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.     

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.     

Agricultural Impact Assessment, Vulnerability, and the Scope for Adaptation

Climate change assessments which have considered climate impacts of a 2xCO₂ climate, using models of the global agricultural system, have found small impacts on overall production, but larger regional changes. Production shifts among regions can be considered one mechanism for adaptation. Adaptation at the farm level, through changes in crops, cultivars, and production practices, is another adaptation mechanism. Existing studies differ in how important these mechanisms will be. Studies that have considered yield effects at specific sites have found very wide ranges of impacts. A useful way to evaluate the impacts of climate change, given the uncertainty about future impacts, is to consider vulnerability. Studies have defined vulnerability in terms of yield, farm profitability, regional economy, and hunger. Vulnerability and climate impacts, particularly in terms of higher order effects on profitability and sustainability, will depend on how society and the economy develop. Lower income populations and marginal agricultural regions, particularly arid or flood prone areas, are most vulnerable to climate change.     

Climate change,weather variability and corn yield at a higher latitude locale: Southwestern Quebec

Climate change has led to increased temperatures, and simulation models suggest that this should affect crop production in important agricultural regions of the world. Nations at higher latitudes, such as Canada, will be most affected. We studied the relationship between climate variability (temperature and precipitation) and corn yield trends over a period of 33 years for the Monteregie region of south-western Quebec using historical yield and climate records and statistical models. Growing season mean temperature has increased in Monterregie, mainly due to increased September temperature. Precipitation did not show any clear trend over the 33 year period. Yield increased about 118 kg ha⁻¹ year⁻¹ from 1973 to 2005 (under normal weather conditions) due mainly to changes in technology (genetics and management). Two climate variables were strongly associated with corn yield variability: July temperature and May precipitation. These two variables explain more than a half of yield variability associated with climate. In conclusion, July temperatures below normal and May precipitation above normal have negative effects on corn yield, and the growing seasons have warmed, largely due to increases in the September temperature.     

对IPCC AR6报告中有关农业系统结论的解读

与IPCC第五次评估报告相比,第六次评估报告（AR6）有关农业的评估对象由作物生产系统延伸到粮食供应链系统,气候变化对作物生产不利影响的证据在加强。气候变化改变了作物适宜种植区,使中高纬度及温带地区作物种植界限向高纬度、高海拔地区推移。人为引起的气候变暖阻碍了作物产量的增长,地表O₃浓度增加使作物产量降低,CH₄排放加剧了这种不利影响。气候变化加剧作物病虫草害,极端气候事件高发加剧了粮食不安全,推升了国际粮食价格。适应措施有助于减缓气候变化不利影响,基于自然的适应方案在增强作物生产系统气候恢复力和保障粮食安全方面具有较高潜力。从保障国家粮食安全和重大战略需求出发,AR6报告对我国农业应对气候变化相关工作的启示如下：需要高度重视气候变化背景下作物种植适宜区转变与种植带北移的重要战略价值,合理规划农业生产布局;加强农业气象灾害和病虫害防治体系和能力建设,保障粮食生产稳定性;关注气候变化对国际作物生产和谷物贸易的影响,统筹国内、国际市场粮食资源,保障粮食安全;推进农业温室气体减排与作物生产高效协同,为实现国家减排目标做出贡献。     

气候变化对中国农业生产的影响研究进展

气候变化已成为当今科学界、各国政府和社会公众普遍关注的环境问题之一,气候变化可能对生态系统和社会经济产生灾难性影响,农业是受气候变化影响最直接的脆弱行业。因此,气候变化对农业生产的影响研究一直是气候变化研究领域中的热点问题之一。该文系统介绍了有关全球气候变化对中国农业生产影响研究的现状与进展,包括气候变化对农业影响的研究方法、大气中温室气体浓度增加对农作物的影响试验、气候变化对农业气候资源的影响、气候变化对农作物生长发育和产量的影响、气候变化对农业种植制度和品种布局的影响、气候变化对农作物气候生产潜力和气候资源利用率的影响等,指出当前在研究气候变化对农业影响评估中存在的问题,提出了今后应加强对气候变化情景和预测模式不确定性的研究、气候变化对农业影响的方法研究。此外,气候变化背景下极端天气气候事件对农业生产的影响以及气候变化对农业病虫害的影响研究等仍较薄弱,有待进一步加强和深入。     

