Changes in the drought sensitivity of US maize yields

Spatio-temporal change of winter wheat yield and its quantitative responses to compound frost-dry events - An example of the Huang-Huai-Hai Plain of China from 2001 to 2020

Extreme climate events such as frost and drought have great influence on wheat growth and yield. Understanding the effects of frost, drought and compound frost-dry events on wheat growth and yield is of great significance for ensuring national food security. In this study, wheat yield prediction model (SCYMvp) was developed by combining crop growth model (CGM), satellite images and meteorological variables. Wheat yield maps in the Huang-Huai-Hai Plain (HHHP) during 2001-2020 were generated using SCYMvp model. Meanwhile, accumulative frost days (AFD), accumulative dry days (ADD) and accumulative frost-dry days (AFDD) in different growth periods of wheat were calculated, and the effects of frost and drought on wheat yield were quantified by the first difference method and linear mixed model. The results showed that wheat yield increased significantly, while the rising trend was obvious at more than half of the regions. Extreme climate events (ECEs) showed a relatively stable change trend, although the change trend was significant only in a few areas. Compared with frost and drought in the early growth period, ECEs in the middle growth period (spring ECEs) had more negative effects on wheat growth and yield. Wheat yield was negatively correlated with spring ECEs, and yield loss was between 4.6 and 49.8 kg/ha for each 1 d increase of spring ECEs. The effects of spring ECEs on wheat yield were ranked as AFDD > AFD > ADD. The negative effect of ADD on wheat yield in the late growth period was higher than that in the other periods. The negative effects of spring ECEs on yield in southern regions were higher than those in northern regions. Overall, due to the adverse effects of frost and drought on wheat yield in the middle and late growth periods, the mean annual yield loss was 6.4 %, among which spring AFD caused the greatest loss to wheat yield (3.1 %). The results have important guiding significance for formulating climate adaptation management strategies.

Predicting rice productivity for ground data-sparse regions: A transferable framework and its application to North Korea

The use of observation-dependent methods for crop productivity and food security assessment is challenging in data-sparse regions. This study presents a transferable framework and applies it to North Korea (NK) to assess rice productivity based on climate similarity, transferable machine-learning techniques, and extendable multi-source data. We initially divided the primary phenological stages of rice in the study region and extracted dynamic rice distributions based on Moderate Resolution Imaging Spectroradiometer products and phenological observations. We compared the performances of four representative environmentally driven models (Linear Regression, back-propagation Neural Network, Support Vector Machine, and Random Forest) in simulating rice productivity using an extensive dataset that included multi-angle vegetation monitoring, climate variables, and planting distribution information. The framework integrated an optimal environmentally driven model with agricultural management practices for transferability to predict rice productivity in NK over multiple years. Additionally, two crop growth scenarios (whole growth period (WGP) and seeding-heading period (SHP)) were compared to assess pre-harvest forecasting capabilities and identify dominant factors. Finally, independent datasets from the Food and Agriculture Organization, World Food Program, and Global Gridded Crop Models were used to validate the magnitude and spatial distribution of the predicted results. The results showed that phenological identification based on remote sensing can accurately capture rice growth characteristics and map rice distribution. Random Forest outperformed other models in simulating rice productivity variation, with r-squares of 0.87 and 0.83 in the WGP and SHP, respectively. The solar-induced chlorophyll fluorescence, maximum temperature, and evapotranspiration collectively determined approximately 40 % of the variation in yield simulated using Random Forest. Conversely, planting areas contributed over 42 % of the variation in rice production. Compared to Food and Agriculture Organization statistics, the environmentally driven framework explained 78.72 % and 76.89 % of the production variation and 69.42 % and 71.15 % of the yield variation in NK under the WGP and SHP, respectively. Moreover, the environmental management-driven framework captured over 90 % of the yield variation. The predicted spatial pattern of rice productivity exhibited significant concordance with the World Food Program and Global Gridded Crop Model reports. In summary, the proposed transferable framework for crop productivity assessment contributes to early warnings of production reduction and has the potential for scalability across various crops and data-sparse regions.

Comprehensive identification of maize ZmE2F transcription factors and the positive role of ZmE2F6 in response to drought stress

BACKGROUND

The early 2 factor (E2F) family is characterized as a kind of transcription factor that plays an important role in cell division, DNA damage repair, and cell size regulation. However, its stress response has not been well revealed.

