Vertical behavior and diet of albacore tuna (Thunnus alalunga) vary with latitude in the South Pacific Ocean

Vertical behavior and diet of albacore tuna (Thunnus alalunga)vary with latitude in the South Pacific Ocean

Ashley J. Williams a,n, Valerie Allain a, Simon J. Nicol a, Karen J. Evans b, Simon D. Hoyle a,1,Cyndie Dupoux a, Elodie Vourey a, Jeff Dubosc a

a Oceanic Fisheries Programme, Secretariat of the Pacific Community, BP D5, 98848 Noumea, New Caledoniab Wealth from Oceans Flagship, CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania, Australia

a r t i c l e i n f o

Keywords:South Pacific albacoreMovementVertical behaviorDietTuna fisheries

a b s t r a c t

Albacore tuna (Thunnus alalunga) are an important upper tropic-level oceanic predator with a circum-global distribution. Little is known of the movements and diet of albacore tuna in the South Pacific Oceanand how variability in both might influence the vulnerability of albacore tuna to fisheries across theirrange. We coupled data derived from satellite-tagged albacore tuna with stomach samples collectedfrom individuals at the same locations to characterize the vertical behavior, thermal and dietary habits ofalbacore tuna at tropical (New Caledonia and Tonga) and temperate (New Zealand) latitudes. A total of18 pop-up satellite archival tags deployed on albacore tuna remained attached for 0–50 days. Positionestimates, calculated from 11 tags, described short-term movements of predominantly less than 500 km,although one fish moved more than 1000 km over a period of 50 days. Vertical behavior and diet differedsubstantially between tropical and temperate latitudes. At tropical latitudes, albacore tuna showed adistinct diel pattern in vertical habitat use, occupying shallower, warmer waters above the mixed layerdepth (MLD) at night, and deeper, cooler waters below the MLD during the day. In contrast, there waslittle evidence of a diel pattern of vertical behavior in albacore tuna at temperate latitudes, with fishlimited to shallow waters above the MLD almost all of the time. Spatial patterns of species compositionin stomach contents were consistent with vertical movement patterns, with significantly more deep-water prey species consumed in tropical waters than in temperate waters. Albacore in tropical watersalso consumed significantly greater diversities of prey than in temperate waters, predominately preyingon fish species, whereas those in temperate waters predominately preyed on crustacea. Our resultsindicate that the vertical distribution of albacore is constrained either by thermal preferences with dietreflecting these preferences, by the vertical distribution of prey species, which may be affected by thethermal structure of the ocean, or most likely by a mixture of both. Spatial differences in the verticaldistribution of albacore tuna suggest that vulnerability of albacore to oceanic fisheries varies withlatitude. Changes in the thermal structure of oceanic waters in temperate areas associated with climatechange might influence the vertical distributions and, therefore, vulnerability of albacore to oceanicfisheries into the future.

& 2014 Elsevier Ltd. All rights reserved.

1. Introduction

Albacore tuna (Thunnus alalunga) are an important uppertropic-level oceanic predator with a circum-global distributionbetween approximately 501N and 401S, although their abundance

is relatively low in equatorial areas (Collette and Nauen, 1983).They are a commercially important species, contributing 6% to theannual global tuna catch of 4.3 million t in 2010 (FAO, 2012). Mostof the world's catch of albacore tuna (54%) is taken from longlinefisheries in the Pacific Ocean, with historically higher catches fromthe North Pacific than from the South Pacific. During the lastdecade, longline fisheries in South Pacific have expanded con-siderably, with catches of albacore tuna increasing from 34,328 t in1996 to 89,021 t in 2010 (Oceanic Fisheries Programme, 2012).Concurrently, longline catch rates for albacore tuna have declinedin the domestic fisheries of some Pacific Island Countries andTerritories (PICTs), which has raised concerns about the economic

Contents lists available at ScienceDirect

journal homepage: www.elsevier.com/locate/dsr2

Deep-Sea Research II

http://dx.doi.org/10.1016/j.dsr2.2014.03.0100967-0645/& 2014 Elsevier Ltd. All rights reserved.

n Corresponding author. Tel.: þ687 262000.E-mail addresses: [email protected] (A.J. Williams), [email protected] (V. Allain),

[email protected] (S.J. Nicol), [email protected] (K.J. Evans),[email protected] (S.D. Hoyle), [email protected] (C. Dupoux),[email protected] (E. Vourey), [email protected] (J. Dubosc).

1 Present address: 20 Bisley Ave, Nelson 7011, New Zealand.

Please cite this article as: Williams, A.J., et al., Vertical behavior and diet of albacore tuna (Thunnus alalunga) vary with latitude in theSouth Pacific Ocean. Deep-Sea Res. II (2014), http://dx.doi.org/10.1016/j.dsr2.2014.03.010i

Deep-Sea Research II ∎ (∎∎∎∎) ∎∎∎–∎∎∎

www.sciencedirect.com/science/journal/09670645

www.elsevier.com/locate/dsr2

http://dx.doi.org/10.1016/j.dsr2.2014.03.010



mailto:[email protected]












sustainability of these fisheries (Langley, 2006). Decline in avail-able biomass due to increased fishing pressure (Hoyle et al., 2012),localized depletion due to concentrated fishing effort in someareas (Langley, 2006) and reduced availability of albacore tuna tolongline fishing gear due to inter-annual variations in prey densityand oceanographic conditions (Bertrand et al., 2002; Briand et al.,2011; Domokos et al., 2007; Domokos, 2009; Yamanaka, 1956) areconsidered likely explanations for the declining catch rates.

In order to better understand the drivers behind variability incatches of albacore tuna and links with prey densities andoceanographic conditions, there is a need to determine both thediet and movement patterns of albacore tuna. Linking horizontaland vertical behavior with dietary habits of albacore tuna is alsoessential to better understand how populations might respond tofuture changes in their environment and prey distribution. Distinctseasonal migratory patterns and a broad range of vertical divingbehavior have been observed in albacore tuna in the North PacificOcean (Childers et al., 2011) and in the North Atlantic Ocean(Cosgrove et al., 2014). Despite attempts to collect similar informa-tion on the movements and behavior of albacore tuna in the SouthPacific Ocean, tag deployments on albacore to date have hadlimited success (Domokos et al., 2007).

The vulnerability of albacore tuna to fisheries is a functionof inter alia physiological tolerance, behavioral patterns, oceano-graphic conditions and the effectiveness of the fishing gear.Longline fisheries in the Pacific Ocean capture albacore tunayear-round, although there are strong seasonal trends in catchdistributions, with fisheries operating in southern latitudes (southof 351S) during late summer and autumn, and moving northwardsduring winter (Hoyle et al., 2012). Configurations of longlinefishing gear used vary depending on the vessel, target speciesand location. Vessels that target albacore tuna at lower latitudestypically set their longlines at depths between 100 and 400 m(Bigelow et al., 2006), while those at higher latitudes typically settheirs at shallower depths of o100 m. Troll fisheries in the PacificOcean operate south of 351S, in coastal waters of New Zealand andin the central Pacific in the region of the sub-tropical convergence

zone (Hoyle et al., 2012). Troll fisheries target albacore tuna fromDecember to April and capture fish near the surface at depths ofo10 m. Here, we integrate temperature and depth data derivedfrom satellite pop-up archival tags with the stomach contents ofalbacore tuna from tropical and temperate regions of the SouthPacific Ocean to investigate potential linkages between move-ments and prey assemblages. We then discuss relationshipsbetween movements and diet in light of vulnerability to fisheriesthroughout the region and how these might vary as oceanographicconditions change into the future.

2. Methods

2.1. Tagging data

We chose to collect data on albacore tuna behavior usingpop-up satellite archival tags (mini-PATs, Wildlife Computers,Redmond, USA) rather than internal archival tags because recoveryrates of tagged albacore tuna in the South Pacific are remarkablylow (1.4%; Langley and Hampton, 2005) compared to other tunaspecies. Use of mini-PATs allow for the collection of data on themovements and thermal habitats of individuals without the needfor return of the tag, thereby avoiding the need for large number ofdeployments to achieve tag returns under low recovery rates.Between March and July 2010, 19 mini-PATs were deployed onSouth Pacific albacore tuna, of 90–107 cm fork length (FL), duringmultiple tagging cruises in waters near New Caledonia (n¼10),Tonga (n¼4) and New Zealand (n¼5) using a chartered domesticcommercial longline vessel (Table 1). Albacore tuna that were ingood condition (lively with minimal or no injuries) and >90 cm FLwere brought to the side of the vessel and lifted on board with apurpose-built sling. Once on board, the FL of the fish wasmeasured to the nearest cm (rounded down). A deck hose with alight flow of seawater was placed in the mouth of the fish tooxygenate the gills, and a moist chamois placed over the eye tocalm the fish. To attach the mini-PAT to the fish, a 38�9 mm

Table 1Release and pop-up information for pop-up satellite archival tags deployed on albacore tuna in three locations in the southwestern Pacific Ocean. Date of pop-up is daterecorded by tag and may be up to two days later than when the tag was released from the fish. TAL: time at liberty.

