Contribution of crop model structure,parameters and climate projections to uncertainty in climate change impact assessments

Climate change impact assessments are plagued with uncertainties from many sources, such as climate projections or the inadequacies in structure and parameters of the impact model. Previous studies tried to account for the uncertainty from one or two of these. Here, we developed a triple‐ensemble probabilistic assessment using seven crop models, multiple sets of model parameters and eight contrasting climate projections together to comprehensively account for uncertainties from these three important sources. We demonstrated the approach in assessing climate change impact on barley growth and yield at Jokioinen, Finland in the Boreal climatic zone and Lleida, Spain in the Mediterranean climatic zone, for the 2050s. We further quantified and compared the contribution of crop model structure, crop model parameters and climate projections to the total variance of ensemble output using Analysis of Variance (ANOVA). Based on the triple‐ensemble probabilistic assessment, the median of simulated yield change was ?4% and +16%, and the probability of decreasing yield was 63% and 31% in the 2050s, at Jokioinen and Lleida, respectively, relative to 1981–2010. The contribution of crop model structure to the total variance of ensemble output was larger than that from downscaled climate projections and model parameters. The relative contribution of crop model parameters and downscaled climate projections to the total variance of ensemble output varied greatly among the seven crop models and between the two sites. The contribution of downscaled climate projections was on average larger than that of crop model parameters. This information on the uncertainty from different sources can be quite useful for model users to decide where to put the most effort when preparing or choosing models or parameters for impact analyses. We concluded that the triple‐ensemble probabilistic approach that accounts for the uncertainties from multiple important sources provide more comprehensive information for quantifying uncertainties in climate change impact assessments as compared to the conventional approaches that are deterministic or only account for the uncertainties from one or two of the uncertainty sources.     

Maize potential yields and yield gaps in the changing climate of northeast China

Northeast China (NEC) is not only one of the major agricultural production areas in China, but it is also the most susceptible to climate variability. This led us to investigate the impact of climate change on maize potential yield and yield gaps in this region, where maize accounts for about 30% of the nation's production. The APSIM‐Maize model was calibrated and validated for maize phenology and yields. The validated model was then used to estimate potential yields, rain‐fed potential yields, and yield gaps for assessing the climate impacts on maize productivity in NEC. During maize growing seasons from 1981 to 2010, the analysis indicates a warming trend all across NEC, whereas the trends in solar radiation and total precipitation tended to decrease. When the same hybrid was specified in APSIM for all years, a simulated increase of maximum temperature resulted in a negative impact on both potential yield and rain‐fed potential yield. A simulated increase in minimum temperature produced no significant changes in potential or rain‐fed potential yield. However, the increase of minimum temperature was shown to result in a positive impact on the on‐farm yield, consistent with our finding that farmers adopted longer season hybrids for which the increase in minimum temperature provided better conditions for germination, emergence, and grain filling during night time. The gap between potential and rain‐fed potential yields was shown to be larger at locations with lower seasonal precipitation (<500 mm). Our results indicate that regions with the largest yield gaps between rain‐fed potential and on‐farm yields were located in the southeast of NEC. Within NEC, on‐farm maize yields were, on average, only 51% of the potential yields, indicating a large exploitable yield gap, which provides an opportunity to significantly increase production by effective irrigation, fertilization, herbicide, and planting density in NEC.     

Modern maize hybrids in Northeast China exhibit increased yield potential and resource use efficiency despite adverse climate change

