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The science of climate change has matured considerably during the past decade, both relative to the strength of the evidence documenting the ongoing anthropogenic climate change and in terms of the quality of climate models projecting future changes in climate. Concomitantly, modeling studies to project the likely impacts of climate change on agricultural production also have become more sophisticated. Nonetheless, agricultural impact assessments still do not account for all important factors; for example, potential changes in yield losses due to altered dynamics and intensity of pests (insects, plant pathogens, and weeds) under climate change are generally ignored — an important omission, given the significant role of plant pests in constraining the production of food and fiber worldwide. This paper highlights selected challenges that must be overcome before we can hope to quantify the impacts of a changing climate on plant disease intensity and yield loss. They pertain both to retrospective analyses seeking to identify fingerprints related to climate change in long-term plant-disease records, as well as to the use of mathematical models to predict likely impacts on plant pathosystems in the future. The use of climate-change fingerprints has been limited because time series containing disease variables collected in a standardized manner are unavailable for most plant pathogens; in cases where such long-term records do exist, trends are often confounded by changes in biological or management factors over time. As for the use of models for impact assessment, key challenges pertain to uncertainty in input variables, the difficulty in predicting biological responses in the presence of nonlinearities and thresholds, and the high likelihood of genetic adaptation to climate change.
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H. Scherm (2004) studied this question.
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