A generalised individual-based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations

A - Papers appearing in refereed journals

Liu, C., Bridges, M. E., Kaundun, S. S., Glasgow, L., Owen, M. D. K. and Neve, P. 2017. A generalised individual-based algorithm for modelling the evolution of quantitative herbicide resistance in arable weed populations. Pest Management Science. 73 (2), pp. 462-474.

AuthorsLiu, C., Bridges, M. E., Kaundun, S. S., Glasgow, L., Owen, M. D. K. and Neve, P.
Abstract

BACKGROUND: Simulation models are useful tools for predicting and comparing the risk of herbicide resistance in weed populations under different management strategies. Most existing models assume a monogenic mechanism governing herbicide resistance evolution. However, growing evidence suggests that herbicide resistance is often inherited in a polygenic or quantitative fashion. Therefore, we constructed a generalised modelling framework to simulate the evolution of quantitative herbicide resistance in summer annual weeds. RESULTS: Real-field management parameters based on Amaranthus tuberculatus (Moq.) Sauer (syn. rudis) control with glyphosate and mesotrione in Midwestern US maize-soybean agroecosystems demonstrated that the model can represent evolved herbicide resistance in realistic timescales. Sensitivity analyses showed that genetic and management parameters were impactful on the rate of quantitative herbicide resistance evolution, whilst biological parameters such as emergence and seed bank mortality were less important. CONCLUSION: The simulation model provides a robust and widely applicable framework for predicting the evolution of quantitative herbicide resistance in summer annual weed populations. The sensitivity analyses identified weed characteristics that would favour herbicide resistance evolution, including high annual fecundity, large resistance phenotypic variance and pre-existing herbicide resistance. Implications for herbicide resistance management and potential use of the model are discussed. (C) 2016 Society of Chemical Industry

Keywordsquantitative resistance; individual-based models; Evolution; Amaranthus; tuberculatus Sauer; Weed management; polygenic resistance; Waterhemp amaranthus-rudis; common waterhemp; glyphosate resistance; inhibiting herbicides; Cropping Systems; giant foxtail; tuberculatus; seed; Plants; delay
Year of Publication2017
JournalPest Management Science
Journal citation73 (2), pp. 462-474
Digital Object Identifier (DOI)doi:10.1002/ps.4317
Open accessPublished as non-open access
Output statusPublished
Publication dates
Online13 May 2016
Publication process dates
Accepted13 May 2016
PublisherWiley
Copyright licensePublisher copyright
ISSN1526-498X

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