Effective flow alignment parameter estimation for motile alga from dynamical data

The kinematics of micro-swimmers in fluid environments are rich with interesting nonlinear behaviors, even in seemingly simple linear flows. These nonlinearities, arising from swimmer-flow interactions, can generate fixed points, periodic orbits, and coherent structures that strongly influence transport. In this talk, we investigate experimentally and theoretically the flow alignment of two motile algae: the marine alga Tetraselmis suecica and the freshwater alga Euglena gracilis, within a linear hyperbolic flow. Despite their inherently helical trajectories and the presence of tumbling and stochastic behavior, we find that the average orientation statistics of these organisms resemble those of smooth-swimming self-propelled particles. These statistics, which we model with a Levy Fokker-Planck equation, converge to the fixed points predicted by Jeffery’s equation for a rigid elliptical particle in a flow. This suggests that the complex swimming dynamics of ensembles of swimmers can be effectively captured by a reduced model: a self-propelled particle with an effective aspect ratio. We discuss possible mechanisms underlying this emergent effective geometry, and its implications for modeling active transport in complex environments.