Prediction of the potential distribution and analysis of the freezing injury risk of winter wheat on the Loess Plateau under climate change

Determining the suitable areas for winter wheat under climate change and assessing the risk of freezing injury are crucial for the cultivation of winter wheat.We used an optimized Maximum Entropy(MaxEnt)Model to predict the potential distribution of winter wheat in the current period(1970-2020)and the future period(2021-2100)under four shared socioeconomic pathway scenarios(SSPs).We applied statistical downscaling methods to downscale future climate data,established a scientific and practical freezing injury index(FII)by considering the growth period of winter wheat,and analyzed the characteristics of abrupt changes in winter wheat freezing injury by using the Mann-Kendall(M-K)test.The results showed that the prediction accuracy AUC value of the MaxEnt Model reached 0.976.The minimum temperature in the coldest month,precipitation in the wettest season and annual precipitation were the main factors affecting the spatial distribution of winter wheat.The total suitable area of winter wheat was approximately 4.40×10^(7)ha in the current period.In the 2070s,the moderately suitable areas had the greatest increase by 9.02×10^(5)ha under SSP245 and the least increase by 6.53×10^(5)ha under SSP370.The centroid coordinates of the total suitable areas tended to move northward.The potential risks of freezing injury in the high-latitude and-altitude areas of the Loess Plateau,China increased significantly.The northern areas of Xinzhou in Shanxi Province,China suffered the most serious freezing injury,and the southern areas of the Loess Plateau suffered the least.Environmental factors such as temperature,precipitation and geographical location had important impacts on the suitable area distribution and freezing injury risk of winter wheat.In the future,greater attention should be paid to the northward boundaries of both the winter wheat planting areas and the areas of freezing injury risk to provide the early warning of freezing injury and implement corresponding management strategies.

An Econometric Analysis on the Effect of Climate Change on Wheat Cropping Area in China

[Objective] This study aimed to explore the impact of climate change on wheat cropping by using province-specific historical data during 1996-2007. [Method] We established a panel data econometric model with lagged wheat cropping area and province-specific fixed-effects model to control the unobserved factors. [Result] The results showed that the temperature positively affects wheat cropping area, while precipitation does not have such impact. [Conclusion] The study provided empirical evidence for analysis of the determinants of wheat cropping area in China.

Impacts of climate change on drought risk of winter wheat in the North China Plain

Drought is a major natural disaster causing crop yield losses,while its occurrence mechanism and spatiotemporal variations in a changing climate are still not clear.Based on a long-term climatic dataset(during 1958–2015)from weather stations in the North China Plain(NCP),the influencing mechanism of various climatic factors on drought risk of winter wheat was quantified by using sensitivity analysis,Mann-Kendall trend test and slope estimation.The results indicated that climatic factors have changed considerably over the past six decades in the growth season of winter wheat.As a result,winter wheat suffered from severe droughts(with 350 mm of water deficit during its growth season),particularly at the jointing–heading and heading–mature stages,which were critical to crop yield formation.There were large spatial and temporal variations in drought risk and climatic change factors at different growth stages of winter wheat.Despite precipitation playing a vital role in determining the spatiotemporal patterns of drought risk,high temperature and low humidity along with other climatic factors at key growth stages of winter wheat aggravated drought risk.Particularly,temperature at nearly 90%weather stations showed a notablely upward trend,which exacerbated water deficit and drought risk of winter wheat.Given the complexity and high uncertainty of climate change,these findings provide important information for adapting crop production to future climate change and accompanied droughts while ensuring food security and agricultural sustainability.

The Influence of Climate Change on Winter Wheat during 2012-2100 under A2 and A1B Scenarios in China

By assuming constant winter wheat varieties and agricultural practices in China, the influence of climate change on winter wheat is simulated using the corrected future climate projections under SRES A2 and A1B scenarios from 2012 to 2100, respectively. The results indicate that the growth of winter wheat would be strongly influenced by climate change in future. The average flowering and maturity dates of winter wheat would advance by 26 and 27 days under scenario A2, and by 23 and 24 days respectively under scenario A1B from 2012 to 2100. The simulated potential productivity of winter wheat shows a decrease of 14.3% and 12.5% for scenarios A2 and A1B respectively without the fertilization effect of CO2, while an increase of 1.3% and 0.6% with the fertilization effect of CO2. Additionally, for northern China, the simulated potential productivity would markedly decrease under both scenarios, independent with the fertilization effect of CO2, which indicates that the current planted winter wheat would be more vulnerable than that in southern China. The most likely reason is the current winter wheat varieties in northern China are winter varieties or strong winter varieties, which need some days of low temperature for dormancy. While in southern China, the winter wheat is spring or half winter varieties and can grow slowly during winter, thus, they would be affected slightly when winter temperature increases. The results of this study may have important implications for adaptation measures.