The impact of global changes on food security is of serious concern. Breeding novel crop cultivars adaptable to climate change is one potential solution, but this approach requires an understanding of complex adaptive traits for climate‐change conditions. In this study, plant growth, nitrogen (N) uptake, and yield in relation to climatic resource use efficiency of nine representative maize cultivars released between 1973 and 2000 in China were investigated in a 2‐year field experiment under three N applications. The Hybrid‐Maize model was used to simulate maize yield potential in the period from 1973 to 2011. During the past four decades, the total thermal time (growing degree days) increased whereas the total precipitation and sunshine hours decreased. This climate change led to a reduction of maize potential yield by an average of 12.9% across different hybrids. However, the potential yield of individual hybrids increased by 118.5 kg ha^?1 yr^?1 with increasing year of release. From 1973 to 2000, the use efficiency of sunshine hours, thermal time, and precipitation resources increased by 37%, 40%, and 41%, respectively. The late developed hybrids showed less reduction in yield potential in current climate conditions than old cultivars, indicating some adaptation to new conditions. Since the mid‐1990s, however, the yield impact of climate change exhibited little change, and even a slight worsening for new cultivars. Modern breeding increased ear fertility and grain‐filling rate, and delayed leaf senescence without modification in net photosynthetic rate. The trade‐off associated with delayed leaf senescence was decreased grain N concentration rather than increased plant N uptake, therefore N agronomic efficiency increased simultaneously. It is concluded that modern maize hybrids tolerate the climatic changes mainly by constitutively optimizing plant productivity. Maize breeding programs in the future should pay more attention to cope with the limiting climate factors specifically.     

Mind the gap: how do climate and agricultural management explain the ‘yield gap’ of croplands around the world?

Aim As the demands for food, feed and fuel increase in coming decades, society will be pressed to increase agricultural production – whether by increasing yields on already cultivated lands or by cultivating currently natural areas – or to change current crop consumption patterns. In this analysis, we consider where yields might be increased on existing croplands, and how crop yields are constrained by biophysical (e.g. climate) versus management factors. Location This study was conducted at the global scale. Methods Using spatial datasets, we compare yield patterns for the 18 most dominant crops within regions of similar climate. We use this comparison to evaluate the potential yield obtainable for each crop in different climates around the world. We then compare the actual yields currently being achieved for each crop with their ‘climatic potential yield’ to estimate the ‘yield gap’. Results We present spatial datasets of both the climatic potential yields and yield gap patterns for 18 crops around the year 2000. These datasets depict the regions of the world that meet their climatic potential, and highlight places where yields might potentially be raised. Most often, low yield gaps are concentrated in developed countries or in regions with relatively high‐input agriculture. Main conclusions While biophysical factors like climate are key drivers of global crop yield patterns, controlling for them demonstrates that there are still considerable ranges in yields attributable to other factors, like land management practices. With conventional practices, bringing crop yields up to their climatic potential would probably require more chemical, nutrient and water inputs. These intensive land management practices can adversely affect ecosystem goods and services, and in turn human welfare. Until society develops more sustainable high‐yielding cropping practices, the trade‐offs between increased crop productivity and social and ecological factors need to be made explicit when future food scenarios are formulated.     

Uncertainties in predicting rice yield by current crop models under a wide range of climatic conditions

Predicting rice (Oryza sativa) productivity under future climates is important for global food security. Ecophysiological crop models in combination with climate model outputs are commonly used in yield prediction, but uncertainties associated with crop models remain largely unquantified. We evaluated 13 rice models against multi‐year experimental yield data at four sites with diverse climatic conditions in Asia and examined whether different modeling approaches on major physiological processes attribute to the uncertainties of prediction to field measured yields and to the uncertainties of sensitivity to changes in temperature and CO₂ concentration [CO₂]. We also examined whether a use of an ensemble of crop models can reduce the uncertainties. Individual models did not consistently reproduce both experimental and regional yields well, and uncertainty was larger at the warmest and coolest sites. The variation in yield projections was larger among crop models than variation resulting from 16 global climate model‐based scenarios. However, the mean of predictions of all crop models reproduced experimental data, with an uncertainty of less than 10% of measured yields. Using an ensemble of eight models calibrated only for phenology or five models calibrated in detail resulted in the uncertainty equivalent to that of the measured yield in well‐controlled agronomic field experiments. Sensitivity analysis indicates the necessity to improve the accuracy in predicting both biomass and harvest index in response to increasing [CO₂] and temperature.     

