Journal of Experimental Marine Biology and Ecology 398 (2011) 9–17

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Journal of Experimental Marine Biology and Ecology

j ourna l homepage: www.e lsev ie r.com/ locate / jembe

Resolving estimation of movement in a vertically migrating pelagic fish: Does GPSprovide a solution?

Karen Evans a,⁎, Heather Baer b, Ed Bryant c, Melinda Holland b, Ted Rupley b, Chris Wilcox a

a Wealth from Oceans Flagship, CSIRO Marine and Atmospheric Research, GPO Box 1538, Hobart, Tasmania, 7001, Australiab Wildlife Computers, 8345 154th Avenue NE, Redmond, Washington, 98052, USAc Wildtrack Telemetry Systems Ltd, Beechcroft, Goose Lane, Hawksworth, Leeds, LS20 8PJ, West Yorkshire, UK

⁎ Corresponding author. Tel.: +61 3 62325007; fax:E-mail address: Karen.Evans@csiro.au (K. Evans).

0022-0981/$ – see front matter © 2010 Elsevier B.V. Aldoi:10.1016/j.jembe.2010.11.006

a b s t r a c t

a r t i c l e i n f o

Article history:Received 6 July 2010Received in revised form 13 November 2010Accepted 15 November 2010Available online 24 December 2010

Keywords:Broadbill swordfishFastloc™ GPSPop-up satellite archival tagSpatial dynamics

Determining geo-positions from light data collected on broadbill swordfish has traditionally beenproblematic. Diving behaviour in this species is typically diel in nature, with the majority of time duringthe day spent at depths of approximately 600–800 m and the majority of time at night spent in waterstypically less than 200 m. Descent into deep waters occurs at dawn and ascent into surface waters occurs atdusk. Diving behaviour such as this result in little light data being collected by archival tags deployed on thisspecies and, as a consequence, calculated positions may be few and far between. This reduces the scale atwhich movement and habitat interaction can be inferred. Swordfish, however, do spend time right at theocean surface at night and in some regions basking during the day also occurs. Periods of surface behaviourmay provide the opportunity to determine position in this species utilising alternative technologies. In aneffort to address this problem and assess the suitability of satellite based technologies for determiningmovement in swordfish, we developed a towed body tag incorporating Fastloc™ GPS technology thatfunctions similarly to a pop-up satellite archival tag. Ten prototype tags were developed with deploymentsoccurring on swordfish off the east coast of Australia during 2008. While tags were deployed on swordfish,GPS locations were recorded from eight of the 10 fish across 1.8–33.3% of days deployed (in comparison to5.3–54.6% of positions determined from light). Utilisation of GPS technology in a configuration similar to apop-up tag provides the potential for determining point estimates of position at higher accuracies than lightdata. By incorporating GPS positions in movement models with light-based positions, it also provides anability to resolve movement at finer spatial scales than previously achievable. This in turn allows for thedetermining of habitats of importance, migratory corridors and the responses of individuals to spatialenvironmental variability at finer scales than previously possible and has broader application for marinewildlife management.

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© 2010 Elsevier B.V. All rights reserved.

1. Introduction

The development of methods to accurately describe the movementof marine species over extended temporal and spatial scales has beenongoing over the last two decades and has provided important insightsinto the movements, migratory routes and habitats of importance ofmarine animals (Evans and Arnold, 2009). The recent development ofdevices that allow fast acquisition of GPS constellation signals duringbrief periods of surfacing behaviour means that high temporal andspatial resolution tracking of a range of marine species includingmammals, seabirds and reptiles is now possible (Weimerskirch et al.,2002; Schofield et al., 2007; Costa et al., 2010). While there have beensome attempts at utilising GPS technology on fish (Sims et al., 2009a),

this is a relatively recent phenomenon and the development of thismethodology is still in its infancy.

Broadbill swordfish (Xiphias gladius), hereafter known as swordfish,have a widespread geographical distribution throughout the world'stemperate, subtropical and tropical regions (Palko et al., 1981). Thespecies is commerciallyfished throughout its range, primarily by pelagiclongline vessels, with smaller catches taken by vessels utilising driftnetsand harpoons and occasional catches taken utilising handlines, troll-lines, traps, purse seines and pole-and-line (Folsom et al., 1997;Ward etal., 2000). In the south-west Pacific, swordfish have comprised acomponent of longline vessel catches since the 1950s, although it wasnot until the mid 1990s that improved access to overseas marketsresulted in the specific targeting of swordfish by longline vessels in boththe Australian and New Zealand fisheries, and regional catchesincreased substantially as a result.