Study on the Sensitivity and Vulnerability of Wheat to Climate Change in China

Based on B2 climate change scenario produced by PRECIS (providing regional climates for impacts studies), which wasdeveloped by the UK Hadley Center, and the wheat yield data outputted by CERES-wheat model, the sensitivity andvulnerability of wheat production to the future climate change in China were studied through analyzing the yield variationusing the GIS (geographical information system) techniques. Results showed that, by the 2070s, there will be threenegative sensitive areas of rain-fed wheat, i.e., northeastern China, the region of the middle and lower reaches of theYangtze River, and part of the Loess Plateau. Irrigated wheat is generally sensitive to the future climate change for mostareas of China, with a lower sensitive degree and a distribution of sensitive areas similar to the rain-fed wheat. For theirrigated wheat, northeast and northwest of China are strongly negative sensitive, while the middle and lower reaches ofthe Yangtze River, the coastal areas of southern China and the southwest of China, are moderately negative sensitive tothe climate change. With the appropriate adaptation to the climate change, the rain-fed wheat in most regions of China willnot be vulnerable and even has a yield increase, while the irrigated wheat will still have a larger vulnerable area (occupyingabout 2/3 of its total area in China), with the highly vulnerable regions distributed in northeastern China and northwesternChina, and the medium and light vulnerable areas distributed along the middle and lower reaches of the Yangtze River,Yunnan and Guizhou provinces.

Impacts of climate change on wheat development and production in the northern China

In this paper, impacts of climate change on wheat development rate and production in the northern China are discussed. The results show that the temperature is a controlling factor of development rate but the precipitation is not. The higher the temperature is. the faster the development and the shorter development period will be. Without consideration to varieties and cropping system, meteorological yield of winter wheat would decrease 170.40, 134.25, 98.70 and 97.20 kg/hm2 in the north China and 13.97, 7.95, 39.60 and 19.80 kg/hm2 in the northwest China compared with that in 1950s, 1960s, 1970s and 1980s, respectively, when the CO2 concentration in the atmosphere is doubled. In drought and semi-drought regions, the spring wheat yield would drop with the temperature rise in and raise with the precipitation increase. The influence of temperature on weight of leaf and stalk is also remarkable.

Quantifying major sources of uncertainty in projecting the impact of climate change on wheat grain yield in dryland environments

Modelling the impact of climate change on cropping systems is crucial to support policy-making for farmers and stakeholders.Nevertheless,there exists inherent uncertainty in such cases.General Circulation Models(GCMs)and future climate change scenarios(different Representative Concentration Pathways(RCPs)in different future time periods)are among the major sources of uncertainty in projecting the impact of climate change on crop grain yield.This study quantified the different sources of uncertainty associated with future climate change impact on wheat grain yield in dryland environments(Shiraz,Hamedan,Sanandaj,Kermanshah and Khorramabad)in eastern and southern Iran.These five representative locations can be categorized into three climate classes:arid cold(Shiraz),semi-arid cold(Hamedan and Sanandaj)and semi-arid cool(Kermanshah and Khorramabad).Accordingly,the downscaled daily outputs of 29 GCMs under two RCPs(RCP4.5 and RCP8.5)in the near future(2030s),middle future(2050s)and far future(2080s)were used as inputs for the Agricultural Production Systems sIMulator(APSIM)-wheat model.Analysis of variance(ANOVA)was employed to quantify the sources of uncertainty in projecting the impact of climate change on wheat grain yield.Years from 1980 to 2009 were regarded as the baseline period.The projection results indicated that wheat grain yield was expected to increase by 12.30%,17.10%,and 17.70%in the near future(2030s),middle future(2050s)and far future(2080s),respectively.The increases differed under different RCPs in different future time periods,ranging from 11.70%(under RCP4.5 in the 2030s)to 20.20%(under RCP8.5 in the 2080s)by averaging all GCMs and locations,implying that future wheat grain yield depended largely upon the rising CO2 concentrations.ANOVA results revealed that more than 97.22% of the variance in future wheat grain yield was explained by locations,followed by scenarios,GCMs,and their interactions.Specifically,at the semi-arid climate locations(Hamedan,Sanandaj,Kermanshah and Khorramabad),most of the variations arose from the scenarios(77.25%),while at the arid climate location(Shiraz),GCMs(54.00%)accounted for the greatest variation.Overall,the ensemble use of a wide range of GCMs should be given priority to narrow the uncertainty when projecting wheat grain yield under changing climate conditions,particularly in dryland environments characterized by large fluctuations in rainfall and temperature.Moreover,the current research suggested some GCMs(e.g.,the IPSL-CM5B-LR,CCSM4,and BNU-ESM)that made moderate effects in projecting the impact of climate change on wheat grain yield to be used to project future climate conditions in similar environments worldwide.

