Lagrangian model of copepod dynamics: Clustering by escape jumps in turbulence

H. Ardeshiri, I. Benkeddad, F. G. Schmitt, S. Souissi, F. Toschi, and E. Calzavarini
Phys. Rev. E 93, 043117 – Published 18 April 2016
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Abstract

Planktonic copepods are small crustaceans that have the ability to swim by quick powerful jumps. Such an aptness is used to escape from high shear regions, which may be caused either by flow perturbations, produced by a large predator (i.e., fish larvae), or by the inherent highly turbulent dynamics of the ocean. Through a combined experimental and numerical study, we investigate the impact of jumping behavior on the small-scale patchiness of copepods in a turbulent environment. Recorded velocity tracks of copepods displaying escape response jumps in still water are here used to define and tune a Lagrangian copepod (LC) model. The model is further employed to simulate the behavior of thousands of copepods in a fully developed hydrodynamic turbulent flow obtained by direct numerical simulation of the Navier-Stokes equations. First, we show that the LC velocity statistics is in qualitative agreement with available experimental observations of copepods in turbulence. Second, we quantify the clustering of LC, via the fractal dimension D2. We show that D2 can be as low as 2.3 and that it critically depends on the shear-rate sensitivity of the proposed LC model, in particular it exhibits a minimum in a narrow range of shear-rate values. We further investigate the effect of jump intensity, jump orientation, and geometrical aspect ratio of the copepods on the small-scale spatial distribution. At last, possible ecological implications of the observed clustering on encounter rates and mating success are discussed.

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  • Received 8 January 2016

DOI:https://doi.org/10.1103/PhysRevE.93.043117

©2016 American Physical Society

Physics Subject Headings (PhySH)

Fluid Dynamics

Authors & Affiliations

H. Ardeshiri1,2,*, I. Benkeddad2, F. G. Schmitt2, S. Souissi2, F. Toschi3,4, and E. Calzavarini1

  • 1Université de Lille, CNRS, FRE 3723, LML, Laboratoire de Mécanique de Lille, F 59000 Lille, France
  • 2Université de Lille, CNRS, Université de Littoral Cote d'Opale, UMR 8187, LOG, Laboratoire d'Océanologie et de Géoscience, F 62930 Wimereux, France
  • 3Department of Applied Physics and Department of Mathematics and Computer Science, Eindhoven University of Technology, 5600 MB, Eindhoven, The Netherlands
  • 4Istituto per le Applicazioni del Calcolo CNR, Via dei Taurini 19, 00185 Rome, Italy

  • *hamidreza.ardeshiri@polytech-lille.fr

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Issue

Vol. 93, Iss. 4 — April 2016

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