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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., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024 Elsevier B.V. All rights reserved.)

Optimizing crop distribution stands as a pivotal approach to climate change adaption, enhancing crop production sustainability, and has been recognized for its immense potential in ensuring food security while minimizing environmental impacts. Here, we developed a climate-adaptive framework to optimize the distribution of staple crops (i.e., wheat, maize, and rice) to meet the multi-dimensional needs of crop production in China. The framework considers the feasibility of the multiple cropping systems (harvesting more than once on a cropland a year) and adopts a multi-dimensional approach, incorporating goals related to crop production, water consumption, and greenhouse gas (GHG) emissions. By optimizing, the total irrigated area of three crops would decrease by 7.7 % accompanied by a substantial 69.8 % increase in rain-fed areas compared to the baseline in 2010. This optimized strategy resulted in a notable 10.0 % reduction in total GHG emissions and a 13.1 % decrease in irrigation water consumption while maintaining consistent crop production levels. In 2030, maintaining the existing crop distribution and relying solely on yield growth would lead to a significant maize production shortfall of 27.0 %, highlighting a looming challenge. To address this concern, strategic adjustments were made by reducing irrigated areas for wheat, rice, and maize by 2.3 %, 12.8 %, and 6.1 %, respectively, while simultaneously augmenting rain-fed areas for wheat and maize by 120.2 % and 55.9 %, respectively. These modifications ensure that production demands for all three crops are met, while yielding a 6.9 % reduction in GHG emissions and a 15.1 % reduction in irrigation water consumption. This optimization strategy offers a promising solution to alleviate severe water scarcity issues and secure a sustainable agricultural future, effectively adapting to evolving crop production demands in China., Competing Interests: Declaration of competing interest The authors declare that they have no known competing financial interests or personal relationships that could have appeared to influence the work reported in this paper., (Copyright © 2024. Published by Elsevier B.V.)

Crop simulation models can be used to estimate impact of current and future climates on crop yields and food security, but require long-term historical daily weather data to obtain robust simulations. In many regions where crops are grown, daily weather data are not available. Alternatively, gridded weather databases (GWD) with complete terrestrial coverage are available, typically derived from: (i) global circulation computer models; (ii) interpolated weather station data; or (iii) remotely sensed surface data from satellites. The present study's objective is to evaluate capacity of GWDs to simulate crop yield potential (Yp) or water-limited yield potential (Yw), which can serve as benchmarks to assess impact of climate change scenarios on crop productivity and land use change. Three GWDs (CRU, NCEP/DOE, and NASA POWER data) were evaluated for their ability to simulate Yp and Yw of rice in China, USA maize, and wheat in Germany. Simulations of Yp and Yw based on recorded daily data from well-maintained weather stations were taken as the control weather data (CWD). Agreement between simulations of Yp or Yw based on CWD and those based on GWD was poor with the latter having strong bias and large root mean square errors (RMSEs) that were 26-72% of absolute mean yield across locations and years. In contrast, simulated Yp or Yw using observed daily weather data from stations in the NOAA database combined with solar radiation from the NASA-POWER database were in much better agreement with Yp and Yw simulated with CWD (i.e. little bias and an RMSE of 12-19% of the absolute mean). We conclude that results from studies that rely on GWD to simulate agricultural productivity in current and future climates are highly uncertain. An alternative approach would impose a climate scenario on location-specific observed daily weather databases combined with an appropriate upscaling method., (© 2013 John Wiley & Sons Ltd.)

Under the 1.5 °C and 2.0 °C warming scenarios, few studies have explored the different influences of CO2, temperature, and precipitation on wheat yield in China. Hence, we analyzed the different influences of above factors on wheat yield after analyzing the wheat yield change. Results show that (1) the wheat yield of China would increase under the two warming scenarios. The spring wheat yield of the Northeast Spring Wheat Region (DB_S) and the Northwest Spring Wheat Region (XB_S) would increase more than that in the other two spring wheat-planting subregions. The winter wheat yield of the Southwest Winter Wheat Region (XN_W) and Middle and Lower Yangtze Winter Wheat Region (CJ_W) would increase more significantly compared with that in the other three winter wheat-planting subregions. (2) CO2 fertilization was identified as the main factor leading to a wheat yield increase, with an estimated increase of 12–18% under the 1.5 °C warming scenario and 18–21% under the 2.0 °C warming scenario. (3) Without considering CO2 fertilization, compared with precipitation, temperature dominated the spatial patterns of the wheat yield responses to climate change. Temperature influence on wheat yield was mainly reflected in the amplitudes of yield increase, while precipitation mainly affected the proportion of yield-increasing area. For wheat-planting regions with less precipitation, such as the North Spring Wheat Region (BB_S) and the Huang-Huai Winter Wheat Region (HH_W), the wheat yield increase caused by precipitation was usually more pronounced. Our findings would help inform policy decisions related to wheat production in China to better cope with future climate warming. [ABSTRACT FROM AUTHOR]

Nitrogen fertilizer is one of the essential nutrients for wheat growth and development, and it plays an important role in increasing and stabilizing wheat yield. Future climate change will affect wheat growth, development, and yield, since climate change will also alter nitrogen cycles in farmland. Therefore, further research is needed to understand the response of wheat yield and nitrogen losses to climate change during cultivation. In this study, we investigate the wheat-producing region in the middle and lower reaches of the Yangtze River in China, one of the leading wheat-producing areas, by employing a random forest model using wheat yield records from agricultural meteorological observation stations and spatial data on wheat yield, nitrogen application rate, and nitrogen losses. The model predicts winter wheat yield and nitrogen losses in the middle and lower reaches of the Yangtze River based on CMIP6 meteorological data and related environmental variables, under SSP126 and SSP585 emission scenarios. The results show that future climate change (temperature and precipitation changes) will decrease winter wheat yield by 2~4% and reduce total nitrogen losses by 0~5%, but in other areas, the total nitrogen losses will increase by 0~5% and the N leaching losses per unit of yield will increase by 0~10%. The results of this study can provide a theoretical basis and reference for optimizing nitrogen application rates, increasing yield, and reducing nitrogen losses in wheat cultivation under climate change conditions. [ABSTRACT FROM AUTHOR]

This study aimed to assess the impact of climate change on spring wheat production and to provide more accurate projections by directly investigating the effect of climate change on crop development and yield. Based on ground observation data from 1981 (1986 Dingxi) to 2020 in four case areas in northwest China, and the relationships among spring wheat growth, yield, and climate factors were analyzed and determined. The results showed that the extreme arid (Dunhuang) and semiarid regions (Dingxi) tend to be warmer and wetter, whereas arid regions (Wuwei) and semihumid regions (Linxia) tend to be warmer and drier. Correlation analysis indicated that yield of spring wheat in Wuwei, Dingxi, and Linxia Stations increased significantly. The decrease in the number of days (≥30 °C) during the growth period at Wuwei resulted in a significant yield increase in the past 40 years. At Dingxi, yield increased over the last 35 years due to the significant increases in precipitation during growth, the number of grains per panicle, and thousand‐grain weight, and the decrease in infertile spikelets. Further increase in global temperature and changes in future precipitation patterns will likely affect spring wheat production in northwest China. Core Ideas: The relationship between climate factors and growth and yield of spring wheat are explored.Dominant climatic factors affecting the growth of spring wheat in different climatic regions of northwest China are studied.Regional differences in spring wheat growth and yield in response to climate change are assessed.Climate change trends in different climatic regions over time are examined.Impact of climate change on crop development and yield are assessed. [ABSTRACT FROM AUTHOR]

Abnormal climate changes have resulted in over-precipitation in many regions. The occurrence and contamination levels of mycotoxins in crops and cereals have been elevated largely. From 2017 to 2019, we did investigation targeting 15 mycotoxins shown in the wheat samples collected from Shandong, a region suffering over-precipitation in China. We found that deoxynivalenol (DON) was the dominant mycotoxin contaminating wheats, with detection rates 304/340 in 2017 (89.41%), 303/330 in 2018 (91.82%), and 303/340 in 2019 (89.12%). The ranges of DON levels were < 4 to 580 μg/kg in 2017, < 4 to 3070 μg/kg in 2018, and < 4 to 1540 μg/kg in 2019. The exposure levels were highly correlated with local precipitation. Male exposure levels were generally higher than female's, with significant difference found in 2017 (1.89-fold, p = 0.023). Rural exposure levels were higher than that of cities but not statistically significant (1.41-fold, p = 0.13). Estimated daily intake (EDI) and margin of exposure (MoE) approaches revealed that 8 prefecture cities have probabilistically extra adverse health effects (vomiting or diarrhea) cases > 100 patients in 100,000 residents attributable to DON exposure. As a prominent wheat-growing area, Dezhou city reached ~ 300/100,000 extra cases while being considered as a major regional contributor to DON contamination. Our study suggests that more effort should be given to the prevention and control of DON contamination in major wheat-growing areas, particularly during heavy precipitation year. The mechanistic association between DON and chronic intestinal disorder/diseases should be further investigated. [ABSTRACT FROM AUTHOR]