Assessment of Climate Change Variability Impacts on Wheat and Barley Production in Palestine

The study aimed at addressing climate variability impacts on wheat and barley production in Palestine. A combination of literature survey and multiple semi-structured interviews with officials from the Palestinian governmental agriculture related agencies and active non-governmental organizations （NGOs） used for gathering information on wheat and barley production in Palestine. The gathered data along with information and subsequent results prevailed that the West Bank since the 1970s has experienced a significant decrease in winter rainfall. Across 15 sites, growing season rainfall （September to May） decreased by an average of 11% and the sum of rainfall in September and October decreased by 45%. Despite the large decline in rainfall, yields based on the actual weather data did not fall. These results were due to the rainfall changes mainly occurring in September and October, a period when rainfall often is less than crop demand. The study arrived at conclusion based on the study results that climate change variabilities have differential impacts on the yield growth of wheat and barley. However, both rainfed dependent crops are adversely affected by the current climate trends. The yields of barley and wheat are decreasing due to increased temperature and decreased precipitation.

The impacts of climate change on wheat yield in the Huang-Huai-Hai Plain of China using DSSAT-CERES-Wheat model under different climate scenarios

Climate change has been documented as a major threat to current agricultural strategies.Progress in understanding the impact of climate change on crop yield is essential for agricultural climate adaptation,especially for the Huang-Huai-Hai Plain(3H Plain)of China which is an area known to be vulnerable to global warming.In this study,the impacts of climate change on winter wheat(Triticum aestivum L.)yield between the baseline period(1981–2010)and two Representative Concentration Pathways(RCP8.5 and RCP4.5)were simulated for the short-term(2010–2039),the medium-term(2040–2069)and the long-term(2070–2099)in the 3H Plain,by considering the relative contributions of changes in temperature,solar radiation and precipitation using the DSSAT-CERES-Wheat model.Results indicated that the maximum and minimum temperatures(TMAX and TMIN),solar radiation(SRAD),and precipitation(PREP)during the winter wheat season increased under these two RCPs.Yield analysis found that wheat yield increased with the increase in SRAD,PREP and CO2 concentration,but decreased with an increase in temperature.Increasing precipitation contributes the most to the total impact,increasing wheat yield by 9.53,6.62 and 23.73%for the three terms of future climate under RCP4.5 scenario,and 11.74,16.38 and 27.78%for the three terms of future climate under RCP8.5 scenario.However,as increases in temperature bring higher evapotranspiration,which further aggravated water deficits,the supposed negative effect of increasing thermal resources decreased wheat yield by 1.92,4.08 and 5.24%for the three terms of future climate under RCP4.5 scenario,and 3.64,5.87 and 5.81%for the three terms of future climate under RCP8.5 scenario with clearly larger decreases in RCP8.5.Counterintuitively,the impacts in southern sub-regions were positive,but they were all negative in the remaining sub-regions.Our analysis demonstrated that in the 3H Plain,which is a part of the mid-high latitude region,the effects of increasing thermal resources were counteracted by the aggravated water deficits caused by the increase in temperature.