RESULTS

In this study, ZmE2F members were comprehensively identified in the maize genome, and 21 ZmE2F genes were identified, including eight E2F subclade members, seven DEL subfamily genes, and six DP genes. All ZmE2F proteins possessed the DNA-binding domain (DBD) characterized by conserved motif 1 with the RRIYD sequence. The ZmE2F genes were unevenly distributed on eight maize chromosomes, showed diversity in gene structure, expanded by gene duplication, and contained abundant stress-responsive elements in their promoter regions. Subsequently, the ZmE2F6 gene was cloned and functionally verified in drought response. The results showed that the ZmE2F6 protein interacted with ZmPP2C26, localized in the nucleus, and responded to drought treatment. The overexpression of ZmE2F6 enhanced drought tolerance in transgenic Arabidopsis with longer root length, higher survival rate, and biomass by upregulating stress-related gene transcription.

CONCLUSIONS

This study provides novel insights into a greater understanding and functional study of the E2F family in the stress response.

Comparative analysis of thermal indices for modeling cold and heat stress in US dairy systems

Quantifying the impact of thermal stress on milk yields is essential to effectively manage present and future risks in dairy systems. Despite the existence of numerous heat indices designed to communicate stress thresholds, little information is available regarding the accuracy of different indices in estimating milk yield losses from both cold and heat stress at large spatio-temporal scales. To address this gap, we comparatively analyzed the performance of existing thermal indices in capturing US milk yield response to both cold and heat stress at the national scale. We selected four commonly used thermal indices: the Temperature and Humidity Index (THI), Black Globe Humidity Index (BGHI), Adjusted Temperature and Humidity Index (THIadj), and Comprehensive Climate Index (CCI). Using a statistical panel regression model with observational and reanalysis weather data from 1981-2020, we systematically compared the patterns of yield sensitivities and statistical performance of the four indices. We found that the US state-level milk yield variability was better explained by the THIadj and CCI, which combine the effects of temperature, humidity, wind, and solar radiation. Our analysis also reveals a continuous and nonlinear responses of milk yields to a range of cold to heat stress across all four indices. This implies that solely relying on fixed thresholds of these indices to model milk yield changes may be insufficient to capture cumulative thermal stress. Cold extremes reduced milk yields comparably to those impacted by heat extremes on the national scale. Additionally, we found large spatial variability in milk yield sensitivities, implying further limitations to the use of fixed thresholds across locations. Moreover, we found decreased yield sensitivity to thermal stress in the most recent two decades, suggesting adaptive changes in management to reduce weather-related risks.

The E3 ligase TaGW2 mediates transcription factor TaARR12 degradation to promote drought resistance in wheat

Drought stress limits crop yield, but the molecular modulators and their mechanisms underlying the trade-off between drought resistance and crop growth and development remain elusive. Here, a grain width and weight2 (GW2)-like really interesting new gene finger E3 ligase, TaGW2, was identified as a pivotal regulator of both kernel development and drought responses in wheat (Triticum aestivum). TaGW2 overexpression enhances drought resistance but leads to yield drag under full irrigation conditions. In contrast, TaGW2 knockdown or knockout attenuates drought resistance but remarkably increases kernel size and weight. Furthermore, TaGW2 directly interacts with and ubiquitinates the type-B Arabidopsis response regulator TaARR12, promoting its degradation via the 26S proteasome. Analysis of TaARR12 overexpression and knockdown lines indicated that TaARR12 represses the drought response but does not influence grain yield in wheat. Further DNA affinity purification sequencing combined with transcriptome analysis revealed that TaARR12 downregulates stress-responsive genes, especially group-A basic leucine zipper (bZIP) genes, resulting in impaired drought resistance. Notably, TaARR12 knockdown in the clustered regularly interspaced short palindromic repeat (CRISPR)/CRISPR-associated nuclease 9 (Cas9)-mediated tagw2 knockout mutant leads to significantly higher drought resistance and grain yield compared to wild-type plants. Collectively, these findings show that the TaGW2-TaARR12 regulatory module is essential for drought responses, providing a strategy for improving stress resistance in high-yield wheat varieties.

