Narrowing uncertainties in the effects of elevated CO2 on crops

Fusarium mycotoxins: The major food contaminants

Mycotoxins, which are secondary metabolites produced by toxicogenic fungi, are natural food toxins that cause acute and chronic adverse reactions in humans and animals. The genus Fusarium is one of three major genera of mycotoxin-producing fungi. Trichothecenes, fumonisins, and zearalenone are the major Fusarium mycotoxins that occur worldwide. Fusarium mycotoxins have the potential to infiltrate the human food chain via contamination during crop production and food processing, eventually threatening human health. The occurrence and development of Fusarium mycotoxin contamination will change with climate change, especially with variations in temperature, precipitation, and carbon dioxide concentration. To address these challenges, researchers have built a series of effective models to forecast the occurrence of Fusarium mycotoxins and provide guidance for crop production. Fusarium mycotoxins frequently exist in food products at extremely low levels, thus necessitating the development of highly sensitive and reliable detection techniques. Numerous successful detection methods have been developed to meet the requirements of various situations, and an increasing number of methods are moving toward high-throughput features. Although Fusarium mycotoxins cannot be completely eliminated, numerous agronomic, chemical, physical, and biological methods can lower Fusarium mycotoxin contamination to safe levels during the preharvest and postharvest stages. These theoretical innovations and technological advances have the potential to facilitate the development of comprehensive strategies for effectively managing Fusarium mycotoxin contamination in the future.

Primary Metabolic Response of Aristolochia contorta to Simulated Specialist Herbivory under Elevated CO2 Conditions

This study explores how elevated carbon dioxide (CO2) levels affects the growth and defense mechanisms of plants. We focused on Aristolochia contorta Bunge (Aristolochiaceae), a wild plant that exhibits growth reduction under elevated CO2 in the previous study. The plant has Sericinus montela Gray (Papilionidae) as a specialist herbivore. By analyzing primary metabolites, understanding both the growth and defense response of plants to herbivory under elevated CO2 conditions is possible. The experiment was conducted across four groups, combining two CO2 concentration conditions (ambient CO2 and elevated CO2) with two herbivory conditions (herbivory treated and untreated). Although many plants exhibit increased growth under elevated CO2 levels, A. contorta exhibited reduced growth with lower height, dry weight, and total leaf area. Under herbivory, A. contorta triggered both localized and systemic responses. More primary metabolites exhibited significant differences due to herbivory treatment in systemic tissue than local leaves that herbivory was directly treated. Herbivory under elevated CO2 level triggered more significant responses in primary metabolites (17 metabolites) than herbivory under ambient CO2 conditions (five metabolites). Several defense-related metabolites exhibited higher concentrations in the roots and lower concentrations in the leaves in response to the herbivory treatment in the elevated CO2 group. This suggests a potential intensification of defensive responses in the underground parts of the plant under elevated CO2 levels. Our findings underscore the importance of considering both abiotic and biotic factors in understanding plant responses to environmental changes. The adaptive strategies of A. contorta suggest a complex response mechanism to elevated CO2 and herbivory pressures.

Statistical sampling of missing environmental variables improves biophysical genomic prediction in wheat

KEY MESSAGE

The integration of genomic prediction with crop growth models enabled the estimation of missing environmental variables which improved the prediction accuracy of grain yield. Since the invention of whole-genome prediction (WGP) more than two decades ago, breeding programmes have established extensive reference populations that are cultivated under diverse environmental conditions. The introduction of the CGM-WGP model, which integrates crop growth models (CGM) with WGP, has expanded the applications of WGP to the prediction of unphenotyped traits in untested environments, including future climates. However, CGMs require multiple seasonal environmental records, unlike WGP, which makes CGM-WGP less accurate when applied to historical reference populations that lack crucial environmental inputs. Here, we investigated the ability of CGM-WGP to approximate missing environmental variables to improve prediction accuracy. Two environmental variables in a wheat CGM, initial soil water content (InitlSoilWCont) and initial nitrate profile, were sampled from different normal distributions separately or jointly in each iteration within the CGM-WGP algorithm. Our results showed that sampling InitlSoilWCont alone gave the best results and improved the prediction accuracy of grain number by 0.07, yield by 0.06 and protein content by 0.03. When using the sampled InitlSoilWCont values as an input for the traditional CGM, the average narrow-sense heritability of the genotype-specific parameters (GSPs) improved by 0.05, with GNSlope, PreAnthRes, and VernSen showing the greatest improvements. Moreover, the root mean square of errors for grain number and yield was reduced by about 7% for CGM and 31% for CGM-WGP when using the sampled InitlSoilWCont values. Our results demonstrate the advantage of sampling missing environmental variables in CGM-WGP to improve prediction accuracy and increase the size of the reference population by enabling the utilisation of historical data that are missing environmental records.

