Impacts of a nuclear war in South Asia on soybean and maize production in the Midwest United States

Crop production would decline in the Midwestern United States from climate change following a regional nuclear conflict between India and Pakistan. Using Agro-IBIS, a dynamic agroecosystem model, we simulated the response of maize and soybeans to cooler, drier, and darker conditions from war-related smoke. We combined observed climate conditions for the states of Iowa, Illinois, Indiana, and Missouri with output from a general circulation climate model simulation that injected 5 Tg of elemental carbon into the upper troposphere. Both maize and soybeans showed notable yield reductions for a decade after the event. Maize yields declined 10–40 % while soybean yields dropped 2–20 %. Temporal variation in magnitude of yield for both crops generally followed the variation in climatic anomalies, with the greatest decline in the 5 years following the 5 Tg event and then less, but still substantial yield decline, for the rest of the decade. Yield reduction for both crops was linked to changes in growing period duration and, less markedly, to reduced precipitation and altered maximum daily temperature during the growing season. The seasonal average of daily maximum temperature anomalies, combined with precipitation and radiation changes, had a quadratic relationship to yield differences; small (0 °C) and large (?3 °C) maximum temperature anomalies combined with other changes led to increased yield loss, but medium changes (?1 °C) had small to neutral effects on yield. The exact timing of the temperature changes during the various crop growth phases also had an important effect.     

How is CO2 affecting yields and technological progress? A statistical analysis

This paper analyzes the impact of climate, crop production technology, and atmospheric carbon dioxide (CO₂) on current and future crop yields. The analysis of crop yields endeavors to advance the literature by estimating the effect of atmospheric CO₂ on observed crop yields. This is done using an econometric model estimated over pooled historical data for 1950–2009 and data from the free air CO₂ enrichment experiments. The main econometric findings are: 1) Yields of C3 crops (soybeans, cotton, and wheat) directly respond to the elevated CO₂, while yields of C4 crops (corn and sorghum) do not, but they are found to indirectly benefit from elevated CO₂ in times and places of drought stress; 2) The effect of technological progress on mean yields is non-linear; 3) Ignoring atmospheric CO₂ in an econometric model of crop yield likely leads to overestimates of the pure effects of technological progress on crop yields of about 51, 15, 17, 9, and 1 % of observed yield gain for cotton, soybeans, wheat, corn and sorghum, respectively; 4) Average climate conditions and climate variability contribute in a statistically significant way to average crop yields and their variability; and 5) The effect of CO₂ fertilization generally outweighs the effect of climate change on mean crop yields in many regions resulting in an increase of 7–22, 4–47, 5–26, 65–96, and 3–35 % for yields of corn, sorghum, soybeans, cotton, and wheat, respectively.     

Spatial and temporal changes in vapor pressure deficit and their impacts on crop yields in China during 1980–2008

Vapor pressure deficit (VPD) is a widely used measure of atmospheric water demand. It is closely related to crop evapotranspiration and consequently has major impacts on crop growth and yields. Most previous studies have focused on the impacts of temperature, precipitation, and solar radiation on crop yields, but the impact of VPD is poorly understood. Here, we investigated the spatial and temporal changes in VPD and their impacts on yields of major crops in China from 1980 to 2008. The results showed that VPD during the growing period of rice, maize, and soybean increased by more than 0.10 kPa (10 yr)^–1 in northeastern and southeastern China, although it increased the least during the wheat growing period. Increases in VPD had different impacts on yields for different crops and in different regions. Crop yields generally decreased due to increased VPD, except for wheat in southeastern China. Maize yield was sensitive to VPD in more counties than other crops. Soybean was the most sensitive and rice was the least sensitive to VPD among the major crops. In the past three decades, due to the rising trend in VPD, wheat, maize, and soybean yields declined by more than 10.0% in parts of northeastern China and the North China Plain, while rice yields were little affected. For China as a whole, the trend in VPD during 1980–2008 increased rice yields by 1.32%, but reduced wheat, maize, and soybean yields by 6.02%, 3.19%, and 7.07%, respectively. Maize and soybean in the arid and semi-arid regions in northern China were more sensitive to the increase in VPD. These findings highlight that climate change can affect crop growth and yield through increasing VPD, and water-saving technologies and agronomic management need to be strongly encouraged to adapt to ongoing climate change.     