Climate change and water shortage have brought great challenges to agricultural production in the North China Plain, and it's crucial to find the suitable method to address these challenges. Climate model projections were used to drive the Agro-Hydrological & chemical and Crop systems simulator (AHC) that considering the impact of irrigation on field microclimate. Yield, evapotranspiration (ET), water productivity (WP), and the impact on groundwater level of 6 wheat varieties under 6 sprinkler irrigation scheduling (IS1: no irrigation; IS6: full irrigation without water deficit; IS2–5: deficit irrigation with 0.2, 0.4, 0.6, and 0.8 times water of IS6 after wheat greening) were estimated in Xingtai under current and two shared social economic paths scenarios (SSP2–4.5 and SSP5–8.5). The optimal combination of irrigation and variety (OC) was selected by Topsis method. The results indicated that AHC had a high accuracy in simulating the growth of six varieties (R2>0.80, NRMSE<20 %) after parameter optimization. The temperature, solar radiation, and precipitation in 2021–2100 increased by 0.1–2.8 °C, 0.7–1.7 MJ m−2 d−1, and 5.2–28.8 mm under SSP2–4.5 and 0.2–4.8 °C, 0.9–1.2 MJ m−2 d−1, and 4.7–73.1 mm under SSP5–8.5 than current climate. As the irrigation amount increased, the simulated yield and ET increased, while WP first increased and then decreased. Due to climate change, irrigation failed to improve the wheat potential yield after 2080 under SSP2–4.5 and 2060 under SSP5–8.5. The OC implied that "Shimai26" and IS5 and IS4 in the future were the best strategy. It saved water by 13–23 % with similar yield than full irrigation. Moreover, the inhibitory effect of OC on annual groundwater level drawdown was stronger than other irrigation by 0.04–0.24 m. These findings were beneficial for mitigating climate impacts on grain yields in water scarce areas. ● Shimai26 was the best wheat variety under climate change. ● 0.8 and 0.6 times full irrigation after wheat regreening were the best in future. ● Irrigation couldn't increase wheat potential yield at the end of 21st century. ● Best irrigation saved 13–23 % water with similar yield than full irrigation. ● Best irrigation had the greatest inhibitory effect on groundwater level decline. [ABSTRACT FROM AUTHOR]

Global surface temperature is increasing significantly under climate change with increasingly uneven distribution of precipitation, which has been making an important impact on the sustainable development of the dryland agriculture in semi-arid regions. The Inner Mongolia Autonomous Region (IMAR) has the largest area ratio of semi-arid regions in China, and spring wheat is one of its major grain crops, and the negative impacts of climate change pose a serious threat to its production. In order to reduce this threat, we assessed the impact thresholds and risks posed by the main climatic factors to spring-wheat production, and put forward quantitative adaptive countermeasures. The results showed that, from 1961 to 2012, the appropriate impact thresholds of average temperature, precipitation, fertilization level, and water supply level were 15.6 °C, 333 mm, 319.5 kg/ha, and 743.7 mm, respectively. Compared with the average values in 1996–2012, the maximum fertilization level and water supply level could be increased by 162.2 kg/ha and 406.5 mm, respectively, to improve the adaptive yield of spring wheat. The risks of adverse impacts of temperature rise, precipitation decrease, and their combined effect on spring-wheat production were found to be 11.1%, 9.3%, and 10.3%, respectively. The whole IMAR showed a high risk of adverse impacts of temperature rise and the combined action of temperature rise and precipitation decrease on spring-wheat production. In particular, the spring-wheat production in the northeastern, eastern, and central areas were found to be at the highest risk to the impacts of climate change. Based on the determined appropriate thresholds of fertilization level and water supply level, it was determined that in the northeastern area, the maximum fertilization level and water supply level could be increased by 229.9 kg/ha and 441.4 mm, respectively, to increase the adaptive yield of spring wheat. In the eastern area, the two factors could be increased by 142.2 kg/ha and 464.3 mm, respectively. In the central area, they could be increased by 242.2 kg/ha and 513.7 mm, respectively. In the southwestern area, they could be increased by 41.4 kg/ha and 201.7 mm, respectively. [ABSTRACT FROM AUTHOR]

Temperature has a large influence on insect abundances, thus under climate change, identifying major drivers affecting pest insect populations is critical to world food security and agricultural ecosystem health. Here, we conducted a meta-analysis with data obtained from 120 studies across China and Europe from 1970 to 2017 to reveal how climate and agricultural practices affect populations of wheat aphids. Here we showed that aphid loads on wheat had distinct patterns between these two regions, with a significant increase in China but a decrease in Europe over this time period. Although temperature increased over this period in both regions, we found no evidence showing climate warming affected aphid loads. Rather, differences in pesticide use, fertilization, land use, and natural enemies between China and Europe may be key factors accounting for differences in aphid pest populations. These long-term data suggest that agricultural practices impact wheat aphid loads more than climate warming. A meta-analysis of wheat aphid populations obtained from 120 studies from 1970 to 2017 reveals that pest loads increased in China but decreased in Europe and suggests this is due to differences in pesticide use, fertilization, land use, and natural enemies. [ABSTRACT FROM AUTHOR]

Agricultural system models provide an effective tool for forecasting crop productivity and nutrient budgets under future climate change. This study investigates the potential impacts of climate change on crop failure, grain yield and soil organic carbon (SOC) for both winter wheat (Triticum aestivum L.) and maize (Zea mays L.) in northern China, using the SPACSYS model. The model was calibrated and validated with datasets from 20-year long-term experiments (1985–2004) for the Loess plateau, and then used to forecast production (2020–2049) under six sharing social-economic pathway climate scenarios for both wheat and maize crops with irrigation. Results suggested that warmer climatic scenarios might be favourable for reducing the crop failure rate and increasing the grain yield for winter wheat, while the same climatic scenarios were unfavourable for maize production in the region. Furthermore, future SOC stocks in the topsoil layer (0–30 cm) could increase but in the subsoil layer (30–100 cm) could decrease, regardless of the chosen crop. [ABSTRACT FROM AUTHOR]

Fusarium asiaticum is a predominant fungal pathogen causing Fusarium Head Blight (FHB) in wheat and barley in China and is associated with approximately £201 million in annual losses due to grains contaminated with mycotoxins. F. asiaticum produces deoxynivalenol and zearalenone whose maximum limits in cereals and cereals-derived products have been established in different countries including the EU. Few studies are available on the ecophysiological behaviour of this fungal pathogen, but nothing is known about the impact of projected climate change scenarios on its growth and mycotoxin production. Therefore, this study aimed to examine the interacting effect of i) current and increased temperature (25 vs 30 °C), ii) drought stress variation (0.98 vs 0.95 water activity; a w) and iii) existing and predicted CO 2 concentrations (400 vs 1000 ppm) on fungal growth and mycotoxin production (type B trichothecenes and zearalenone) by three F. asiaticum strains (CH024b, 82, 0982) on a wheat-based matrix after 10 days of incubation. The results showed that, when exposed to increased CO 2 concentration (1000 ppm) there was a significant reduction of fungal growth compared to current concentration (400 ppm) both at 25 and 30 °C, especially at 0.95 a w. The multi-mycotoxin analysis performed by LC-MS/MS qTRAP showed a significant increase of deoxynivalenol and 15-acetyldeoxynivalenol production when the CH024b strain was exposed to elevated CO 2 compared to current CO 2 levels. Zearalenone production by the strain 0982 was significantly stimulated by mild water stress (0.95 a w) and increased CO 2 concentration (1000 ppm) regardless of the temperature. Such results highlight that intraspecies variability exist among F. asiaticum strains with some mycotoxins likely to exceed current EU legislative limits under prospected climate change conditions. • Ecophysiological behaviour of F. asiaticum grown on a wheat-based matrix • Fungal growth decreased at higher CO 2 concentrations especially at 0.95 a w • Intraspecies variability in terms of mycotoxins production • Higher DON and 15-ADON production at 1000 ppm by CH024b strain • Increased ZEN concentration at 0.95 a w × 1000 ppm by 0982 strain [ABSTRACT FROM AUTHOR]

Wheat is one of the most common and productive crops in the world, and the growth and production of wheat are sensitive to climate change. Climate change affects wheat phenology by influencing sowing/maturity dates and the duration of growing stages, and ultimately affects the grain yield. Reliable prediction of changes in wheat yield is significant for maintaining global food security. However, studies addressing the potential impact of crop phenology changes on grain yield are rarely reported, which is a big challenge. Using the CERES-Wheat model and first-order differential equation models, we quantified the impact of future climate change on wheat phenology and grain yield for two periods (P1: 2011-2040; P2: 2041-2070) under three representative concentration pathways (RCP2.6, RCP4.5, RCP8.5) in China's twomain wheat-growing areas (Northwest SpringWheat-Growing Area(NWSWA) and Huang-Huai-Hai Winter Wheat-Growing Area (HHWWA)); the baseline period was 1981-2010. Accumulated thermal time during thewhole growing period (WGP) tends to significantly increase in NWSWA and HHWWA under all RCPs and periods. This rising accumulated thermal time will reduce the time to anthesis and maturity and shorten the vegetative growing period (VGP), reproductive growing period (RGP), and theWGP. In P2, spring wheat grain yield is projected to diminish by a regional average of 2.67% for RCP2.6, 4.07% for RCP4.5, and 5.66% for RCP8.5, which is dominated by the lower accumulated solar radiation during the VGP in NWSWA. Additionally, for the winter wheat grain yield in HHWWA in P2, its grain yield reduction is projected to decline by 4.8% (RCP2.6), 7.9% (RCP4.5), and 9.8% (RCP8.5), which is caused by increasing accumulated thermal time in the VGP. These results suggest that breeding high-temperature-tolerant varieties with high calorie requirements is an adaptive strategy to mitigate the negative impact of climate change on wheat yield in the study areas. [ABSTRACT FROM AUTHOR]

