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Related Experiment Videos

Pathogen-Driven Outbreaks in Forest Defoliators Revisited: Building Models from Experimental Data.

Greg Dwyer, Jonathan Dushoff, Joseph S Elkinton

    The American Naturalist
    |June 17, 2000
    PubMed
    Summary

    New models of forest insect outbreaks, using gypsy moth (Lymantria dispar) and virus data, reveal that seasonality and host susceptibility drive epidemics. These findings offer broader insights into host-pathogen dynamics.

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    Area of Science:

    • Ecology
    • Epidemiology
    • Entomology

    Background:

    • Traditional forest insect outbreak models rely on a priori assumptions and long-term abundance data.
    • Previous models often overlook crucial host-pathogen interaction details like seasonality and host variability.

    Purpose of the Study:

    • To develop and test a novel model of forest insect outbreaks using experimental data.
    • To incorporate key biological details into outbreak modeling for improved accuracy.

    Main Methods:

    • Model development based on experimental data of gypsy moth (Lymantria dispar) and its nuclear polyhedrosis virus.
    • Testing the model with epidemic data to identify critical interaction parameters.
    • Incorporating seasonality, infection-to-death delays, and host susceptibility heterogeneity.
    Keywords:
    Lymantria disparheterogeneity in susceptibilityhost‐pathogen interactionsmathematical modelsnuclear polyhedrosis virus

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    Main Results:

    • Models incorporating biological details predict annual epidemics followed by survivor reproduction.
    • Outbreaks are partly driven by higher susceptibility in younger insect larvae.
    • Seasonality and infection delays can create unstable cycles, stabilized by host susceptibility heterogeneity.

    Conclusions:

    • Gypsy moth-virus model dynamics closely match real-world gypsy moth population dynamics.
    • The model's insights are generalizable to other defoliator-pathogen and seasonal host-pathogen interactions.
    • This approach provides qualitative ecological insights and quantitative data interpretation for host-pathogen systems.