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1 NO.3 XU Yanhong, GUO Jianping, ZHAO Junfang, et al. 469 Scenario Analysis on the Adaptation of Different Maize Varieties to Future Climate Change in Northeast China XU Yanhong (Mòù), GUO Jianping (Hï ), ZHAO Junfang (ëd ), and MU Jia (; Z) Chinese Academy of Meteorological Sciences, Beijing (Received July 10, 2013; in final form February 20, 2014) ABSTRACT Based on gridded meteorological data for the period from the RegCM3 regional model, the changing trends of climatic resources in Northeast China are analyzed, and the distributions of maize varieties are accordingly adjusted. In order to explore the effects of different adaptation countermeasures on climatic productivity and meteorological suitability in the future, maize cultivars with resistance to high temperatures and/or drought are selected. The results show that, in the future, there is likely to be a significant increase in thermal resources, and potential atmospheric evaporation will increase correspondingly. Meanwhile, radiation is predicted to increase significantly during in the growing season. However, changes in precipitation are unlikely to be sufficient enough to offset the intensification in atmospheric evaporation caused by the temperature increase. Water resources and high temperatures are found to be the two major factors constraining grain yield. The results also show that the warming climate will be favorable for maize production where thermal resources are already limited, such as in central and northern Heilongjiang Province and eastern Jilin Province; while in areas that are already relatively warm, such as Liaoning Province, climatic productivity will be reduced. The climatic productivity and the meteorological suitability of maize are found to improve when the planting of resistant varieties is modeled. The utilization of agricultural climatic resources through the adaptation countermeasures of maize varieties is to increase obviously with time. Specifically, maize with drought-resistant properties will have a marked influence on meteorological suitability during , with suitable areas expanding. During , those maize varieties with their upper limit of optimum temperature and maximum temperature increased by 2, or water requirement reduced to 94%, or upper limit of optimum temperature and maximum temperature increased by 1 and water requirement reduced to 98%, all exhibit significant differences in climatic potential productivity, compared to the present-day varieties. The meteorological suitability of maize is predicted to increase in some parts of Heilongjiang Provine, with the eastern boundary of the unavailable area shifting westward. Key words: climate change, Northeast China, variety adaptation countermeasure, Agro-Ecological Zone (AEZ) model, climatic productivity Citation: Xu Yanhong, Guo Jianping, Zhao Junfang, et al., 2014: Scenario analysis on the adaptation of different maize varieties to future climate change in Northeast China. J. Meteor. Res., 28(3), , doi: /s Introduction Over the last 100 years, the global average surface temperature has risen by almost 0.74, and the heating rate is twice as high in the second half of that period (Qin and Luo, 2008). In the context of global warming, the annual mean surface temperature in China has increased significantly during the past 50 years. At the same time, the national mean temperature has increased by 1.1. This magnitude of increase in surface temperature is greater than that of the Northern Hemisphere and the globe (Ding et al., 2006), and the trend is expected to continue during the next years (Tang et al., 2011). The costs and benefits of climate change are not equally distributed around the world (Darwin et al., 1995). Developed countries can benefit from climate change through rising crop production while in developing countries production becomes limited; in other words, disparities in cereal production between the developed and develop- Supported by the China Meteorological Administration Special Public Welfare Research Fund (GYHY ) and National Natural Science Foundation of China ( ). Corresponding author: gjp@cams.cma.gov.cn. The Chinese Meteorological Society and Springer-Verlag Berlin Heidelberg 2014

2 470 JOURNAL OF METEOROLOGICAL RESEARCH VOL.28 ing worlds will likely increase under global warming (Rosenzweig and Parry, 1994). Climate change can have adverse effects on agricultural production, and ultimately threatens food security. Therefore, studying how agricultural production can adapt under climate change is an important topic in order to achieve agricultural sustainable development. To date, a variety of adaptation options have been proposed as having the potential to reduce the vulnerability of agroecosystems to risks related to climate change (Smit and Skinner, 2002), some of which are already well developed, such as the adjustment of sowing date, planting resistant varieties, and farm management (Lü et al., 2010). Northeast China is an important agricultural region and