Air quality improvements can strengthen China's food security

Air pollution exerts crucial influence on crop yields and impacts regional and global food supplies. Here we employ a statistical model using satellite-based observations and flexible functional forms to analyse the synergistic effects of reductions in ozone and aerosols on China's food security. The model consistently shows that ozone is detrimental to crops, whereas aerosol has variable effects. China's maize, rice and wheat yields are projected to increase by 7.84%, 4.10% and 3.43%, respectively, upon reaching two air quality targets (60 μg m-3 for peak-season ozone and 35 μg m-3 for annual fine particulate matter). Average calories produced from these crops would surge by 4.51%, potentially allowing China to attain grain self-sufficiency 2 years earlier than previously estimated. These results show that ozone pollution control should be a high priority to increase staple crop edible calories, and future stringent air pollution regulations would enhance China's food security.

Spatiotemporal co-optimization of agricultural management practices towards climate-smart crop production

Co-optimization of multiple management practices may facilitate climate-smart agriculture, but is challenged by complex climate-crop-soil management interconnections across space and over time. Here we develop a hybrid approach combining agricultural system modelling, machine learning and life cycle assessment to spatiotemporally co-optimize fertilizer application, irrigation and residue management to achieve yield potential of wheat and maize and minimize greenhouse gas emissions in the North China Plain. We found that the optimal fertilizer application rate and irrigation for the historical period (1995-2014) are lower than local farmers' practices as well as trial-derived recommendations. With the optimized practices, the projected annual requirement of fertilizer, irrigation water and residue inputs across the North China Plain in the period 2051-2070 is reduced by 16% (14-21%) (mean with 95% confidence interval), 19% (7-32%) and 20% (16-26%), respectively, compared with the current supposed optimal management in the historical reference period, with substantial greenhouse gas emission reductions. We demonstrate the potential of spatiotemporal co-optimization of multiple management practices and present digital mapping of management practices as a benchmark for site-specific management across the region.

A Remote Sensing Approach for Assessing Daily Cumulative Evapotranspiration Integral in Wheat Genotype Screening for Drought Adaptation

This study considers critical aspects of water management and crop productivity in wheat cultivation, specifically examining the daily cumulative actual evapotranspiration (ETa). Traditionally, ETa surface energy balance models have provided estimates at discrete time points, lacking a holistic integrated approach. Field trials were conducted with 22 distinct wheat varieties, grown under both irrigated and rainfed conditions over a two-year span. Leaf area index prediction was enhanced through a robust multiple regression model, incorporating data acquired from an unmanned aerial vehicle using an RGB sensor, and resulting in a predictive model with an R2 value of 0.85. For estimation of the daily cumulative ETa integral, an integrated approach involving remote sensing and energy balance models was adopted. An examination of the relationships between crop yield and evapotranspiration (ETa), while considering factors like year, irrigation methods, and wheat cultivars, unveiled a pronounced positive asymptotic pattern. This suggests the presence of a threshold beyond which additional water application does not significantly enhance crop yield. However, a genetic analysis of the 22 wheat varieties showed no correlation between ETa and yield. This implies opportunities for selecting resource-efficient wheat varieties while minimizing water use. Significantly, substantial disparities in water productivity among the tested wheat varieties indicate the possibility of intentionally choosing lines that can optimize grain production while minimizing water usage within breeding programs. The results of this research lay the foundation for the development of resource-efficient agricultural practices and the cultivation of crop varieties finely attuned to water-scarce regions.

Assessment of the sustainability of groundwater utilization and crop production under optimized irrigation strategies in the North China Plain under future climate change

Over-exploitation of groundwater due to intensive irrigation and anticipated climate change pose severe threats to the water and food security worldwide, particularly in the North China Plain (NCP). Limited irrigation has been recognized as an effective way to improve crop water productivity and slow the rapid decline of groundwater levels. Whether optimized limited irrigation strategies could achieve a balance between groundwater pumping and grain production in the NCP under future climate change deserves further study. In this study, an improved Soil and Water Assessment Tool (SWAT) model was used to simulate climate change impacts on shallow groundwater levels and crop production under limited irrigation strategies to suggest optimal irrigation management practices under future climate conditions in the NCP. The simulations of eleven limited irrigation strategies for winter wheat with targeted irrigations at different growth stages and with irrigated or rainfed summer maize were compared with future business-as-usual management. Climate change impacts showed that mean wheat (maize) yield under adequate irrigation was expected to increase by 13.2% (4.9%) during the middle time period (2041-2070) and by 11.2% (4.6%) during the late time period (2071-2100) under three SSPs compared to the historical period (1971-2000). Mean decline rate of shallow groundwater level slowed by approximately 1 m a-1 during the entire future period (2041-2100) under three SSPs with a greater reduction for SSP5-8.5. The average contribution rate of future climate toward the balance of shallow groundwater pumping and replenishment was 62.9%. Based on the simulated crop yields and decline rate of shallow groundwater level under the future climate, the most appropriate limited irrigation was achieved by applying irrigation during the jointing stage of wheat with rainfed maize, which could achieve the groundwater recovery and sustainable food production.