Integrated crop and livestock systems increase both climate change adaptation and mitigation capacities

Integrated crop-livestock systems (ICLS) are proposed as key solutions to the various challenges posed to present-day agriculture which must guarantee high and stable yields while minimizing its impacts on the environment. Yet the complex relationships between crops, grasslands and animals on which they rely demand careful and precise management. In this study, from a 18-year ICLS field experiment in Brazil, that consists in annual no-till soybean-pastures grazed by beef cattle, we investigated the impacts of contrasted pastures grazing intensities (defined by sward heights of 10, 20, 30 and 40 cm, plus an ungrazed treatment) on the agroecosystem productivity and soil organic carbon (SOC) under both historical and future (2040-2070, RCP8.5) climatic conditions. We used an innovative methodology to model the ICLS with the STICS soil-crop model, which was validated with field observations. Results showed that the total system production increased along with grazing intensity because of higher stocking rates and subsequent live weight gains. Moderate and light grazing intensities (30 and 40 cm sward heights) resulted in the largest increase in SOC over the 18-year period, with all ICLS treatments leading to greater SOC contents than the ungrazed treatment. When facing climate change under future conditions, all treatments increased in productivity due to the CO2 fertilization effect and the increases in organic amendments that result from the larger stocking rate allowed by the increased pasture carrying capacity. Moderate grazing resulted in the most significant enhancements in productivity and SOC levels. These improvements were accompanied by increased resistance to both moderate and extreme climatic events, benefiting herbage production and live weight gain. Globally, our results show that adding a trophic level (i.e. herbivores) into cropping systems, provided that their carrying capacities are respected, proved to increase their ability to withstand climate change and to contribute to its mitigation.

Beyond the Farm to Fork Strategy: Methodology for designing a European agro-ecological future

The publication of the European Commission's Farm to Fork Strategy has sparked a heated debate between those who advocate the intensification of agriculture in the name of food security and those who recommend its de-intensification for environmental reasons. The design of quantified scenarios is a key approach to objectively evaluate the arguments of the two sides. To this end, we used the accounting methodology GRAFS (Generalized Representation of Agri-Food Systems) to describe the agri-food system of Europe divided into 127 geographical units of similar agricultural area, in terms of nitrogen (N) fluxes across cropland, grassland, livestock, and human consumption. This analysis reveals, in current European agriculture, a high level of territorial specialization, a strong dependence on long distance trade, and environmental N losses amounting to about 14 TgN/yr, i.e. nearly 70 % of the annual N input (including N synthetic fertilizers, symbiotic N fixation, oxidized N deposition and import of food and feed). Based on the analysis of the yield-fertilization relationship of cropping systems at the scale of their full rotation cycle, and on a simplified model of livestock ingestion, excretion and production, we advanced the GRAFS methodology for prospective scenario design. Three scenarios for the European agri-food system were explored for 2050: a business-as-usual (BAU) scenario, a scenario based on the measures considered by the EU Farm to Fork Strategy (F2F), and a fully agro-ecological scenario (AE). The results show that the F2F scenario reduces the dependence of Europe on imports of synthetic fertilizers and feed resources by 40 % as well as the environmental N losses by 30 %, but not to the level of its claimed ambitions as N lost to the environment still amounts to about 10 TgN/yr, i.e. 67 % of N inputs. Of the three scenarios studied, only in the AE scenario, involving the relocation of feed production, the generalization of organic crop rotations with N fixing legume crops, and a shift of agricultural production and food consumption toward less animal-based products, would Europe be able to dispense with N imports, still being able to export some cereals, meat, and milk products to the rest of the world, while halving today's reactive N emissions to the environment.