Agricultural risk management policies under climate uncertainty

Climate change is forecasted to increase the variability of weather conditions and the frequency of extreme events. Due to potential adverse impacts on crop yields it will have implications for demand of agricultural risk management instruments and farmers’ adaptation strategies. Evidence on climate change impacts on crop yield variability and estimates of production risk from farm surveys in Australia, Canada and Spain, are used to analyse the policy choice between three different types of insurance (individual, area-yield and weather index) and ex post payments. The results are found to be subject to strong uncertainties and depend on the risk profile of different farmers and locations; the paper provides several insights on how to analyse these complexities. In general, area yield performs best more often across our countries and scenarios, in particular for the baseline and marginal climate change (without increases in extreme events). However, area yield can be very expensive if farmers have limited information on how climate change affects yields (misalignment in expectations), and particularly so under extreme climate change scenarios. In these more challenging cases, ex post payments perform well to increase low incomes when the risk is systemic like in Australia; Weather index performs well to reduce the welfare costs of risks when the correlation between yields and index is increased by the extreme events. The paper also analyses the robustness of different instruments in the face of limited knowledge of the probabilities of different climate change scenarios; highlighting that this added layer of uncertainty could be overcome to provide sound policy advice under uncertainties introduced by climate change. The role of providing information to farmers on impacts of climate change emerges as a crucial result of this paper as indicated by the significantly higher budgetary expenditures occurring across all instruments when farmers’ expectations are misaligned relative to actual impacts of climate change.     

Agricultural impacts of climate change in Spain: developing tools for a spatial analysis

CERES-Wheat, a dynamic process crop growth model, is specified and validated for seven sites in the major wheat-growing regions of Spain. Variables explaining a significant proportion of simulated yield variance are crop water (sum of precipitation and irrigation) and temperature during the growing season. A multiple linear regression model is developed to represent simulated yield response to these variables. Seven agro-climatic regions are defined based on K-mean cluster analysis of temperature and precipitation data from 329 meteorological stations and provincial crop yield data. The yield functions derived from the validated crop model were then used with the gridded agro-climatic database to conduct a spatial analysis of climate change impacts on national wheat production. Climate change scenarios with and without sulfate aerosols developed from the Hadley Centre (HCGG and HCGS) and Canadian Climate Centre (CCGG and CCGC) are tested.     

USE OF A STOCHASTIC WEATHER GENERATOR IN THE DEVELOPMENT OF CLIMATE CHANGE SCENARIOS

Climate change scenarios with a high spatial and temporal resolution are required in the evaluation of the effects of climate change on agricultural potential and agricultural risk. Such scenarios should reproduce changes in mean weather characteristics as well as incorporate the changes in climate variability indicated by the global climate model (GCM) used. Recent work on the sensitivity of crop models and climatic extremes has clearly demonstrated that changes in variability can have more profound effects on crop yield and on the probability of extreme weather events than simple changes in the mean values. The construction of climate change scenarios based on spatial regression downscaling and on the use of a local stochastic weather generator is described. Regression downscaling translated the coarse resolution GCM grid-box predictions of climate change to site-specific values. These values were then used to perturb the parameters of the stochastic weather generator in order to simulate site-specific daily weather data. This approach permits the incorporation of changes in the mean and variability of climate in a consistent and computationally inexpensive way. The stochastic weather generator used in this study, LARS-WG, has been validated across Europe and has been shown to perform well in the simulation of different weather statistics, including those climatic extremes relevant to agriculture. The importance of downscaling and the incorporation of climate variability are demonstrated at two European sites where climate change scenarios were constructed using the UK Met. Office high resolution GCM equilibrium and transient experiments.     

Weeds, Insects, and Diseases

The geographic distribution, vigor, virulence, and agricultural impact of weeds, insects, and plant pathogens will be affected by climatic changes accompanying the global "greenhouse effect." Weed/crop competitive interactions, particularly among species differing in photosynthetic pathway (C₃ v C₄), may be altered, with the C₃ species favored by increasing CO₂. Physiological and biochemical changes induced in host crop plants by rising CO₂ may affect feeding patterns of pest insects. Compilation of climatic thresholds for phenological development of pest insects reveals the potential for shifts in pest behavior induced by global warming and other climatic change. Generation times may be reduced, enabling more rapid population increases to occur. Poleward migration may be accelerated during the crop season. The epidemiology of plant diseases also will be altered. Prediction of disease outbreaks will be more difficult in periods of rapidly changing climate and unstable weather. Environmental instability and increased incidence of extreme weather may reduce the effectiveness of pesticides on targeted pests or result in more injury to non-target organisms. Biological control may be affected either negatively or positively. Overall, the challenge to agriculture from pests probably will increase.     

Modern climate-related changes in heat supply,moistening, and productivity of the agrosphere in Russia

Climate changes observed in recent decades are analyzed, and the respective climate-related tendencies of changes in heat supply, moistening, and productivity of the agrosphere that determine the natural resourse of potential Russia are determined. The grain crop yield trends are used additionally as climate change indicators. It is shown that climate changes observed in the last 30 years promote the increase in potential agriculture productivity in most of the Russian Federation, where not less than 85% of agricultural products are produced. At the same time, the increase in climate aridity is observed in several regions of Siberia and Chernozem Center, which results in a reduced productivity of agriculture.     

