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Mathematical model reveals hidden economic costs of fungicide resistance in agriculture

Fungicides are plant protection products that kill fungi or their spores. In agriculture, these products are used to combat fungal diseases and ensure crop yields. The disadvantage: if used excessively, resistant pathogens can develop and even infect neighboring fields.

An international research team has developed a mathematical model that can be used to calculate the economic and often hidden costs of fungicide resistance. Chaitanya Gokhale, professor of theoretical evolutionary biology at Julius-Maximilians-Universität Würzburg (JMU), was one of the researchers involved. The results have been in the journal PLOS Sustainability and Transformation.

For the calculations, the researchers used a model that can be used to calculate the spread of fungal diseases in several fields. The team combined this with analysis methods from economics.

Creating a mathematical framework

"Our results show that the economic costs of fungicide resistance are not so easy to determine," says the JMU professor. The study showed that yields can increase or decrease depending on the context. The highest costs of resistance are generated by pathogens with a medium invasiveness—i.e., a medium ability to spread into new areas.

"We observed that while intuitively the total economic costs increase with more resistance and more yield loss, they actually decrease with expensive fungicides," says Gokhale. The team was also able to identify several biological factors that influence the costs. The degree of resistance within a pathogen population is important, and the basic reproduction number of a pathogen is also decisive. In addition, it depends on how much field yield is lost due to a fungal infection.

"Our study provides the mathematical framework with which political decision-makers and stakeholders from the agricultural sector can work," says the evolutionary biologist. On this basis, effective measures for the sustainable use of fungicides can be designed. This in turn could help to secure crop yields, reduce the unnecessary use of chemicals and ensure long-term food security.

As this is a theoretical model, the appeal to researchers is clear: "Future data collection and empirical studies will help test our findings in the field," says Gokhale.