Elucidating the impact of temperature variability and extremes on cereal croplands through remote sensing

Remote sensing‐derived wheat crop yield‐climate models were developed to highlight the impact of temperature variation during thermo‐sensitive periods (anthesis and grain‐filling; TSP) of wheat crop development. Specific questions addressed are: can the impact of temperature variation occurring during the TSP on wheat crop yield be detected using remote sensing data and what is the impact? Do crop critical temperature thresholds during TSP exist in real world cropping landscapes? These questions are tested in one of the world's major wheat breadbaskets of Punjab and Haryana, north‐west India. Warming average minimum temperatures during the TSP had a greater negative impact on wheat crop yield than warming maximum temperatures. Warming minimum and maximum temperatures during the TSP explain a greater amount of variation in wheat crop yield than average growing season temperature. In complex real world cereal croplands there was a variable yield response to critical temperature threshold exceedance, specifically a more pronounced negative impact on wheat yield with increased warming events above 35 °C. The negative impact of warming increases with a later start‐of‐season suggesting earlier sowing can reduce wheat crop exposure harmful temperatures. However, even earlier sown wheat experienced temperature‐induced yield losses, which, when viewed in the context of projected warming up to 2100 indicates adaptive responses should focus on increasing wheat tolerance to heat. This study shows it is possible to capture the impacts of temperature variation during the TSP on wheat crop yield in real world cropping landscapes using remote sensing data; this has important implications for monitoring the impact of climate change, variation and heat extremes on wheat croplands.     

Impacts of climate change on paddy rice yield in a temperate climate

The crop simulation model is a suitable tool for evaluating the potential impacts of climate change on crop production and on the environment. This study investigates the effects of climate change on paddy rice production in the temperate climate regions under the East Asian monsoon system using the CERES‐Rice 4.0 crop simulation model. This model was first calibrated and validated for crop production under elevated CO₂ and various temperature conditions. Data were obtained from experiments performed using a temperature gradient field chamber (TGFC) with a CO₂ enrichment system installed at Chonnam National University in Gwangju, Korea in 2009 and 2010. Based on the empirical calibration and validation, the model was applied to deliver a simulated forecast of paddy rice production for the region, as well as for the other Japonica rice growing regions in East Asia, projecting for years 2050 and 2100. In these climate change projection simulations in Gwangju, Korea, the yield increases (+12.6 and + 22.0%) due to CO₂ elevation were adjusted according to temperature increases showing variation dependent upon the cultivars, which resulted in significant yield decreases (?22.1% and ?35.0%). The projected yields were determined to increase as latitude increases due to reduced temperature effects, showing the highest increase for any of the study locations (+24%) in Harbin, China. It appears that the potential negative impact on crop production may be mediated by appropriate cultivar selection and cultivation changes such as alteration of the planting date. Results reported in this study using the CERES‐Rice 4.0 model demonstrate the promising potential for its further application in simulating the impacts of climate change on rice production from a local to a regional scale under the monsoon climate system.     

Agroclimatic conditions in Europe under climate change

To date, projections of European crop yields under climate change have been based almost entirely on the outputs of crop‐growth models. While this strategy can provide good estimates of the effects of climatic factors, soil conditions and management on crop yield, these models usually do not capture all of the important aspects related to crop management, or the relevant environmental factors. Moreover, crop‐simulation studies often have severe limitations with respect to the number of crops covered or the spatial extent. The present study, based on agroclimatic indices, provides a general picture of agroclimatic conditions in western and central Europe (study area lays between 8.5°W–27°E and 37–63.5°N), which allows for a more general assessment of climate‐change impacts. The results obtained from the analysis of data from 86 different sites were clustered according to an environmental stratification of Europe. The analysis was carried for the baseline (1971–2000) and future climate conditions (time horizons of 2030, 2050 and with a global temperature increase of 5 °C) based on outputs of three global circulation models. For many environmental zones, there were clear signs of deteriorating agroclimatic condition in terms of increased drought stress and shortening of the active growing season, which in some regions become increasingly squeezed between a cold winter and a hot summer. For most zones the projections show a marked need for adaptive measures to either increase soil water availability or drought resistance of crops. This study concludes that rainfed agriculture is likely to face more climate‐related risks, although the analyzed agroclimatic indicators will probably remain at a level that should permit rainfed production. However, results suggests that there is a risk of increasing number of extremely unfavorable years in many climate zones, which might result in higher interannual yield variability and constitute a challenge for proper crop management.     