Study on the Future Climate Change and Its Influence on the Growth Stage and Yield of Wheat in Weifang City

In order to study the trend of climate change in the future in Weifang,and analyze the impact of climate change on the local wheat production,the air temperature and precipitation in Weifang from 2021 to 2050 were simulated by using the regional climate model PRECIS.And then put the meteorological data into the crop model to simulate the growth of wheat under climate change conditions in the future.The results showed that there would be a trend of rising temperature and increasing precipitation in Weifang in the future.Climate warming would result in growth period of wheat to be ahead of schedule and yield reduction.If taking into account the effect of CO2,the yield of wheat would increase.

Impact of Climate Change on Epidemiology of Various Pests of Wheat Crop in Punjab Pakistan

Wheat [Triticum aestivum L. (Poaceae)] is the staple diet of people in Pakistan. It is attacked by many types of pests. Therefore the purpose of this study was to assess the impact of climate change on the ecology and epidemiology of various wheat pests in Punjab, Pakistan. Results indicate that maximum weeds hot spots 242 (5.98%) Phalaris minor, 45 (1.18%) wild oat and 203 (5.01%) broad leaf weeds were noted in 2015. Aphid 31 (0.86%) hot spots were recorded in 2016 while maximum army worm 13 (0.26%) hot spots were noted in 2017. Maximum 70 (1.73%) spots of yellow rust and 85 (2.10%) hot spots of brown rust were observed during 2015 while 84 (4.16%) spots of loose smut were observed during 2017. ANOVA shows that years have no significant difference (P > 0.05) but weeks have significant effect on occurrence of these pest incidences except brown rust. But regression ANOVA was significant (P ≤ 0.05) and regression models equations have been developed on the bases of recorded data. Pest incidence was taken as dependent variable Y and weather factors i.e. minimum temperature as X1, maximum temperature as X2, relative humidity as X3 and rain fall as X4 were taken as independent variables. This study will help in recommendations for moving forward aiming at integration of biology of rust and smut diseases of wheat with changing climate for development of resistant varieties for resilient and durable management of these pathogens.

Impact of Climate Change and Variability on Wheat and Corn Production in Buenos Aires, Argentina

From the Global Historical Climate Network (GHCN-V3), monthly mean summer (DJF) temperature (1856-2012) and total precipitation (1861-2012) are analyzed in correlation with four climate modes and sunspot number to better understand the role of teleconnections on Buenos Aires’ (Argentina) climate. A general increase in temperature and precipitation was observed. Temperature has increased by about 1.8°C and precipitation has increased by about 300 mm in the past century and a half. Indices of Arctic Oscillation (AO), Pacific North American (PNA), Antarctic Oscillation (AAO), and El Nino-Southern Oscillation (ENSO) are evaluated to study their effects on wheat and corn production and export. AO and PNA show strong relationships with precipitation and temperature received. AAO and ENSO show strong negative correlations with precipitation patterns and weak correlations with temperature. Sunspot Number shows a positive correlation with temperature. ENSO phases are strongly linked with the wheat and corn production and export;during El Nino Buenos Aires tends to experience extremely wet summer weather, causing soggy fields and extremely dry summer weather during La Nina causing drought. Both of these conditions result in reducing wheat and corn production and export.

Climate Change Impact on Wheat Production in the Southern Great Plains of the US Using Downscaled Climate Data

Gradually developing climatic and weather anomalies due to increasing concentration of atmospheric greenhouse gases can pose threat to farmers and resource managers. There is a growing need to quantify the effects of rising temperature and changing climates on crop yield and assess impact at a finer scale so that specific adaptation strategies pertinent to that location can be developed. Our work aims to quantify and evaluate the influence of future climate anomalies on winter wheat (Triticum aestivum L.) yield under the Representative Concentration Pathways 6.0 and 8.5 using downscaled climate projections from different General Circulation Models (GCMs) and their ensemble. Marksim downscaled daily data of maximum (TMax) and minimum (TMin) air temperature, rainfall, and solar radiation (SRAD) from different Coupled Model Intercomparison Project GCMs (CMIP5 GCMs) were used to simulate the wheat yield in water and nitrogen limiting and non-limiting conditions for the future period of 2040-2060. The potential impact of climate changes on winter wheat production across Oklahoma was investigated. Climate change predictions by the downscaled GCMs suggested increase in air temperature and decrease in total annual rainfall. This will be really critical in a rainfed and semi-arid agro-ecological region of Oklahoma. Predicted average wheat yield during 2040-2060 increased under projected climate change, compared with the baseline years 1980-2014. Our results indicate that downscaled GCMs can be applied for climate projection scenarios for future regional crop yield assessment.