Catches off eastern Australia within the Eastern Tuna and BillfishFishery (ETBF) have been largely associated with three oceanographic/geographic regions: inshore activities along the continental shelf

Fig. 1. Ten day archival record of diving behaviour of swordfish from a recovered Mk10 PAT demonstrating typical diel behaviour.

10 K. Evans et al. / Journal of Experimental Marine Biology and Ecology 398 (2011) 9–17

associated with oceanographic fronts and eddies of the East AustralianCurrent (EAC); inshore activities associated with seamounts; andoffshore activities associated with oceanographic fronts and seamounts(Ward et al., 2000). Similar to many fisheries targeting swordfish,swordfish catches throughout the ETBF have demonstrated a serialpattern of depletion,with catch thatdeclines progressivelymoving fromnear shore fishing grounds to those further offshore (Ward et al., 2000;Campbell and Hobday, 2003).

In response to concern over depletions in catches and the status ofthe swordfish fishery in the western Pacific Ocean (WPO) region, anassessment of the swordfish stock was undertaken in 2006. However, anumber of fundamental uncertainties implicit in the models used,particularly in association with movement, residency around bathy-metric features and degree of mixing of swordfish throughout theregion raised concerns over the ability of the models used to providerealistic indicationsof the status of thefishery (Kolody et al., 2006). In aneffort to address this uncertainty, anelectronic taggingprogramutilisingpop-up satellite archival tags (PSATs) was initiated with the aims ofbetter defining the spatial dynamics of swordfish in the WPO.

Initial results from deployments of PSATs in the western TasmanSea revealed that the diving behaviour of swordfish affected theability to calculate geo-positions from light data.1 Diving behaviourwas observed to be almost strictly diel in nature, with the majority oftime during the day spent by individuals at depths of approximately600–800 m and the majority of time at night spent in waters typicallyless than 200 m (Fig. 1). Descent into deep waters occurs at dawn andascent into surface waters occurs at dusk, similar to that reported forswordfish in electronic tagging studies in other regions (Carey andRobison, 1981; Takahashi et al., 2003; Canese et al., 2008; Abascal etal., 2010). Such a large proportion of time spent at depth during theday resulted in little light data being collected by PSATs deployed and,as a consequence, estimates of position were few and far between.This thereby reduced the scale at which movement, residency andhabitat interaction could be inferred.

Swordfish were however observed to spend a significant amountof time at or near the ocean surface at night (Fig. 1), similarly to thatreported for swordfish in electronic tagging studies elsewhere (Careyand Robison, 1981; Takahashi et al., 2003; Canese et al., 2008).Swordfish elsewhere have also been reported to demonstrate baskingbehaviour at the ocean surface during the day (Ward et al., 2000). Theability to spend periods of time at the ocean surface and the possibility

1 Evans K. 2010. Investigation of local movement and regional migration behaviourof broadbill swordfish targeted by the Eastern Tuna and Billfish Fishery. Report 2006/809 to the Australian Fisheries Management Authority. 100p.

of basking behaviour by swordfish prompted initial discussions withelectronic tag manufacturers about the viability of alternativetechnologies for utilisation in the determination of movement inswordfish.

The use of satellite tagging technology involving transmissions viathe Argos satellite network has been demonstrated in striped marlin(Tetrapturus audax) in the WPO (Holdsworth et al., 2009). Althoughinitially discussed as a possibility for deployment on swordfish, theavailability of Fastloc™ global positioning system (GPS) technology(www.wildtracker.com) was considered as a more suitable option.Position calculation based on satellite telemetry using the Argosnetwork requires that three or more transmissions from the tag bereceived by the polar orbiting satellites used require in order tocalculate position using the Doppler effect on transmission frequency(see www.argos-system.org for further details). Archival depth dataretrieved from a recovered PSAT suggested that if animals werebreaking the surface of the water it was only for lengths of time on theorder of seconds, rather than the much longer time periods requiredto obtain positions based on satellite telemetry using Argos (thesevary depending on the transmission frequency of the tag platform andthe length of the satellite pass over the tag, but are on the order ofminutes rather than seconds). Standard GPS technology was alsoconsidered to be unsuitable as it requires many seconds to minutes ofexposure to GPS satellites in order to determine position and theonboard calculations require considerable amounts of energy.Fastloc™ GPS technology promised the potential for estimations ofpositions from time periods of less than a second in duration at thesurface. Here we describe a re-configuration of current generationpop-up satellite archival tags to include Fastloc™ GPS technology foruse on pelagic predators and assess the suitability of Fastloc™technology for determining movement in swordfish and potentiallyother fish species also.

