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Fisheries Research
journal homepage: www.elsevier.com/locate/fishres

Defining the stock structures of key commercial tunas in the Pacific Ocean I:
Current knowledge and main uncertainties
Bradley R. Moorea,b,*, Johann D. Bellc,d, Karen Evanse, Jessica Farleye, Peter M. Grewee,
John Hamptonf, Amandine D. Marieg, Carolina Minte-Verah, Simon Nicolf,i, Graham M. Pillingf,
Joe Scutt Phillipsf, Laura Tremblay-Boyerj, Ashley J. Williamsk,l, Neville SmithfaNational Institute of Water and Atmospheric Research, Nelson 7010, New ZealandInstitute for Marine and Antarctic Studies, University of Tasmania, Hobart, TAS 7001, AustraliacConservation International, Center for Oceans, 2011 Crystal Drive, Suite 500, Arlington, VA 22202, USAdAustralian National Centre for Ocean Resources and Security, University of Wollongong, Wollongong, NSW 2522, Australiae
CSIRO Oceans and Atmosphere, GPO Box 1538, Hobart, TAS 7001, AustraliafOceanic Fisheries Programme, Pacific Community (SPC), Nouméa, BP D5 98848, New CaledoniagESE, Ecology and Ecosystems Health, Agrocampus Ouest, INRAE, 35042 Rennes, FrancehInter-American Tropical Tuna Commission, La Jolla, CA 92037-1509, USAi
Institute for Applied Ecology, University of Canberra, Bruce, ACT 2617, AustraliajDragonfly Data Science, Te Aro, Wellington 6011, New ZealandkAustralian Bureau of Agricultural and Resource Economics and Sciences, Department of Agriculture, Canberra, ACT 2601, AustralialCentre for Sustainable Tropical Fisheries and Aquaculture, College of Science and Engineering, James Cook University, Townsville, QLD 4811, Australiab

ARTICLE INFOABSTRACT

Handled by A.E. Punt

Tunas are the focus of significant fisheries in the Pacific Ocean, where landings of four species – skipjack tuna
(Katsuwonus pelamis), yellowfin tuna (Thunnus albacares), bigeye tuna (Thunnus obesus) and albacore tuna(Thunnus alalunga) – constitute approximately 70 % of the global tuna catch. Stock assessments for skipjack,yellowfin and bigeye tunas in the Pacific Ocean currently assume eastern and western stocks. For albacore tuna,separate North Pacific Ocean and South Pacific Ocean stocks are currently assumed. In each case, these geographic definitions reflect the historical development of fisheries management across the Pacific rather thanbiological considerations. There is widespread agreement that uncertainties surrounding the stock structures ofthese four tuna species could have important impacts on the population dynamics models used to assess theirstatus and inform management options. Knowledge of stock structure is also essential for improved modelling of
the effects of climate change on tuna distribution and abundance and associated implications for fisheries. This
paper reviews current knowledge and understanding of the stock structures of skipjack, yellowfin, bigeye andSouth Pacific albacore tunas in the Pacific Ocean, by exploring available literature relating to their biology,
movement and spatial dynamics. As a guide for future research in this area, we identify the main uncertainties indefining the stock structure of these four tunas in the Pacific, including i) spawning dynamics; ii) the degree of
spawning area fidelity and localised residency; iii) the provenance of individuals in, and proportional contributions of self-replenishing populations to, fishery catches within the Pacific Ocean; iv) linkages with adjacent‘stocks’; v) the effects of climate change on stock structure and proportional contributions of self-replenishing
populations to fisheries; and vi) the implications of improved knowledge of tuna stock structure for stock
assessment and climate change model assumptions and fisheries management. We also briefly propose someapproaches that future studies could use to address these uncertainties.

Keywords:
Tuna
Pacific Ocean
Movement
Spatial dynamics
Stock structure
Fisheries management

1. Introduction
Tunas (Family Scombridae, Tribe Thunnini) are ecologically important top-order predators in pelagic ocean ecosystems (Sund et al.,⁎

1981; Young et al., 2010). They occur across tropical to sub-polar habitats and support extensive fisheries worldwide (FAO, 2018; Reglero
et al., 2014). In the Pacific Ocean, tunas support major industrial
fisheries and a variety of small-scale domestic and subsistence fisheries.

Corresponding author at: National Institute of Water and Atmospheric Research, Nelson 7010, New Zealand.
E-mail address: bradley.moore@niwa.co.nz (B.R. Moore).

https://doi.org/10.1016/j.fishres.2020.105525
Received 28 May 2019; Received in revised form 31 January 2020; Accepted 31 January 20200165-7836/ © 2020 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license(http://creativecommons.org/licenses/BY-NC-ND/4.0/).

Please cite this article as: Bradley R. Moore, et al., Fisheries Research, https://doi.org/10.1016/j.fishres.2020.105525

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The principal target species are skipjack tuna (Katsuwonus pelamis),
yellowfin tuna (Thunnus albacares), bigeye tuna (Thunnus obesus), andalbacore tuna (Thunnus alalunga). Combined, these four species comprise over 90 % of industrial tuna catches from the Pacific Ocean andapproximately 70 % of global commercial tuna catches (SPC-OFP,
2018a).
The majority of catches for each of these four tuna species from the
Pacific Ocean comes from the tropical and sub-tropical waters of theWestern and Central Pacific Ocean (WCPO) (Fig. 1), with an estimated
2.5 million metric tonnes (mt) harvested commercially in 2017 (SPCOFP, 2018a). Substantial harvests of tuna are also made in the Eastern
Pacific Ocean (EPO), with an estimated 637,397 mt of skipjack, yellowfin and bigeye tunas caught in 2017 (IATTC, 2018).
Management of tuna fisheries in the Pacific Ocean, whose distributions straddle exclusive economic zones (EEZs) and the high seas,
is coordinated primarily through two international conventions: theConvention on the Conservation and Management of Highly Migratory
Fish Stocks in the Western and Central Pacific Ocean1; and the Antigua
Convention2 (which revised the Convention for the Establishment of anInter-American Tropical Tuna Commission). These conventions areoperationalised by two independent tuna Regional Fisheries Management Organisations (tRFMOs): the Western and Central Pacific FisheriesCommission (WCPFC) in the WCPO, and the Inter-American Tropical
Tuna Commission (IATTC) in the EPO.
Current assessments for skipjack, yellowfin and bigeye tunas assume
single stocks of each species in the WCPO and the EPO, whereas separate North Pacific Ocean and South Pacific Ocean stocks are assumed
for albacore tuna. In each case, these geographic definitions reflect thehistorical development of fisheries management across the Pacific rather than biological features of the species that might be considered in
population assessments. Further, regional structures within stock assessments, when present, typically represent the spatial distribution offishing gears with differing selectivities, tag mixing assumptions, andmanagement regimes (McKechnie et al., 2014; Tremblay-Boyer et al.,2017, 2018; Vincent et al., 2019). There is growing evidence, however,that the spatial structure and population dynamics of these four target
tunas may be more complex than currently assumed. Complexities instock structure, if present at scales different to those currently assumed
in the population dynamics models used to assess stock status, may
have important implications for stock assessments and fisheries management arrangements. For example, undertaking a stock assessment
based on a single closed stock within a defined area when there are
multiple individual stocks within the area, or assessing only a portion ofa larger stock, is likely to produce misleading results (Begg et al., 1999).
Failure to recognise stock structure can lead to under-fishing of stocks
with high productivity if overly conservative population parameters are
assumed, or over-fishing of less productive stocks should less conservative population parameters be assumed (Begg et al., 1999; Tuckand Possingham, 2000). Where stocks may be undergoing rebuilding
from past over-harvesting, differential restoration between unidentified
stock components can lead to an inability to anticipate future recruitment to those stocks (Begg et al., 1999; Kell et al., 2009). Inappropriate
assumptions of stock structure may also have implications for modelbased investigations of the effects of climate change on the distribution
and abundance of the four tuna species (e.g., Lehodey et al., 2017;
Senina et al., 2018). Models to date have assumed that single, self-replenishing populations exist for each of the four tuna species across the
Pacific basin. Defining stock structure for the four tuna species is thus
considered to be a key research priority for fisheries management(WPRFMC, 2014; Kolody and Hoyle, 2015; Kumar and Kocour, 2015;

Evans et al., 2016; Pecoraro et al., 2017) and essential for planningeffective adaptation of the region’s tuna fisheries to climate change(SPC, 2019).
With the aim of updating current understanding of the movement
and stock structure of skipjack, yellowfin, bigeye and South Pacificalbacore tunas in the Pacific, an international workshop was held in
Nouméa, New Caledonia, in October 2018. The objectives of theworkshop were to: 1) review the current understanding of movement
and stock structure of these four tuna species in the Pacific Ocean, anddefine and discuss the main related knowledge gaps and uncertainties;
and 2) outline sampling considerations and approaches aimed at reducing these gaps and uncertainties. The workshop focused on thesefour species due to their importance to fisheries throughout the Pacific,
their overlap in habitats (particularly as adults), their collective management under the two tRFMOs in the Pacific, and their importance toPacific Island countries and territories (PICTs). Here, we provide a
synthesis of the current knowledge and understanding relating to the
biology, movement and spatial dynamics of these four species used to
guide the workshop discussions. With the perspective that self-replenishing populations should be the basic unit of fisheries management, we examine the relevant biology and spatial considerations incurrent stock assessment approaches for each tuna species, and review
published research on their movement, connectivity and stock structurein the region. Recognising that genetic approaches provide the only
direct evidence of gene flow, this latter discussion is split into genetic
and non-genetic studies, noting and comparing results of any multidisciplinary studies where relevant. We then outline the main knowledge gaps and uncertainties to defining the stock structure of the four
species in the Pacific Ocean, and identify some approaches that futurestudies could adopt to address these gaps.
2. Current understanding of the stock structures of skipjack,yellowfin, bigeye and South Pacific albacore tunas in the PacificOcean
2.1. Skipjack tuna
2.1.1. Relevant biology and spatial considerations in stock assessment
approaches
Skipjack tuna are broadly distributed across the Pacific Ocean, inhabiting tropical to temperate waters from the equator to around 35° oflatitude in the WCPO, extending to around 40 °N and 43 °S with theseasonal extensions of warm poleward flowing currents (Blackburn andServenty, 1981; Kiyofuji et al., 2019). In the EPO, their distribution
narrows to approximately 15° of latitude from the equator east of about
145 °W, extending to around 30 °N and 25 °S seasonally offshore fromthe Americas (Sund et al., 1981; Matsumoto et al., 1984). The bulk ofskipjack tuna biomass, however, occurs within 10° of latitude from theequator (Fig. 1). Tagging and fishery catch data suggest that the distribution of skipjack tuna may vary with the El Niño-Southern Oscillation (ENSO), with an eastwards shift in core distribution to the central
Pacific Ocean (CPO) under El Niño conditions (Lehodey et al., 1997).
Based on observations of gonad state of mature individuals and the
distribution of larvae, spawning in skipjack tuna is considered to occur
in both the WCPO and EPO where sea surface temperatures (SSTs)
generally exceed 24 °C, with the greatest proportion of spawning occurring in waters between 26 °C and 29 °C (Nishikawa et al., 1985;
Schaefer, 2001a; Servidad-Bacordo et al., 2012; Ashida and Horie,
2015; Schaefer and Fuller, 2019). This is considered to result in yearround spawning in tropical waters with spawning occurring seasonallyelsewhere across the species’ distribution (Schaefer and Orange, 1956;
Orange, 1961; Schaefer and Fuller, 2019; Ohashi et al., 2019). Off
Japan, for example, gonad weights of skipjack tuna are relatively higher
in May and June than in other months (Yabe, 1954), with fish observedwith spent ovaries in July and August. Larval densities of skipjack tuna
are higher in the WCPO than in the EPO, suggesting the main spawning1
https://www.wcpfc.int/doc/convention-conservation-and-managementhighly-migratory-fish-stocks-western-and-central-pacific.
2
https://www.iattc.org/PDFFiles/IATTC-Instruments/_English/IATTC_
Antigua_Convention%20Jun%202003.pdf.

