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Climate change is often cited in the 'collapse' of complex societies and linked to agricultural resilience or lack thereof. In this article, the authors consider how demand affected agricultural strategies as farmers navigated the transformations of the Late Harappan phase (c. 1900-1700 BC) of the Indus tradition. Through the modelling of monocropping/multicropping, low/high yield crops, and supply-driven versus flexible production, various economic, environmental and social demands are explored with reference to the choices of farmers and how these decisions differed regionally, and how they impacted the wider Late Harappan de-urbanisation process. The authors' archaeobotanical perspective on the Indus contributes to wider understanding of how urban societies and their agricultural bases change over time. Keywords: South Asia, Indus civilisation, climate change, archaeobotany, cities, agriculture, collapse, Introduction How cities and civilisations produce and sustain their food supplies is fundamental to their survival. Across both the Old and New Worlds, researchers have investigated the nature of past [...]

Food insecurity is a concern in Benin not only because of seasonal variations in food availability but also the limited access to food experienced by some households. This study analysed the effect of seasonality on household access to food in a rural area of Benin characterised by a unimodal climate. One hundred and seventy volunteer households were recruited in the study area and monitored during the increased, intermediate and decreased (or lean) food availability periods (FAPs) from September 2018 to July 2019. Socio-demographic data were collected during individual interviews with household heads and used to describe the sample. Data on households' access to food were collected on a bimonthly basis using a food consumption score (FCS) questionnaire. Food consumption scores were used to divide the households into three food consumption groups (FCGs): poor (FCS [less than or equal to] 21), borderline (21.5 [less than or equal to] FCS [less than or equal to] 35) and acceptable (FCS > 35). Generalized estimate equation (GEE) was used to compare FCGs among the repeated measures. The principal occupation of household heads was agriculture (72.9%) and the mean household size was 6.8[+ or -]3.6 persons. The FCS ranged from 59.7[+ or -]15.5 to 69.4[+ or -]15.9. The lowest FCS was recorded in September (intermediate FAP) whereas the highest was obtained in May (lean FAP). All the households (100%) had acceptable food consumption during the increased FAP (November to January). The proportion of households with acceptable food consumption was 91% in September and decreased from 99% in March to 90% in July, that is, during the lean FAP. On the other hand, the proportion of households with borderline and poor food consumption was 9% in September and increased from 1% in March to 10% in July. The proportions of FCGs obtained in November, January, March and May significantly differed from that of July (p Keys words: Households, access to food, food consumption score, longitudinal studies, unimodal climate, Benin Republic, INTRODUCTION Over the past five years, the hunger rate in the world has increased. It was estimated that there would be an annual increase of about 60 million food insecure [...]

Temperature data over the past five decades show faster warming of the global land surface during the night than during the day (1). This asymmetric warming is expected to affect [...]

Producers increasingly rely on irrigation to enhance yields and improve return on investment. The greater demand for ground water to support irrigation in the Mississippi River Alluvial Flood Plain has resulted in a decline in the aquifer, and a subsequent implementation of more stringent regulations for well permits. Given the concerns of ground water depletion, producers can clearly benefit from a tool that would indicate when they need to irrigate and how much. However, no easy to use irrigation scheduling tools have been developed and calibrated for the humid, high-rainfall environment of Mississippi. Researchers at USDA-ARS and Mississippi State University are developing a daily irrigation scheduling tool that calculates reference evapotranspiration (ET) from weather data to establish a crop water balance which will indicate when irrigation is needed. The weather parameters required for the calculation of ET include temperature, vapor pressure (determined from relative humidity and temperature), wind, and solar radiation. Rainfall and irrigation are also needed to track water balance in the field. Accurate determination of ET requires weather data that are consistent, accurate, and reliable. Errors in archived weather records are introduced from several sources, including sensor limitations and failures, instrument siting and deployment issues, lack of timely cleaning or re-calibration of instruments, data logger failures or programming errors, data transmission problems, and human errors. Further errors in the calculation of ET can result from mixing units in the calculations (e.g, degrees Fahrenheit and Centigrade), incorrectly converting units, or failing to adjust wind measurements to a common height. Since the archived data has not undergone any systematic assessment of data quality, potential users must conduct their own rigorous quality assurance before using the data to calculate ET. The research described here identifies common sources of errors in the available Mississippi weather station data, and develops statistical and range limit tests to identify erroneous records. Such quality assessment and control procedures are essential to ensure that values produced by the daily irrigation scheduling tool are reasonable and useful for decision support. The protocols described here will establish accurate data needed for calculation of reference crop ET for irrigation scheduling and crop management. Developing technologies to manage agricultural water resources of the humid Mid-South United States will provide means for agricultural producers to increase water use efficiency and mitigate ground water depletion., INTRODUCTION There is a growing and substantial need for water management technologies for crop production in humid areas. Historically, humid regions have had plentiful ground water resources and rainfall with [...]

