Climate-induced decline in the quality and quantity of European hops calls for immediate adaptation measures.

A recent rise in the global brewery sector has increased the demand for high-quality, late summer hops. The effects of ongoing and predicted climate change on the yield and aroma of hops, however, remain largely unknown. Here, we combine meteorological measurements and model projections to assess the climate sensitivity of the yield, alpha content and cone development of European hops between 1970 and 2050 CE, when temperature increases by 1.4 °C and precipitation decreases by 24 mm. Accounting for almost 90% of all hop-growing regions, our results from Germany, the Czech Republic and Slovenia show that hop ripening started approximately 20 days earlier, production declined by almost 0.2 t/ha/year, and the alpha content decreased by circa 0.6% when comparing data before and after 1994 CE. A predicted decline in hop yield and alpha content of 4-18% and 20-31% by 2050 CE, respectively, calls for immediate adaptation measures to stabilize an ever-growing global sector.

Mitigation efforts will not fully alleviate the increase in water scarcity occurrence probability in wheat-producing areas.

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 8.5), up to 60% of the current wheat-growing area will face simultaneous SWS events by the end of this century, compared to 15% today. Climate change stabilization in line with the Paris Agreement would substantially reduce the negative effects, but they would still double between 2041 and 2070 compared to current conditions. Future assessments of production shocks in food security should explicitly include the risk of severe, prolonged, and near-simultaneous droughts across key world wheat-producing areas.

Determination of areas with the most significant shift in persistence of pests in Europe under climate change.

BACKGROUND: This study aimed to estimate the impact of climate change on the ranges of crop pest species in Europe. The organisms included in the study were species from the family Tortricidae (Cydia pomonella, Lobesia botrana) and the family Pyralidae (Ostrinia nubilalis), Chrysomelidae beetles (Leptinotarsa decemlineata, Oulema melanopus) and species from the family Aphididae (Ropalosiphum padi, Sitobion avenae). Climate conditions in the year 2055 were simulated using a subset of five representative global circulation models. Model simulations using these climate change scenarios showed significant shifts in the climatic niches of the species in this study. RESULTS: For Central Europe, the models predicted a shift in the ranges of pest species to higher altitudes and increases in the number of generations (NG) of the pests. In contrast, in the southern regions of Europe, the NG is likely to decrease owing to insufficient humidity. The ranges of species are likely to shift to the north. CONCLUSION: Based on the ensemble-scenario mean for 2055, a climate-driven northward shift of between 3° N (O. nubilalis) and 11° N (L. botrana) is expected. The areas that are most sensitive to experiencing a significant increase in climate suitability for future pest persistence were identified. These areas include Central Europe, the higher altitudes of the Alps and Carpathians and areas above 55° N.

Effect of Estimated Daily Global Solar Radiation Data on the Results of Crop Growth Models.

The results of previous studies have suggested that estimated daily globalradiation (RG) values contain an error that could compromise the precision of subsequentcrop model applications. The following study presents a detailed site and spatial analysis ofthe RG error propagation in CERES and WOFOST crop growth models in Central Europeanclimate conditions. The research was conducted i) at the eight individual sites in Austria andthe Czech Republic where measured daily RG values were available as a reference, withseven methods for RG estimation being tested, and ii) for the agricultural areas of the CzechRepublic using daily data from 52 weather stations, with five RG estimation methods. In thelatter case the RG values estimated from the hours of sunshine using the ångström-Prescottformula were used as the standard method because of the lack of measured RG data. At thesite level we found that even the use of methods based on hours of sunshine, which showedthe lowest bias in RG estimates, led to a significant distortion of the key crop model outputs.When the ångström-Prescott method was used to estimate RG, for example, deviationsgreater than ±10 per cent in winter wheat and spring barley yields were noted in 5 to 6 percent of cases. The precision of the yield estimates and other crop model outputs was lowerwhen RG estimates based on the diurnal temperature range and cloud cover were used (mean bias error 2.0 to 4.1 per cent). The methods for estimating RG from the diurnal temperature range produced a wheat yield bias of more than 25 per cent in 12 to 16 per cent of the seasons. Such uncertainty in the crop model outputs makes the reliability of any seasonal yield forecasts or climate change impact assessments questionable if they are based on this type of data. The spatial assessment of the RG data uncertainty propagation over the winter wheat yields also revealed significant differences within the study area. We found that RG estimates based on diurnal temperature range or its combination with daily total precipitation produced a bias of to 30 per cent in the mean winter wheat grain yields in some regions compared with simulations in which RG values had been estimated using the ångström-Prescott formula. In contrast to the results at the individual sites, the methods based on the diurnal temperature range in combination with daily precipitation totals showed significantly poorer performance than the methods based on the diurnal temperature range only. This was due to the marked increase in the bias in RG estimates with altitude, longitude or latitude of given region. These findings in our view should act as an incentive for further research to develop more precise and generally applicable methods for estimating daily RG based more on the underlying physical principles and/or the remote sensing approach.