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Fig. 1. Distribution and magnitude of total catches for skipjack, yellowfin, bigeye and albacore tunas in the Pacific Ocean between 2009–2018 by 5° square andfishing gear: purse-seine (blue), longline (green), pole-and-line (yellow) and others (pink). The shaded area represents the overlap in management area between theWestern and Central Pacific Fisheries Commission (WCPFC; west) and Inter-American Tropical Tuna Commission (IATTC; east) Convention Areas. Note that pies are
positioned at the centre of each 5° square and only those catches > 1 mt are shown. Source: Pacific Community (SPC), supplemented by IATTC Public Domain Data(available at: https://www.iattc.org/PublicDomainData/IATTC-Catch-by-species1.htm). (For interpretation of the references to colour in this figure legend, thereader is referred to the web version of this article).

areas are in the WCPO (Ueyanagi, 1969; Matsumoto et al., 1984;
Nishikawa et al., 1985), although it should be noted that there has been
comparatively less sampling effort in the EPO. Patchy distribution ofskipjack tuna larvae in the Phoenix Islands Protected Area has been
proposed to occur as a result of spatial variability in the distribution of
spawning individuals (Hernández et al., 2019).
Several studies have explored the degree to which schools of skipjack tuna maintain their temporal integrity. Sharp (1978) found evidence of genetic similarity between individuals in ‘core’ schools, concluding that there was a high probability that some members of theschools were siblings. Based on parasite assemblages, Lester et al.
(1985) estimated that schools maintain their integrity for several
weeks, but not for life. From conventional tagging data, Bayliff (1988a)
estimated that schools of skipjack tuna maintain integrity for weeks tomonths, while Hilborn (1991) concluded that schools in the WCPO ‘donot appear to remain composed of the same individuals for more than a
few weeks’. Based on ultrasonic tracking of individuals associated withdrifting fish aggregating devices (FADs) across temporal scales of hours
to a few days, Schaefer and Fuller (2013) concluded that tagged skipjack tuna were not a cohesive unit, and that the associated schools did
not exhibit a high degree of permanence in structure or size.
In the WCPO, the stock assessment area for skipjack tuna extends
from 20 °S to 50 °N (Vincent et al., 2019). The 2019 assessment was
split into eight regions (Fig. 2), based on the nature of the operating
fleets (purse-seine fleets operating in equatorial waters, artisanal fisheries taking a large proportion of the catch in the westernmost region,and pole-and-line fleets active throughout much of the area but particularly in the northern and westernmost regions), seasonal movement
dynamics and differences in size composition for the pole-and-line
fleets in the northern regions, and tag mixing assumptions around release sites (Vincent et al., 2019).

In the EPO, the last formal stock assessment was conducted in 2005
and was considered uncertain due to unreliable indices of abundance(Maunder and Harley, 2005). Indicators of stock status are now used tomonitor skipjack tuna in the EPO (Maunder and Deriso, 2007; Maunder,2019), which implicitly assume a single stock. Spatially structured assessment models have been explored (e.g., Maunder, 2012), but to datethere has been insufficient information for catch-per-unit-effort (CPUE)
and length-composition data to provide reliable estimates of stock sizefor most candidate sub-populations of skipjack tuna in the EPO.
2.1.2. Genetic studies
Studies applying genetic approaches to skipjack tuna in the Pacific
Ocean have identified varying levels of population structure. Based onblood groups, two phenotypes were identified from fish caught around
Hawaii (Cushing, 1956). Variability in blood groups was also identified
from fish caught around Hawaii and French Polynesia (Marquesas,
Tuamotu and Society Islands), suggesting isolated populations (Spragueand Holloway, 1962). Using blood groups and isozymes, Fujino (1970)
proposed the occurrence of two skipjack tuna groups across the Pacific
Ocean: a ‘western Pacific’ population, including fish sampled from theeast coast of Japan, Marcus Islands, Bonin-Marianas and Palau, and a‘central east Pacific’ population, including samples from Baja California, Ecuador, French Polynesia (Society Islands), Line Islands andHawaii. From genetic, conventional tagging and size distribution data,
Fujino (1996) identified three sub-populations of skipjack tuna within
this central east Pacific population: the central west Pacific, the central
northeast Pacific, and the central southeast Pacific. Fujino (1996) further identified that fish from each group occurred in Hawaiian waters at
different times of the year, and proposed that archipelagos and ocean
currents played a significant role in their observed structuring, with, forexample, the Izu-Bonin-Mariana-Caroline archipelagos delineating the3

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Fig. 2. Top left: The geographic area and regional structure used in the recent stock assessments of skipjack tuna in the Western and Central Pacific Ocean (WCPO;
numbered areas) and Eastern Pacific Ocean (EPO; line shaded area) by Vincent et al. (2019) and Maunder (2019), respectively; bottom left: movements of skipjack
tuna tagged during the Regional Tuna Tagging Programme (RTTP; red arrows) and the Pacific Tuna Tagging Programme (PTTP; blue arrows) recaptured > 1000 nmi
from their release point; top right: proportional distribution of total biomass by weight in each WCPO assessment region apportioned by the source regions; bottom
right: distribution of observed tag displacements for skipjack tuna at liberty for ≥ 3 months from RTTP and PTTP data. All tagging data shown are based on SPC
holdings. Skipjack tuna image: Les Hata, © SPC. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of thisarticle).

westward limit of the range of the central west Pacific population.
Fujino (1996) concluded that the observed geographical genetic heterogeneities could not be attained without the combination of isolation
by distance and homing for spawning, although noted there was nodirect evidence for the latter.
Heterogeneity in allozyme markers has been observed in skipjack
tuna caught around Japan and Hawaii, whereas no differences were
found between fish from Hawaii and Palau (Fujino and Kang, 1968).
Variability in allozyme markers has also been used to propose at least
five ‘subpopulations’ of skipjack tuna with overlapping geographicalboundaries in the Pacific Ocean (New Zealand, north-eastern Pacific,
south-eastern Pacific, north-western Pacific, and Papua New Guinea /Solomon Islands) (Sharp, 1978). Observing spatial clines in enzyme
allele frequencies, Richardson (1983) proposed an isolation-by-distancemodel for skipjack tuna in the Pacific, with the average radius of agenetic neighbourhood in the order of ∼1080 nautical miles (nmi).
DNA isolation, mtDNA D-loop region amplification and nucleotide
sequence analyses failed to detect any genetic differentiation between
skipjack tuna samples from Solomon Islands in the western Pacific
Ocean (WPO) and those from the EPO (Ely et al., 2005). Furthermore,
no differences were found in these markers between skipjack tuna
sampled in the Pacific and Atlantic Oceans, a result which Ely et al.
(2005) suggested was likely due to the large effective population sizesof skipjack tuna in each basin.
More recently, Grewe et al. (2019) used next generation sequencing(NGS) approaches and single nucleotide polymorphism (SNP) makers toinvestigate population structuring of skipjack tuna in the Indian andPacific Oceans. Based on a preliminary analysis the authors reportsignificant differentiation between skipjack tuna sampled from the EPO
and the Indo-Pacific (Maldives, Bismarck and Coral Seas), but notamong their Indo-Pacific sampling locations.
2.1.3. Non-genetic studies
Skipjack tuna has been the primary focus of a number of dedicated,large-scale, conventional tagging programmes conducted in both the
WCPO and EPO. In the WCPO, these studies date back to the 1970s,
commencing with the Skipjack Survey and Assessment Programme(SSAP; 1977–1981). Large numbers of skipjack tuna have since beentagged through the Regional Tuna Tagging Programme (RTTP;
1990–1996), which operated in waters between the Philippines and the
Phoenix Islands of Kiribati, including off the east coast of Australia, and
the Pacific Tuna Tagging Programme (PTTP; 2006–present), operating inwaters 10 °N–10 °S; 120 °E–130 °W (Hampton and Gunn, 1998; Leroyet al., 2015). Combined, these three programmes have tagged over
469,000 skipjack tuna to date, with over 65,000 recoveries reported byJune 2018, including almost 47,000 recoveries of skipjack tuna tagged in
the PTTP alone (Leroy et al., 2015; SPC-OFP, 2018b). Within the WCPO,
these programmes have been complemented by a number of nationallevel tagging activities (Leroy et al., 2015). In the EPO, tagging operations
have been conducted by the IATTC since the 1950s. Around 130,000
skipjack tuna had been tagged by 2015, with 1426 recoveries deemedsuitable for analyses of movement by Fonteneau and Hallier (2015).
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Results from these programmes demonstrate that the movement
dynamics of skipjack tuna are both spatially and temporally complex. In
the WCPO, tagged skipjack tuna have been recaptured well in excess of1000 nmi from original tagging locations (Fig. 2), with displacements
increasing with fish size (SPC-OFP, 2015). The majority of recaptures ofskipjack tuna tagged in the WCPO, however, suggest that long-distancemovements are uncommon, with 95 % of skipjack tuna tagged in the
SSAP, for example, being recaptured within 1000 nmi of their original
release point (Fig. 2) (Hilborn and Sibert, 1998). Sibert and Hampton(2003) estimated skipjack tuna tagged during the SSAP and RTTP tohave a median lifetime displacement ranging from 420 to 470 nmi.
Modelling suggests comparatively low rates of movement for tagged
fish in the region surrounding Solomon Islands (Kleiber and Hampton,
1994; SPC-OFP, 2017). Notwithstanding issues associated with time-atliberty, the distribution of tag releases and the distribution and variability of fishing effort (Leroy et al., 2015), observations from these
programmes suggest the potential for some degree of regional fidelity ofskipjack tuna.
Seasonality of movements of skipjack tuna in the Pacific Ocean has
also been proposed. Using a combination of conventional tagging, genetic and size distribution data, Fujino (1996) hypothesised that fishfrom the WCPO follow two routes to waters off Japan with the extension of the Kuroshio Current in late spring: one from Hawaii throughthe Midway Islands, and a second moving northward from the MarianaBonin-Izu archipelagos. Both groups are then considered to return totropical waters with the Kuroshio Current Extension in late autumn(Fujino, 1996). From archival tagging data, Kiyofuji et al. (2019) observed strong seasonality in movement of skipjack tuna tagged in the
sub-tropical waters south of Japan between 17 °N and 28 °N and theKuroshio Extension Area north of 28 °N, with northward movement offish from subtropical areas (20°–30 °N) commencing in spring. In contrast, individuals tagged in waters surrounding the Nansei Islands,
south-west of mainland Japan, were considered to display greater residency to that area, at least over the duration these fish were at liberty(12–402 days). In the southwestern Pacific Ocean, tag returns suggest
skipjack tuna move south along the Australian east coast during the
austral summer, reaching as far as Tasmania before returning to tropical waters in late autumn and winter (Blackburn and Serventy, 1981).
Tagging data from the EPO suggest a similar mix of seasonally cyclical movement, limited large-scale displacements, and regional fidelity, as well as extensive offshore-onshore movements (Fink and Bayliff,
1970; Bayliff, 1984, 1988b). Based on conventional tagging data, Fink
and Bayliff (1970) concluded that there appear to be two main ‘groups’of skipjack tuna in the EPO: a northern group, occurring around Baja
California, the Gulf of California, and the Revillagigedo Islands off thecoast of Mexico, and a southern group, occurring from Central America(∼Panama) south to northern Chile, with some exchange between
groups. The origins of the two groups are largely uncertain, with someauthors (e.g., Rothschild, 1965) hypothesising that they both originate
from spawning in the central equatorial Pacific Ocean east of 130 °W.
However, significant spawning is known to occur in waters of the EPO
where SST is 24 °C or higher (Schaefer, 2001a), and fish in spawning
condition have since been reported off the coasts of Panama andEcuador (Schaefer, 2001a; Schaefer and Fuller, 2019), suggesting thatat least some proportion of fish in both groups may result from local
spawning.
Movements appear to differ between the two groups of skipjack
tuna in the EPO. In general, fish in the northern group undertake anorthern and then southern movement between 20 °N and 30 °N, coincident with the seasonal movement of the 20 °C surface water isotherm (Fink and Bayliff, 1970). The movements of the southern group
appear to be more complex than those of the northern group (Fink andBayliff, 1970). Young fish that appear in the Panama Bight appear tomove either northward or southward along the coast, before returningto equatorial waters as adults to spawn (Schaefer, 2001a). Movementsof skipjack tuna tagged in the EPO into the WCPO have also been