An Assessment of Integrated Climate Change Impacts on the Agricultural Economy of Egypt

This study used a quadratic programming sector model to assess the integrated impacts of climate change on the agricultural economy of Egypt. Results from a dynamic global food trade model were used to update the Egyptian sector model and included socio-economic trends and world market prices of agricultural goods. In addition, the impacts of climate change from three bio-physical sectors – water resources, crop yields, and land resources – were used as inputs to the economic model. The climate change scenarios generally had minor impacts on aggregated economic welfare (sum of Consumer and Producer Surplus or CPS), with the largest reduction of approximately 6 percent. In some climate change scenarios, CPS slightly improved or remained unchanged. These scenarios generally benefited consumers more than producers, as world market conditions reduced the revenue generating capacity of Egyptian agricultural exporters but decreased the costs of imports. Despite increased water availability and only moderate yield declines, several climate change scenarios showed producers being negatively affected by climate change. The analysis supported the hypothesis that smaller food importing countries are at a greater risk to climate change, and impacts could have as much to do with changes in world markets as with changes in local and regional biophysical systems and shifts in the national agricultural economy.     

The impacts of climate change on agricultural production systems in China

Climate change can bring positive and negative effects on Chinese agriculture, but negative impacts tend to dominate. The annual mean surface temperature has risen about 0.5–0.8 °C. The precipitation trends have not been identified during the past 100 years in China, although the frequency and intensity of extreme weather/climate events have increased, especially of drought. Water scarcity, more frequent and serious outbreaks of insects and diseases, and soil degradation caused by climate change have impacted agro-environmental conditions. However, temperature rise prolonged the crop growth seasons and cold damages have reduced in Northeast China. The projection of climate change indicates that the surface temperature will continue to increase with about 3.9 to 6.0 °C and precipitation is expected to increase by 9 to 11 % at the end of 21st century in China. Climate warming will provide more heat and as a consequence, the boundary of the triple-cropping system (TCS) will extend northwards by as much as 200 to 300 km, from the Yangtze River Valley to the Yellow River Basin, and the current double-cropping system (DCS) will move to the central part of China, into the current single cropping system (SCS) area which will decrease in SCS surface area of 23.1 % by 2050. Climate warming will also affect the optimum location for the cultivation of China’s main crop varieties. If no measures are taken to adapt to climate changes, compared with the potential yield in 1961–1990, yields of irrigated wheat, corn and rice are projected to decrease by 2.2–6.7 %, 0.4 %–11.9 % and 4.3–12.4 % respectively in the 2050s. Climate warming will enhance potential evaporation and reduce the availability of soil moisture, thus causing a greater need for agricultural irrigation, intensifying the conflict between water supply and demand, especially in arid and semi-arid areas of China. With adequate irrigation, the extent of the reduction in yield of China’s corn and wheat can be improved by 5 % to 15 %, and rice by 5 % or so than the potential yield in 1961–1990. Adaptive measures can reduce the agricultural loss under climate change. If effective measures are taken in a timely way, then climate change in the next 30–50 years will not have a significant influence on China’s food security.     

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.     

East African food security as influenced by future climate change and land use change at local to regional scales

Climate change impacts food production systems, particularly in locations with large, vulnerable populations. Elevated greenhouse gases (GHG), as well as land cover/land use change (LCLUC), can influence regional climate dynamics. Biophysical factors such as topography, soil type, and seasonal rainfall can strongly affect crop yields. We used a regional climate model derived from the Regional Atmospheric Modeling System (RAMS) to compare the effects of projected future GHG and future LCLUC on spatial variability of crop yields in East Africa. Crop yields were estimated with a process-based simulation model. The results suggest that: (1) GHG-influenced and LCLUC-influenced yield changes are highly heterogeneous across this region; (2) LCLUC effects are significant drivers of yield change; and (3) high spatial variability in yield is indicated for several key agricultural sub-regions of East Africa. Food production risk when considered at the household scale is largely dependent on the occurrence of extremes, so mean yield in some cases may be an incomplete predictor of risk. The broad range of projected crop yields reflects enormous variability in key parameters that underlie regional food security; hence, donor institutions’ strategies and investments might benefit from considering the spatial distribution around mean impacts for a given region. Ultimately, global assessments of food security risk would benefit from including regional and local assessments of climate impacts on food production. This may be less of a consideration in other regions. This study supports the concept that LCLUC is a first-order factor in assessing food production risk.     