Tag Releases Pop-up transmissions

Date Latitude (1S) Longitude (1E) FL (cm) Date Latitude (1S) Longitude (1E) TAL

New Caledonia09P0275 27 Jun 2010 20.02 161.80 100 14 Jun 2011 20.98 162.25 3a

09P0283 03 Jul 2010 20.23 162.58 101 10 Jul 2010 19.45 161.87 709P0310 01 Jul 2010 19.62 162.05 100 21 Jul 2010 18.71 159.64 2009P0315 03 Jul 2010 20.22 162.57 101 09 Jul 2010 18.99 162.12 509P0316 28 Jun 2010 19.82 161.73 102 30 Jun 2010 19.90 161.57 209P0317 03 Jul 2010 20.12 162.43 101 Failed to transmit –

09P0320 27 Jun 2010 19.93 161.72 97 06 Jul 2010 18.52 161.76 909P0321 27 Jun 2010 19.90 161.68 102 16 Jul 2010 18.81 161.88 1909P0347 02 Jul 2010 20.13 162.42 107 05 Jul 2010 19.05 162.21 309P0348 25 Jun 2010 20.18 161.72 98 28 Jun 2010 20.41 161.65 2

Tonga09P0375 01 Jul 2010 20.15 184.24 95 04 Jul 2010 19.35 183.71 309P0376 05 Jul 2010 19.90 184.62 89 08 Jul 2010 19.69 184.77 209P0377 05 Jul 2010 20.07 184.59 105 07 Jul 2010 20.00 184.96 209P0378 06 Jul 2010 19.72 184.63 91 11 Aug 2010 21.03 181.73 35

New Zealand09P0370 07 May 2010 39.60 178.40 93 26 Jun 2010 33.44 174.07 5009P0371 07 May 2010 39.60 178.40 98 18 May 2010 38.96 179.72 1109P0372 07 May 2010 39.59 178.41 98 06 Jun 2010 39.71 179.53 3009P0373 07 May 2010 39.60 178.44 98 19 Jun 2010 37.85 184.23 4309P0374 08 May 2010 39.63 178.44 102 21 May 2010 38.57 179.05 13

a Tag transmitted after 352 days, but was likely attached to the fish for only three days.

A.J. Williams et al. / Deep-Sea Research II ∎ (∎∎∎∎) ∎∎∎–∎∎∎2





stainless steel dart head was inserted between the pterygiophoresimmediately below the first dorsal fin using a purpose builtapplicator. The dart head was not inserted below the seconddorsal fin, as is common practice for other tuna species, becausethe antenna of the tag would have interfered with the caudal findue to the small size of the fish. A second anchor of the samedesign as the primary anchor was inserted approximately 10 cmposterior to the primary anchor. This was designed to reduceexcessive movement of the tag. Once the tag was attached, the fishwas returned to the water in the sling and released. The total timeout of water for each tagged fish was between one and twominutes. All personnel involved in tagging were experienced inthe selection of candidate fish for tagging (i.e. those of suitable sizeand condition) and methods used. All efforts were made to ensurepotential impacts on fish were minimized.

Tags were programmed to record light, temperature and depthreadings every 15 s, with light readings only recorded duringdawn and dusk periods. Time series data were then summarizedinto 10 min intervals and time-at-depth, time-at temperature anddepth profiles were summarized into 24 h periods. On-board dataprocessing by the mini-PATs determined the depth and tempera-ture of the surface mixed layer. Tags were programmed to releasefrom fish and transmit summarized depth, temperature and lightdata, as well as daily average depth and temperature of the surfacemixed layer after 352 days.

2.1.1. Electronic tag analysesEstimated daily positions for each tag were derived from the

light-level data recorded by the tag and the state-space modeldescribed in Nielsen and Sibert (2007) implemented in the Rsoftware package “trackit” (downloaded from: www.soest.hawaii.edu/tag-data/trackit). Transmitted temperature and depth time-series data were used to examine the vertical movement behaviorof each fish. Depth and temperature data were categorized as day,night or crepuscular. Crepuscular periods were defined as each60 min period centered on sunrise and sunset, corresponding tothe inflection points of the light-intensity curves. Crepuscularperiods were excluded from the diel analyses as they wereconsidered times of vertical transitional behavior (Childers et al.,2011). Statistical summaries of depths and temperatures weregenerated.

2.2. Diet data

A total of 733 stomachs of albacore tuna, of 43–106 cm FL, werecollected from a subsample of albacore tuna that were not suitablefor tagging during each tagging cruise and during longline andtroll commercial fishing operations in New Caledonia, Tonga andNew Zealand between 2008 and 2010 (Table 2, Fig. 1). Associatedwith each stomach sample, the fishing gear used (longline, troll),fish length, date, time and position of the beginning of each fishingevent (set) were recorded. Stomachs were frozen onboard.

In the laboratory, stomachs were thawed and classified asempty or non-empty. Stomachs were considered empty whenthey contained only digestive fluids. In those stomachs containingitems, prey were identified to the lowest taxonomic level possible,based on identification keys (Allain et al., 2012). Few stomachscontained hard part remains of prey (i.e. otoliths or cephalopodbeaks), so identification of prey items was conducted on wetremains only. For each prey taxon, the total weight in grams andthe number of specimens were determined.

2.2.1. Diet descriptionThe data associated with stomach samples were grouped by

location, gear type and year. To explore differences in diet betweengroups due to prey availability and foraging behavior, four para-meters were used to describe albacore tuna diet in each group:(i) taxonomic composition, (ii) prey diversity, (iii) fullness ratioand (iv) proportion of deep prey.

(i) Each taxon identified was expressed in weight of the taxon asa percentage of total weight of all the prey in the stomachconsidered. Values per stomach were then used to calculatemean percentage weight (%MW) and standard deviation foreach group. Prey frequencies, defined as the percentage ofalbacore tuna containing the prey taxa, were determined forall groups combined and for each group.

(ii) Diversity of prey in the diet was estimated based on the totalnumber of prey taxa in each group. Because numbers ofsamples varied between datasets, it was important to accountfor these differences in establishing species diversity of each

Table 2Details of the sampling program for the dietary component of the study on albacore tuna 2008–2010.

Dataset NZ_T_2008 NZ_T_2009 NZ_T_2010 NZ_L_2010 NC_L_2010 TO_L_2010

Date Jan–Apr 2008 Jan–Mar 2009 Apr–May 2010 Apr–May 2010 Feb–Oct 2010 Jun–Jul 2010Location SW New Zealand SW New Zealand NE New Zealand NE New Zealand New Caledonia TongaOperation Commercial Scientific Scientific Scientific Commercial ScientificFishing gear Trolling Trolling Trolling Longlining Longlining LongliningSetting Day Day Day Day and night Day and night Day and nightDepth Surface Surface �20 m Shallow Deep ShallowFish size range (FL cm) 43–86 43–90 69–95 60–100 73–106 76–105Number of stomachs 160 72 11 51 344 95

Fig. 1. Location of deployments of pop-up satellite archival tags and collection ofdiet samples for albacore tuna in the south Pacific Ocean, 2008–2010.

A.J. Williams et al. / Deep-Sea Research II ∎ (∎∎∎∎) ∎∎∎–∎∎∎ 3


www.soest.hawaii.edu/tag-data/trackit





group observed. Two indices were calculated: rarefied speciesrichness and Shannon–Weaver diversity index (Legendreand Legendre, 1998) using the R package vegan, version2.13.2 (R Development Core Team, 2011).

(iii) A fullness ratio was calculated for non-empty stomachs bydividing the total weight of prey items by the estimated totalweight of the fish from which the stomach was derived. Theweight for each albacore tuna was estimated from lengthmeasurements collected using the length-weight relation-ship:

W ¼ aFLb

where W is the weight of the fish in kilograms, FL is the forklength in cm, a¼2.971e-05 and b¼2.901. Coefficients a and bwere derived by fitting the length-weight relationship to 8891albacore tuna weighed and measured as part of the Westernand Central Pacific Ocean Regional Observer Programme (SPC,unpublished data).

(iv) To better understand the vertical feeding behavior of albacoretuna, prey species were classified into one of two ecologicalgroups (mixed or deep) according to their depth distributionand vertical migration behavior based on published literature(e.g. Grandperrin, 1975; Poore, 2004; Roper and Young, 1975;Smith and Heemstra, 1986). Understanding of the depthdistributions of micronekton organisms is very limited withdepth ranges for each species at each of the samplinglocations unknown. As a result, the broad classification ofprey into the two ecological groups was considered appro-priate for assessing broad-scale difference in vertical foragingbehavior. Prey classified as deep comprised species perma-nently inhabiting mesopelagic waters (Bertrand et al., 1999;Grandperrin, 1969). It was assumed that in order to consumethese species, albacore must have foraged at depth. Preyclassified as mixed comprised species distributed in theepipelagic layer and included those migrating from deeper

waters into the epipelagic layer during the night as well asthose permanently inhabiting epipelagic waters. Consump-tion of these species indicated feeding in surface waters andpotentially deeper waters during the day. The depth limitbetween epipelagic and mesopelagic layers is variable accord-ing to physical factors such as temperature, currents, seasonalmixing, and light (Brodeur and Yamamura, 2005; Robinsonet al., 2010; Suntsov and Domokos, 2013), but is generallyconsidered to be between 100 and 200 m. Prey that could notbe classified into an ecological group were not considered.

The proportion of deep prey identified in each stomach wasexpressed as the weight of classified deep prey relative to totalweight of stomach contents.

2.2.2. Diet analysesThe four parameters were then analyzed to investigate poten-

tial differences in albacore tuna diet associated with the year ofsampling, fishing area, the habitat characteristics of each area, fishsize (length), and fishing gear used. The effect of season could notbe tested as it was confounded with area, year and fishing gear(Table 2).

The potential influence of year, sampling area, fish size andfishing gear used on taxonomic composition of the diet wasexplored using multivariate regression tree analysis (De’ath,2002). The analysis was conducted based on percentage of preyin weight per stomach by calculating the Bray–Curtis distancematrix (Legendre and Legendre, 1998). The tree with minimumcross-validated relative error was selected as the optimal modelusing the mvpart package in R version 2.13.2 (R Development CoreTeam, 2011).

The influences of fish size, fishing gear used and environmentalparameters associated with the habitat characteristics of eachlocation on the fullness ratio of stomachs and the proportion

Table 3Explanatory variables included in models used to investigate variability in the stomach fullness and proportion of deep prey in the diet of albacore tuna.