Numerous models and indices exist that attempt to characterize the effect of environmental factors on the comfort of animals and humans. Heat and cold indices have been utilized to adjust ambient temperature (Ta) for the effects of relative humidity (RH) or wind speed (WS) or both for the purposes of obtaining a 'feels-like' or apparent temperature. However, no model has been found that incorporates adjustments for RH, WS, and radiation (RAD) over conditions that encompass hot and cold environmental conditions. The objective of this study was to develop a comprehensive climate index (CCI) that has application under a wide range of environmental conditions and provides an adjustment to Ta for RH, WS, and RAD. Environmental data were compiled from 9 separate summer periods in which heat stress events occurred and from 6 different winter periods to develop and validate the CCI. The RH adjustment is derived from an exponential relationship between Ta and RH with temperature being adjusted up or down from an RH value of 30%. At 45[degrees]C, the temperature adjustment for increasing RH from 30 to 100% equals approximately 16[degrees]C, whereas at -30[degrees]C temperature adjustments due to increasing RH from 30 to 100% equal approximately -3.0[degrees]C, with greater RH values contributing to a reduced apparent temperature under cold conditions. The relationship between WS and temperature adjustments was also determined to be exponential with a logarithmic adjustment to define appropriate declines in apparent temperature as WS increases. With this index, slower WS results in the greatest change in apparent temperature per unit of WS regardless of whether hot or cold conditions exist. As WS increases, the change in apparent temperature per unit of WS becomes less. Based on existing wind-chill and heat indices, the effect of WS on apparent temperature is sufficiently similar to allow one equation to be utilized under hot and cold conditions. The RAD component was separated into direct solar radiation and ground surface radiation. Both of these were found to have a linear relationship with Ta. This index will be useful for further development of biological response functions, which are associated with energy exchange, and improving decision-making processes, which are weather-dependent. In addition, the defined thresholds can serve as management and environmental mitigation guidelines to protect and ensure animal comfort. Key words: bioclimatic index, cold stress, domestic livestock, environmental factor, environmental model, heat stress doi: 10.2527/jas.2009-2586

A set of agroclimatic indices representing Canadian climatic conditions for field crop production are analyzed for long-term trends during 1895-2007. The indices are categorized for three crop types: cool season, warm season, and overwintering. Results indicate a significant lengthening of the growing season due to a significantly earlier start and a significantly later end of the growing season. Significant positive trends are also observed for effective growing degree-days and crop heat units at most locations across the country. The occurrence of extremely low temperatures has become less frequent during the nongrowing season, implying a more favorable climate for overwinter survival. In addition, the total numbers of cool days, frost days, and killing-frost days within a growing season have a decreasing trend. This means that crops may also be less vulnerable to cold stress and injury during the growing season. Extreme daily precipitation amounts and 10-day precipitation totals during the growing season have been increasing. Significant trends associated with increased availability of water during the growing season are identified by the standardized precipitation index and seasonal water deficits. The benefit of the increased precipitation may have been offset by an upward trend in evaporative demand; however, this would depend on the amount of growth and productivity resulting from increased actual evapotranspiration. DOI: 10.1175/2009JAMC2275.1

Byline: Enli Wang (1), Peter McIntosh (2), Qiang Jiang (1), Johnny Xu (1) Abstract: A well tested agricultural systems model was used together with 114 years of historical climate data to study the performance of a dryland wheat--fallow system as impacted by climate variations and nitrogen input levels in southeast Australia, and to investigate the value of: (1) historical climate knowledge, (2) a perfect climate forecast, and (3) various forecasts of targeted variables. The potential value of historical climate records increases exponentially with the number of years of data. In order to confidently quantify the long term optimal nitrogen application rate at the study site at least 30 years of climate data are required. For nitrogen management only, the potential value of a perfect climate forecast is about $54/ha/year with a reduction of excess nitrogen application of 20 kg N/ha/year. The value of an ENSO based forecast system is $2/ha/year. Perfect forecasting of three or six categories of growing season rainfall would have a value of $10--12/ha/year. Perfect forecasts of three or six categories of simulated crop yield would bring about $33--34/ha/year. Choosing integrated variables as a forecasting target, for example crop yield derived from agricultural modelling, has the potential to significantly increase the value of forecasts. Author Affiliation: (1) CSIRO Land and Water, GPO Box 1666, Canberra, ACT, 2601, Australia (2) CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, TAS, 7001, Australia Article History: Registration Date: 07/04/2009 Received Date: 19/04/2007 Accepted Date: 16/12/2008 Online Date: 16/05/2009