BACKGROUND Adaptive crop management is critical to food security in a changing climate, but the respective contributions of climate change and crop management to yields remain unclear. Thus, we distinguished and quantified the respective contribution of climate change and crop management on wheat yield between 1981 and 2018 in China, using first‐difference multivariate regression model. RESULTS: Wheat production in China has increased over the past four decades. Under the sole impact of climate change, wheat yield generally decreased (−5.45 to +1.09% decade−1). Crop management increased the wheat yield from 7.11 to 19.94% decade−1. Sensitivities of wheat yield to climatic variables (average temperature, accumulated sunshine hours, accumulated precipitation) were spatially heterogeneous; notably, in spring‐wheat planting areas, wheat yield was more susceptible to the negative impact of warming. In terms of relative contribution, the contribution of climate change to spring wheat yield was −24.08% to −5.41%, and the contribution to winter wheat was −4.98% to +34.69%. Crop management had a positive contribution to all wheat‐growing areas (65.31–96.84%). CONCLUSION: Crop management had a greater effect on wheat yield than climate change did. Among the three climatic variables investigated, average temperature had the dominant effect on wheat yield change; the impact of precipitation was minimal but mostly negative. The results provide insight regarding the contribution of climate change and crop management to wheat yield; adaptation measures may be more effective in planting areas where crop management contributes more, which will help stakeholders optimize crop management and adaptation strategies. © 2020 Society of Chemical Industry [ABSTRACT FROM AUTHOR]

The responses of wheat yield to large-scale atmospheric circulation indices (LACI) were explored in Henan province, north China. With using the annual series of climate-driven yield index (CDYI) extracted from winter wheat yield collected in 17 cites and the monthly series of 15 types of LACI during 1988–2017, the main findings were as follows: (1) this province could be divided into four sub-regions (central-east, west, north, and south Henan) with different CDYI variations; (2) the CDYI in central-east, west, south Henan was dominated by a 3-year oscillation, while the CDYI in north Henan presented a notable 7.5-year oscillation; (3) among the four sub-regions, central-east Henan had the most significant CDYI-LACI relationship, and the higher Nino 1 + 2 in December were a key yield reduction signal; (4) during 2008–2017, the stronger increase of Nino1 + 2_in December had caused the yield decrease in central Henan by 6.58%. In summary, linking wheat yield to LACI anomalies should be instrumental in alleviating the adverse effects of climate change on wheat production. [ABSTRACT FROM AUTHOR]

Understanding the change of water requirement (ET) for crop production under climate change can provide scientific support for the management of agricultural water resources. The objective behind this study was to analyze spatiotemporal distribution characteristics of ET, effective rainfall (Pe), irrigation requirement (IR) and aridity index (AI) of winter wheat, and evaluate the driving force of ET changes as a result of the variation of climatic factors. Daily meteorological data from 18 meteorological stations from 1969 to 2019 distributed throughout Shandong Province, China were collected. Five climatic variables including maximum daily temperature (Tmax), minimum daily temperature (Tmin), relative humidity (RH), wind speed (WS), and sunlight hours (SH), were selected to identify their contribution to the variability of ET. Results indicated that (1) ET distribution differed significantly both in temporal and spatial scale on a general, and decreased -14.11-3.88 mm decade-1 . (2) Tmax was the most influential climatic variable related to ET variability with sensitivity coefficient of 0.36, followed by RH (-0.34), SH (0.13), WS (0.11) and Tmin (-0.07). (3) Declines of WS and SD were indicated by the decrease of ET while the increase of Tmax and the decrease of RH contributed to enhancing ET. [ABSTRACT FROM AUTHOR]

Against the background of rising international disputes, numerous countries have placed great importance on ensuring self-sufficiency of crop production. Weather, as a notably variable factor than others, has a considerable influence on agricultural productivity, production variability and, in turn, on food security. Our primary objectives were to: (1) evaluate the relative importance of climate, soil, and field management factors on wheat production across major wheat-producing regions in China, (2) explore the direct and indirect ways of the effect of climate on wheat production at different phenological stages, and (3) forecast future trends in wheat production levels and stability based on historical insights. Initially, we analyzed the spatiotemporal variations in production and phenology across six subregions using linear regression. This analysis was based on data from 124 agro-meteorological stations, spanning the period from 1999 to 2013. Subsequently, we used the Random Forest algorithm to discern the relative importance of climate, soil, and field management on wheat production. Moreover, we utilized a structural equation model to elucidate the direct and indirect pathways through which climatic factors affected production during different phenological stages, incorporating the first difference method. Finally, with a Support Vector Machine algorithm, the production level and stability under RCP4.5 and RCP8.5 were predicted using 33 Global Climate Models. Over the 1999–2013 period, among 124 wheat stations, 33 stations showed a significant (P < 0.05) increase in wheat production, while 53 exhibited an insignificant (P > 0.05) increase. Conversely, 4 stations exhibited a significant (P < 0.05) decrease, and 34 showed an insignificant (P > 0.05) decrease in wheat production. Climate, soil, and field management all played significant roles in wheat production in each of the six subregions, with relative importance ranging from 19.0% to 44.2%, 30.4% to 35.9%, and 25.4% to 45.1%, respectively. Climate factors, predominantly temperature-related, influenced wheat production by altering key growth period lengths, while other factors directly impacted production. Finally, our findings suggested that the wheat production level in China is expected to increase in the future, while its production stability could decrease. These findings hold the potential to guide policymakers in different regions towards ensuring food security and enhancing agricultural system resilience in the context of climate change. [Display omitted] • The relative importance of climate, soil, and field management were analyzed. • Direct and indirect impact pathways for climate-affected production were explained. • Wheat production level will increase in the future, while stability may decrease. [ABSTRACT FROM AUTHOR]

The evaluation of ancient crop production and its response to climate change is key to exploring the ancient demographic and social changes. Wheat is currently the third most widely cultivated crop worldwide and was a major component across of the agricultural systems of the ancient Eurasia. In this study, the Δ13C values of 116 charred wheat grains from 28 archaeological sites, with direct AMS 14C dating of 3952 ± 66 to 389 ± 73 cal yr BP, across northern China are reported. The result shows that the Δ13C values estimated wheat yields ranged from 0.5 to 2.5 Mg ha−1, during the past 4000 years. The water supply and grain yield of wheat cultivation is the highest in China during the Bronze Age; however, the water supply and yield were significantly affected by climate fluctuation in the middle-late Holocene. No significant long-term trend of increasing wheat yield is observed over this interval, but a correlation between Δ13C values estimated wheat yield and cyclical climate changes can be noted. [ABSTRACT FROM AUTHOR]

Future extreme climate events will become more intense and frequent with global warming, which is a great threat to wheat productivity in the North China Plain (NCP). Projecting future changes in extreme climate events is an important prerequisite for exploring crop adaptation measures to climate variation. In this study, we calculated 11 extreme climate indices at different wheat growth stages that are sensitive to wheat yield across NCP. The future climate projections were sourced from thirteen Global Climate Models (GCMs) from the Coupled Model Inter‐comparison Project phase 6 (CMIP6) under two emission scenarios of future societal development pathway (SSP) 245 and SSP585. Daily climate data of thirteen GCMs were generated by using a statistically downscaled method. Two multi‐model ensemble methods, that is, arithmetic mean and independence weighted mean (IWM), were used to assess the performance of thirteen GCMs in reproducing historical changes of extreme climate indices. The IWM ensemble results could better reproduce historical changes of extreme climate indices than multi‐model arithmetic mean and any individual GCM. We found that the frequency and intensity of heat extremes were projected to increase over the 21st century for both scenarios, but those of cold extremes will decrease. Heat stress intensity (HSI) increases around 1.0°C for SSP245 scenario and 1.6°C for SSP585 scenario by the end of the 21st century. There was no significant change in extreme precipitation indices across the NCP, but the changes of extreme precipitation had strong spatial heterogeneity. Overall, wheat production in the NCP might have a higher frequency of exposure to extreme climate, especially under heat stress. Therefore, adopting effective adaptation measures to mitigate heat stress for wheat is the first priority in the NCP. [ABSTRACT FROM AUTHOR]

