Over the last 100 years, the global average surfacetemperature has risen by almost 0. 74℃, and theheating rate is twice as high in the second half ofthat period(Qin and Luo, 2008). In the context ofglobal warming, the annual mean surface temperaturein China has increased significantly during the past50 years. At the same time, the national mean temperaturehas increased by 1. 1℃. This magnitude ofincrease in surface temperature is greater than that ofthe Northern Hemisphere and the globe(Ding et al., 2006), and the trend is expected to continue during thenext 20–100 years(Tang et al., 2011). The costs and benefits of climate change are not equally distributedaround the world(Darwin et al., 1995). Developedcountries can benefit from climate change through risingcrop production while in developing countries productionbecomes limited; in other words, disparities incereal production between the developed and developing worlds will likely increase under global warming(Rosenzweig and Parry, 1994). Climate change canhave adverse effects on agricultural production, and ultimately threatens food security. Therefore, studyinghow agricultural production can adapt under climatechange is an important topic in order to achieveagricultural sustainable development. To date, a varietyof adaptation options have been proposed as havingthe potential to reduce the vulnerability of agroecosystemsto risks related to climate change(Smit and Skinner, 2002), some of which are already well developed, such as the adjustment of sowing date, plantingresistant varieties, and farm management(Lü et al., 2010).
Northeast China is an important agricultural region and occupies a key strategic position in the grainmarket. The annual output of maize in this region isalmost 40 million tons, accounting for approximately30% of the total maize yield in China(Ma et al., 2008). On one h and , the warming climate serves to extend thegrowing season in Northeast China, which is conduciveto an improvement in total grain production; on theother h and , the warmer and drier conditions presentgreat challenges to maize production. For example, the grain-fill period of maize can shorten, meaningthat kernel weight and ultimately yield can decrease. There have been many studies carried out that have focusedon how maize varieties in Northeast China couldadapt to future climate change, and the results havelargely showed that early-maturing and mid-maturingvarieties will be replaced by late-maturing varieties undera warming climate(Jia and Guo, 2009; Zhao et al., 2009). Furthermore, in areas that are originallycooler, grain yields could benefit from a transition tonew varieties; while in areas that are already relativelywarm, such a transition may not have much of an effect(Yuan et al., 2012).
Therefore, how to make full use of climatic resourcesto maximize maize yields is an important topicof research. Climatic productivity can not only revealthe relationship between crop’s growth and development, yield and climatic resources, but also help todiscover the main yield-limiting factors and reflect resourceutilization(Liu, 2010). In the present study, we use daily meteorological data for the period 1981–2100, from simulations by RegCM3 under the A1Bfuture-climate scenario, to quantitatively assess thecontributions of different climate-change adaption options(e. g., adjustment of maize variety layout, useof resistant varieties)to potential increases in maizeproductivity. Based on the results, we also discusspossible future development directions with respect tomaize varieties in Northeast China. Furthermore, beyondNortheast China, the study provides a theoreticalbasis for agricultural adaptation options to climatechange and the reasonable utilization of climatic resourcesfor realizing high and stable maize yields. 2. Data and methods2. 1 Data
We chose Heilongjiang, Jilin, and Liaoningprovinces as our study areas. Meteorological data forNortheast China covering the period 1981–2100, assimulated by RegCM3 under the A1B future-climatescenario, are used. These data include daily averagetemperature, daily maximum and minimum temperature, daily total radiation, daily net radiation, dailyaverage wind speed at 2 m above ground level, dailyrelative humidity, precipitation, etc., and are availableon a 0. 25° × 0. 25° grid. Error correction for thegridded data was performed as detailed in Yuan et al. (2012). The growing seasons of maize for the period1981–2010 are provided by the National MeteorologicalInformation Center. 2. 2 Methods2. 2. 1 Thermal index
Different maize cultivars require differentamounts of cumulative temperature during the growingseason(Gong, 1988). Based on previous work, we divided maize varieties into four types: earlymaturing, mid-maturing, mid-late-maturing, and latematuring(Wang et al., 2011). Then, according toactual maize-growth data for Northeast China during1981–2010, we established the statistical relationshipbetween each variety type and its required cumulativetemperature in corresponding stages of the growing season. Jiayin agro-meteorological station waschosen as a typical station representing early-maturingvarieties; Hailun agro-meteorological station was chosenas a typical station representing mid-maturing varieties; Changling and Harbin agro-meteorological stationswere chosen as typical stations representing midlate-maturing varieties; and Wafangdian, Fuxin, and Zhuanghe agro-meteorological stations were chosen astypical stations representing late-maturing varieties. The resulting thermal index values for the differentvarieties in different stages of the growing season aredetailed in Table 1.2. 2. 2 Resistant varieties
Like any other crop, maize grows more vigorously and accumulates more dry matter in a suitableenvironment. Under unsuitable conditions, thecrop’s growth and development will be inhibited, and dry matter accumulation will be less. Therefore, wechanged the basic temperature(Table 2) and waterrequirements to generate theoretical maize varietiesadapted to future climate, and we then used thesehigh-temperature and /or drought-resistant varieties tomodel the increase in climatic productivity. The nineproposed resistant varieties in the context of days requiredfor growth remaining the same are detailed inTable 3. Use of these varieties as agricultural adaptationoptions to climate change was then evaluated.
