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

Environmental and Ecological Statistics volume 27, pages 649–664 (2020)Cite this article

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.

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Notes

  1. The area of the Pacific Ocean between the coast of the Americas to 150° W from 50° S to 50° N.

  2. Bigeye tuna, skipjack tuna, and yellowfin tuna.

  3. Interacting cooperatively (i.e., “cooperative fishing”), refers to the sharing of information among vessels that may improve their fishing success. Such information can include the specific locations and dates of the purse-seine sets each vessel made, and its catch amounts, or it may be more general spatial–temporal information on the distribution of schools of tunas seen during the fishing trip. This information is shared via radio or satellite phone, for example. The names of vessels with whom another vessel communicates, as well as what is said, is strictly confidential information and not recorded by onboard observers.

  4. Agreement on the International Dolphin Conservation Program: http://www.iattc.org/IDCPENG.htm.

  5. Purse-seine vessels with > 363 metric tons fish-carrying capacity.

  6. Marine mammal sightings are typically the product of active searching and observers must record position information for every marine mammal sighting.

  7. There are two fishery closures each year and vessels must choose to participate in one: July 29–October 8 and November 9 to January 19 of the following year.

  8. Centroid = [average (latitudes), average(longitudes)].

  9. For example, the great circle distance between two points at 25°N separated by one degree of longitude is 54 nm or 90% of the distance at the equator, which is 60 nm.

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Authors and Affiliations

  1. Inter-American Tropical Tuna Commission, 8901 La Jolla Shores Drive, La Jolla, CA, 92037-1508, USA

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

  2. Department of Mathematics, Keio University, 3-14-1 Hiyoshi, Kohoku-ku, Yokohama, Kanagawa, 223-8522, Japan

    Mihoko Minami

Authors
  1. Cleridy E. Lennert-Cody
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  2. Mark N. Maunder
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  3. Marlon H. Román
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  4. Haikun Xu
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  5. Mihoko Minami
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  6. Jon Lopez
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Correspondence to Cleridy E. Lennert-Cody.

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Handling Editor: Bryan F. J. Manly.

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Lennert-Cody, C.E., Maunder, M.N., Román, M.H. et al. Cluster analysis methods applied to daily vessel location data to identify cooperative fishing among tuna purse-seiners. Environ Ecol Stat 27, 649–664 (2020). https://doi.org/10.1007/s10651-020-00451-7

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  • DOI: https://doi.org/10.1007/s10651-020-00451-7

Keywords

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