Among other foci, recent research on adaptation to climatic variability and change has sought to evaluate the merit of adaptation generally, as well as the suitability of particular adaptations. Additionally, there is a need to better understand the likely uptake of adaptations. For example, diversification is one adaptation that has been identified as a potential farm-level response to climatic variability and change, but its adoption by farmers for this reason is not well understood. This paper serves two purposes. The first is to document the adoption of crop diversification in Canadian prairie agriculture for the period 1994-2002, reflect upon its strengths and limitations for managing a variety of risks, including climatic ones, and gauge its likely adoption by producers in response to anticipated climate change. The second purpose is to draw on this case to refine our current understanding of climate change adaptation more generally. Based upon data from over 15 000 operations, it was determined that individual farms have become more specialized in their cropping patterns since 1994, and this trend is unlikely to change in the immediate future, notwithstanding anticipated climate change and the known risk-reducing benefits of crop diversification. More broadly, the analysis suggests that 'suitable' and even 'possible' climate change adaptations need to be more rigorously assessed in order to understand their wider strengths and limitations.

Understanding climate effects on crop yield has been a continuous endeavor aiming at improving farming technology and management strategy, minimizing negative climate effects, and maximizing positive climate effects on yield. Many studies have examined climate effects on corn yield in different regions of the United States. However, most of those studies used yield and climate records that were shorter than 10 years and were for different years and localities. Although results of those studies showed various influences of climate on corn yield, they could be time specific and have been difficult to use for deriving a comprehensive understanding of climate effects on corn yield. In this study, climate effects on corn yield in central Missouri are examined using unique long-term (1895-1998) datasets of both corn yield and climate. Major results show that the climate effects on corn yield can only be explained by within-season variations in rainfall and temperature and cannot be distinguished by average growing-season conditions. Moreover, the growing-season distributions of rainfall and temperature for high-yield years are characterized by less rainfall and warmer temperature in the planting period, a rapid increase in rainfall, and more rainfall and warmer temperatures during germination and emergence. More rainfall and cooler-than-average temperatures are key features in the anthesis and kernel-filling periods from June through August, followed by less rainfall and warmer temperatures during the September and early October ripening time. Opposite variations in rainfall and temperature in the growing season correspond to low yield. Potential applications of these results in understanding how climate change may affect corn yield in the region also are discussed.

A remote sensing package called the agricultural irrigation imaging system (AgIIS) aboard a linear move irrigation system was developed to simultaneously monitor water status, nitrogen status, and canopy density at one-meter spatial resolution. The present study investigated the relationship between water status detected by AgIIS and soil moisture for the 1999 cotton (Gossypium hirsutum, Delta Pine 90b) season in Maricopa, Ariz. Water status was quantified by the water deficit index (WDI), an expansion of the crop water stress index where the influence of soil temperature is accounted for through a linear mixing model of soil and vegetation temperature. The WDI was best correlated to soil moisture through the FAO 56 water stress coefficient [K.sub.s] model; stability correction of aerodynamic resistance did not improve correlation. The AgIIS did provide field images of the WDI that might aid irrigation scheduling and increase water use efficiency. CE Database keywords: Remote sensing; Sprinkler irrigation; Stress.

The present study investigated the relationship between the crop water stress index (CWSI) and soil moisture for surface irrigated cotton (Gossypium hirsutum, Delta Pine 90b) at Maricopa, Arizona during the 1998 season. The CWSI was linked to soil moisture through the water stress coefficient [K.sub.s] that accounts for reduced crop evapotranspiration when there is a shortage of soil water. A stress recovery coefficient [K.sub.rec] was introduced to account for reduced crop evapotranspiration as the crop recovered from water stress after irrigation events. A soil water stress index (SWSI) was derived in terms of [K.sub.s] and [K.sub.rec]. The SWSI compared reasonably well to the CWSI, but atmospheric stability correction for the CWSI did not improve comparisons. When the CWSI was substituted into the SWSI formulation, it gave good prediction of soil moisture depletion (fDEP; when to irrigate) and depth of root zone depletion ([D.sub.r]; how much to irrigate). Disagreement was greatest for fDEP CE Database keywords: Soil moisture; Surface irrigation.

The major objective of this study was to investigate the effects of climate change on evapotranspiration from paddy fields. A sensitivity analysis of meteorological variables at the Kao-Hsiung station, one of meteorological stations in southern Taiwan, was carried out using the modified Penman formula. Forty-eight-year records of temperature, relative humidity, sunshine duration, wind speed, and precipitation depth comprised the database. Trend and persistence analyses of the data were performed using the Mann--Kendall test, the Cumulative Deviation test, Linear Regression, and the Autocorrelation Coefficient. The results indicated that only temperature and relative humidity have significant long-term trends and persistence. Two climatic scenarios, viz. (1) linear extrapolation of climatic trends and (2) the predictions of General Circulation Models (GCMs), were assumed to investigate the effects of climate change on evapotranspiration. The study revealed that evapotranspiration from paddy fields increased under both climatic scenarios studied.