|T1, T2, and T3 are high-temperature resistant varieties; T4, T5, and T6 are drought-resistant varieties; T7, T8, and T9 are bothhigh-temperature- and drought-resistant varieties; Tm is the crop water requirement; other symbols are the same as in Table 2.|
The Food and Agriculture Organization-Agro-Ecological Zone(FAO-AEZ)model is a commonlyused method to calculate crop productivity under differentclimates. In different stages of the growing season, maize requires different quantities of climaticresources. Therefore, in order to make the resultsmore realistic, the growth period of maizewas divided into the following four stages: sowingemergence, emergence-jointing, jointing-heading, and heading-maturity. Photosynthetic productivity, photosyntheticthermal productivity, and climatic productivityin these different stages of the growing seasonwere calculated separately. Then, the crop potentialproductivity during the whole period was determined. The specific quantities calculated were as follows:
a)Photosynthetic productivityLiu et al., 2001), F is cloud coverage, Rse(MJ m−2)is the maximum effective shortwaveradiation on a clear day, and Rs is the observed radiation(MJ m−2).
b)Photosynthetic thermal productivity
Photosynthetic thermal productivity is the yielddetermined mostly by sunlight and thermal resources. First, we calibrated y0 and yc of the reference crop bythe values of Ym at different temperatures. When Ym ≥ 20 kg hm−2 h−1,
When Ym < 20 kg hm−2 h−1,
The calculation method for photosynthetic thermalproductivity was as follows:
where Ymp is photosynthetic thermal productivity(kghm−2). CL is the correction coefficient of LAI(Wang et al., 2008). The change in LAI is a single peak curveduring the whole growing season and LAI generallyreaches its maximum value in the flowering stage ofthe growing season. Ymp should be corrected whenLAI < 5. In this study, the values of LAI were obtainedfrom Yuan and Guo(2010). CN is the correctioncoefficient of net dry-matter production. CN is0. 6 when the average temperature is < 20℃, and itis 0. 5 when the average temperature is ≥ 20℃(Zhao and Zhao, 1988). CH is the harvest index, for whichthe value in this study is 0. 55(Liu Wei et al., 2010). Finally, G is the number of days in the growing season.
Climatic productivity is the highest per hectareyield obtained by radiation, temperature, and precipitationunder the assumption that soil fertility and agro-technical measures are optimal for crop growth(Wang et al., 2003). The calculation method was asfollows:Wang Xiufen et al., 2012); Tm(mm)is crop water requirement; kc is the crop coefficientobtained by vegetation fractional cover duringdifferent periods(Sun, 2008; Tian et al., 2009); and ET0 is the reference crop’s evapotranspiration computedby the Penman-Monteith model(Liu Yuan et al., 2010).
