The extreme 2016 wheat yield failure in France

France suffered, in 2016, the most extreme wheat yield decline in recent history, with some districts losing 55% yield. To attribute causes, we combined the largest coherent detailed wheat field experimental dataset with statistical and crop model techniques, climate information, and yield physiology. The 2016 yield was composed of up to 40% fewer grains that were up to 30% lighter than expected across eight research stations in France. The flowering stage was affected by prolonged cloud cover and heavy rainfall when 31% of the loss in grain yield was incurred from reduced solar radiation and 19% from floret damage. Grain filling was also affected as 26% of grain yield loss was caused by soil anoxia, 11% by fungal foliar diseases, and 10% by ear blight. Compounding climate effects caused the extreme yield decline. The likelihood of these compound factors recurring under future climate change is estimated to change with a higher frequency of extremely low wheat yields.

Extreme rainfall reduces one-twelfth of China's rice yield over the last two decades

Extreme climate events constitute a major risk to global food production. Among these, extreme rainfall is often dismissed from historical analyses and future projections, the impacts and mechanisms of which remain poorly understood. Here we used long-term nationwide observations and multi-level rainfall manipulative experiments to explore the magnitude and mechanisms of extreme rainfall impacts on rice yield in China. We find that rice yield reductions due to extreme rainfall were comparable to those induced by extreme heat over the last two decades, reaching 7.6 ± 0.9% (one standard error) according to nationwide observations and 8.1 ± 1.1% according to the crop model incorporating the mechanisms revealed from manipulative experiments. Extreme rainfall reduces rice yield mainly by limiting nitrogen availability for tillering that lowers per-area effective panicles and by exerting physical disturbance on pollination that declines per-panicle filled grains. Considering these mechanisms, we projected ~8% additional yield reduction due to extreme rainfall under warmer climate by the end of the century. These findings demonstrate that it is critical to account for extreme rainfall in food security assessments.

Simulation of winter wheat response to variable sowing dates and densities in a high-yielding environment

Crop multi-model ensembles (MME) have proven to be effective in increasing the accuracy of simulations in modelling experiments. However, the ability of MME to capture crop responses to changes in sowing dates and densities has not yet been investigated. These management interventions are some of the main levers for adapting cropping systems to climate change. Here, we explore the performance of a MME of 29 wheat crop models to predict the effect of changing sowing dates and rates on yield and yield components, on two sites located in a high-yielding environment in New Zealand. The experiment was conducted for 6 years and provided 50 combinations of sowing date, sowing density and growing season. We show that the MME simulates seasonal growth of wheat well under standard sowing conditions, but fails under early sowing and high sowing rates. The comparison between observed and simulated in-season fraction of intercepted photosynthetically active radiation (FIPAR) for early sown wheat shows that the MME does not capture the decrease of crop above ground biomass during winter months due to senescence. Models need to better account for tiller competition for light, nutrients, and water during vegetative growth, and early tiller senescence and tiller mortality, which are exacerbated by early sowing, high sowing densities, and warmer winter temperatures.

A new direction for tackling phosphorus inefficiency in the UK food system

The UK food system is reliant on imported phosphorus (P) to meet food production demand, though inefficient use and poor stewardship means P is currently accumulating in agricultural soils, wasted or lost with detrimental impacts on aquatic environments. This study presents the results of a detailed P Substance Flow Analysis for the UK food system in 2018, developed in collaboration with industry and government, with the key objective of highlighting priority areas for system interventions to improve the sustainability and resilience of P use in the UK food system. In 2018 the UK food system imported 174.6 Gg P, producing food and exportable commodities containing 74.3 Gg P, a P efficiency of only 43%. Three key system hotspots for P inefficiency were identified: Agricultural soil surplus and accumulation (89.2 Gg P), loss to aquatic environments (26.2 Gg P), and waste disposal to landfill and construction (21.8 Gg P). Greatest soil P accumulation occurred in grassland agriculture (85% of total accumulation), driven by loadings of livestock manures. Waste water treatment (12.5 Gg P) and agriculture (8.38 Gg P) account for most P lost to water, and incineration ashes from food system waste (20.3 Gg P) accounted for nearly all P lost to landfill and construction. New strategies and policy to improve the handling and recovery of P from manures, biosolids and food system waste are therefore necessary to improve system P efficiency and reduce P accumulation and losses, though critically, only if they effectively replace imported mineral P fertilisers.

