Adopting epidemiological approaches for herbicide resistance monitoring and management

The widespread use and increasing reliance on herbicides for weed control has resulted in a global epidemic of evolved herbicide resistance in weed populations. In response, there has been a great deal of research effort to document resistance cases, understand the genetic and physiological mechanisms of resistance, and use models and model organisms to explore resistance management strategies. Here, we argue that the field of epidemiology, which systematically studies the extent, distribution and determinants of a harmful organism or condition, can greatly contribute to our efforts to understand the emergence, selection and spread of herbicide resistance. By systematically collecting data on weed abundance and distribution, the frequency and mechanisms of resistance, and agronomic and environmental metadata, it is possible to develop statistical models that identify the underlying relationships between these elements. In doing so, these approaches can provide novel insight into the relative importance, origin, and spread of different resistance mechanisms, and the agronomic, ecological and evolutionary drivers that dictate the dynamics of resistance evolution at local to global scales. Emerging technologies in weed surveillance, genomics and resistance diagnostics, statistics, and data science will greatly facilitate the collection and analysis of large-scale data sets, providing unprecedented potential for epidemiological analyses of the evolution of herbicide resistance at landscape scales.