ETa(mm)is the actual evapotranspiration determinedby the quantitative relation between availablewater(precipitation and previous soil water storage) and crop water requirement. ETa was calculated bytaking 10 days as the unit of time:Zhao et al., 2011). 3. Results and analysis3. 1 Agro-climatic resources in Northeast China
Agro-climatic resources include thermal, water, and light resources. They reflect the influence of climatechange on agricultural production. Maize inNortheast China grows mainly over the period fromMay to September. The ≥ 10℃ day cumulative temperature and the sum of mean air temperature duringthat period can be used to reflect the heat conditionsduring the growing season(Ma et al., 2000). Likewise, total precipitation from May to September, probable evaporation, and aridity index can be usedas indicators of drought. The aridity index is definedas the ratio of probable evaporation and precipitation, meaning the lower the aridity index value is, the morehumid the atmosphere is, and vice versa. To discusslight resources, solar radiation needs to be considered; changes in light resources can be expressed in terms oftotal radiation during the growing season.
Table 4 shows the predicted changes in climaticresources during 1981–2100, based on the RegCM3data. As can be seen, the sum of mean air temperaturefrom May to September and the ≥ 10℃ day accumulatedtemperature significantly increase. However, precipitation during the growing season increases lesssignificantly in the model. Meanwhile, the rising temperaturecauses a continuous increase in atmosphericevaporation, showing a tendency toward an arid climate. Total radiation during the growing season from1981 to 2100 also increases. In particular, the modelpredicts that total radiation will increase significantlyduring 2041–2070, but the rate of change will thenslow during 2071–2100.
|* 0. 05 significance level; ** 0. 01 significance level.|
According to the different cumulative requirementsof the different varieties of maize, we produceda theoretical distribution for maize in Northeast Chinafor the period 1981–2100 and calculated the potentialclimate productivity on that basis. The results showthat radiation has no significant influence on photosyntheticthermal productivity and climatic productivityin most periods. Temperature and precipitationare the main meteorological factors affecting climaticproductivity for maize. Photosynthetic thermalproductivity in Northeast China shows an S-shapedcurve over the entire period(i. e., 1981–2100). Climaticproductivity changes from 5921. 3 to 15559. 4 kghm−2 with large interannual variations. Photosyntheticthermal productivity is low during 1981–2010(base period), and in one particular year(1993)theair temperature in most areas of China was lower thanusual. This was a cold summer in the northeast region, and the photosynthetic thermal productivity reachedits lowest value of 11895. 5 kg hm−2. With the increasein temperature from 2011 to 2070, early-maturing varietiesare gradually replaced by late-maturing varietiesto make full use of the thermal resources, and thephotosynthetic thermal productivity increases rapidly. However, when the temperature rises beyond the upperlimit of optimum temperature for maize after 2071, the photosynthetic thermal productivity begins to decrease. Unsuitable water resource is an importantfactor limiting climatic productivity during the entiremodeled period. Climatic productivity accounts forabout 64. 6% of the photosynthetic thermal productivity.
Climatic productivity shows a south-north decliningtrend during the base period. Higher values arefound in the southeast of Liaoning and the Tieling-Fushun area, and lower values appear mainly in thenorthwest of Jilin and the west of Heilongjiang. Themaximum value is almost three times larger than theminimum value(Fig. 1). Climatic productivity in thewestern areas during 2011–2040 is lower than that duringthe base period because of the increased potentialevaporation and high-temperature weather. The resultsindicate that, during 2011–2040, spring maizecould be planted in the Zhangguangcai and LaoyeMountains, where the climate is not currently(i. e., inthe base period)suitable for maize growth. The nongrowingareas will be reduced in the Changbai Mountains, and the climatic productivity will increase in theXiao Higgan Mountains. After 2041, late-maturingvarieties could be planted in most areas of NortheastChina, and the climatic productivity largely increasesin the east of Jilin and in most areas of Heilongjiang. Climatic productivity decreases by > 20% under climatewarming and drying in western areas. Furthermore, the distribution of varieties in western areaswould no longer need to be adjusted. Both high and low value areas are reduced. The results show thatthe climatic productivity in Liaoning Province, havingpreviously had the highest values, will be lowerthan that in Jilin Province during 2071–2100; the disparitiesbetween these provinces will be narrowed.
