Aim: The evolution of pesticide resistance through space and time is of great economic significance to modern agricultural production systems, and consequently, is often well documented. It can thus be used to dissect the evolutionary and ecological processes that underpin large-scale evolutionary responses. There are now nearly 600 documented cases of pesticide resistance in arthropod pests. Although the evolution of resistance is often attributed to the persistent use of chemicals for pest suppression, the rate of development of resistance should also depend on other factors, including climatic conditions that influence population size and generation time. Here, we test whether climatic variables are linked to evolution of resistance by examining the spatial pattern of pyrethroid resistance in an important agricultural pest.
Location: Southern, agricultural regions of Australia. Time period: 2007–2015.
Major taxa studied: The redlegged earth mite, Halotydeus destructor.
Methods: We quantified patterns of chemical usage based on paddock histories and collated long-term climatic data. These data were then compared against presence–absence data on resistance using a boosted regression-tree approach, applied here for the first time to the spatial categorization of pesticide resistance.
Results: Although chemical usage was a key driver of resistance, our analysis revealed climate-based signals in the spatial distribution of resistance, linked to regional variation in aridity, temperature seasonality and precipitation patterns. Climatic regions supporting increased voltinism were positively correlated with resistance, in line with expectations that increased voltinism should accelerate evolutionary responses to selection pressures.
Main conclusions:Our findings suggest that the prediction of rapid evolutionary processes at continental scales, such as pesticide resistance, will be improved through methods that incorporate climate and ecology, in addition to more immediate selection pressures, such as chemical usage. Boosted regression trees present a powerful tool in the management of resistance issues that has hitherto not been used.