Plankton predation rates in turbulence: a study of the limitations imposed on a predator with a non-spherical field of sensory perception.
This paper presents an extension to previously published work which studied encounter rates of planktonic predators with restricted perception fields, to examine the related problems of prey capture and predation rates. Small-scale turbulence influences planktonic predation in two ways: the extra energy of the flow enhances the number of encounter events between individual predator and prey meso/micro-zooplankton, but it lowers the capture probability (because the time spent by the predator and prey in close proximity is reduced). Typically, an 'encounter' has usually been defined as an event when a potential prey swims (or is advected) to within a distance R of the predator in any direction. However, there is a considerable body of experimental evidence showing that predators perception fields are far from spherical; often they are wedge shaped (e.g. fish larvae), or strongly aligned with the directions of sensory antennae (e.g. copepods); and this is certain to influence optimal predation strategies. This paper presents a theoretical model which for the first time examines the combined problems of both encounter and capture for a predator with a restricted perception field swimming in a turbulent flow. If such a predator adopts a cruising strategy (continuous swimming, possibly with direction changes) the model predictions suggest that predation rates actually vary little with swimming speed, in contrast to predictions made for spherical perception fields. Consequently, cruising predators are predicted to swim at relatively low speeds whilst foraging. However, application of the model to examine the net energy gain of a typical pause-travel predator (the Atlantic cod larva), does predict the existence of an optimal ratio of the length of pauses to time spent swimming (specifically one pause phase to every two travel phases), in line with experimental observations. Kinematic simulations are presented which support these findings.
Lewis
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DM
Department of Applied Mathematics, University of Liverpool, M & O Building, Peach Street, Liverpool L69 7ZL, UK. d.m.lewsi@liv.ac.uk
Bala
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SI
D000818:Animals; D005399:Fishes / Q000502:physiology*; D008954:Models, Biological; D009068:Movement; D010465:Perception / Q000502:physiology*; D010933:Plankton; D011235:Predatory Behavior / Q000502:physiology*; D012684:Sensory Thresholds; D014872:Water Movements