Validation of AOGCMs Capabilities for Simulation Length of Dry Spells under the Climate Change in Southwestern Area of Iran

Identification and extraction length of dry spells in arid and semi-arid regions is very important. Thus, the use of climate change prediction models for study the behavior of the climatic parameters in the future time is inevitable. With recognition of the spatial and temporal behavior variables such as precipitation, we can prevent from destructive effects. In this research, the performance of Atmosphere-Ocean General Circulation Models (AOGCMs) was evaluated for simulation length of dry spells in the south-western area of Iran. The results show that the length of dry spell is relatively decreased in cold seasons (autumn and winter) and increased in the warm season (spring and summer) in both A2 and B2 Scenarios. The length of the dry spell on monthly scale for scenario A2 is 6% (equivalent to 2 days) and for scenario B2 is 9 percent (approximately 2.4 day) increased compared to the baseline period. For assess the uncertainty, AOGCMs were weighting. The results show that the best model for simulation of dry spells is HADCM3 and GFCM2.1, because the results have a less error. On the other hand, NCCCSM have the lowest weight for simulation dry spells in both scenarios.

Quantitative Simulation of Dynamic Changes in Cultivated Land in Areas of Reclamation and Returning Cultivated Land to Forest or Pastures under RCPs Climate Scenarios

Northeast China as one of important agricultural production bases is an area under reclamation and returning cultivated land to forests or pastures. Therefore, it is of great practical significance in guaranteeing the sustainable development and national food security to study the spatial and temporal variation of cultivated land in Northeast China under future climate scenarios. In this study, based on data of land use, natural environment and social-economy, dynamics of land system（DLS） model was used to to simulate the spatial distribution and changing trends of cultivated land in the typical areas of reclamation and returning cultivated land to forest or pastures in Northeast China during 2010-2030 under land use planning scenario and representative concentration pathways（RCPs） scenarios quantitatively.The results showed that the area of cultivated land had an overall decreasing trend under the land use planning scenario, but the area of upland field increased slightly from 2000 to 2010 and then declined greatly, while the area of paddy field continuously declined from 2000 to 2030. Under the Asia-Pacific Integrated model（AIM）scenario, the total area of cultivated land had a tendency to increase considerably,with the upland field expanding more obviously and the paddy field declining slightly.In addition, the cultivated land showed a greater decreasing trend under the model for energy supply strategy alternatives and their general environmental impact（MESSAGE） scenario compared to the land use planning scenario. Moreover, analysis on the conversion between different land use types indicated that the reclamation and returning cultivated land to forests or pastures was likely to continue under future scenarios, but the frequency of occurrence could decrease as the time goes by. The conclusions can provide significant decision-making information for the rational agricultural planning and cultivated land protection in Northeast China to adapt to the climate change.

Simulation of Climate Change Induced by CO_2 Increasing for East Asia with IAP/ LASG GOALS Model

Two simulations, one for the control run and another for the perturbation run, with a global coupled ocean-atmosphere-land system model (IAP/LASG GOALS version 4) have been carried out to study the global warming, with much detailed emphasis on East Asia. Results indicate that there is no climate drift in the control run and at the time of CO, doubling the global temperature increases about 1.65 degreesC. The GOALS model is able to simulate the observed spatial distribution and annual cycles of temperature and precipitation for East Asia quite well. But, in general, the model underestimates temperature and overestimates rainfall amount for regional annual average. For the climate change in East Asia, the temperature and precipitation in East Asia increase 2.1 degreesC and 5% respectively, and the maximum warming occurs at middle-latitude continent and the maximum precipitation increase occurs around 25 degreesN with reduced precipitation in the tropical western Pacific.

Simulation of Climate Change Scenarios for Phu Luong Watershed in Northern Viet Nam

The purpose of this paper is to apply ＂LARS-WG （Long Ashton Research Station--Weather Generator）＂ model to simulate the climate change scenarios for Phu Luong watershed in northem Viet Nam. Results indicated that LARS-WG adequately predicted precipitation and temperature with R2 = 0.80 and 0.73, respectively. Likewise, p-value of F test = 0.062 and p-value of t test = 0.885 for precipitation, meanwhile, for temperature are 0.092 and 0.564 at 0.05 level of significance, respectively. Moreover, results also stated that mean annual precipitation increases 1.62%, 2.17% and 3.96% and mean annual temperature increases 0.6 ℃, 0.8 ℃ and 1.05 ℃ in 2020, 2030 and 2040, respectively, with respect to those from baseline periods. This study also showed that LARS-WG model was used successfully for Viet Nam＇s watershed conditions.

