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Discrete Eulerian model for population genetics and dynamics under flow.

Giorgia Guccione1, Roberto Benzi2, Abigail Plummer3

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Marine population dynamics and genetics are impacted by fluid flows. This study introduces a new algorithm to simulate these effects, showing increased fixation probability for organisms in certain flows.

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Area of Science:

  • Ecology
  • Fluid Dynamics
  • Computational Biology

Background:

  • Marine species dynamics are influenced by fluid advection.
  • The impact of fluid flows on population genetics is poorly understood.
  • Agent-based simulations offer detailed insights but are computationally intensive.

Purpose of the Study:

  • To develop and validate a novel algorithm for simulating marine species in fluid flows.
  • To investigate the effects of fluid dynamics on population dynamics and genetic changes.
  • To model phytoplankton behavior in oceanic upwelling/downwelling events.

Main Methods:

  • Developed a discrete agent-based simulation algorithm.
  • Validated the algorithm in 1D and 2D environments without flow.
  • Applied the algorithm to simulate organisms in 2D weakly compressible flows.

Main Results:

  • The algorithm accurately simulates species dynamics without flow.
  • Organisms in 2D time-independent flows show altered population dynamics.
  • Increased fixation probability was observed for organisms born at sources in simulated flows.

Conclusions:

  • The proposed algorithm effectively models marine species in fluid flows.
  • Fluid dynamics significantly influence population genetics, increasing fixation probability.
  • This research provides a computational tool for ecological and evolutionary studies in marine environments.