This paper reinvestigated the climate-crop yield relationship with the statistical model at crops' growing stage scale. Compared to previous studies, our model introduced monthly climate variables in the production function of crops, which enables separating the yield changes induced by climate change and those caused by inputs variation and technique progress, as well as examining different climate effects during each growing stage of crops. By applying the fixed effect regression model with province-level panel data of crop yields, agricultural inputs, and the monthly climate variables of temperature and precipitation from 1985 to 2015, we found that the effects of temperature generally are negative and those of precipitation generally are positive, but they vary among different growth stages for each crop. Specifically, GDDs (i.e., growing degree days) have negative effects on spring maize's yield except for the sowing and ripening stages; the effects of precipitation are negative in September for summer maize. Precipitation in December and the next April is significantly harmful to the yield of winter wheat; while, for the spring wheat, GDDs have positive effects during April and May, and precipitation has negative effects during the ripening period. In addition, we computed climate-induced losses based on the climate-crop yield relationship, which demonstrated a strong tendency for increasing yield losses for all crops, with large interannual fluctuations. Comparatively, the long-term climate effects on yields of spring maize, summer maize, and spring wheat are more noticeable than those of winter wheat. [ABSTRACT FROM AUTHOR]

In agro‐ecosystems, fertilization practices must accomplish high and stable crop productivity, with maximum soil organic carbon (SOC) sequestration to address climate change and food security challenges. However, the impacts of these practices on SOC and crop yields are variable over the long‐term duration, and an improved understanding of the factors influencing SOC sequestration and sustainable productivity is still needed to provide evidence‐based management decisions. Therefore, we conducted a meta‐analysis to evaluate the impact of long‐term (≥10 years) application of different fertilizer management practices adapted across China on crop productivity, yield sustainability, and SOC sequestration. Results indicated that unbalanced mineral fertilizer (UMF), balanced mineral fertilizer (BMF), organic fertilizers (OF), combined unbalanced mineral and OF, and combined balanced mineral and organic fertilizers (BMOF) significantly enhanced the grain yield, and SOC sequestration compared with control (p <.05). For UMF, the increases in SOC and grain yields were least among fertilization practices. Comparing OF, BMF mostly produced more grain yields, but with a slight increase in C sequestration. Highest SOC sequestration rate of 0.43 Mg C ha−1 yr−1 was recorded in BMOF, among all the treatments. The data obtained indicated that SOC sequestration is highly time‐dependent. Irrespective of fertilization mode, SOC gradually increased and attained the peak of sequestration rate in the initial two decades rather than at later stages of fertilizer addition. The linear fitted model indicated that an increase in SOC sequestration benefits sustainable productivity. The available data indicate that crop yields can be improved by 143 kg ha−1 for rice (Oryza sativa), 255 kg ha−1 for maize (Zea mays), and 202 kg ha−1 for wheat (Triticum aestivum) with every 1 Mg ha−1 increase in SOC stock by fertilization in the root zone. In crux, BMOF can maintain and improve soil quality while producing high and stable crop yields. [ABSTRACT FROM AUTHOR]

How to plan crop planting under global warming is a key issue in the context of an emerging global food crisis. Although previous studies have utilized crop potential distribution for crop planting strategies, they overlooked the high and stable crop-yielding areas within the potential distribution zone, which hinders the optimal utilization of these areas. Taking China as a case, this study proposed a high and stable yield index based on crop potential yield using a hybrid model at site scale (i.e., establishing the relationship between the observed crop yield and the outputs of process-based LPJ-GUESS model as well as climate variables using the random forest method) and assessed planting suitability of China's main grain crops (i.e., maize, wheat, and rice) under future climate change using the index. According to the results, (1) the determination coefficients between observed and modeled yield in the hybrid models were 0.71, 0.49, and 0.66 for maize, wheat, and rice, respectively, suggesting that the hybrid model had an acceptable performance. Moreover, the hybrid models had much better performance than the LPJ-GUESS model in crop yield simulation at site scale. (2) Compared with the 2001–2020, future average potential yield of three crops in the actual cultivated land would decline in 2081–2100, where the declined areas for maize, wheat, and rice would account for 83.8–89.2 %, 68.2–70.2 %, and 74.2–80.9 % of cultivated land, respectively. (3) High yield and stable yield areas of each crop do not overlap completely spatially, indicating that establishment of the high and stable yield index for crop planting suitability measurement is necessary. Compared with the 2001–2020, the optimal suitability areas of each crop will decrease under future climate change, implying that future climate change will reduce and shift the high and stable yield area of each crop. (4) Spatial overlay between the actual distribution and the optimal suitability area of each crop demonstrates that the optimal suitability area of each crop has not and will not be occupied completely by actual crop planting, suggesting a large available area for the adjustment of future crop planting area. This work could facilitate spatial optimization of crop planting to adapt to future climate change in China. • A hybrid model was developed to estimate crop yield. • An index of high and stable yield for crop was established for crop planting. • Future climate will reduce potential yield and planting suitability of crops. • Optimal suitability area has not been completely occupied by actual crop planting. • Large space was detected for adjusting and newly developing crop planting. [ABSTRACT FROM AUTHOR]

Responses of wheat yield in different regions to separate and joint changes in mean temperature (T mean), precipitation (Prec), and solar radiation (Rad) are the foundation for sustainable development under climate change; however, these remain uncertain. Here, we quantified the response of wheat yield variation to changes in T mean , Prec, and Rad by building multiple regression models, de-trending analysis, and MK trend tests. Multi-site meteorological data was obtained from different wheat growing areas and corresponding wheat yield data from provinces. Our findings showed that the effects of different climatic elements on wheat yield are spatially heterogeneous by region, and the combined effects of climatic elements are higher than those of single elements. Climate change caused an increase of 1% and 4.52% in winter and winter-spring wheat areas, respectively, and a loss of 3.72% in spring wheat areas. In addition, the effect of single meteorological factors on wheat yield varied depending on their rate of change. Rad and Prec are the main drivers of wheat yield variability; in winter, spring and winter-spring wheat areas, Rad significantly impacted wheat yield by 0.89%, −1.18%, and 2.46%, respectively, and Prec caused changes of −0.18%, −1.54%, and 1.33%, respectively. Considering normal and extreme climate fluctuations, we found that the contribution of climate change to wheat yield changes in different wheat-growing regions reached 26.1%, 18.6%, and 16.7%, respectively. Our results indicate that the overall climatic conditions in the spring wheat region are moving in an unfavourable direction, while Prec variability has become the main limiting factor for wheat production in the current winter and winter-spring wheat regions. These comprehensive and detailed findings provide a reference for the development of more accurate adaptation strategies and management measures in different regions. Going forward, the results of this study can be better applied to the development of region-specific climate-smart agricultural practices and extended to other crops and regions to better understand the broader impacts of climate change on global food security. [Display omitted] • Spatial differences in crop yield responses to different climate drivers at large scales. • We quantified the effects of climate variation on wheat yield variability. • Uniquely illustrates spatial patterns in the relationship between climate variability and wheat yield variability. • Uncovering the main drivers of climate change impact on wheat yield in China. • Light-efficient varieties and effective irrigation may improve China's wheat yield. [ABSTRACT FROM AUTHOR]

• Wheat production in the NCP will benefit from warming and CO 2 fertilization. • Wheat growth cycle is expected to shorten under climate change. • Mulching and deficit irrigation practices can increase water use efficiency. • Variability in projections is higher under RCP 8.5 than under RCP 2.6. Climate change impacts on winter wheat yield and water-use were assessed with the AquaCrop model for different representative concentration pathway (RCP) scenarios (RCP 2.6, RCP 4.5, RCP 6.0 and RCP 8.5) and time slices (2040s, 2060s, 2080s) using ensemble projections from 10 general circulation models (GCM) for a site in the North China Plain. To test the role of crop and soil management practices under climate change, simulations with deficit irrigation (DI) and mulching were also performed. DI was defined as a practice where soil water content was restored to field capacity after depleting 150% of readily available water (RAW). The chosen mulching practice had a fixed capacity to reduce evaporation by 60%. Simulated outputs were compared with the baseline simulations (baseline period: 1984–2015). The results indicate that yield and water use efficiency (WUE) of wheat will increase under all RCP scenarios and time slices. Analysis revealed that winter wheat in the NCP would benefit from both CO 2 fertilization and warming. Warming will shorten the growing cycle but largely due to curbing of the overwintering period. Due to accelerated growth/development, flowering and maturity will be advanced compared to the baseline period. Warming will also ease the low-temperature stress on biomass production. The seasonal evapotranspiration will reduce mainly due to the shorter growing cycle and the CO 2 -induced reduction in transpiration. Increase in yield and WUE is expected even under DI, while mulching can further increase WUE. Projections using individual GCMs indicated that the variability in crop production would be higher for the high-end scenario (RCP 8.5) than for RCP 2.6. These findings imply that in general, wheat in the NCP is less vulnerable to climate change than in other parts of the world. In addition, the expected increase in the yield and WUE of wheat may positively affect current depletion rates of groundwater for irrigation; however, more work is needed to quantify this. In future, it will be possible to introduce short duration wheat and long duration maize (second crop in rotation) cultivars. [ABSTRACT FROM AUTHOR]

