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     

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.     

Climate change impacts on dryland cropping systems in the Central Great Plains,USA

Agricultural systems models are essential tools to assess potential climate change (CC) impacts on crop production and help guide policy decisions. In this study, impacts of projected CC on dryland crop rotations of wheat-fallow (WF), wheat-corn-fallow (WCF), and wheat-corn-millet (WCM) in the U.S. Central Great Plains (Akron, Colorado) were simulated using the CERES V4.0 crop modules in RZWQM2. The CC scenarios for CO₂, temperature and precipitation were based on a synthesis of Intergovernmental Panel on Climate Change (IPCC 2007) projections for Colorado. The CC for years 2025, 2050, 2075, and 2100 (CC projection years) were super-imposed on measured baseline climate data for 15–17 years collected during the long-term WF and WCF (1992–2008), and WCM (1994–2008) experiments at the location to provide inter-annual variability. For all the CC projection years, a decline in simulated wheat yield and an increase in actual transpiration were observed, but compared to the baseline these changes were not significant (p > 0.05) in all cases but one. However, corn and proso millet yields in all rotations and projection years declined significantly (p < 0.05), which resulted in decreased transpiration. Overall, the projected negative effects of rising temperatures on crop production dominated over any positive impacts of atmospheric CO₂ increases in these dryland cropping systems. Simulated adaptation via changes in planting dates did not mitigate the yield losses of the crops significantly. However, the no-tillage maintained higher wheat yields than the conventional tillage in the WF rotation to year 2075. Possible effects of historical CO₂ increases during the past century (from 300 to 380 ppm) on crop yields were also simulated using 96 years of measured climate data (1912–2008) at the location. On average the CO₂ increase enhanced wheat yields by about 30%, and millet yields by about 17%, with no significant changes in corn yields.     

Projected temperature changes indicate significant increase in interannual variability of U.S. maize yields

Climate change has the potential to be a source of increased variability if crops are more frequently exposed to damaging weather conditions. Yield variability could respond to a shift in the frequency of extreme events to which crops are susceptible, or if weather becomes more variable. Here we focus on the United States, which produces about 40% of the world’s maize, much of it in areas that are expected to see increased interannual variability in temperature. We combine a statistical crop model based on historical climate and yield data for 1950–2005 with temperature and precipitation projections from 15 different global circulation models. Holding current growing area constant, aggregate yields are projected to decrease by an average of 18% by 2030–2050 relative to 1980–2000 while the coefficient of variation of yield increases by an average of 47%. Projections from 13 out of 15 climate models result in an aggregate increase in national yield coefficient of variation, indicating that maize yields are likely to become more volatile in this key growing region without effective adaptation responses. Rising CO₂ could partially dampen this increase in variability through improved water use efficiency in dry years, but we expect any interactions between CO₂ and temperature or precipitation to have little effect on mean yield changes.     

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.     

Effects of changes in temperature and CO2 concentration on simulated spring wheat yields in The Netherlands

A crop growth simulation model based on SUCROS87 was constructed to study the effects of temperature rise and increase of the atmospheric CO₂ concentration on spring wheat yields in The Netherlands. The model simulated potential production (limited by crop characteristics, temperature and radiation but without any stress from water or nutrient shortages or pests, diseases and weeds) and water-limited production in which growth is also limited by water shortage. The model was validated for the present climatic conditions. When daily weather data from a nearby station were used, the model was well able to simulate yields obtained in field experiments.Effects of several combinations of temperature rise and atmospheric CO₂ concentration on simulated yields were studied. A temperature rise resulted in a reduction in simulated yield due to shortening of the growing period. Large variations existed in the magnitude of this reduction. Increases in atmospheric CO₂ concentration led to yield increases due to higher assimilation rates and to increase of the water use efficiency. Combination of temperature rise and higher CO₂ concentration resulted in small yield increases in years in which water was not limiting growth and large yield increases in dry years.Change of variety or of sowing date could not reduce the negative effects of temperature rise on simulated yields.     

Impact assessment of climate change,carbon dioxide fertilization and constant growing season on rice yields in China

Rice is the staple food in China, and the country’s enlarging population puts increasing pressure on its rice production as well as on that of the world. In this study, we estimate the impact of climate change, CO₂ fertilization, crop adaptation and the interactions of these three factors on the rice yields of China using model simulation with four hypothetical scenarios. According to the results of the model simulation, the rice yields without CO₂ fertilization are predicted to decrease by 3.3 % in the 2040s. Considering a constant rice-growing season (GS), the rice yields are predicted to increase by 3.2 %. When the effect of CO₂ fertilization is integrated into the Agro-C model, the expected rice yields increase by 20.9 %. When constant GS and CO₂ fertilization are both integrated into the model, the predicted rice yield increases by 28.6 %. In summary, the rice yields in China are predicted to decrease in the 2040s by 0.22 t/ha due to climate change, to increase by 0.44 t/ha due to a constant GS and to increase by 1.65 t/ha due to CO₂ fertilization. The benefits of crop adaptation would completely offset the negative impact of climate change. In the future, the most of the positive effects of climate change are expected to occur in northeastern and northwestern China, and the expansion of rice cultivation in northeastern China should further enhance the stability of rice production in China.     

