Managing the evolution of herbicide resistance

Abstract

Background: Understanding and managing the evolutionary responses of pests and pathogens to control efforts is essential to human health and survival. Herbicide-resistant (HR) weeds undermine agricultural sustainability, productivity and profitability, yet the epidemiology of resistance evolution - particularly at landscape scales - is poorly understood. We studied glyphosate resistance in a major agricultural weed, Amaranthus tuberculatus (common waterhemp), using landscape, weed and management data from 105 central Illinois grain farms, including over 500 site-years of herbicide application records.

Results: Glyphosate-resistant (GR) A. tuberculatus occurrence was greatest in fields with frequent glyphosate applications, high annual rates of herbicide mechanism of action (MOA) turnover and few MOAs field(-1) year(-1) . Combining herbicide MOAs at the time of application by herbicide mixing reduced the likelihood of GR A. tuberculatus.

Conclusions: These findings illustrate the importance of examining large-scale evolutionary processes at relevant spatial scales. Although measures such as herbicide mixing may delay GR or other HR weed traits, they are unlikely to prevent them. Long-term weed management will require truly diversified management practices that minimize selection for herbicide resistance traits.

Keywords: Amaranthus tuberculatus; common waterhemp; glyphosate resistance; herbicide mixing; herbicide rotation; modes of action; resistance evolution.

Figure 1

Study field relative locations within Fayette and Effingham counties, Illinois. A more detailed map is available in supporting information Fig. S1.

Figure 2

Final regression tree of proportional herbicide resistance. R ² = 0.27. HR is the mean proportion of herbicide‐resistant plants per field at each node. The percentage of fields at each node is shown below the node. The bold text indicates the splitting criteria at each node. Fields where the criterion is true are moved down the tree to the right to the next node or terminal leaf. For example, the first split indicates that if the herbicide turnover index is at least 0.57, move to the right. If it is less than 0.57, move to the left. Observations were weighted by the number of years of management data available. N = 76 fields.

Figure 3

Final classification tree of the presence/absence of the resistance trait within the field. R ² = 0.53, accuracy = 0.60. At each node, HR is the mean probability of the glyphosate resistance trait occurring within a field, followed by the percentage of fields represented at the node or leaf. For example, the first node includes 100% of the farms in the dataset, of which 49% have glyphosate resistance. The first split is based on manure use. The label indicates that if manure is applied, go to the left. The leaf to the left includes 18% of the fields in the dataset that together have a mean resistance probability of 0.15. Note: for all other splits, if the splitting criterion is true, observations are included in the branch or leaf to the right of the split. Observations were weighted by the number of years of management data available. N = 105 fields.

Figure 4

Logistic regressions of the per capita probability of glyphosate resistance (proportion of plants resistant) versus three indices of herbicide MOA β diversity. Each metric was calculated for the 3 year period 2004–2006 (n = 55 sites; left column) and for all available years for sites with at least 3 years of data (n = 76 sites; right column). The three metrics are Harrison's β ₁ (β _H1), Whittaker's β (β _W) and our own herbicide turnover index (see methods).

Figure 5

GR seed production of A. tuberculatus in 2010 versus herbicide mixture complexity prior to detection of resistance in Illinois. (A) Probability that resistance > 0 versus the mean MOAs application⁻¹ year⁻¹. The solid black curve shows the predicted probabilities from a logistic regression with resistance status as the binary response variable. The dashed line shows the predictions excluding sites with MOAs > 2.5 from the analysis. (B) Proportion of GR seed produced per field versus the maximum MOAs application⁻¹ year⁻¹. Colors correspond to cluster identities in supporting information Fig. S1. N = 40 in both panels.