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Pattern Formation Driven by Nonlocal Perception in a Delayed Pine Wilt Disease Model with Top-Hat Kernel.

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Summary
This summary is machine-generated.

Nonlocal perception influences animal movement and disease spread. This study reveals how perception scale and delay affect pattern formation, offering insights into controlling pine wilt disease and understanding collective behaviors like flocks.

Keywords:
DelayNonlocal perceptionPine wilt diseaseTop-hat kernelTuring-Hopf bifurcation

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Area of Science:

  • Mathematical Biology
  • Ecology
  • Animal Behavior

Background:

  • Nonlocal perception is key to understanding animal movement and collective behaviors.
  • Pine wilt disease dynamics involve complex spatiotemporal patterns.

Purpose of the Study:

  • Analyze the impact of nonlocal perception on pattern formation.
  • Apply these findings to model and control pine wilt disease.
  • Investigate the role of perception scale and delay in system stability.

Main Methods:

  • Mathematical modeling of nonlocal perception.
  • Analysis of Turing-Hopf bifurcation.
  • Numerical simulations with biologically relevant parameters.
  • Data analysis for parameter selection.

Main Results:

  • The interaction of perception scale and delay can lead to Turing-Hopf bifurcation.
  • Diverse spatiotemporal patterns, including peak alternating periodic and aggregation patterns, were simulated.
  • Artificial introduction of natural enemies can stabilize pest populations.

Conclusions:

  • Nonlocal perception provides a theoretical basis for pine wilt disease outbreaks and aggregation.
  • The study explains disease transmission mechanisms and contributes to understanding flocking and swarming.
  • Control strategies involving natural enemies can effectively manage pest populations.