The impacts of climate change on the winter hardiness zones of woody plants in Europe

The potential impacts of climate change on potatoes cropping in the Peruvian highlands (Altiplano) is assessed using climate projections for 2071–2100, obtained from the HadRM3P regional atmospheric model of the Hadley Centre. The atmospheric model is run under two different special report on emission scenarios: high CO₂ concentration (A2) and moderate CO₂ concentration (B2) for four locations situated in the surroundings of Lake Titicaca. The two main varieties of potato cultivated in the area are studied: the Andean potato (Solanum tuberosum) and the bitter potato (Solanum juzepczukii). A simple process-oriented model is used to quantify the climatic impacts on crops cycles and yields by combining the effects of temperature on phenology, of radiation and CO₂ on maximum yield and of water balance on yield deficit. In future climates, air temperature systematically increases, precipitation tends to increase at the beginning of the rainy season and slightly decreases during the rest of the season. The direct effects of these climatic changes are earlier planting dates, less planting failures and shorter crop cycles in all the four locations and for both scenarios. Consequently, the harvesting dates occur systematically earlier: roughly in January for the Andean potato instead of March in the current situation and in February for the bitter potato instead of April. Overall, yield deficits will be higher under climate change than in the current climate. There will be a strong negative impact on yields for S. tuberosum (stronger under A2 scenario than under B2); the impact on S. juzepczukii yields, however, appears to be relatively mixed and not so negative.     

Influence d'un changement climatique dû à une hausse de gaz à effet de serre sur l'agriculture au quebec

Abstract

This study, using a climate change scenario generated by the Canadian Climate Centre (CCC) general circulation model (GCM) examines the impacts of such a climate change on agriculture in southern Quebec. Using a crop model from the Food and Agriculture Organization (FAO), yield responses of a variety of cereals, legumes, oleaginous and special crops to climate change are analysed and discussed.

Results show that under the 2 × CO₂ climate scenario the growing season would be longer and accumulation of corn heat units and growing degree days would be more important than under actual climate (1961–1990). One of the more important results of this study is that, on the one hand yield of C₃ cereals would be lower and that of C₄ cereals higher in most agricultural regions. On the other hand, the direct fertilisation effect of increased CO₂ is not considered. It must be cautioned however that we can not generalise results obtained for one legume crop to all legumes.     

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.     

Effects of climate change on grain maize yield potential in the european community

Grain maize yield in the main arable areas of the European Community (E.C.) was calculated with a simulation model, WOFOST, using historical weather data and average soil characteristics. The sensitivity of the model to individual weather variables was determined. Subsequent analyses were made using climate change scenarios with and without the direct effects of increased atmospheric CO₂. The impact of crop management (sowing date, irrigation and cultivar type) in a changed climate was also assessed. Scenario climate change generally results in larger grain yields for the northern E.C., similar or slightly smaller yields for the central E.C. and considerably smaller yields for the southern E.C. The various climate change scenarios used appear to give considerably different changes in grain yield, both for each location and for the E.C. as a whole. Management analyses show that for both current and scenario climates the largest grain yield will be attained by varieties with an early start of grain filling, that average irrigation requirements to attain potential grain yield in the E.C. will increase with climate change but will decrease with both increased CO₂ and climate change, and that sowing at both current and scenarios climate should occur as early as possible.The U.S. Government right to retain a nonexclusive, royalty-free licence in and to any copyright is acknowledged.     

Changes in Soybean Yields in the Midwestern United States as a Result of Future Changes in Climate, Climate Variability, and CO2 Fertilization

This modeling study addresses the potential impacts of climate change and changing climate variability due to increased atmospheric CO₂ concentration on soybean (Glycine max (L.) Merrill) yields in theMidwestern Great Lakes Region. Nine representative farm locations and six future climate scenarios were analyzed using the crop growth model SOYGRO. Under the future climate scenarios earlierplanting dates produced soybean yield increases of up to 120% above current levels in the central and northern areas of the study region. In the southern areas, comparatively small increases (0.1 to 20%) and small decreases (–0.1 to–25%) in yield are found. The decreases in yield occurred under the Hadley Center greenhouse gas run (HadCM2-GHG), representing a greater warming, and the doubled climate variability scenario – a more extreme and variableclimate. Optimum planting dates become later in the southern regions. CO₂fertilization effects (555 ppmv) are found to be significant for soybean, increasing yields around 20% under future climate scenarios.For the study region as a whole the climate changes modeled in this research would have an overall beneficial effect, with mean soybean yield increases of 40% over current levels.     

