Skip to main navigation Skip to search Skip to main content

Merging technologies and supervised classification methods to quantify capture behavior on hook-and-line

  • Ryan J. Knotek
  • , Edward J. Brooks
  • , Lucy A. Howey
  • , James G. Gelsleichter
  • , Brendan S. Talwar
  • , Maggie M. Winchester
  • , Lance K.B. Jordan
  • , Sean Williams
  • , Mark E. Bond
  • , Annabelle M.L. Brooks
  • , Oliver N. Shipley
  • , Trevor Bacon
  • , Jeff R. Kneebone
  • , John W. Mandelman
  • New England Aquarium
  • University of Massachusetts Boston
  • Oceanic Whitetip Shark Consortium
  • Cape Eleuthera Institute
  • University of Exeter
  • University of North Florida
  • Florida International University

Research output: Contribution to journalArticlepeer-review

5 Scopus citations

Abstract

Animal behavior varies in response to capture between/within species and fisheries, and its expression may contribute to incidental mortality when behaviors result in physiological ramifications that cannot be resolved. However, this relationship between capture behavior and animal health is poorly understood, and it remains a logistical challenge to evaluate behavior during capture. We describe an experimental technique that characterizes and quantifies capture behavior in hook-and-line fisheries. This technique includes (1) simultaneously monitoring the behavioral response to capture with accelerometers and cameras, (2) characterizing behavior from video footage and linking discrete behaviors to acceleration data, and (3) predicting behavior based solely on acceleration data using an ensemble of supervised classification methods. We captured oceanic whitetip sharks, Carcharhinus longimanus, with experimental (hook-and-line) gear to test these techniques (n = 38 capture events), with capture durations ranging from 4 to 68 min. In all, 145,589 tri-axial acceleration observations were collected across these events, including simultaneous video footage (six hours total) from 10 capture events. Three discrete capture behaviors were characterized: steady swimming, a high-energy response consisting of thrashing and burst swimming, and a loss of body orientation while hanging motionless from the gear. The latter two behaviors can lead to physiological stress if exhibited for prolonged periods. Our trained ensemble of supervised classification methods successfully predicted behaviors from acceleration data with up to 95.2% accuracy. This technique provides a better understanding of the behavioral response to hook-and-line capture and, if paired with health or fate assessments, can characterize the influence of behavior on mortality. Our technique also provides a method for predicting behavior based on acceleration data alone, which can be more feasible to collect across the spectrum of fishing conditions and practices within a fishery. Such information will assist in understanding how species respond to capture on hook-and-line gear and in the formulation of species- and fishery-specific strategies for mitigating mortality.

Original languageEnglish
Article number151782
JournalJournal of Experimental Marine Biology and Ecology
Volume555
DOIs
StatePublished - Oct 2022

Keywords

  • Acceleration data logger
  • Capture behavior
  • Ethogram
  • Hook-and-line fisheries
  • Oceanic whitetip shark
  • Supervised ensemble classification

Fingerprint

Dive into the research topics of 'Merging technologies and supervised classification methods to quantify capture behavior on hook-and-line'. Together they form a unique fingerprint.

Cite this