There is interest in growing pigeonpea [Cajanus cajan (L.) Millsp.], a tropical grain legume crop, in temperate regions. A few extra-short-duration lines were developed in Minnesota (~45° N), USA, to improve the crop's adaptation to temperate regions. We investigated whether photoperiod responses of the Minnesota lines (MN #) differed with lines (ICPL #) bred in the tropics. Five ICPL lines and three MN lines were grown under artificially extended daylength (ED) simulating 45° N and normal daylength (ND) at Patancheru, India, (17° N) during the 1995 and 1996 rainy seasons. Six ICPL and two MN lines were also tested at Suwon (37° N), Korea, in 1998. At Patancheru, the line x photoperiod interactions were highly significant for grain yield, total dry matter (TDM), harvest index (HI), days to flowering (DF), and maturity (DM). Under ND, yield was significantly more for ICPL lines and correlated with TDM (r = 0.892 and 0.902, n = 8), DF, and DM, but not with HI. Under ED, yield was more for MN lines and correlated positively with HI and negatively with DF and DM (in 1996), but not with TDM. The additive main effects and multiplicative interaction (AMMI) analysis suggested a distinct interaction pattern for MN lines. Yield was correlated negatively with DF and DM in Korea also where a MN line gave the highest yield. The results suggest that there has been a selection for a high HI potential and early flowering in MN lines for better adaptation to longer days and a high TDM production potential in ICPL lines to shorter days., PIGEONPEA is a tropical grain legume crop that is well adapted to subsistence agriculture in the tropical and subtropical regions. However, in recent years there has been interest in developing [...]

An analysis of long-term records of corn yields and seasonal weather conditions in Illinois found major temporal shifts and important spatial variations in the types of seasonal weather conditions, expressed as the normality of temperature and rainfall conditions, that create positive and negative impacts on yields. Nineteen different types of corn-weather seasons (May-August) occurred during 1901-1997, and 9 of these seasons accounted for most of the high corn yields (top 20 of the 97) and 8 seasonal types produced most low yields (lowest 20 values). Assessment of the years with either high or low yields revealed (1) some corn-weather seasonal types were uniformly distributed throughout the century; (2) others were unevenly time distributed, some occurring only in early decades and others only in the last few decades; and (3) certain weather types varied regionally. The yield responses to certain seasonal types varied over time, being good early and not so later, or vice versa. The findings indicate that time changes in farming practices, corn varieties, and agricultural technology have altered how certain types of growing season weather affect corn yields. Regional differences in yield outcomes from a given set of weather conditions reflect varying soil and climate differences across Illinois. The spatial and temporal differences reveal the importance of using weather-impact results to define seasonal weather extremes. The kinds of seasons creating high yields predominated during 1901-1910 and 1961-1997, and most seasons creating low yields were concentrated between 1911 and 1960. Comparison of the 1901-1997 temporal distributions of yield extremes (high and low) with the temporal distributions of cyclone passages and the incidence of ENSO conditions that affect growing season weather conditions revealed a generally good relationship. The shifting temporal responses to various kinds of seasonal weather conditions during the 20th century reveal some of the difficulties facing efforts to project realistic and detailed impacts in agriculture from altered future seasonal weather conditions.

This paper presents the method to develop response surface diagrams (RSD) suitable to evaluate the impacts of climate change on potential crop production and crop area. The diagrams depict the response of different agricultural crops to average long-term changes in ambient temperature and precipitation on a country basis. They take into account the spatial and seasonal variability of climate, and differences in the climate response of important crops. RSDs for Germany and the Democratic Republic of Congo illustrate that countries and crop types differ greatly in their sensitivity to unit changes in long-term average climate. In comparing the area-weighted RSDs for Germany and Democratic Republic of Congo, it was found that the potential production in Germany of a weighted aggregation of crops is mainly sensitive to changes in temperature, whereas the potential crop production in the Democratic Republic of Congo mainly responds to changes in precipitation (over the specified ranges of climate variables). The RSDs can provide a visual overview of these varying sensitivities, and are a convenient and simple-to-understand method to summarize crop responses to climate change in a particular country.

Scientific knowledge concerning the effects of climate change on agriculture is discussed. Topics include difficulties in determining the effects of climate change on agricultural production, communication of predictive content, adaptation to climate change, and estimated effects on global food production.

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.

