Weather affects the severity of many plant diseases. Climate change is likely to shift weather patterns and the incidence and severity of crop diseases. Modelling likely weather and disease patterns can help in prioritizing research in crop breeding and disease management.
Models based on ecological processes study the distribution and assess the response of a species to environmental conditions. But such models typically require daily or hourly weather readings and are very cumbersome, or impossible, to use over large areas.
The models do not capture the short lifecycles of the microbes and insects that carry plant and animal diseases. To deal with this, researchers at the International Potato Center (CIP), the International Rice Research Institute (IRRI) and their partners, working under CCAFS, adapted the models to combine data recording changes over very short timeframes with data recording changes over longer timeframes.
Scientists chose potato blight – a disease that affects potato production worldwide – as a disease to model because it has been widely studied. Researchers have thoroughly validated data relating to potato blight, high-resolution models are available and it illustrates the type of sensitivity to weather common to many microbes and insects.
Scientists modelled five agro-ecosystems and three emissions scenarios. The risk of blight rose initially under all three scenarios, though less so for the lower emissions scenario. Later in the scenarios, the estimated risk of blight fell below historical levels because there was insufficient relative humidity to maintain infection as temperatures increased.
While analyses of global disease scenarios make a number of assumptions, high temperatures may be an important limiting factor for many foliar diseases such as late blight in the future.
The work with potato blight has much wider applications. The major advances that CCAFS is enabling will improve our ability to forecast and manage major pests and diseases as the climate changes.