Simulation of Climate Change Induced by CO2 Increasing for East Asia with IAP/ LASG GOALS Model

Two simulations, one for the control run and another for the perturbation run, with a global coupled ocean-atmosphere-land system model(IAP / LASG GOALS version 4) have been carried out to study the global warming, with much detailed emphasis on East Asia. Results indicate that there is no climate drift in the control run and at the time of CO2 doubling the global temperature increases about 1.65℃. The GOALS model is able to simulate the observed spatial distribution and annual cycles of temperature and precipitation for East Asia quite well. But, in general, the model underestimates temperature and overestimates rainfall amount for regional annual average. For the climate change in East Asia, the temperature and precipitation in East Asia increase 2.1 ℃ and 5% respectively, and the maximum warming occurs at middle-latitude continent and the maximum precipitation increase occurs around 25°N with reduced precipitation in the tropical western Pacific.

Wheat Breeding Strategies under Climate Change based on CERES-Wheat Model

Climate change has inevitably had a negative impact on agricultural production and food security.Crop breeding improvement is an efficient option to adapt to future climate and increase grain production.To study the potential to provide valuable advice for breeding under climate change condition,the crop growth model was used as basis to investigate,the effects of the cultivar genotype parameters of the crop estimation through resource and environment synthesis-wheat(CERES-Wheat)model on yield under different climate scenarios.In this study,solar radiation had a positive effect on the yield of winter wheat,while the effects of daily temperature change conditions on yield were vague,particularly under a change in daily maximum temperature.For the seven cultivar genotype parameters in the CERES-Wheat model,the yield had an approximately linear increasing relationship with kernel number(G1)and kernel size(G2).Vernalization days(P1V)had a fluctuating effect on winter yield without an evident unidirectional tendency.The yield of winter wheat increased with an increase in photoperiodic response(P1D)when P1D values varied from 64.81 to 79.81.Phyllochron interval(PHINT)had a positive impact on the yield of winter wheat.This study presented the potential benefits of the crop growth model to provide directional suggestions for crop breeding.

Assessing the impact of climate change on agricultural production in central Afghanistan

Afghanistan has faced extreme climatic crises such as drought,rising temperature,and scarce precipitation,and these crises will likely worsen in the future.Reduction in crop yield can affect food security in Afghanistan,where the majority of population and economy are completely dependent on agriculture.This study assessed the interaction between climate change and crop yield in Kabul of Afghanistan during the reference(1990–2020)and future(2025–2100)periods.Climate data(1990–2020)were collected from four meteorological stations and three local organizations,and wheat yield data(1990–2020)were acquired from the United States Agriculture Department.Data during the reference period(1990–2020)were used for the validation and calibration of the statistical downscaling models such as the Statistical Downscaling Model(SDSM)and Long Ashton Research Station Weather Generator(LARS-WG).Furthermore,the auto-regression model was used for trend analysis.The results showed that an increase in the average annual temperature of 2.15℃,2.89℃,and 4.13℃will lead to a reduction in the wheat yield of 9.14%,10.20%,and 12.00%under Representative Concentration Pathway(RCP)2.6,RCP4.5,and RCP8.5 during the future period(2025–2100),respectively.Moreover,an increase in the annual maximum temperature of 1.79℃,2.48℃,and 3.74℃also causes a significant reduction in the wheat yield of 2.60%,3.60%,and 10.50%under RCP2.6,RCP4.5,and RCP8.5,respectively.Furthermore,an increase in the annual minimum temperature of 2.98℃,2.23℃,and 4.30℃can result in an increase in the wheat yield of 6.50%,4.80%,and 9.30%under RCP2.6,RCP4.5,and RCP8.5,respectively.According to the SDSM,the decrease of the average monthly precipitation of 4.34%,4.10%,and 5.13%results in a decrease in the wheat yield of 2.60%,2.36%,and 3.18%under RCP2.6,RCP4.5,and RCP8.5,respectively.This study suggests that adaptation strategies can be applied to minimize the consequences of climate change on agricultural production.