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

研究成果: Article査読

1 被引用数 (Scopus)

抄録

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.

本文言語English
ページ(範囲)649-664
ページ数16
ジャーナルEnvironmental and Ecological Statistics
27
4
DOI
出版ステータスPublished - 2020 12

ASJC Scopus subject areas

  • 統計学および確率
  • 環境科学(全般)
  • 統計学、確率および不確実性

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