The Experts below are selected from a list of 29610 Experts worldwide ranked by ideXlab platform

Olcay Akman - One of the best experts on this subject based on the ideXlab platform.

  • Model selection for Integrated Pest Management with stochasticity.
    Journal of Theoretical Biology, 2018
    Co-Authors: Olcay Akman, Timothy Comar, Daniel Hrozencik
    Abstract:

    Abstract In Song and Xiang (2006), an Integrated Pest Management model with periodically varying climatic conditions was introduced. In order to address a wider range of environmental effects, the authors here have embarked upon a series of studies resulting in a more flexible modeling approach. In Akman et al. (2013), the impact of randomly changing environmental conditions is examined by incorporating stochasticity into the birth pulse of the prey species. In Akman et al. (2014), the authors introduce a class of models via a mixture of two birth-pulse terms and determined conditions for the global and local asymptotic stability of the Pest eradication solution. With this work, the authors unify the stochastic and mixture model components to create further flexibility in modeling the impacts of random environmental changes on an Integrated Pest Management system. In particular, we first determine the conditions under which solutions of our deterministic mixture model are permanent. We then analyze the stochastic model to find the optimal value of the mixing parameter that minimizes the variance in the efficacy of the Pesticide. Additionally, we perform a sensitivity analysis to show that the corresponding Pesticide efficacy determined by this optimization technique is indeed robust. Through numerical simulations we show that permanence can be preserved in our stochastic model. Our study of the stochastic version of the model indicates that our results on the deterministic model provide informative conclusions about the behavior of the stochastic model.

  • An analysis of an impulsive stage structured Integrated Pest Management model with refuge effect
    Chaos Solitons & Fractals, 2018
    Co-Authors: Olcay Akman, Timothy Comar, Miranda Henderson
    Abstract:

    Abstract Integrated Pest Management (IPM) utilizes a combination of control methods in order to control Pest populations in agricultural systems. Here, we construct a stage structured impulsive Integrated Pest Management with added prey refuge. By considering the ability of Pests to hide from Management strategies, we establish properties for Pest eradication and permanence of the proposed system. Simulations of eradicated and permanent solutions are also included in order to illustrate the behavior of Pest and predator populations.

  • On impulsive Integrated Pest Management models with stochastic effects.
    Frontiers in Neuroscience, 2015
    Co-Authors: Olcay Akman, Timothy Comar, Daniel Hrozencik
    Abstract:

    We extend existing impulsive differential equation models for Integrated Pest Management (IPM) by including stage structure for both predator and prey as well as by adding stochastic elements in the birth rate of the prey. Based on our model, we propose an approach that incorporates various competing stochastic components. This approach enables us to select a model with optimally determined weights for maximum accuracy and precision in parameter estimation. This is significant in the case of Integrated Pest Management because the proposed model accommodates varying unknown environmental and climatic conditions, which affect the resources needed for Pest eradication.

Daniel Hrozencik - One of the best experts on this subject based on the ideXlab platform.

  • Model selection for Integrated Pest Management with stochasticity.
    Journal of Theoretical Biology, 2018
    Co-Authors: Olcay Akman, Timothy Comar, Daniel Hrozencik
    Abstract:

    Abstract In Song and Xiang (2006), an Integrated Pest Management model with periodically varying climatic conditions was introduced. In order to address a wider range of environmental effects, the authors here have embarked upon a series of studies resulting in a more flexible modeling approach. In Akman et al. (2013), the impact of randomly changing environmental conditions is examined by incorporating stochasticity into the birth pulse of the prey species. In Akman et al. (2014), the authors introduce a class of models via a mixture of two birth-pulse terms and determined conditions for the global and local asymptotic stability of the Pest eradication solution. With this work, the authors unify the stochastic and mixture model components to create further flexibility in modeling the impacts of random environmental changes on an Integrated Pest Management system. In particular, we first determine the conditions under which solutions of our deterministic mixture model are permanent. We then analyze the stochastic model to find the optimal value of the mixing parameter that minimizes the variance in the efficacy of the Pesticide. Additionally, we perform a sensitivity analysis to show that the corresponding Pesticide efficacy determined by this optimization technique is indeed robust. Through numerical simulations we show that permanence can be preserved in our stochastic model. Our study of the stochastic version of the model indicates that our results on the deterministic model provide informative conclusions about the behavior of the stochastic model.