A review is given of the state of knowledge in the field of assessing climate change impacts on agricultural crops and livestock. Starting from the basic processes controlling plant growth and development, the possible impacts and interactions of climatic and other biophysical variables in different agro-environments are highlighted. Qualitative and quantitative estimations of shifts in biomass production and water relations, inter-plant competition and crop species adaptability are discussed. Special attention is given to the problems encountered when scaling up physiological responses at the leaf- and plant level to yield estimates at regional to global levels by using crop simulation models in combination with geo-referenced, agro-ecological databases. Some non-linear crop responses to environmental changes and their relations to adaptability and vulnerability of agro-ecosystems are discussed.

A study has been conducted on the effect of temperature changes on the structure of methanogenic archaeal community. To accurately determine temperature change effects, DNA was extracted from soil slurries that were incubated at 30 deg and 15 deg Celcius. Researchers discovered that archaeal community structure changed when the temperature shifted from 30 deg to 15 deg Celcius. This resulted in the decrease of CH4 production rate, steady state H2 partial pressure and a transient accumulation of acetate.

Lodging due to severe weather conditions is observed in crops each year. A 2-yr study was conducted to determine the effectiveness of anther-derived dihaploids for improving lodging resistance, and to examine certain morphological traits which may contribute to lodging in Maryland tobacco (Nicotiana tabacum L). Forty-five and 35 dihaploid lines were derived from F, plants of `MD 201' x `Catterton' (Population 1) and MD 201 x `NC 13' (Population 2) crosses, respectively, using standard anther and midvein culture techniques. Mature plants were subjected to artificially produced wind, and evaluated by a severity rating based on the degree of lean from the vertical position. Significant variation among the dihaploid lines was observed for severity rating over the 2 yr. Heritability values for Populations 1 and 2 were 0.61 and 0.64, respectively. Based on severity ratings from the first year field study, five good and five poor dihaploid lines in Population 2 were evaluated in a 2-yr greenhouse study for top and root fresh weights and top/root ratio (TRR). Significant variation was observed among the 10 dihaploid lines for TRR only; however, the five lines selected for good lodging performance had larger root weights and smaller TRR than the five lines selected for poor lodging performance. Results obtained from these field and greenhouse studies suggest that the development of dihaploid lines with low severity ratings, larger roots, and smaller TRR is possible, and should provide superior genetic material with a good level of lodging resistance., LODGING IS A SERIOUS PRODUCTION PROBLEM and a major constraint to yield improvement for many crops, including wheat (Triticum aestivum L.), barley (Hordeum vulgate L.), oat (Avena sativa L.) (28), [...]

The present study involves using the Canadian Climate Centre (CCC) climate change scenario to evaluate the impacts of a C[O.sub.2]-induced climate change on agriculture in Quebec 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 ([C.sub.3] and [C.sub.4]), leguminous, oleaginous, vegetable and special crops, for twelve major agricultural regions in southern Quebec. 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.

Influence of the group 1 chromosomes of wheat on ear-emergence times and their involvement with vernalization and day length are discussed based on a study using aneuploid wheat lines in Chinese Spring in which each homeologous group 1 chromosome delayed ear emergence. The genes interacted with each other, with vernalization, and with day length.

Artificial Neural Networks (ANN's) are used to model the interactions that occur between ozone pollution, climatic conditions, and the sensitivity of crops and other plants to ozone. A number of generic methods for analysis and modeling are presented. These methods are applicable to the modeling and analysis of any data where an effect (in this case damage to plants) is caused by a number of variables that have a nonlinear influence. Multilayer perceptron ANN's are used to model data from a number of sources and analysis of the trained optimized models determines the accuracy of the model's predictions. The models are sufficiently general and accurate to be employed as decision support systems by United Nations Economic Commission for Europe (UNECE) in determining the critical acceptable levels of ozone in Europe. Comparison is made of the accuracy of predictions for a number of modeling approaches. It is shown that the ANN approach is more accurate than other methods and that the use of principal components analysis on the inputs can improve the model. The validation of the models relies on more than simply an error measure on the test data. The relative importance of the causal agents in the model is established in the first instance by summing absolute weight values. This indicates whether the model is consistent with domain knowledge. The application of a range of conditions to the model then allows predictions to be made about the nonlinear influences of the individual principal inputs and of combinations of two inputs viewed as a three-dimensional graph. Equations are synthesized from the ANN to represent the model in an explicit mathematical form. Models are formed with essential parameters and other inputs are added as necessary, in order of decreasing priority, until an acceptable error level is reached. Secondary indicators substituting for primary indicators with which they are strongly correlated can be removed. From the synthesized equations both known and novel aspects of the process modeled can be identified. Known effects validate the model. Novel effects form the basis of hypotheses which can then be tested. Index Terms - Climate, crop damage, environmental data, equation synthesis, modeling, ozone, pollution, prediction, statistics.

