Effects of Climate Change and Variability on Agricultural Production Systems

During the past 30 or so years there has been an ongoing debate about whether global climate change is occurring, what effects there might be, and what, if anything, should be done to mitigate the causes or adapt to the changes. Although a few skeptics (e.g., Singer, 2001; Michaels and Balling, 2000) remain, there is a remarkable scientific consensus that global climate change is occurring. This consensus is illustrated by articles published recently in many highly respected journals, e.g., recently published articles in Nature (Schneider, 2001) and in Science (Kennedy, 2001). The following quotation is from an editorial published in Science (Seventeen National Academies, 2001).

Assessment of the impact of climate change on food production systems and the policies needed to adjust to these changes, begins with the biophysical evaluation of crop production as influenced by soil properties, weather variability with climate change superimposed upon it, and potential changes in agrotechnology. The biophysical outcomes must be combined with economic and trade models for final decisions regarding optimal policies to deal with climate change. The outcomes should be appropriately responsive to the most likely climate changes of increased air temperature and higher atmospheric carbon dioxide (CO₂)and to the changing technology required for adjusting to the projected climate changes. The biophysical outcomes will be no better than the general circulation model projections of the actual climate change.

Integrated assessments allow researchers to provide answers to complex questions. This approach is particularly well suited for issues such as determining the impacts of climate change on agriculture. The strength of projects using the integrated assessment approach lies in providing information or research results which are the product of investigation of a broad range of subject matter, using differing research methods, and thoughtful discussion among persons with complementary areas of expertise.

Our modeling efforts used VEMAP data (and NOAA data for calibration), and the HadCM2 General Circulation Model (GCM) data for two scenarios: one for the greenhouse gas only run, and one for a greenhouse gas and sulfate run. The study area for this analysis is shown in Figure 1, with the approximate location of our representative farm sites shown. These farm locations represent the area for which the modeling was done. Following is a detailed discussion of all the climate data used in this study.

Validation of crop models is a prerequisite for predicting crop responses under a given set of conditions. The validation process also gives the model users an indication of the magnitude of errors associated with various management and crop variables and their interaction. Model development is a continuous process. At any given point in time a crop simulation model can at best be as good as the current level of understanding of the various processes that govern crop growth and development and, more important, what has been codified into the model. Testing model performance during its development usually results in a very restricted form of evaluation (De Vries and Van Laar, 1982). Adjustment of parameters or coefficients in the model without any rationale, with the sole objective of matching the simulated results with the observed, results in degrading the simulation model into curve fitting. Such an adjusted model’s capability to predict the crop performance under other sets of environmental and soil conditions would be severely restricted. Unlike interpolative regression models, simulation models have the ability to extrapolate (Gangadhar Rao and Bhaskar Rao, 1992).

Most climate change studies are for either a single location or a countrywide scale. The research discussed here is novel due to the creation of a set of representative farms for this modeling project. The use of these representative farms allows for a more complete validation process to be undertaken and, hence, greater reliability of our results. In addition, this methodology allows us to evaluate the effects of a number of climate change scenarios, CO₂ fertilization, climate variability, etc. for different crop types across a multitude of locations, each of which is experiencing different climatic conditions, soil types, and farm-level management practices. The ten areas we studied were scaled up to analyze the impacts of climate change on the Midwest USA, one of the most important agricultural areas in the world.

For farmers, climate-induced changes in crop yields are probably most interesting for their effects on farm income. In this chapter, we attempt to trace a few of the more obvious implications of our modeled yield changes on the economic circumstances of hypothetical midwestern commodity crop producers. Nothing in our work should be taken as a prediction or forecast of the future, but as a possible outcome given specific climate conditions.

Farm-level decisions are made based in part on the farmer’s assessment of the level of risk associated with an option. The risk of lowerthan- expected yields or worse, a crop failure, is not easily discerned by an analysis of averages. Variation around the average yields are of critical importance to the viability of the farming operations and, sometimes, to the long-term success of a crop in a region. The variability of the climate plays a large role in generating the range of yields, and the interaction ofthe two is of significant importance.

Argentina is located between 22° and 55° latitude South and between 54° and 73° longitude West, and includes 2.7 million km² of continental area. The country has great production potential in agriculture, cattle, and forestry. In the years 1989–1999 national grain production attained an average of 47.6 million tonnes (Mt) with a minimum of 34.6 Mt and a maximum of 66.1 Mt. Agricultural products are important contributors to country exports, about 60% of wheat and maize grain production and approximately 85% of oilseed (soybean and sunflower) products are destined to foreign markets.

Wheat is the major crop in Australia in terms of both value and volume. National wheat production is currently about 24 million tones (Mt) from an area of 11.9 million hectares (Mha) with both production and area generally increasing over time (Figure 1). Yields are generally low (national average over the past decade of 1.75 t/ha) due to low rainfall, high vapor pressure deficit, and low physical and chemical soil fertility. High climate variability forces low input management to limit financial risk (Hammer et al., 1996). Irrigation can ameliorate this factor, but restricted volumes of irrigation water limit irrigated cropping. Consequently, regional yields are generally highly correlated with rainfall, although in high rainfall years yield reductions can occur due to waterlogging, lodging, and pest and disease problems (Stephens and Lyons, 1998a).

Land degradation poses an increasing threat to agricultural production. Under natural conditions, topsoil in the aggregate is renewed at a rate approximately equal to the rate at which degradation occurs. However, much agricultural land degrades at faster than “tolerable rates.” (1976) estimate that more than one-third of cropland topsoil in the USA has been lost in the last 200 years. The U.S. Department of Agriculture (USDA) estimates that combined water and wind erosion from cultivated cropland averages approximately 14 tonnes (t)/ha/yr and considers tolerable rates of soil loss on the vast majority of this land to be between 9 and 11 t/ha/yr (USDA, 1994). The majority of the world’s agricultural soils are probably eroding at a faster pace than soils in the USA.

In a study of this duration and complexity, distilling the work of many persons to a concise set of conclusions presents a daunting challenge. As discussed in the Introduction, we had a broad objective of using integrated assessment methodologies to examine potential adaptive responses for the agricultural sector in the Upper Midwest USA while maintaining crop productivity and profitability under future climate change. Our focus in this is the farm level, which we believe is critical because this is where adaptation decisions will be made.