Global wheat production could benefit from closing the genetic yield gap

Global food security requires food production to be increased in the coming decades. The closure of any existing genetic yield gap (Y_ig) by genetic improvement could increase crop yield potential and global production. Here we estimated present global wheat Y_ig, covering all wheat-growing environments and major producers, by optimizing local wheat cultivars using the wheat model Sirius. The estimated mean global Y_ig was 51%, implying that global wheat production could benefit greatly from exploiting the untapped global Y_ig through the use of optimal cultivar designs, utilization of the vast variation available in wheat genetic resources, application of modern advanced breeding tools, and continuous improvements of crop and soil management.

Climate impacts on global agriculture emerge earlier in new generation of climate and crop models

Potential climate-related impacts on future crop yield are a major societal concern. Previous projections of the Agricultural Model Intercomparison and Improvement Project's Global Gridded Crop Model Intercomparison based on the Coupled Model Intercomparison Project Phase 5 identified substantial climate impacts on all major crops, but associated uncertainties were substantial. Here we report new twenty-first-century projections using ensembles of latest-generation crop and climate models. Results suggest markedly more pessimistic yield responses for maize, soybean and rice compared to the original ensemble. Mean end-of-century maize productivity is shifted from +5% to -6% (SSP126) and from +1% to -24% (SSP585)-explained by warmer climate projections and improved crop model sensitivities. In contrast, wheat shows stronger gains (+9% shifted to +18%, SSP585), linked to higher CO₂ concentrations and expanded high-latitude gains. The 'emergence' of climate impacts consistently occurs earlier in the new projections-before 2040 for several main producing regions. While future yield estimates remain uncertain, these results suggest that major breadbasket regions will face distinct anthropogenic climatic risks sooner than previously anticipated.

Narrowing uncertainties in the effects of elevated CO2 on crops

Plant responses to rising atmospheric carbon dioxide (CO₂) concentrations, together with projected variations in temperature and precipitation will determine future agricultural production. Estimates of the impacts of climate change on agriculture provide essential information to design effective adaptation strategies, and develop sustainable food systems. Here, we review the current experimental evidence and crop models on the effects of elevated CO₂ concentrations. Recent concerted efforts have narrowed the uncertainties in CO₂-induced crop responses so that climate change impact simulations omitting CO₂ can now be eliminated. To address remaining knowledge gaps and uncertainties in estimating the effects of elevated CO₂ and climate change on crops, future research should expand experiments on more crop species under a wider range of growing conditions, improve the representation of responses to climate extremes in crop models, and simulate additional crop physiological processes related to nutritional quality.

Modelling climate change impacts on maize yields under low nitrogen input conditions in sub-Saharan Africa

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. We evaluated the impact of varying [CO₂ ], temperature and rainfall conditions on maize yield, for different nitrogen (N) inputs (0, 80, 160 kg N/ha) for five environments in SSA, including cool subhumid Ethiopia, cool semi-arid Rwanda, hot subhumid Ghana and hot semi-arid Mali and Benin using an ensemble of 25 maize models. Models were calibrated with measured grain yield, plant biomass, plant N, leaf area index, harvest index and in-season soil water content from 2-year experiments in each country to assess their ability to simulate observed yield. Simulated responses to climate change factors were explored and compared between models. Calibrated models reproduced measured grain yield variations well with average relative root mean square error of 26%, although uncertainty in model prediction was substantial (CV = 28%). Model ensembles gave greater accuracy than any model taken at random. Nitrogen fertilization controlled the response to variations in [CO₂ ], temperature and rainfall. Without N fertilizer input, maize (a) benefited less from an increase in atmospheric [CO₂ ]; (b) was less affected by higher temperature or decreasing rainfall; and (c) was more affected by increased rainfall because N leaching was more critical. The model intercomparison revealed that simulation of daily soil N supply and N leaching plays a crucial role in simulating climate change impacts for low-input systems. Climate change and N input interactions have strong implications for the design of robust adaptation approaches across SSA, because the impact of climate change in low input systems will be modified if farmers intensify maize production with balanced nutrient management.