Decoupling of impact factors reveals the response of German winter wheat yields to climatic changes

Yield development of agricultural crops over time is not merely the result of genetic and agronomic factors, but also the outcome of a complex interaction between climatic and site‐specific soil conditions. However, the influence of past climatic changes on yield trends remains unclear, particularly under consideration of different soil conditions. In this study, we determine the effects of single agrometeorological factors on the evolution of German winter wheat yields between 1958 and 2015 from 298 published nitrogen (N)‐fertilization experiments. For this purpose, we separate climatic from genetic and agronomic yield effects using linear mixed effect models and estimate the climatic influence based on a coefficient of determination for these models. We found earlier occurrence of wheat growth stages, and shortened development phases except for the phase of stem elongation. Agrometeorological factors are defined as climate covariates related to the growth of winter wheat. Our results indicate a general and strong effect of agroclimatic changes on yield development, in particular due to increasing mean temperatures and heat stress events during the grain‐filling period. Except for heat stress days with more than 31°C, yields at sites with higher yield potential were less prone to adverse weather effects than at sites with lower yield potential. Our data furthermore reveal that a potential yield levelling, as found for many West‐European countries, predominantly occurred at sites with relatively low yield potential and about one decade earlier (mid‐1980s) compared to averaged yield data for the whole of Germany. Interestingly, effects related to high precipitation events were less relevant than temperature‐related effects and became relevant particularly during the vegetative growth phase. Overall, this study emphasizes the sensitivity of yield productivity to past climatic conditions, under consideration of regional differences, and underlines the necessity of finding adaptation strategies for food production under ongoing and expected climate change.     

Negative effects of climate warming on maize yield are reversed by the changing of sowing date and cultivar selection in Northeast China

Northeast China (NEC) accounts for about 30% of the nation's maize production in China. In the past three decades, maize yields in NEC have increased under changes in climate, cultivar selection and crop management. It is important to investigate the contribution of these changing factors to the historical yield increases to improve our understanding of how we can ensure increased yields in the future. In this study, we use phenology observations at six sites from 1981 to 2007 to detect trends in sowing dates and length of maize growing period, and then combine these observations with in situ temperature data to determine the trends of thermal time in the maize growing period, as a measure of changes in maize cultivars. The area in the vicinity of these six sites accounts for 30% of NEC's total maize production. The agricultural production systems simulator, APSIM‐Maize model, was used to separate the impacts of changes in climate, sowing dates and thermal time requirements on maize phenology and yields. In NEC, sowing dates trended earlier in four of six sites and maturity dates trended later by 4–21 days. Therefore, the period from sowing to maturity ranged from 2 to 38 days longer in 2007 than it was in 1981. Our results indicate that climate trends alone would have led to a negative impact on maize. However, results from the adaptation assessments indicate that earlier sowing dates increased yields by up to 4%, and adoption of longer season cultivars caused a substantial increase in yield ranging from 13% to 38% over the past 27 years. Therefore, earlier sowing dates and introduction of cultivars with higher thermal time requirements in NEC have overcome the negative effects of climate change and turned what would have otherwise been a loss into a significant increase in maize yield.     

Effects of precipitation and temperature on crop production variability in northeast Iran

Climate variability adversely impacts crop production and imposes a major constraint on farming planning, mostly under rainfed conditions, across the world. Considering the recent advances in climate science, many studies are trying to provide a reliable basis for climate, and subsequently agricultural production, forecasts. The El Niño-Southern Oscillation phenomenon (ENSO) is one of the principle sources of interannual climatic variability. In Iran, primarily in the northeast, rainfed cereal yield shows a high annual variability. This study investigated the role played by precipitation, temperature and three climate indices [Arctic Oscillation (AO), North Atlantic Oscillation (NAO) and NINO 3.4] in historically observed rainfed crop yields (1983–2005) of both barley and wheat in the northeast of Iran. The results revealed differences in the association between crop yield and climatic factors at different locations. The south of the study area is a very hot location, and the maximum temperature proved to be the limiting and determining factor for crop yields; temperature variability resulted in crop yield variability. For the north of the study area, NINO 3.4 exhibited a clear association trend with crop yields. In central locations, NAO provided a solid basis for the relationship between crop yields and climate factors.     

