(Mt) – AA Climate change impact on agriculture and global beer market

Articles https://doi.org/10.1038/s41477-018-0263-1 Decreases in global beer supply due to extreme drought and heat Wei Xie 1*, Wei Xiong2,3,4, Jie Pan 2, Tariq Ali1, Qi Cui5, Dabo Guan Nathaniel D. Mueller9, Erda Lin 2* and Steven J. Davis9,10 *, Jing Meng 6,7 , 8 Beer is the most popular alcoholic beverage in the world by volume consumed, and yields of its main ingredient, barley, decline sharply in periods of extreme drought and heat. Although the frequency and severity of drought and heat extremes increase substantially in range of future climate scenarios by five Earth System Models, the vulnerability of beer supply to such extremes has never been assessed. We couple a process-based crop model (decision support system for agrotechnology transfer) and a global economic model (Global Trade Analysis Project model) to evaluate the effects of concurrent drought and heat extremes projected under a range of future climate scenarios. We find that these extreme events may cause substantial decreases in barley yields worldwide. Average yield losses range from 3% to 17% depending on the severity of the conditions. Decreases in the global supply of barley lead to proportionally larger decreases in barley used to make beer and ultimately result in dramatic regional decreases in beer consumption (for example, −​32% in Argentina) and increases in beer prices (for example, +​193% in Ireland). Although not the most concerning impact of future climate change, climate-related weather extremes may threaten the availability and economic accessibility of beer. R ising incomes are strongly correlated with increases in consumption of resource-intensive animal products (meat and dairy)1,2, processed foods3 and alcoholic beverages4 (Supplementary Figs. 1 and 2). Despite concerns that such trends are not healthy or environmentally sustainable2,5,6, global demand for these foods and beverages will continue to grow as economic development proceeds7. At the same time that demand for such products is increasing, climate change threatens to disrupt the supply of agricultural products8–12. A substantial and increasingly sophisticated body of research has begun to project the impacts of climate change on world food production, focusing on staple crops of wheat13,14, maize15,16, soybean17,18 and rice19,20. However, if adaptation efforts prioritize necessities, climate change may undermine the availability, stability and access to ‘luxury’ goods to a greater extent than staple foods. Although some attention has been paid to the potential impacts of climate change on luxury goods such as wine and coffee21–23, the impacts of climate change on the most popular alcoholic beverage in the world, beer, have not been carefully evaluated. Here, we assess the vulnerability of the global beer supply to disruptions by extreme drought and heat events that may occur during the twenty-first century as the climate changes—these are the main mechanisms by which climate damages crop production24,25. Details of our analytical approach are in the Methods and Supplementary Information Section 2. In summary, we develop an extreme events severity index for barley based on extremes in historical data (1981– 2010) and use it to characterize the frequency and severity of concurrent drought and heatwaves (that is, extreme events severity) under climate change, as projected by five different Earth System Models (ESMs) during the period 2010–2099. Extreme events years are classified as those with concurrent drought and heat (1) during the barley-growing season, (2) in areas where barley is now grown and (3) more severe than 100-year events in the historical record (as a weighted average of the barley-growing grid cells). Among the 450 modelled years (90 years ×​five ESMs) of each Representative Concentration Pathway (RCP), we identify 17, 77, 80 and 139 such extreme events years under RCP2.6, RCP4.5, RCP6.0 and RCP8.5, respectively. We then model the impacts of these extreme events on barley yields (the primary agricultural input to most beer26) in 34 world regions (most of which are individual countries with significant barley or beer production, consumption, and/or trade, both in total and per capita terms) using a process-based crop model (Decision Support System for Agrotechnology Transfer, DSSAT). Next, we examine the effects of the resulting barley supply shocks on the supply and price of beer