Prior to the introduction of wheat and barley from Central Asia during the Neolithic period, northern Chinese agricultural groups subsisted heavily on millet. Despite being the focus of many decades of intensive interest and research, the exact route(s), date(s), and mechanisms of the spread and adoption of wheat and barley into the existing well-established millet-based diet in northern China are still debated. As the majority of the important introduced crops are C3 plants, while the indigenous millet is C4, archaeologists can effectively identify the consumption of any introduced crops using stable carbon isotope analysis. Here we examine published stable isotope and dental caries data of human skeletal remains from 77 archaeological sites across northern and northwestern China. These sites date between 9000 to 1750 BP, encompassing the period from the beginning of agriculture to wheat’s emergence as a staple crop in northern China. The aim of this study is to evaluate the implications of the spread and adoption of these crops in ancient China. Detailed analysis of human bone collagen δ13C values reveals an almost concurrent shift from a C4-based to a mixed C3/ C4– based subsistence economy across all regions at around 4500–4000 BP. This coincided with a global climatic event, Holocene Event 3 at 4200 BP, suggesting that the sudden change in subsistence economy across northern and northwestern China was likely related to climate change. Moreover, the substantially increased prevalence of dental caries from pre–to post–4000 BP indicates an increase in the consumption of cariogenic cereals during the later period. The results from this study have significant implications for understanding how the adoption of a staple crop can be indicative of large-scale environmental and socio-political changes in a region. [ABSTRACT FROM AUTHOR]

Aims: This study evaluated the influence of cultivar number in wheat cultivar mixtures on aboveground biomass and grain yield across two years with different rainfall. Methods: Field experiments were conducted in the 2014–2015 (wetter-than-average) and 2015–2016 (drier-than-average) growing seasons in northern China. The study contained either one cultivar (16 × monoculture) or combinations of cultivar mixtures containing two (8 × mixture-2), four (8 × mixture-4), eight (8 × mixture-8) or 16 (1 × mixture-16) wheat cultivars. Results: In the wetter year (2014–2015), grain yield and aboveground biomass in the cultivar mixtures did not differ from the monoculture mean and had no relationship with the number of cultivars across monocultures or cultivar mixtures. However, in the drier year (2015–2016), wheat grain yield and aboveground biomass had a significantly positive relationship with the number of cultivars across monocultures and cultivar mixtures, and both were significantly higher in the cultivar mixtures than the monoculture mean. The higher yields in cultivar mixtures were attributed to higher thousand-grain weights and spike numbers per unit area. The cultivar mixtures had more root biomass and root distribution at depth than the monoculture mean, which contributed to higher water use efficiencies in the drier year. Conclusions: Cultivar mixtures can improve crop performance under water-deficit conditions and are likely to buffer the negative effects of drought on wheat yield under global climate change. [ABSTRACT FROM AUTHOR]

Abstract: China is facing the challenge of feeding a growing population with the declining cropland and increasing shortage of water resources under the changing climate. This study identified that the opportunistic profit‐driven shifts of planting areas and crop species composition have strongly reduced the food production capacity of China. First, the regional cultivation patterns of major crops in China have substantially shifted during the past five decades. Southeast and South China, the regions with abundant water resources and fewer natural disasters, have lost large planting areas of cropland in order to pursue industry and commerce. Meanwhile, Northeast and Northwest China, the regions with low water resources and frequent natural disasters, have witnessed increases in planting areas. These macroshifts have reduced the national food production by 1.02% per year. The lost grain production would have been enough to feed 13 million people. Second, the spatial shifts have been accompanied by major changes in crop species composition, with substantial increases in planting area and production of maize, due to its low water consumption and high economic returns. Consequently, the stockpile of maize in China has accounted for more than half of global stockpile, and the stock to use ratio of maize in China has exceeded the reliable level. Market‐driven regional shifts of cropping practices have resulted in larger irrigation requirements and aggravated environmental stresses. Our results highlighted the need for Chinese food policies to consider the spatial shifts in cultivation, and the planting crop compositions limited by regional water resources and climate change. [ABSTRACT FROM AUTHOR]

This study aims to evaluate the impacts of climate change and technical progress on the wheat yield per unit area from 1970 to 2014 in Henan, the largest agricultural province in China, using an autoregressive distributed lag approach. The bounded F-test for cointegration among the model variables yielded evidence of a long-run relationship among climate change, technical progress, and the wheat yield per unit area. In the long run, agricultural machinery and fertilizer use both had significantly positive impacts on the per unit area wheat yield. A 1% increase in the aggregate quantity of fertilizer use increased the wheat yield by 0.19%. Additionally, a 1% increase in machine use increased the wheat yield by 0.21%. In contrast, precipitation during the wheat growth period (from emergence to maturity, consisting of the period from last October to June) led to a decrease in the wheat yield per unit area. In the short run, the coefficient of the aggregate quantity of fertilizer used was negative. Land size had a significantly positive impact on the per unit area wheat yield in the short run. There was no significant short-run or long-run impact of temperature on the wheat yield per unit area in Henan Province. The results of our analysis suggest that climate change had a weak impact on the wheat yield, while technical progress played an important role in increasing the wheat yield per unit area. The results of this study have implications for national and local agriculture policies under climate change. To design well-targeted agriculture adaptation policies for the future and to reduce the adverse effects of climate change on the wheat yield, climate change and technical progress factors should be considered simultaneously. In addition, adaptive measures associated with technical progress should be given more attention. [ABSTRACT FROM AUTHOR]

To develop strategies for sustainable intensification of agricultural production, it is necessary to obtain precise and spatially explicit knowledge of crop potential and yield gap at a large scale. In this study, we estimated the yield potential for winter wheat by county during the period of 1981–2008 in North China using an ensemble simulation of a well validated large-scale crop model, MCWLA-Wheat, for each 0.5° × 0.5° grid. An ensemble simulation was used to better represent the heterogeneous conditions in climate, soil and cultivars over a large area. The spatio-temporal patterns of winter wheat actual yield, yield potential and yield gap were evaluated according to the simulation results. We found that more than 90% of counties had experienced an overall increase in wheat yield. However, 30.1% of counties have already experienced yield stagnation. The mean yield potential ranged generally from approximately 5000 to 8000 kg/ha. The yield potential under water-limited conditions showed considerably smaller values, ranging from about 2000 to 5000 kg/ha. Yield gaps in about 62% of counties were generally lower than 40% of potential yields, indicating a relatively small potential for yield improvement. During the study period, yield potential decreased in most counties because of a significant increase in temperature and decrease in solar radiation. In contrast, the increase of yield potential in the west and southeast areas could be attributed to the increase of solar radiation during the growing season. Overall, yield gap in the past decades showed a substantial decrease due to the changing pattern of yield potential and the rapid increase of actual yield, especially in the North China Plain, with a rate of 1–3% per year. These patterns imply a shrinking of space for further yield improvement. Our results highlight the necessity of applying advanced management technologies to realize a high yield, as well as adopting technical progress and policy support to overcome the yield bottleneck. Moreover, breeding climate-resilient cultivars to further increase yield potential should be of equal importance. [ABSTRACT FROM AUTHOR]

China's large population and deteriorating environment have created great concern related to the sustainability of food production, especially since details related to this topic remain poorly studied. Thus, an integrated analysis of both crop yield and cultivated area is essential for gaining a better understanding of cereal grain production in China and for making corresponding policies designed to achieve food security. In this study, we adopt trend analysis of both provincial yield and cultivated area to assess the subsequent provincial-level cereal production sustainability between 1980 and 2011 with the goal of providing a better understanding of regional agricultural development. The results indicate that while maize shows the most promise for yield improvement, rice and wheat production is experiencing substantial yield stagnation among most provinces across mainland China. In addition, the trends in spatial patterns are prominently different from those of yields. The sizes of the main rice- and wheat-growing areas in China have declined greatly, suggesting that the related production of these cereals should attract more attention from land management planners and farmers. Specifically, the south-eastern coastal provinces have largely failed to sustain both crop yield and area, while the north-eastern provinces have witnessed thriving agricultural production during the last three decades. Moreover, we find that cereal production in China is significantly affected by governmental policies related to the agricultural sector. Thus, this analysis of food production in China will help policymakers to better understand how the potential implications of food security in China may be applicable to countries worldwide. [ABSTRACT FROM AUTHOR]

