To grapple with the considerable complexity in impact analysis, two basic methods have been used. These are: (i) structural modelling of crop and farmer response, combining the agronomic response of plants with economic/management decisions of farmers; and (ii) spatial analogue models that exploit observed differences in agricultural production and climate among regions.
For the first approach, sufficient structural detail is needed to represent specific crops and crop varieties whose responses to different conditions are known through detailed experiments. This structural detail is represented in crop response models, which require details about weather on a daily or hourly basis and specific information on soil properties. Farm management models at a similarly detailed level can be linked to such crop response models and include details about the timing of field operations throughout the growing season, choice of which crop and crop variety to plant, how much fertilizer to use and whether and when to irrigate. They are solved to maximize the profits of farmers given expectations about what the weather, yields and prices will be over the season. An advantage of this approach is that the results can provide detailed understanding of the physical, biological and economic responses and adjustments. A disadvantage is that, for aggregate studies, inferences must be made from relatively few sites and crops to large areas and diverse production systems.
The spatial analogue approach uses cross-section data. It relates an agricultural performance measure, such as observed yields, production, revenue, profits or the value of agricultural land, to climatic conditions that vary regionally. The simplest application of this approach is to map shifts in cropping boundaries as a function of temperature or precipitation changes. More elaborate versions of this approach use statistical analyses of data across geographical areas. Such statistical analyses allow researchers to separate the effects of various climatic factors (temperature, precipitation, temperature extremes, variation in precipitation, etc.) from factors other than climate, such as soil type, that may also explain production differences across regions. An advantage of the spatial analogue approach is that it provides direct evidence on how farmers operating under commercial conditions have responded to different climatic conditions. An inherent assumption is that the adjustments that have been made over long periods of time across regions could be made easily as climate changes in a region.
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