Genetic and molecular exploration of maize environmental stress resilience: Toward sustainable agriculture

Global climate change exacerbates the effects of environmental stressors, such as drought, flooding, extreme temperatures, salinity, and alkalinity, on crop growth and grain yield, threatening the sustainability of the food supply. Maize (Zea mays) is one of the most widely cultivated crops and the most abundant grain crop in production worldwide. However, the stability of maize yield is highly dependent on environmental conditions. Recently, great progress has been made in understanding the molecular mechanisms underlying maize responses to environmental stresses and in developing stress-resilient varieties due to advances in high-throughput sequencing technologies, multi-omics analysis platforms, and automated phenotyping facilities. In this review, we summarize recent advances in dissecting the genetic factors and networks that contribute to maize abiotic stress tolerance through diverse strategies. We also discuss future challenges and opportunities for the development of climate-resilient maize varieties.

Impact of soil moisture stress during the silk emergence and grain-filling in maize

Suboptimal soil moisture during the growing season often limits maize growth and yield. However, the growth stage-specific responses of maize to soil moisture regimes have not been thoroughly investigated. This study investigated the response of maize to five different soil moisture regimes, that are, 0.25, 0.20, 0.15, 0.10, and 0.05 m3  m-3 volumetric water content (VWC), during flowering and grain-filling stages. Sub-optimal soil moisture at the flowering and grain-filling stages reduced ear leaf stomatal conductance by 73 and 64%, respectively. An increase in stress severity caused significant reductions in ear leaf chlorophyll content and greenness-associated vegetation indices across growth stages. Fourteen days of soil moisture stress during flowering delayed silk emergence, reduced silk length (19%), and silk fresh weight (34%). Furthermore, sub-optimal soil moisture caused a significant reduction in both kernel number (53%) and weight (54%). Soil moisture stress at the flowering had a direct impact on kernel number and an indirect effect on kernel weight. During grain-filling, disruption of ear leaf physiology resulted in a 34% decrease in kernel weight and a 43% decrease in kernel number. Unlike grain-filling, treatments at the flowering significantly reduced kernel starch (3%) and increased protein by 29%. These findings suggest that developing reproductive stage stress-tolerant hybrids with improved resilience to soil moisture stress could help reduce the yield gap between irrigated and rainfed maize.

A genetic tradeoff for tolerance to moderate and severe heat stress in US hybrid maize

Global climate change is increasing both average temperatures and the frequencies of extreme high temperatures. Past studies have documented a strong negative effect of exposures to temperatures >30°C on hybrid maize yields. However, these studies could not disentangle genetic adaptation via artificial selection from changes in agronomic practices. Because most of the earliest maize hybrids are no longer available, side-by-side comparisons with modern hybrids under current field conditions are generally impossible. Here, we report on the collection and curation of 81 years of public yield trial records covering 4,730 maize hybrids, which enabled us to model genetic variation for temperature responses among maize hybrids. We show that selection may have indirectly and inconsistently contributed to the genetic adaptation of maize to moderate heat stress over this time period while preserving genetic variance for continued adaptation. However, our results reveal the existence of a genetic tradeoff for tolerance to moderate and severe heat stress, leading to a decrease in tolerance to severe heat stress over the same time period. Both trends are particularly conspicuous since the mid-1970s. Such a tradeoff poses challenges to the continued adaptation of maize to warming climates due to a projected increase in the frequency of extreme heat events. Nevertheless, given recent advances in phenomics, enviromics, and physiological modeling, our results offer a degree of optimism for the capacity of plant breeders to adapt maize to warming climates, assuming appropriate levels of R&D investment.

