Climate change impacts on regional rice production in China

Rice (Oryza sativa L.) production is an important contributor to China’s food security. Climate change, and its impact on rice production, presents challenges in meeting China’s future rice production requirements. In this study, we conducted a comprehensive analysis of how rice yield responds to climate change under different scenarios and assessed the associated simulation uncertainties of various regional-scale climate models. Simulation was performed based on a regional calibrated crop model (CERES-Rice) and spatially matched climatic (from 17 global climate models), soil, management, and cultivar parameters. Grain-filling periods for early rice were shortened by 2–7 days in three time slices (2030s, 2050s, and 2070s), whereas grain-filling periods for late rice were shortened by 10–19 days in three time slices. Most of the negative effects of climate change were predicted to affect single-crop rice in central China. Average yields of single-crop rice treated with CO₂ fertiliser in central China were predicted to be reduced by 10, 11, and 11% during the 2030s, 2050s, and 2070s, respectively, compared to the 2000s, if planting dates remained unchanged. If planting dates were optimised, single-crop rice yields were predicted to increase by 3, 7, and 11% during the 2030s, 2050s, and 2070s, respectively. In response to climate changes, early and single-crop rice should be planted earlier, and late rice planting should be delayed. The predicted net effect would be to prolong the grain-filling period and optimise rice yield.     

Modelling China’s potential maize production at regional scale under climate change

With the continuing warming due to greenhouse gases concentration, it is important to examine the potential impacts on regional crop production spatially and temporally. We assessed China’s potential maize production at 50 × 50 km grid scale under climate change scenarios using modelling approach. Two climate changes scenarios (A2 and B2) and three time slices (2011–2040, 2041–2070, 2071–2100) produced by the PRECIS Regional Climate Model were used. Rain-fed and irrigated maize yields were simulated with the CERES-Maize model, with present optimum management practices. The model was run for 30 years of baseline climate and three time slices for the two climate change scenarios, without and with simulation of direct CO₂ fertilization effects. Crop simulation results under climate change scenarios varied considerably between regions and years. Without the CO₂ fertilization effect, China’s maize production was predicted to suffer a negative effect under both A2 and B2 scenarios for all time slices, with greatest production decreases in today’s major maize planting areas. When the CO₂ fertilization effect is taken into account, production was predicted to increase for rain-fed maize but decrease for irrigated maize, under both A2 and B2 scenarios for most time periods.     

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.     

Assessing the impacts of climate change on rice yields in the main rice areas of China

This paper assesses the impact of climate change on irrigated rice yield using B2 climate change scenario from the Regional Climate Model (RCM) and CERES-rice model during 2071--2090. Eight typical rice stations ranging in latitude, longitude, and elevation that are located in the main rice ecological zones of China are selected for impact assessment. First, Crop Estimation through Resource and Environment Synthesis (CERES)-rice model is validated using farm experiment data in selected stations. The simulated results represent satisfactorily the trend of flowering duration and yields. The deviation of simulation within ± 10% of observed flowering duration and ± 15% of observed yield. Second, the errors of the outputs of RCM due to the difference of topography between station point and grid point is corrected. The corrected output of the RCM used for simulating rice flowering duration and yield is more reliable than the not corrected. Without CO₂ direct effect on crop, the results from the assessment explore that B2 climate change scenario would have a negative impact on rice yield at most rice stations and have little impacts at Fuzhou and Kunming. To find the change of inter-annual rice yield, a preliminary assessment is made based on comparative cumulative probability at low and high yield and the coefficient variable of yield between the B2 scenario and baseline. Without the CO₂ direct effect on rice yield, the result indicates that frequency for low yield would increase and it reverses for high yield, and the variance for rice yield would increase. It is concluded that high frequency at low yield and high variances of rice yield could pose a threat to rice yield at most selected stations in the main rice areas of China. With the CO₂ direct effect on rice yield, rice yield increase in all selected stations.     

