Population assessment of tropical tuna based on their associative behavior around floating objects

Type Article
Date 2016-11
Language English
Author(s) Capello M.1, 2, Deneubourg J. L.2, Robert MarianneORCID3, Holland K. N.4, Schaefer K. M.5, Dagorn L.1
Affiliation(s) 1 : Univ Montpellier, CNRS, IFREMER, IRD,UMR MARBEC, Sete, France.
2 : ULB, Unit Social Ecol, Brussels, Belgium.
3 : IFREMER, Lab Technol & Biol Halieut, Lorient, France.
4 : Univ Hawaii Manoa, Hawaii Inst Marine Biol, Honolulu, HI 96822 USA.
5 : IATTC, La Jolla, CA USA.
Source Scientific Reports (2045-2322) (Nature Publishing Group), 2016-11 , Vol. 6 , N. 36415 , P. 1-14
DOI 10.1038/srep36415
WOS© Times Cited 10
Abstract Estimating the abundance of pelagic fish species is a challenging task, due to their vast and remote habitat. Despite the development of satellite, archival and acoustic tagging techniques that allow the tracking of marine animals in their natural environments, these technologies have so far been underutilized in developing abundance estimations. We developed a new method for estimating the abundance of tropical tuna that employs these technologies and exploits the aggregative behavior of tuna around floating objects (FADs). We provided estimates of abundance indices based on a simulated set of tagged fish and studied the sensitivity of our method to different association dynamics, FAD numbers, population sizes and heterogeneities of the FAD-array. Taking the case study of yellowfin tuna (Thunnus albacares) acoustically-tagged in Hawaii, we implemented our approach on field data and derived for the first time the ratio between the associated and the total population. With more extensive and long-term monitoring of FAD-associated tunas and good estimates of the numbers of fish at FADs, our method could provide fisheries-independent estimates of populations of tropical tuna. The same approach can be applied to obtain population assessments for any marine and terrestrial species that display associative behavior and from which behavioral data have been acquired using acoustic, archival or satellite tags.
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