With the plantable areas for late-maturing varietiesshifting northward and enlarging in the east, thepotential climatic productivity increases in the north and central Heilongjiang, and the east of Jilin. Meanwhile, climate productivity decreases in the southeastof Liaoning, the Changchun and Gannan-Harbin area, and Heilongjiang, as the climatic resources becomemismatched. These results indicate that an increase inheat resources could favor agricultural production inareas that currently experience heat shortages. However, soil evaporation and plant transpiration wouldcontinue to increase under climate warming, such thatprecipitation is unlikely to meet crop water requirementswithout irrigation. The shift to a warmer and drier climate will therefore bring severe challenges toagricultural production, especially in overheated areas. Therefore, we need to consider agricultural adaptationoptions in order to increase the utilization ofclimatic resources against a background of climatechange. 3. 3 Effects of developing resistant varieties onclimatic productivity
The warming and drying climate is an importantfactor that limits the potential of increasing yields inan overheated area. The current variety of maize is unlikelyto be able to adapt to a future warmer climate. Based on adjusting the species distribution, our resultsindicate that developing resistant varieties would helpincrease climatic productivity(Fig. 2), and the influenceis closely related to the allocation of climaticresources. The extra output of high-temperatureresistantvarieties(T1–T3)increases with time. Thechanges in Yp of drought-resistant varieties(T4–T6)are consistent with that of the current variety(T0), while Yp of T4–T6 is higher than that of T0, with theextra output fluctuating during 2011–2100. The abilityof both high-temperature- and drought-resistantvarieties(T7–T9)to adapt to climate change is betterthan that of T1–T6. High-temperature resistance increasesclimatic resources utilization to a large degreeas the climate becomes warmer and drier during 2071–2100. The higher values of Yp for T7–T9 compared toT0 show a significant increase.3. 3. 1 Variance analysis of climatic productivity ofdifferent cultivation patterns
Under the scenario of a growing mismatch of climaticfactors, to slow the downward trend of climaticproductivity, we need to enhance resistance from thepoint of view of the basic temperatures and water requirements. In order to further analyze how much and to what extent the basic temperature and waterrequirements would need to be adjusted to makethe difference between the current variety and the resistantvarieties statistically significant, we perform avariance analysis of climatic productivity of the currentvariety and the resistant varieties(Table 5). Ascan be seen from the results, during 2071–2100, theclimatic productivity of T2 and T3 is significantly differentfrom T0, but the difference between T2 and T3is not significant. The climatic productivity of T4 and T5 is not significantly higher than that of T0. Whenthe water requirement is reduced to 94%(T6), theclimatic productivity is significantly higher than thatof T0 during 2011–2100. Both high-temperature- and drought-resistant varieties largely decrease the adverseeffects of the warming/drying climate. The differencebetween T7 and T0 is significant during 2071–2100, T8 is significantly different from T0 after 2041, and the climatic productivity of T9 is significantly differentfrom T0 after 2011.
|The superscripts a, b, c, and d are the names of the similar subsets at the 95% confidence level. Values in the same row withdifferent superscript letters are significantly different.|
Climatic productivity is the highest biomass yieldobtained by the full utilization of thermal, water, and light resources, and the value can be used to reflectthe suitable grade of meteorological conditions in aparticular region. In this study, climatic productivityis classified into five groups through cluster analysis(Table 6): unavailable(value 1), relatively unavailable(value 2), relatively available(value 3), available(value 4), and most available(value 5).
According to the variance analysis, the differencebetween the resistant varieties T2, T6, and T9 and the current variety in terms of meteorological suitabilitywas analyzed and the results are shown in Fig. 3. The most available areas for T0 during 2011–2040 aremainly in the east of Liaoning and central Jilin; theavailable areas are in central Liaoning, east to Dunhua(except the area around the Changbai Mountains), central Jilin, and eastern Heilongjiang; the relativelyavailable areas are in southwestern Liaoning, the areaswest to Changchun, and the areas south to Humain and western Heilongjiang; a relatively unavailablearea is around Songnen Plain; and the regions inthe Changbai Mountains and northern Heilongjiang, with their scarce heat resources, are classified as unavailable for maize growth. The difference betweenT2 and T0 is not significant in terms of the distributionof meteorological suitability in the period 2011–2040. Meanwhile, the available area for T6 exp and s:the western boundary grows to Fuxin from Xinmin and central Liaozhong, the northern boundary extendsnorthward in Heilongjiang, meteorological suitabilityincreases in Qinan and central Suiling, and the westernboundary of the relatively unavailable area shiftswestward by 0. 4° of longitude. Climate suitability forT9 increases the most, with the northern boundary ofavailable area moving from 44. 86° to 45. 88°N.