Effects of Climate Change on Rice Production in the Tropical Humid Climate of Kerala, India

The CERES-Rice v3. crop simulation model, calibrated and validated for its suitability to simulate rice production in the tropical humid climate Kerala State of India, is used for analysing the effect of climate change on rice productivity in the state. The plausible climate change scenario for the Indian subcontinent as expected by the middle of the next century, taking into account the projected emissions of greenhouse gases and sulphate aerosols, in a coupled atmosphere-ocean model experiment performed at Deutsches Klimarechenzentrum, Germany, is adopted for the study. The adopted scenario represented an increase in monsoon seasonal mean surface temperature of the order of about 1.5°C, and an increase in rainfall of the order of 2 mm per day, over the state of Kerala in the decade 2040–2049 with respect to the 1980s. The IPCC Business-as-usual scenario projection of plant usable concentration of CO₂ about 460 PPM by the middle of the next century are also used in the crop model simulation. On an average over the state with the climate change scenario studied, the rice maturity period is projected to shorten by 8% and yield increase by 12%. When temperature elevations only are taken into consideration, the crop simulations show a decrease of 8% in crop maturity period and 6% in yield. This shows that the increase in yield due to fertilisation effect of elevated CO₂ and increased rainfall over the state as projected in the climate change scenario nearly makes up for the negative impact on rice yield due to temperature rise. The sensitivity experiments of the rice model to CO₂ concentration changes indicated that over the state, an increase in CO₂ concentration leads to yield increase due to its fertilisation effect and also enhance the water use efficiency of the paddy. The temperature sensitivity experiments have shown that for a positive change in temperature up to 5°C, there is a continuous decline in the yield. For every one degree increment the decline in yield is about 6%. Also, in another experiment it is observed that the physiological effect of ambient CO₂ at 425 ppm concentration compensated for the yield losses due to increase in temperature up to 2°C. Rainfall sensitivity experiments have shown that increase in rice yield due to increase in rainfall above the observed values is near exponential. But decrease in rainfall results in yield loss at a constant rate of about 8% per 2 mm/day, up to about 16 mm/day.     

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.     

An estimate of equilibrium sensitivity of global terrestrial carbon cycle using NCAR CCSM4

Increasing concentrations of atmospheric CO₂ influence climate, terrestrial biosphere productivity and ecosystem carbon storage through its radiative, physiological and fertilization effects. In this paper, we quantify these effects for a doubling of CO₂ using a low resolution configuration of the coupled model NCAR CCSM4. In contrast to previous coupled climate-carbon modeling studies, we focus on the near-equilibrium response of the terrestrial carbon cycle. For a doubling of CO₂, the radiative effect on the physical climate system causes global mean surface air temperature to increase by 2.14 K, whereas the physiological and fertilization on the land biosphere effects cause a warming of 0.22 K, suggesting that these later effects increase global warming by about 10 % as found in many recent studies. The CO₂-fertilization leads to total ecosystem carbon gain of 371 Gt-C (28 %) while the radiative effect causes a loss of 131 Gt-C (~10 %) indicating that climate warming damps the fertilization-induced carbon uptake over land. Our model-based estimate for the maximum potential terrestrial carbon uptake resulting from a doubling of atmospheric CO₂ concentration (285–570 ppm) is only 242 Gt-C. This highlights the limited storage capacity of the terrestrial carbon reservoir. We also find that the terrestrial carbon storage sensitivity to changes in CO₂ and temperature have been estimated to be lower in previous transient simulations because of lags in the climate-carbon system. Our model simulations indicate that the time scale of terrestrial carbon cycle response is greater than 500 years for CO₂-fertilization and about 200 years for temperature perturbations. We also find that dynamic changes in vegetation amplify the terrestrial carbon storage sensitivity relative to a static vegetation case: because of changes in tree cover, changes in total ecosystem carbon for CO₂-direct and climate effects are amplified by 88 and 72 %, respectively, in simulations with dynamic vegetation when compared to static vegetation simulations.     

Response of Soybean and Sorghum to Varying Spatial Scales of Climate Change Scenarios in the Southeastern United States

This study examines how uncertainty associated with the spatial scale of climate change scenarios influences estimates of soybean and sorghum yield response in the southeastern United States. We investigated response using coarse (300-km, CSIRO) and fine (50-km, RCM) scale climate change scenarios and considering climate changes alone, climate changes with CO₂ fertilization, and climate changes with CO₂ fertilization and adaptation. Relative to yields simulatedunder a current, control climate scenario, domain-wide soybean yield decreased by 49% with the coarse-scale climate change scenario alone, and by26% with consideration for CO₂ fertilization. By contrast, thefine-scale climate change scenario generally exhibited higher temperatures and lower precipitation in the summer months resulting in greater yield decreases (69% for climate change alone and 54% with CO₂fertilization). Changing planting date and shifting cultivars mitigated impacts, but yield still decreased by 8% and 18% respectively for the coarse andfine climate change scenarios. The results were similar for sorghum. Yield decreased by 51%, 42%, and 15% in response to fine-scaleclimate change alone, CO₂ fertilization, and adaptation cases, respectively– significantly worse than with the coarse-scale (CSIRO) scenarios. Adaptation strategies tempered the impacts of moisture and temperature stress during pod-fill and grain-fill periods and also differed with respect to the scale of the climate change scenario.     