Variable type Covariate Units Source Resolution

Location Latitude and longitude Decimaldegree

Grid squares 1, 2 or 5 deg2

Exclusive Economic Zone (EEZ)Longhurst province Longhurst (2007)Temperate/tropical classification Divided at

latitude 301S

Oceanographic Temperature at the surface 1C Commonwealth Scientific and Industrial Research Organisation (CSIRO)Atlas of Regional Seas (CARS), http://www.marine.csiro.au/�dunn/cars2009/

Climatologicalestimates,0.5 deg2

Temperature at 150 ma depth 1C

Oxygen estimate at the surface ml/l See above See aboveOxygen estimate at 150 m depth ml/lMixed layer depth m See above See aboveSea surface temperature (Reyn_Smith_sst) 1C National Oceanic and Atmospheric Administration (NOAA) Optimum

interpolation OI.v2 analysis http://iridl.ldeo.columbia.edu/SOURCES/.NOAA/.NCEP/.EMC/.CMB/.GLOBAL/.Reyn_SmithOIv1/.monthly/.dataset_documentation.html; Reynolds et al. (2002)

Month–year,1 deg2

Other Fishing gearPredator length cmDistance to closest land m National Geospatial Intelligence (NGA) World Vector Shoreline (WVS)

http://shoreline.noaa.gov/data/datasheets/wvs.htmlBathymetry (depth of the sea floor) m Earth Topography Digital Dataset (ETOPO1) bathymetry National

Geophysical Data Center, NOAA; Amante and Eakins (2009)10

Prey density index in the surface layer(0–200 m), deep layer (>200 m) or total(surfaceþdeep layers)

g/m2 Output of the physical-biogeochemical-biological SEAPODYM model(Lehodey et al., 2010; Briand et al., 2011)

Month–year,1 deg2

a Approximate mixed layer depth in tropical areas.





http://www.wcpfc.int/doc/SA-WP-04/Stock-Assessment-Albacore-south-Pacific-Ocean



http://www.wcpfc.int/node/1759




of deep prey were investigated using generalized linear mixedmodels (GLMM) with the lme4 package in R version 2.13.2(R Development Core Team, 2011). Environmental parametersincluded the oceanographic parameters water temperature, oxy-gen concentration and mixed layer depth, the distance of thesampling location to the closest land, bathymetric data for eachsampling location and modeled prey density estimates for eachsampling location (Table 3). Chlorophyll a or primary productionwas unavailable for inclusion in the analysis. It was assumed thatfish caught in the same fishing set probably experienced similarprey availability and, consequently, we used GLMM with a randomeffect applied to fishing set.

Fullness ratios of stomachs were log transformed and dataanalyzed using GLMM with a Gaussian response and identity linkfunction.

The frequency distribution of the proportion of deep prey instomachs was skewed towards zero (56% of the stomachs). Toaccount for this data structure, we analyzed the data in two steps(Stefánson and Pálsson, 1997). Firstly, the response variable wasdefined as the presence of deep prey in the sample, which wasanalyzed using a GLMM with a binomial response and logit linkfunction. Secondly, samples containing deep prey were analyzedusing the proportion of deep prey (in weight). Proportions of deepprey were logit transformed and analyzed using a GLMM witha Gaussian response and identity link function. Samples thatcontained 100% deep prey (2.7% of the predator samples, i.e.6 samples: 2 in New Caledonia, 2 in Tonga, 1 in New Zealand-longline-2010 and 1 in New Zealand-troll-2008) were omitted(because logit(1)¼ Inf.).

Log transformations and splines with various degrees of free-dom were explored for continuous explanatory variables. Todetermine which models better described the variability of thefullness ratio and of the proportion of deep prey, a large number ofmodels were fitted to the data from the simplest model 1 to themost complex model 2, testing all the intermediate models withall possible combinations of the explanatory variables.

Model 1: response variable�(1|set)Model 2: response variable� location or oceanographic_parameter or fishing_gearþpredator_lengthþdistance_to_landþbathymetryþforage_densityþ(1|set)

where response variable is fullness ratio or proportion of deepprey, and (1|set) represents the random effect for fishing set.

Model fits were compared using the BIC Bayesian InformationCriterion (Schwarz, 1978) and models with lower BIC were pre-ferred because they explained substantially more variability whileminimizing the number of explanatory variables.

3. Results

3.1. Tagging

Of the 19 tags deployed on albacore, 18 reported to the Argossystem and remained attached for 0–50 days. One tag deployed onan albacore tuna in waters around New Caledonia appeared tohave been consumed by a large bathypelagic predator shortly afterdeployment. Data from this tag showed the tagged fish descendedrapidly to approximately 800 m three days after tagging, where itremained for a further three days. The tag then recorded a regulardiel cycle of vertical movements ranging 400–800 m at tempera-tures 7–15 1C during which time the light sensors recorded nodiscernible light. After 351 days, the tag recorded a rapid ascent tothe surface where it transmitted approximately 100 km south–southeast of the release location.

3.1.1. Horizontal movementHorizontal movements could be estimated from 11 of the 17

tags that remained at liberty for five days or more (Fig. 2). Theseincluded five tags deployed in New Caledonian waters, one inTongan waters and five in New Zealand waters (Fig. 2). Thenumber of days for which positions could be estimated wasgenerally higher for those tags deployed in New Zealand waters(mean7SD¼24.8714.4 days) than for those tagged in NewCaledonian waters (mean7SD¼7.674.3 days), reflecting longeroverall periods of attachment. Position estimates could be calcu-lated for 30 of the 35 days that the albacore tuna tagged in Tonganwaters was at liberty.

Estimated movements of the five albacore tuna tagged inwaters off New Caledonia were relatively limited, with all fishremaining in waters to the northwest of New Caledonia (Fig. 2).Displacements between release and transmission location wereless than 155 km, with tags remaining attached a maximum of 17days. Estimated movements of fish tagged in New Zealand waterswere highly variable, with fish moving to the northeast and thenorthwest of the North Island (Fig. 2). Maximum displacement byalbacore tuna in the New Zealand region was 1105 km in 50 days.Estimated positions suggest that this fish initially moved north ofNew Zealand, then northwest within the vicinity of the NorfolkRidge towards New Caledonia (Fig. 2). The Tongan fish wasestimated to move in a westerly direction, and likely entered thewaters of Fiji’s EEZ, before moving back into Tongan waters (Fig. 2).Maximum displacement of this tag was 282 km, which occurredover 35 days.

3.1.2. Vertical movement and thermal habitatThe depths and temperatures experienced by albacore tuna

tagged with PSATs ranged between 1–409 m and 12–26.2 1C,respectively, and the mixed layer depths (MLD) and temperaturescalculated by the tags ranged between 53–173 m and 15.9–27.9 1C(Table 4). The percent time that tagged albacore tuna spent at orabove the calculated MLD ranged between 21.4% and 94.9%(Table 4).

Distinct differences in depth and temperature profiles betweentagging locations were apparent both in individual fish and whenrecords were pooled across fish within each location (Fig. 3).Albacore tuna tagged in New Caledonian and Tongan watersdemonstrated a distinct diel pattern in depth and temperaturepreferences, with fish occupying shallower, warmer waters abovethe MLD at night, and deeper, cooler waters below the MLD duringthe day. In contrast, there was little evidence of a diel pattern inthe vertical behavior for albacore tuna tagged in waters off NewZealand, with fish limited to shallow waters above the MLD almostall of the time. In New Zealand waters, there was evidence ofregular deeper dives during crepuscular periods, particularlyduring dusk periods, which were often the only dives below theMLD (Fig. 3).

Tagged albacore tuna in all locations spent most of the time(New Caledonia: 81%, Tonga: 96%, New Zealand: 99%) during thenight in waters shallower than 150 m, above the MLD (Fig. 4).Albacore tuna tagged in the two tropical locations spent most(New Caledonia: 56%, Tonga: 63%) of the night-time between 50and 150 m, while fish tagged in New Zealand waters spent most(92%) of the time in less than 100 m. Albacore tuna tagged in NewZealand waters occupied similar depths during the day and night,remaining above the MLD, and only occasionally diving below150 m (Figs. 3 and 4). In contrast, albacore tuna tagged in NewCaledonian and Tongan waters rarely occupied water shallowerthan 100 m during the day, remaining below the MLD, with fishspending most (New Caledonia: 80%, Tonga: 88%) of the timebetween 150 and 250 m and 200–350 m, respectively (Fig. 4).






Fig. 2. Estimated positions derived from albacore tuna tagged with pop-up satellite archival tags and at liberty >5 days in (A) New Caledonian, (B) Tongan and (C) NewZealand waters in 2010.






Maximum depths recorded by albacore tagged in New Caledonian,Tongan and New Zealand waters were 372 m, 409 m and 250 m,respectively (Table 4).

Temperatures experienced reflected depth distributions(Fig. 4). A wider temperature range was experienced by taggedalbacore tuna in waters off New Caledonia (15.3–26.2 1C) andTonga (13.8–26.1 1C) than those tagged in New Zealand waters(12.0–19.6 1C) (Table 4, Fig. 4). Those albacore tagged in NewZealand waters primarily spent most (85–97%) of their time inwater 17–20 1C both during the day and during the night. In thetwo tropical locations, albacore tuna spent most of their time(New Caledonia: 80%, Tonga: 98%) at night between 22 and 26 1C,with the fish tagged in Tongan waters occupying mostly coolerwaters (16–21 1C) during the day than those albacore tagged offNew Caledonia (19–23 1C).

3.2. Diet

3.2.1. Prey diversity and taxonomic compositionDiversity of prey was low for albacore tuna caught by the troll

fishery off the southwest coast of New Zealand (Tables 5 and 6,Fig. 5), with 21–31 prey taxa identified, values of 5–7 for rarefiedspecies and a Shannon diversity index of 0.8–1.3. Albacore tunacaught in this region fed mainly on crustaceans (72–75% MW),with smaller amounts of fish (15–23% MW), molluscs (4–8% MW)and gelatinous plankton (o1% MW) consumed. Some taxa such askrill (Euphausiacea, mainly Nyctiphanes australis) were consumedin large quantities (42–53% MW) and at high frequency (>38%). Ofthe fish taxa in the diet, the most important species belonged tothe family Scomberesocidae (surface and coastal-related sauries).