中国北方气候暖干化对粮食作物的影响及应对措施

东北、华北和西北50a来的平均气温增幅高于全国平均水平,气候变暖明显,尤其冬季增温最显著。区域增暖的极端最低气温远比极端最高气温的贡献大。东北、华北大部、西北东部降水量明显减少,平均每10a减少20—40mm,尤其春夏季减少最明显。这种趋势一直延续到20世纪90年代以后,干旱化趋势非常突出。在综述我国北方现代气候变化基本特征是暖干化的基础上,重点阐述了喜凉作物冬小麦、春小麦、马铃薯和喜温作物水稻、玉米、谷子、糜子等7种主要粮食作物的生长发育、品种熟性、种植区域与面积、产量与品质等对气候暖干化的响应特征。揭示了气候暖干化使春播作物播期提早,苗期生长发育速度加快,营养生长期提前,生殖生长期和全生育期延长;秋作物发育期推迟,生殖生长期和全生长期延长;越冬作物播期推迟,越冬死亡率降低,种植风险减少,春初提前返青,生殖生长期提早,全生育期缩短。使作物适宜种植区域向高纬度高海拔扩展;品种熟性向偏中晚熟高产品种发展;喜温作物和越冬作物以及冷凉气候区的作物种植面积迅速扩大;在旱作区种植不较耐旱的玉米、春小麦等作物种植面积受到制约。对雨养农业区的作物气候产量影响严重,尤其对不够耐旱的小麦和玉米的气候产量受影响最大;对较耐旱的谷子、糜子、马铃薯等影响较轻。从作物属性而言,对喜温作物水稻、玉米和越冬作物冬小麦有利于气候产量提高;对喜凉作物春小麦和马铃薯的气候产量将产生不利影响。同时,提出了从5个方面应对气候暖干化的技术措施,调整作物种植结构,确保粮食生产安全;根据不同气候年型调整各种作物种植比例;针对不同气候区域发展优势作物和配置作物种植格局;采取不同栽培技术和管理模式应对气候变化;采取综合配套技术提髙抵御灾害能力。为粮食作物安全生产和种植结构调整与布局提供科学依据。     

Analysis of climate signals in the crop yield record of sub‐Saharan Africa

Food security and agriculture productivity assessments in sub‐Saharan Africa (SSA) require a better understanding of how climate and other drivers influence regional crop yields. In this paper, our objective was to identify the climate signal in the realized yields of maize, sorghum, and groundnut in SSA. We explored the relation between crop yields and scale‐compatible climate data for the 1962–2014 period using Random Forest, a diagnostic machine learning technique. We found that improved agricultural technology and country fixed effects are three times more important than climate variables for explaining changes in crop yields in SSA. We also found that increasing temperatures reduced yields for all three crops in the temperature range observed in SSA, while precipitation increased yields up to a level roughly matching crop evapotranspiration. Crop yields exhibited both linear and nonlinear responses to temperature and precipitation, respectively. For maize, technology steadily increased yields by about 1% (13 kg/ha) per year while increasing temperatures decreased yields by 0.8% (10 kg/ha) per °C. This study demonstrates that although we should expect increases in future crop yields due to improving technology, the potential yields could be progressively reduced due to warmer and drier climates.     