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.     

Predicted changes in fire weather suggest increases in lightning fire initiation and future area burned in the mixedwood boreal forest

Forecasting future fire activity as a function of climate change is a step towards understanding the future state of the western mixedwood boreal ecosystem. We developed five annual weather indices based on the Daily Severity Rating (DSR) of the Canadian Forest Fire Weather Index System and estimated their relationship with annual, empirical counts of lightning fire initiation for 588 landscapes in the mixedwood boreal forest in central-eastern Alberta, Canada from data collected between 1983 and 2001 using zero-inflated negative binomial regression models. Two indices contributed to a parsimonious model of initiation; these were Seasonal Severity Rating (SSR), and DSR-sequence count. We used parameter estimates from this model to predict lightning fire initiation under weather conditions predicted in 1 × CO₂ (1975–1985), 2 × CO₂ (2040–2049) and 3 × CO₂ (2080–2089) conditions simulated by the Canadian Regional Climate Model (CRCM). We combined predicted initiation rates for these conditions with existing empirical estimates of the number of fire initiations that grow to be large fires (fire escapes) and the fire size distribution for the region, to predict the annual area burned by lightning-caused fires in each of the three climate conditions. We illustrated a 1.5-fold and 1.8-fold increase of lightning fire initiation by 2040–2049 and 2080–2089 relative to 1975–1985 conditions due to changes in fire weather predicted by the CRCM; these increases were calculated independent of changes in lightning activity. Our simulations suggested that weather-mediated increases in initiation frequency could correspond to a substantial increase in future area burned with 1.9-fold and 2.6-fold increases in area burned in 2040–2049 and 2080–2089 relative to 1975–1985 conditions, respectively. We did not include any biotic effects in these estimates, though future patterns of initiation and fire growth will be regulated not only by weather, but also by vegetation and fire management.     

Can ocean iron fertilization mitigate ocean acidification?

Ocean iron fertilization has been proposed as a method to mitigate anthropogenic climate change, and there is continued commercial interest in using iron fertilization to generate carbon credits. It has been further speculated that ocean iron fertilization could help mitigate ocean acidification. Here, using a global ocean carbon cycle model, we performed idealized ocean iron fertilization simulations to place an upper bound on the effect of iron fertilization on atmospheric CO₂ and ocean acidification. Under the IPCC A2 CO₂ emission scenario, at year 2100 the model simulates an atmospheric CO₂ concentration of 965 ppm with the mean surface ocean pH 0.44 units less than its pre-industrial value of 8.18. A globally sustained ocean iron fertilization could not diminish CO₂ concentrations below 833 ppm or reduce the mean surface ocean pH change to less than 0.38 units. This maximum of 0.06 unit mitigation in surface pH change by the end of this century is achieved at the cost of storing more anthropogenic CO₂ in the ocean interior, furthering acidifying the deep-ocean. If the amount of net carbon storage in the deep ocean by iron fertilization produces an equivalent amount of emission credits, ocean iron fertilization further acidifies the deep ocean without conferring any chemical benefit to the surface ocean.     

Future cereal production in China: The interaction of climate change,water availability and socio-economic scenarios

Food production in China is a fundamental component of the national economy and driver of agricultural policy. Sustaining and increasing output to meet growing demand faces significant challenges including climate change, increasing population, agricultural land loss and competing demands for water. Recent warming in China is projected to accelerate by climate models with associated changes in precipitation and frequency of extreme events. How changes in cereal production and water availability due to climate change will interact with other socio-economic pressures is poorly understood. By linking crop and water simulation models and two scenarios of climate (derived from the Regional Climate Model PRECIS) and socio-economic change (downscaled from IPCC SRES A2 and B2) we demonstrate that by the 2040s the absolute effects of climate change are relatively modest. The interactive effects of other drivers are negative, leading to decreases in total production of ?18% (A2) and ?9% (B2). Outcomes are highly dependent on climate scenario, socio-economic development pathway and the effects of CO₂ fertilization on crop yields which may almost totally offset the decreases in production. We find that water availability plays a significant limiting role on future cereal production, due to the combined effects of higher crop water requirements (due to climate change) and increasing demand for non-agricultural use of water (due to socio-economic development). Without adaptation, per capita cereal production falls in all cases, by up to 40% of the current baseline.By simulating the effects of three adaptation scenarios we show that for these future scenarios China is able to maintain per capita cereal production, given reasonable assumptions about policies on land and water management and progress in agricultural technology. Our results are optimistic because PRECIS simulates much wetter conditions than a multi-model average, the CO₂ crop yield response function is highly uncertain and the effects of extreme events on crop growth and water availability are likely to be underestimated.     

