| Abstract | Helical swimming is among the most common movement behaviors in a wide range of microorganisms. Helical characteristics affect long-term migrations, short-term taxes, transmission and detection of hydrodynamic signals, predator-prey encounter rates, swimming energetics and other critical elements of microorganism ecology. However, microscopy data to characterize helical swimming in microorganisms is usually two-dimensional. We present a versatile, continuous, stochastic model of individual movement that can reflect helical swimming and a variety of other three-dimensional trajectories, but that can be efficiently parameterized from two-dimensional velocity autocorrelation data. The model separates the instantaneous velocity into a slowly varying, advective component and a perpendicularly oriented rotation. These deterministic movements, together with randomness and scales of autocorrelation in each of the components, can be interpreted in terms of the mechanics of movement and environmental stochasticity. As a case study, we estimate three-dimensional swimming parameters for hundreds of videotaped trajectories of a biflaggelate unicellular alga, Heterosigma akashiwo. On the basis of these parameters, we quantify cell-level and strain-level differences algal cells, and demonstrate how microscopic observations can be "scaled up" with data-driven simulations to much larger ecological time and space scales. |
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