| Records |
| Author |
Rötter, R.P.; Appiah, M.; Fichtler, E.; Kersebaum, K.C.; Trnka, M.; Hoffmann, M.P. |
| Title |
Linking modelling and experimentation to better capture crop impacts of agroclimatic extremes-A review |
Type |
Journal Article |
| Year |
2018 |
Publication |
Field Crops Research |
Abbreviated Journal |
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| Volume |
221 |
Issue |
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Pages |
142-156 |
Keywords  |
ft_macsur; Agroclimatic extremes; Crop model; Heat; Drought; Heavy rain; Anthropogenic Climate-Change; Head-Emergence Frost; Weather Extremes; Wheat Yields; Temperature Variability; Induced Sterility; Food Security; Soil-Moisture; Plant-Growth; Winter-Wheat |
| Abstract |
Climate change implies higher frequency and magnitude of agroclimatic extremes threatening plant production and the provision of other ecosystem services. This review is motivated by a mismatch between advances made regarding deeper understanding of abiotic stress physiology and its incorporation into ecophysiological models in order to more accurately quantifying the impacts of extreme events at crop system or higher aggregation levels. Adverse agroclimatic extremes considered most detrimental to crop production include drought, heat, heavy rains/hail and storm, flooding and frost, and, in particular, combinations of them. Our core question is: How have and could empirical data be exploited to improve the capability of widely used crop simulation models in assessing crop impacts of key agroclimatic extremes for the globally most important grain crops? To date there is no comprehensive review synthesizing available knowledge for a broad range of extremes, grain crops and crop models as a basis for identifying research gaps and prospects. To address these issues, we selected eight major grain crops and performed three systematic reviews using SCOPUS for period 1995-2016. Furthermore, we amended/complemented the reviews manually and performed an in-depth analysis using a sub-sample of papers. Results show that by far the majority of empirical studies (1631 out of 1772) concentrate on the three agroclimatic extremes drought, heat and heavy rain and on the three major staples wheat, maize and rice (1259 out of 1772); the concentration on just a few has increased over time. With respect to modelling studies two model families, i.e. CERES-DSSAT and APSIM, are dearly dominating for wheat and maize; for rice, ORYZA2000 and CERES-Rice predominate and are equally strong. For crops other than maize and wheat the number of studies is small. Empirical and modelling papers don’t differ much in the proportions the various extreme events are dealt with drought and heat stress together account for approx. 80% of the studies. There has been a dramatic increase in the number of papers, especially after 2010. As a way forward, we suggest to have very targeted and well-designed experiments on the specific crop impacts of a given extreme as well as of combinations of them. This in particular refers to extremes addressed with insufficient specificity (e.g. drought) or being under-researched in relation to their economic importance (heavy rains/storm and flooding). Furthermore, we strongly recommend extending research to crops other than wheat, maize and rice. |
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MA @ admin @ |
Serial |
5199 |
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| Author |
Siebert, S.; Ewert, F.; Rezaei, E.E.; Kage, H.; Grass, R. |
| Title |
Impact of heat stress on crop yield-on the importance of considering canopy temperature |
Type |
Journal Article |
| Year |
2014 |
Publication |
Environmental Research Letters |
Abbreviated Journal |
Environ. Res. Lett. |
| Volume |
9 |
Issue |
4 |
Pages |
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| Keywords |
heat stress; crop yield; temperature; soil moisture; modelling; wheat; rye; harvest index; wheat yields; climate-change; winter-wheat; grain number; extreme heat; maize; variability; irrigation; drought |
| Abstract |
Increasing crop productivity while simultaneously reducing the environmental footprint of crop production is considered a major challenge for the coming decades. Even short episodes of heat stress can reduce crop yield considerably causing low resource use efficiency. Studies on the impact of heat stress on crop yields over larger regions generally rely on temperatures measured by standard weather stations at 2 m height. Canopy temperatures measured in this study in field plots of rye were up to 7 degrees C higher than air temperature measured at typical weather station height with the differences in temperatures controlled by soil moisture contents. Relationships between heat stress and grain number derived from controlled environment studies were only confirmed under field conditions when canopy temperature was used to calculate stress thermal time. By using hourly mean temperatures measured by 78 weather stations located across Germany for the period 1994-2009 it is estimated, that mean yield declines in wheat due to heat stress during flowering were 0.7% when temperatures are measured at 2 m height, but yield declines increase to 22% for temperatures measured at the ground. These results suggest that canopy temperature should be simulated or estimated to reduce uncertainty in assessing heat stress impacts on crop yield. |
| Address |
2016-10-31 |
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English |
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1748-9326 |
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| Notes |
CropM, ftnotmacsur |
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no |
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MA @ admin @ |
Serial |
4814 |
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| Author |
Pasqui, M.; Di Giuseppe, E. |
| Title |
Climate change, future warming, and adaptation in Europe |
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Journal Article |
| Year |
2019 |
Publication |
Animal Frontiers |
Abbreviated Journal |
Animal Frontiers |
| Volume |
9 |
Issue |
1 |
Pages |
6-11 |
| Keywords |
heat waves; impacts; perception; vulnerability; temperature-humidity index; extremes indexes |
| Abstract |
In recent decades, the increased temperatures reported in Europe and in the Mediterranean basin represent one of the clearest footprints of climate change along with increased frequency of heat waves. These climate modifications put the environment and human activities under strong pressure with a resulting need for designing new adaptation and mitigation strategies. The climate change challenge is unprecedented for humanity and is recognized as a priority topic for future research. Changes in the way we think and behave are critical challenges at the global and regional levels. |