Albacore tuna caught off the northeast coast of New Zealand in2010 by troll and longline fisheries had intermediate prey diversitywith 29–40 prey taxa identified, a rarified species index of 26–31and a Shannon diversity index of 2.2 (Tables 5 and 6, Fig. 5).Similar to albacore tuna caught off southwest New Zealand, theyconsumed primarily crustaceans (53–58% MW), with smalleramounts of fish (24–26% MW), molluscs (4–15% MW) and gelati-nous plankton (7–12% MW) consumed. Of the crustaceans,Euphausiacea comprised an important component of the diet(4–13% MW). Amphipods recorded in the diet were mainlyrepresented by members of the family Phronimidae. Among thefew fish taxa consumed, the most frequent were members of the

Sternoptychidae (deep hatchetfish) and Myctophidae (lanternfish)families. No scomberesocids were recorded.

Prey diversity was higher for albacore tuna caught in NewCaledonian and Tongan waters with 72–163 prey taxa identified, ararified species diversity index of 57–72 and a Shannon diversityindex of 3.1–3.6 (Tables 5 and 6, Fig. 5). Most prey taxa contributedless than 1% in weight to the diet and no single prey taxoncontributed more than 7%. Albacore tuna in New Caledonian andTongan waters primarily consumed fish, with those from Tonga(56% MW) consuming greater amounts than those from NewCaledonia (39% MW). Conversely, albacore tuna sampled fromNew Caledonian waters consumed higher amounts of crustaceans(31% MW) than those from Tongan waters (11% MW). Both groupsconsumed similar amounts of molluscs (�25% MW) and gelati-nous plankton (4–6% MW). Important fish prey in terms of weightand/or frequency in both locations were those of the familiesParalepididae (deep barracudinas), Scopelarchidae (pearleyes),Myctophidae (lanternfish), Sternoptychidae (hatchetfish) andreef-related species from the families Acanthuridae (surgeon fish)and Pomacanthidae (angelfish). Important prey species observedin the diet of albacore tuna in New Caledonian waters includedspecies from the family Engraulidae (anchovies), the crustaceansThalassocaris sp., Stomatopoda, Amphipoda Phrosinidae, Palinuraand Phronimidae. Important molluscs in albacore tuna fromNew Caledonian waters were the purple squid Sthenoteuthisoualaniensis, and Onychoteuthis sp., while planktonic molluscs(Atlantidae, Carinariidae, Cavoliniidae, Littorinimorpha and Ptero-tracheoidea) were important in the diet of albacore tuna fromTongan waters.

Multivariate regression tree analysis based on prey compositionseparated samples into three groups with two branches, the firston the basis of year and the second on the basis of location. Thefirst branch of the tree separated samples collected prior to 2010(small troll caught fish from waters southwest of New Zealandduring January–March of 2008 and 2009) from those collected in2010 (large troll and longline caught fish from waters northeastof New Zealand during April–May and from waters off NewCaledonia and Tonga during February–July), explaining 23% ofvariation in the diet. The second branch of the tree separatedsamples collected in 2010 in waters northeast of New Zealand(troll and longline fisheries) from those collected in Tongan andNew Caledonian waters (longline fisheries), explaining 1.6% ofvariation in the diet.

Table 4Mean7standard deviation (range) of depth (m), temperature (1C) and percent time spent above the mixed layer by albacore tuna tagged with pop-up satellite archival tagsin the South Pacific Ocean.

Tag Day Night Mixed layer

Temperature Depth Temperature Depth Temperature Depth % Time

New Caledonia09P0283 22.771.5 (17.8–25.5) 183732 (122–326) 25.071.0 (19.8–25.8) 92750 (13–256) 25.370.3 (24.3–25.8) 14878 (137–158) 42.509P0310 20.771.5 (15.3–24.6) 206746 (99–372) 24.370.8 (15.8–26.2) 83741 (15–364.5) 24.670.5 (23.5–27.9) 123721 (83–162) 35.309P0315 20.270.9 (18.5–23.4) 237730 (31–301) 24.171.3 (19.4–25.1) 70766 (5–263) 25.170.7 (22.7–26.1) 150733 (127–173) 54.009P0320 20.671.2 (17.2–24.3) 213736 (106–316) 23.471.6 (18.9–25.3) 128746 (15–288) 24.970.3 (24.3–25.4) 119718 (87–136) 21.409P0321 21.871.4 (17.1–25.4) 192735 (114–343) 24.171.7 (19.4–26.0) 116749 (10–245) 25.570.2 (24.8–26.0) 123716 (99–148) 23.2

Tonga09P0378 18.471.7 (13.8–23.0) 284751 (114–409) 24.571.0 (18.5–26.1) 78743 (13–266) 25.270.4 (23.7–26.2) 106719 (73–143) 29.3

New Zealand09P0370 17.870.9 (12.8–19.2) 80731 (13–222) 18.170.7 (13.3–19.3) 64731 (6–224) 18.170.6 (16.1–19.3) 116722 (73–162) 87.309P0371 17.371.4 (13.0–19.2) 86739 (6–250) 18.470.9 (12.0–19.4) 32728 (1–222) 18.470.8 (15.9–19.3) 102717 (79–122) 74.609P0372 18.071.1 (12.5–19.4) 88727 (20–220) 18.470.8 (12.9–19.6) 76730 (7–342) 18.470.5 (16.4–19.6) 119720 (75–153) 81.509P0373 17.970.5 (16.5–19.2) 35716 (5–109) 18.070.6 (12.5–19.2) 28716 (3–82) 17.870.5 (16.4–19.1) 71714 (53–94) 94.909P0374 18.371.0 (12.7–19.3) 74725 (12–179) 18.670.8 (15.3–19.5) 57724 (7–139) 18.470.8 (16.6–19.4) 109724 (68–143) 89.8






3.2.2. Fullness ratioA total of 97 of 733 albacore tuna stomachs examined were

empty. The proportion of empty stomachs was lowest in NewCaledonia samples (0.01), higher in New Zealand, particularly for fishcaught from longline vessels (0.47) and highest in Tonga (0.56)(Table 5).

Stomach fullness was significantly related to the size ofalbacore tuna with fish length being the primary covariate in thefive best models (Table S1). Because of the spatial distribution ofsamples, water temperature and oxygen concentration were notcontinuous, and showed a clear separation between temperateand tropical regions. This resulted in relationships with stomachfullness being unclear and water temperature and oxygen con-centration being included in only some best-fit models. Becausethe inclusion of water temperature and oxygen concentration wasnot consistent across models and because of the spatial effects onboth variables, we chose the simplest model which included fish

size only (Table 7, Fig. 6). Fullness ratios predicted by the modeldecreased with fish size with albacore tuna smaller than 62 cm FLconsuming more than 3 g/kg and those larger than 100 cm lessthan 1 g/kg (Fig. 6).

3.2.3. Probability of consumption and weight proportion of deepprey consumed

The level of digestion affected the ability to identify some itemsof prey to a taxonomic level sufficient to determine their ecologicalgroup (mixed or deep), with 58% (in weight) of prey able to beassigned. The percentage of prey not assigned varied with data-sets, with approximately 34–38% (in weight) for samples fromNew Caledonia, Tonga and New Zealand (longline samples in 2010and troll samples in 2009), 18% for troll samples from NewZealand in 2010, and 60% for troll samples from New Zealandin 2008.

Fig. 3. One week of depth data derived from one individual, and depth and temperature data for all observations by local time of day from albacore tuna tagged with pop-upsatellite archival tags in (A) New Caledonian, (B) Tongan and (C) New Zealand waters. Night and crepuscular periods are indicated by dark gray and light gray shading,respectively. Solid blue line represents the average daily mixed layer depth.






Models identified relationships between the presence of deepprey in the diet and latitudinal location, water temperature andoxygen concentration at the surface, and fishing gear (Table S2).

Relationships with water temperature, oxygen concentration andfishing gear were largely the result of high correlation betweenthese covariates and latitude. As a result, latitudinal location alone

Fig. 4. Average proportion of time spent at depth (left) and temperature (right) of albacore tuna tagged with pop-up satellite archival tags in (A) New Caledonian, (B) Tonganand (C) New Zealand waters. Error bars are standard deviations. Solid lines are the average depth and temperature of the mixed layer and dashed lines represent thestandard deviations.

Table 5Number, weight and diversity of prey consumed by albacore tuna sampled 2008–2010.

Dataset NZ_T_2008 NZ_T_2009 NZ_T_2010 NZ_L_2010 NC_L_2010 TO_L_2010

Number of non-empty stomachs 152 61 11 27 342 42Number (proportion) of empty stomachs 8 (0.05) 11 (0.15) 0 (0.00) 24 (0.47) 2 (0.006) 53 (0.56)Number of prey individuals 33,871 39,970 506 662 8456 335Weight of prey (g) 1360.1 1049.6 279.1 204.6 3916.5 420.1Number of prey taxa 31 21 29 40 163 72Rarefied number of prey taxa (for 335 prey individuals) 7 5 26 31 57 72Shannon–Weaver diversity index 1.34 0.78 2.22 2.24 3.12 3.6






Table 6Mean percentage weight (%MW), standard deviation (SD) and frequency (F) of the prey taxa consumed by albacore tuna sampled 2008–2010 (see Table 2 for details on the datasets). Only prey with complete-dataset-frequencies>1% are included. Prey class indicates the vertical distribution as defined in the methods: M¼mixed, D¼deep, U¼undefined.