Developing Functional Relationships between Soil Moisture Content and Corn Early-Season Physiology, Growth, and Development

Drought is a severe threat to agriculture production that affects all growth stages of plants, including corn (Zea mays L.). Any factor affecting early seedling growth and development will significantly impact yield. Despite the recurrence of low rainfall during the growing seasons, corn responses to different early-season soil moisture content levels have not been investigated. In this study, we investigated how corn morpho-physiological and biomass traits responded to varied soil moisture content during the early vegetative stage. Two corn hybrids were grown in a pot-culture facility under five different soil moisture treatments (0.15, 0.12, 0.09, 0.06, and 0.03 m³ m^-3 volumetric water content, VWC) to assess the growth and developmental responses to varied soil moisture content during early-season growth (V2 to V7) stage. Sub-optimal soil moisture content limited plant growth and development by reducing physiological and phenotypic expression. Stomatal conductance and transpiration were decreased by an average of 65% and 59% across stress treatments relative to optimum conditions. On average, soil moisture deficit reduced the total leaf area by 71% and 72% compared to the control in 'A6659VT2RIB' and 'P1316YHR', respectively. Shoot and root dry weights were reduced by 74% and 43% under 0.03 m³ m^-3 VWC. An increase in the root-to-shoot ratio was noticed under low VWC conditions compared to the control. Based on the stress tolerance index, the physiology and leaf growth parameters were more sensitive to soil moisture deficit. Our results highlight the impact of sub-optimal soil moisture on physiology and morphological traits during early-season growth. 'P1316YHR' demonstrated better physiological performance under stress conditions, while 'A6659VT2RIB' produced relatively better root growth. The findings suggest that biomass partitioning between shoot and root components is dynamic and depends on stress intensity. The current findings can help to prioritize traits associated with the early-season drought tolerance in corn. The functional relationships developed between soil moisture content and growth and developmental responses can be integrated into corn crop modeling to allow better irrigation management decisions.

Rice yield benefits from historical climate warming to be negated by extreme heat in Northeast China

Rice is currently benefiting from climate warming in Northeast China, but whether such positive effect will continue in the future remains unknown. Here, we evaluate the impacts of individual and combined climate variables on rice yields in Northeast China during 1980-2015. Results show that there is 10% yield increase induced by climate change in Northeast China since 1980. At present, the reduced chilling results in 5.4% yield increase (approximately 28,000 tons) and the higher growing degree-day contributes to 4.6% yield increase (approximately 24,000 tons), while the high-temperature extreme reduced yield by 0.054% (approximately 280 tons). However, with continuous warming, the harmful impact of such high-temperature extreme will outweigh other positive climate effects when the temperature increases by 3.36 °C. Therefore, high-temperature extremes cannot be ignored despite their influence on rice yield being quite limited at present in Northeast China. Climate change mitigation and heat tolerance breeding are thus necessary for rice production in Northeast China.

Possible factors determining global-scale patterns of crop yield sensitivity to drought

In recent decades, droughts have critically limited crop production, inducing food system shocks regionally and globally. It was estimated that crop yield variability in around one-third to three-fourths of global harvested areas is explained significantly by drought, revealing the notable vulnerability of crop systems to such climate-related stressors. However, understanding the key factors determining the global pattern of crop yield sensitivity to drought is limited. Here, we investigate a wide range of physical and socioeconomic factors that may determine crop-drought vulnerability in terms of yield sensitivity to drought based on the Standardized Precipitation Index at 0.5° resolution from 1981 to 2016 using machine learning approaches. The results indicate that the spatial variations of the crop-drought sensitivity were mainly explained by environmental factors (i.e., annual precipitation, soil water-holding capacity, soil acidity, annual potential evapotranspiration) and crop management factors (i.e., fertilizer rate, growing season). Several factors might have a positive effect in mitigating crop-drought vulnerability, such as annual precipitation, soil water holding capacity, and fertilizer rate. This study quantitatively assesses the possible effect of various determinants which might control crop vulnerability to drought. This understanding may provide insights for further studies addressing better crop vulnerability measures under future drought stress.

Vapour pressure deficit determines critical thresholds for global coffee production under climate change

Our understanding of the impact of climate change on global coffee production is largely based on studies focusing on temperature and precipitation, but other climate indicators could trigger critical threshold changes in productivity. Here, using generalized additive models and threshold regression, we investigate temperature, precipitation, soil moisture and vapour pressure deficit (VPD) effects on global Arabica coffee productivity. We show that VPD during fruit development is a key indicator of global coffee productivity, with yield declining rapidly above 0.82 kPa. The risk of exceeding this threshold rises sharply for most countries we assess, if global warming exceeds 2 °C. At 2.9 °C, countries making up 90% of global supply are more likely than not to exceed the VPD threshold. The inclusion of VPD and the identification of thresholds appear critical for understanding climate change impacts on coffee and for the design of adaptation strategies.