Impact of future climate change on wheat production in relation to plant-available water capacity in a semiaridenvironment

Conceptions encompassing climate change are irreversible rise of atmospheric carbon dioxide (CO₂) concentration, increased temperature, and changes in rainfall both in spatial- and temporal-scales worldwide. This will have a major impact on wheat production, particularly if crops are frequently exposed to a sequence, frequency, and intensity of specific weather events like high temperature during growth period. However, the process of wheat response to climate change is complex and compounded by interactions among atmospheric CO₂ concentration_, climate variables, soil, nutrition, and agronomic management. In this study, we use the Agricultural Production Systems sIMulator (APSIM)-wheat model, driven by statistically downscaled climate projections of 18 global circulation models (GCMs) under the 2007 Intergovernmental Panel on Climate Change (IPCC) Special Report on Emission Scenarios (SRES) A2 CO₂ emission scenario to examine impact on future wheat yields across key wheat growing regions considering different soil types in New South Wales (NSW) of Australia. The response of wheat yield, yield components, and phenology vary across sites and soil types, but yield is closely related to plant available water capacity (PAWC). Results show a decreasing yield trend during the period of 2021–2040 compared to the baseline period of 1961–1990. Across different wheat-growing regions in NSW, grain yield difference in the future period (2021–2040) over the baseline (1961–1990) varies from +3.4 to ?14.7 %, and in most sites, grain number is decreased, while grain size is increased in future climate. Reduction of wheat yield is mainly due to shorter growth duration, where average flowering and maturing time are advanced by an average of 11 and 12 days, respectively. In general, larger negative impacts of climate change are exhibited in those sites with higher PAWC. Current wheat cultivars with shorter growing season properties are viable in the future climate, but breading for early sowing wheat varieties with longer growing duration will be a desirable adaptation strategy for mitigating the impact of changing climate on wheat yield.     

Vulnerability and adaptation assessments of agriculturalcrops under climate change in the Southeastern USA

Summary  It is expected that a change in climatic conditions due to global warming will directly impact agricultural production. Most climate change studies have been applied at very large scales, in which regions were represented by only one or two weather stations, which were mainly located at airports of major cities. The objective of this study was to determine the potential impact of climate change at a local level, taking into account weather data recorded at remote locations. Daily weather data for a 30-year period were obtained for more than 500 sites, representing the southeastern region of the USA. Climate change scenarios, using transient and equilibrium global circulation models (GCM), were defined, created and applied to the daily historical weather data. The modified temperature, precipitation and solar radiation databases corresponding to each of the climate change scenarios were used to run the CERES v.3.5 simulation model for maize and winter wheat and the CROPGRO v.3.5 model for soybean and peanut. The GCM scenarios projected a shorter duration of the crop-growing season. Under the current level of CO₂, the GCM scenarios projected a decrease of crop yields in the 2020s. When the direct effects of CO₂ were assumed in the study, the scenarios resulted in an increase in soybean and peanut yield. Under equilibrium , the GCM climate change scenarios projected a decrease of maize and winter wheat yield. The indirect effects of climate change also tended to decrease soybean and peanut yield. However, when the direct effects of CO₂ were included, most of the scenarios resulted in an increase in legume yields. Possible changes in sowing data, hybrids and cultivar selection, and fertilization were considered as adaptation options to mitigate the potential negative impact of potential warming. Received July 20, 1999/Revised April 18, 2000     

Effects of temperature rise and increase in CO2 concentration on simulated wheat yields in Europe