Concerns about the effects of global warming on crop yields have risen due to stagnating yield progress in recent years. Understanding crop traits and grain yield variations in different climate zones is critical to gain insights into crop response and adaptation mechanisms to ongoing climate change. However, the interactions of genotype, environment and management on crop traits and historical yield progress are lacking. This study is to investigate the variations and trends in wheat traits in different climate zones across China, trade-offs among phenological and yield-related traits, the effects of genotype, environment and management interactions on wheat traits, as well as the contributions of traits, management, climate and genetic changes to grain yield. The genotype, environment and management interactions on wheat traits and grain yield variations were analyzed based on long-term field trials during 2003–2016 at five representative stations across China. And then, a machine learning method was applied to quantify the relative contributions of these factors to wheat traits and grain yield variations. A significant warming trend during the reproductive growth period and a decreasing trend in solar radiation were observed. Significant trends and variations in wheat traits and significant interactions between genotype, station and year were discovered. Compared with fertilization, grain yield under no-fertilization was significantly lower by 80.3% at five representative stations across China. With local farmer's practices, about 3.5–40.9%, 19.6–58.3% and 0.1–8.2% of the yield variations were associated with agricultural management practices, climate change and cultivar shifts, respectively, contradicting some previous studies which highlight the weight of genetic yield improvement. The findings are valuable for understanding the mechanisms underlying crop traits and grain yield variations, for breeders to breed desirable traits, and for agronomists to adopt suitable cultivars and agricultural management practices. [Display omitted] • The interactions of genotype, environment and management throughout the traits on historical yield progress are lacking. • Understanding crop traits and grain yield variations in different climate zones helps to crop response and adaptation mechanisms to ongoing climate change. • A machine learning method and meta-regression analyses were used to distinguish the relative contributions of these factors to grain yield variations based on long-term field trials at five representative stations across China. • Climate and agronomy, especially changes in traits, not genetics, affect wheat yield. [ABSTRACT FROM AUTHOR]

• Simulated yields increase 4.5∼5.5% with full realization of elevated CO 2 by 2050s. • Uncertainty in future wheat yield is ∼ 4 times higher than growing season duration. • RCPs, crop and climate models contribute > 70% of total uncertainty in wheat growth. • Regions where growing season t ave > 20 ℃ are more subject to higher uncertainty. • Regions where growing season rainfall < 400 mm would suffer larger uncertainty. Exploring and quantifying the uncertainties in climate impact assessment with multiple climate-crop models is crucial to reducing the total uncertainty and guiding adaptation strategies for crop production. Here, we carried out a climate-crop ensemble simulation to measure the uncertainty in estimated climate impacts on China's wheat productivity by the 2050s. The ensemble included the simulations conducted with the three-DSSAT wheat model ensemble. As for the future climate, five Global Climate projections (GCMs) under two Representative Concentration Pathways (RCP4.5 and 8.5) and two CO 2 concentrations were selected. Our results indicate that the median of simulated yield change was between 4.5% ∼ 5.5%, and -7.7% ∼ -5.6% respectively under elevated and current CO 2 concentrations by 2050s compared to 1981–2010. The median of simulated phenology change was nearly -12 ∼ -10 d In percentage terms, higher uncertainty in national yield change was observed compared to phenology change. The total relative contributions of climate projections, crop models, and RCP scenarios have been more than 70% of the total uncertainty of national phenology and yield change. Crop models have accounted for the largest uncertainty of irrigated yield, while crop models and climate projections almost contributed a similar share of the total uncertainty of rainfed yield. These findings highlight the distribution of uncertainty and sources of uncertainty both at the national and grid scales, which would provide a more comprehensive understanding of uncertainties in future yield prediction. Our results also showed that larger uncertainty has been observed in warmer regions (growing season average temperature > 20 °C) than in cooler regions, while the wet regions (growing season rainfall > 400 mm) would suffer smaller uncertainty than dry regions. These findings emphasize the relationships between uncertainty and climate factors, which offers insights for improving crop models and designing adaptation strategies. [ABSTRACT FROM AUTHOR]

After a remarkable 86% increase in cereal production from 1980 to 2005, recent crop yield growth in China has been slow. County level crop production data between 1980 and 2010 from eastern and middle China were used to analyze spatial and temporal patterns of rice, wheat and maize yield in five major farming systems that include around 90% of China's cereal production. Site-specific yield trends were assessed in areas where those crops have experienced increasing yield or where yields have stagnated or declined. We find that rice yields have continued to increase on over 12.3 million hectares (m. ha) or 41.8% of the rice area in China between 1980 and 2010. However, yields stagnated on 50% of the rice area (around 14.7 m. ha) over this time period. Wheat yields increased on 13.8 m. ha (58.2% of the total harvest area), but stagnated on around 3.8 m. ha (15.8% of the harvest area). Yields increased on a smaller proportion of the maize area (17.7% of harvest area, 5.3 m. ha), while yields have stagnated on over 54% (16.3 m. ha). Many parts of the lowland rice and upland intensive sub-tropical farming systems were more prone to stagnation with rice, the upland intensive sub-tropical system with wheat, and maize in the temperate mixed system. Large areas where wheat yield continues to rise were found in the lowland rice and temperate mixed systems. Land and water constraints, climate variability, and other environmental limitations undermine increased crop yield and agricultural productivity in these systems and threaten future food security. Technology and policy innovations must be implemented to promote crop yields and the sustainable use of agricultural resources to maintain food security in China. In many production regions it is possible to better match the crop with input resources to raise crop yields and benefits. Investments may be especially useful to intensify production in areas where yields continue to improve. For example, increased support to maize production in southern China, where yields are still rising, seems justified. [ABSTRACT FROM AUTHOR]

With the growth in population over the past decades, China's food demand has been increasing. However, crops are facing greater water stress with the rising temperature and increasing drought in future. Therefore, identifying potential crop yield and its driving factors is necessary to ensure continued food production. In the present study, we estimated the potential yields of maize and wheat in China, with and without water limits, from 1985 to 2015 using a simple generic crop model (SIMPLE). We then investigated how climate factors (temperature, precipitation, and solar radiation) drove the spatial and temporal variation of yield gaps (quantified as the difference between potential yields with and without water limits). We found an increasing trend in the water limited yield gap of maize in northern China (3.9 ± 4.3 kg ha-1 yr-2) and wheat in central China (2.6 ± 2.4 kg ha-1 yr-2). The temporal trends of maize and wheat yield gaps in China were mainly related to precipitation and temperature. However, the spatial variation in maize yield gap trends was mainly related to the variations in precipitation, whereas for wheat it was attributed to changes in temperature or solar radiation. Upgrading irrigation infrastructure and management techniques or spatially adjusting crop types could help closing the yield gap of wheat in some zones. • The change trends of yield gap between maize and wheat are inconsistent. • The maize yield gaps variation was spatially related to variations in precipitation. • For wheat, it was attributed to changes in temperature or solar radiation. • Management techniques should be upgraded or crop types adjusted to close yield gaps. [ABSTRACT FROM AUTHOR]

• Assessing impacts of climate change on wheat production in climate-suitable area. • Quantifying projected uncertainty of wheat production under future climate change. • SDM dominated projected uncertainty of wheat production in climate-suitable area. • CM was more certain when projecting future wheat production in climate-suitable area. Climate change poses a great challenge to global food security. Recently the combination of crop models (CMs), global climate models (GCMs), and species distribution models (SDMs) has been applied to assess the impacts of climate change on crop production with consideration of changes of crop climate-suitable regions. However, little is known about the uncertainty sources in the wheat production projections with consideration of crop climatic suitability under future climate. In this study, an integration method based on multiple CMs, SDMs, and GCMs was adopted to assess the impacts of climate change on winter wheat production in the Loess Plateau of China. A comprehensive analysis of different uncertainty sources (i.e. CM, GCM, SDM, Emission Scenario or Scen , and their interactions) was conducted through the ANOVA (Analysis of variance) method. Based on the projections of CM ensemble and ensemble-SDMs driven by 27 GCMs, multi-model mean winter wheat production would increase by 14.6% and 19.7% in 2041–2060 and 4.9% and 3.5% in 2081–2100 under SSP245 and SSP585, respectively. We found that the changes in climate-suitable areas of winter wheat caused larger changes in winter wheat production than the changes of per unit yield. SDM was the largest uncertainty contributor among the four main factors of CM, GCM, SDM, and Scen in the projections of winter wheat production under future climate in the Loess Plateau, accounting for about 20.3% of total uncertainty. At the same time, CM was the lowest uncertainty contributor and accounted for only about 3.0% of total uncertainty. Thus, CM was proved more certain in future projections of winter wheat production when considering the changes of crop climate-suitable areas. The efforts in this study could help to rationally integrate the crop modeling, species distribution modeling, and climate models on the projections of global wheat production under future global climate change. [ABSTRACT FROM AUTHOR]