Natural variations of ZmSRO1d modulate the trade-off between drought resistance and yield by affecting ZmRBOHC-mediated stomatal ROS production in maize

While crop yields have historically increased, drought resistance has become a major concern in the context of global climate change. The trade-off between crop yield and drought resistance is a common phenomenon; however, the underlying molecular modulators remain undetermined. Through genome-wide association study, we revealed that three non-synonymous variants in a drought-resistant allele of ZmSRO1d-R resulted in plasma membrane localization and enhanced mono-ADP-ribosyltransferase activity of ZmSRO1d toward ZmRBOHC, which increased reactive oxygen species (ROS) levels in guard cells and promoted stomatal closure. ZmSRO1d-R enhanced plant drought resilience and protected grain yields under drought conditions, but it led to yield drag under favorable conditions. In contrast, loss-of-function mutants of ZmRBOHC showed remarkably increased yields under well-watered conditions, whereas they showed compromised drought resistance. Interestingly, by analyzing 189 teosinte accessions, we found that the ZmSRO1d-R allele was present in teosinte but was selected against during maize domestication and modern breeding. Collectively, our work suggests that the allele frequency reduction of ZmSRO1d-R in breeding programs may have compromised maize drought resistance while increased yields. Therefore, introduction of the ZmSRO1d-R allele into modern maize cultivars would contribute to food security under drought stress caused by global climate change.

Building social resilience in North Korea can mitigate the impacts of climate change on food security

Adaptation based on social resilience is proposed as an effective measure to mitigate hunger and avoid food shocks caused by climate change. But these have not been investigated comprehensively in climate-sensitive regions. North Korea (NK) and its neighbours, South Korea and China, represent three economic levels that provide us with examples for examining climatic risk and quantifying the contribution of social resilience to rice production. Here our data-driven estimates show that climatic factors determined rice biomass changes in NK from 2000 to 2017, and climate extremes triggered reductions in production in 2000 and 2007. If no action is taken, NK will face a higher climatic risk (with continuous high-temperature heatwaves and precipitation extremes) by the 2080s under a high-emissions scenario, when rice biomass and production are expected to decrease by 20.2% and 14.4%, respectively, thereby potentially increasing hunger in NK. Social resilience (agricultural inputs and population development for South Korea; resource use for China) mitigated climate shocks in the past 20 years (2000-2019), even transforming adverse effects into benefits. However, this effect was not significant in NK. Moreover, the contribution of social resilience to food production in the undeveloped region (15.2%) was far below the contribution observed in the developed and developing regions (83.0% and 86.1%, respectively). These findings highlight the importance of social resilience to mitigate the adverse effects of climate change on food security and human hunger and provide necessary quantitative information.

Physiological adaptive traits are a potential allele reservoir for maize genetic progress under challenging conditions

Combined phenomic and genomic approaches are required to evaluate the margin of progress of breeding strategies. Here, we analyze 65 years of genetic progress in maize yield, which was similar (101 kg ha^-1 year^-1) across most frequent environmental scenarios in the European growing area. Yield gains were linked to physiologically simple traits (plant phenology and architecture) which indirectly affected reproductive development and light interception in all studied environments, marked by significant genomic signatures of selection. Conversely, studied physiological processes involved in stress adaptation remained phenotypically unchanged (e.g. stomatal conductance and growth sensitivity to drought) and showed no signatures of selection. By selecting for yield, breeders indirectly selected traits with stable effects on yield, but not physiological traits whose effects on yield can be positive or negative depending on environmental conditions. Because yield stability under climate change is desirable, novel breeding strategies may be needed for exploiting alleles governing physiological adaptive traits.