  • On impulsive Integrated Pest Management models with stochastic effects.
    Frontiers in Neuroscience, 2015
    Co-Authors: Olcay Akman, Timothy Comar, Daniel Hrozencik
    Abstract:

    We extend existing impulsive differential equation models for Integrated Pest Management (IPM) by including stage structure for both predator and prey as well as by adding stochastic elements in the birth rate of the prey. Based on our model, we propose an approach that incorporates various competing stochastic components. This approach enables us to select a model with optimally determined weights for maximum accuracy and precision in parameter estimation. This is significant in the case of Integrated Pest Management because the proposed model accommodates varying unknown environmental and climatic conditions, which affect the resources needed for Pest eradication.

Sergio Gomez-y-paloma - One of the best experts on this subject based on the ideXlab platform.

  • Incentives and policies for Integrated Pest Management in Europe: a review
    Agronomy for Sustainable Development, 2015
    Co-Authors: Marianne Lefebvre, Stephen R. H. Langrell, Sergio Gomez-y-paloma
    Abstract:

    Integrated Pest Management and organic farming are alternatives for sustainable agriculture and less Pesticide use in the European Union. All professional users of Pesticides in the European Union should follow the general principles of Integrated Pest Management from 2014. States should report to the European Commission on their national action plan for the effective application of those general principles through crop-specific guidelines. The major remaining issues are: (1) when guidelines are not already applied, what incentives would encourage European farmers to adopt those guidelines? (2) How and to what extent should public money be used to promote the adoption of guidelines? Here, we review the adoption of Integrated Pest Management in Europe. We deliver a framework to understand the drivers of changes in farmers’ Pest Management practices. This framework also helps to understand farmer reaction to different policy incentives.

Jay Ram Lamichhane - One of the best experts on this subject based on the ideXlab platform.

Timothy Comar - One of the best experts on this subject based on the ideXlab platform.

  • Model selection for Integrated Pest Management with stochasticity.
    Journal of Theoretical Biology, 2018
    Co-Authors: Olcay Akman, Timothy Comar, Daniel Hrozencik
    Abstract:

    Abstract In Song and Xiang (2006), an Integrated Pest Management model with periodically varying climatic conditions was introduced. In order to address a wider range of environmental effects, the authors here have embarked upon a series of studies resulting in a more flexible modeling approach. In Akman et al. (2013), the impact of randomly changing environmental conditions is examined by incorporating stochasticity into the birth pulse of the prey species. In Akman et al. (2014), the authors introduce a class of models via a mixture of two birth-pulse terms and determined conditions for the global and local asymptotic stability of the Pest eradication solution. With this work, the authors unify the stochastic and mixture model components to create further flexibility in modeling the impacts of random environmental changes on an Integrated Pest Management system. In particular, we first determine the conditions under which solutions of our deterministic mixture model are permanent. We then analyze the stochastic model to find the optimal value of the mixing parameter that minimizes the variance in the efficacy of the Pesticide. Additionally, we perform a sensitivity analysis to show that the corresponding Pesticide efficacy determined by this optimization technique is indeed robust. Through numerical simulations we show that permanence can be preserved in our stochastic model. Our study of the stochastic version of the model indicates that our results on the deterministic model provide informative conclusions about the behavior of the stochastic model.

  • An analysis of an impulsive stage structured Integrated Pest Management model with refuge effect
    Chaos Solitons & Fractals, 2018
    Co-Authors: Olcay Akman, Timothy Comar, Miranda Henderson
    Abstract:

    Abstract Integrated Pest Management (IPM) utilizes a combination of control methods in order to control Pest populations in agricultural systems. Here, we construct a stage structured impulsive Integrated Pest Management with added prey refuge. By considering the ability of Pests to hide from Management strategies, we establish properties for Pest eradication and permanence of the proposed system. Simulations of eradicated and permanent solutions are also included in order to illustrate the behavior of Pest and predator populations.

  • On impulsive Integrated Pest Management models with stochastic effects.
    Frontiers in Neuroscience, 2015
    Co-Authors: Olcay Akman, Timothy Comar, Daniel Hrozencik
    Abstract:

    We extend existing impulsive differential equation models for Integrated Pest Management (IPM) by including stage structure for both predator and prey as well as by adding stochastic elements in the birth rate of the prey. Based on our model, we propose an approach that incorporates various competing stochastic components. This approach enables us to select a model with optimally determined weights for maximum accuracy and precision in parameter estimation. This is significant in the case of Integrated Pest Management because the proposed model accommodates varying unknown environmental and climatic conditions, which affect the resources needed for Pest eradication.