Potential impact of future climate change on crop yield in northeastern China

We evaluated the potential impact of future climate change on spring maize and single-crop rice in northeastern China(NEC) by employing climate and crop models. Based on historical data, diurnal temperature change exhibited a distinct negative relationship with maize yield, whereas minimum temperature correlated positively to rice yield. Corresponding to the evaluated climate change derived from coupled climate models included in the Coupled Model Intercomparison Project Phase 5(CMIP5) under the Representative Concentration Pathway 4.5 scenario(RCP4.5), the projected maize yield changes for three future periods [2010–39(period 1), 2040–69(period 2), and 2070–99(period 3)] relative to the mean yield in the baseline period(1976–2005) were 2.92%, 3.11% and 2.63%, respectively. By contrast, the evaluated rice yields showed slightly larger increases of 7.19%, 12.39%, and 14.83%, respectively. The uncertainties in the crop response are discussed by considering the uncertainties obtained from both the climate and the crop models. The range of impact of the uncertainty became markedly wider when integrating these two sources of uncertainty. The probabilistic assessments of the evaluated change showed maize yield to be relatively stable from period 1 to period 3, while the rice yield showed an increasing trend over time. The results presented in this paper suggest a tendency of the yields of maize and rice in NEC to increase(but with great uncertainty) against the background of global warming, which may offer some valuable guidance to government policymakers.     

An assessment of regional vulnerability of rice to climate change in India

A simulation analysis was carried out using the InfoCrop-rice model to quantify impacts and adaptation gains, as well as to identify vulnerable regions for irrigated and rain fed rice cultivation in future climates in India. Climates in A1b, A2, B1 and B2 emission scenarios as per a global climate model (MIROC3.2.HI) and a regional climate model (PRECIS) were considered for the study. On an aggregated scale, the mean of all emission scenarios indicate that climate change is likely to reduce irrigated rice yields by ~4 % in 2020 (2010–2039), ~7 % in 2050 (2040–2069), and by ~10 % in 2080 (2070–2099) climate scenarios. On the other hand, rainfed rice yields in India are likely to be reduced by ~6 % in the 2020 scenario, but in the 2050 and 2080 scenarios they are projected to decrease only marginally (<2.5 %). However, spatial variations exist for the magnitude of the impact, with some regions likely to be affected more than others. Adaptation strategies comprising agronomical management can offset negative impacts in the near future—particularly in rainfed conditions—but in the longer run, developing suitable varieties coupled with improved and efficient crop husbandry will become essential. For irrigated rice crop, genotypic and agronomic improvements will become crucial; while for rainfed conditions, improved management and additional fertilizers will be needed. Basically climate change is likely to exhibit three types of impacts on rice crop: i) regions that are adversely affected by climate change can gain in net productivity with adaptation; ii) regions that are adversely affected will still remain vulnerable despite adaptation gains; and iii) rainfed regions (with currently low rainfall) that are likely to gain due to increase in rainfall can further benefit by adaptation. Regions falling in the vulnerable category even after suggested adaptation to climate change will require more intensive, specific and innovative adaptation options. The present analysis indicates the possibility of substantial improvement in yields with efficient utilization of inputs and adoption of improved varieties.     