occupies a key strategic position in the grain market. The annual output of maize in this region is almost 40 million tons, accounting for approximately 30% of the total maize yield in China (Ma et al., 2008). On one hand, the warming climate serves to extend the growing season in Northeast China, which is conducive to an improvement in total grain production; on the other hand, the warmer and drier conditions present great challenges to maize production. For example, the grain-fill period of maize can shorten, meaning that kernel weight and ultimately yield can decrease. There have been many studies carried out that have focused on how maize varieties in Northeast China could adapt to future climate change, and the results have largely showed that early-maturing and mid-maturing varieties will be replaced by late-maturing varieties under a warming climate (Jia and Guo, 2009; Zhao et al., 2009). Furthermore, in areas that are originally cooler, grain yields could benefit from a transition to new varieties; while in areas that are already relatively warm, such a transition may not have much of an effect (Yuan et al., 2012). Therefore, how to make full use of climatic resources to maximize maize yields is an important topic of research. Climatic productivity can not only reveal the relationship between crop s growth and development, yield and climatic resources, but also help to discover the main yield-limiting factors and reflect resource utilization (Liu, 2010). In the present study, we use daily meteorological data for the period , from simulations by RegCM3 under the A1B future-climate scenario, to quantitatively assess the contributions of different climate-change adaption options (e.g., adjustment of maize variety layout, use of resistant varieties) to potential increases in maize productivity. Based on the results, we also discuss possible future development directions with respect to maize varieties in Northeast China. Furthermore, beyond Northeast China, the study provides a theoretical basis for agricultural adaptation options to climate change and the reasonable utilization of climatic resources for realizing high and stable maize yields. 2. Data and methods 2.1 Data We chose Heilongjiang, Jilin, and Liaoning provinces as our study areas. Meteorological data for Northeast China covering the period , as simulated by RegCM3 under the A1B future-climate scenario, are used. These data include daily average temperature, daily maximum and minimum temperature, daily total radiation, daily net radiation, daily average wind speed at 2 m above ground level, daily relative humidity, precipitation, etc., and are available on a grid. Error correction for the gridded data was performed as detailed in Yuan et al. (2012). The growing seasons of maize for the period are provided by the National Meteorological Information Center. 2.2 Methods Thermal index Different maize cultivars require different amounts of cumulative temperature during the growing season (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 to actual maize-growth data for Northeast China during , we established the statistical relationship between each variety type and its required cumulative temperature in corresponding stages of the grow-

3 NO.3 XU Yanhong, GUO Jianping, ZHAO Junfang, et al. 471 ing season. Jiayin agro-meteorological station was chosen as a typical station representing early-maturing varieties; Hailun agro-meteorological station was chosen as a typical station representing mid-maturing varieties; Changling and Harbin agro-meteorological stations were chosen as typical stations representing midlate-maturing varieties; and Wafangdian, Fuxin, and Zhuanghe agro-meteorological stations were chosen as typical stations representing late-maturing varieties. The resulting thermal index values for the different varieties in different stages of the growing season are detailed in Table 1. Table 1. Cumulative temperature ( day) required by the different maize variety types in different stages of the growing season Sowing-emergence Emergence-jointing Jointing-heading Heading-maturity Early-maturing Mid-maturing Mid-late-maturing Late-maturing Resistant varieties Like any other crop, maize grows more vigorously and accumulates more dry matter in a suitable environment. Under unsuitable conditions, the crop s growth and development will be inhibited, and dry matter accumulation will be less. Therefore, we changed the basic temperature (Table 2) and water requirements to generate theoretical maize varieties adapted to future climate, and we then used these high-temperature and/or drought-resistant varieties to model the increase in climatic productivity. The nine proposed resistant varieties in the context of days required for growth remaining the same are detailed in Table 3. Use of these varieties as agricultural adaptation options to climate change was then evaluated Productivity The Food and Agriculture Organization-Agro- Ecological Zone (FAO-AEZ) model is a commonly used method to calculate crop productivity under