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

Igal Berenshtein*, Claire B. Paris, Hezi Gildor, Erick Fredj, Yael Amitai, Omri Lapidot, Moshe Kiflawi

*Corresponding author for this work

Research output: Contribution to journalArticlepeer-review

13 Scopus citations

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.

Original languageEnglish
Pages (from-to)76-85
Number of pages10
JournalJournal of Theoretical Biology
Volume439
DOIs
StatePublished - 14 Feb 2018

Bibliographical note

Publisher Copyright:
© 2017 Elsevier Ltd

Keywords

  • Connectivity
  • Correlated random walk
  • Directional swimming
  • Gulf of Aqaba
  • Larval dispersal
  • Orientation
  • Pelagic

Fingerprint

Dive into the research topics of 'Auto-correlated directional swimming can enhance settlement success and connectivity in fish larvae'. Together they form a unique fingerprint.

Cite this