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2020-06-08 |
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LiveM, ft_macsur |
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MA @ admin @ |
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5236 |
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Kuhnert, M.; Yeluripati, J.; Smith, P.; Hoffmann, H.; van Oijen, M.; Constantin, J.; Coucheney, E.; Dechow, R.; Eckersten, H.; Gaiser, T.; Grosz, B.; Haas, E.; Kersebaum, K.-C.; Kiese, R.; Klatt, S.; Lewan, E.; Nendel, C.; Raynal, H.; Sosa, C.; Specka, X.; Teixeira, E.; Wang, E.; Weihermüller, L.; Zhao, G.; Zhao, Z.; Ogle, S.; Ewert, F. |
| Title |
Impact analysis of climate data aggregation at different spatial scales on simulated net primary productivity for croplands |
Type |
Journal Article |
| Year |
2016 |
Publication |
European Journal of Agronomy |
Abbreviated Journal |
European Journal of Agronomy |
| Volume |
88 |
Issue |
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Pages |
41-52 |
| Keywords |
Net primary production; NPP; Scaling; Extreme events; Crop modelling; Climate Data; aggregation |
| Abstract |
For spatial crop and agro-systems modelling, there is often a discrepancy between the scale of measured driving data and the target resolution. Spatial data aggregation is often necessary, which can introduce additional uncertainty into the simulation results. Previous studies have shown that climate data aggregation has little effect on simulation of phenological stages, but effects on net primary production (NPP) might still be expected through changing the length of the growing season and the period of grain filling. This study investigates the impact of spatial climate data aggregation on NPP simulation results, applying eleven different models for the same study region (∼34,000 km2), situated in Western Germany. To isolate effects of climate, soil data and management were assumed to be constant over the entire study area and over the entire study period of 29 years. Two crops, winter wheat and silage maize, were tested as monocultures. Compared to the impact of climate data aggregation on yield, the effect on NPP is in a similar range, but is slightly lower, with only small impacts on averages over the entire simulation period and study region. Maximum differences between the five scales in the range of 1–100 km grid cells show changes of 0.4–7.8% and 0.0–4.8% for wheat and maize, respectively, whereas the simulated potential NPP averages of the models show a wide range (1.9–4.2 g C m−2 d−1 and 2.7–6.1 g C m−2 d−1for wheat and maize, respectively). The impact of the spatial aggregation was also tested for shorter time periods, to see if impacts over shorter periods attenuate over longer periods. The results show larger impacts for single years (up to 9.4% for wheat and up to 13.6% for maize). An analysis of extreme weather conditions shows an aggregation effect in vulnerability up to 12.8% and 15.5% between the different resolutions for wheat and maize, respectively. Simulations of NPP averages over larger areas (e.g. regional scale) and longer time periods (several years) are relatively insensitive to climate data. |
| Address |
2016-09-13 |
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English |
Summary Language |
Newsletter July |
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1161-0301 |
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Article |
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| Notes |
CropM, ft_macsur |
Approved |
no |
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MA @ admin @ |
Serial |
4775 |
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| Author |
Ruiz-Ramos, M.; Rodriguez, A.; Dosio, A.; Goodess, C.M.; Harpham, C.; Minguez, M.I.; Sanchez, E. |
| Title |
Comparing correction methods of RCM outputs for improving crop impact projections in the Iberian Peninsula for 21st century |
Type |
Journal Article |
| Year |
2016 |
Publication |
Climatic Change |
Abbreviated Journal |
Clim. Change |
| Volume |
134 |
Issue |
1-2 |
Pages |
283-297 |
| Keywords |
regional climate model; bias correction; weather generator; circulation model; simulations; temperature; precipitation; ensemble; uncertainty; extremes |
| Abstract |
Assessment of climate change impacts on crops in regions of complex orography such as the Iberian Peninsula (IP) requires climate model output which is able to describe accurately the observed climate. The high resolution of output provided by Regional Climate Models (RCMs) is expected to be a suitable tool to describe regional and local climatic features, although their simulation results may still present biases. For these reasons, we compared several post-processing methods to correct or reduce the biases of RCM simulations from the ENSEMBLES project for the IP. The bias-corrected datasets were also evaluated in terms of their applicability and consequences in improving the results of a crop model to simulate maize growth and development at two IP locations, using this crop as a reference for summer cropping systems in the region. The use of bias-corrected climate runs improved crop phenology and yield simulation overall and reduced the inter-model variability and thus the uncertainty. The number of observational stations underlying each reference observational dataset used to correct the bias affected the correction performance. Although no single technique showed to be the best one, some methods proved to be more adequate for small initial biases, while others were useful when initial biases were so large as to prevent data application for impact studies. An initial evaluation of the climate data, the bias correction/reduction method and the consequences for impact assessment would be needed to design the most robust, reduced uncertainty ensemble for a specific combination of location, crop, and crop management. |
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2016-10-31 |
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English |
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0165-0009 |
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CropM, ft_macsur |
Approved |
no |
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MA @ admin @ |
Serial |
4805 |
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