Securing maize reproductive success under drought stress by harnessing CO2 fertilization for greater productivity

Securing maize grain yield is crucial to meet food and energy needs for the future growing population, especially under frequent drought events and elevated CO2 (eCO2) due to climate change. To maximize the kernel setting rate under drought stress is a key strategy in battling against the negative impacts. Firstly, we summarize the major limitations to leaf source and kernel sink in maize under drought stress, and identified that loss in grain yield is mainly attributed to reduced kernel set. Reproductive drought tolerance can be realized by collective contribution with a greater assimilate import into ear, more available sugars for ovary and silk use, and higher capacity to remobilize assimilate reserve. As such, utilization of CO2 fertilization by improved photosynthesis and greater reserve remobilization is a key strategy for coping with drought stress under climate change condition. We propose that optimizing planting methods and mining natural genetic variation still need to be done continuously, meanwhile, by virtue of advanced genetic engineering and plant phenomics tools, the breeding program of higher photosynthetic efficiency maize varieties adapted to eCO2 can be accelerated. Consequently, stabilizing maize production under drought stress can be achieved by securing reproductive success by harnessing CO2 fertilization.

Integrating biophysical crop growth models and whole genome prediction for their mutual benefit: a case study in wheat phenology

Running crop growth models (CGM) coupled with whole genome prediction (WGP) as a CGM-WGP model introduces environmental information to WGP and genomic relatedness information to the genotype-specific parameters modelled through CGMs. Previous studies have primarily used CGM-WGP to infer prediction accuracy without exploring its potential to enhance CGM and WGP. Here, we implemented a heading and maturity date wheat phenology model within a CGM-WGP framework and compared it with CGM and WGP. The CGM-WGP resulted in more heritable genotype-specific parameters with more biologically realistic correlation structures between genotype-specific parameters and phenology traits compared with CGM-modelled genotype-specific parameters that reflected the correlation of measured phenotypes. Another advantage of CGM-WGP is the ability to infer accurate prediction with much smaller and less diverse reference data compared with that required for CGM. A genome-wide association analysis linked the genotype-specific parameters from the CGM-WGP model to nine significant phenology loci including Vrn-A1 and the three PPD1 genes, which were not detected for CGM-modelled genotype-specific parameters. Selection on genotype-specific parameters could be simpler than on observed phenotypes. For example, thermal time traits are theoretically more independent candidates, compared with the highly correlated heading and maturity dates, which could be used to achieve an environment-specific optimal flowering period. CGM-WGP combines the advantages of CGM and WGP to predict more accurate phenotypes for new genotypes under alternative or future environmental conditions.

A comprehensive meta-analysis of the impacts of intensified drought and elevated CO2 on forage growth

Forage crops are used worldwide as key feed sources for dairy systems. However, their productivity and quality are limited due to intensified drought events, elevated carbon dioxide (CO₂), and their interaction with climate change, with consequences for the security of animal husbandry and the agricultural economy. Although studies have quantified the impacts of such stresses on forage growth, these impacts have been less systematically investigated in a global context due to differences among various forage groups, regional microclimates, and environmental factors. Herein we employed nine forage growth-related variables involving three perspectives, i.e., photosynthetic parameters, production, and quality, from research articles published between 1990 and 2021 via a meta-analysis. A linear mixed-effect model was then used to explore the quantitative relationship between these factors in a restricted dataset. Decreasing trends in all four photosynthetic parameters were detected across different eco-geographical regions with increasing drought stress. The maximum decrease in DMY occurred in the Mediterranean, with 52.8% under drought conditions. Globally, eCO₂ significantly increased photosynthetic rate (P_n) and instantaneous water use efficiency (WUE_i) by 40.8% and 62.1%, respectively, which also had positive effects on forage dry matter yield (DMY) (+25.1%), especially for forage in Northern Europe. However, this stress would significantly decrease forage quality by decreasing crude protein (CP) (-19.7%) and nitrogen content (N content) (-13.5%). These negative impacts would be aggravated under the co-occurrence of drought and eCO₂, including a significant increase in WUE_i (+111.1%) and a decrease in DMY (-12.3%). Gramineae showed a more sensitive response to drought stress in photosynthetic parameters and DMY than Leguminosae, but the latter exhibited a better response in photosynthetic parameters and production under eCO₂. Our analysis provides a consensus concerning how the growth parameters of forage have changed under environmental stresses.