A crop-growth-simulation model based on SUCROS87 was used to study effects of temperature rise and increase of atmospheric CO₂ concentration on wheat yields in several regions in Europe. The model simulated potential and water-limited crop production (growth with ample supply of nutrients and in the absence of damage by pests, diseases and weeds). Historic daily weather data from 13 sites in Western Europe were used as starting point.For potential production (optimal water) a 3 °C temperature rise led to a yield decline due to a shortening of the growing period on all locations. Doubling of the CO₂ concentration caused an increase in yield of 40% due to higher assimilation rates. It was found that effects of higher temperature and higher CO₂ concentration were nearly additive and the combination of both led to a yield increase of 1–2 ton ha^-1. A very small CO₂-temperature interaction was found: the effect of doubled CO₂ concentration on crop yield was larger at higher temperatures. The inter-annual yield variability was hardly affected.When water was limiting crop-production effects of temperature rise and higher CO₂ levels were different than for the potential production. Rise in temperature led to a smaller yield reduction, doubled CO₂ concentration to a larger yield increase and combination of both led to a large yield increase (3 ton ha^-1) in comparison with yields simulated for the present situation. Both rise in temperature and increase in the CO₂ concentration reduced water requirements of the crop. Water shortages became smaller, leading to a reduction in inter-annual variability. It is concluded that when no major changes in precipitation pattern occur a climate change will not affect wheat yields since negative effects of higher temperatures are compensated by positive effects of CO₂ enrichment.     

The Effect of Spatial Scale of Climatic Change Scenarios on Simulated Maize, Winter Wheat, and Rice Production in the Southeastern United States

We use the CERES family of crop models to assess the effect of different spatial scales of climate change scenarios on the simulated yield changes of maize (Zea mays L.), winter wheat (Triticum aestivum L.),and rice (Oryza sativa L.) in the Southeastern United States. The climate change scenarios were produced with the control and doubled CO₂ runs of a high resolution regional climate model anda coarse resolution general circulation model, which provided the initial and lateral boundary conditions for the regional model. Three different cases were considered for each scenario: climate change alone, climate change plus elevated CO₂, and the latter with adaptations. On the state level,for most cases, significant differences in the climate changed yields for corn were found, the coarse scale scenario usually producing larger modeled yield decreases or smaller increases. For wheat, however, which suffered large decreases in yields for all cases, very little contrast in yield based on scale of scenario was found. Scenario scale resulted in significantly different rice yields, but mainly because of low variability in yields. For maize the primary climate variable that explained the contrast in the yields calculated from the two scenarios is the precipitation during grain fill leading to different water stress levels. Temperature during vernalization explains some contrasts in winter wheat yields. With adaptation, the contrasts in the yields of all crops produced by the scenarios were reduced but not entirely removed. Our results indicate that spatial resolution of climate change scenarios can be an important uncertainty in climate change impact assessments, depending on the crop and management conditions.     

Crop yield response to economic, site and climatic variables

This paper examines the effects of climatic and non-climatic factors on the mean and variance of corn, soybean and winter wheat yield in southwestern Ontario, Canada over a period of 26 years. Average crop yields increase at a decreasing rate with the quantity of inputs used, and decrease with the area planted to the crop. Climate variables have a major impact on mean yield with the length of the growing season being the primary determinant across all three crops. Increases in the variability of temperature and precipitation decrease mean yield and increase its variance. Yield variance is poorly explained by both seasonal and monthly climate variable models. Projections of future climate change suggest that average crop yield will increase with warmer temperatures and a longer growing season which is only partially offset by forecast increases in the variability of temperature and rainfall. The projections would also depend on future technological developments, which have generated significant increases in yield over time despite changing annual weather conditions.     