in each region using a global economic general equilibrium model (Global Trade Analysis Project model, GTAP). Finally, we compare the impacts of extreme events with the impacts of changes in mean climate and test the sensitivity of our results to key sources of uncertainty, including extreme events of different severities, technology and parameter settings in the economic model27,28. Thus, we assess future sudden changes in barley production and subsequent changes in beer consumption across the world in years when extreme drought and heat occur. We do not consider how demand for beer may change in the future because such extreme events could occur in any future year and it is not possible to anticipate how agricultural and socio-economic systems will evolve. We therefore analyse impacts based on the recent geographical distribution of barley production, recent levels of China Center for Agricultural Policy, School of Advanced Agricultural Sciences, Peking University, Beijing, China. 2Institute of Environment and Sustainable Development in Agriculture, Chinese Academy of Agricultural Sciences, Beijing, China. 3International Maize and Wheat Improvement Center, Texcoco, Mexico. 4College of Agronomy, Henan Agricultural University, Zhengzhou, Henan, China. 5School of Economics and Resource Management, Beijing Normal University, Beijing, China. 6Department of Earth System Science, Tsinghua University, Beijing, China. 7School of International Development, University of East Anglia, Norwich, UK. 8Department of Politics and International Studies, University of Cambridge, Cambridge, UK. 9Department of Earth System Science, University of California, Irvine, CA, USA. 10Department of Civil and Environmental Engineering, University of California, Irvine, CA, USA. *e-mail: xiewei.ccap@pku.edu.cn; dabo.guan@uea.ac.uk; linerda@caas.cn 1 Nature Plants | www.nature.com/natureplants Articles NATurE PlAnTS b RCP8.5 n = 139 6 Annual likelihood of extreme events Extreme events severity index (concurrent and extreme drought + heat) a 4 2 RCP6.0 n = 80 0 RCP2.6 n = 17 1 3 RCP4.5 n = 77 60% After 2050 Mean Before 2050 40% 20% 0 5 7 Change in mean annual temperature during the years of extreme events (°C) 3.8% RCP2.6 17.1% 17.8% 30.9% RCP4.5 RCP6.0 RCP8.5 Emissions pathway Fig. 1 | Extreme events severity and frequency in barley-growing regions and during the barley-growing season under future climate change. a, The relationship between change in global mean (land) surface temperature in extreme events years (relative to the 1981–2010 observational mean) and the severity of concurrent drought and heat in barley-growing regions and during the barley-growing season, where the solid curve represents polynomial regression and the shaded envelopes the 95% confidence interval (n =​17, 77, 80 and 139 extreme events under RCP2.6, RCP4.5, RCP6.0 and RCP8.5, respectively). b, Annual likelihood of concurrent extreme events under each of the RCPs as projected by five ESMs (n =​450 independent experiments for each RCP). Top and bottom whiskers indicate the annual likelihood of extreme events after 2050 and before 2050, respectively. economic development and structure, recent population, and recent demands for barley and beer (as of 2011, which is the latest available year for data for our economic model). Extreme events limit beer supply Figure 1a shows the relationship between future increases in global mean (land) surface temperatures and the index of extreme events severity (that is, the prevalence and magnitude of concurrent extreme drought and heat during barley-growing seasons and in barley-growing regions) for each ‘extreme events year’ identified (Supplementary Fig. 13 shows the historical trend). The trend is relatively flat as global mean (land) surface temperatures increase up to ~3 °C, above which there is a rapid increase in extreme events severity up to ~8 °C of warming (RCP8.5, Fig. 1a). The corresponding annual likelihoods of concurrent drought and heatwave in the pathways and models are summarized by the bars in Fig. 1b. On average, the annual likelihood of such extreme events projected by climate models over the twenty-first century is ~4% under RCP2.6 (that is, an emissions pathway likely to avoid 3 °C of mean temperature increase during this century), increasing to ~17–18% under RCP4.5 and RCP6.0 (temperature increases of 4–5 °C) and up to ~31% under RCP8.5 (temperature increases >​5 °C). The likelihoods of extreme events in the