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Stochastic dynamics of social patch foraging decisions.

Subekshya Bidari1, Ahmed El Hady2,3,4, Jacob D Davidson3

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This study introduces a new model for social foraging, showing how groups share information to improve food patch decisions. Different communication methods impact group efficiency and robustness.

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Area of Science:

  • Behavioral Ecology
  • Theoretical Ecology
  • Mathematical Biology

Background:

  • Social foraging enhances survival and reduces uncertainty in resource discovery.
  • Existing theoretical models predominantly focus on solitary foragers, neglecting group dynamics.
  • Understanding group decision-making in foraging is crucial for behavioral ecology.

Purpose of the Study:

  • To develop a mechanistic model of group foraging behavior.
  • To investigate how information transfer influences foraging efficiency in cohesive groups.
  • To differentiate between pulsatile and diffusive communication strategies in foraging groups.

Main Methods:

  • Developed a mechanistic model of individuals foraging in groups using evidence accumulation.
  • Modeled information sharing via intermittent pulsatile and continuous diffusive coupling.
  • Calculated foraging efficiency using a reward rate function and ordered first passage time analysis.
  • Utilized synthetic departure time data for parameter identification and model validation.

Main Results:

  • Pulsatile coupling can yield higher foraging efficiency, strongly dependent on the coupling parameter.
  • Diffusive coupling offers greater robustness against variations in individual decision-making criteria.
  • The model allows for distinguishing between communication modes and estimating model parameters from empirical data.
  • Foraging efficiency is determined by a balance between energy gain and time investment in a patch.

Conclusions:

  • The developed social patch foraging framework models group decision-making and information exchange.
  • The study distinguishes between pulsatile and diffusive communication strategies and their effects on foraging.
  • The model provides a tool for analyzing field data from animal foraging groups and understanding their social decision strategies.