Modelling climate change impacts on maize growth and development in the Czech Republic

Summary The crop growth model CERES-Maize is used to estimate the direct (through enhanced fertilisation effect of ambient CO₂) and indirect (through changed climate conditions) effects of increased concentration of atmospheric CO₂ on maize yields. The analysis is based on multi-year crop model simulations run with daily weather series obtained alternatively by a direct modification of observed weather series and by a stochastic weather generator. The crop model is run in two settings: stressed yields are simulated in water and nutrient limited conditions, potential yields in water and nutrient unlimited conditions. The climate change scenario was constructed using the output from the ECHAM3/T42 model (temperature), regression relationships between temperature and solar radiation, and an expert judgement (precipitation). Results: (i) After omitting the two most extreme misfits, the standard error between the observed and modelled yields is 11%. (ii) The direct effect of doubled CO₂: The stressed yields would increase by 36–41% in the present climate and by 61–66% in the 2 × CO₂ climate. The potential yields would increase only by 9–10% as the improved water use efficiency does not apply. (iii) The indirect effect of doubled CO₂: The stressed yields would decrease by 27–29% (14–16%) at present (doubled) ambient CO₂ concentration. The increased temperature shortens the phenological phases and does not allow for the optimal development of the crop. The simultaneous decrease of precipitation and increase of temperature and solar radiation deepen the water stress, thereby reducing the yields. The reduction of the potential yields is significantly smaller as the effect of the increased water stress does not apply. (iv) If both direct and indirect effects of doubled CO₂ are considered, the stressed yields should increase by 17–18%, and the potential yields by 5–14%. (v) The decrease of the stressed yields due to the indirect effect may be reduced by applying earlier planting dates. Received March 9, 2001 Revised September 25, 2001     

MEAN AND VARIANCE CHANGE IN CLIMATE SCENARIOS: METHODS, AGRICULTURAL APPLICATIONS, AND MEASURES OF UNCERTAINTY

Our central goal is to determine the importance of including both mean and variability changes in climate change scenarios in an agricultural context. By adapting and applying a stochastic weather generator, we first tested the sensitivity of the CERES-Wheat model to combinations of mean and variability changes of temperature and precipitation for two locations in Kansas. With a 2°C increase in temperature with daily (and interannual) variance doubled, yields were further reduced compared to the mean only change. In contrast, the negative effects of the mean temperature increase were greatly ameliorated by variance decreased by one-half. Changes for precipitation are more complex, since change in variability naturally attends change in mean, and constraining the stochastic generator to mean change only is highly artificial. The crop model is sensitive to precipitation variance increases with increased mean and variance decreases with decreased mean. With increased mean precipitation and a further increase in variability Topeka (where wheat cropping is not very moisture limited) experiences decrease in yield after an initial increase from the 'mean change only case. At Goodland Kansas, a moisture-limited site where summer fallowing is practiced, yields are decreased with decreased precipitation, but are further decreased when variability is further reduced. The range of mean and variability changes to which the crop model is sensitive are within the range of changes found in regional climate modeling (RegCM) experiments for a CO₂ doubling (compared to a control run experiment). We then formed two types of climate change scenarios based on the changes in climate found in the control and doubled CO₂ experiments over the conterminous U. S. of RegCM: (1) one using only mean monthly changes in temperature, precipitation, and solar radiation; and (2) another that included these mean changes plus changes in daily (and interannual) variability. The scenarios were then applied to the CERES-Wheat model at four locations (Goodland, Topeka, Des Moines, Spokane) in the United States. Contrasting model responses to the two scenarios were found at three of the four sites. At Goodland, and Des Moines mean climate change increased mean yields and decreased yield variability, but the mean plus variance climate change reduced yields to levels closer to their base (unchanged) condition. At Spokane mean climate change increased yields, which were somewhat further increased with climate variability change. Three key aspects that contribute to crop response are identified: the marginality of the current climate for crop growth, the relative size of the mean and variance changes, and timing of these changes. Indices for quantifying uncertainty in the impact assessment were developed based on the nature of the climate scenario formed, and the magnitude of difference between model and observed values of relevant climate variables.     

