Herbicide resistance modelling: past, present and future

A - Papers appearing in refereed journals

Renton, M., Busi, R., Neve, P., Thornby, D. and Vila-Aiub, M. 2014. Herbicide resistance modelling: past, present and future. Pest Management Science. 70 (9), pp. 1394-1404. https://doi.org/10.1002/ps.3773

AuthorsRenton, M., Busi, R., Neve, P., Thornby, D. and Vila-Aiub, M.

Computer simulation modelling is an essential aid in building an integrated understanding of how different factors interact to affect the evolutionary and population dynamics of herbicide resistance, and thus in helping to predict and manage how agricultural systems will be affected. In this review, we first discuss why computer simulation modelling is such an important tool and framework for dealing with herbicide resistance. We then explain what questions related to herbicide resistance have been addressed to date using simulation modelling, and discuss the modelling approaches that have been used, focusing first on the earlier, more general approaches, and then on some newer, more innovative approaches. We then consider how these approaches could be further developed in the future, by drawing on modelling techniques that are already employed in other areas, such as individual-based and spatially explicit modelling approaches, as well as the possibility of better representing genetics, competition and economics, and finally the questions and issues of importance to herbicide resistance research and management that could be addressed using these new approaches are discussed. We conclude that it is necessary to proceed with caution when increasing the complexity of models by adding new details, but, with appropriate care, more detailed models will make it possible to integrate more current knowledge in order better to understand, predict and ultimately manage the evolution of herbicide resistance. (C) 2014 Society of Chemical Industry

Keywordscomputer; Simulation; Evolution; integration; Genetics; integrated weed management; lolium-rigidum; glyphosate resistance; Cropping Systems; amaranthus-palmeri; rapid evolution; alopecurus-myosuroides; Insecticide Resistance; simulating evolution; population-dynamics
Year of Publication2014
JournalPest Management Science
Journal citation70 (9), pp. 1394-1404
Digital Object Identifier (DOI)https://doi.org/10.1002/ps.3773
Open accessPublished as non-open access
Output statusPublished
Publication dates
Online01 Mar 2014
Publication process dates
Accepted22 Feb 2014
Copyright licensePublisher copyright

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