Dataset Prey NZ_T_2008 NZ_T_2009 NZ_T_2010 NZ_L_2010 NC_L_2010 TO_L_2010

Class %MW SD F %MW SD F %MW SD F %MW SD F %MW SD F M SD F

CRUSTACEAAmphipoda Amphipoda M 2.8 11.7 18.4 4.2 14.2 34.4 3.9 8.4 54.5 6.2 12.3 48.1 1.3 4.5 40.4 2.8 10.3 28.6– Hyperiidae U 0.8 8.3 1.3 0.7 3.4 4.9 0.0 0.1 9.1 3.4 10.9 14.8 0.0 0.4 3.2– Phronimidae M 0.1 1.2 1.3 0.1 1 1.6 11.3 11.6 72.7 6.6 15.4 37 4.4 10.6 38.3 1.1 3.9 11.9– Phrosinidae M 0.0 0.1 0.7 0.1 0.7 1.6 0.2 0.6 9.1 1.3 3.2 22.2 2.8 8.3 36.8 0.2 0.8 9.5Decapoda Brachyuran megalopa M 11.6 20.8 36.4 1.9 6 18.5 0.4 1.9 17.3 0.0 0.1 2.4– Palinura M 0.0 0.2 0.7 1.6 3.8 18.2 2.8 6.8 22.2 2.4 8.6 23.4 1 5.1 4.8– Enoplometopus sp. M 0.9 5 14.9 0.4 2.6 2.4– Thalassocaris sp. M 3.3 11.4 26.6Euphausiacea Nyctiphanes australis M 7.8 25 13.2 20.4 38.2 27.9– Euphausiacea unid. M 44.9 47.1 52 21.8 37.9 37.7 4.4 8 54.5 13.2 24.3 44.4 0.1 0.6 3.2 0.1 0.3 4.8Stomatopoda Stomatopoda M 5.7 21.2 12.5 4 18.1 9.8 3.1 6.7 39.2 0.1 0.3 4.8

Crustacea unid. U 12.1 31.1 15.8 23.6 41.2 31.1 27.6 21.8 90.9 20.7 27.2 51.9 12.8 19.4 76 2.5 5.4 45.2

MOLLUSCBolitaenidae Bolitaenidae D 0.1 0.7 1.8 0.1 0.4 2.4Octopodidae Octopodidae U 0.1 0.3 9.1 0.4 1.9 3.7 0.2 0.7 8.5 0.5 2.6 14.3Sepiolidae Heteroteuthis sp. M 0.5 2.7 5.3 0.3 2 2.4– Sepiolidae M 0.0 0.5 0.7 0.4 1.6 7 0.2 0.9 7.1Cranchiidae Cranchiidae D 0.5 1.4 14.8 0.2 1.1 6.1 0.7 4.3 2.4– Liocranchia sp. D 0.4 2.5 7.6 0.0 0.2 2.4Enoploteuthidae Enoploteuthidae M 0.0 0.4 1.8 0.4 2.6 2.4Histioteuthidae Histioteuthidae D 0.1 0.3 3.7 0.0 0.3 2 0.0 0.2 2.4Ommastrephidae Hyaloteuthis pelagica M 0.5 3.2 2.9 0.3 1.7 2.4– Ommastrephidae D 1 7.1 3.3 1.1 8.6 1.6 0.7 4.3 5.8– Ornithoteuthis volatilis D 0.5 3 3.8– Sthenoteuthis oualaniensis M 0.6 2.2 9.1 0.2 0.8 3.7 1.1 8 3.2 0.1 0.3 4.8Onychoteuthidae Onychoteuthidae M 1.9 8.4 9.4– Onychoteuthis sp. M 3.7 19.2 3.7 3.6 10 26.9 0.5 2.8 7.1Pyroteuthidae Pyroteuthidae M 0.0 0.4 2.3 0.8 3.7 16.7

Planktonic mollusc M 0.1 0.5 2 1.1 5.1 6.6 4 19.2 14.8 0.9 2.9 33.6 2.1 3.3 52.4Cephalopod unid. U 2.8 15 16.4 5.7 15.9 24.6 2.9 4.1 90.9 6.4 19.2 44.4 15.1 19.4 97.1 21.8 25.7 92.9

TELEOSTAlepisauridae Alepisauridae D 0.9 5.8 7.9 0.0 2.4– Alepisaurus sp. D 1 7.9 2.6 0.5 3.1 2.4– Omosudis lowii D 0.4 3.5 2.6 0.7 4.6 2.4Paralepididae Paralepididae D 3.1 10.2 18.1 1.8 7.3 16.7Scopelarchidae Scopelarchidae D 0.3 1.6 3.7 1.5 7.3 7.6 0.9 2.6 21.4Scomberesocidae Scomberesocidae M 8.8 25.5 13.2 4.4 18.8 8.2Engraulidae Engraulidae M 1.6 11.2 3.2Myctophidae Myctophidae M 0.2 2.4 0.7 0.4 2.9 3.3 0.9 2 18.2 2.9 10.5 7.4 0.9 5.6 5.8 1.6 6.4 16.7Acanthuridae Acanthuridae M 0.8 3.4 12.6 0.8 4.1 11.9

A.J.W

illiamset

al./Deep-Sea

Research

II∎(∎∎∎∎)

∎∎∎–∎∎∎

10Pleasecite

this

articleas:

William

s,A.J.,et

al.,Vertical

behavior

anddiet

ofalbacore

tuna(Thunnus

alalunga)vary

with

latitudein

the

South

PacificOcean

.Deep

-SeaRes.II

(2014),http

://dx.d

oi.org/10.1016/j.dsr2.2014.03.010i




could be used to best describe variability in the presence of deepprey in the diet (Table 7), with individuals in temperate watersconsuming less deep prey (probability and 95% confidence inter-val: 0.1370.06) than those in tropical waters (0.5670.07).

Because albacore tuna in temperate waters around New Zeal-and rarely consumed deep prey, investigation of variability in theweight proportion of deep prey in the diet of albacore wasrestricted to tropical datasets collected from New Caledonianand Tongan waters (n¼197). Models explored showed no clearrelationships between the weight proportion of deep prey in thediet and any of the covariates.

4. Discussion

This study provides the first investigation of linkages betweenvertical diving behavior and prey assemblages for albacore tuna.We observed distinct patterns in the vertical behavior, thermaland dietary habits of albacore tuna at tropical and temperatelatitudes in the South Pacific Ocean. Albacore tuna at tropicallatitudes displayed a distinct diel pattern in vertical habitat use,occupying deeper and cooler water below the MLD during the day,and shallower, warmer waters above the MLD at night. Their preyconsisted primarily of fish, with significantly more deepwaterspecies and a greater diversity of prey species, in small propor-tions, compared to albacore tuna in temperate waters. In contrast,albacore tuna at temperate latitudes remained in relatively shal-low water above the MLD throughout deployments and consumeda low diversity of prey consisting primarily of crustaceans, some-times in large proportions, and very few deepwater species.

4.1. Horizontal movements

The short durations for which all mini-PATs remained attachedto tagged fish precluded any detailed exploration of horizontalmovement patterns. The limited information collected suggeststhat albacore tuna are capable of residing within an area ofapproximately 300–400 km2 for periods of at least days to weeks,but are also capable of moving larger distances (>1000 km) withinperiods of weeks. This variation in horizontal movement behavioris consistent with albacore tuna in the North Atlantic Ocean(Cosgrove et al., 2014) and the North Pacific where at least fivedifferent migration patterns have been described, most involvingseasonal migrations of 1000's km between areas of residency(Childers et al., 2011). The migration patterns of albacore tuna inthe South Pacific remain unknown. Seasonal trends in longlinecatches, however, suggest a southern migration of albacore tunaduring early summer and a northward movement of fish duringwinter (Langley and Hampton, 2005). This movement is correlatedwith the seasonal oscillation in the location of the 20�28 1C seasurface temperature isotherms (Langley, 2006).

4.2. Vertical movements and relationships with diet

Prior to this study, knowledge of the vertical behavior patternsof adult albacore tuna in the south Pacific Ocean was limited to asingle study in American Samoa, where data were collected fromtwo fish at liberty for five and 16 days (Domokos et al., 2007).Cosgrove et al. (2014) used X-tags (Microwave Telemetry Inc.),which are similar in dimensions to mini-PATs, to obtain data onvertical behavior from five albacore tuna in the North AtlanticOcean. A more comprehensive study of the vertical behavior ofalbacore tuna was conducted using internal archival tags onjuvenile albacore (62–90 cm FL) in the North Pacific Ocean(Childers et al., 2011). Although limited by sample size and sizerange of fish, these previous studies provide the only comparable

Bramidae

Bramidae

M0.1

1.4

0.7

8.8

29.3

9.1

0.5

3.2

6.7

0.2

1.6

2.4

–Pterycom

buspe

tersii

M0.7

4.3

4.7

2.2

14.4

2.4

Chae

todon

tidae

Chae

todon

tidae

M0.1

0.5

3.8

0.1

0.8

2.4

Chiasm

odon

tidae

Chiasm

odon

tidae

D0.1

1.2

2Gem

pylid

aeGem

pylid

aeM

1.1

4.4

9.6

0.0

0.2

2.4

Malacan

thidae

Malacan

thidae

M0.2

1.1

7.9

0.3

1.3

4.8

Pomacan

thidae

Pomacan

thidae

M0.2

0.7

12.9

0.2

0.6

19Po

lymixiid

aePo

lymixia

sp.

D0.3

2.1

3.5

Sternop

tych

idae

Sternop

tych

idae

D0.0

0.5

0.7

4.2

1036

.41.6

8.4

3.7

0.6

3.8

5.6

0.5

1.9

9.5

Tetrao

don

tidae

Tetrao

don

tidae

M0.3

1.6

8.5

0.4

2.1

4.8

Cap

roidae

Cap

roidae

M0.1

0.6

2Fish

unid.

U11

.528

.823

.711

23.1

27.9

7.7

1536

.415

.322

.951

.924

23.3

82.7

46.3

30.7

88.1

GEL

ATINOUS

PLANKTO

NGelatinou

splankton

U0.2

21.3

0.8

4.6

6.6

1415

.854

.58.6

22.2

29.6

3.6

9.7

35.1

723

21.4

UNREC

OGNIZABLE

Unreco

gnizab

leU

17.9

3.9

0.5

2.6

6.6

0.2

22.6

0.6

2.8

7.1






data from which to draw inferences about processes that mayaffect Pacific albacore tuna vertical behavior.

