Cluster analysis methods applied to daily vessel location data to identify cooperative fishing among tuna purse-seiners

Cleridy E. Lennert-Cody, Mark N. Maunder, Marlon H. Román, Haikun Xu, Mihoko Minami, Jon Lopez

Research output: Contribution to journalArticle

Abstract

Management of large-scale pelagic fisheries relies heavily on fishery data to provide information on tuna population status because, for widely distributed populations, the cost of collecting survey data is often prohibitively high. However, fishery data typically do not provide direct information on interactions among fishing vessels, and thus methods of analysis often assume that vessels operate independently, despite the belief that cooperative fishing occurs. Cluster analysis methods were applied to daily vessel location data collected by onboard fisheries observers to identify groups of tuna purse-seine vessels searching for fish close to each other in space. Some vessel groups were found to reoccur through time, both on daily and monthly or longer time scales. This temporal persistence and reoccurrence are interpreted as an indication of cooperative fishing. Results indicate that there may be multiple layers of vessel interactions, from groups of a few vessels to networks of larger numbers of vessels. The use of reoccurring vessel group characteristics to study the temporal and spatial persistence of areas of high tuna abundance is discussed.

Original languageEnglish
JournalEnvironmental and Ecological Statistics
DOIs
Publication statusAccepted/In press - 2020

Keywords

  • Cluster analysis
  • Eastern Pacific Ocean
  • Moving clusters
  • Purse-seine
  • Tuna
  • Vessel behavior

ASJC Scopus subject areas

  • Statistics and Probability
  • Environmental Science(all)
  • Statistics, Probability and Uncertainty

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