Elevation Dependence of Winter Wheat Production in Eastern Washington State with Climate Change: A Methodological Study

Crop growth models, used in climate change impact assessments to project production on a local scale, can obtain the daily weather information to drive them from models of the Earth's climate. General Circulation Models (GCMs), often used for this purpose, provide weather information for the entire globe but often cannot depict details of regional climates especially where complex topography plays an important role in weather patterns. The U.S. Pacific Northwest is an important wheat growing region where climate patterns are difficult to resolve with a coarse scale GCM. Here, we use the PNNL Regional Climate Model (RCM) which uses a sub-grid parameterization to resolve the complex topography and simulate meteorology to drive the Erosion Productivity Impact Calculator (EPIC) crop model. The climate scenarios were extracted from the PNNL-RCM baseline and 2 × CO₂ simulationsfor each of sixteen 90 km² grid cells of the RCM, with differentiation byelevation and without correction for climate biases. The dominant agricultural soil type and farm management practices were established for each grid cell. Using these climate and management data in EPIC, we simulated winter wheat production in eastern Washington for current climate conditions (baseline) and a 2 × CO₂ `greenhouse' scenario of climate change.Dryland wheat yields for the baseline climate averaged 4.52 Mg ha^–1 across the study region. Yields were zero at high elevations where temperatures were too low to allow the crops to mature. The highest yields (7.32 Mgha^–1) occurred at intermediate elevations with sufficientprecipitation and mild temperatures. Mean yield of dryland winter wheat increased to 5.45 Mg ha^–1 for the 2 × CO₂ climate, which wasmarkedly warmer and wetter. Simulated yields of irrigated wheat were generally higher than dryland yields and followed the same pattern but were, of course, less sensitive to increases in precipitation. Increases in dryland and irrigated wheat yields were due, principally, to decreases in the frequency of temperature and water stress. This study shows that the elevation of a farm is a more important determinant of yield than farm location in eastern Washington and that climate changes would affect wheat yields at all farms in the study.     

Contributions of individual variation in temperature, solar radiation and precipitation to crop yield in the North China Plain, 1961–2003

An understanding of the relative impacts of the changes in climate variables on crop yield can help develop effective adaptation strategies to cope with climate change. This study was conducted to investigate the effects of the interannual variability and trends in temperature, solar radiation and precipitation during 1961–2003 on wheat and maize yields in a double cropping system at Beijing and Zhengzhou in the North China Plain (NCP), and to examine the relative contributions of each climate variable in isolation. 129 climate scenarios consisting of all the combinations of these climate variables were constructed. Each scenario contained 43 years of observed values of one variable, combined with values of the other two variables from each individual year repeated 43 times. The Agricultural Production Systems Simulator (APSIM) was used to simulate crop yields using the ensemble of generated climate scenarios. The results showed that the warming trend during the study period did not have significant impact on wheat yield potential at both sites, and only had significant negative impact on maize yield potential at Beijing. This is in contrast with previous results on effect of warming. The decreasing trend in solar radiation had a much greater impact on simulated yields of both wheat and maize crops, causing a significant reduction in potential yield of wheat and maize at Beijing. Although decreasing trends in rainfed yield of both simulated wheat and maize were found, the substantial interannual variability of precipitation made the trends less prominent.     

Climate Change Impacts and Adaptation Strategies in Spring Barley Production in the Czech Republic

