Researchers might be interested in the relationship between temperature and yields for various reasons: (i) to forecast a yield at a given place in a given year under existing weather conditions; (ii) to simulate the effects of changes in average weather (i.e., climate) in the future. There is a clear distinction between the two. The former relies on the fact that farmers in a location have optimized their production process and adapted to the given climate. A historic time series at the specific location is sufficient to predict yields under various weather outcomes. Imagine a field in Iowa that has been in production for several years. If one were interested in predicting yields in that location, a good guess is to look at what happened to yields in previous years under various weather conditions and use that relationship in the forecast. This is an adequate procedure as farmers have to sow a crop before the weather is realized. For example, corn is usually sown in early spring in Iowa. There is no way to switch the crop in June if the weather turned warmer (or colder) than expected. The farmer is stuck with the crop that was initially chosen. While there are some possible adaptation measures even after the crop is planted (for example, increased use of irrigation or other inputs), the major decision has been made. Hence a farmer uses the existing distribution of possible weather outcomes when making the planting decision.
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D. Lobell and M. Burke (eds.), Climate Change and Food Security, Advances in Global Change Research 37, DOI 10.1007/978-90-481-2953-9_6, © Springer Science + Business Media, B.V. 2010
The situation is quite different if the goal is to predict the impacts of changing climate conditions. If Iowa is to become permanently warmer, farmers might find it no longer optimal to grow the same corn variety but rather switch to a longer season variety instead. If it becomes significantly warmer, farmers might prefer to switch to an entirely new crop, e.g., cotton or citrus, two crops currently grown in warmer climates. Looking at past data at a given location does not incorporate switching to a different crop variety or entirely different crop species as the analysis keeps the crop variety and crop species fixed. Using historic yield data at the location of interest therefore might give an inaccurate prediction of what farmers would to do if the climate permanently changed.
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Renewable energy is energy that is generated from sunlight, rain, tides, geothermal heat and wind. These sources are naturally and constantly replenished, which is why they are deemed as renewable. The usage of renewable energy sources is very important when considering the sustainability of the existing energy usage of the world. While there is currently an abundance of non-renewable energy sources, such as nuclear fuels, these energy sources are depleting. In addition to being a non-renewable supply, the non-renewable energy sources release emissions into the air, which has an adverse effect on the environment.