Abstract

Transgenic crops expressing insecticidal toxins of Bacillus thuringiensis (Bt) have been deployed in agricultural landscapes around the globe. While the key strategy to delay resistance is the mandatory planting of a non-Bt refuge crop that is preferred by the target pest, the efficacy of this resistance management strategy across different landscape contexts over time is rarely considered. Here, we develop an individual-based model to simulate the spatio-temporal distribution of a highly mobile, polyphagous, global pest, Helicoverpa spp, across agricultural landscapes dominated by transgenic cotton. The simulation model allows us to explore refuge ‘electivity’, the relative utilization of refuge habitat by female Helicoverpa, in relation to Bt cotton habitat. Refuge electivity is an emergent function of egg distributions resulting from individual moth behavior, within multiple landscapes during different seasons and crop phenology.The individual-based model is validated against independent data collected from the field. Our findings suggest that refuge electivity is sensitive to the spatial and temporal context of the attractiveness of host crops in the landscape and the preferences of the moths. The attractiveness of mandated refuges, such as pigeon pea relative to Bt cotton, influences how effective they are in the landscape. Dynamics between other host crops, such as sorghum, also play an important role that varies over time and space. We use the model to identify scenarios where refuge strategies are likely to be most effective in terms of boosting susceptible populations and increasing landscape movement (genetic mixing). This dynamic approach has potential to inform better refuge design for Bt resistance management across a wide range of landscape contexts. For example, these findings justify the removal of sorghum as an option for mandated refuge in the Risk Management Plan (RMP) for Bt cotton in Australia.

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