Global wheat production with 1.5 and 2.0°C above pre-industrial warming

Efforts to limit global warming to below 2°C in relation to the pre-industrial level are under way, in accordance with the 2015 Paris Agreement. However, most impact research on agriculture to date has focused on impacts of warming >2°C on mean crop yields, and many previous studies did not focus sufficiently on extreme events and yield interannual variability. Here, with the latest climate scenarios from the Half a degree Additional warming, Prognosis and Projected Impacts (HAPPI) project, we evaluated the impacts of the 2015 Paris Agreement range of global warming (1.5 and 2.0°C warming above the pre-industrial period) on global wheat production and local yield variability. A multi-crop and multi-climate model ensemble over a global network of sites developed by the Agricultural Model Intercomparison and Improvement Project (AgMIP) for Wheat was used to represent major rainfed and irrigated wheat cropping systems. Results show that projected global wheat production will change by -2.3% to 7.0% under the 1.5°C scenario and -2.4% to 10.5% under the 2.0°C scenario, compared to a baseline of 1980-2010, when considering changes in local temperature, rainfall, and global atmospheric CO₂ concentration, but no changes in management or wheat cultivars. The projected impact on wheat production varies spatially; a larger increase is projected for temperate high rainfall regions than for moderate hot low rainfall and irrigated regions. Grain yields in warmer regions are more likely to be reduced than in cooler regions. Despite mostly positive impacts on global average grain yields, the frequency of extremely low yields (bottom 5 percentile of baseline distribution) and yield inter-annual variability will increase under both warming scenarios for some of the hot growing locations, including locations from the second largest global wheat producer-India, which supplies more than 14% of global wheat. The projected global impact of warming <2°C on wheat production is therefore not evenly distributed and will affect regional food security across the globe as well as food prices and trade.

Climate change impact and adaptation for wheat protein

Wheat grain protein concentration is an important determinant of wheat quality for human nutrition that is often overlooked in efforts to improve crop production. We tested and applied a 32-multi-model ensemble to simulate global wheat yield and quality in a changing climate. Potential benefits of elevated atmospheric CO₂ concentration by 2050 on global wheat grain and protein yield are likely to be negated by impacts from rising temperature and changes in rainfall, but with considerable disparities between regions. Grain and protein yields are expected to be lower and more variable in most low-rainfall regions, with nitrogen availability limiting growth stimulus from elevated CO₂ . Introducing genotypes adapted to warmer temperatures (and also considering changes in CO₂ and rainfall) could boost global wheat yield by 7% and protein yield by 2%, but grain protein concentration would be reduced by -1.1 percentage points, representing a relative change of -8.6%. Climate change adaptations that benefit grain yield are not always positive for grain quality, putting additional pressure on global wheat production.

Using reanalysis in crop monitoring and forecasting systems

Weather observations are essential for crop monitoring and forecasting but they are not always available and in some cases they have limited spatial representativeness. Thus, reanalyses represent an alternative source of information to be explored. In this study, we assess the feasibility of reanalysis-based crop monitoring and forecasting by using the system developed and maintained by the European Commission- Joint Research Centre, its gridded daily meteorological observations, the biased-corrected reanalysis AgMERRA and the ERA-Interim reanalysis. We focus on Europe and on two crops, wheat and maize, in the period 1980-2010 under potential and water-limited conditions. In terms of inter-annual yield correlation at the country scale, the reanalysis-driven systems show a very good performance for both wheat and maize (with correlation values higher than 0.6 in almost all EU28 countries) when compared to the observations-driven system. However, significant yield biases affect both crops. All simulations show similar correlations with respect to the FAO reported yield time series. These findings support the integration of reanalyses in current crop monitoring and forecasting systems and point to the emerging opportunities linked to the coming availability of higher-resolution reanalysis updated at near real time.

Diverging importance of drought stress for maize and winter wheat in Europe

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. Across Europe, on average heat stress does not increase for either crop in rainfed systems, while drought stress intensifies for maize only. In low-yielding years, drought stress persists as the main driver of losses for both crops, with elevated CO₂ offering no yield benefit in these years.

Drivers of crop yield variability require quantification, and historical records can help in improving understanding. Here, Webber et al. report that drought stress will remain a key driver of yield losses in wheat and maize across Europe, and benefits from CO₂ will be limited in low-yielding years.