documented, although the proportion of fish observed to undertakesuch displacements is low, with only 27 fish of the almost 130,000
tagged in the EPO having been recaptured in the WCPO; 21 of whichhave been recaptured around Hawaii (Bayliff, 1988b).
Differences in morphometrics and growth rates of skipjack tuna
have been reported at varying spatial scales (Hennemuth, 1959; Sibert
et al., 1983; Bayliff, 1988b), suggesting some spatial structuring of individuals in the region. Ianelli (1993) observed temporal differences inrecruitment of skipjack tuna in EPO and in the waters around Hawaii,
indicating they had originated from different spawning events. Within
the EPO, significant spatial variation in estimates of maturity at length
have been reported for skipjack tuna in waters north of 15 °N, between
15 °N and 5 °S, and south of 5 °S (Schaefer and Fuller, 2019). Differencesin growth rates of larval and juvenile skipjack tuna collected from twoof the main ecological provinces comprising the Pacific Ocean – theWestern Pacific Warm Pool and the North Pacific Tropical Gyre(Longhurst, 2006) – have also been observed, suggesting that these fish
had grown under differing environmental conditions (Ashida et al.,2018). Lester et al. (1985) found no evidence that would support thepresence of more than one parasitological stock of skipjack tuna in the
Pacific.
Few studies have been published on the otolith chemistry of skipjack tuna. An investigation into the ontogenetic patterns in otolith Sr:Ca
ratios of skipjack tuna (32.2–58.2 cm fork length (FL)) collected fromthe tropical western Pacific (Marshall Islands and Palau) and off thecoast of Japan reported results consistent with a mix of individual
movement behaviours (Arai et al., 2005). Sr:Ca ratios suggested thatmost skipjack tuna sampled from the Marshall Islands were resident intropical waters. Elemental ratios in one individual suggested that thisfish had moved into a temperate region after hatching, before returning
to the Marshall Islands prior to capture (Arai et al., 2005). Sr:Ca ratios
in the otoliths of most fish from Japan suggested they had originated in
the tropics and moved to temperate waters (Arai et al., 2005), consistent with conclusions from tagging data (Aoki et al., 2017).
Based on tagging, size, catch and CPUE data, the most recent stock
assessment for skipjack tuna in the WCPO estimated that biomass in thenorthernmost assessment regions (Regions 1–3) largely results fromself-recruitment with exchange between these regions (Fig. 2) (Vincent
et al., 2019). Biomass in Region 4 (encompassing Hawaii and thenorthern Marshall Islands) was estimated to result predominantly fromthese three regions, as well as from self-recruitment. Biomass in Region
5 (Indonesia and the Philippines) and Region 6 (northern Australia,
Papua New Guinea and north-western Solomon Islands) was estimatedto result largely from self-recruitment, whereas biomass in Region 7
and Region 8 was estimated to result predominantly from recruitment
from regions encompassing the equator (Fig. 2) (Vincent et al., 2019).
Overall, the model estimated little exchange of biomass between regions north and south of 10 °N. However, the lack of north-south mixing
estimated by the model could be due in part to low reporting rates
observed by vessels from particular countries whose vessels are activein the North Pacific Ocean (Peatman et al., 2019).
An ecosystem model (the Spatial Ecosystem and Population
Dynamics Model (SEAPODYM; Lehodey et al., 2008)) estimates mean
optimal spawning temperatures for skipjack tuna to be between
28.5–29 °C (Senina et al., 2016). These results generally match observations that skipjack tuna spawn nearly continuously in the Western
Pacific Warm Pool (e.g., Nishikawa et al., 1985), where such temperatures are most consistent. Occasional seasonality of high and low
larval densities in the Bismarck Sea are predicted during May-November, and December-February, respectively (Senina et al., 2016).
Seasonally favourable areas for spawning of skipjack tuna are predictedin the EPO as occurring during April-June, partially matching observations of spawning in that region by Schaefer and Orange (1956)(although contrasting with more recent observations of Schaefer andFuller (2019)), the central equatorial Pacific in May-August, and thenorth-west East China Sea in August-October (Senina et al., 2016).
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A larval dispersal model (the Individual-based Kinesis, Advection
and Movement of Ocean Animals model (Ikamoana; Scutt Phillips et al.,2018)) estimated quarterly transfer rates of skipjack tuna between the
Solomon and Bismarck Seas to the oceanic Western Pacific Warm Poolof greater than 10 % in both directions, with a transfer of up to 42 %from the former to the latter during a La Niña event (Scutt Phillips
et al., 2018). Simulated transfer of fish between the Western PacificWarm Pool and central equatorial Pacific under non-El Niño conditions
was also high. Exchange between the EPO and the WCPO appeared tobe relatively low, dominated by a quarterly influx of between 5%–15%of EPO biomass moving into the central equatorial region (Scutt Phillips
et al., 2018).

by the majority of individual skipjack tuna in equatorial waters may
result in an isolation by distance structure, whereby increasing genetic
differentiation is correlated with increasing distance. The observationsof Richardson (1983), who proposed an isolation by distance model for
Pacific Ocean skipjack tuna based on spatial clines in enzyme allele
frequencies, and conclusions of Fujino (1996), are consistent with thishypothesis. Alternatively, the regional fidelity exhibited by most fish,coupled with occasional broad-scale movement and gene flow of individuals and/or larval dispersal among regions, may result in a metapopulation structure, or a series of population units wherein individual units exhibit dynamics that are largely determined by local
demography, but are also influenced to a non-trivial degree by exchange with other units (Kritzer and Sale, 2004; Sale et al., 2006, andreferences therein). The observed differences in demographic parameters such as growth rates, maturity profiles and spawning dynamics
are consistent with such a structure. Further sampling is required to test
these various hypotheses.

2.1.4. Synthesis of available information on skipjack tuna stock structure
Based on observations to date, there is some evidence for structuringof skipjack tuna at broad spatial scales within the Pacific Ocean.
Genetic studies (e.g., Sharp, 1978; Fujino, 1996; Grewe et al., 2019)
have demonstrated varying degrees of structure between the EPO and
WCPO, although results between methodologies, and the markers used,have not always been consistent. Finer-scale genetic structuring within
the EPO and WCPO is largely unclear. This is in part because genetic
studies conducted on skipjack tuna in the Pacific Ocean to date havegenerally been constrained by design and logistical issues, including alack of structured sampling, sample sizes and limitations associatedwith the choice of markers investigated (see Section 3). A comprehensive assessment using NGS approaches across the Pacific Ocean has
yet to be conducted. Tagging data (e.g., Hilborn and Sibert, 1998;
Bayliff, 1984, 1988b) suggest movements of skipjack tuna in the Pacific
Ocean are both spatially and temporally complex, but generally support
genetic results that indicate restricted movement of skipjack tuna between the EPO and the WCPO. In equatorial waters, where the bulk oftagging has been conducted, the majority of tagged individuals appear
to exhibit regional fidelity, suggesting the potential for complex structuring within this area, although movement with seasonal expansions ofhabitat have also been observed. Identifying the self-replenishing populations from which individuals undertaking such movements originate will be key to resolving stock boundaries and dynamics (Moore
et al., this issue). However, several caveats exist around the use oftagging data to resolve stock structure of skipjack tuna, relating to thetypes of tags used, tag return rates and distributions and uncertainties
associated with population representativeness (see Section 3). In parallel, information from body morphometrics (Hennemuth, 1959),
growth patterns (e.g., Sibert et al., 1983; Ashida et al., 2018) and reproductive biology (Schaefer and Fuller, 2019) also indicate potential
spatial structuring and residency of Pacific skipjack tuna at varying
spatial scales, however the actual number of stocks present, theirboundaries, and the manner by which they are structured, remains
unresolved.
The regional fidelity indicated by tagging and biological data suggests that Pacific Ocean skipjack tuna may exhibit finer-scale and more
complex structuring than that currently assumed in assessment models.
However, fishery data indicate a continuous distribution of skipjack
tuna in tropical waters of the EPO and WCPO (IATTC, 2018; Williams
and Reid, 2019), while the observation of at least some tagged individuals undertaking large-scale movement (Fig. 2) indicates the potential for a degree of broad-scale gene flow among regions. As such,the occurrence of multiple, genetically distinct and non-overlapping
populations of skipjack tuna in each of the EPO and WCPO is unlikely,
at least without some additional structuring mechanism, such as fish
returning to specific areas for spawning (a form of spawning area fidelity; see Section 3). Unlike those tuna species for which such behaviour is proposed (e.g., Atlantic bluefin tuna, Thunnus thynnus; Blocket al., 2005), there is little evidence for specific, isolated spawning areas
for skipjack tuna, or for the cyclical movement patterns typically associated with fish returning to specific spawning areas.
Potentially more plausible is that the limited movements displayed

2.2. Yellowfin tuna
2.2.1. Relevant biology and spatial considerations in stock assessment
approaches
Yellowfin tuna are broadly distributed across the Pacific Ocean,
inhabiting tropical to temperate waters from approximately 30 °N to
30 °S, extending to 40° in both hemispheres seasonally (Sund et al.,1981). The locations and timing of spawning of yellowfin tuna acrossthe Pacific have been inferred from patterns of larval distribution andhistological examinations of gonad condition. These data suggest thatspawning occurs year-round in tropical waters, and seasonally at higher
latitudes when surface water temperatures are generally above 24 °C(Nishikawa et al., 1985; Schaefer, 1998; Itano, 2000), althoughspawning has been recorded in surface water temperatures of as low as
21.5 °C (Schaefer, 1998). In the EPO, the greatest proportion of
spawning occurs in waters between 26 °C and 30 °C (Schaefer, 1998).
Yellowfin tuna are considered to be serial spawners, capable of repeatedspawning at near daily intervals during each spawning event(McPherson, 1991; Schaefer, 1996; Itano, 2000). Key areas in which
individuals have been observed spawning include the Banda Sea inIndonesia, the north-western Coral Sea, the eastern and southern Philippines, northeast of Solomon Islands, and around Fiji (McPherson,
1988, 1991; Gunn et al., 2002; Servidad-Bacordo et al., 2012). On thebasis of gonad maturity and larval distribution data, Suzuki et al.
(1978) identified three ‘relatively discrete areas of intensive spawning
activity along the equatorial zone’, corresponding to the WPO (withspawning peaking in the third and fourth quarters of the year), CPO(with spawning peaking in the second and third quarters) and EPO(with spawning peaking in the first and second quarters).
The most recent assessment for yellowfin tuna in the WCPO
(Tremblay-Boyer et al., 2017) incorporated a 9-region structure acrossthe area 50 °N–40 °S (Fig. 3). Spatial structuring of the assessment was
informed by the nature of the operating fleets (longline vessels targeting larger individuals and operating primarily in temperate waters;
purse-seine vessels catching smaller individuals and operating almost
exclusively in equatorial waters), and tag mixing assumptions, withadditional spatial areas introduced along the longitudinal axes to increase east-to-west resolution (McKechnie et al., 2014). Assessment
models used in the EPO do not currently incorporate any spatial component explicitly but adopt a ‘fleets-as-areas’ approach, which assumes
several fisheries that are defined by partitioning the data in space andact on the stock with differing catchabilities and selectivities (MinteVera et al., 2019).
2.2.2. Genetic studies
Early genetic investigations into the structure of yellowfin tuna in
the Pacific Ocean included those of Barrett and Tsuyuki (1967), who
did not identify any heterogeneity among yellowfin tuna sampled in the6Fisheries Research xxx (xxxx) xxxx

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Fig. 3. Top left: The geographic area and regional structure used in the recent stock assessments of yellowfin tuna in the Western and Central Pacific Ocean (WCPO;
numbered areas) and Eastern Pacific Ocean (EPO; line shaded area) by Tremblay-Boyer et al. (2017) and Minte-Vera et al. (2019), respectively; bottom left:
movements of yellowfin tuna tagged during the Regional Tuna Tagging Programme (RTTP; red arrows) and the Pacific Tuna Tagging Programme (PTTP; blue arrows)
recaptured > 1000 nmi from their release point; top right: proportional distribution of total biomass by weight in each WCPO assessment region apportioned by thesource regions; bottom right: distribution of observed tag displacements for yellowfin tuna at liberty for ≥ 3 months from RTTP and PTTP data. All tagging data
shown are based on SPC holdings. Yellowfin tuna image: Les Hata, © SPC. (For interpretation of the references to colour in this figure legend, the reader is referred to
the web version of this article).