different climates. In different stages of the growing sea- Table 2. Basic temperature ( ) requirements of maize in Northeast China during different stages of the growing season Sowing-emergence Emergence-jointing Jointing-heading Heading-maturity T L T S T S T H T L : minimum temperature limit; T H : maximum temperature limit; T S1 : minimum limit of optimum temperature; T S2 :maximum limit of optimum temperature (Wang et al., 2005; Yuan et al., 2012). Table 3. Parameters of the modeled resistant maize varieties Varieties Performance characteristics T0 Current variety T1 T L and T S1 unchanged; T S2 and T H increased by 1 ; T m unchanged T2 T L and T S1 unchanged; T S2 and T H increased by 2 ; T m unchanged T3 T L and T S1 unchanged; T S2 and T H increased by 3 ; T m unchanged T4 T m reduced to 98%; all basic temperature requirements unchanged T5 T m reduced to 96%; all basic temperature requirements unchanged T6 T m reduced to 94%; all basic temperature requirements unchanged T7 T L and T S1 unchanged; T S2 and T H increased by 1 ; T m reduced to 98% T8 T L and T S1 unchanged; T S2 and T H increased by 2 ; T m reduced to 96% T9 T L and T S1 unchanged; T S2 and T H increased by 3 ; T m reduced to 94% T1, T2, and T3 are high-temperature resistant varieties; T4, T5, and T6 are drought-resistant varieties; T7, T8, and T9 are both high-temperature- and drought-resistant varieties; T m is the crop water requirement; other symbols are the same as in Table 2.

4 472 JOURNAL OF METEOROLOGICAL RESEARCH VOL.28 son, maize requires different quantities of climatic resources. Therefore, in order to make the results more realistic, the growth period of maize was divided into the following four stages: sowingemergence, emergence-jointing, jointing-heading, and heading-maturity. Photosynthetic productivity, photosynthetic thermal productivity, and climatic productivity in these different stages of the growing season were calculated separately. Then, the crop potential productivity during the whole period was determined. The specific quantities calculated were as follows: a) Photosynthetic productivity Y 0 = Fy 0 +(1 F )y c, (1) F = R se 0.5R s, (2) 0.8R se where Y 0 (kg hm 2 ) is the daily photosynthetic production of the reference crop (LAI = 5; dry matter productivity Y m =20kghm 2 h 1 ), y 0 and y c (kg hm 2 ) are the dry-matter production on an overcast and clear day, respectively (Liu et al., 2001), F is cloud coverage, R se (MJ m 2 ) is the maximum effective shortwave radiation on a clear day, and R s is the observed radiation (MJ m 2 ). b) Photosynthetic thermal productivity Photosynthetic thermal productivity is the yield determined mostly by sunlight and thermal resources. First, we calibrated y 0 and y c of the reference crop by the values of Y m at different temperatures. When Y m 20 kg hm 2 h 1, Y 0 = F ( Y m )y 0 +(1 F ) ( Y m )y c. (3) When Y m < 20 kg hm 2 h 1, Y 0 = F ( Y m )y 0 +(1 F ) (0.05Y m )y c. (4) The calculation method for photosynthetic thermal productivity was as follows: Y mp = C L C N C H G Y 0, (5) where Y mp is photosynthetic thermal productivity (kg hm 2 ). C L is the correction coefficient of LAI (Wang et al., 2008). The change in LAI is a single peak curve during the whole growing season and LAI generally reaches its maximum value in the flowering stage of the growing season. Y mp should be corrected when LAI < 5. In this study, the values of LAI were obtained from Yuan and Guo (2010). C N is the correction coefficient of net dry-matter production. C N is 0.6 when the average temperature is < 20, andit is 0.5 when the average temperature is 20 (Zhao and Zhao, 1988). C H is the harvest index, for which the value in this study is 0.55 (Liu Wei et al., 2010). Finally, G is the number of days in the growing season. c) Climatic productivity Climatic productivity is the highest per hectare yield obtained by radiation, temperature, and precipitation under the assumption that soil fertility and agro-technical measures are optimal for crop growth (Wang et al., 2003). The calculation method was as follows: Y p = Y mp f(p), (6) f(p) =1 k y (1 ET a ), T m (7) T m = k c ET 0, (8) where Y p (kg hm 2 ) is the climatic productivity; f(p) is the moisture modification function; k y is the productivity response index, with its average value during the whole period being 1.25 (Wang Xiufen et al., 2012); T m (mm) is crop water requirement; k c is the crop coefficient obtained by vegetation fractional cover during different periods (Sun, 2008; Tian et al., 2009); and ET 0 is the reference crop s evapotranspiration computed by the Penman-Monteith model (Liu Yuan et al., 2010). ET a (mm) is the actual evapotranspiration determined by the quantitative relation between available water (precipitation and previous soil water storage) and crop water requirement. ET a was calculated by taking 10 days as the unit of time: ET a = { T m, P a + S a T m, P a + S a, P a + S a <T m, (9) where S a and P a is the soil water storage and precipitation, respectively, in the last 10 days (Zhao et al., 2011).

