatively stable stage with the value of 0.74 when the drought index 20 reaches 0.66. (2) The stage transitions of the vulnerability curve lag in the southern mountain area, indicating a stronger tolerance to drought in the system, in contrast to the Pod Plain. (3) According to the loss characteristics during the initial, development and attenuation stages, the vulnerability curves can be divided into five clusters, namely, Low-Low-Low, Low-Low-Medium, Medium-Medium-Medium, High-High-High and Low-Medium-High loss types, corresponding to the spatial distribution from low 25 latitude to high latitude and from mountain to plain. It is recommended to improve the integrated mitigation capability in the Medium-Medium-Medium and High-High-High loss type areas and to develop the ability to mitigate droughts in the 0.3-0.6 intensity range, as non-engineering measures for the droughts greater than 0.6 intensity in Low-Medium-High loss type areas.

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Section: Application Of Vulnerability Curvesupporting

confidence: 87%

Establishment and characteristics analysis of a crop-drought vulnerability curve: a case study of European winter wheat

Guo

Zhang

et al. 2019

Preprint

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“…Collectively, these studies demonstrate how the temporal pattern and event size of precipitation and resulting soil moisture regime represent an important knowledge gap. Recent studies suggest that heavy rainfall caused even greater negative effects on grass reproduction and wheat yield than extreme drought (Gellesch et al ., ; Mäkinen et al ., ), which is often presumed to have the strongest and most widespread effects on terrestrial ecosystems (Reichstein et al ., ; Frank et al ., ). However, except for these limited examples, little is known about heavy rainfall impacts across multiple hierarchical levels from individual plants to the ecosystem scale.…”

Section: Introductionmentioning

confidence: 99%

Ecological responses to heavy rainfall depend on seasonal timing and multi‐year recurrence

Zheng

et al. 2019

New Phytologist

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Summary Heavy rainfall events are expected to increase in frequency and severity in the future. However, their effects on natural ecosystems are largely unknown, in particular with different seasonal timing of the events and recurrence over multiple years. We conducted a 4 yr manipulative experiment to explore grassland response to heavy rainfall imposed in either the middle of, or late in, the growing season in Inner Mongolia, China. We measured hierarchical responses at individual, community and ecosystem levels. Surprisingly, above‐ground biomass remained stable in the face of heavy rainfall, regardless of seasonal timing, whereas heavy rainfall late in the growing season had consistent negative impacts on below‐ground and total biomass. However, such negative biomass effects were not significant for heavy rainfall in the middle of the growing season. By contrast, heavy rainfall in the middle of the growing season had greater positive effects on ecosystem CO2 exchanges, mainly reflected in the latter 2 yr of the 4 yr experiment. This two‐stage response of CO2 fluxes was regulated by increased community‐level leaf area and leaf‐level photosynthesis and interannual variability of natural precipitation. Overall, our study demonstrates that ecosystem impacts of heavy rainfall events crucially depend on the seasonal timing and multiannual recurrence. Plant physiological and morphological adjustment appeared to improve the capacity of the ecosystem to respond positively to heavy rainfall.

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“…Although conventional breeding has led to substantial improvements in wheat grain yield (GY), breeders are constantly challenged with extreme weather conditions and increasing drought and heat-stressed environments (Trnka et al 2014; Tack et al 2015; Mäkinen et al 2017; Zampieri et al 2017). Hence, breeding for tolerance to abiotic stress is one of the key goals of the International Maize and Wheat Improvement Center (CIMMYT) in several mega-environments (Braun et al 1996).…”

Section: Introductionmentioning

confidence: 99%

Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat

et al. 2018

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Genomic selection and high-throughput phenotyping (HTP) are promising tools to accelerate breeding gains for high-yielding and climate-resilient wheat varieties. Hence, our objective was to evaluate them for predicting grain yield (GY) in drought-stressed (DS) and late-sown heat-stressed (HS) environments of the International maize and wheat improvement center’s elite yield trial nurseries. We observed that the average genomic prediction accuracies using fivefold cross-validations were 0.50 and 0.51 in the DS and HS environments, respectively. However, when a different nursery/year was used to predict another nursery/year, the average genomic prediction accuracies in the DS and HS environments decreased to 0.18 and 0.23, respectively. While genomic predictions clearly outperformed pedigree-based predictions across nurseries, they were similar to pedigree-based predictions within nurseries due to small family sizes. In populations with some full-sibs in the training population, the genomic and pedigree-based prediction accuracies were on average 0.27 and 0.35 higher than the accuracies in populations with only one progeny per cross, indicating the importance of genetic relatedness between the training and validation populations for good predictions. We also evaluated the item-based collaborative filtering approach for multivariate prediction of GY using the green normalized difference vegetation index from HTP. This approach proved to be the best strategy for across-nursery predictions, with average accuracies of 0.56 and 0.62 in the DS and HS environments, respectively. We conclude that GY is a challenging trait for across-year predictions, but GS and HTP can be integrated in increasing the size of populations screened and evaluating unphenotyped large nurseries for stress–resilience within years.Electronic supplementary materialThe online version of this article (10.1007/s00122-018-3206-3) contains supplementary material, which is available to authorized users.

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Sensitivity of European wheat to extreme weather

Cited by 118 publications

References 45 publications

Establishment and characteristics analysis of a crop-drought vulnerability curve: a case study of European winter wheat

Establishment and characteristics analysis of a crop-drought vulnerability curve: a case study of European winter wheat

Ecological responses to heavy rainfall depend on seasonal timing and multi‐year recurrence

Integrating genomic-enabled prediction and high-throughput phenotyping in breeding for climate-resilient bread wheat

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