EPO based on the use of allozymes, and Fujino and Kang (1968), who
did not observe any significant heterogeneity among samples from the
EPO, Hawaii and Kiribati (Line Islands). At a broader spatial scale,significant genetic differentiation between individuals from the WCPO
and EPO was first reported by Sharp (1978) at the Glucose Phosphate
Isomerase (GPI) locus. Temporal stability of the spatial differentiation
observed at the GPI locus was confirmed by Ward et al. (1994). Conversely, Scoles and Graves (1993) found no differences in restriction
fragment length polymorphism (RFLP) mtDNA markers between yellowfin tuna from five widely-separated locations in the Pacific Ocean(Australia, Papua New Guinea, Hawaii, Mexico and Ecuador), or between the Pacific Ocean locations and the Atlantic Ocean, which someauthors (e.g., Díaz-Jaimes and Uribe-Alcocer, 2006) have proposed may
be due to the small sample sizes used. Ward et al. (1997) proposed theexistence of distinct WCPO (encompassing Philippines, Coral Sea, Kiribati and Hawaii sampling locations) and EPO (encompassing southern
California and northern Mexico sampling locations) populations basedon variation within allozymes, but was unable to differentiate WCPO
and EPO samples using mtDNA. At a finer spatial scale, Díaz-Jaimes andUribe-Alcocer (2003) did not observe any significant genetic differentiation in allozymes and Random Amplified Polymorphic DNA(RAPD) markers among yellowfin tuna caught around the Clipperton
and Revillagigedo Islands and Baja California. More recently, examination of mtDNA cytochrome c oxidase subunit (COI) suggested thepossible existence of sub-populations within the CPO (Li et al., 2015).
Examinations of microsatellite markers have provided varying

results, with some studies (Appleyard et al., 2001; Nomura et al., 2014)
unable to demonstrate clear evidence of population differentiation at
ocean-wide scales, whereas others have reported observations of differentiation over finer geographical scales. For example, microsatellite
markers have been used to differentiate yellowfin tuna from thenorthern equatorial (Clipperton Islands, Gulf of California, and coastal
Mexico) and southern equatorial (Peru) regions of the EPO (DíazJaimes and Uribe-Alcocer, 2006), although the authors note these results may be due temporal variation in sample collection or nonrandom sampling. Microsatellite markers also suggest population
structuring of yellowfin tuna between the Philippines and the BismarckSea, Papua New Guinea (Aguila et al., 2015).
More recently, NGS approaches and SNP markers have been used toinvestigate population structuring of yellowfin tuna in the Pacific
Ocean. Using SNPs, including loci putatively under selection, Greweet al. (2015) observed population differentiation among samples fromthe EPO (Baja California), CPO (Tokelau) and WPO (Coral Sea).
Pecoraro et al. (2018) identified genetic variation in neutral and potentially adaptive genomic loci between yellowfin tuna caught in the
EPO (Mexico) and WCPO (Nauru and Solomon Islands). Sampling on
finer geographic scales within the WCPO has not been able to confirm
the presence of more than one genetic population from samples collected from yellowfin tuna caught in waters off Australia, Fiji and the
Marshall Islands (Evans et al., 2019). In their multidisciplinary study
into the stock structure of yellowfin and bigeye tunas in the Indonesian
region, Proctor et al. (2019) observed a cline in SNPs in yellowfin tuna7

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sampled across the Indonesian archipelago, with those in the west moresimilar to those sampled from the central Indian Ocean and those in theeast more similar to those in the WPO. The authors concluded that there
was likely to be greater gene flow between fish caught in central Indonesia with the WPO than there was between fish in central Indonesia
and the Indian Ocean.
Based on an analysis of SNPs, Anderson et al. (2019a) identified two
genetic groupings of yellowfin tuna from samples collected opportunistically from the EEZs of the Federated States of Micronesia (FSM),
Kiribati (Gilbert Islands), New Caledonia, and Papua New Guinea in the
WPO. They also reported a very high proportion of kin (half- or fullsibling) pairs among yellowfin tuna collected in the same individual
sampling events, including between individuals caught at the same FAD
than between those caught in the wider EEZ, with most of the individuals identified as kin being sampled from the FSM. Removal of one
member of each full-sibling pair resulted in only a single genetic
grouping being identified in the samples analysed. From these observations, Anderson et al. (2019a) proposed that yellowfin tuna inassociation with FADs may remain with related individuals throughtheir first year of life, which may generalise to regional fidelity as
adults. The authors cautioned, however, that these observations may
result from processes unique to the FSM or the ad-hoc sampling design
and, as such, should not be generalised to the broader WCPO. The relatively high levels of heterozygosity and outbreeding reported for the
FSM samples are unusual and require further investigation, ideallythrough the analysis of additional quality-assured DNA samples fromthis location. Future studies would benefit from structured designs that
explicitly consider the spawning dynamics of the species, provide forrepresentative sampling and, importantly, include specific protocols toensure quality control in tissue sampling and analyses of DNA data.
Analyses of kinship relationships may provide a rich source of information that delivers fine-scale resolution of population structure anda more detailed examination of stock dynamics than permitted withcurrent approaches (Bravington et al., 2016; Davies et al., 2016).

yellowfin tuna across the WPO, and archival tags have been deployedin the CPO as part of the PTTP (SPC-OFP, 2018b). Preliminary analyses of archival tag data support the results from conventional tagging programmes, demonstrating that although some individuals undertake large-scale movements the displacement of most tagged fish isless pronounced (Leroy et al., 2014, 2015). Archival tag returns suggest that small fish tend to move further and that distances travelledincrease with time-at-liberty (SPC-OFP, 2015). Modelling of the
movement dynamics of yellowfin tuna, based predominantly on therecoveries of tagged juveniles, indicates that movements of fish in theregion surrounding Solomon Islands are relatively limited (SPC-OFP,
2017).
Few tagging studies have focused on the movement of adult yellowfin tuna. The only detailed investigation of movement of adultyellowfin tuna in the WCPO to date is that of Evans et al. (2011), who
examined data from 20 pop-up satellite archival tags (PSATs) deployedon yellowfin tuna ranging from 135 to 158 cm FL in the northern
Tasman Sea and southern Coral Sea. Similar to the results from tagging
programmes on juveniles, tagged adult yellowfin tuna showed a limited
range of movements (estimated displacements of 54 to 1463 km) withall tagged fish remaining within the Coral and Tasman Seas (Evanset al., 2011). However, the findings were somewhat limited by the relatively short time that tags remained attached (2–168 days).
Results from conventional tagging studies on yellowfin tuna in the
EPO suggest that net movements of tagged fish at liberty for more than
30 days tend to be restricted to less than 1000 nmi from their release
positions, with little exchange of fish between northern and southern
regions (Fink and Bayliff, 1970; Bayliff, 1979, 1984). As a result,
Schaefer (2009) concluded that yellowfin tuna from northern andsouthern areas within the EPO probably represent spatially-segregatedsub-stocks. Data from archival tags deployed in the northern EPO indicate that 95 % of tagged fish remained within 1358 km of their release points, with little movement from the northern to the southern
regions (Schaefer et al., 2011, 2014).
Variations in life history, morphometrics and meristics have been
observed for yellowfin tuna at different spatial scales across the Pacific
Ocean. For example, length at 50 % maturity (L50) for female yellowfin
tuna differs for fish in the WCPO and EPO, with 95 % confidence intervals around L50 ranging from 96.5 to 99.5 cm FL for females inIndonesia and Philippines, 107.2–108.5 cm FL for females in theequatorial western Pacific, 110.1–114.6 cm FL for females caught off
Hawaii (Itano, 2000), and 88.6–95.0 cm FL for females in the EPO between 0 °N and 20 °N (Schaefer, 1998). Latitudinal differences in maturity have been observed in the EPO, with yellowfin tuna maturing at
smaller sizes in southern areas (off Costa Rica) than areas to the north(southern Baja California, southern Gulf of California and the Revillagigedo Islands) (Schaefer and Orange, 1956; Orange, 1961). Differences in growth have been observed between fish from Hawaii and
the WCPO, although it is unclear whether these differences are due tothe existence of separate populations or methodological differences in
the preparation and interpretation of otoliths (Farley et al., 2018a).
Regional differences in growth have also been predicted from modelbased approaches, with yellowfin tuna from Indonesia and Philippines
having slower growth rates than those in the wider WCPO (Hoyle et al.,2009). Differences in morphometrics have been observed between
yellowfin tuna from Japan, Hawaii, Peru and north-eastern Pacificwaters (Godsil, 1948; Godsil and Greenhood, 1951), as well as between
French Polynesia, Hawaii and Central America (Schaefer, 1955). Royce(1964) proposed the occurrence of a cline in morphometric charactersalong the equator from Costa Rica to Micronesia. Schaefer (1991, 1992)
demonstrated morphometric and meristic differences among yellowfin
tuna from the WPO, CPO and EPO, as well as latitudinal differences forfish from both the WPO and EPO. In the EPO, Schaefer (1992) observedthat yellowfin tuna caught off Ecuador have deeper bodies, and have on
average one more gill-raker, than those sampled around the

2.2.3. Non-genetic studies
Large numbers of predominantly juvenile yellowfin tuna have beentagged in the WCPO using conventional tags through the SSAP, RTTP
and PTTP, and other local and regional initiatives. Analyses of tag recoveries indicate that although individual yellowfin tuna are capable ofextensive movements, the majority of recaptures have been made close
to release sites, suggesting limited movement and a degree of regional
fidelity (Fig. 3) (Itano and Williams, 1992; Hampton and Gunn, 1998;
Sibert and Hampton, 2003; Fonteneau and Hallier, 2015). For example,
in their analysis of conventional tagging returns from activities of the
RTTP in the north-west Coral Sea, Hampton and Gunn (1998) observed
recaptures as far away as Fiji, Japan, Micronesia, Papua New Guinea
and Solomon Islands, suggesting individuals have the potential to mix
across their range. The majority of recaptures, however, were in therelease area or adjacent Coral Sea (Hampton and Gunn, 1998). Of thetags recovered from yellowfin tuna tagged during the RTTP, ∼90 %have been within 1000 nmi of the point of release (SPC unpublisheddata, cited in Hampton and Gunn, 1998). Sibert and Hampton (2003)
estimated yellowfin tuna tagged in the WCPO during the SSAP and
RTTP to have a median tagged lifetime displacement ranging fromapproximately 337–380 nmi. Yellowfin tuna tagged around FADs andseamounts within the Hawaiian archipelago appear to demonstratehigh fidelity to these devices and features (Klimley and Holloway,
1999; Itano and Holland, 2000), with observations of tagged fish returning to the site of tagging suggesting that yellowfin tuna may becapable of precise homing (Klimley and Holloway, 1999). Yellowfin
tuna has cranial biogenic magnetite, suggesting the presence of amagnetic sense organ (Walker et al., 1984), which may facilitate such
behaviour.
Acoustic and archival tags have also been deployed in juvenile
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Revillagigedo Islands off the coast of Mexico, indicating limited mixing
between groups.
Moore et al. (2019) examined parasite assemblages of juvenile
yellowfin tuna collected from locations within Indonesia and two outlier locations in the Indian Ocean and WPO, as part of a larger multidisciplinary study into the stock structure of the species in and adjacentto Indonesia’s EEZ (Proctor et al., 2019). Parasite data, and particularly
abundances and prevalences of didymozoid species, suggested that little
movement of fish occurs from the WPO into the Indonesian archipelago
or from the Indonesia archipelago into the eastern Indian Ocean, withthe latter observation largely consistent with genetic results (Proctor
et al., 2019).
Several studies have used otolith chemistry to investigate hypotheses relating to the origin of sampled populations throughout the
WCPO. Gunn et al. (2002) examined elemental concentrations in yellowfin tuna otoliths to investigate the probable origins of fish caught in
the western Tasman Sea. Otolith chemistry from the majority of fishcaught in the Tasman Sea most closely resembled that of fish originating from the adjacent Coral Sea, rather than fish from other Pacificsampling sites. Combined with the broader understanding of biology,
fisheries data, oceanography and tagging, the results suggest that, insome years, yellowfin tuna caught in the Tasman Sea originate predominantly from the Coral Sea, with lower numbers originating fromthe broader WPO (Gunn et al., 2002).
Wells et al. (2012) examined δ13C and δ18O in otolith cores of youngof the year (YOY) yellowfin tuna collected from Hawaii, the Line Islandsof Kiribati, Marshall Islands, Philippines, and Solomon Islands and subadults (age-1) collected from Hawaii to investigate nursery-specificcontribution rates. Mixed-stock analysis revealed that most sub-adults
in the Hawaiian fishery had otolith core chemistries representative ofnursery areas within Hawaii, with < 10% having core chemistries indicating that they had originated from equatorial nurseries outside
Hawaii (Wells et al., 2012).
Using trace elements in addition to stable isotopes, Rooker et al.
(2016) reanalysed the same otoliths examined by Wells et al. (2012),
along with additional samples from 1 to 2-year-old fish caught in the
Marshall Islands. Results suggested that fish caught in Marshall Islands
were almost entirely derived from local production, with only a minor
contribution of recruits from the central equatorial Pacific, and that all
sampled yellowfin tuna from Hawaii originated locally (Rooker et al.,2016).
As part of their multidisciplinary study, Proctor et al. (2019) examined otolith chemistry of yellowfin tuna in and adjacent to Indonesian waters. Patterns in stable isotope and elemental compositionindicated fish had not moved large distances in their first six months oflife, a result that was consistent with those from examination of parasiteassemblages (Moore et al., 2019).
Studies investigating variability in muscle stable isotope ratios
suggest limited movement of yellowfin tuna in both the WCPO andEPO. Popp et al. (2007) observed similar latitudinal trends between
yellowfin tuna muscle and amino acid δ15N values and basal food web
δ15N values in the EPO, indicating limited movements of individuals in
the months leading up to capture. Strong spatial trends in muscle δ15N
values were also observed by Houssard et al. (2017) for yellowfin tunain the WCPO, suggesting restricted movement of individuals and highregional residency, at least over the scale of their muscle nitrogenturnover rate (i.e., half-life = 167 days). Enriched size-standardised
mercury (Hg) concentrations in muscle of yellowfin tuna at southernlatitudes (> 15 °S) relative to the equator have also been reported(Houssard et al., 2019), suggesting constrained latitudinal dispersion offish over the lifetime of these signals.
The most recent stock assessment for yellowfin tuna in the WCPO
estimated that biomass in the two northernmost assessment regions(north of 20 °N) and in the westernmost assessment region (aroundIndonesia and the Philippines) results largely from self-recruitment(Fig. 3) (Tremblay-Boyer et al., 2017). Biomass in the two southernmost