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.     

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     

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.     

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.     

Impacts of a Ghg-Induced Climate Change on Crop Yields: Effects of Acceleration in Maturation, Moisture Stress and Optimal Temperature

The present study involves using the Canadian Climate Centre (CCC) climate change scenario to evaluate the impacts of a CO₂-induced climate change on agriculture in Québec and vicinity. Climate change using the CCC General Circulation Model (GCM) data are fed into a crop model (FAO) so as to gauge the changes in agroclimatic factors such as growing season length and growing degree days, and subsequently potential yield changes for a variety of cereal (C₃ and C₄), leguminous, oleaginous, vegetable and special crops, for twelve major agricultural regions in southern Québec. Our results show that depending upon the agricultural zone and crop type, yields may increase (ex. corn and sorghum by 20%) or decrease (ex. wheat and soybean by 20 to 30%). Also, these crop yield changes appear to be related to acceleration in maturation rates, mainly to change in moisture stress and to shifts in optimal thermal growth conditions. These possible shifts in agricultural production potentials would solicit the formulation of appropriate adaptation strategies.     

Hydrological effects of the increased CO2 and climate change in the Upper Mississippi River Basin using a modified SWAT

Increased atmospheric CO₂ concentration and climate change may significantly impact the hydrological and meteorological processes of a watershed system. Quantifying and understanding hydrological responses to elevated ambient CO₂ and climate change is, therefore, critical for formulating adaptive strategies for an appropriate management of water resources. In this study, the Soil and Water Assessment Tool (SWAT) model was applied to assess the effects of increased CO₂ concentration and climate change in the Upper Mississippi River Basin (UMRB). The standard SWAT model was modified to represent more mechanistic vegetation type specific responses of stomatal conductance reduction and leaf area increase to elevated CO₂ based on physiological studies. For estimating the historical impacts of increased CO₂ in the recent past decades, the incremental (i.e., dynamic) rises of CO₂ concentration at a monthly time-scale were also introduced into the model. Our study results indicated that about 1–4% of the streamflow in the UMRB during 1986 through 2008 could be attributed to the elevated CO₂ concentration. In addition to evaluating a range of future climate sensitivity scenarios, the climate projections by four General Circulation Models (GCMs) under different greenhouse gas emission scenarios were used to predict the hydrological effects in the late twenty-first century (2071–2100). Our simulations demonstrated that the water yield would increase in spring and substantially decrease in summer, while soil moisture would rise in spring and decline in summer. Such an uneven distribution of water with higher variability compared to the baseline level (1961–1990) may cause an increased risk of both flooding and drought events in the basin.     

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.     

Impacts of extreme weather on wheat and maize in France: evaluating regional crop simulations against observed data

Extreme weather conditions can strongly affect agricultural production, with negative impacts that can at times be detected at regional scales. In France, crop yields were greatly influenced by drought and heat stress in 2003 and by extremely wet conditions in 2007. Reported regional maize and wheat yields where historically low in 2003; in 2007 wheat yields were lower and maize yields higher than long-term averages. An analysis with a spatial version (10?×?10?km) of the EPIC crop model was tested with regards to regional crop yield anomalies of wheat and maize resulting from extreme weather events in France in 2003 and 2007, by comparing simulated results against reported regional crops statistics, as well as using remotely sensed soil moisture data. Causal relations between soil moisture and crop yields were specifically analyzed. Remotely sensed (AMSR-E) JJA soil moisture correlated significantly with reported regional crop yield for 2002–2007. The spatial correlation between JJA soil moisture and wheat yield anomalies was positive in dry 2003 and negative in wet 2007. Biweekly soil moisture data correlated positively with wheat yield anomalies from the first half of June until the second half of July in 2003. In 2007, the relation was negative the first half of June until the second half of August. EPIC reproduced observed soil dynamics well, and it reproduced the negative wheat and maize yield anomalies of the 2003 heat wave and drought, as well as the positive maize yield anomalies in wet 2007. However, it did not reproduce the negative wheat yield anomalies due to excessive rains and wetness in 2007. Results indicated that EPIC, in line with other crop models widely used at regional level in climate change studies, is capable of capturing the negative impacts of droughts on crop yields, while it fails to reproduce negative impacts of heavy rain and excessively wet conditions on wheat yield, due to poor representations of critical factors affecting plant growth and management. Given that extreme weather events are expected to increase in frequency and perhaps severity in coming decades, improved model representation of crop damage due to extreme events is warranted in order to better quantify future climate change impacts and inform appropriate adaptation responses.