Marine Biology

, Volume 156, Issue 1, pp 13–24 | Cite as

Mitochondrial DNA and electronic tracking reveal population structure of Atlantic bluefin tuna (Thunnus thynnus)

  • Andre M. BoustanyEmail author
  • Carol A. Reeb
  • Barbara A. Block
Original Paper


Population subdivision was examined in Atlantic bluefin tuna (Thunnus thynnus) through sequencing of the control region of the mitochondrial genome. A total of 178 samples from the spawning grounds in the Gulf of Mexico, Bahamas and Mediterranean Sea were analyzed. Among the samples from these locations were 36 electronically tagged bluefin tuna that were tagged in the North Atlantic and subsequently traveled to one of these known spawning grounds during the spawning season. Bluefin tuna populations from the Gulf of Mexico and the Mediterranean Sea were found to be genetically distinct based on Φst, and sequence nearest neighbor analyses, showing that these two major spawning areas support independent stocks. Sequence nearest neighbor analysis indicated significant population subdivision among the Gulf of Mexico, western Mediterranean and eastern Mediterranean Sea. However, it was not possible to find significant pairwise differences between any sampling areas when using all samples. If only samples that had a high likelihood of assignment to a specific spawning site were used (young of the year, spawning adults), the differentiation increased among all sampling areas and the Western Mediterranean Sea was distinct from the Eastern Mediterranean Sea and the Gulf of Mexico. It was not possible to distinguish samples from the Bahamas from those collected at any of the other sampling sites. These data support tagging results that suggested distinctness of the Gulf of Mexico, Eastern and Western Mediterranean Sea spawning areas. This level of stock differentiation is only possible if Atlantic bluefin tuna show strong natal homing to individual spawning grounds.


Bluefin Tuna Population Subdivision Western Basin Control Region Sequence Pacific Bluefin 
These keywords were added by machine and not by the authors. This process is experimental and the keywords may be updated as the learning algorithm improves.



We wish to thank Gregorio De Metrio, Eric Prince, Steve Turner, Andy Seitz, Izumi Nakamura, Michael Stokesbury, Steven Teo, Shana Beemer, Steve Loga, Robert Schallert and Kevin Weng for collection of samples. We wish to thank Steve Palumbi, Kim Heiman, Heather Galindo and Michael Castleton for assistance with analysis and manuscript preparation. This study was made possible through grants from the Packard Foundation, the Monterey Bay Aquarium Foundation, the Meyers Trust and NOAA. All samples were collected and all experiments were performed in compliance with any and all laws governing them.


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Copyright information

© Springer-Verlag 2008

Authors and Affiliations

  • Andre M. Boustany
    • 1
    • 2
    Email author
  • Carol A. Reeb
    • 1
  • Barbara A. Block
    • 1
  1. 1.Stanford UniversityPacific GroveUSA
  2. 2.Nicholas School of the Environment and Earth SciencesDuke UniversityDurhamUSA

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