The suitability of meteorological conditions decreasesdue to increasing temperature and less precipitationduring 2041–2070. The most available and available areas for T0 decrease, while the relativelyavailable and relatively unavailable areas increase. Meteorological suitability increases less when only thebasic temperature requirements are adjusted; whenthe crop water requirement is reduced, the climaticsuitability rises. The northern boundary of the mostavailable area shifts from 44. 20° to 44. 58°N, the availablearea increases, and the relatively unavailable areadecreases in Heilongjiang. Climatic resources utilizationwill improve after adjusting the basic temperature and water requirements, but the difference between T9 and T6 in terms of the distribution of meteorologicalsuitability is not significant.
The climatic suitability for T0 during 2071–2100is higher than that during 2041–2070, with precipitationincreasing. High temperature is also the mainfactor limiting the increase of potential productivityduring 2071–2100, suggesting that enhancing the toleranceof maize to high temperatures could increasethe climatic productivity in this period. The availablearea in Huachuan and Jixian in Heilongjiang Provincefor T2 is larger than T0, and the available area is reclassifiedas the most available in southern Yichuan. The climatic suitability for T6 changes markedly inHeilongjiang: the available area exp and s, and the relativelyavailable areas transform into available areasin southern Huanan, southern Huachuan, and in partsof southern Jixian. The boundary of the availablearea shifts westward. The available area for T9 furtherexp and s; the relatively available areas transforminto available areas in Hulin and Mishan; the availablearea exp and s to central Huanan and Jixian; theboundary of the most available area advances westward; and the boundary of the relatively unavailablearea shifts westward by about 1. 3° of longitude.
Overall, the results suggest that enhancing stresstolerance in maize would be beneficial for climatechangeadaptation through an increase in climatic resourcesutilization. 4. Conclusions and discussion
The impact of cultivar-based adaptation measureson increasing the potential productivity of maize undera warmer and drier climate was quantitatively evaluatedby using the FAO-AEZ model. The results show that:
(1)Heat resources are likely to change significantlyin Northeast China under climate warming, with the ≥ 10℃ day cumulative temperature and thesum of temperature from May to September increasing. Precipitation in the growing season shows a nonsignificantincreasing trend with a large degree of interdecadalfluctuation. Total radiation is predicted toincrease significantly during 2041–2070. Thermal conditionsare found to improve over Northeast China asthe climate warms, but precipitation may not compensatefor the increasing evapotranspiration, the aridityindex could increase, and the climate is likely to begenerally warmer and drier.
(2)The increase in heat resources could bringfavorable conditions for agricultural production inNortheast China. In the model’s results, the plantingboundaries for different patterns extend eastward and northward. The instability in precipitation leads tounstable climatic productivity. The climatic productivitychanges from 5921. 3 to 15559. 4 kg hm−2; becausethe computation models are different from others, this value is lower than that in a previous study(Yuan et al., 2012). The increased value of photosyntheticthermal productivity is not enough to offset thenegative effects of lower water suitability, and the increasein climatic productivity is limited during thestudy period. However, we find great potential for increasedclimatic productivity in the future if accompaniedby irrigation. Maize climatic productivity graduallyimproves due to climate warming in places whereheat is originally insufficient. Meanwhile, the increaseof heat resources has an adverse effect on maize growth and development in places that are already relativelyhot, especially in Liaoning Province, resulting in a declineof climatic productivity. The change in climaticproductivity in the southwestern area is opposite tothe changes in the southeast and northwest, and thedisparities between high and low values will be narrowed.