Expert assessment of vulnerability of permafrost carbon to climate change

Approximately 1700 Pg of soil carbon (C) are stored in the northern circumpolar permafrost zone, more than twice as much C than in the atmosphere. The overall amount, rate, and form of C released to the atmosphere in a warmer world will influence the strength of the permafrost C feedback to climate change. We used a survey to quantify variability in the perception of the vulnerability of permafrost C to climate change. Experts were asked to provide quantitative estimates of permafrost change in response to four scenarios of warming. For the highest warming scenario (RCP 8.5), experts hypothesized that C release from permafrost zone soils could be 19–45 Pg C by 2040, 162–288 Pg C by 2100, and 381–616 Pg C by 2300 in CO₂ equivalent using 100-year CH₄ global warming potential (GWP). These values become 50 % larger using 20-year CH₄ GWP, with a third to a half of expected climate forcing coming from CH₄ even though CH₄ was only 2.3 % of the expected C release. Experts projected that two-thirds of this release could be avoided under the lowest warming scenario (RCP 2.6). These results highlight the potential risk from permafrost thaw and serve to frame a hypothesis about the magnitude of this feedback to climate change. However, the level of emissions proposed here are unlikely to overshadow the impact of fossil fuel burning, which will continue to be the main source of C emissions and climate forcing.     

Comparison of Agricultural Impacts of Climate Change Calculated from High and Low Resolution Climate Change Scenarios: Part II. Accounting for Adaptation and CO2 Direct Effects

We assert that the simulation of fine-scale crop growth processes and agronomic adaptive management using coarse-scale climate change scenarios lower confidence in regional estimates of agronomic adaptive potential. Specifically, we ask: 1) are simulated yield responses tolow-resolution climate change, after adaptation (without and with increased atmospheric CO₂), significantly different from simulated yield responses tohigh-resolution climate change, after adaptation (without and with increased atmospheric CO₂)? and 2) does the scale of the soils information, in addition to the scale of the climate change information, affect yields after adaptation? Equilibrium (1 × CO₂ versus 2 × CO₂)climate changes are simulated at two different spatial resolutions in the Great Plains using the CSIRO general circulation model (low resolution) and the National Center for Atmospheric Research (NCAR) RegCM2 regional climate model (high resolution). The EPIC crop model is used to simulate the effects of these climate changes; adaptations in EPIC include earlier planting and switch to longer-season cultivars. Adapted yields (without and with additional carbon dioxide) are compared at the different spatial resolutions. Our findings with respect to question 1 suggest adaptation is more effective in most cases when simulated with a higher resolution climate change than its more generalized low resolution equivalent. We are not persuaded that the use of high resolution climate change information provides insights into the direct effects of higher atmospheric CO₂ levels on crops beyond what can be obtained with low resolution information. However, this last finding may be partly an artifact of the agriculturally benign CSIRO and RegCM2 climate changes. With respect to question 2, we found that high resolution details of soil characteristics are particularly important to include in adaptation simulations in regions typified by soils with poor water holding capacity.     

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.     

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.     

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.     

Possible Impacts of Global Warming on the Hydrology of the Ogallala Aquifer Region

The Ogallala or High Plains aquifer provides water for about 20% of the irrigated land in the United States. About 20 km³ (16.6 million acre-feet) of water are withdrawn annually from this aquifer. In general, recharge has not compensated for withdrawals since major irrigation development began in this region in the 1940s. The mining of the Ogallala has been pictured as an analogue to climate change in that many GCMs predict a warmer and drier future for this region. In this paper we attempt to anticipate the possible impacts of climate change on the sustainability of the aquifer as a source of water for irrigation and other purposes in the region. We have applied HUMUS, the Hydrologic Unit Model of the U.S. to the Missouri and Arkansas-White-Red water resource regions that overlie the Ogallala. We have imposed three general circulation model (GISS, UKTR and BMRC) projections of future climate change on this region and simulated the changes that may be induced in water yields (runoff plus lateral flow) and ground water recharge. Each GCM was applied to HUMUS at three levels of global mean temperature (GMT) to represent increasing severity of climate change (a surrogate for time). HUMUS was also run at three levels of atmospheric CO₂ concentration (hereafter denoted by [CO₂]) in order to estimate the impacts of direct CO₂ effects on photosynthesis and evapotranspiration. Since the UKTR and GISS GCMs project increased precipitation in the Missouri basin, water yields increase there. The BMRC GCM predicts sharply decreased precipitation and, hence, reduced water yields. Precipitation reductions are even greater in the Arkansas basin under BMRC as are the consequent water yield losses. GISS and UKTR climates lead to only moderate yield losses in the Arkansas. CO₂-fertilization reverses these losses and yields increase slightly. CO₂ fertilization increases recharge in the base (no climate change) case in both basins. Recharge is reduced under all three GCMs and severities of climate change.