5 NO.3 XU Yanhong, GUO Jianping, ZHAO Junfang, et al Results and analysis 3.1 Agro-climatic resources in Northeast China Agro-climatic resources include thermal, water, and light resources. They reflect the influence of climate change on agricultural production. Maize in Northeast China grows mainly over the period from May to September. The 10 day cumulative temperature and the sum of mean air temperature during that period can be used to reflect the heat conditions during the growing season (Ma et al., 2000). Likewise, total precipitation from May to September, probable evaporation, and aridity index can be used as indicators of drought. The aridity index is defined as the ratio of probable evaporation and precipitation, meaning the lower the aridity index value is, the more humid the atmosphere is, and vice versa. To discuss light resources, solar radiation needs to be considered; changes in light resources can be expressed in terms of total radiation during the growing season. Table 4 shows the predicted changes in climatic resources during , based on the RegCM3 data. As can be seen, the sum of mean air temperature from May to September and the 10 day accumulated temperature significantly increase. However, precipitation during the growing season increases less significantly in the model. Meanwhile, the rising temperature causes a continuous increase in atmospheric evaporation, showing a tendency toward an arid climate. Total radiation during the growing season from 1981 to 2100 also increases. In particular, the model predicts that total radiation will increase significantly during , but the rate of change will then slow during Table 4. Modeled changes in climatic resources during the maize growing season during Thermal resources Water resources Light resources Sum of temperature Cumulative temperature Precipitation Evapotranspiration Aridity Total radiation ( (10 yr) 1 ) 10 ( day (10 yr) 1 ) (mm (10 yr) 1 ) (mm (10 yr) 1 ) ((10 yr) 1 )(MJm 2 (10 yr) 1 ) ** 93.91** ** ** * ** ** ** 0.36* 59.79** ** ** * 0.05 significance level; ** 0.01 significance level. 3.2 Climatic productivity after adjusting the maize variety distribution pattern According to the different cumulative requirements of the different varieties of maize, we produced a theoretical distribution for maize in Northeast China for the period and calculated the potential climate productivity on that basis. The results show that radiation has no significant influence on photosynthetic thermal productivity and climatic productivity in most periods. Temperature and precipitation are the main meteorological factors affecting climatic productivity for maize. Photosynthetic thermal productivity in Northeast China shows an S-shaped curve over the entire period (i.e., ). Climatic productivity changes from to kg hm 2 with large interannual variations. Photosynthetic thermal productivity is low during (base period), and in one particular year (1993) the air temperature in most areas of China was lower than usual. This was a cold summer in the northeast region, and the photosynthetic thermal productivity reached its lowest value of kg hm 2. With the increase in temperature from 2011 to 2070, early-maturing varieties are gradually replaced by late-maturing varieties to make full use of the thermal resources, and the photosynthetic thermal productivity increases rapidly. However, when the temperature rises beyond the upper limit of optimum temperature for maize after 2071, the photosynthetic thermal productivity begins to decrease. Unsuitable water resource is an important factor limiting climatic productivity during the entire modeled period. Climatic productivity accounts for about 64.6% of the photosynthetic thermal productivity.