The two adult albacore tuna tagged in waters around AmericanSamoa displayed similar vertical behavior to albacore tagged inNew Caledonia and Tonga in this study, spending time in deeper,cooler waters during the day and shallower warmer waters duringthe night (Domokos et al., 2007). Albacore tuna tagged at highlatitudes (>401N) in the North Atlantic displayed similar verticalbehavior to albacore tagged in New Zealand in this study,predominantly inhabiting shallow water (o50 m) above theMLD during the day and night. Cosgrove et al. (2014) observed asignificant increase in depth occupied during the day for one fishthat migrated to lower latitudes (�351N), consistent with ourobservation that albacore tuna occupy deeper water during theday at lower latitudes. Juvenile albacore tuna tagged in the NorthPacific Ocean have been observed to demonstrate a broad range ofvertical behaviors, including behaviors similar to those observed inthis study (Childers et al., 2011). Those in temperate latitudes ofthe North Pacific (�451N) remained above the MLD near thesurface during both day and night, similar to albacore tuna in NewZealand waters. Those tagged further south in subtropical waters(�281N) displayed a clear diel pattern in vertical behavior, similarto albacore tuna in New Caledonian and Tongan waters, asobserved here, and in American Samoan waters (Domokos et al.,2007). Overall, however, albacore tuna tagged in the North Atlanticand North Pacific oceans regularly occupied water that wassubstantially cooler than that occupied by albacore tuna in theSouth Pacific, with average water temperatures experienced ran-ging 14.4–20.6 1C (Childers et al., 2011; Cosgrove et al., 2014).

Albacore tuna are thought to use physiological thermoregula-tion to maintain a stable body temperature at approximately 20 1Cin water temperatures between 11.5 and 18.0 1C (Graham andDickson, 1981). Below 11.5 1C, the body temperature of albacoretuna has been observed to decline, and in response, individualshave been observed to modify their behavior, moving verticallyinto warmer water, to raise the body temperature. Albacore tunatagged in this study, including those in New Zealand waters, didnot enter water less than 12 1C. This suggests that the relativelyshallow distribution of albacore tuna in waters around NewZealand may not be associated with physiological limitations,but may instead be associated with individuals exploiting rela-tively high abundance of krill in surface layers.

Albacore tuna in an active growth phase require high energeticintakes which could explain their presence in areas where preyaggregate at the surface. Foraging by albacore tuna almost exclu-sively on one or two main epipelagic prey species has beenobserved previously in New Zealand (Bailey and Habib, 1982;O’Brien, 1988), and in other temperate areas, where prey speciessuch as euphausid, mackerel, saury, and anchovy are consumed inproximity to oceanographic features such as upwelling, conver-gence or eddies (Bailey, 1986, 1989; Fiedler and Bernard, 1987;Glaser, 2010; Goñi et al., 2011; Iversen, 1962, 1971; Pearcy, 1976;Watanabe et al., 2004). Albacore tuna smaller than 90 cm FL,similar to those sampled in this study from New Zealand waters,have specifically been observed to forage on aggregations of preyat the surface. Fish of this size are still immature (Farley et al.,2014) and in an active growth phase (Williams et al., 2012),requiring high energetic intake. The high energetic requirementsof such fish are likely to influence their distributions, concentrat-ing individuals in areas of high productivity, where food isavailable in large quantities. Influenced by important land massesand the subtropical convergence zone, the waters around NewZealand are characterized by a complex and dynamic oceanogra-phy. Strong physical and nutrient gradients occur throughout theregion (Butler et al., 1992; Heath, 1985; Vincent et al., 1991), whichcreate favorable conditions for high productivity (Fig. 7) and the

development of plankton swarms at the surface (Fenwick, 1978;O’Brien, 1988). High abundances of prey species in surface watersmay result in restricting the vertical distributions of albacore tunato surface waters with little requirement to utilize deeper watersto forage. However, we know they do have the ability to dive(Childers et al., 2011) in relation to thermoregulation capacity(Graham and Dickson, 1981) and swimbladder development(Dotson, 1976). The swimbladders of albacore tuna are not welldeveloped in fish smaller than 60 cm FL, and are not completelydeveloped until fish reach at least 80 cm FL (Dotson, 1976).Because of the importance of the swimbladder in the divingcapability of individuals, those individuals smaller than 60 cm FLand feeding on surface prey may also be limited in their diving andfeeding behavior due to their under-developed swimbladder.

High energetic requirements associated with growth and alsomaintenance of endothermy in cold waters might explain thehigher stomach fullness observed in smaller fish. Reduced stomachfullness with increasing size has also been observed in other studies(Goñi et al., 2011; Iversen, 1962; Young et al., 2010). Decreases instomach fullness have also been associated with increasing watertemperatures (Aloncle and Delaporte, 1973), which was also evidentin our dataset. Ratios of stomach fullness measured in temperateand tropical areas in our study (1–5.5 g kg�1) were similar to thoseobserved in albacore tuna sampled off the east coast of Australia(2–2.6 g kg�1, Young et al., 2010). Much higher values have beenobserved in similar sized albacore tuna in the northeast AtlanticOcean and Mediterranean Sea (3–15 g kg�1; Goñi et al., 2011).Higher fullness in the northeast Atlantic than in the southwestPacific could be linked to higher productivity (Behrenfeld andFalkowski, 1997; Moriarty and O’Brien, 2013) and higher preyavailability in the northeast Atlantic.

The diet of albacore tuna in the two tropical regions sampledwas highly diversified comprising higher numbers of prey species,particularly those associated with deeper waters, than those fromtemperate waters. Prey were also eaten in small quantitiescompared with temperate latitudes. There was no clear relation-ship between the proportion of deep prey in the diet and anycovariate, which may be associated with limited sample sizes orwith inappropriate scales, precision and confidence at whichcovariates were sampled. High diversities of prey and higherabundances of deep water species have also been observed invarious other studies on albacore tuna in the Pacific Ocean(Bertrand et al., 2002; Grandperrin, 1975; Legand et al., 1972;Young et al., 2010). Tropical waters are typically oligotrophic(Longhurst, 2007) and primary productivity in tropical areas ismuch lower than in temperate areas (Fig. 7). Very little data onzooplankton biomass exist in the tropical or subtropical SouthPacific, but global trends indicate that there is a decrease frompolar to more temperate regions in mesozooplankton biomass(Letessier et al., 2009; Moriarty and O’Brien, 2013). Similarly, thereare few studies on micronekton distribution and abundance in thetropical and subtropical South Pacific (Grandperrin, 1975; Hidakaet al., 2003; Legand et al., 1972). Information that is availableprovides little indication of large aggregations of single speciessuch as euphausiids in temperate areas such as that which might beexpected on the basis of the diets of albacore tuna described here.Models of forage abundance and distribution (Lehodey et al., 2010)indicate that prey in surface waters are less dense around NewCaledonia and Tonga than around New Zealand, while prey indeeper waters are typically more dense in tropical regions andsimilar to temperate regions. Values derived from such models areindicative and should only be considered as indices not as absolutevalues. However, if tropical waters are typified by lower abundancesof forage in surface waters and higher abundances in deeper waters,this may result in albacore tuna spending more time in watersbelow the MLD to feed on more abundant deepwater prey species.






4.3. Future studies

Collection of longer time series will be critical if we are tobetter understand the movement patterns of albacore tuna. Themaximum attachment period achieved in this study was 50 days,

with only four deployments of more than 20 days. This wasshorter than the maximum deployment time of 106 days formini-PATs attached to albacore tuna in the North Atlantic(Cosgrove et al., 2014), and substantially shorter than deploymentsof externally attached electronic tags reported for other tunaspecies, which have exceeded 200 days for bluefin tunas (e.g.Patterson et al., 2008; Wilson et al., 2005), 100 days for bigeyetuna (Matsumoto et al., 2005) and 50 days for yellowfin tuna(Weng et al., 2009). Individual time series of depth data clearlyindicate that at least six albacore tuna in this study died shortlyafter being tagged, resulting in tag detachment, while for otherindividuals the tag detached from the fish for unknown reasons.

A number of factors may have contributed to the deaths andshort attachment times for albacore tuna in this study. These mayhave related to the use of longline fishing gear to capture albacoretuna, or the design of the tag anchor and tether. Times betweendeployment and retrieval of longline gear can be as long as 12 h.This can result in some individuals remaining on a hook for longperiods before being retrieved, thereby compromising post-releasesurvival. Further, the depth at which longlines are set may haveresulted in individuals being hauled from relatively deep (>100 m)water, thus increasing the likelihood of fish injuries such asbarotraumas. Without information on the time at which fish werehooked and the depths at which they were caught, it is difficult toassociate fishing methods with fish mortalities observed.

The mini-PATs used in this study, although smaller in size andlighter than standard models of pop-up satellite archival tags, maystill be too large for albacore tuna of the sizes tagged in this study(>90 cm FL). Increased miniaturization of models in futuremay reduce the impact of tags on individuals and lengthenattachment times.

Fig. 5. Mean percentage weight (and standard deviation) of the prey categories consumed by albacore tuna in relation to sampling location, fishing gear and year (see Table 2for details on the datasets).

Table 7The selected GLM models for stomach fullness ratio and presence of deep prey in the diet of albacore tuna.

Response variable Covariates Df Chi sq p-value BIC

Fullness ratio �Set_code random effect 2257.59þPredator length 1 57.76 o0.001 2221.26

Presence of deep prey �set_code random effect 674.31þTropical-temperate factor 1 47.16 o0.001 628.92

Df, degree of freedom; Chi sq, Deviance of the final model; p-value from Anova Chi-test; BIC, Bayesian Information Criterion.

Fig. 6. Predicted and observed fullness ratio of non-empty stomachs (g/kg) inrelation to the length (cm FL) of albacore tuna. Predicted value (solid line) with 95%confidence interval (dashed line), observations (dots) with 95% confidence interval,and distribution of observations along the x-axis (ticks on the inner-axis). Predictedvalues were corrected for the log-normal bias according to Strimbu (2012).