Contributions of climatic and crop varietal changes to crop production in the North China Plain,since 1980s

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

A process‐based approach to modelling impacts of climate change on the damage niche of an agricultural weed

Predicting the impact of climate change on the damage niche of an agricultural weed at a local scale requires a process‐based modelling approach that integrates local environmental conditions and the differential responses of the crop and weed to change. A simulation model of the growth and population dynamics of winter wheat and a competing weed, Sirius 2010, was calibrated and validated for the most economically damaging weed in UK cereals, Alopecurus myosuroides. The model was run using local‐scale climatic scenarios generated by the LARS‐WG weather generator and based on the HadCM3 projections for the periods 2046–2065 and 2080–2099 to predict the impact of climate change on the population dynamics of the weed and its effect on wheat yields. Owing to rising CO₂ concentration and its effect on radiation use efficiency of wheat, weed‐free wheat yields were predicted to increase. The distribution of the weed was predicted to remain broadly similar with a possible northward shift in range. Local‐scale variation in the impact of climate change was apparent owing to variation in soil type and water holding capacity. The competitive balance was shifted in favour of the deeper rooted crop under climate change, particularly on sites with lighter soils, owing to more frequent and severe drought stress events. Although the damage niche of A. myosuroides was predicted to reduce under climate change, it is likely that weeds with contrasting physiology, such as C4 species, will be better adapted to future conditions and pose a more serious threat.     

Increasing influence of heat stress on French maize yields from the 1960s to the 2030s

Improved crop yield forecasts could enable more effective adaptation to climate variability and change. Here, we explore how to combine historical observations of crop yields and weather with climate model simulations to produce crop yield projections for decision relevant timescales. Firstly, the effects on historical crop yields of improved technology, precipitation and daily maximum temperatures are modelled empirically, accounting for a nonlinear technology trend and interactions between temperature and precipitation, and applied specifically for a case study of maize in France. The relative importance of precipitation variability for maize yields in France has decreased significantly since the 1960s, likely due to increased irrigation. In addition, heat stress is found to be as important for yield as precipitation since around 2000. A significant reduction in maize yield is found for each day with a maximum temperature above 32 °C, in broad agreement with previous estimates. The recent increase in such hot days has likely contributed to the observed yield stagnation. Furthermore, a general method for producing near‐term crop yield projections, based on climate model simulations, is developed and utilized. We use projections of future daily maximum temperatures to assess the likely change in yields due to variations in climate. Importantly, we calibrate the climate model projections using observed data to ensure both reliable temperature mean and daily variability characteristics, and demonstrate that these methods work using retrospective predictions. We conclude that, to offset the projected increased daily maximum temperatures over France, improved technology will need to increase base level yields by 12% to be confident about maintaining current levels of yield for the period 2016–2035; the current rate of yield technology increase is not sufficient to meet this target.     

Single rice growth period was prolonged by cultivars shifts,but yield was damaged by climate change during 1981–2009 in China,and late rice was just opposite

Based on the crop trial data during 1981–2009 at 57 agricultural experimental stations across the North Eastern China Plain (NECP) and the middle and lower reaches of Yangtze River (MLRYR), we investigated how major climate variables had changed and how the climate change had affected crop growth and yield in a setting in which agronomic management practices were taken based on actual weather. We found a significant warming trend during rice growing season, and a general decreasing trend in solar radiation (SRD) in the MLRYR during 1981–2009. Rice transplanting, heading, and maturity dates were generally advanced, but the heading and maturity dates of single rice in the MLRYR (YZ_SR) and NECP (NE_SR) were delayed. Climate warming had a negative impact on growth period lengths at about 80% of the investigated stations. Nevertheless, the actual growth period lengths of YZ_SR and NE_SR, as well as the actual length of reproductive growth period (RGP) of early rice in the MLRYR (YZ_ER), were generally prolonged due to adoption of cultivars with longer growth period to obtain higher yield. In contrast, the actual growth period length of late rice in the MLRYR (YZ_LR) was shortened by both climate warming and adoption of early mature cultivars to prevent cold damage and obtain higher yield. During 1981–2009, climate warming and decrease in SRD changed the yield of YZ_ER by ?0.59 to 2.4%; climate warming during RGP increased the yield of YZ_LR by 8.38–9.56%; climate warming and decrease in SRD jointly reduced yield of YZ_SR by 7.14–9.68%; climate warming and increase in SRD jointly increased the yield of NE_SR by 1.01–3.29%. Our study suggests that rice production in China has been affected by climate change, yet at the same time changes in varieties continue to be the major factor driving yield and growing period trends.     

