10.5061/DRYAD.MB4G0
Takahashi, Daisuke
UmeƄ University
Yamanaka, Takehiko
National Institute for Agro-Environmental Sciences
Sudo, Masaaki
National Institute for Agro-Environmental Sciences
Andow, David A.
University of Minnesota
Data from: Is a larger refuge always better? Dispersal and dose in
pesticide resistance evolution
Dryad
dataset
2017
spatially implicit model
high-dose / refuge strategy
pesticide resistance management
genetically modified organism
Directional selection
dominance
2017-04-10T14:42:23Z
2017-04-10T14:42:23Z
en
https://doi.org/10.1111/evo.13255
27064 bytes
1
CC0 1.0 Universal (CC0 1.0) Public Domain Dedication
The evolution of resistance against pesticides is an important problem of
modern agriculture. The high-dose/refuge strategy, which divides the
landscape into treated and non-treated (refuge) patches, has proven
effective at delaying resistance evolution. However, theoretical
understanding is still incomplete, especially for combinations of limited
dispersal and partially recessive resistance. We reformulate a two-patch
model based on the Comins model and derive a simple quadratic
approximation to analyze the effects of limited dispersal, refuge size and
dominance for high efficacy treatments on the rate of evolution. When a
small but substantial number of heterozygotes can survive in the treated
patch, a larger refuge always reduces the rate of resistance evolution.
However, when dominance is small enough, the evolutionary dynamics in the
refuge population, which is indirectly driven by migrants from the treated
patch, mainly describes the resistance evolution in the landscape. In this
case, for small refuges, increasing the refuge size will increase the rate
of resistance evolution. Our analysis distils major driving forces from
the model, and can provide a framework for understanding directional
selection in source-sink environments.
R script to compute modelsmodel.R implements the simple Comins model
(eq.1) and our approximation (eq.5). The code generates all plots in the
main text and the supplemental information.model.R