regions (south of 10 °S) was also estimated to result largely from selfrecruitment but with some exchange with the neighbouring equatorial
regions (Fig. 3) (Tremblay-Boyer et al., 2017). In contrast, the remaining tropical regions were estimated to have half to two-thirds oftheir biomass derived from movement of fish that recruited to otherregions along the equatorial axis. The same caveats applied to recruitment of skipjack tuna from the assessment model also apply to yellowfin tuna, with potentially low tag reporting rates from tropicaltagging programmes in the North Pacific Ocean, as well as fewer tagging data available outside the equatorial region to inform movement(Tremblay-Boyer et al., 2017).
Studies using SEAPODYM suggest that the distribution of yellowfin
tuna larvae is strongly contrasted between the WPO and EPO. Large
areas of high larval density and seasonally favourable ‘hot spots’ forspawning are predicted to occur in the Western Pacific Warm Poolaround Solomon Islands and Papua New Guinea during the beginning of
the third quarter (∼July), and within the East China Sea during AugustSeptember, with smaller high-density areas occurring in the EPO
around Peru and Costa Rica, peaking in March-April (Senina et al.,2015; Lehodey et al., 2017). The model also suggests that in the absenceof fishing, slightly stronger rates of transfer occur from Indonesia to
Papua New Guinea than in the opposite direction. Papua New Guinea
was also identified as a key source of recruits for the WCPO, with themodel estimating a 23.6 % reduction in adult biomass in the WCPO
when recruitment from Papua New Guinea was removed (Senina et al.,2015).
2.2.4. Synthesis of available information on yellowfin tuna stock structure
The weight of evidence from both genetic and non-genetic studies
supports the presence of discrete stocks of yellowfin tuna in the EPO
and WCPO, as well as the potential for finer-scale spatial structuring
within each of these regions. Analyses of SNPs suggest the occurrence ofat least three stocks broadly associated with the WPO, CPO and EPO(Grewe et al., 2015). Further investigation with temporally-repeatedsamples, quality control of tissue collection, including confirmation of
species identification, and consistent application of genetic methods are
required to confirm these patterns.
Structuring at finer spatial scales within the WCPO and EPO is lessclear. The lack of differentiation of yellowfin tuna caught in waters off
Australia, Fiji and the Marshall Islands observed by Evans et al. (2019)suggests that if finer-scale structuring does exist, it occurs at relatively
broad geographical scales. In both the WCPO and EPO, tagging data
generally suggest limited movement and regional fidelity for the majority of tagged individuals, and support genetic results that indicate
limited movement between these two regions. However, as with skipjack tuna, the majority of tagging studies have largely focused on juveniles using conventional tagging approaches in areas of high abundance and concentrated fishing effort, and are constrained byuncertainties around the population representativeness of tagged individuals (see Section 3), limiting resolution of stock boundaries. In the
WCPO, information from parasite assemblages (Moore et al., 2019) andotolith chemistry (Gunn et al., 2002; Wells et al., 2012; Rooker et al.,2016; Proctor et al., 2019) also suggest yellowfin tuna do not mix
uniformly, although as with tagging studies the majority of these studies have been conducted on juveniles, and are limited by a lack ofspatial and temporal replication.
In the EPO, information from tagging (e.g., Fink and Bayliff, 1970;
Bayliff, 1979, 1984; Schaefer et al., 2011, 2014), length at maturity(e.g., Schaefer and Orange, 1956; Orange, 1961), muscle stable isotope
ratios (Popp et al., 2007) and body morphometrics and meristics (e.g.,
Schaefer, 1992) suggest spatial structuring between fish in the northernand southern areas. Analyses of DNA microsatellites (Díaz-Jaimes andUribe-Alcocer, 2006) also support this differentiation, however further
studies incorporating larger sample sizes and temporal replicates are
required to confirm whether these fish represent different stocks. As
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Ocean, their geographic boundaries, and the mechanisms by which they
are structured, remains unresolved.
Assuming data are representative, the limited movement observed
for most individual yellowfin tuna from tagging data, together with theobserved regional differences in biological parameters, parasite assemblages and otolith chemistry may result in the occurrence of regionally resident populations. However, given their largely continuous
distributions in tropical waters of the EPO and WCPO evident fromfishery data (IATTC, 2018; Williams and Reid, 2019), and observationsof at least some tagged individuals undertaking large-scale movements(e.g., Hampton and Gunn, 1998; Schaefer et al., 2007; SPC-OFP, 2015,2017; Fig. 3), the occurrence of multiple, fully isolated genetic populations of yellowfin tuna in the Pacific Ocean is unlikely, at least
without some additional structuring mechanism, such as fish returningto specific spawning areas. While there is currently no evidence tosupport such behaviour in Pacific Ocean yellowfin tuna, movements ofadult fish, particularly in the WCPO, are poorly understood. In the
Atlantic Ocean, trans-basin movements by yellowfin tuna have been
proposed to result from fidelity between feeding grounds in the western
Atlantic and spawning grounds in the Gulf of Guinea (Bard and Hervé,
1994), however the nature and rate of these hypothesised spawningmigrations are yet to be confirmed (Pecoraro et al., 2018). Alternatively, the limited movements displayed by the majority of individuals may result in an isolation by distance structure, particularly if
individuals reproduce with their nearest neighbours. Supporting thishypothesis is the observation of a cline in genetic structure from SNP
markers in yellowfin tuna across sampling locations in the Indian and
far western Pacific Oceans by Proctor et al. (2019). Further studies are
required to test these various hypotheses.

‘fleets-as-areas’ approach (Xu et al., 2018). Schaefer (2009) observedthat bigeye tuna are caught primarily in two distinct areas in the EPO, asouthern area between 10 °N and 20 °S from coastal waters to 150 °W,
and a northern area between about 15 °N and 35 °N from 130 °W to
150 °W.
A Pacific-wide assessment for bigeye tuna encompassing both the
WCPO and the EPO was conducted in 2015 and included regional
spatial structuring that matched the WCPO and the EPO assessments atthe time. This assessment assumed ‘EPO-style’ growth patterns (seeSection 2.3.3. below) across the Pacific Ocean. The resulting estimatesof stock status of WCPO bigeye tuna from the Pacific-wide model were
not substantially different from those estimated using the WCPO-onlymodel, so it was concluded that conducting separate assessments in the
WCPO and EPO was appropriate (McKechnie et al., 2015).
2.3.2. Genetic studies
To date, the majority of studies using allozymes, mtDNA and microsatellites have not observed evidence of spatial structuring in bigeye
tuna from differing locations in the Pacific Ocean, or between Pacific
Ocean and Indian Ocean sampling locations (Fujino and Kang, 1968;
Alvarado Bremer et al., 1998; Chow et al., 2000; Wu et al., 2014). Manyof these studies have suggested that a lack of structuring is consistent
with broad-scale panmixia among bigeye tuna in the region but also
recognise that additional sampling and alternative techniques may berequired to further investigate population structure (Fujino and Kang,
1968; Alvarado Bremer et al., 1998; Chow et al., 2000; Wu et al., 2014).
However, Grewe and Hampton (1998) found some evidence for restricted gene flow between the Philippines and Ecuador, their two mostwidely separated sampling areas. The ability to further differentiate
populations, however, was limited by small sample sizes. Grewe andHampton (1998) recommended that larger sample sizes and examination of additional loci would be needed to adequately determine thepopulation structure of bigeye tuna in the Pacific Ocean.
Examination of SNPs by Proctor et al. (2019) from bigeye tuna
sampled across the Indonesian archipelago and two outlier locations in
the Indian and Pacific Oceans revealed a cline in genetic structure
across sampling locations consistent with an isolation by distancemodel. Their results suggested restricted connectivity between the Indian Ocean and WPO sampling locations, with the central Indonesiansites appearing to have limited connectivity to both areas. These conclusions were largely consistent with analyses of otolith chemistry andparasite assemblages in the same study (see Section 2.3.3).

2.3. Bigeye tuna
2.3.1. Relevant biology and spatial considerations in stock assessment
approaches
Bigeye tuna are broadly distributed across the Pacific Ocean, inhabiting tropical to temperate waters from approximately 45 °N to 40 °S
in the WCPO, and from approximately 40 °N to 30 °S in the EPO(Calkins, 1980). On the basis of gonad condition of mature fish andobserved distributions of larvae, spawning of bigeye tuna is considered
to occur year-round in tropical equatorial waters of the Pacific Oceanand seasonally in subtropical waters when water temperatures exceed
24 °C (Schaefer, 2001b; Schaefer et al., 2005). Farley et al. (2017) observed spawning capable females between 12 °N and 12 °S and between
137 °E and 130 °W, in water temperatures between 27.7 °C and 30.3 °C,
suggesting central equatorial waters may be an important spawning
region for bigeye tuna. Nishikawa et al. (1985) suggested that the region between Japan and the Philippines is a particularly important
spawning area for bigeye tuna in the WPO, with spawning occurring
there during spring and early summer. Aggregations of bigeye tuna in
the north-western Coral Sea have been associated with spawning(McPherson, 1988; Farley et al., 2003). In the EPO, Schaefer et al.
(2005) observed spawning across a wide area spanning approximately
15 °N and 15 °S to 105 °W to 175 °W.
The most recent stock assessment for bigeye tuna in the WCPO incorporated a 9-region structure across the area 40 °S–50 °N (Fig. 4). This
spatial structuring was informed by the nature of the operating fleets(longline vessels targeting larger individuals and operating primarily inmore temperate waters, and purse-seine vessels catching smaller individuals and operating almost exclusively in equatorial waters) and tag
mixing assumptions, with additional division of areas along the longitudinal axes (McKechnie et al., 2014, 2017a). Shifting the northernedge of the equatorial region from 20 °N to 10 °N suggested the assessment could be sensitive to the configuration of regional structure(McKechnie et al., 2017b; Vincent et al., 2018). The most recent assessment for bigeye tuna in the EPO did not explicitly include regional
structuring but, similar to the assessments of yellowfin tuna, adopted a

2.3.3. Non-genetic studies
Large numbers of bigeye tuna have been tagged across the Pacific
Ocean. The bulk of tagging studies however, particularly in the WCPO,
have focused on juveniles and sub-adults, typically less than 70 cm FL(Leroy et al., 2015). Recaptured bigeye tuna marked with conventionaltags across the WCPO have revealed a range of movements, with someindividuals dispersing large distances (Fig. 4). However, the vast majority of fish tagged with conventional tags have been recaptured lessthan 1000 nmi from their release points (Fig. 4) (Miyabe, 1994;
Hampton and Gunn, 1998; Itano and Holland, 2000; Gunn et al., 2005).
Recaptures of predominantly juvenile bigeye tuna conventionallytagged at the 140 °W, 155 °W, 170 °W and 180° meridians in the CPO
and at liberty for between 30 and 1701 days were mainly within approximately 1000 nmi of their original release point, and within 10° of
latitude from the equator, suggesting a high degree of regional residency and constrained latitudinal dispersion (Schaefer et al., 2015).
Dispersal, where it did occur, was primarily eastwards, and there wassubstantial mixing of bigeye tuna between release longitudes (Schaefer
et al., 2015). Bigeye tuna (predominantly < 80 cm FL) tagged around
FADs and seamounts within the Hawaiian archipelago have been shownto demonstrate high fidelity to these features (Itano and Holland,2000).
Archival tagging studies conducted in the WCPO (primarily on
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Fig. 4. Top left: The geographic area and regional structure used in the recent stock assessments of bigeye tuna in the Western and Central Pacific Ocean (WCPO;
numbered areas) and Eastern Pacific Ocean (EPO; line shaded area) by McKechnie et al. (2017a) and Xu et al. (2018), respectively; bottom left: movements of bigeye
tuna tagged during the Regional Tuna Tagging Programme (RTTP; red arrows) and the Pacific Tuna Tagging Programme (PTTP; blue arrows) recaptured > 1000 nmi
from their release point; top right: proportional distribution of total biomass by weight in each WCPO assessment region apportioned by the source regions; bottom
right: distribution of observed tag displacements for bigeye tuna at liberty for ≥ 3 months from RTTP and PTTP data. All tagging data shown are based on SPC
holdings. Bigeye tuna image: Les Hata, © SPC. (For interpretation of the references to colour in this figure legend, the reader is referred to the web version of thisarticle).