The crop model CERES-Barley was used to assess the impacts of increased concentration of atmospheric CO₂ on growth and development of the most important spring cereal in Central and Western Europe, i.e., spring barley, and to examine possible adaptation strategies. Three experimental regions were selected to compare the climate change impacts in various climatic and pedological conditions. The analysis was based on multi-year crop model simulations run with daily weather series obtained by stochastic weather generator and included two yield levels: stressed yields and potential yields. Four climate change scenarios based on global climate models and representing 2 × CO₂ climate were applied. Results: (i) The crop model is suitable for use in the given environment, e.g., the coefficient of determination between the simulated and experimental yields equals 0.88. (ii) The indirect effect related to changed weather conditions is mostly negative. Its magnitude ranges from ?19% to +5% for the four scenarios applied at the three regions. (iii) The magnitude of the direct effect of doubled CO₂ on the stressed yields for the three test sites is 35–55% in the present climate and 25–65% in the 2 × CO₂ climates. (iv) The stressed yields would increase in 2 × CO₂ conditions by 13–52% when both direct and indirect effects were considered. (v) The impacts of doubled CO₂ on potential yields are more uniform throughout the localities in comparison with the stressed yields. The magnitude of the indirect and direct effects ranges from ?1 to ?9% and from +31 to +33%, respectively. Superposition of both effects results in 19–30% increase of the potential yields. (vi) Application of the earlier planting date (up to 60 days) would result in 15–22% increase of the yields in 2 × CO₂ conditions. (vii) Use of a cultivar with longer vegetation duration would bring 1.5% yield increase per one extra day of the vegetation season. (viii) The initial water content in the soil water profile proved to be one of the key elements determining the spring barley yield. It causes the yields to increase by 54–101 kg.ha^?1 per 1% increase of the available soil water content on the sowing day.     

Changes in Climate and Crop Production During the 20th Century in Argentina

This work was focused on the assessment of changes occurring in crop production and climate during the 20th century in Argentina. The study was carried out for nine sites located in the Pampas region that are representative of contrasting environments. We have considered the four main crops cultivated in this area (wheat, maize, sunflower and soybean). Historical climatic data and crop production related variables (yield, planted area, harvested area) were analyzed and, by means of crop simulation models, we quantified the impact of climate on crop yields. Changes occurring in climate during the three last decades of the 20th century were characterized by important increases in precipitation especially between October and March, decreases in maximum temperature and solar radiation in particular during spring and summer and increases in minimum temperature during almost all of the year. These changes contributed to increases in yields, especially in summer crops and in the semiarid zone, mostly due to increases in precipitation, although changes in temperature and radiation also affected crop yields but to a lesser extent. Comparing the period 1950–1970 with 1971–1999, yields increases attributable to changes in climate were 38% in soybean, 18% in maize, 13% in wheat, and 12% in sunflower while mean observed yield increases were 110% for maize, 56% for wheat and 102% for sunflower.     

Impacts of climate change as a function of global mean temperature: maize productivity and water use in China

Projections of future climate change are plagued with uncertainties from global climate models and emission scenarios, causing difficulties for impact assessments and for planners taking decisions on adaptation measure. Here, we developed an approach to deal with the uncertainties and to project the changes of maize productivity and water use in China using a process-based crop model, against a global mean temperature (GMT) increase scale relative to 1961?C1990 values. From 20 climate scenarios output from the Intergovernmental Panel on Climate Change Data Distribution Centre, we adopted the median values of projected changes in monthly mean climate variables for representative stations and driven the CERES-Maize model to simulate maize production under baseline and future climate scenarios. Adaptation options such as automatic planting, automatic application of irrigation and fertilization were considered, although cultivars were assumed constant over the baseline and future. After assessing representative stations across China, we projected changes in maize yield, growing period, evapotranspiration, and irrigation-water use for GMT changes of 1°C, 2°C, and 3°C, respectively. Results indicated that median values of projected decreases in the yields of irrigated maize without (with) consideration of CO₂-fertilization effects ranged from 1.4% to 10.9% (1.6% to 7.8%), 9.8% to 21.7% (10.2% to 16.4%), and 4.3% to 32.1% (3.9% to 26.6%) for GMT changes of 1°C, 2°C, and 3°C, respectively. Median values of projected changes in irrigation-water use without (with) consideration of CO₂-fertilization effects ranged from ?1.3% to 2.5% (?18.8% to 0.0%), ?43.6% to 2.4% (?56.1% to ?18.9%), and ?19.6% to 2.2% (?50.6% to ?34.3%), which were ascribed to rising CO₂ concentration, increased precipitation, as well as reduced growing period with GMT increasing. For rainfed maize, median values of projected changes in yields without (with) consideration of CO₂-fertilization effects ranged from ?22.2% to ?1.0% (?10.8% to 0.7%), ?27.6% to ?7.9% (?18.1% to ?5.6%), and ?33.7% to ?4.6% (?25.9% to ?1.6%). Approximate comparisons showed that projected maize yield losses were larger than previous estimates, particularly for rainfed maize. Our study presents an approach to project maize productivity and water use with GMT increases using process-based crop models and multiple climate scenarios. The resultant impact function is fundamental for identifying which climate change level is dangerous for food security.     