In order to minimize potential injuries to the fish, we usedmodified stainless dart anchors that were considerably smallerthan primary anchors used in other studies on larger tunas. Use ofsuch a small anchor may have had minimal benefit in terms ofsecuring the tag and maximizing attachment periods. Longerdeployments may be achieved by using different and perhapslarger tag anchors than those used in this study, but inevitablythere will be a trade-off between anchor size and increased risk ofinjury and mortality to individuals.

Although sample sizes were limited, tags deployed on albacoretuna in New Zealand waters were retained longer than thosedeployed in tropical regions. A substantially higher percentage ofalbacore tuna from New Zealand waters (51%) were landed in goodcondition compared with the two tropical locations (�2%,Williams et al., 2010), suggesting that fish captured from surfacewaters (�50 m) rather than deeper waters (100–200 m) may havea higher probability of survival, perhaps due to reduced barotrau-mas. The lower temperatures of waters around New Zealand mayhave also contributed to lower rates of localized infection ofanchor sites and faster wound recovery rates (Musyl et al., 2011).The relatively long attachment times for X-tags deployed onalbacore in the North Atlantic (Cosgrove et al., 2014) are consistentwith achieving longer deployments in temperate waters than intropical waters, although other factors, such as type of tag, tetheror anchor, could have contributed to the different attachmenttimes between studies.

4.4. Conclusions

Our results indicate that the vertical distribution of albacore isconstrained either by thermal preferences, with diet reflectingthese preferences, by the vertical distribution of prey species,which is dictated by the thermal structure of the ocean, or by amixture of both. Our results are consistent with what is known ofthe life history of albacore tuna. Immature albacore tuna (o85 cmFL) inhabit temperate waters where large quantities of surfaceprey are available which support faster somatic growth. Maturealbacore tuna (>85 cm FL) occupy predominantly subtropical andtropical waters where temperatures are suitable for spawning(Farley et al., 2013), but food is less concentrated, resulting in

higher diversification of forage species and a requirement foralbacore tuna to forage across a wider vertical distribution to takeadvantage of prey species distributed below the MLD.

Spatial patterns in the vertical distributions of albacore tunasuggest that the vulnerability of albacore tuna to oceanic fisheriesmay also vary spatially. This has important implications for anyanalyses of catch data from albacore tuna fisheries in the SouthPacific Ocean. The vertical habitats and diet observed betweentropical and temperate regions in this study suggest that it isunlikely that the fisheries will be operating in exactly the samemanner in both regions. Such variability in operational compo-nents of the fishery can affect interpretation of catch data(Maunder et al., 2006) and, therefore, should be considered whenstandardizing catch per unit effort data for deriving indices ofrelative abundance in population assessments (Brill et al., 2005).Changes in the thermal structure of oceanic waters in temperateareas associated with climate change could potentially also influ-ence the vertical distributions and vulnerability of albacore tuna tooceanic fisheries. Understanding how these might change will beimportant for identifying potential changes to the fishery and, inassociation, potential management strategies that can be appliedto ensure sustainable catches of albacore tuna into the future.

Acknowledgments

This research was funded by the 9th European Union Devel-opment Fund (SCIFISH project), the Global Environment Facility(Pacific Islands Oceanic Fisheries Management Project), the Aus-tralian Overseas Aid Program (AusAID), and the New CaledonianZone Economique de Nouvelle-Caledonie (ZoNeCo) program. Weare grateful to the New Zealand Ministry for Primary Industries(MPI) observers, the New Caledonia observer programme, LyndaGriggs, Charles Cuewapuru and Hugues Gossuin, for collection ofsamples and logistical assistance. We would like to thank CarolineSanchez and Malo Hosken for their assistance with stomachcontent analysis and Christophe Menkes for the provision ofFig. 7. We also thank the two anonymous reviewers whosecomments significantly improved this manuscript.

Fig. 7. Satellite derived net primary production (mgC/m2/day) in the euphotic layer, averaged for the period 1998–2011 from satellite (VGPM: http://www.science.oregonstate.edu/ocean.productivity/, based on Behrenfeld and Falkowski (1997). Areas shallower than 200 m have been masked.








Appendix A. Supplementary Information

Supplementary data associated with this article can be found inthe online version at http://dx.doi.org/10.1016/j.dsr2.2014.03.010.

References

Allain, V., Fernandez, E., Hoyle, S.D., Caillot, S., Jurado-Molina, J., Andréfouët, S.,Nicol, S.J., 2012. Interaction between coastal and oceanic ecosystems of theWestern and Central Pacific Ocean through predator-prey relationship studies.PLoS ONE 7, e36701.

Aloncle, H., Delaporte, F., 1973. Données nouvelles sur le germon Thunnus alalungaBonnaterre 1788 dans le Nord-Est Atlantique. 1ère partie. Rythmes alimentaireset circadiens chez le germon Thunnus alalunga dans le nord-est Atlantique. Rev.Trav. Instit. Pêches Marit. 38, 475–572.

Amante, C., Eakins, B.W., 2009. ETOPO1 1 arc-minute global relief model: proce-dures, data sources and analysis. NOAA Technical Memorandum NESDIS NGDC24, 19 pp.

Bailey, K.N., 1986. A Preliminary Analysis of the Stomach Contents of Albacore,Thunnus alalunga, from the Subtropical Convergence Zone East of New Zealand.South Pacific Albacore Research Meeting Working Paper 17.

Bailey, K.N., 1989. Description and surface distribution of juvenile Peruvian jackmackerel, Trachurus murphyi, Nichols from the Subtropical convergence zone ofthe central South Pacific. Fish. Bull. 87, 273–278.

Bailey, K.N., Habib, G., 1982. Food of Incidental Fish Species Taken in the Purse-Seine Skipjack Fishery, 1976–81. New Zealand Ministry of Agriculture andFisheries. Fisheries Research Division. Occasional Publication: Data Series 6,pp. 1–24.

Behrenfeld, M.J., Falkowski, P.G., 1997. Photosynthetic rates derived from satellite-based chlorophyll concentration. Limnol. Ocean 42, 1–20.

Bertrand, A., Bard, F.-X., Josse, E., 2002. Tuna food habits related to the micronektondistribution in French Polynesia. Mar. Biol. 140, 1023–1037.

Bertrand, A., Le Borgne, R., Josse, E., 1999. Acoustic characterisation of micronektondistribution in French Polynesia. Mar. Ecol. Prog. Ser. 191, 127–140.

Bigelow, K., Musyl, M.K., Poisson, F., Kleiber, P., 2006. Pelagic longline gear depthand shoaling. Fish. Res. 77, 173–183.

Briand, K., Molony, B., Lehodey, P., 2011. A study on the variability of albacore(Thunnus alalunga) longline catch rates in the southwest Pacific Ocean. Fish.Oceanogr. 20, 517–529.

Brill, R.W., Bigelow, K.A., Musyl, M.K., Fritsches, K.A., Warrant, E.J., 2005. Bigeye tuna(Thunnus obesus) behavior and physiology and their relevance to stock assess-ments and fishery biology. Collect. Vol. Sci. Pap. ICCAT 57, 142–161.

Brodeur, R., Yamamura, O., 2005. Micronekton of the North Pacific. PICES Sci. Rep.30, 1–115.

Butler, E.C.V., Butt, J.A., Lindstrom, E.J., Teldesley, P.C., Pickmere, S., Vincent, W.F.,1992. Oceanography of the Subtropical Convergence Zone around southernNew Zealand. New Zealand J. Mar. Freshw. Res. 26, 131–154.

Childers, J., Snyder, S., Kohin, S., 2011. Migration and behavior of juvenile NorthPacific albacore (Thunnus alalunga). Fish. Oceanogr. 20, 157–173.

Collette, B., Nauen, C., 1983. FAO Species Catalogue, Vol 2. Scombrids of the World.An Annotated and Illustrated Catalogue of Tunas, Mackerels, Bonitos andRelated Species Known to Date. Rome: FAO Fish Synop no. 125(2), 137 pp.

Cosgrove, R., Arregui, I., Arrizablaga, H., Goñi, N., Sheridan, M., 2014. New insights tobehavior of North Atlantic albacore tuna (Thunnus alalunga) observed withpop-up satellite archival tags. Fish. Res. 150, 89–99.

De’ath, G., 2002. Multivariate regression trees: a new technique for modelingspecies-environment relationships. Ecology 83, 1105–1117.

Domokos, R., 2009. Environmental effects on forage and longline fishery perfor-mance for albacore (Thunnus alalunga) in the American Samoa ExclusiveEconomic Zone. Fish. Oceanogr. 18, 419–438.

Domokos, R., Seki, M.P., Polovina, J.J., Hawn, D.R., 2007. Oceanographic investigationof the American Samoa albacore (Thunnus alalunga) habitat and longline fishinggrounds. Fish. Oceanogr. 16, 555–572.

Dotson, R.C., 1976. Minimum swimming speed of albacore, Thunnus alalunga. Fish.Bull. 74, 955–960.

FAO, 2012. The State of World Fisheries and Aquaculture 2012. FAO, Rome.Farley, J.H., Hoyle, S.D., Eveson, J.P., Williams, A.J., Davies, C.R., Nicol, S.J., 2014.

Maturity ogives for South Pacific albacore tuna (Thunnus alalunga) that accountfor spatial and seasonal variation in the distributions of mature and immaturefish. PloS One 9, e83017.

Farley, J.H., Williams, A.J., Hoyle, S.D., Davies, C.R., Nicol, S.J., 2013. Reproductivedynamics and potential annual fecundity of South Pacific albacore tuna(Thunnus alalunga). PloS One 8, e60577.

Fenwick, G.D., 1978. Plankton swarms and their predators at the Snares Islands(note). J. Mar. Freshw. Res. 12, 223–224.

Fiedler, P.C., Bernard, H.J., 1987. Tuna aggregation and feeding near fronts observedin satellite imagery. Cont. Shelf Res. 7, 871–881.