(3)As the climate becomes warmer and drier, enhancingthe stress tolerance of maize could increase itsproductivity and the climatic resources utilization effectively. The warmer and drier the climate becomes, the greater the increase will be in terms of the rangeof production potential of resistant varieties, especiallyhigh-temperature-resistant varieties, whose productivityis found to rise obviously with time. Thecombined effect of high-temperature- and droughtresistantvarieties on increasing productivity is betterthan high-temperature- or drought-resistant varietiesonly. The suitability of meteorological conditions isgraded on the basis of the production potential values, and the results show that the “available” areacould exp and by enhancing stress tolerance, while the“unavailable” area may shrink.
(4)Solar radiation is an important resource affectingagricultural production because it has a directinfluence on photosynthetic productivity, and thus ultimatelyclimatic productivity as well. If we use thebase radiation and the simulation from RegCM3 asthe initial conditions to compute the potential productivity, the changing trend of Yp is similar, and thedifferences in values are not significant. The resultsshow rich solar resources in Northeast China, suggestingthat it is not the main factor limiting agriculturalproduction. This is consistent with the previous studyby Wang Ming et al. (2012).
Crop physiological characteristics during differentstages of the growing season are considered. Growth and development as well as yield production are regardedas dynamic processes, and meteorological factorsaffecting crop growth and yield are comprehensivelyanalyzed in the AEZ model, which has beenwidely applied internationally in theoretical studies. Actual maize production is also affected by soil, agriculturaltechniques, socioeconomics, natural disastersetc. In this study, only light, heat, and water resourcesare taken into consideration to calculate the climaticproductivity, i. e., it is an ideal output. By takingother factors affecting agricultural production into account, the calculated values of climatic productivitycould be more accurate.
The abilities of three kinds of resistant varietiesto adapt to climate change are evaluated in our study. We assume that the upper limit of optimum temperature and the upper limit of temperature wouldincrease by 1, 2, and 3℃, respectively, in these hightemperature-resistant varieties, but this assumptionis not based on future temperature-change scenarios. How to better design the basic parameters of temperaturerequirements of resistant varieties will be animportant focus of our work in the future. In addition, the degree of stress tolerance to high temperature and drought is regarded as the same in different regions. Actually, climatic resources vary on the regional scale, and thus the main factors restricting climatic productivityare often different in different areas. Howto determine the range of optimum temperatures ofhigh-temperature- and drought-tolerant varieties indifferent regions needs to be further studied.
|||Darwin, R., M. Tsigas, J. Lewandrowski, et al., 1995: World Agriculture and Climate Change: Economic Adaptations. Agricultural Economic Report No.703, America, Washington, United States Department of Agriculture, 1-86.|
|||Ding Yihui, Ren Guoquan, Shi Guangyu, et al., 2006: National assessment report of climate change. I: Climate change in China and its future trend. Adv. Climatic Res., 2, 3-8. (in Chinese)|
|||Gong Shaoxian, 1988: Crop and Meteorology. China Agricultural University Press, Beijing, 245-253. (in Chinese)|
|||Jia Jianying and Guo Jianping, 2009: Studies on climatic resources change for maize over last 46 years in Northeast China. Chinese J. Agrometeor., 30, 302-307. (in Chinese)|
|||Liu Ji, 2010: Research of climatic production potential of cotton in China based on the AEZ model. Master dissertation, Dept. of Cartography and Physics, Henan University, China, 76 pp. (in Chinese)|
|||Liu Jiandong, Zhou Xiuji, and Yu Qiang, 2001: Modification of the basic parameters in FAO productivity model. J. Nat. Resour., 16, 240-247. (in Chinese)|