Stronger temperature-moisture couplings exacerbate the impact of climate warming on global crop yields

Rising air temperatures are a leading risk to global crop production. Recent research has emphasized the critical role of moisture availability in regulating crop responses to heat and the importance of temperature-moisture couplings in driving concurrent heat and drought. Here, we demonstrate that the heat sensitivity of key global crops depends on the local strength of couplings between temperature and moisture in the climate system. Over 1970-2013, maize and soy yields dropped more during hotter growing seasons in places where decreased precipitation and evapotranspiration more strongly accompanied higher temperatures, suggestive of compound heat-drought impacts on crops. On the basis of this historical pattern and a suite of climate model projections, we show that changes in temperature-moisture couplings in response to warming could enhance the heat sensitivity of these crops as temperatures rise, worsening the impact of warming by -5% (-17 to 11% across climate models) on global average. However, these changes will benefit crops where couplings weaken, including much of Asia, and projected impacts are highly uncertain in some regions. Our results demonstrate that climate change will impact crops not only through warming but also through changing drivers of compound heat-moisture stresses, which may alter the sensitivity of crop yields to heat as warming proceeds. Robust adaptation of cropping systems will need to consider this underappreciated risk to food production from climate change.

Reproductive resilience but not root architecture underpins yield improvement under drought in maize

Because plants capture water and nutrients through roots, it was proposed that changes in root systems architecture (RSA) might underpin the 3-fold increase in maize (Zea mays L.) grain yield over the last century. Here we show that both RSA and yield have changed with decades of maize breeding, but not the crop water uptake. Results from X-ray phenotyping in controlled environments showed that single cross (SX) hybrids have smaller root systems than double cross (DX) hybrids for root diameters between 2465 µm and 181µm (P<0.05). Soil water extraction measured under field conditions ranged between 2.6 mm d-1 and 2.9 mm d-1 but were not significantly different between SX and DX hybrids. Yield and yield components were higher for SX than DX hybrids across densities and irrigation (P<0.001). Taken together, the results suggest that changes in RSA were not the cause of increased water uptake but an adaptation to high-density stands used in modern agriculture. This adaptation may have contributed to shift in resource allocation to the ear and indirectly improved reproductive resilience. Advances in root physiology and phenotyping can create opportunities to maintain long-term genetic gain in maize, but a shift from ideotype to crop and production system thinking will be required.

Maladaptation of U.S. corn and soybeans to a changing climate

We quantify long-run adaptation of U.S. corn and soybean yields to changes in temperature and precipitation over 1951-2017. Results show that although the two crops became more heat- and drought-tolerant, their productivity under normal temperature and precipitation conditions decreased. Over 1951-2017, heat- and drought-tolerance increased corn and soybean yields by 33% and 20%, whereas maladaptation to normal conditions reduced yields by 41% and 87%, respectively, with large spatial variations in effects. Changes in climate are projected to reduce average corn and soybean yields by 39-68% and 86-92%, respectively, by 2050 relative to 2013-2017 depending on the warming scenario. After incorporating estimated effects of climate-neutral technological advances, the net change in yield ranges from (-)13 to 62% for corn and (-)57 to (-)26% for soybeans in 2050 relative to 2013-2017. Our analysis uncovers the inherent trade-offs and limitations of existing approaches to crop adaptation.

Narrow and Brittle or Broad and Nimble? Comparing Adaptive Capacity in Simplifying and Diversifying Farming Systems

Humanity faces a triple threat of climate change, biodiversity loss, and global food insecurity. In response, increasing the general adaptive capacity of farming systems is essential. We identify two divergent strategies for building adaptive capacity.Simplifyingprocesses seek to narrowly maximize production by shifting the basis of agricultural production toward centralized control of socially and ecologically homogenized systems.Diversifyingprocesses cultivate social-ecological complexity in order to provide multiple ecosystem services, maintain management flexibility, and promote coordinated adaptation across levels. Through five primarily United States focused cases of distinct agricultural challenges—foodborne pathogens, drought, marginal lands, labor availability, and land access and tenure—we compare simplifying and diversifying responses to assess how these pathways differentially enhance or degrade the adaptive capacity of farming systems in the context of the triple threat. These cases show that diversifying processes can weave a form of broad and nimble adaptive capacity that is fundamentally distinct from the narrow and brittle adaptive capacity produced through simplification. We find that while there are structural limitations and tradeoffs to diversifying processes, adaptive capacity can be facilitated by empowering people and enhancing ecosystem functionality to proactively distribute resources and knowledge where needed and to nimbly respond to changing circumstances. Our cases suggest that, in order to garner the most adaptive benefits from diversification, farming systems should balance the pursuit of multiple goals, which in turn requires an inclusive process for active dialogue and negotiation among diverse perspectives. Instead of locking farming systems into pernicious cycles that reproduce social and ecological externalities, diversification processes can enable nimble responses to a broad spectrum of possible stressors and shocks, while also promoting social equity and ecological sustainability.