second half of the century (top of error bars in Fig. 1b) are considerably greater, with extreme events occurring roughly one in every three years under RCP6.0 (top whisker of orange bar in Fig. 1b) and roughly one in every two years under RCP8.5 (top whisker of red bar in Fig. 1b) (Supplementary Figs. 14 and 15 show corresponding spatial patterns). Crop modelling using the weather conditions from each extreme events year projects the average barley yield losses, as shown in Fig. 2 (see Supplementary Fig. 21 for the uncertainty of yield losses). The greatest losses occur in tropical areas such as Central and South America and Central Africa (Fig. 2). In the same years, yields in temperate barley-growing areas such as Europe decrease moderately (yellow in Fig. 2) or even increase (blue and dark blue in Fig. 2), including in northern parts of the United States and Northwest Asia. The box-and-whisker plots on the right in Fig. 2 show the global barley yield changes. Global mean barley yields decrease during extreme events years, with more severe extreme events and yield losses associated with higher emission pathways; average yield reductions during these years are –3%, –9%, –10% and –17% under RCP2.6, RCP4.5, RCP6.0 and RCP8.5, respectively. Yield impacts are thus well-matched with increases in extreme events severity (see the correlation of yield changes and severity index in Supplementary Fig. 20). Although we assume that the current geographical distribution and area of barley cultivation is maintained, final barley production may not decrease to the same degree estimated by the weatherdriven crop model if agronomic inputs, such as labour, machinery, fertilizer and irrigation, are diverted to barley production during extreme events (for example, as in Nelson et al.28 and Iglesias et al.29). The contribution of these inputs is modelled in the GTAP model as the nonlinear reduction of labour and other inputs. For example, under RCP8.5, increases in labour and capital factors of production mean that a 17% mean decrease of DSSAT-modelled barley yields worldwide (Fig. 2a) corresponds to only a 15% reduction in the global barley production (see the global panel in Fig. 3; also see Supplementary Figs. 21 and 22 for national/regional barley yield/ production changes). Our economic modelling shows that global- and country-level barley supply declines progressively in more severe extreme events years (that is, under higher emissions pathways; solid bars in Fig. 3), with the largest mean supply decrease of 27–38% under RCP8.5 projected for some European countries (Belgium, the Czech Republic and Germany). Barley supply changes are not only affected by shifts in barley production, but also by international trade among countries. For example, in some net-importing countries whose domestic production decreases (for example, Brazil; see the hatched areas), trade between countries mediates the effects of changes in local production on country-specific barley supply, with an increasing share of imported barley consumed. On the other hand, depending on the magnitude of production losses, barley-exporting countries may conserve their domestic production via reduced net exports (for example, Australia; decreasing length of red hatched areas in Fig. 3) or increase their exports to meet demand in other countries (for example, the United States); however, the larger decreases in barley supply occur in countries that rely heavily on barley imports (for example, China, Japan and Belgium) because demand for such imports exceeds any increases in exports. Nature Plants | www.nature.com/natureplants Articles NATurE PlAnTS 80° N a +10% 40° N 0 Global yield change 60° N 20° N 0° 20° S –10% –20% –17% –30% –40% 40° S RCP8.5 180° 80° N 150° W 120° W 90° W 60° W 30° W 0° 30° E 60° E 90° E 120° E 150° E b +10% 40° N 0 Global yield change 60° N 20° N 0° 20° S –10% –10% –20% –30% –40% 40° S RCP6.0 180° 80° N 150° W 120° W 90° W 60° W 30° W 0° 30° E 60° E 90° E 120° E 150° E c +10% 40° N 0 Global yield change 60° N 20° N 0° 20° S –10% –9% –20% –30% –40% 40° S RCP4.5 180° 80° N 150° W 120° W 90° W 60° W 30° W 0° 30° E 60° E 90° E 120° E 150° E d 60° N +10% Global yield change 40° N 20° N 0° 20° S 150° W –3% –10% –20% –30% –40% 40° S RCP2.6 180° 0 120° W 90° W 60° W 30° W 0° 30° E 60° E 90° E 120° E 150° E Mean yield change –90% –50% –10% 0 +10% +50% +90% Fig. 2 | Average barley yield shocks during extreme events years. a–d, Gridded average yield change