Impacts of meteorological factors and ozone variation on crop yields in China concerning carbon neutrality objectives in 2060

Carbon neutrality objectives affect meteorology and ozone (O₃) concentration in China, both of which would influence crop yields, thus food security. However, the joint impact of these two factors on crop yields in China is not clear. In this study, we investigated future trends in China's maize, rice, soybean, and wheat yields under a carbon-neutral scenario considering both regional emission reduction and global climate change in 2060. By combining a process-based crop model (Agricultural Production Systems sIMulator, APSIM) with O₃ exposure equations, the impacts of regional emission reduction and global climate change were studied. The results suggest that regional emission reduction dominated the increase in yield by reducing the O₃ concentration, whereas global climate change led to yield loss mainly through meteorological factors. The national yield decreases for the four crops ranged from 1.0% to 38.0% owing to meteorological factors, while O₃ reduction resulted in additional yield increases ranging from 2.8% to 7.0%. The combined effect of carbon neutrality, which included both meteorological factors and O₃ concentration, resulted in changes to the yields of maize, rice, soybean, and wheat of +4.3%, -7.3%, -24.0%, and -31.7%, respectively. It seems that crop production loss caused by meteorological factors in 2060 would be mitigated by the O₃ reduction. Given the advantages of declining O₃ concentration, regional emission reduction would likely benefit crop growth. However, global climate change may offset the benefits and threaten food production in China. Therefore, more strict emission reduction policies and global climate change mitigation actions are necessary to ensure food security in China.

Climate service driven adaptation may alleviate the impacts of climate change in agriculture

Building a resilient and sustainable agricultural sector requires the development and implementation of tailored climate change adaptation strategies. By focusing on durum wheat (Triticum turgidum subsp. durum) in the Euro-Mediterranean region, we estimate the benefits of adapting through seasonal cultivar-selection supported by an idealised agro-climate service based on seasonal climate forecasts. The cost of inaction in terms of mean yield losses, in 2021–2040, ranges from −7.8% to −5.8% associated with a 7% to 12% increase in interannual variability. Supporting cultivar choices at local scale may alleviate these impacts and even turn them into gains, from 0.4% to 5.3%, as soon as the performance of the agro-climate service increases. However, adaptation advantages on mean yield may come with doubling the estimated increase in the interannual yield variability.

Study on the Impact of Climate Change on China's Import Trade of Major Agricultural Products and Adaptation Strategies

With global warming, China's agricultural products are facing severe production conditions and a complex international trade situation. In order to clarify the relationship between climate change and China's agricultural trade, this paper uses the GTAP model to explore the impact of climate change on China's agricultural trade from the perspectives of agricultural production and supply, energy substitution and trade policy. The results show that: (1) From the overall effect, the production supply risk and energy substitution risk caused by climate change have a positive impact on China's import trade, among which the energy substitution risk has brought about an import trade growth of 38.050%, the production supply risk has brought about an import trade growth of 12.635%, and the trade policy risk has a negative impact, bringing about an import trade decline of 12.589%. (2) Under the impact of production and supply risks caused by climate change, the import volume of different industrial sectors has increased by varying degrees, including livestock products (16.521%) > food crops (14.162%) > cash crops (7.220%). The increase in import trade mainly comes from the United States (10.731%), Canada (10.650%) and Australia (9.455%). (3) Under the impact of energy substitution risk caused by climate change, the increase in import trade was concentrated in food crops (48.144%) and livestock products (42.834%), mainly from the United States (57.098%), the European Union (55.014%) and Canada (53.508%). (4) Under the impact of trade policy risks caused by climate change, the import trade of different industrial sectors showed a downward trend, with cash crops (13.039%) > livestock products (12.588%) > cash crops (12.140%). The countries and regions with significant decline in import trade were ASEAN (-46.131%) and the United States (-28.028%). The trade deficit shifted to surplus, and the terms of trade were improved. Therefore, this paper suggests that we should deal with the impact of climate change on agricultural trade by developing "climate smart" agriculture, actively responding to low-carbon trade measures, and establishing an agricultural trade promotion mechanism to address the risk of climate change.

Six decades of warming and drought in the world's top wheat-producing countries offset the benefits of rising CO2 to yield

Future atmospheric carbon-dioxide concentration ([CO₂]) rise is expected to increase the grain yield of C3 crops like wheat even higher under drought. This expectation is based on small-scale experiments and model simulations based on such observations. However, this combined effect has never been confirmed through actual observations at the nationwide or regional scale. We present the first evidence that warming and drought in the world's leading wheat-producing countries offset the benefits of increasing [CO₂] to wheat yield in the last six decades. Using country-level wheat yield census observations, [CO₂] records, and gridded climate data in a statistical model based on a well-established methodology, we show that a [CO₂] rise of ~ 98 μmol mol^-1 increased the yield by 7% in the area of the top-twelve wheat-producing countries, while warming of 1.2 °C and water depletion of ~ 29 mm m^-2 reduced the wheat grain yield by ~ 3% and ~ 1%, respectively, in the last six decades (1961-2019). Our statistical model corroborated the beneficial effect of [CO₂] but contrasted the expected increase of grain yield under drought. Moreover, the increase in [CO₂] barely offsets the adverse impacts of warming and drought in countries like Germany and France, with a net yield loss of 3.1% and no gain, respectively, at the end of the sampling period relative to the 1961-1965 baseline. In China and the wheat-growing areas of the former Soviet Union-two of the three largest wheat-producing regions-yields were ~ 5.5% less than expected from current [CO₂] levels. Our results suggest shifting our efforts towards more experimental studies set in currently warm and dry areas and combining these with statistical and numerical modeling to improve our understanding of future impacts of a warmer and drier world with higher [CO₂].