The implication of irrigation in climate change impact assessment: a European-wide study

This study evaluates the impacts of projected climate change on irrigation requirements and yields of six crops (winter wheat, winter barley, rapeseed, grain maize, potato, and sugar beet) in Europe. Furthermore, the uncertainty deriving from consideration of irrigation, CO2 effects on crop growth and transpiration, and different climate change scenarios in climate change impact assessments is quantified. Net irrigation requirement (NIR) and yields of the six crops were simulated for a baseline (1982-2006) and three SRES scenarios (B1, B2 and A1B, 2040-2064) under rainfed and irrigated conditions, using a process-based crop model, SIMPLACE <LINTUL5, DRUNIR, HEAT>. We found that projected climate change decreased NIR of the three winter crops in northern Europe (up to 81 mm), but increased NIR of all the six crops in the Mediterranean regions (up to 182 mm yr(-1) ). Climate change increased yields of the three winter crops and sugar beet in middle and northern regions (up to 36%), but decreased their yields in Mediterranean countries (up to 81%). Consideration of CO2 effects can alter the direction of change in NIR for irrigated crops in the south and of yields for C3 crops in central and northern Europe. Constraining the model to rainfed conditions for spring crops led to a negative bias in simulating climate change impacts on yields (up to 44%), which was proportional to the irrigation ratio of the simulation unit. Impacts on NIR and yields were generally consistent across the three SRES scenarios for the majority of regions in Europe. We conclude that due to the magnitude of irrigation and CO2 effects, they should both be considered in the simulation of climate change impacts on crop production and water availability, particularly for crops and regions with a high proportion of irrigated crop area.

Green fluorescent protein functions as a reporter for protein localization in Escherichia coli

The use of green fluorescent protein (GFP) as a reporter for protein localization in Escherichia coli was explored by creating gene fusions between malE (encoding maltose-binding protein [MBP]) and a variant of gfp optimized for fluorescence in bacteria (GFPuv). These constructs encode hybrid proteins composed of GFP fused to the carboxy-terminal end of MBP. Fluorescence was not detected when the hybrid protein was synthesized with the MBP signal sequence. In contrast, when the MBP signal sequence was deleted, fluorescence was observed. Cell fractionation studies showed that the fluorescent MBP-GFP hybrid protein was localized in the cytoplasm, whereas the nonfluorescent version was localized to the periplasmic space. Smaller MBP-GFP hybrid proteins, however, exhibited abnormal fractionation. Expression of the gene fusions in different sec mutants, as well as signal sequence processing assays, confirmed that the periplasmically localized hybrid proteins were exported by the sec-dependent pathway. The distinction between fluorescent and nonfluorescent colonies was exploited as a scorable phenotype to isolate malE signal sequence mutations. While expression of hybrid proteins comprised of full-length MBP did not result in overproduction lethality characteristic of some exported beta-galactosidase hybrid proteins, synthesis of shorter, exported hybrid proteins was toxic to the cells. Purification of MBP-GFP hybrid protein from the different cellular compartments indicated that GFP is improperly folded when localized outside of the cytoplasm. These results suggest that GFP could serve as a useful reporter for genetic analysis of bacterial protein export and of protein folding.

Mutation analysis of UBE3A in Angelman syndrome patients

Angelman syndrome (AS) is caused by chromosome 15q11-q13 deletions of maternal origin, by paternal uniparental disomy (UPD) 15, by imprinting defects, and by mutations in the UBE3A gene. UBE3A encodes a ubiquitin-protein ligase and shows brain-specific imprinting. Here we describe UBE3A coding-region mutations detected by SSCP analysis in 13 AS individuals or families. Two identical de novo 5-bp duplications in exon 16 were found. Among the other 11 unique mutations, 8 were small deletions or insertions predicted to cause frameshifts, 1 was a mutation to a stop codon, 1 was a missense mutation, and 1 was predicted to cause insertion of an isoleucine in the hect domain of the UBE3A protein, which functions in E2 binding and ubiquitin transfer. Eight of the cases were familial, and five were sporadic. In two familial cases and one sporadic case, mosaicism for UBE3A mutations was detected: in the mother of three AS sons, in the maternal grandfather of two AS first cousins, and in the mother of an AS daughter. The frequencies with which we detected mutations were 5 (14%) of 35 in sporadic cases and 8 (80%) of 10 in familial cases.