juveniles) support the findings of conventional tagging programmes.
Bigeye tuna tagged in the Coral Sea demonstrated local residence, cyclical movements between the Coral Sea and the broader WPO, andpotentially broad-scale longitudinal dispersal eastwards into the wider
WCPO (Gunn et al., 2005; Evans et al., 2008). Gunn et al. (2005) hypothesised that the cyclical movement observed for bigeye tuna in thenorthwest Coral Sea may be linked in part to movements from
spawning sites and into areas of the Coral Sea and WPO at the completion of spawning. Bigeye tuna tagged with archival tags in the Bismarck and Solomon Seas were also observed to undertake limited
movements over their time at liberty (Leroy et al., 2014; Abascal et al.,2018). Results from archival tagging studies on fish generally < 100 cm
in length in the CPO show similar patterns of movement to that derived
from conventional tagging, demonstrating constrained latitudinal dispersal, some regional fidelity, substantial mixing of bigeye tuna between release locations, particularly between adjacent areas, as well assome extensive eastward longitudinal movement, particularly in thosefish tagged at 140 °W and 170 °W (Schaefer et al., 2015).
Regional fidelity and limited latitudinal movement has also been
observed in conventionally-tagged bigeye tuna released in the equatorial EPO (Schaefer and Fuller, 2009). Bigeye tuna tagged between
95 °W and 97 °W that were at liberty for between 31 to 2291 days werepredominantly recaptured within approximately 1000 nmi of their
original release point with limited latitudinal displacement (Schaefer
and Fuller, 2009). Dispersal of fish tagged was predominantly westward
in nature and the distance dispersed appeared to be positively related tofish size and time at liberty (Schaefer and Fuller, 2009). Regional fidelity has also been observed from archival tag deployments on bigeye
tuna in the EPO, with restricted westward movements (Schaefer andFuller, 2009). Notably, of the 96 recaptures of archivally-tagged bigeye
tuna tagged in the EPO analysed by Schaefer and Fuller (2010), one
individual that was at liberty for 4.1 years undertook two very similar
cyclical movements during its third and fourth years at liberty, moving
into the CPO between ∼150 °W and ∼160 °W in November-December,before returning to ∼84 °W in early May in each year.
On the basis of archival tagging data from the equatorial WPO, CPO
and EPO, Schaefer et al. (2015) proposed that bigeye tuna demonstrated three types of movement behaviours: i) fish that are residents
within an area (<1000 nmi of release location), ii) fish that are residents, yet undertake cyclical excursions outside the area of residency,
and iii) fish that are nomadic and do not demonstrate type 1 or type 2
movement patterns. They further proposed, based on the degree of
mixing observed in association with these behaviours, the existence of
three putative stocks of bigeye tuna in the equatorial Pacific Ocean –eastern, central, and western stocks – with stock boundaries at about
120 °W and 180°, and constrained between 10 °N and 10 °S. On the basisof constrained latitudinal movement evident in each region, they suggested that there was potential for the existence of six additional stocks;
three northward and three southward of the equatorial stocks.
Spatial analysis of length-at-age data suggests that there are differences in growth of bigeye tuna within the Pacific Ocean, indicatingthat mixing is not uniform. Farley et al. (2017) identified four broad
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areas in the WCPO with differing growth profiles, corresponding
roughly to areas i) west of ∼140 °E (encompassing Indonesia and thePhilippines), ii) east of ∼140 °E to ∼150 °W and north to ∼5 °N, iii)
north of 5 °N, and iv) east of ∼150 °W (encompassing French Polynesia
samples), with fish from the westernmost (<140 °E) and easternmost(∼155 °W–130 °W) areas of the sampling region observed to growfaster compared to those from central longitudes (Farley et al., 2017,2018b). However, the authors cautioned that the data were limited
both spatially and by length/age coverage and that further work wasnecessary to fully explore spatial variation in growth across the Pacific
Ocean. Examination of otolith weight-at-length data over a broader
area revealed similar spatial patterns with larger length-at-otolithweight occurring east of ∼130 °W (Farley et al., 2018b). This is consistent with faster growth rates observed in bigeye tuna from the EPO(Schaefer and Fuller, 2006). There is ongoing work to clarify whether
the differences in growth between the WCPO and EPO is due to theexistence of separate stocks or methodological differences in the preparation and interpretation of otoliths (Farley et al., 2018b). Spatialdifferences in length at maturity have also been observed, with mean
length at 50 % maturity of females estimated to be ∼103 cm in the
WPO, ∼108 cm in the CPO and 135 cm FL in the EPO (Schaefer et al.,2005; Zhu et al., 2010; Sun et al., 2013; Farley et al., 2017).
Studies investigating variability in parasite assemblages or otolithchemistry in bigeye tuna in the Pacific have been limited. Moore et al.
(2019) examined the parasite fauna of juvenile bigeye tuna collectedfrom locations within the Indonesian EEZ and two outlier locations –Maldives and Solomon Islands – as part of the multidisciplinary study ofProctor et al. (2019). Their results suggested little movement of juvenile
bigeye tuna between Indonesia waters and the two outlier locations,from the WPO sites into the Indonesian archipelago, or from the Indonesia archipelago to the eastern Indian Ocean. These results werelargely consistent with otolith isotope and elemental composition data,
which suggested that fish had not moved very far in their first few
months of life (Proctor et al., 2019).
Comparisons of stable isotopes (δ13C and δ18O) and chemical signatures of the natal regions of otoliths from young of the year bigeye
tuna collected from four regions throughout the WCPO have revealed
spatial variability in these isotopes, particularly in the depletion of δ18O
(Rooker et al., 2016). When compared with the stable isotope andchemical signatures of natal regions of otoliths from 1 to 2-year-old
bigeye tuna from the Marshall Islands and Hawaii, Rooker et al. (2016)concluded that bigeye tuna from the Marshall Islands were derived
almost entirely from local production, with a minor contribution ofrecruits from the central equatorial Pacific. In contrast, a large proportion of bigeye tuna caught off Hawaii were deemed to have originated from the central equatorial region (Rooker et al., 2016).
Examination of the stable isotopes of muscle tissue from bigeye tuna
also suggests some spatial structuring of individuals. Houssard et al.
(2017) observed strong spatial trends in δ15N values for bigeye tuna
sampled across the WCPO, suggesting restricted movement of individuals and a degree of regional residency, at least over the scale oftheir muscle nitrogen turnover rate (i.e., half-life = 167 days). Spatial
variation in Hg concentrations of bigeye tuna muscle have also been
documented, with Houssard et al. (2019) observing enriched sizestandardised Hg concentrations in fish caught in southern latitudes(>15 °S) relative to those caught from the equator, and comparably
higher (size-standardised) Hg concentrations in fish caught off Tonga
and Fiji than those caught at comparable latitudes in French Polynesia.
The most recent stock assessment for bigeye tuna in the WCPO estimated some north-south exchange between equatorial regions and theNorth Pacific Ocean, as well as movement of recruits from west to eastin the North Pacific (Fig. 4). The same general trend that occurs foryellowfin tuna is otherwise predicted, i.e., mixing throughout theequatorial regions but with higher retention of recruits in the westernmost tropical region. Bigeye tuna in the southernmost assessment
regions were estimated to result mostly from self-recruitment, with asmall proportion of recruits predicted to move from west to east (Fig. 4)(McKechnie et al., 2017a).
Applications of SEAPODYM estimate an optimum mean spawningtemperature of 26.8 °C for bigeye tuna, resulting in peak larval distributions between 26° to 28 °C (Lehodey et al., 2018). As a result,model outputs predict a large spawning area in the central equatorial
region, with juvenile bigeye tuna concentrated mainly in the wider
tropical CPO, and adults extending from this zone into more temperate
latitudes following the Kuroshio Current Extension to the north andEast Australian Current to the south. Bigeye tuna movement parameters
appear to have varied considerably across parameter optimisations(Lehodey et al., 2018; Senina et al., 2018), suggesting very low tomoderate diffusion in response to habitat quality, potentially affecting
mixing.
2.3.4. Synthesis of available information on bigeye tuna stock structure
The stock structure of bigeye tuna in the Pacific Ocean remains
unresolved. Genetic studies for the most part have provided little evidence of significant structuring between the EPO and WCPO, with only
Grewe and Hampton (1998) indicating potential restricted gene flow
between the far WPO and far EPO. However, genetic studies conductedto date have been limited by sampling design effects, including limited
sample sizes, and a comprehensive assessment using NGS approaches
across the Pacific Ocean has yet to be conducted. Finer-scale structuring
is similarly unclear. Observations from tagging studies suggest a degreeof regional fidelity in both the EPO and WCPO, some extensive eastward longitudinal dispersion (particularly in the WPO and CPO), constrained latitudinal movement and the likely occurrence of spatial
structuring of bigeye tuna stocks between the EPO, CPO and WPO (e.g.,
Schaefer et al., 2015). However tagging studies conducted to date havebeen limited by relatively low numbers of recaptures, time at liberty of
individuals, varying tag reporting rates, and uncertainties around the
population representativeness of tagged individuals (see Section 3),
precluding resolution of stock boundaries. Observations of regional
differences in growth and reproductive biology (Farley et al., 2017,2018b) support the differentiation of fish from the EPO and WCPO, andfiner-scale patterns, where available, are consistent with the occurrenceof regional fidelity. Available otolith chemistry data (Rooker et al.,2016) appear to contrast with the observation of constrained latitudinal
dispersion of bigeye tuna within central equatorial waters evident fromtagging data, potentially indicating that the dispersal evident fromotolith chemistry may have occurred when fish were at younger ages
than those of tagged individuals. Structured sampling programmes are
required to test this hypothesis. More broadly, information on otolithchemistry (e.g., Rooker et al., 2016; Proctor et al., 2019) and parasiteassemblages (e.g., Moore et al., 2019) suggest bigeye tuna do not mix
uniformly, but as with those conducted on yellowfin tuna, these studies
are life-stage specific, and have been limited by a lack of spatial andtemporal diversity. As such, the spatial resolution of bigeye tuna stocks
across the Pacific Ocean is poorly understood, and warrants further
investigation.
As with yellowfin tuna, the largely continuous distribution of bigeye
tuna in tropical waters of the EPO and WCPO evident from fishery data
(IATTC, 2018), and observations of individuals undertaking large-scale
movement from tagging studies (e.g., Hampton and Gunn, 1998;
Schaefer et al., 2015; SPC-OFP, 2015, 2017; Fig. 4), indicate that theoccurrence of multiple, fully discrete, closed populations of bigeye tunain the Pacific Ocean is unlikely, at least without some additional
structuring mechanism, such as fish returning to specific spawningareas (see Section 3). Although there is no direct evidence of fidelity tospawning areas in bigeye tuna, the hypothesis of Gunn et al. (2005),
who proposed that the small numbers of cyclical movements observedin bigeye tuna in the northwest Coral Sea may be linked in part tomovements from spawning sites and into more dispersed areas of theCoral Sea and WPO at the completion of spawning, is consistent with
spawning area fidelity, at least for a proportion of the population.
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Similar cyclical movements have also been observed in an individual
bigeye tuna tagged in the EPO (Schaefer and Fuller, 2010). Alternatively, limited movements may result in stock structure via isolation
by distance, particularly if individuals reproduce with their nearest
neighbours. The observed cline in genetic structure in bigeye tunaacross sampling locations spanning the Indian Ocean and far WPO by
Proctor et al. (2019) is consistent with an isolation by distance hypothesis, although additional studies are required to assess whether thispattern is demonstrated by the species more broadly across its Pacific
Ocean distribution. The similarity of these results with those of yellowfin tuna suggest a common underlying biogeographic mechanismthat restricts genetic connectivity at ocean basin scales. The observationof Schaefer et al. (2015) that the greatest amount of mixing of tagged
bigeye tuna occurs between adjacent areas is also broadly consistent
with an isolation by distance model. Further sampling is required to test
these various hypotheses.
2.4. South Pacific albacore tuna
2.4.1. Relevant biology and spatial considerations in stock assessment
approaches
Albacore tuna are widely distributed in the Pacific Ocean between
approximately 50 °N and 40 °S, although fisheries catch and tagging
data suggest limited occurrence in equatorial waters between 5 °N and
5 °S (Lewis, 1990; Williams et al., 2012; Nikolic et al., 2017). Historically, two stocks have been recognised in the Pacific: a North Pacific
Ocean stock and a South Pacific Ocean stock. However, several recent
genetic studies report apparent homogeneity of fish caught in thenorthern and southern hemispheres (e.g., Montes et al., 2012; Albaina
et al., 2013), casting some doubt on the existence of separate stocks.
In contrast to skipjack, yellowfin and bigeye tunas, South Pacificalbacore tuna have a relatively discrete spawning season, with
spawning occurring in tropical and sub-tropical waters exceeding 24 °C
between 10 °S and 25 °S between September and May, with a peak
between October and December (Ramon and Bailey, 1996; Farley et al.,2013). Juveniles are thought to move south from their spawning
grounds into surface waters around New Zealand and in the vicinity ofthe subtropical convergence zone in the central Pacific, where they arecaught by longline and troll-fisheries at around one year old. As theyage, South Pacific albacore tuna gradually disperse into lower latitudes
north of 30 °S (Langley, 2004, 2006; Langley and Hampton, 2005),
where they are primarily caught by longline fleets. Longline catch data
indicate that adult South Pacific albacore tuna may migrate seasonally
between tropical and subtropical waters, moving south during earlysummer, and north during winter, coincident with the seasonal shift in
the 20–28 °C sea surface temperature isotherm (Langley, 2004, 2006;
Langley and Hampton, 2005). Spatial variability in maturity at age andmuscle fatty acid composition support the latitudinal separation of age
groups evident from the size distribution of fisheries catches (Farley
et al., 2014; Parrish et al., 2015).
Although South Pacific-wide assessments for the species have been
performed historically, the most recent stock assessment for South
Pacific albacore tuna incorporated a 5-region structure in the area from
50 °S to the equator between 140 °E and 150 °W, and from 50 °S to 5 °S
between 150 °W and 130 °W (Fig. 5) (Tremblay-Boyer et al., 2018). Thisregion corresponds closely to the WCPFC Convention Area south of theequator. The eastern Pacific component of the stock has not been included in recent assessments, due to low catches and poor data quality,
although increasing catches in this region have resulted in requests for a
Pacific-wide assessment of the species (Pilling and Brouwer, 2018).
Spatial structuring of the assessment model used in the WCPO hasvaried through time with the structure informed by biological hypotheses of seasonal movement, spatial structuring of the population byage, and patterns of fishing activity. The distribution of recruitment wasconstrained to the southernmost regions in the most recent assessment
based on the distribution of newly-recruited fish in the catch,

