Linking Plant Disease Models to Climate Change Scenarios to Project Future Risks of Crop Diseases: A Review

Abstract

The objective of this review is to summarize and evaluate disease risk simulation studies, where crop disease models have been linked to climate projections derived from one or several global circulation models. Altogether, 70 single crop disease risk simulation studies were analyzed which meet this criterion. These studies refer to about 35 plant diseases in 15 different agricultural crops, whereby wheat (especially the diseases fusarium head blight, leaf rust, and septoria tritici blotch) was most often investigated followed by grapevine (especially the disease downy mildew) and oilseed rape (especially the disease phoma stem canker). Most studies refer to Brazil and different Western European countries (e.g. France, Germany, Italy, and United Kingdom). Few considered the entire globe. Interestingly, in about 40% of the studies, disease risk is projected to remain unchanged (seven cases) or to be reduced (22 cases) in the future, particularly in Brazil at the end of the 21st century, mainly due to supra-optimal temperature conditions for the development of some pathogens during the growing season and/or reduced rainfall and leaf wetness, respectively. However, survival of most pathogens, particularly under temperate climatic conditions, during winter-time is projected to be favoured in most simulation studies due to warming. These results suggest that projections of future pathogen/disease dynamics and ranges should include several climatic factors and several pathogen/disease life cycle stages to be more reliable. Only in three of the disease risk simulation studies an option for agronomic adaptation (timing of sowing, cultivar choice) is included in the model runs. Such approaches are particularly valuable because they comprise future options to manage disease risks and minimise potentially adverse effects on crop yield. Therefore, basic tools of the IPM toolbox should be included in disease risk simulation studies in order to take their potential disease risk mitigation capacity into account, which is particularly relevant where crop disease risk is projected to increase in the future.