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.

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

The space-time distribution of the crop hail loss-to-risk ratio over the whole Bulgarian territory has been ascertained using the rank approach. The relationships between hailfall characteristics (sizes and kinetic energy) and the percentage of the crop damage for wheat, corn, and vines were obtained using field observations and hailpad data. A physical-statistical method for evaluating the changes in damaged crop areas was tested over a 5000-[km.sup.2] target area (numbers for three hall suppression ranges). Using a regression equation (worked out for 120 nonseeded days) for evaluation of the damaged area changes, reductions in damaged area of 34%-48% were obtained for 7 and 9 years of heavy hail. The magnitude of the reduction is comparable with the one obtained using double-mass ratio and bivariate test of loss-to-risk data in the control and target areas. Similar results were obtained in other hail suppression projects in France, North Dakota, and Greece. A short overview of the physical effects of cloud seeding is presented. The physical-statistical approach for severe hailstorms, based on the regression between thermodynamical indices of instability and damaged areas, shows promise as a perspective to evaluate the efficiency of the seeding operations in problematic cases.

Between 1986 and 1992 a research project was developed and carried out on hail climatology and the economic repercussions of hail on agriculture in Leon (northwestern Spain). A target area with an extent of 6825 [km.sup.2] was defined, within which a network of meteorological observers was established at an average density of 1 per 17 [km.sup.2]. A network of 250 hailpads installed in a grid formation was also laid out over an area of 1000 [km.sup.2] inside the target area. The frequent occurrence of hailfalls - 122 hail days over seven consecutive summers - provided a detailed database and allowed several climatological studies to be made. Crop damage was also closely monitored and quantified. Barley and wheat were selected as crops on which to base an analysis of the relationship between hailfall characteristics and crop damage. As the resistance of plants to hailstones is held to vary according to their physiological state, four different stages of plant growth were defined, beginning with the formation of grain heads. An important conclusion was drawn: the dispersion of percentages of damage always covers the possible variations in resistance caused by the physiological state of the plants. As a result, using only minimal information about hailfall characteristics - namely, the initial reports of observers regarding hailstone size - a working statistical model has successfully been constructed to predict losses to barley and wheat, using data provided by the Leon hail project.

Future climate changes, as well as differences in climates from one location to another, may involve changes in climatic variability as well as changes in means. In this study, a synthetic weather generator is used to systematically change the within-year variability of temperature and precipitation (and therefore also the interannual variability), without altering long-term mean values. For precipitation, both the magnitude and the qualitative nature of the variability are manipulated. The synthetic daily weather series serve as input to four crop simulation models. Crop growth is simulated for two locations and three soil types. Results indicate that average predicted yield decreases with increasing temperature variability where growing-season temperatures are below the optimum specified in the crop model for photosynethsis or biomass accumulation. However, increasing within-year variability of temperature has little impact on year-to-year variability of yield. The influence of changed precipitation variability on yield was mediated by the nature of the soil. The response on a droughtier soil was greatest when precipitation amounts were altered while keeping occurrence patterns unchanged. When increasing variability of precipitation was achieved through fewer but larger rain events, average yield on a soil with a large plant-available water capacity was more affected. This second difference is attributed to the manner in which plant water uptake is simulated. Failure to account for within-season changes in temperature and precipitation variability may cause serious errors in predicting crop-yield responses to future climate change when air temperatures deviate from crop optima and when soil water is likely to be depleted at depth.

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

Climatic variations such as changes in precipitation levels and atmospheric temperature influence agriculture. High temperature variability affects photosynthesis and dormancy in perennial plants while precipitation variability impacts soil water retention and infiltration. The influence of climatic variability on crop yields and development can be simulated through General Circulation Models.

Drought is a major constraint limiting rainfed crop production in semiarid regions. Selection criteria for increasing transpiration efficiency (TE) may be useful for enhancing drought adaptation. Carbon isotope discrimination (A) has been negatively correlated with TE in cowpea [Vigna unguiculata (L.) Walp.] and several other [C.sub.3] species. However, the realized heritability of [Delta] is not known and A has shown negative associations with days to flowering, which could limit its usefulness as a selection criterion for enhancing drought adaptation. Field studies were undertaken to estimate the heritability of [Delta], estimate the genetic correlation between [Delta] and earliness, and determine the response to selection for high and low [Delta] and for earliness and lateness in two cowpea populations. Broad-sense heritabilities were low to intermediate (0.27 and 0.58) for [Delta] and high (0.72 and 0.80) for days to first flower (DFF). Selections were made among individual [F.sub.2] plants, and selected progenies were evaluated as [F.sub.3] and [F.sub.4] families. Realized heritabilities were low for [Delta] (0.25-0.31) but significant and high for DFF (0.89-0.96). Selecting individual [F.sub.2] plants for high and low [Delta] was effective in identifying [F.sub.3] and [F.sub.4] families with high and low [Delta] only in one of the crosses. Genetic correlations between A and earliness were negative and low to intermediate in magnitude (-0.14 to -0.66). Selection for earliness can be effective in the [F.sub.2] generation, but it may result in some indirect selection for high [Delta] and, therefore, low TE. Selection for low [Delta] may be most efficient with advanced families.