|||Liu Wei, Lü Peng, Su Kai, et al., 2010: Effects of planting density on the grain yield and source-sink characteristics of summer maize. Chinese J. Appl. Ecol., 21, 1737-1743. (in Chinese)|
|||Liu Yuan, Wang Ying, and Yang Xiaoguang, 2010: Trends in reference crop evapotranspiration and possible climatic factors in the North China Plain. Acta Ecologica Sinica, 30, 923-932. (in Chinese)|
|||Lü Qintang, Wang Junru, and Guo Yingwei, 2010: Effects of climate change on agricultural production and countermeasures. Modern Agricult. Sci. Tech., 39, 344-348. (in Chinese)|
|||Ma Shuqing, An Gang, Wang Qi, et al., 2000: Study on the variation laws of the thermal resources in maize growing belt of Northeast China. Resources Science, 22, 41-45. (in Chinese)|
|||—-, Wang Qi, and Luo Xinlan, 2008: Effect of climate change on maize (Zea mays) growth and yield based on stage sowing. Acta Ecologica Sinica, 28, 21312139. (in Chinese)|
|||Qin Dahe and Luo Yong, 2008: Causes of global climate change and future trends. Impact of Science on Society, 28, 16-21. (in Chinese)|
|||Rosenzweig, C., and M. L. Parry, 1994: Potential impact of climate change on world food supply. Nature, 367, 133-138.|
|||Smit, B., and M. W. Skinner, 2002: Adaptation options in agriculture to climate change: Atypology. Mitigation and Adaptation Strategies for Global Change, 7, 85-114.|
|||Sun Weiguo, 2008: Summary on Climate Resources. China Meteorological Press, Beijing, 180-182. (in Chinese)|
|||Tang Xu, Yang Xuchao, Tian Zhan, et al., 2011: Impacts of climate change on agro-climatic resources in China. Resources Science, 33, 1962-1968. (in Chinese)|
|||Tian Jing, Su Hongbo, Sun Xiaomin, et al., 2009: The estimation of vegetation fractional cover and its affecting factors based on surface experiments. Remote Sensing for Land and Resources, 21, 1-6. (in Chinese)|
|||Wang Ming, Li Xiujun, Liu Xingtu, et al., 2012: Potential of agricultural climatic productivity and requirement rate of climatic resources in northeastern China. Soil and Crop, 1, 27-33. (in Chinese)|
|||Wang Peijuan, Liang Hong, Li Hanjun, et al., 2011: Influences of climate warming on key growth stages and cultivated patterns of spring maize in Northeast China. Resources Science, 33, 1976-1983. (in Chinese)|
|||Wang Suyan, Huo Zhiguo, Li Shikui, et al., 2003: Water deficiency and climatic productive potentialities of winter wheat in North China: Study on its dynamic change in recent 40 years. Journal of Natural Disasters, 12, 121-130. (in Chinese)|
|||Wang Xiufen, You Fei, and Yang Yanzhao, 2012: Analysis of maize potential productivity change based on AEZ model in Heilongjiang Province. Journal of Northwest Agriculture and Forestry University (Nat. Sci. Ed.), 40, 59-64. (in Chinese)|
|||Wang Xueqiang, Jia Zhikuan, and Li Yibing, 2008: Evaluations on the productive potential of wheat based on AEZ model in Henan Province. Journal of Northwest Agriculture and Forestry University (Nat. Sci. Ed.), 36, 85-90. (in Chinese)|
|||Wang Zongming, Zhang Bai, Zhang Shuqing, et al., 2005: Studies on agricultural climatic potential productivity and natural resources utilization ratio in Songnen Plain of Heilongjiang Province. Chinese J. Agrometeor., 26, 1-6. (in Chinese)|
|||Yuan Bin, Guo Jianping, Ye Mingzhu, et al., 2012: Variety distribution pattern and climatic potential productivity of spring maize in Northeast China under climate change. Chinese Sci. Bull., 57, 3497-3508.|
|||Yuan Dongmin and Guo Jianping, 2010: Numerical simulation of impact of CO2 enrichment on maize growth in Northeast China. J. Nat. Resour., 25, 822-829. (in Chinese)|
|||Zhao An and Zhao Xiaomin, 1988: Analysis on the modeling and application of calculation of potential net biomass and potential yield through FAOAEZ methodology. Acta Agriculturae Universitatis Jiangxiensis, 20, 120-125. (in Chinese)|
|||Zhao Junfang, Yang Xiaoguang, and Liu Zhijuan, 2009: Influence of climate warming on serious low temperature and cold damage and cultivation pattern of spring maize in Northeast China. Acta Ecologica Sinica, 29, 6544-6551. (in Chinese)|
|||—-, Guo Jianping, Wu Dingrong, et al., 2011: Climatic potential productivity of winter wheat and summer maize in Huanghuaihai Plain in 2011-2050. Chinese J. Appl. Ecology, 22, 3189-3195. (in Chinese)|