6 474 JOURNAL OF METEOROLOGICAL RESEARCH VOL.28 Climatic productivity shows a south-north declining trend during the base period. Higher values are found in the southeast of Liaoning and the Tieling- Fushun area, and lower values appear mainly in the northwest of Jilin and the west of Heilongjiang. The maximum value is almost three times larger than the minimum value (Fig. 1). Climatic productivity in the western areas during is lower than that during the base period because of the increased potential evaporation and high-temperature weather. The results indicate that, during , spring maize could be planted in the Zhangguangcai and Laoye Mountains, where the climate is not currently (i.e., in the base period) suitable for maize growth. The nongrowing areas will be reduced in the Changbai Mountains, and the climatic productivity will increase in the Xiao Higgan Mountains. After 2041, late-maturing varieties could be planted in most areas of Northeast China, and the climatic productivity largely increases in the east of Jilin and in most areas of Heilongjiang. Climatic productivity decreases by > 20% under climate warming and drying in western areas. Furthermore, the distribution of varieties in western areas would no longer need to be adjusted. Both high and low value areas are reduced. The results show that the climatic productivity in Liaoning Province, having previously had the highest values, will be lower than that in Jilin Province during ; the disparities between these provinces will be narrowed. With the plantable areas for late-maturing varieties shifting northward and enlarging in the east, the potential climatic productivity increases in the north and central Heilongjiang, and the east of Jilin. Meanwhile, climate productivity decreases in the southeast of Liaoning, the Changchun and Gannan-Harbin area, and Heilongjiang, as the climatic resources become mismatched. These results indicate that an increase in heat resources could favor agricultural production in areas that currently experience heat shortages. However, soil evaporation and plant transpiration would Fig. 1. Climatic productivity of spring maize during the base period and its change (%) during in Northeast China.

7 NO.3 XU Yanhong, GUO Jianping, ZHAO Junfang, et al. 475 continue to increase under climate warming, such that precipitation is unlikely to meet crop water requirements without irrigation. The shift to a warmer and drier climate will therefore bring severe challenges to agricultural production, especially in overheated areas. Therefore, we need to consider agricultural adaptation options in order to increase the utilization of climatic resources against a background of climate change. 3.3 Effects of developing resistant varieties on climatic productivity The warming and drying climate is an important factor that limits the potential of increasing yields in an overheated area. The current variety of maize is unlikely to be able to adapt to a future warmer climate. Based on adjusting the species distribution, our results indicate that developing resistant varieties would help increase climatic productivity (Fig. 2), and the influence is closely related to the allocation of climatic resources. The extra output of high-temperatureresistant varieties (T1 T3) increases with time. The changes in Y p of drought-resistant varieties (T4 T6) are consistent with that of the current variety (T0), while Y p of T4 T6 is higher than that of T0, with the extra output fluctuating during The ability of both high-temperature- and drought-resistant varieties (T7 T9) to adapt to climate change is better than that of T1 T6. High-temperature resistance increases climatic resources utilization to a large degree as the climate becomes warmer and drier during The higher values of Y p for T7 T9 compared to T0 show a significant increase Variance analysis of climatic productivity of different cultivation patterns Under the scenario of a growing mismatch of climatic factors, to slow the downward trend of climatic productivity, we need to enhance resistance from the Fig. 2. Increases in climatic productivity resistant varieties compared to the current variety (T0) of maize. (a) T1 T0, T2 T0, and T3 T0; (b) T4 T0, T5 T0, and T6 T0; (c) T7 T0, T8 T0, and T9 T0.