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 CO(sub 2). The impact of crop management (sowing date, irrigation anti 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 CO(sub 2) and climate change, and that sowing at both current and scenarios climate should occur as early as possible.

The accuracy of impact estimates relating climate Change to regional-scale agricultural production is constrained by the temporal and spatial resolution of climate change projections. Several techniques have been used to compensate for these limitations in order to provide reasonable estimates of the impact of climate change on crop yield. One approach assumes that variability over time can substitute for spatial variability, thereby reducing the need to estimate the impacts at a spatially dense network of stations - an assumption that has not been generally tested. This study evaluates this assumption using methods similar to those employed in the climate impact literature. The findings suggest that current practices are generally defensible if the goal is to provide a range of possible crop responses to climate change. However, the results also show that the assumption is highly sensitive to specific interactions at the soil-plant-atmosphere interface and, consequently, does not hold under certain circumstances. Key Words: climate change, agricultural impacts, scale, temporal variability, spatial variability.

Common bean (Phaseolus vulgaris L.) is grown in regions where high temperatures during reproductive development reduce yields. The purpose of this study was to identify sensitive growth stages during reproductive development and to investigate the genetics of heat tolerance during these stages. Exposure to hig temperatures during two reproductive growth stages, namely flower bud formation and pod filling, resulted in particularly severe damage. This damage was evaluated by scoring two corresponding traits - flower bud abortion and reduced pod fill. For each trait, two tolerant and two susceptible large-seeded dry bea genotypes were chosen and crossed in all combinations, including reciprocals. The parents and control cultivars were evaluated under heat stress conditions a two locations in the Central Valley of California; this allowed us to determine that genotype X environment interactions were present for both traits. Genetic studies included parents, [F.sub.1] and [F.sub.2] progenies, and control cultivars at one of the above locations. Both traits displayed continuous variation, indicating quantitative inheritance. Generation means analyses demonstrated that additive genetic effects were significant for both heat tolerance traits, but were more important for tolerance to bud abortion. Significant dominance effects for tolerance to bud abortion were attributed to either linkage or pleiotropy of the single dominant gene conferring indeterminate growth habit. Both generation means and diallel analyses demonstrated the presence of cytoplasmic effects including interactions of cytoplasmic with nuclear genes. The significant additive effects observed indicate that gain from selection for improved heat tolerance should be possibl for both traits.

Esophageal contents of 842 common grackles (Quiscalus quiscula), collected in north-central North Dakota from 1 May-21 October 1989, were examined. The esophageal contents varied significantly between habitats and seasons (P is less than or equal to 0.05) but did not differ among age-sex classes (P > 0.05). Insects comprised 79% (mean dry weight) of the diet during May and June. From July to mid-August, common grackles ate primarily small grains (42%) and insects (34%); whereas, between mid-August and late October small grains (36%) and sunflower seeds (48%) were important diet items. Overall, crop phenology and habitat influenced the diets of common grackles.

Countries in the temperate zone will benefit from future climate changes, while countries in tropical and subtropical zones will be susceptible to famine and food shortage. The international trade system must make adjustments for changes in the world food system. The possibility of increased global cereal production depends on costly changes in current agricultural systems.

The temperate maize (Zea mays L.) race Cateto may have potential for improving grain quality in temperate breeding programs. Temperate germplasm may also be useful in tropical breeding programs for improving yield, agronomic traits, and grain quality. The objective of our study was to assess the yield potential of Cateto race accessions testcrossed with two Corn Belt inbreds for grain yield and other agronomic traits in both temperate and tropical environments. Exotic inbreds representing Cateto, intermediate, and non-Cateto races were crossed to two U.S. Corn Belt inbreds (Mo17 and B73). Testcrosses (F(sub 1)s), their F(sub 2) and backcross generations, and four checks were evaluated in 1989 through 1991 at three temperate (two in Iowa and one in Missouri) and two tropical (Florida and Zimbabwe) locations. Data were recorded for grain yield, harvest moisture content, days to tassel, ear height, stalk lodging, and root lodging. The testcross-by-generation interaction was significant for all traits, except grain yield, whereas the testcross-by-tester interaction was significant for ear height, stalk lodging, and root lodging. B73 contributed more favorable alleles for improved standability and grain yield than did Mo17. Although the testcross by location interaction was significant for all traits, the tropical and temperate environments ranked testcrosses similarly. The tropical locations had both the highest and the lowest mean grain yields. The best testcrosses identified in temperate locations may have potential for introgression in the tropics.

