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  • 1. Sudo, Masaaki
    et al.
    Takahashi, Daisuke
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Andow, David A.
    Suzuki, Yoshito
    Yamanaka, Takehiko
    Optimal management strategy of insecticide resistance under various insect life histories: heterogeneous timing of selection and interpatch dispersal2018In: Evolutionary Applications, ISSN 1752-4571, E-ISSN 1752-4571, Vol. 11, no 2, p. 271-283, article id GENTINE JA, 1994, JOURNAL OF AGRICULTURAL ENTOMOLOGY, V11, P137 elza Pablo, 2008, PEST MANAGEMENT SCIENCE1st Global Workshop on Stewardship of Neonicotinoid secticides, JUN 05-SEP 09, 2008, Honolulu, HI, V64, P1131Article in journal (Refereed)
    Abstract [en]

    Although theoretical studies have shown that the mixture strategy, which uses multiple toxins simultaneously, can effectively delay the evolution of insecticide resistance, whether it is the optimal management strategy under different insect life histories and insecticide types remains unknown. To test the robustness of this management strategy over different life histories, we developed a series of simulation models that cover almost all the diploid insect types and have the same basic structure describing pest population dynamics and resistance evolution with discrete time steps. For each of two insecticidal toxins, independent one-locus two-allele autosomal inheritance of resistance was assumed. The simulations demonstrated the optimality of the mixture strategy either when insecticide efficacy was incomplete or when some part of the population disperses between patches before mating. The rotation strategy, which uses one insecticide on one pest generation and a different one on the next, did not differ from sequential usage in the time to resistance, except when dominance was low. It was the optimal strategy when insecticide efficacy was high and premating selection and dispersal occur.

  • 2.
    Takahashi, Daisuke
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Yamanaka, Takehiko
    Sudo, Masaaki
    Andow, David A.
    Is a larger refuge always better?: Dispersal and dose in pesticide resistance evolution2017In: Evolution, ISSN 0014-3820, E-ISSN 1558-5646, Vol. 71, no 6, p. 1494-1503Article in journal (Refereed)
    Abstract [en]

    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 nontreated (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.

  • 3. Yamauchi, Atsushi
    et al.
    Takahashi, Daisuke
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics. Center for Ecological Research, Kyoto University, Otsu, Japan.
    Environmental variation does not always promote plasticity: evolutionarily realized reaction norm for costly plasticity2014In: Evolutionary Ecology Research, ISSN 1522-0613, E-ISSN 1937-3791, Vol. 16, no 8, p. 631-647Article in journal (Refereed)
    Abstract [en]

    Question: How does environmental variability influence evolutionarily realized phenotypic plasticity? Mathematical method: Optimization in a spatially fluctuating environment. Key assumptions: Either the maintenance cost of plasticity results from the amount of phenotypic response, or it results from the slope of the reaction norm. And there are two alternative types of state-specific benefit functions: either the benefit is maximal at an intermediate phenotype, or it is a monotonically increasing function of phenotype. Conclusion: Organisms may not respond to rare environmental states. In this case, environmental variability suppresses two indices of phenotypic plasticity, i. e. the range of plasticity and the maximum slope of the reaction norm.

  • 4.
    Zhang, Lai
    et al.
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics. School of Mathematical Science, Yangzhou University, Si Wang Ting Road, Yangzhou 225002, People’s Republic of China.
    Takahashi, Daisuke
    Umeå University, Faculty of Science and Technology, Department of Mathematics and Mathematical Statistics.
    Hartvig, Martin
    Andersen, Ken H.
    Food-web dynamics under climate change2017In: Proceedings of the Royal Society of London. Biological Sciences, ISSN 0962-8452, E-ISSN 1471-2954, Vol. 284, no 1867, article id 20171772Article in journal (Refereed)
    Abstract [en]

    Climate change affects ecological communities through its impact on the physiological performance of individuals. However, the population dynamic of species well inside their thermal niche is also determined by competitors, prey and predators, in addition to being influenced by temperature changes. We use a trait-based food-web model to examine how the interplay between the direct physiological effects from temperature and the indirect effects due to changing interactions between populations shapes the ecological consequences of climate change for populations and for entire communities. Our simulations illustrate how isolated communities deteriorate as populations go extinct when the environment moves outside the species' thermal niches. High-trophic-level species are most vulnerable, while the ecosystem function of lower trophic levels is less impacted. Open communities can compensate for the loss of ecosystem function by invasions of new species. Individual populations show complex responses largely uncorrelated with the direct impact of temperature change on physiology. Such complex responses are particularly evident during extinction and invasion events of other species, where climaticallywell-adapted species may be brought to extinction by the changed food-web topology. Our results highlight that the impact of climate change on specific populations is largely unpredictable, and apparently well-adapted species may be severely impacted.

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