Fig. 5. Top: The geographic area and regional structure used in the recent stock
assessment for South Pacific albacore tuna in the Western and Central Pacific
Ocean (WCPO; numbered areas) by Tremblay-Boyer et al. (2018); middle:
movements of tagged albacore tuna tagged during the Regional Tuna Tagging
Programme (RTTP; red arrows) and the South Pacific Albacore Tagging Programme (SPATP; blue arrows); bottom: distribution of observed tag displacements for albacore tuna at liberty for ≥ 3 months from RTTP and SPATP data.
All tagging data shown are based on SPC holdings. Note predictions of total
biomass distributions are not available from the assessment model (see text).
Albacore tuna image: Les Hata, © SPC. (For interpretation of the references tocolour in this figure legend, the reader is referred to the web version of thisarticle).

precluding model predictions on regional sources of recruitment toadult biomass (Tremblay-Boyer et al., 2018).
2.4.2. Genetic studies
Few studies have used molecular approaches to examine the presence of population structuring within South Pacific albacore tuna.
Differences in DNA microsatellites have been reported between albacore tuna in the WPO (Australia) and EPO (Chile and Peru) (Takagi
et al., 2001), and the WPO (between New Caledonia and Vanuatu) andCPO (French Polynesia) (Montes et al., 2012). In contrast, Davies et al.
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(2011) found no differentiation of microsatellites between samples
from New Caledonia and French Polynesia. Analyses using SNPs havealso yielded potentially contrasting results. Laconcha et al. (2015)
found little evidence to indicate differentiation in SNPs between samples from New Caledonia and French Polynesia, or between these locations and the North Pacific Ocean. Anderson et al. (2019b) found noevidence to support the presence of genetic variability in South Pacificalbacore tuna from four sampling areas in the WPO and CPO (French
Polynesia, New Caledonia, New Zealand and Tonga) at neutral SNP
loci. They reported observations of greater potential structure at
adaptive SNP loci, with samples from French Polynesia differentiatedfrom those sampled at locations to the west. The authors advise caution
in the interpretation of their results, noting that it is unclear to what
extent spatial or temporal differences in sampling strategies might havecontributed to their observations. Preliminary analyses of SNPs fromsamples collected from finer geographic scales within the WCPO has notbeen able to confirm the presence of more than one genetic populationfrom albacore tuna collected off Australia, New Caledonia and New
Zealand (Evans et al., 2019).

origins were not identified, these results demonstrate the potential forsome degree of spatial structuring of spawning populations of albacore
tuna within the South Pacific (Macdonald et al., 2013).
Spatial patterns in Hg concentrations of albacore tuna muscle havealso been reported. Houssard et al. (2019) observed enriched sizestandardised Hg concentrations in fish caught in southern latitudes(∼15 °S–25 °S) relative to those caught north of 15 °S. However, theseresults were limited by the restricted size range of fish sampled and thenarrow latitudinal band the samples were collected from, precluding
conclusions as to whether the observed patterns were a result of fish
size or location.
Applications of SEAPODYM estimate an optimal spawning SST for
South Pacific albacore tuna of 28 °C, with the northward spawningmigration peaking in early May (Senina et al., 2018). Optimal temperatures for foraging habitats for the species were estimated as ranging
from 11.8–23.5 °C. Little evidence on connectivity and stock structure
per se is available from SEAPODYM, with the model estimating broadscale movement of albacore tuna corresponding with seasonal shifts ofthe 23° to 28 °C SST isotherm location (Senina et al., 2018).
Fishery data indicate that catch rates tend to be lower in EEZs of
those PICTs where fishing effort is highest, and higher in the EEZs of
PICTS where fishing effort has been lower (Brouwer et al., 2019),
suggesting the possible occurrence of regional fidelity of adults.

2.4.3. Non-genetic studies
Albacore tuna are more challenging to tag than skipjack, yellowfin
and bigeye tunas, largely because many of the fish do not survive thelongline capture process (the predominant method by which they arecaught). As a result, comparatively few conventionally-tagged albacore
tuna have been released in the Pacific Ocean. Nevertheless, some tagging of South Pacific albacore tuna has been undertaken to inform stock
assessments for this species with respect to growth, movement, andmortality, with tagging operations having been conducted primarily
south of 35 °S, and predominantly on juveniles. Although recaptures
have been low (∼1 % of tagged fish), the information derived supports
connectivity of fish between high and low latitudes, and highlights thepotential for individual fish to undertake long-range latitudinal andlongitudinal dispersion, with some individuals being recaptured several
thousands of kilometres from their release sites (Fig. 5) (Labelle andHampton, 2003; SPC-OFP, 2017, 2018b). There have been 19 pop-up
satellite archival tags deployed on South Pacific albacore tuna, in thewaters of New Caledonia, New Zealand and Tonga (Williams et al.,2015). Although the durations of these tag deployments were limited(≤ 50 days), displacements varied between release sites. Fish tagged in
New Zealand waters moved greater distances than those tagged in New
Caledonia and Tonga (Williams et al., 2015).
Spatial variability in growth has been reported within South Pacificalbacore tuna, with both females and males reaching greater length-atage at easterly than at westerly longitudes (Williams et al., 2012).
Longitudinal differences have also been observed in gonad development, with mature albacore tuna in the east having heavier gonads inrelation to their length than those in the west (Farley et al., 2013).
Together, these results suggest some structuring of individuals at broad
spatial scales within the WCPO.
Jones (1991) examined parasite assemblages of albacore tuna acrossthe south-western Pacific. Based on the abundances of 10 species ofdidymozoid, he concluded that fish moved south from the tropics to
New Zealand and then returned north to spawn with the onset of sexual
maturity, a result that is consistent with tagging and fishery catch data.
In addition, there was evidence to suggest that fish were also moving
longitudinally along the subtropical convergence zone.
Examination of the otolith chemistry of South Pacific albacore tunahas been limited to one study by Macdonald et al. (2013). They investigated chemical signatures at the natal region of otoliths from fish
(80–95 cm FL) captured around New Caledonia, New Zealand andFrench Polynesia. Albacore tuna caught off New Caledonia and New
Zealand had similar chemical signatures, suggesting that they originated from areas of similar water chemistry. In contrast, those from
French Polynesia were significantly different, suggesting they had originated from a separate larval source. Although the locations of larval

2.4.4. Synthesis of available information on South Pacific albacore tunastock structure
The most recent stock assessment for South Pacific albacore tuna
(Tremblay-Boyer et al., 2018) assumes the boundary of the stock extends from the east coast of Australia to 130 °W. This model structure
assumes that South Pacific albacore tuna east of 130 °W are a separate
stock. However, it is not clear whether the boundaries of the model
domain reflect the underlying population structure of South Pacificalbacore tuna. Microsatellite DNA analyses (Takagi et al., 2001) support
the separation of fish from the southwest and southeast Pacific, although the boundary between these putative stocks, and number of
additional stocks between these widely-spaced areas, is unknown.
Within the assessment area, DNA microsatellites (Montes et al., 2012)
appear to contrast the current single stock paradigm, suggesting thepossible occurrence of at least two genetic stocks. These results arepotentially supported by separate analyses of adaptive SNP loci(Anderson et al., 2019b). Biological (Williams et al., 2012; Farley et al.,2013) and otolith chemistry (Macdonald et al., 2013) data further
support these findings, with those individuals caught in the far easternregions of the stock assessment area demonstrating biological characteristics and otolith core chemistries that vary from those in thewestern regions of the assessment area. However, such studies havebeen limited by a general lack of spatial and temporal resolution andstructured sampling. Recoveries of tagged fish indicate the potential for
individuals to undertake long-range latitudinal and longitudinal dispersion, potentially resulting in stock mixing. The majority of tagging,
however, has been conducted on individuals south of ∼35 °S, and thus
predominantly on juveniles. Further sampling is required to quantify
the actual number of stocks present and their geographic boundaries,
both within and beyond the current spatial domain used for stock assessment.
The latitudinal ontogenetic movement of South Pacific albacoretuna, coupled with more limited longitudinal dispersal of adults, may
facilitate the maintenance of regionally resident groups of adults in theSouth Pacific Ocean, with genetic linkages potentially maintained atvarying spatial scales by larval dispersal and/or longitudinal movements of juveniles along the subtropical convergence zone. The observed longitudinal differences biological and fishery catch rate data
are consistent with expectations from regional residency of adults.
Alternatively, limited longitudinal movements may result in an isolation by distance structure, particularly if individuals reproduce with
their nearest neighbours, or tend towards a metapopulation structure
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should larvae and/or juveniles disperse and mix among largely resident
adult populations. There is currently limited evidence to support orrefute either of these two scenarios. Broad-scale spawning area fidelity
appears unlikely for South Pacific albacore tuna, as there is no evidenceof specific spawning areas for the species, although individual fish may
return to specific spawning sites. Further studies are warranted to explore these various hypotheses.