Cultivar seed size and yield potential of common bean (Phaseolus vulgaris L.) are negatively associated. Large-seeded cultivars are predominately of Andean background, while small-seeded cultivars are predominately of Mesoamerican background. Crop growth analyses were conducted to examine the association of cultivar seed size with crop growth rate (CGR), seed growth rate (SGR) on a land-area basis, intensity of partitioning to seed (land-area SGR divided by CGR), and effective seed-filling period. Sixteen cultivars, ranging in seed size from 190 to 540 mg seed to the -1, were grown at two sites in Colombia at elevations of 1000 m (warm) and 1800 m (cool). The seed size groups did not differ in CGR at either site. At the warmer site, the small-seeded Mesoamerican lines had greater mean partitioning to seed (1.29 vs. 0.97 for the Mesoamerican and Andean lines, respectively), greater land-area SGR (11.7 vs. 8.3 g m to the -2 d to the -1), and higher yield (2030 vs. 1750 kg ha to the -1) than did the large-seeded Andean lines. At the cool site, the seed size groups did not differ in any of these variables. At both sites, the Mesoamerican lines flowered approximately equal to 6 d later and acquired more total N than did the Andean lines. It is postulated that the greater land-area SGR and yield of the Mesoamerican lines at the warmer site was due to their greater accumulation of N, which allowed them to sustain greater rates of canopy photosynthesis during seed-filling.

Little is known about environmental and physiological factors affecting centipedegrass (Eremochloa ophiruoides (Munro) Hackel) winter survival. Stolons of common and 'Oklawn' centipedegrass were sampled from field- or growth chamber-grown turf in three separate experiments to (i) determine freezing tolerance of acclimated and nonacclimated turf; (ii) identify and quantify nonstructural carbohydrates (NSC) in acclimated and nonacclimated turf, and (iii) relate NSC levels to freezing tolerance. Lethal temperatures for common and Oklawn were similar throughout all studies. Freezing tolerance estimated by electrolyte leakage for turf sampled from the field in winter 1988-1989, indicated that lethal temperatures ranged from about -7 to -8 degrees C in February and March, to -9 degrees C in December and January. In a 1990-1991 field and growth chamber studies, injury was estimated by stolon recovery growth in the greenhouse after freezing at -2, -4, -6, -8, and -10 degrees C for 1 h. Lethal temperatures in mid-winter were approximately equal to 2 degrees C lower than in fall or spring during active growth. In stolons, starch and sucrose were the primary NSC ranging from approximately equal to 2 to 13 mg (100 mg) to the -1 dry weight. Sucrose was higher in acclimated than pre- or post-acclimated turf. In a growth chamber study, 47% more sucrose was present in acclimated vs. preacclimated turf. Sixty-nine percent more acclimated stolons survived -4 degrees C than preacclimated stolons, and a positive correlation (r = 0.78) was observed between sucrose level and number of surviving stolons. Higher sucrose concentrations in low-temperature-acclimated vs. nonacclimated common centipedegrass stolons may be a component of improved freezing tolerance.

Twenty-two cultivars of rice (Oryza sativa L.) from diverse origins were grown under greenhouse conditions and exposed to ultraviolet-B radiation (UV-B; 280-320 nm) simulating a 5% reduction in stratospheric ozone in spring for the Philippines (14 degrees N lat.) to evaluate growth and morphological responses to UV-B. In comparison to controls that received no UV-B, plants exposed to UV-B exhibited significantly reduced dry matter production (total plant and shoot), shoot height, leaf blade length and total leaf area, increased number of tillers, and greater weight fractions in leaf blades and roots. For most cultivars, the relative effects of UV-B on shot morphology were greater than the effects on biomass production. The direction of the UV-B effects were generally similar for all cultivars, however, there were significant differences among cultivars in the magnitude of the UV-B-induced changes. Upland cultivars (IRAT104 and OS4) and two low-land cultivars commonly planted in the USA (Star Bonnet and Lemont) were found to be least affected by the UV-B, whereas modern, high yielding, lowland cultivars developed in the Philippines (IR52, IR35546-17-33, and IR58) were found to be among the most sensitive to UV-B. Our results indicate that in rice, as in other grasses, shoot morphology may be more responsive to solar UV-B change than plant productivity. Intraspecific variation in morphological responses to UV-B could contribute to differences among cultivars in susceptibility to UV-B induced changes in competitive balance between rice and associated weeds of the rice agroecosystem.