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     

Potential effects of global climatic change on the phenology and yield of maize in venezuela

Simulated impacts of global and regional climate change, induced by an enhanced greenhouse effect and by Amazonian deforestation, on the phenology and yield of two grain corn cultivars in Venezuela (CENIAP PB-8 and OBREGON) are reported. Three sites were selected:Turén, Barinas andYaritagua, representing two important agricultural regions in the country. The CERES-Maize model, a mechanistic process-based model, in theDecision Support System for Agrotechnology Transfer (DSSAT) was used for the crop simulations. These simulations assume non-limiting nutrients, no pest damage and no damage from excess water; therefore, the results indicate only the difference between baseline and perturbed climatic conditions, when other conditions remain the same. Four greenhouse-induced global climate change scenarios, covering different sensitivity levels, and one deforestation-induced regional climate change scenario were used. The greenhouse scenarios assume increased air temperature, increased rainfall and decreased incoming solar radiation, as derived from atmospheric GCMs for doubled CO₂ conditions. The deforestation scenarios assume increased air temperature, increased incoming solar radiation and decreased rainfall, as predicted by coupled atmosphere-biosphere models for extensive deforestation of a portion of the Amazon basin. Two baseline climate years for each site were selected, one year with average precipitation and another with lower than average rainfall. Scenarios associated with the greenhouse effect cause a decrease in yield of both cultivars at all three sites, while the deforestation scenarios produce small changes. Sensitivity tests revealed the reasons for these responses. Increasing temperatures, especially daily maximum temperatures, reduce yield by reducing the duration of the phenological phases of both cultivars, as expected from CERES-Maize. The reduction of the duration of the kernel filling phase has the largest effect on yield. Increases of precipitation associated with greenhouse warming have no effects on yield, because these sites already have adequate precipitation; however, the crop model used here does not simulate potential negative effects of excess water, which could have important consequences in terms of soil erosion and nutrient leaching. Increases in solar radiation increased yields, according to the non-saturating light response of the photosynthesis rate of a C₄ plant like corn, compensating for reduced yields from increased temperatures in deforestation scenarios. In the greenhouse scenarios, reduced insolation (due to increased cloud cover) and increased temperatures combine to reduce yields; a combination of temperature increase with a reduction in solar radiation produces fewer and lighter kernels.A report of thePAN-EARTH Project, Venezuela Case Study.     

Assessing the impact of climate change on representative field crops in Israeli agriculture: a case study of wheat and cotton

Climate changes, associated with accumulation of greenhouse gases, are expected to have a profound influence on agricultural sustainability in Israel, a semi-arid area characterized by a cold wet winter and a dry warm summer. Accordingly this study explored economic aspects of agricultural production under projected climate-change scenarios by the “production function” approach, as applied to two representative crops: wheat, as the major crop grown in Israel’s dry southern region, and cotton, representing the more humid climate in the north. Adjusting outputs of the global climate model HadCM3 to the specific research locations, we generated projections for 2070–2100 temperatures and precipitations for two climate change scenarios. Results for wheat vary among climate scenarios; net revenues become negative under the severe scenario (change from −145 to −273%), but may increase under the moderate one (−43 to +35%), depending on nitrogen applied to the crop. Distribution of rain events was found to play a major role in determining yields. By contrast, under both scenarios cotton experiences a considerable decrease in yield with significant economic losses (−240 and −173% in A2 and B2 scenarios, respectively). Additional irrigation and nitrogen may reduce farming losses, unlike changes in seeding dates.     

Transient responses of North-American grasslands to changes in climate

Our objective was to evaluate the transient responses of grasslands in the central grassland region of North America to changes in climate. We used an individual plant-based gap dynamics simulation model (STEPPE-GP) linked with a soil water model (SOILWAT) to evaluate the effects of changes in climate on the composition and structure of grassland vegetation. Five functional types of plants were simulated based upon lifeform, physiology, and rooting distribution with depth. C₃ and C₄ perennial grasses with either a shallow or deep rooting distribution, and deeply rooted C₃ shrubs were simulated under current climatic conditions and under a GFDL climate change scenario for nine sites representative of the temperature and precipitation regimes in the grassland region.Although vegetation at the sites responded differently to climate change, shifts in functional types occurred within 40 years of the start of the climate change. C₄ grasses increased in dominance or importance at all sites with a change in climate, primarily as a result of increases in temperature in all months at all sites. The coolest sites that arc currently dominated by C₃ grasses were predicted to shift to a dominance by C₄ grasses, whereas sites that are currently dominated by C₄ grasses had an increase in importance of this functional type with a change in climate. Current annual temperature was the best predictor of changes in C₃ biomass, and C₃ and C₄ biomass combined; current annual precipitation was the best predictor of changes in C₄ biomass. These predicted shifts in dominance and importance of C₃ versus C₄ grasses would have important implications for the management of natural grasslands as well as the cultivation of crops in the central grassland region.     

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.