Auto-correlated directional swimming can enhance settlement success and connectivity in fish larvae

J Theor Biol. 2018 Feb 14:439:76-85. doi: 10.1016/j.jtbi.2017.11.009. Epub 2017 Nov 16.

Abstract

Larvae of coastal-marine fishes have been shown repeatedly to swim directionally in the pelagic environment. Yet, biophysical models of larval dispersal typically impose a Simple Random Walk (SRW) algorithm to simulate non-directional movement in the open ocean. Here we investigate the use of a Correlated Random Walk (CRW) algorithm; imposing auto-correlated directional swimming onto simulated larvae within a high-resolution 3D biophysical model of the Gulf of Aqaba, the Red Sea. Our findings demonstrate that implementation of auto-correlated directional swimming can result in an increase of up to ×2.7 in the estimated success rate of larval-settlement, as well as an increase in the extent of connectivity. With accumulating empirical support for the capacity for directional-swimming during the pelagic phase, we propose that CRW should be applied in biophysical models of dispersal by coastal marine fish-larvae.

Keywords: Connectivity; Correlated random walk; Directional swimming; Gulf of Aqaba; Larval dispersal; Orientation; Pelagic.

Publication types

  • Research Support, Non-U.S. Gov't
  • Research Support, U.S. Gov't, Non-P.H.S.

MeSH terms

  • Algorithms
  • Animals
  • Behavior, Animal
  • Fishes
  • Larva / physiology*
  • Models, Biological*
  • Movement
  • Orientation*
  • Random Allocation
  • Swimming*