Wheat has been documented to be vulnerable to climate change in broad regions of the world including China. Adaptation to future climate change by breeding climate resilient cultivars is essential. However the precise information as to where, when, and what cultivar traits should be applied to adapt to climate change in the coming decades has not been available. In this study, we developed novel hybrid assessment models by incorporating a process-based crop model and machine learning algorithms based on a large number of cultivars field experiments data. The models were applied to assess the impact of climate change on wheat productivity and to identify the timescale of wheat cultivar adaptation in the major wheat cultivation regions across China. Wheat yield was projected to decrease on average by 6.3% (9.4%) in the 2050 s under RCP 4.5 (8.5), relative to the baseline period (1986–2005), without the CO 2 effect. By contrast, it was projected to increase on average by 5.7% (8.1%) in the 2050 s with the CO 2 effect, across the regions and cultivar-maturing traits in China. Solar radiation, precipitation, temperature, cultivar-maturing traits, and CO 2 are critical factors affecting wheat productivity in the major wheat cultivation regions. About 44% (39%) and 68% (57%) of wheat planting grids would require cultivar renewal before 2050 (2040) under RCP 4.5 and 8.5 emission scenario, respectively, at a medium risk level without the CO 2 effect. The cultivars with a long reproductive growth duration, high photosynthetic efficiency and large harvest index would be generally promising although there are specific traits desirable for certain regions. This study developed a novel framework to identify the precise information on where, when, and what cultivar traits should be applied for wheat to adapt to future climate change, helping the stakeholders to cope with climate change timely and precisely. Timescale of wheat cultivar adaptation under RCPs 4.5 and 8.5. The time plotted in the figure is mean time when cultivar adaptation is required for the grid without the CO 2 fertilization effect. Grey areas indicate the areas where cultivar adaptation is not needed by 2050 under the RCPs. [Display omitted] • Develop novel hybrid assessment models by incorporating crop model and machine learning. • Identify where, when, and what cultivar traits should be applied to adapt to future climate change. • Impacts of future climate change on wheat productivity would depend on regions and cultivar traits. • 39% and 57% of wheat planting grids would require cultivar renewal before 2040 under RCP 4.5 and 8.5. • Region-specific wheat cultivars ideotypic traits are identified. [ABSTRACT FROM AUTHOR]

• Wheat phenological observations with the longest time period at the most stations were applied. • Climate warming impacts increased for winter wheat but declined for spring wheat. • Growing periods were more sensitive to mean and maximum than minimum temperature. • Cultivar shifts only partly offset the negative effects of climate warming. • Changes in sowing date shortened growing periods on average by <0.5 days/decade. Investigating crop phenology change has important implications to understand crop response and adaptation to climate change. The spatiotemporal changes of wheat phenology had been investigated before, nevertheless some key scientific questions remain inconclusive. Here, the updated phenological observations with the longest time period (1981–2018) and the largest number of records (7,659 records at 357 stations) for wheat in China were applied to investigate whether the response of wheat phenology to recent climate warming declined, how wheat responded to asymmetric warming, and how different drivers affected wheat phenology change. The results showed wheat sowing date delayed but heading and maturity date advanced generally during 1981–2018. Trends in wheat sowing date, heading date, maturity date, vegetative growing period (VGP), reproductive growing period (RGP) and whole growing period (GP) between 1981–1999 and 2000–2018 changed heterogeneously across the agro-ecological zones. This inconsistence may be ascribed to the compound impacts of climate change and agricultural managements such as cultivar shifts. Climate warming impacts on GP increased for winter wheat but declined for spring wheat in most regions from 1981–1999 to 2000–2018. Daily minimum temperature increased more than mean and maximum temperature, however VGP, RGP and GP were more sensitive to mean and maximum temperature than to minimum temperature. Maximum and minimum temperature had contrasting effects. Spring wheat was more sensitive to temperature than winter wheat, and RGP was more sensitive to temperature than VGP and GP because the later was also subject to photoperiod and vernalization. During 1981–2018, climate warming shortened GP on average by 4.2 and 4.6 days/decade for winter and spring wheat, respectively. Cultivar shifts prolonged it by 2.0 and 2.9 days/decade, respectively. Changes in sowing date shortened it on average by 0.5 and 0.4 days/decade, respectively. The effects of other factors such as fertilization and irrigation changed it on average by 0.1 and -0.3 days/decade, respectively. And the effects of all agricultural managements together prolonged it on average by 1.6 and 2.4 days/decade, respectively. Our findings provide new insights into the spatiotemporal changes of wheat phenology, as well as their drivers, across China in the past four decades. [ABSTRACT FROM AUTHOR]

• Remote sensing data assimilation was used to simulate the winter wheat growth. • RC and PA were used to assess the effect of climate on winter wheat. • Solar radiation and sunshine duration were the two most important climate factors. • Approximately 90% of the variation in yield could be explained by IR and Phe. Understanding the response mechanism winter wheat growth in response to climate change is critical for winter wheat production and field management. Therefore, in this study, we employed relative contribution and path analysis along with a crop model and remote sensing data to investigate to the effect of climate on winter wheat production for the 2009–2019 period in China's Guanzhong Plain (GZP). We registered three key findings. First, winter wheat yield and water use efficiency (WUE) were increasing in the central-south and eastern GZP and were decreasing in the central-north and western GZP. Average temperature (T avg) influenced winter wheat production by shorting vegetative and reproductive stage. Net solar radiation (R n) and sunshine hours (Ssh) affected winter wheat production by altering irrigation requirements (IRs), and precipitation (P) had a strong correlation with yield and WUE despite a limited contribution. Second, climatic factors were not independent, and they affected each other; T avg and P mainly affected winter wheat production through R n and Ssh. Finally, approximately 90% of the variation in yield and WUE of winter wheat could be explained by IRs and phenology, the yield and WUE decreased with an increase in IRs, and the prolongation of the reproductive stage exerted a positive effect on winter wheat production and effectively offset the negative effect of the shortening of the vegetative stage. This means that the adoption of long-lasting winter wheat varieties and high irrigation levels in a changing climate benefit winter wheat production and may be a viable strategy for adaptation to climate change. The results provide potentially valuable information for alleviating the impact of climate change on winter wheat production and improving the planting management of winter wheat in the GZP. [ABSTRACT FROM AUTHOR]

Climatic warming is often predicted to reduce wheat yield and grain quality in China. However, direct evidence is still lacking. We conducted a three-year experiment with a Free Air Temperature Increase (FATI) facility to examine the responses of winter wheat growth and plant N accumulation to a moderate temperature increase of 1.5°C predicted to prevail by 2050 in East China. Three warming treatments (AW: all-day warming; DW: daytime warming; NW: nighttime warming) were applied for an entire growth period. Consistent warming effects on wheat plant were recorded across the experimental years. An increase of ca. 1.5°C in daily, daytime and nighttime mean temperatures shortened the length of pre-anthesis period averagely by 12.7, 8.3 and 10.7 d (P<0.05), respectively, but had no significant impact on the length of the post-anthesis period. Warming did not significantly alter the aboveground biomass production, but the grain yield was 16.3, 18.1 and 19.6% (P<0.05) higher in the AW, DW and NW plots than the non-warmed plot, respectively. Warming also significantly increased plant N uptake and total biomass N accumulation. However, warming significantly reduced grain N concentrations while increased N concentrations in the leaves and stems. Together, our results demonstrate differential impacts of warming on the depositions of grain starch and protein, highlighting the needs to further understand the mechanisms that underlie warming impacts on plant C and N metabolism in wheat. [ABSTRACT FROM AUTHOR]

Highlights: [•] The drought trend in China's semiarid areas has intensified over the past 50 years. [•] This study investigated the effects of climate change on crop water use efficiency. [•] The water use efficiency by crop has significantly increased over the past 50 years. [ABSTRACT FROM AUTHOR]

Global warming and altered precipitation patterns pose a serious threat to crop production in the North China Plain (NCP). Quantifying the frequency of adverse climate events (e.g., frost, heat and drought) under future climates and assessing how those climatic extreme events would affect yield are important to effectively inform and make science-based adaptation options for agriculture in a changing climate. In this study, we evaluated the effects of heat and frost stress during sensitive phenological stages at four representative sites in the NCP using the APSIM-wheat model. climate data included historical and future climates, the latter being informed by projections from 22 Global Climate Models (GCMs) in the Coupled Model Inter-comparison Project phase 6 (CMIP6) for the period 2031–2060 (2050s). Our results show that current projections of future wheat yield potential in the North China Plain may be overestimated; after more accurately accounting for the effects of frost and heat stress in the model, yield projections for 2031-60 decreased from 31% to 9%. Clustering of common drought-stress seasonal patterns into key groups revealed that moderate drought stress environments are likely to be alleviated in the future, although the frequency of severe drought-stress environments would remain similar (25%) to that occurring under the current climate. We highlight the importance of mechanistically accounting for temperature stress on crop physiology, enabling more robust projections of crop yields under future the burgeoning climate crisis. [ABSTRACT FROM AUTHOR]

Abstract: Wheat is the second primary crop in China. Wheat production in China is an important component for national food security. The combination of high-resolution Global Climate Model (GCM) and WheatGrow model was used to assess the effects of climate change on wheat yields in the main wheat production regions of China. With the application of many techniques including the downscaling of meteorological data, rasterizing of sowing date, parameterization of region cultivar and vectorization of soil data, the spatial data in study area is divided into homogeneous grids with the resolution of 0.1°×0.1°. The grid is taken as the basic simulation unit, and each grid has a complete set of input data (meteorological, soil, management and varieties). Regional productivities are simulated with WheatGrow for each grid cell under scenarios of climate-change. There is an advance in flowering date in future climate compare to 2000s, but with a more homogeneous pattern for the whole producing region. The changes in grain filling period are relatively stable. Under rain-fed conditions, wheat yield is reduced in the north regions of China in three future periods, while wheat yield increases in the south regions of China. Under full-irrigation conditions, irrigated wheat yields will increase in almost all regions of whole producing region. The spatial pattern of evapotranspiration change is quite similar to that of yield change under rain-fed and full-irrigation conditions. The correlation between wheat yield and evapotranspiration (ET) increases to 0.96 and 0.51 (p <0.01) under rain-fed and full-irrigation conditions, respectively. The irrigation water use efficiency (IWUE) will decrease under three time slices in 2030s, 2050s and 2070s in western Shandong, southern Sichuan, as well as northern Henan, Shanxi and Shaanxi, while IWUE will increase under scenarios of climate-change in other areas. The results revealed that the increase in effective irrigation in the future would help to increase the ET and further improve the wheat yield in the northern regions of China, and the limited water should be mad full use of in the regions with relatively high IWUE under scenarios of climate-change. [Copyright &y& Elsevier]

