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Evolutionary dynamics from deterministic microscopic ecological processes.

Vaibhav Madhok1

  • 1Department of Physics, Indian Institute of Technology Madras, Chennai 600036, India.

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|April 16, 2020
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Summary
This summary is machine-generated.

This study develops a deterministic model for evolution, showing it mirrors stochastic models under competition. It provides a mechanistic view of evolution, focusing on birth-death events rather than fitness.

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Area of Science:

  • Evolutionary biology
  • Ecological modeling
  • Theoretical biology

Background:

  • Dynamical theory of evolution aims to model mean evolutionary trajectories using individual-level ecological processes.
  • Existing models often rely on stochasticity, but a deterministic approach can offer insights, especially under intense competition.

Purpose of the Study:

  • To develop a deterministic individual-based model for evolution.
  • To derive the canonical equation of adaptive dynamics from this model.
  • To investigate evolution and sympatric speciation under maximal competition.

Main Methods:

  • Developed a deterministic individual-based model focusing on individual births and deaths.
  • Derived the canonical equation of adaptive dynamics from the microscopic ecological model.
  • Analyzed conditions for evolutionary branching and compared deterministic and stochastic models.

Main Results:

  • Deterministic models replicate the mean evolutionary trajectory equations found in stochastic models under maximal competition.
  • Evolutionary branching conditions are similar between deterministic and stochastic models.
  • Deterministic models accelerate population dynamics and biodiversity generation but do not increase the total number of species.

Conclusions:

  • Deterministic individual-based models provide a valid and simplified framework for studying evolutionary dynamics.
  • This approach supports a mechanistic view of evolution, deriving fitness from fundamental birth-death events.
  • The model captures key features of stochastic models, offering an intuitive geometric interpretation of evolution.