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From individual behaviour to population models: a case study using swimming algae
Authors:Bearon R N  Grünbaum D
Institution:a Department of Mathematical Sciences, University of Liverpool, Liverpool L69 7ZL, UK
b School of Oceanography, Box 357940, University of Washington, Seattle, WA 98195-7940, USA
Abstract:Trajectories of swimming algae are analysed, and two random-walk models developed to link the individual-level behaviour of cells to population-level advection-diffusion models for the spatial-temporal distribution of cells. The models are both of the advection-diffusion form but are based on two different sets of assumptions about the underlying random-walk behaviours, a velocity jump behaviour and a velocity diffusion behaviour. The mathematical models were developed to allow for an arbitrary (non-weak) bias in the random walk and a variable swimming speed in order to represent the experimental data. For the algal species considered, Heterosigma akashiwo, the mean upward swimming speed was computed as View the MathML source, and the calculated diffusion constants ranged from 2×103 to View the MathML source depending on the details of the models. That two widely used modelling approaches yield substantially different population-level predictions when applied to the same empirical data suggests that better theoretical tools are needed for identifying adequate approximations for behavioural characteristics.
Keywords:Random walks  Micro-organisms  Collective motion  Diffusion  Heterosigma akashiwo
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