In the North China Plain, the grain yield of irrigated wheat-maize cropping system has been steadily increasing in the past decades under a significant warming climate. This paper combined regional and field data with modeling to analyze the changes in the climate in the last 40 years, and to investigate the influence of changes in crop varieties and management options to crop yield. In particular, we examined the impact of a planned adaptation strategy to climate change -'Double-Delay' technology, i.e., delay both the sowing time of wheat and the harvesting time of maize, on both wheat and maize yield. The results show that improved crop varieties and management options not only compensated some negative impact of reduced crop growth period on crop yield due to the increase in temperature, they have contributed significantly to crop yield increase. The increase in temperature before over-wintering stage enabled late sowing of winter wheat and late harvesting of maize, leading to overall 4-6% increase in total grain yield of the wheat-maize system. Increased use of farming machines and minimum tillage technology also shortened the time for field preparation from harvest time of summer maize to sowing time of winter wheat, which facilitated the later harvest of summer maize. [ABSTRACT FROM AUTHOR]

Abstract: Wheat/maize related multi-cropping systems are the dominant cropping systems in North China. To improve and adjust those systems, and to study competition effects within intercropping, extended field experiments are necessary. As field experiments are time consuming, laborious and expensive, a viable alternative is the use of crop growth models that can quantify the effects of management practices on crop growth and productivity. Field experiments showed that intercropped maize yielded as high as monocropped maize, and grain yield of intercropped wheat increased by up to 32%. Based on a process-oriented modeling approach, this study focuses on analyzing and modeling competitive relationships in a wheat/maize relay intercropping system with regard to yield, solar radiation and microclimate effects. A simple shading algorithm was applied and integrated into the CERES models, which are part of the DSSAT software shell vs. 4.5. The algorithm developed estimates the proportion of shading as affected by neighbouring plant height. The model was tested to investigate the applicability of this shading algorithm within the CERES models in the simulation of grain yield and dry matter yield of wheat and maize. Model error of grain and dry matter yield for both species was below 10%. There was a tendency for grain yield to be simulated adequately but for dry matter yield to be slightly underestimated. Increased top soil temperature in intercropped wheat increased the mineralization of nitrogen and improved N supply. The wheat/maize system was N efficient. Thus, N dynamics were taken into account for simulation as well as CO2 dynamics based upon modified wind speed. Wheat border rows were exposed to a higher wind speed until mid-June and to reduced wind speed thereafter. As a result, solar radiation, soil temperature and wind speed differed between monocropping and intercropping and could provide a starting point for simulating intercropping. Microclimate effects are often small, subtle or non-existent, while spatial and climate variability and the heterogeneity of plant populations can be considerable. Quantifying microclimatic effects may prove difficult but should not be neglected when simulating intercropping systems. [Copyright &y& Elsevier]

Abstract: Recent changes in climate have had a measurable impact on crop yield in China. The objective of this study is to investigate how climate variability affects wheat yield in China at different spatial scales. First the response of wheat yield to the climate at the provincial level from 1978 to 1995 for China was analysed. Wheat yield variability was only correlated with climate variability in some regions of China. At the provincial level, the variability of precipitation had a negative impact on wheat yield in parts of southeast China, but the seasonal mean temperature had a negative impact on wheat yield in only a few provinces, where significant variability in precipitation explained about 23–60% of yield variability, and temperature variability accounted for 37–41% of yield variability from 1978 to 1995. The correlation between wheat yield and climate for the whole of China from 1985 to 2000 was investigated at five spatial scales using climate data. The Climate Research Unit (CRU) and National Centers for Environmental Prediction (NCEP) proportions of the grid cells with a significant yield–precipitation correlation declined progressively from 14.6% at 0.5° to 0% at 5° scale. In contrast, the proportion of grid cells significant for the yield–temperature correlation increased progressively from 1.9% at 0.5° scale to 16% at 5° scale. This indicates that the variability of precipitation has a higher association with wheat yield at small scales (0.5°, 2°/2.5°) than at larger scales (4°/5.0°); but wheat yield has a good association with temperature at all levels of aggregation. The precipitation variable at the smaller scales (0.5°, 2°/2.5°) is a dominant factor in determining inter-annual wheat yield variability more so than at the larger scales (4°/5°). We conclude that in the current climate the relationship between wheat yield and each of precipitation and temperature becomes weaker and stronger, respectively, with an increase in spatial scale. [Copyright &y& Elsevier]

The North China Plain (NCP) is the most important agricultural production area in China. Crop production in the NCP is sensitive to changes in both climate and management practices. While previous studies showed a negative impact of climatic change on crop yield since 1980s, the confounding effects of climatic and agronomic factors have not been separately investigated. This paper used 25 years of crop data from three locations (Nanyang, Zhengzhou and Luancheng) across the NCP, together with daily weather data and crop modeling, to analyse the contribution of changes in climatic and agronomic factors to changes in grain yields of wheat and maize. The results showed that the changes in climate were not uniform across the NCP and during different crop growth stages. Warming mainly occurred during the vegetative (preflowering) growth stage of wheat and maize, while there was a cooling trend or no significant change in temperatures during the postflowering stage of wheat (spring) or maize (autumn). If varietal effects were excluded, warming during vegetative stages would lead to a reduction in the length of the growing period for both crops, generally leading to a negative impact on crop production. However, autonomous adoption of new crop varieties in the NCP was able to compensate the negative impact of climatic change. For both wheat and maize, the varietal changes helped stabilize the length of preflowering period against the shortening effect of warming and, together with the slightly reduced temperature in the postflowering period, extend the length of the grain-filling period. The combined effect led to increased wheat yield at Zhengzhou and Luancheng; increased maize yield at Nanyang and Luancheng; stabilized wheat yield at Nanyang, and a slight reduction in maize yield at Zhengzhou, compared with the yield change caused entirely by climatic change. [ABSTRACT FROM AUTHOR]

Abstract: In the North China Plain (NCP), while irrigation using groundwater has maintained a high-level crop productivity of the wheat–maize double cropping systems, it has resulted in rapid depletion of groundwater table. For more efficient and sustainable utilization of the limited water resources, improved understanding of how crop productivity and water balance components respond to climate variations and irrigation is essential. This paper investigates such responses using a modelling approach. The farming systems model APSIM (Agricultural Production Systems Simulator) was first calibrated and validated using 3 years of experimental data. The validated model was then applied to simulate crop yield and field water balance of the wheat–maize rotation in the NCP. Simulated dryland crop yield ranged from 0 to 4.5tha−1 for wheat and 0 to 5.0tha−1 for maize. Increasing irrigation amount led to increased crop yield, but irrigation required to obtain maximum water productivity (WP) was much less than that required to obtain maximum crop yield. To meet crop water demand, a wide range of irrigation water supply would be needed due to the inter-annual climate variations. The range was simulated to be 140–420mm for wheat, and 0–170mm for maize. Such levels of irrigation applications could potentially lead to about 1.5myear−1 decline in groundwater table when other sources of groundwater recharge were not considered. To achieve maximum WP, one, two and three irrigations (i.e., 70, 150 and 200mmseason−1) were recommended for wheat in wet, medium and dry seasons, respectively. For maize, one irrigation and two irrigations (i.e., 60 and 110mmseason−1) were recommended in medium and dry seasons, while no irrigation was needed in wet season. [Copyright &y& Elsevier]

Abstract: The interplay between the carbon and other nutrient cycles is the key to understand the responses of soil ecosystems to climatic change. Using the free-air CO2 enrichment (FACE) techniques, we carried out a multifactorial experiment in a Chinese rice–wheat rotation system, to investigate the response of soil nematodes to elevated CO2 under different application rates of N fertilizer (225.0 kg N ha−1 (HN) and 112.5 kg N ha−1(LN), respectively) and residue incorporation (0 kg C ha−1 (ZR), 1000 kg C ha−1 (MR) and 2000 kg C ha−1 (HR), respectively). This study was conducted during the wheat growing season of 2007 after expose to the elevated CO2 for three years. The results in our study indicated that seasonality is an important factor in determining changes in the nematode abundance and diversity. The residue addition effects were more obvious than the elevated CO2, which significantly influenced the abundance of total nematodes and plant-parasites, and some ecological indices. The interactions between residue addition and CO2 significantly influenced nematode dominance and structure indices. High level of N fertilization was found to decrease the nematode diversity, generic richness and maturity indices at wheat jointing stage. There are significant interactions between N fertilization and elevated CO2 for abundance of total nematodes and different trophic groups. [Copyright &y& Elsevier]