Repeated use of xenobiotic chemicals has selected for the rapid evolution of resistance, threatening health and food security at a global scale. Strategies for preventing the evolution of resistance include cycling and mixtures of chemicals and diversification of management. We currently lack large-scale studies that evaluate the efficacy of these different strategies for minimizing the evolution of resistance. Here we use a national-scale data set of occurrence of the weed Alopecurus myosuroides (black-grass) in the United Kingdom to address this. Weed densities are correlated with assays of evolved resistance, supporting the hypothesis that resistance is driving weed abundance at a national scale. Resistance was correlated with the frequency of historical herbicide applications, suggesting that evolution of resistance is primarily driven by intensity of exposure to herbicides, but was unrelated directly to other cultural techniques. We find that populations resistant to one herbicide are likely to show resistance to multiple herbicide classes. Finally, we show that the economic costs of evolved resistance are considerable: loss of control through resistance can double the economic costs of weeds. This research highlights the importance of managing threats to food production and healthcare systems using an evolutionarily informed approach in a proactive not reactive manner.

Intense selection by pesticides and antibiotics has resulted in a global epidemic of evolved resistance. In agriculture and medicine, using mixtures of compounds from different classes is widely accepted as optimal resistance management. However, this strategy may promote the evolution of more generalist resistance mechanisms. Here we test this hypothesis at a national scale in an economically important agricultural weed: blackgrass (Alopecurus myosuroides), for which herbicide resistance is a major economic issue. Our results reveal that greater use of herbicide mixtures is associated with lower levels of specialist resistance mechanisms, but higher levels of a generalist mechanism implicated in enhanced metabolism of herbicides with diverse modes of action. Our results indicate a potential evolutionary trade-off in resistance management, whereby attempts to reduce selection for specialist resistance traits may promote the evolution of generalist resistance. We contend that where specialist and generalist resistance mechanisms co-occur, similar trade-offs will be evident, calling into question the ubiquity of resistance management based on mixtures and combination therapies.

Summary: Globally, weedy plants are a major constraint to sustainable crop production. Much of the success of weeds rests with their ability to rapidly adapt in the face of human‐mediated management of agroecosystems. Alopecurus myosuroides (blackgrass) is a widespread and impactful weed affecting agriculture in Europe. Here we report a chromosome‐scale genome assembly of blackgrass and use this reference genome to explore the genomic/genetic basis of non‐target site herbicide resistance (NTSR). Based on our analysis of F2 seed families derived from two distinct blackgrass populations with the same NTSR phenotype, we demonstrate that the trait is polygenic and evolves from standing genetic variation. We present evidence that selection for NTSR has signatures of both parallel and non‐parallel evolution. There are parallel and non‐parallel changes at the transcriptional level of several stress‐ and defence‐responsive gene families. At the genomic level, however, the genetic loci underpinning NTSR are different (non‐parallel) between seed families. We speculate that variation in the number, regulation and function of stress‐ and defence‐related gene families enable weedy species to rapidly evolve NTSR via exaptation of genes within large multi‐functional gene families. These results provide novel insights into the potential for, and nature of plant adaptation in rapidly changing environments.

BACKGROUND: Unravelling the genetic architecture of non‐target‐site resistance (NTSR) traits in weed populations can inform questions about the inheritance, trade‐offs and fitness costs associated with these traits. Classical quantitative genetics approaches allow study of the genetic architecture of polygenic traits even where the genetic basis of adaptation remains unknown. These approaches have the potential to overcome some of the limitations of previous studies into the genetics and fitness of NTSR.RESULTS: Using a quantitative genetic analysis of 400 pedigreed Alopecurus myosuroides seed families from nine field‐collected populations, we found strong heritability for resistance to the acetolactate synthase and acetyl CoA carboxylase inhibitors (h² = 0.731 and 0.938, respectively), and evidence for shared additive genetic variance for resistance to these two different herbicide modes of action, r_g = 0.34 (survival), 0.38 (biomass). We find no evidence for genetic correlations between life‐history traits and herbicide resistance, indicating that resistance to these two modes of action is not associated with large fitness costs in blackgrass. We do, however, demonstrate that phenotypic variation in plant flowering characteristics is heritable, h² = 0.213 (flower height), 0.529 (flower head number), 0.449 (time to flowering) and 0.372 (time to seed shed), demonstrating the potential for adaptation to other nonchemical management practices (e.g. mowing of flowering heads) now being adopted for blackgrass control.CONCLUSION: These results highlight that quantitative genetics can provide important insight into the inheritance and genetic architecture of NTSR, and can be used alongside emerging molecular techniques to better understand the evolutionary and fitness landscape of herbicide resistance. © 2022 The Authors. Pest Management Science published by John Wiley & Sons Ltd on behalf of Society of Chemical Industry.