The effect of changes in daily and interannual climatic variability on CERES-Wheat: A sensitivity study

We investigate the effect of changes in daily and interannual variability of temperature and precipitation on yields simulated by the CERES-Wheat model at two locations in the central Great Plains. Changes in variability were effected by adjusting parameters of the Richardson daily weather generator. Two types of changes in precipitation were created: one with both intensity and frequency changed; and another with change only in persistence. In both types mean total monthly precipitation is held constant. Changes in daily (and interannual) variability of temperature result in substantial changes in the mean and variability of simulated wheat yields. With a doubling of temperature variability, large reductions in mean yield and increases in variability of yield result primarily from crop failures due to winter kill at both locations. Reduced temperature variability has little effect. Changes in daily precipitation variability also resulted in substantial changes in mean and variability of yield. Interesting interactions of the precipitation variability changes with the contrasting base climates are found at the two locations. At one site where soil moisture is not limiting, mean yield decreased and variability of yield increased with increasing precipitation variability, whereas mean yields increased at the other location, where soil moisture is limiting. Yield changes were similar for the two different types of precipitation variability change investigated. Compared to an earlier study for the same locations wherein variability changes were effected by altering observed time series, and the focus was on interannual variability, the present results for yield changes are much more substantial. This study demonstrates the importance of taking into account change in daily (and interannual) variability of climate when analyzing the effect of climate change on crop yields.The National Center for Atmospheric Research is sponsored by the National Science Foundation.     

Effects of drought on winter wheat yield in north China during 2012�C2100

Winter wheat is one of China’s most important staple food crops, and its production is strongly influenced by weather, especially droughts. As a result, the impact of drought on the production of winter wheat is associated with the food security of China. Simulations of future climate for scenarios A2 and A1B provided by GFDL-CM2, MPI_ECHAM5, MRI_CGCM2, NCAR_CCSM3, and UKMO_HADCM3 during 2001-2100 are used to project the influence of drought on winter wheat yields in North China. Winter wheat yields are simulated using the crop model WOFOST (WOrld FOod STudies). Future changes in temperature and precipitation are analyzed. Temperature is projected to increase by 3.9-5.5 for scenario A2 and by 2.9-5.1 for scenario A1B, with fairly large interannual variability. Mean precipitation during the growing season is projected to increase by 16.7 and 8.6 mm (10 yr)-1 , with spring precipitation increasing by 9.3 and 4.8 mm (10 yr)-1 from 2012-2100 for scenarios A2 and A1B, respectively. For the next 10-30 years (2012-2040), neither the growing season precipitation nor the spring precipitation over North China is projected to increase by either scenario. Assuming constant winter wheat varieties and agricultural practices, the influence of drought induced by short rain on winter wheat yields in North China is simulated using the WOFOST crop model. The drought index is projected to decrease by 9.7% according to scenario A2 and by 10.3% according to scenario A1B during 2012-2100. This indicates that the drought influence on winter wheat yields may be relieved over that period by projected increases in rain and temperature as well as changes in the growth stage of winter wheat. However, drought may be more severe in the near future, as indicated by the results for the next 10-30 years.     