Influence of seasonal weather and climate variability on crop yields in Scotland

The climatic sensitivity of four important agriculture crops (wheat, barley, oats, potatoes) in a northern temperate bioclimatic region is investigated using national-level yield data for 1963–2005. The climate variables include monthly and annual meteorological data, derived bioclimatic metrics, and the North Atlantic Oscillation index. Statistical analysis shows that significant relationships between yield and climate vary depending on the crop type and month but highlight the influence of precipitation (negative correlation) and sunshine duration (positive correlation) rather than temperature. Soil moisture deficit is shown to be a particular useful indicator of yield with drier summers providing the best yields for Scotland as a whole. It is also tentatively inferred that the sensitivity of these crops, particularly wheat and barley, to soil moisture deficits has increased in recent years. This suggests that improved crop yields are optimised for dry sunny years despite the continued prevalence of considerable inter-annual variability in seasonal weather.     

Climatic and technological ceilings for Chinese rice stagnation based on yield gaps and yield trend pattern analysis

Climatic or technological ceilings could cause yield stagnation. Thus, identifying the principal reasons for yield stagnation within the context of the local climate and socio‐economic conditions are essential for informing regional agricultural policies. In this study, we identified the climatic and technological ceilings for seven rice‐production regions in China based on yield gaps and on a yield trend pattern analysis for the period 1980–2010. The results indicate that 54.9% of the counties sampled experienced yield stagnation since the 1980. The potential yield ceilings in northern and eastern China decreased to a greater extent than in other regions due to the accompanying climate effects of increases in temperature and decreases in radiation. This may be associated with yield stagnation and halt occurring in approximately 49.8–57.0% of the sampled counties in these areas. South‐western China exhibited a promising scope for yield improvement, showing the greatest yield gap (30.6%), whereas the yields were stagnant in 58.4% of the sampled counties. This finding suggests that efforts to overcome the technological ceiling must be given priority so that the available exploitable yield gap can be achieved. North‐eastern China, however, represents a noteworthy exception. In the north‐central area of this region, climate change has increased the yield potential ceiling, and this increase has been accompanied by the most rapid increase in actual yield: 1.02 ton ha^?1 per decade. Therefore, north‐eastern China shows a great potential for rice production, which is favoured by the current climate conditions and available technology level. Additional environmentally friendly economic incentives might be considered in this region.     

气候变化背景下中国农业气候资源变化Ⅰ.华南地区农业气候资源时空变化特征

基于华南地区1961-2007年66个气象台站的地面观测资料,对华南地区全年及温度生长期内热量、光照和水分的时空变化特征进行了分析.结果表明：1961-2007年,华南地区年均气温以0.20 ℃·（10 a）^-1的趋势上升,温度生长期内积温的气候倾向率［平均为98 ℃·d·（10 a）^-1］由北向南递增;1981-2007年,6200～7500 ℃·d和7500～8000 ℃·d积温带面积分别较1961-1980年增加了1.5×10⁴和4.7×10⁴ km².研究期间,华南地区全年和温度生长期日照时数分别以-57和-38 h·（10 a）^-1的速率递减;与1961-1980年相比,1981-2007年全年和温度生长期内≥1800 h日照时数的区域面积均呈减少趋势.全年和温度生长期降水量均呈略微增加趋势,但不同地区的增减幅度明显不同.全年及温度生长期分别有62%和52%站点参考作物蒸散量的气候倾向率为负值;与1961-1980年相比,1981-2007年全年和温度生长期参考作物蒸散量均表现为高值区缩小、低值区扩大.全年湿润指数的平均气候倾向率为0.01·（10 a）^-1,70%站点的年湿润指数呈上升趋势;与1961-1980年相比,1981-2007年温度生长期内湿润指数增加了0.02,53%站点的气候倾向率为正值.研究期间华南地区气候变化总体表现为暖湿趋势,这将对该地区作物种植制度、作物产量和农业结构等产生影响.