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Neve, P.

Paul Neve,

Simulation modelling to understand the evolution and management of glyphosate resistance in weeds.

BACKGROUND: A simulation model is used to explore the influence of biological, ecological, genetic and operational (management) factors on the probability and rate of glyphosate resistance in model weed species. RESULTS: Glyphosate use for weed control prior to crop emergence is associated with low risks of resistance. These low risks can be further reduced by applying glyphosate in sequence with other broad-spectrum herbicides prior to crop seeding. Post-emergence glyphosate use, associated with glyphosate-resistant crops, very significantly increases risks of resistance evolution. Annual rotation with conventional crops reduces these risks, but the proportion of resistant populations can only be reduced to close to zero by mixing two of three post-emergence glyphosate applications with alternative herbicide modes of action. Weed species that are prolific seed producers with high seed bank turnover rates are most at risk of glyphosate resistance evolution. The model is especially sensitive to the initial frequency of R alleles, and other genetic and reproductive parameters, including weed breeding system, dominance of the resistance trait and relative fitness, influence rates of resistance. CONCLUSION: Changing patterns of glyphosate use associated with glyphosate-resistant crops are increasing risks of evolved glyphosate resistance. Strategies to mitigate these risks can be explored with simulation models. Models can also be used to identify weed species that are most at risk of evolving glyphosate resistance.[1]

References

Simulation modelling to understand the evolution and management of glyphosate resistance in weeds. Neve, P. Pest Manag. Sci. (2008) [Pubmed]

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