extent of spawning units. For each of the four tunas reviewed here,
spawning is considered to take place in waters > 24 °C which, ifwater temperature alone is used to predict spawning location, would
result in spawning occurring across large regions of the Pacific
Ocean where and whenever temperatures are suitable. Several authors posit that actual spawning areas, however, may be more
spatially and temporally variable than predicted by water temperature alone (Reglero et al., 2014; Muhling et al., 2017). A
number of temporally-consistent spawning ‘hot spots’ have been
observed for yellowfin and bigeye tunas (e.g., McPherson, 1988,
1991; Gunn et al., 2002; Servidad-Bacordo et al., 2012), supporting
this theory. A comprehensive assessment of spawning activity, including both spatial patterns and associated timing of spawning(particularly identifying temporal overlaps or offsets between locations), examined in conjunction with known information on mesoscale oceanographic features such as eddies, currents and upwellings, would provide a key first-step in better understanding the
spatio-temporal structuring of the spawning dynamics of each species. Examination of a range of data sources, including larval distributions from scientific surveys, the stomach contents of predatorsof larval tuna, large catches by set in longline fisheries (that target
older and larger fish, and thus may indicate spawning activity),
records of visibly spawning (i.e., running ripe) fish from fisheries
observers, histological examination of previously collected gonadmaterial and multi-year movement data from reproductively matureindividuals, should help further resolve spatial and temporal dynamics in spawning of the four tunas.
2. The degree of spawning area fidelity and localised residency. For each of
the four tunas covered here, it is currently unknown whether individuals i) spawn in different areas over the course of their life
where and whenever conditions are suitable, or ii) spawn in thesame general area throughout their life. If the latter, it is unknown
whether they remain in close proximity to specific spawning areas
or disperse widely after spawning and then return to the same area
to spawn and, if they do, whether these movements represent fish
returning to their natal spawning areas (i.e., natal homing). Because
most tuna tagging studies in the Pacific Ocean have focused on juveniles using conventional tags, understanding of adult movement
and the degree of spawning area fidelity is limited. Although someefforts have been made to examine movement of adults via electronic tagging approaches (Schaefer et al., 2007; Evans et al., 2011;
Schaefer et al., 2011), existing data are largely inadequate for assessing potential spawning area fidelity. Studies assessing a combination of genetic and environmentally/physiologically-mediatedattributes (e.g., otolith chemistry) of fish in spawning condition
between different spatial strata may provide a suitable starting point
for determining the degree of spawning area fidelity, and overall
structure of stocks, of the four tunas. Modern genetic approaches,such as the use of NGS approaches and the identification of SNPs,
have demonstrated a promising avenue for future research in thisarea (Casey et al., 2016; Pecoraro et al., 2017; Rodríguez-Ezpeleta
et al., 2019). This approach offers numerous advantages over
mtDNA and microsatellite-based approaches in stock structure studies, including the potential for higher genotyping efficiency,
greater data quality and reliability, genome-wide coverage andanalytical simplicity (Morin et al., 2004; Corander et al., 2013). The
advent of NGS approaches provides a better representation of the
genome and the identification of loci that are potentially under selection (so-called outlier loci), increasing the power to discriminate
between weakly differentiated populations by disentangling between neutral evolutionary processes (i.e., genetic drift) and those
influenced by selection (e.g., local adaptation) (Grewe et al., 2015;
Pecoraro et al., 2017; Anderson et al., 2019c). However, a carefully
designed sampling strategy that provides for representative sampling and includes spatial and temporal replication is needed to
avoid introducing bias into such studies, such as those associated

3. Main uncertainties and future directions to understanding thestock structures of skipjack, yellowfin, bigeye and South Pacificalbacore tunas in the Pacific Ocean
Recent studies across the Pacific Ocean have resulted in increased
knowledge of the spatial dynamics of the four tuna species reviewed
here. They identify the potential for varying degrees of spatial structuring of stocks, rather than panmixia, for each species. However, fromavailable data, it is currently not possible to define the stock structureof any of the four tuna species at scales relevant to regional management. This is because most studies have typically been constrained byeffects of scale (both spatial and temporal), sampling design, limitations
in resolution of the techniques, availability of samples or data and,potentially, the behaviour of the tuna species themselves. For example,
although a large amount of tagging data exists, particularly for skipjack
and yellowfin tunas, most tagging studies have focused on juvenile fish
tagged with conventional tags, and have been spatially limited, withreleases conducted mainly in areas of high abundance and concentrated
fishing effort. This is partly because these studies were not designed
solely to provide information on stock structure, but to assess a range ofparameters for use in stock assessments, including movement andmixing, estimations of growth rates, natural and fishing mortality, andabundance (Leroy et al., 2015). Furthermore, inferences of stock
structure based on movement and mixing from conventional tagging
studies are inherently limited by the point-to-point nature of the resulting data, with no information on the movement of fish between
release and recovery, as well as the number of recaptures (particularly
for South Pacific albacore tuna), time of individuals at liberty, thedistribution of tagging and recapture effort, varying tag reporting rates,
and uncertainties around the population representativeness of taggedindividuals (Hunter et al., 1986; Leroy et al., 2015; Evans et al., 2016).
Genetic studies conducted to date have largely proven inconclusive
in resolving the stock structure of the four tuna species. Historically,
most genetic studies on Pacific tuna populations have used a small
number of markers distributed in a limited portion of the genome(Appleyard et al., 2001), that are extremely sensitive to the movementof small numbers of individuals between populations (Slatkin, 1987), orthat show low levels of genetic differentiation resulting from large
population sizes and high fecundity (Palumbi, 2003; Ely et al., 2005),
such as estimated for skipjack, yellowfin, bigeye and South Pacific albacore tunas. Elsewhere, studies have been limited by sampling designand logistical issues, including sample size limitations; opportunistic
sampling of fish on fishing grounds, which may include a mix of several
stocks, to identify discrete reproductive units; a lack of structured
sampling; or by widely-separated sampling locations (Richardson,
1983; Grewe and Hampton, 1998; Grewe et al., 2015; Pecoraro et al.,2018; Anderson et al., 2019a, b). Studies employing biochemical analyses (e.g., otolith or muscle chemistry), parasites, morphometrics andmeristics have yielded informative results but have been limited by thespatial and temporal scales over which such studies have operated and/or a lack of structured sampling.
Based on the review of information currently available for the
species conducted here, several main uncertainties associated with
understanding of stock structure can be identified:
1. Spawning dynamics. An important part of understanding the natal
origins of individuals is a detailed knowledge of the location andtiming of spawning, and ultimately the number and geographical15

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B.R. Moore, et al.

with the sampling of multiple spawning units at the same locationand time. Increased deployment of electronic tags, particularly on
adults in running ripe condition, may further elucidate the degree of
spawning area fidelity within the four species, and help resolve
patterns in spawning activity observed through other methods.
3. The provenance of individuals in, and proportional contributions of selfreplenishing populations to, fishery catches within the Pacific Ocean. A
key challenge for management of tuna fisheries in the Pacific isunderstanding the proportion each potential self-replenishing population, or stock, contributes to harvested assemblages. This isparticularly important given that i) fishing mortality is unevenly
distributed across the region, ii) there is the potential for fisheries to
exploit individuals from several stocks, if present, more-or-less simultaneously, iii) different stocks, if present, may have differinglevels of productivity, and iv) there is potential for local depletion,
particularly for less productive stocks, if they are structured in sucha way that they are subject to higher fishing mortality. Althoughsome studies have explored provenance and mixing across small
spatial scales (Gunn et al., 2002; Wells et al., 2012; Rooker et al.,2016), expanding this work to scales relevant for regional fisheries
management has yet to be undertaken. To do this effectively, coordinated and intensive systematic sampling efforts will be required,including extensive spatial and temporal components. Mixed stock
analyses, incorporating complementary approaches such as examination of SNPs, otolith chemistry, and parasite assemblages,
provide one potential approach for testing specific hypotheses about
natal origins, movement and mixing of post-larval assemblages andthe proportional contributions of source populations to fisheries.
Mixed stock analyses have been used to clarify stock or population
structure in a range of highly mobile species where adult assemblages may represent a mixture of individuals from different origins,
including Pacific bluefin tuna (Shiao et al., 2010) and, at restrictedspatial and temporal scales, for yellowfin, bigeye and South Pacificalbacore tunas (Wells et al., 2012; Macdonald et al., 2013; Rooker
et al., 2016).
4. Linkages with adjacent ‘stocks’. Historically, the South Pacific albacore tuna population was considered to be distinct from individuals
in the North Pacific Ocean. However, recent evidence suggests thatsome gene flow may occur between these regions (Montes et al.,2012; Albaina et al., 2013; Laconcha et al., 2015). Similarly, linkages between the South Pacific albacore tuna stock assessed in the
WCPO and individuals to the east are unknown. For bigeye tuna,differences between some components of adjacent stocks, such asindividuals in the eastern Indian Ocean and those in Indonesian
waters, in the far WPO, appear to be less clear-cut than previously
thought (Proctor et al., 2019). Inclusion of samples from outlier
areas in any sampling program is required to adequately assess stock
relationships beyond currently accepted boundaries for the stocks.
Inclusion of samples from adjacent stocks may further facilitate thedevelopment of an origin traceability tool that may enable the development of population-specific quotas (Rodríguez-Ezpeleta et al.,2019) and help curb illegal, unregulated and unreported (IUU)
fishing.
5. Effects of climate change on stock structure and proportional contributions of self-replenishing populations to fisheries. Recent projections
using SEAPODYM suggest that under climate change, shifts in the
distribution of skipjack and yellowfin tunas at the basin scale arelikely to occur (Senina et al., 2016, 2018). Current modelling approaches, however, are based on assumptions of single rather thanmultiple stocks for each species of tuna. Understanding how the
introduction of spatial structure into the parameterisation of models
used to investigate the responses of tuna populations to climatechange might influence overall projections for population distributions is contingent on obtaining a better understanding of the uncertainties described above.
6. Implications of improved knowledge of tuna stock structure for stock

assessment and climate change model assumptions and fisheries management. The spatial scale and structure of Pacific tuna stock assessments have been based on tRFMO management boundaries, thenature of the fishing fleets exploiting each species, and the parameterisation of inputs required to achieve a robust model. Prior toundertaking sampling programs and analyses to determine the stock
structure of tuna species, it would be prudent to simulate the extent
to which different hypothetical stock structures might affect current
stock assessments approaches and the associated management
measures. The WCPFC is currently in the process of developing
management procedures for the main tuna species that will allow for
pre-agreed decisions for management action to be tested for robustness to plausible hypotheses of environmentally-driven movement (WCPFC, 2014; Scott et al., 2019a, 2019b), and a similar approach could be used to test robustness to different stock structure
scenarios. The process can also examine the value of new information in terms of its potential to improve decision making, thereby
providing further support for undertaking research activities. Similarly, models such as SEAPODYM could be used to examine theresponses of multiple putative stocks of skipjack and yellowfin
tunas, for example, to compare the composite redistribution of tuna
biomass from these stocks due to climate change with projected
redistribution of biomass from modelling a single, panmictic stock.
4. Conclusions
Although current assessments of skipjack, yellowfin, bigeye andSouth Pacific albacore tunas within each of the WPCFC and IATTC
Convention Areas typically assume that each species forms a single
stock, several lines of evidence reviewed here identify the potential
occurrence of multiple stocks of each species within the Pacific Ocean
basin at varying spatial scales. To better define the stock structures ofPacific tunas, and the underlying mechanisms by which spatial structuring occurs, uncertainty needs to be reduced in understanding of
spawning dynamics (including any potential fidelity to particularspawning areas), origins and mixing of post-juvenile assemblages, andthe proportional contributions of spawning units to mixed fisheries
assemblages. More powerful and cost effective genetic and genomic
tools, in particular NGS approaches and modern molecular markers
such as SNPs, combined with complementary approaches based on
otolith chemistry and parasites and well-designed electronic tagging
experiments, provide a promising way forward for testing specific hypotheses regarding uncertainties around the presence of self-replenishing populations and their contributions to harvested assemblages. It is recommended that management strategy simulations andclimate modelling, based on various hypothetical scenarios of stock
structure, be thoroughly evaluated for each species to determine how
an improved understanding of stock structure would influence themanagement of tuna stocks and implementation of adaptations to reduce the impacts of climate-driven redistribution of tuna species on
island economies.
Acknowledgments
We thank participants at the ‘Identifying the spatial structure ofPacific tuna stocks’ workshop held in Nouméa, 8–12 October 2018, inparticular Tim Adams, Valerie Allain, Mark Bigler, Don Bromhead,
Sangaa Clark, Campbell Davies, Ueta Faasili Jr., Mark Fitchett, John
Hyde, Bruno Leroy, Antony Lewis, Anne Lorrain, Janice Natasha, Pablo
Obregon, Thomas Peatman, Carlo Pecoraro, Naiten Bradley Phillip Jr.,Ciro Rico, Caroline Sanchez, Brian Stockwell and Thomas Usu, forconstructive discussions that greatly sharpened this paper. Sylvain
Caillot, Bruno Leroy and Thomas Peatman provided the tagging data.
Peter Horn, two anonymous reviewers and the Guest Editor provided
useful comments on an earlier draft of the manuscript. Development of
this review was supported by Conservation International as part of the16Fisheries Research xxx (xxxx) xxxx

B.R. Moore, et al.

GEF-funded, World Bank-implemented Ocean Partnerships for sustainable fisheries and biodiversity conservation (OPP), a sub-project of theCommon Oceans ABNJ Program led by UN-FAO, as well as the respective research agencies of the authors.

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