with 0.5° ×​0.5° resolution across all predictions of extreme events years (left) and global aggregated change in barley yield (right) under RCP8.5 (a), RCP6.0 (b), RCP4.5 (c) and RCP2.6 (d) compared to the average yield from 1981–2010. Box-and-whisker plots to the right show the range of global changes, with white points indicating the mean; white lines the median; top and bottom of the box the 25th and 75th percentiles; and whiskers the minimum and maximum of all data (n =​17, 77, 80 and 139 extreme events under RCP2.6, RCP4.5, RCP6.0 and RCP8.5, respectively); dashed lines indicate no yield change. We map all grid cells where the barley harvested area exceeded 1% of the grid cell area. The grid cell barley areas are from the gridded global dataset in 2000 and combined two data products from ref. 51 and Spatial Production Allocation Model (SPAM)52. Nature Plants | www.nature.com/natureplants Articles NATurE PlAnTS Barley consumption (%) 40% 60% 80% Barley consumption (%) 100% Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 120% 140% China Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 US UK 80% 100% 120% 120% Belgium Russia Australia Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 Japan 60% 100% Italy Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 40% 80% Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 20% 60% Germany Recent RCP2.6 Czech Republic RCP4.5 RCP6.0 RCP8.5 0 40% Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 20% Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 Brazil Recent RCP2.6 RCP4.5 RCP6.0 RCP8.5 0 140% Global 0 20% 40% Barley consumption (%) 60% 80% 100% Barley consumption (%) Beer Livestock feed Food and other 120% 0% 60 0% 80 0% 20% 40 0 Net exports Net imports Fig. 3 | Barley consumption by country and globally under future climate change. For each country and the global aggregate, the bars show the total consumption of barley averaged over all extreme events years during 2010–2099 and the share for different barley uses. Whiskers indicate the 25th and 75th percentiles of all total consumption changes (n =​17, 77, 80 and 139 extreme events under RCP2.6, RCP4.5, RCP6.0 and RCP8.5, respectively). The source of the shares in recent years (2011) is the improved GTAP database. The selected countries are a mix of countries that have one or more of significant barley production, consumption, export and/or import. Supplementary Figs. 24 and 25 show the absolute and relative shares for all the countries. Changes in barley supply due to extreme events will affect the barley available for making beer differently in each region because the allocation of barley among livestock feed, beer brewing and other uses will depend on region-specific prices and demand elasticities as different industries seek to maximize profits (Fig. 3, yellow bars indicate barley allocated to the beer sector). In 2011, the beer sector consumed around 17% of global barley production but, as seen in Fig. 3, this share varied drastically across major beer-producing countries, from 83% in Brazil to 9% in Australia. Further analysing the relative changes in shares of barley use, we find that in most cases barley-to-beer shares shrink more than barley-to-livestock shares, showing that food commodities (in this case, animals fed on barley) will be prioritized over luxuries such as beer during extreme events years. At the global level, the most severe climate events (that is, RCP8.5) cause the barley supply to decrease by 15% (ranging from 6% to 22% in our uncertainty analysis over 25th– 75th percentiles), but the share of barley-to-beer decreases by 20% (from the initial 17% of all barley to 14%). Among countries, we see that the reduction in barley consumption under RCP8.5 is greatest in Belgium (38% with uncertainty range of 18–57%), where the barley-to beer share decreases by 50% (from the initial 28% of all barley to14%). Therefore, future drought and heat events will not only lower the total availability of barley for most key countries, but will also reduce the share of barley used for beer production (see Supplementary Figs. 24 and 25 for the changes in absolute and relative shares in all countries/regions). Global reductions in beer consumption Ultimately, our modelling suggests that increasingly widespread and severe droughts and heat under climate change will cause considerable disruption to global beer consumption and increase beer prices (Supplementary Figs. 26 and 27). During the