Performance Prediction of Durum Wheat Genotypes in Response to Drought and Heat in Climate Change Conditions

With an approach combining crop modelling and biotechnology to assess the performance of three durum wheat cultivars (Creso, Duilio, Simeto) in a climate change context, weather and agronomic datasets over the period 1973–2004 from two sites, Benatzu and Ussana (Southern Sardinia, Itay), were used and the model responses were interpreted considering the role of DREB genes in the genotype performance with a focus on drought conditions. The CERES-Wheat crop model was calibrated and validated for grain yield, earliness and kernel weight. Forty-eight synthetic scenarios were used: 6 scenarios with increasing maximum air temperature; 6 scenarios with decreasing rainfall; 36 scenarios combining increasing temperature and decreasing rainfall. The simulated effects on yields, anthesis and kernel weights resulted in yield reduction, increasing kernel weight, and shortened growth duration in both sites. Creso (late cultivar) was the most sensitive to simulated climate conditions. Simeto and Duilio (early cultivars) showed lower simulated yield reductions and a larger anticipation of anthesis date. Observed data showed the same responses for the three cultivars in both sites. The CERES-Wheat model proved to be effective in representing reality and can be used in crop breeding programs with a molecular approach aiming at developing molecular markers for the resistance to drought stress.

Agricultural breadbaskets shift poleward given adaptive farmer behavior under climate change

Modern food production is spatially concentrated in global "breadbaskets." A major unresolved question is whether these peak production regions will shift poleward as the climate warms, allowing some recovery of potential climate-related losses. While agricultural impacts studies to date have focused on currently cultivated land, the Global Gridded Crop Model Intercomparison Project (GGCMI) Phase 2 experiment allows us to assess changes in both yields and the location of peak productivity regions under warming. We examine crop responses under projected end of century warming using seven process-based models simulating five major crops (maize, rice, soybeans, and spring and winter wheat) with a variety of adaptation strategies. We find that in no-adaptation cases, when planting date and cultivar choices are held fixed, regions of peak production remain stationary and yield losses can be severe, since growing seasons contract strongly with warming. When adaptations in management practices are allowed (cultivars that retain growing season length under warming and modified planting dates), peak productivity zones shift poleward and yield losses are largely recovered. While most growing-zone shifts are ultimately limited by geography, breadbaskets studied here move poleward over 600 km on average by end of the century under RCP 8.5. These results suggest that agricultural impacts assessments can be strongly biased if restricted in spatial area or in the scope of adaptive behavior considered. Accurate evaluation of food security under climate change requires global modeling and careful treatment of adaptation strategies.

Developing climate-resilient crops: improving plant tolerance to stress combination

Global warming and climate change are driving an alarming increase in the frequency and intensity of different abiotic stresses, such as droughts, heat waves, cold snaps, and flooding, negatively affecting crop yields and causing food shortages. Climate change is also altering the composition and behavior of different insect and pathogen populations adding to yield losses worldwide. Additional constraints to agriculture are caused by the increasing amounts of human-generated pollutants, as well as the negative impact of climate change on soil microbiomes. Although in the laboratory, we are trained to study the impact of individual stress conditions on plants, in the field many stresses, pollutants, and pests could simultaneously or sequentially affect plants, causing conditions of stress combination. Because climate change is expected to increase the frequency and intensity of such stress combination events (e.g., heat waves combined with drought, flooding, or other abiotic stresses, pollutants, and/or pathogens), a concentrated effort is needed to study how stress combination is affecting crops. This need is particularly critical, as many studies have shown that the response of plants to stress combination is unique and cannot be predicted from simply studying each of the different stresses that are part of the stress combination. Strategies to enhance crop tolerance to a particular stress may therefore fail to enhance tolerance to this specific stress, when combined with other factors. Here we review recent studies of stress combinations in different plants and propose new approaches and avenues for the development of stress combination- and climate change-resilient crops.

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.