Glaser, S.M., 2010. Interdecadal variability in predator–prey interactions of juvenileNorth Pacific albacore in the California Current System. Mar. Ecol. Prog. Ser. 414,209–221.

Goñi, N., Logan, J., Arrizabalaga, H., Jarry, M., Lutcavage, M., 2011. Variability ofalbacore (Thunnus alalunga) diet in the Northeast Atlantic and MediterraneanSea. Mar. Biol. 158, 1057–1073.

Graham, J.B., Dickson, K.A., 1981. Physiological thermoregulation in the albacoretuna Thunnus alalunga. Physiol. Zool. 54, 470–486.

Grandperrin, R., 1969. Couches diffusantes dans le Pacifique équatorial et sud-tropical. Cah. Orstom série Océanographie VII, 99–112.

Grandperrin, R., 1975. Structures trophiques aboutissant aux thons de longue lignedans le Pacifique sud-ouest tropical. Thèse d’état de l’Université d’Aix-MarseilleII, pp. 1–296.

Heath, R.A., 1985. A review of the physical oceanography of the seas around NewZealand – 1982. New Zealand J. Mar. Freshw. Res. 19, 79–124.

Hidaka, K., Kawaguchi, K., Tanabe, T., Takahashi, M., Kubodera, T., 2003. Biomass andtaxonomic composition of micronekton in the western tropical–subtropicalPacific. Fish. Ocean 12, 112–125.

Hoyle, S., Hampton, J., Davies, N., 2012. Stock assessment of albacore tuna in theSouth Pacific Ocean. Working paper SA-WP-04, 7th Scientific Committeemeeting of the Western and Central Pacific Fisheries Commission. Accessed2013 August 11. Available: ⟨http://www.wcpfc.int/doc/SA-WP-04/Stock-Assessment-Albacore-south-Pacific-Ocean⟩.

Iversen, R.T.B., 1962. Food of albacore tuna, Thunnus germo (Lacépède), in thecentral and northeastern Pacific. Fish. Bull. 62, 459–481.

Iverson, I.L.K., 1971. Albacore food habits. California Department of Fish and Game.Fish Bull. 152, 11–46.

Langley, A.D., 2006. The South Pacific albacore fishery management issues ofrelevance to Pacific Island countries and territories. Working Paper SA-WP-3,5th Scientific Committee meeting of the Western and Central Pacific FisheriesCommission, Manila, Philippines.

Langley, A., Hampton, J., 2005. Stock assessment of albacore tuna in the southPacific Ocean. Working Paper SA-WP-3, 1st Scientific Committee meeting of theWestern and Central Pacific Fisheries Commission, Noumea, New Caledonia.

Legand, M., Bourret, P., Fourmanoir, P., Grandperrin, R., Guérédrat, J.A., Michel, A.,Rancurel, P., Repelin, R., Roger, C., 1972. Relations trophiques et distributionsverticales en milieu pélagique dans l’Océan Pacifique intertropical. Cahier del’ORSTOM. Sér. Océanogr. X, 303–393

Legendre, P., Legendre, L., 1998. Numerical Ecology, Developments in Environmen-tal Modelling. Elsevier, Amsterdam.

Lehodey, P., Murtugudde, R., Senina, I., 2010. Bridging the gap from ocean models topopulation dynamics of large marine predators: a model of mid-trophicfunctional groups. Prog. Oceanogr. 84, 69–84.

Letessier, T.B., Cox, M.J., Brierley, A.S., 2009. Drivers of euphausiid species abundanceand numerical abundance in the Atlantic Ocean. Mar. Biol. 156, 2539–2553.

Longhurst, A.R., 2007. Ecological Geography of the Sea. Academic Press, Burlington,MA.

Matsumoto, T., Saito, H., Miyabe1, N., 2005. Swimming behavior of adult bigeyetuna using pop-up tags in the central Atlantic Ocean. Collect. Vol. Sci. Pap.ICCAT 57, 151–170.

Maunder, M.N., Sibert, J.R., Hampton, J., Kleiber, P., Harley, S., 2006. Interpretingcatch per unit effort data to assess the status of individual stocks andcommunities. ICES J. Mar. Sci. 63, 1373–1385.

Moriarty, R., O’Brien, T.D., 2013. Distribution of mesozooplankton biomass in theglobal ocean. Earth Syst. Sci. Data 5, 45–55.

Musyl, M.K., Domeier, M.L., Nasby-Lucas, N., Brill, R.W., McNaughton, L.M., Swim-mer, J.Y., Lutcavage, M.S., Wilson, S.G., Galuardi, B., Liddle, J.B., 2011. Perfor-mance of pop-up satellite archival tags. Mar. Ecol. Prog. Ser. 433, 1–28.

Nielsen, A., Sibert, J.R., 2007. State–space model for light-based tracking of marineanimals. Can. J. Fish. Aquat. Sci. 64, 1055–1068.

O’Brien, D.P., 1988. Surface schooling behaviour of the coastal krill Nyctiphanesaustralis (Crustacea: Euphausiacea) off Tasmania, Australia. Mar. Ecol. Prog. Ser.42, 219–233.

Oceanic Fisheries Programme, 2012. Western and Central Pacific Fisheries Commis-sion Tuna Fishery Yearbook 2011. Available: ⟨http://www.wcpfc.int/node/1759⟩.

Patterson, T.A., Evans, K., Carter, T.I., Gunn, J.S., 2008. Movement and behaviour oflarge southern bluefin tuna (Thunnus maccoyii) in the Australian regiondetermined using pop-up satellite archival tags. Fish. Oceanogr. 17, 352–367.

Pearcy, W.G., 1976. Albacore oceanography off Oregon – 1970. Fish. Bull. 71, 489–504.Poore, G., 2004. Marine Decapod Crustacean of Southern Australia. A Guide to

Identification. CSIRO Publishing, Collingwood.R Development Core Team, 2011. R: A language and environment for statistical

computing. R Foundation for Statistical Computing, Vienna, Austria. ⟨http://www.R-project.org/⟩.

Reynolds, R.W., Rayner, N.A., Smith, T.M., Stokes, D.C., Wang, W., 2002. An improvedin situ and satellite SST analysis for climate. J. Climate 15, 1609–1625.

Robinson, C., Steinberg, D.K., Anderson, T.R., Arístegui, J., Carlson, C.A., Frost, J.R.,Ghiglione, J.-F., Hernández-León, S., Jackson, G.A., Koppelmann, R., Quéguiner,B., Ragueneau, O., Rassoulzadegan, F., Robison, B.H., Tamburini, C., Tanaka, T.,Wishner, K.F., Zhang, J., 2010. Mesopelagic zone ecology and biogeochemistry –

a synthesis. Deep-Sea Res. II 57, 1504–1518.Roper, C.F.E., Young, R.E., 1975. Vertical distribution of pelagic cephalopods.

Smithson. Contrib. Zool. 209, 1–51.Schwarz, G., 1978. Estimating the dimension of a model. Ann. Stat. 6, 461–464.Smith, M., Heemstra, P., 1986. Smith's Sea Fishes. Springer-Verlag, Berlin.Stefánson, G., Pálsson, Ó.K., 1997. Statistical evaluation and modelling of the stomach

contents of Icelandic cod (Gadus morhua). Can. J. Fish. Aquat. Sci. 54, 169–181.Strimbu, B., 2012. Correction for bias of models with lognormal distributed

variables in absence of original data. Ann. For. Res. 55, 265–279.Suntsov, A., Domokos, R., 2013. Vertically migrating micronekton and macrozoo-

plankton communities around Guam and the Northern Mariana Islands. DeepSea Res. Part Oceanogr. Res. Pap. 71, 113–129.




http://refhub.elsevier.com/S0967-0645(14)00075-7/sbref1











































































































http://www.wcpfc.int/node/1759







http://www.R-project.org/

http://www.R-project.org/






















Vincent, W.F., Howard‐Williams, C., Tildesley, P., Butler, E., 1991. Distribution andbiological properties of oceanic water masses around the South Island, NewZealand. New Zealand J. Mar. Freshw. Res. 25, 21–42.

Watanabe, H., Kubodera, T., Masuda, S., Kawahara, S., 2004. Feeding habits ofalbacore Thunnus alalunga in the transition region of the central North Pacific.Fish. Sci. 70, 573–579.

Weng, K.C., Stokesbury, M.J., Boustany, A.M., Seitz, A.C., Teo, S.L., Miller, S.K., Block,B.A., 2009. Habitat and behaviour of yellowfin tuna Thunnus albacares in theGulf of Mexico determined using pop-up satellite archival tags. J. Fish. Biol. 74,1434–1449.

Williams, A., Nicol, N., Leroy, B., 2010. South Pacific Albacore Tagging Project: 2010Summary Report. Working Paper GN-IP-06, 6th Scientific Committee Meetingof the Western and Central Pacific Fisheries Commission, Nuku’alofa, Tonga.

Williams, A.J., Farley, J.H., Hoyle, S.D., Davies, C.R., Nicol, S.J., 2012. Spatial and sex-specific variation in growth of albacore tuna (Thunnus alalunga) across theSouth Pacific Ocean. PloS One 7, e39318.

Wilson, S.G., Lutcavage, M.E., Brill, R.W., Genovese, M.P., Cooper, A.B., Everly, A.W.,2005. Movements of bluefin tuna (Thunnus thynnus) in the northwesternAtlantic Ocean recorded by pop-up satellite archival tags. Mar. Biol. 146,409–423.

Yamanaka, H., 1956. Vertical structure of the ocean and albacore fishing conditionsin the vicinity of 10 1S in the western South Pacific. Bull. Jpn. Soc. Fish. 21,1187–1193.

Young, J.W., Lansdell, M., Campbell, R., Cooper, S., Juanes, F., Guest, M., 2010.Feeding ecology and niche segregation in oceanic top predators off easternAustralia. Mar. Biol. 157, 2347–2368.





























Documents

Vertical behavior and diet of albacore tuna (Thunnus alalunga) vary with latitude in the South Pacific Ocean