Sensitivity of carbon budget to historical climate variability and atmospheric CO2 concentration in temperate grassland ecosystems in China

Chinese temperate grasslands play an important role in the terrestrial carbon cycle. Based on the parameterization and validation of Terrestrial Ecosystem Model (TEM, Version 5.0), we analyzed the carbon budgets of Chinese temperate grasslands and their responses to historical atmospheric CO₂ concentration and climate variability during 1951–2007. The results indicated that Chinese temperate grassland acted as a slight carbon sink with annual mean value of 7.3 T?g C, ranging from -80.5 to 79.6 T?g C yr^-1. Our sensitivity experiments further revealed that precipitation variability was the primary factor for decreasing carbon storage. CO₂ fertilization may increase the carbon storage (1.4 %) but cannot offset the proportion caused by climate variability (-15.3 %). Impacts of CO₂ concentration, temperature and precipitation variability on Chinese temperate grassland cannot be simply explained by the sum of the individual effects. Interactions among them increased total carbon storage of 56.6 T?g C which 14.2 T?g C was stored in vegetation and 42.4 T?g C was stored in soil. Besides, different grassland types had different responses to climate change and CO₂ concentration. NPP and R_H of the desert and forest steppes were more sensitive to precipitation variability than temperature variability while the typical steppe responded to temperature variability more sensitively than the desert and forest steppes.     

Impacts of Present and Future Climate Variability on Agriculture and Forestry in the Temperate Regions: Europe

Agriculture and forestry will be particularly sensitive to changes in mean climate and climate variability in the northern and southern regions of Europe. Agriculture may be positively affected by climate change in the northern areas through the introduction of new crop species and varieties, higher crop production and expansion of suitable areas for crop cultivation. The disadvantages may be determined by an increase in need for plant protection, risk of nutrient leaching and accelerated breakdown of soil organic matter. In the southern areas the benefits of the projected climate change will be limited, while the disadvantages will be predominant. The increased water use efficiency caused by increasing CO₂ will compensate for some of the negative effects of increasing water limitation and extreme weather events, but lower harvestable yields, higher yield variability and reduction in suitable areas of traditional crops are expected for these areas. Forestry in the Mediterranean region may be mainly affected by increases in drought and forest fires. In northern Europe, the increased precipitation is expected to be large enough to compensate for the increased evapotranspiration. On the other hand, however, increased precipitation, cloudiness and rain days and the reduced duration of snow cover and soil frost may negatively affect forest work and timber logging determining lower profitability of forest production and a decrease in recreational possibilities. Adaptation management strategies should be introduced, as effective tools, to reduce the negative impacts of climate change on agricultural and forestry sectors.     

Climate Change Impacts for the Conterminous USA: An Integrated Assessment

Here we simulate dryland agriculture in the United States in order to assess potential future agricultural production under a set of general circulation model (GCM)-based climate change scenarios. The total national production of three major grain crops—corn, soybeans, and winter wheat—and two forage crops—alfalfa and clover hay—is calculated for the actual present day core production area (CPA) of each of these crops. In general, higher global mean temperature (GMT) reduces production and higher atmospheric carbon dioxide concentration ([CO₂]) increases production. Depending on the climatic change scenarios employed overall national production of the crops studied changes by up to plus or minus 25% from present-day levels. Impacts are more significant regionally, with crop production varying by greater than ±50% from baseline levels. Analysis of currently possible production areas (CPPAs) for each crop indicates that the regions most likely to be affected by climate change are those on the margins of the areas in which they are currently grown. Crop yield variability was found to be primarily influenced by local weather and geographic features rather than by large-scale changes in climate patterns and atmospheric composition. Future US agronomic potential will be significantly affected by the changes in climate projected here. The nature of the crop response will depend primarily on to what extent precipitation patterns change and also on the degree of warming experienced.