Population Dynamics (PD) is a long standing research field in biology, mathematical physics and statistical mechanics. PD deals with changes in size, density and structure of one or more populations over time. In realistic settings, for population living in a fluid environment, it is largely unknown, both theoretically and experimentally, how the phenomenology of Population Dynamics is changed by the presence of turbulence. Effective compressibility can arise, for example, from the convergence and divergence of water masses at which passively URLanisms are restricted to live. The flow can significantly diminish the effect of selective advantage on fixation probabilities. Selective advantage means the ability of one species to growth faster than others. However, because of number fluctuations a relatively small selective advantage may not be successful since the characteristic time scale is much smaller than the one associated to turbulent effects. This project, focus on the enhancement or inhibition of selective advantage in PD subject to advection of compressible turbulence. We find that in presence of weak flows compared to the no-flow case, on URLanisms born at sources acquiring a significant advantage .
Marine species reproduce and compete while being advected by turbulent flows. It is largely unknown, both theoretically and experimentally, how population dynamics and genetics are changed by the presence of fluid flows. Discrete agent-based simulations in continuous space allow for accurate treatment of advection and number fluctuations, but can be computationally expensive for even URLanism densities. In this report, we propose a new algorithm to overcome some of these challenges. We first provide a thorough validation of the algorithm in one and two dimensions without flow. Next, we focus on the case of weakly compressible flows in two dimensions. This URLanisms such as phytoplankton living at a specific depth in the three-dimensional, incompressible ocean experiencing upwelling and/or downwelling events. We show URLanisms born at sources in a 2D time-independent flow experience an increase in fixation probability .
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Population Dynamics (PD) is a long standing research field in biology, mathematical physics and statistical mechanics. PD deals with changes in size, density and structure of one or more populations over time. In realistic settings, for population living in a fluid environment, it
Marine species reproduce and compete while being advected by turbulent flows. It
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the phenomenology of Population Dynamics is
population dynamics and genetics are
R
turbulence. Effective compressibility can arise, for example, from the convergence and divergence of water masses at which passively URLanisms are restricted to live. The flow can significantly diminish the effect of selective advantage on fixation probabilities. Selective advantage means the ability of one species to growth faster than others. However, because of number fluctuations a relatively small selective advantage may not be successful since the characteristic time scale is much smaller than the one associated to turbulent effects. This project,
fluid flows. Discrete agent-based simulations in continuous space allow for accurate treatment of advection and number fluctuations, but can be computationally expensive for even URLanism densities. In this report, we propose a new algorithm to overcome some of these challenges. We first provide a thorough validation of the algorithm in one and two dimensions without flow. Next, we
R
enhancement or inhibition of selective advantage in PD subject to advection of compressible turbulence. We find that in presence of weak flows compared to the no-flow case, on
case of weakly compressible flows in two dimensions. This URLanisms such as phytoplankton living at a specific depth in the three-dimensional, incompressible ocean experiencing upwelling and/or downwelling events. We show
R
acquiring a significant advantage
in a 2D time-independent flow experience an increase in fixation probability