8 476 JOURNAL OF METEOROLOGICAL RESEARCH VOL.28 point of view of the basic temperatures and water requirements. In order to further analyze how much and to what extent the basic temperature and water requirements would need to be adjusted to make the difference between the current variety and the resistant varieties statistically significant, we perform a variance analysis of climatic productivity of the current variety and the resistant varieties (Table 5). As can be seen from the results, during , the climatic productivity of T2 and T3 is significantly different from T0, but the difference between T2 and T3 is not significant. The climatic productivity of T4 and T5 is not significantly higher than that of T0. When the water requirement is reduced to 94% (T6), the climatic productivity is significantly higher than that of T0 during Both high-temperature- and drought-resistant varieties largely decrease the adverse effects of the warming/drying climate. The difference between T7 and T0 is significant during , T8 is significantly different from T0 after 2041, and the climatic productivity of T9 is significantly different from T0 after Table 5. Variance analysis of climatic productivity of resistant maize varieties Variety type Variety Mean climatic productivity (kg hm 2 ) name Current variety T a a a High-temperature-resistant varieties T ab ab ab T ab abc bc T ab abc bc Drought-resistant varieties T ab abc ab T abc abc ab T bc bcd bc Both high-temperature- and drought-resistant varieties T abc abc bc T abc cd c T c d d The superscripts a, b, c, and d are the names of the similar subsets at the 95% confidence level. Values in the same row with different superscript letters are significantly different Distribution of suitable meteorological conditions for different cultivation patterns Climatic productivity is the highest biomass yield obtained by the full utilization of thermal, water, and light resources, and the value can be used to reflect the suitable grade of meteorological conditions in a particular region. In this study, climatic productivity is 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 difference between the resistant varieties T2, T6, and T9 and the current variety in terms of meteorological suitability was analyzed and the results are shown in Fig. 3. The most available areas for T0 during are mainly in the east of Liaoning and central Jilin; the available areas are in central Liaoning, east to Dunhua (except the area around the Changbai Mountains), central Jilin, and eastern Heilongjiang; the relatively available areas are in southwestern Liaoning, the areas west to Changchun, and the areas south to Humain and western Heilongjiang; a relatively unavailable area is around Songnen Plain; and the regions in the Changbai Mountains and northern Heilongjiang, with their scarce heat resources, are classified as un- Table 6. Classification criterion of meteorological suitability based on climatic productivity of T0 Grade (value) Period Unavailable Relatively Relatively Available Most (1) unavailable (2) available (3) (4) available (5) Y p=0 0 <Y p < Y p < Y p < Y p Y p=0 0 <Y p < Y p < Y p < Y p Y p=0 0 <Y p < Y p < Y p < Y p 15163

9 NO.3 XU Yanhong, GUO Jianping, ZHAO Junfang, et al. 477 Fig. 3. The distribution of meteorological suitability for different maize varieties T0, T2, T6, and T9. available for maize growth. The difference between T2 and T0 is not significant in terms of the distribution of meteorological suitability in the period Meanwhile, the available area for T6 expands: the western boundary grows to Fuxin from Xinmin and central Liaozhong, the northern boundary extends northward in Heilongjiang, meteorological suitability increases in Qinan and central Suiling, and the western boundary of the relatively unavailable area shifts westward by 0.4 of longitude. Climate suitability for T9 increases the most, with the northern boundary of available area moving from to N. The suitability of meteorological conditions decreases due to increasing temperature and less precipitation during The most available and available areas for T0 decrease, while the relatively

10 478 JOURNAL OF METEOROLOGICAL RESEARCH VOL.28 available and relatively unavailable areas increase. Meteorological suitability increases less when only the basic temperature requirements are adjusted; when the crop water requirement is reduced, the climatic suitability rises. The northern boundary of the most available area shifts from to N, the available area increases, and the relatively unavailable area decreases in Heilongjiang. Climatic resources utilization will improve after adjusting the basic temperature and water requirements, but the difference between T9 and T6 in terms of the distribution of meteorological suitability is not significant. The climatic suitability for T0 during is higher than that during , with precipitation increasing. High temperature is also the main factor limiting the increase of potential productivity during , suggesting that enhancing the tolerance of maize to high temperatures could increase the climatic productivity in this period. The available area in Huachuan and Jixian in Heilongjiang Province for T2 is larger than T0, and the available area is reclassified as the most available in southern Yichuan. The climatic suitability for T6 changes markedly in Heilongjiang: the available area expands, and the relatively available areas transform into available areas in southern Huanan, southern Huachuan, and in parts of southern Jixian. The boundary of the available area shifts westward. The available area for T9 further expands; the relatively available areas transform into available areas in Hulin and Mishan; the available area expands to central Huanan and Jixian; the boundary of the most available area advances westward; and the boundary of the relatively unavailable area shifts westward by about 1.3 of longitude. Overall, the results suggest that enhancing stress tolerance in maize would be beneficial for climatechange adaptation through an increase in climatic resources utilization. 