Global patterns and inferences of tuna movements and trophodynamics

Type Article
Date 2020-05
Language English
Author(s) Logan J.M.1, Pethybridge Heidi2, Lorrain Anne3, Somes C.4, Allain Valerie5, Bodin Nathalie6, Choy C.A.7, Duffy L.8, Goñi N.9, Graham B.10, Langlais C.1, Ménard F.11, Olson R.8, Young J.2
Affiliation(s) 1 : Massachusetts Division of Marine Fisheries, New Bedford, MA, 02744, USA
2 : CSIRO Oceans & Atmosphere, GPO Box 158, Hobart, Tasmania, Australia
3 : IRD, Univ Brest, CNRS, Ifremer, LEMAR, F-29280, Plouzané, France
4 : GEOMAR Helmholtz Centre for Ocean Research Kiel, Kiel, Germany
5 : Pacific Community (SPC), Nouméa, New Caledonia
6 : Seychelles Fishing Authority (SFA), Fishing Port, Victoria, Mahé Island, Seychelles
7 : Scripps Institution of Oceanography, University of California, San Diego, Integrative Oceanography Division, La Jolla, CA, 92037, USA
8 : Inter-American Tropical Tuna Commission (IATTC), La Jolla, CA, 92037, USA
9 : AZTI-Tecnalia/Marine Research, Herrera Kaiaportualdea Z/g, 20110, Pasaia, Gipuzkoa, Spain
10 : National Institute of Water and Atmospheric Research, Ltd. (NIWA), Wellington, 6021, New Zealand
11 : Aix Marseille Univ, Université de Toulon, CNRS, IRD, MIO, 13288, Marseille, France
Source Deep-sea Research Part Ii-topical Studies In Oceanography (0967-0645) (Elsevier BV), 2020-05 , Vol. 175 , P. 104775 (19p.)
DOI 10.1016/j.dsr2.2020.104775
WOS© Times Cited 5
Keyword(s) Albacore tuna, Bigeye tuna, Yellowfin tuna, Carbon isotope analysis, Movement indicators, Global ocean, Fisheries management
Abstract

A global dataset of carbon stable isotope (δ13C) values from yellowfin, bigeye, and albacore tuna muscle tissue (n = 4275) was used to develop a novel tool to infer broad-scale movement and residency patterns of these highly mobile marine predators. This tool was coupled with environmental models and lipid content (C:N ratio) of tuna muscle tissues to examine ocean warming impacts on tuna ecology and bioenergetic condition across Longhurst provinces. Over a 16-year study period (2000–2015), latitudinal gradients in tuna δ13C values were consistent, with values decreasing with increasing latitude. Tuna δ13C values, reflecting modelled global phytoplankton δ13C landscapes (“isoscapes”), were largely related to spatial changes in oxygen concentrations at depth and temporal changes in sea surface temperature. Observed tuna isoscapes (δ13CLScorr), corrected for lipid content and the Suess effect (oceanic changes in CO2 over time), were subtracted from model-predicted baseline isoscapes (Δ13Ctuna-phyto) to infer spatial movement and residency patterns of the different tuna species. Stable isotope niche width was calculated for each Longhurst province using Δ13Ctuna-phyto and baseline-corrected nitrogen isotope (δ15Ntuna-phyto) values to further quantify isotopic variability as evidence of movements across isoscapes. A high degree of movement—defined as the deviation from expected range of Δ13Ctuna-phyto values— was evident in four Longhurst provinces: Guinea current coast, North Atlantic drift, Pacific equatorial divergence, and the North Pacific equatorial counter current. The highest level of population dispersal (variability in Δ13Ctuna-phyto values) was observed in Longhurst provinces within the western and central Pacific Oceans and in the Guinea current coast. While lipid content was low in yellowfin and bigeye, high and variable lipid stores in albacore muscle were consistent with seasonal movements between productive foraging and oligotrophic spawning habitats. Our ability to characterize tuna movement patterns without ambiguity remains challenged by uncertainty in trophic discrimination factors and ecological (e.g. diet variability) processes. However, this study illustrates that model-corrected δ13C values are a valuable, relatively cost-effective tool for identifying potential areas of mixing across management zones, particularly when electronic tagging studies are limited or absent. Stable isotope analyses of tuna tissues can therefore be an additional tool for guiding spatial stock assessments on top predator movement, dispersal patterns, and how they may be altered under a changing climate.

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Logan J.M., Pethybridge Heidi, Lorrain Anne, Somes C., Allain Valerie, Bodin Nathalie, Choy C.A., Duffy L., Goñi N., Graham B., Langlais C., Ménard F., Olson R., Young J. (2020). Global patterns and inferences of tuna movements and trophodynamics. Deep-sea Research Part Ii-topical Studies In Oceanography, 175, 104775 (19p.). Publisher's official version : https://doi.org/10.1016/j.dsr2.2020.104775 , Open Access version : https://archimer.ifremer.fr/doc/00617/72943/