most severe climate events (for example, under RCP8.5), our results indicate that global beer consumption would decline by 16% (0–41%) (roughly equal to the total annual beer consumption of the United States in 2011), and that beer prices would, on average, double (100–656% of recent prices). Even in less severe extreme events (for example, those occurring under RCP2.6 simulations), global beer consumption drops by 4% (0–15%) and prices jump by 15% (0–52%). Figure 4 shows, for each RCP, ten key countries according to changes in total beer consumption by volume (Fig. 4a–d), changes in the price of beer (Fig. 4e–h) and changes in the per-capita consumption of beer (Fig. 4i–l) (see percentage changes for all main beer-consuming countries in Supplementary Figs. 26–28 and absolute changes in Supplementary Figs. 30–32). For comparison, consumption data from ten key countries in recent year (2011) are shown in Fig. 5 (see Supplementary Figs. 3–5 for additional details). Total beer consumption decreases most under climate change in the countries that consume the most beer by volume in recent year (2011) (Fig. 4a). For example, the volume of beer consumed in China—the largest consuming country by volume (Fig. 5a)— decreases by more than any other country as the severity of extreme events increases (we model a decrease in consumption in China Nature Plants | www.nature.com/natureplants Articles NATurE PlAnTS Changes in beer consumption (total) a RCP2.6 Changes in beer price (per 500 ml) e –1.08 US +0.87 –0.78 China +0.72 –0.73 Germany +0.71 –0.48 Poland +0.61 Ireland Canada Poland Czechia –26 Ireland –25 Poland Italy –18 Belgium Russia +0.46 Japan –18 Germany UK +0.44 Denmark –18 Austria –0.27 Argentina +0.42 Belgium –17 Brazil +0.31 –0.24 Japan –0.22 Canada –2 –4 –6 –13 +0.31 Estonia –13 Argentina +0.26 Czech Republic –13 Canada –8 0 1.50 3.00 4.50 0 6.00 –1.32 +1.26 Germany –0.91 +1.23 Russia –80 –49 Poland –45 Italy Czech Republic –35 Poland Canada –34 Belgium Poland +1.03 Japan –33 –0.67 UK +0.90 Belgium –32 –0.53 Brazil +0.80 Denmark –27 Denmark –0.48 Japan +0.71 –24 Estonia Argentina +0.60 –0.37 Canada +0.56 0 –2 –4 –6 –8 c –2.18 Russia –0.76 Canada –38 Belgium –37 Poland Argentina +0.70 –0.41 Canada +0.66 –8 –37 Germany Belgium –36 Austria Denmark –30 Denmark –28 Estonia Poland Estonia UK Portugal 0 Billions of litres 1.50 3.00 4.50 –1.82 h Russia –24 Netherlands –24 UK 6.00 0 US$ per 500 ml +4.84 Germany l –40 –80 –120 –81 Ireland Ireland +4.52 Italy +4.35 Canada –81 Czech Republic –63 +3.53 Poland –61 Estonia –59 Germany Austria UK +3.45 –1.11 Poland +3.44 –1.04 Brazil +2.77 Belgium –50 Estonia –0.92 Japan +2.60 Denmark –49 Denmark –0.63 Canada +1.90 U.K. –42 –0.53 Argentina +1.64 Portugal –39 –2 –4 –6 –8 0 4.00 8.00 12.00 US$ per 500 mL 35 GDP per capita (thousands of US$ per person) Fig. 4 | Changes in beer consumption and price under increasingly severe drought–heat events. Each column presents the results for the ten most affected countries in the regional aggregation of this study. a–d, Absolute change in the total volume of beer consumed. e–h, Change in beer price per 500 ml. i–l, Change in annual beer consumption per capita. The severity of extreme events increases from top to bottom. The length of the bars for each RCP shows average changes of all modelled extreme events years from 2010 to 2099, which are shown to the left of each bar, and the colours of the bars represent per-capita gross domestic product (see colour scale). Whiskers indicate the 25th and 75th percentiles of all changes (n =​17, 77, 80 and 139 extreme events under RCP2.6, RCP4.5, RCP6.0 and RCP8.5, respectively; see percentage changes with full range for all main beer-consuming countries in Supplementary Figs. 26–28; absolute changes in Supplementary Figs. 30–32). Nature Plants | www.nature.com/natureplants Articles a NATurE PlAnTS US 25.3 Brazil 13.2 c Beer price (per 500 ml) 3.93 China 48.8 Recent b Beer consumption (total) Beer consumption (per capita) 276 Australia 2.56 Japan 274 2.51 Ireland 213 Czech Republic Russia 1.95 US 201 8.1 Germany UK 1.93 UK 191 Estonia 1.87 Canada 188 Poland Denmark 176 Belgium Poland 4.9 1.79 3.6 Spain 1.68 3.5 Japan 1.51 2.8 South Africa 1.42 0 20 40 Billions of litres 60 0 Germany 168 Australia Brazil 168 Romania Belgium 162 France 1.50 3.00 4.50 US$ per 500 ml 6.00 30 Austria 10.0 6.5 >35 Ireland 25 20 15 US 0 100 200 500 ml bottles per year 300

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