4. Conclusions and discussion The impact of cultivar-based adaptation measures on increasing the potential productivity of maize under a warmer and drier climate was quantitatively evaluated by using the FAO-AEZ model. The results show that: (1) Heat resources are likely to change significantly in Northeast China under climate warming, with the 10 day cumulative temperature and the sum of temperature from May to September increasing. Precipitation in the growing season shows a nonsignificant increasing trend with a large degree of interdecadal fluctuation. Total radiation is predicted to increase significantly during Thermal conditions are found to improve over Northeast China as the climate warms, but precipitation may not compensate for the increasing evapotranspiration, the aridity index could increase, and the climate is likely to be generally warmer and drier. (2) The increase in heat resources could bring favorable conditions for agricultural production in Northeast China. In the model s results, the planting boundaries for different patterns extend eastward and northward. The instability in precipitation leads to unstable climatic productivity. The climatic productivity changes from to kg hm 2 ;because the computation models are different from others, this value is lower than that in a previous study (Yuan et al., 2012). The increased value of photosynthetic thermal productivity is not enough to offset the negative effects of lower water suitability, and the increase in climatic productivity is limited during the study period. However, we find great potential for increased climatic productivity in the future if accompanied by irrigation. Maize climatic productivity gradually improves due to climate warming in places where heat is originally insufficient. Meanwhile, the increase of heat resources has an adverse effect on maize growth and development in places that are already relatively hot, especially in Liaoning Province, resulting in a decline of climatic productivity. The change in climatic productivity in the southwestern area is opposite to the changes in the southeast and northwest, and the disparities between high and low values will be narrowed. (3) As the climate becomes warmer and drier, enhancing the stress tolerance of maize could increase its productivity and the climatic resources utilization effectively. The warmer and drier the climate becomes, the greater the increase will be in terms of the range

11 NO.3 XU Yanhong, GUO Jianping, ZHAO Junfang, et al. 479 of production potential of resistant varieties, especially high-temperature-resistant varieties, whose productivity is found to rise obviously with time. The combined effect of high-temperature- and droughtresistant varieties on increasing productivity is better than high-temperature- or drought-resistant varieties only. The suitability of meteorological conditions is graded on the basis of the production potential values, and the results show that the available area could expand by enhancing stress tolerance, while the unavailable area may shrink. (4) Solar radiation is an important resource affecting agricultural production because it has a direct influence on photosynthetic productivity, and thus ultimately climatic productivity as well. If we use the base radiation and the simulation from RegCM3 as the initial conditions to compute the potential productivity, the changing trend of Y p is similar, and the differences in values are not significant. The results show rich solar resources in Northeast China, suggesting that it is not the main factor limiting agricultural production. This is consistent with the previous study by Wang Ming et al. (2012). Crop physiological characteristics during different stages of the growing season are considered. Growth and development as well as yield production are regarded as dynamic processes, and meteorological factors affecting crop growth and yield are comprehensively analyzed in the AEZ model, which has been widely applied internationally in theoretical studies. Actual maize production is also affected by soil, agricultural techniques, socioeconomics, natural disasters etc. In this study, only light, heat, and water resources are taken into consideration to calculate the climatic productivity, i.e., it is an ideal output. By taking other factors affecting agricultural production into account, the calculated values of climatic productivity could be more accurate. The abilities of three kinds of resistant varieties to adapt to climate change are evaluated in our study. We assume that the upper limit of optimum temperature and the upper limit of temperature would increase by 1, 2, and 3, respectively, in these hightemperature-resistant varieties, but this assumption is not based on future temperature-change scenarios. How to better design the basic parameters of temperature requirements of resistant varieties will be an important 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 productivity are often different in different areas. How to determine the range of optimum temperatures of high-temperature- and drought-tolerant varieties in different regions needs to be further studied. REFERENCES 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, 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, (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, (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, (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, (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, (in Chinese) Lü Qintang, Wang Junru, and Guo Yingwei, 2010: Effects of climate change on agricultural production

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