2. Materials and methods

2.1. Preliminary field trials

Important to the collection of data on movements and behaviour ofswordfish independent of fishery operations was a tag design similar tothat of a PSAT, which allowed storage of position, depth andtemperature data onboard the tag and then detachment of the tagfrom the fish and subsequent transmission of data after a pre-determined period of time. Tag designs incorporating Fastloc™ GPStechnology available at the time were largely capable of collection andtransmission of location data only (Weimerskirch et al., 2002; Schofield

Fig. 2. Prototype towed body Mk10 PAT-Fs.

11K. Evans et al. / Journal of Experimental Marine Biology and Ecology 398 (2011) 9–17

et al., 2007; Riding et al., 2009; Sims et al., 2009a) and those that werecapable of collecting depth and temperature data lacked the stream-lined, light and buoyant requirements for towed body designs suitablefor deployment on fish; they were rather designed for deployments onmammals, seabirds and reptiles (Ryan et al., 2004; Kuhn et al., 2009)where the tag could be directly attached to the animal.

Wave wash, submersion and poor antenna orientation are allproblems that can prevent GPS receivers from providing locationinformation. We therefore needed to determine two key factorsassociatedwith the ability of the GPS antenna to acquire GPS signals ina towed body design before tag design could begin. Firstly, we neededto identify if the surfacing behaviour of swordfish would allowclearance of the GPS receiver and acquisition of GPS constellationsignals. Secondly, a towed body attachment was likely to result insome rolling (longitudinal movement along the centre of the tag fromside to side) and pitching (vertical movement from the centre of thetag forward or backwards) of the GPS antenna as the tag movedthrough the water. We therefore needed to determine the antennasability to acquire GPS constellation signals under varying angles of tilt.

In order to determine the suitability of swordfish surfacingbehaviour for acquisition of GPS data, we modified two Mk10 PATs(Wildlife Computers, Redmond) so that they transmitted signals toArgos satellites opportunistically once clear of the ocean surface. Thetwo tags were programmed for 60 day deployments and deployed onswordfish in the western Tasman Sea in January 2007. One tagprematurely detached after five days, the other detached on time afterthe full 60 days. During the 60 day deployment, transmissionattempts were received by Argos on six occasions, confirming thatsurface swimming behaviour in the swordfish allowed the tag to clearthe ocean surface.

We then conducted a range of tests on a Mk10-AF (WildlifeComputers, Redmond) to determine the capability of the Fastloc™GPS antenna to successfully acquire GPS constellation signals under arange of degrees of tilt (0–40°). While we had no way of estimatingthe degree of roll and pitch likely to occur by tags externally deployedon swordfish, we felt that any movement in either plane beyond 40°would result in the tag antenna unlikely to be completely clear of thewater surface and therefore unable to receive GPS constellationsignals. The tag was fixed on to a customised holding cradle whichcould be tilted in two planes to simulate both roll and pitch and placedin a seawater bath with a clear view of the sky. The tag was then leftfor 4 h and the cradle tilted in 10° increments in the two planes. Eachtest was conducted at the same time of day over a period ofconsecutive days in an effort to minimise the effects of changingsatellite trajectories.

The ability of the GPS antenna to acquire GPS constellation signalsdemonstrated little deterioration across tilt angles, with the greatestdeviation in distance from the true location occurred at 40° roll and

Table 1Performance of a Mk10-AF in acquiring GPS constellation signals and determining location

Tilt angle (°) Number of satellites acquired(range)

Deviation flatitude in

0 8.18±1.56 (6–12) 0.0002±0

Pitch angle10 8.24±1.21 (6–11) 0.0002±020 8.55±1.29 (6–12) 0.0023±030 7.28±1.02 (5–9) 0.0014±040 8.01±1.14 (6–10) 0.0003±0

Roll angle10 8.06±1.31 (6–11) 0.0002±020 8.17±1.22 (5–11) 0.0034±030 8.19±1.19 (6–11) 0.0002±040 7.74±1.49 (4–11) 0.0186±0

30° pitch (Table 1). Deviation from true latitude was worst at 40° rolland 20° pitch, with deviation from true longitudeworst at 40° roll and30° pitch. Location errors were similar to those recorded in tests ofFastloc™GPS units elsewhere (Costa et al., 2010; Hazel, 2009). In lightof the positive results, it was decided that the development of aprototype design for a towed body GPS tag should go ahead.

2.2. Tag design

The tag design essentially took the components of a Mk10-AF(Wildlife Computers, Redmond) and transferred them into aconfiguration which placed the circuitry in front of the GPS antenna(rather than underneath) and an AA battery below the GPS antenna.Initial designs (n=4) contained the GPS antenna and associatedcircuitry only; later designs (n=6) also incorporated a light sensor, athermistor and a pressure (depth) sensor. A saltwater switch allowedfor the determination of when the tag was out of water and a batterysensor monitored the state of the AA battery. The components werethen encased into a float comprised of beaded epoxy and fashionedinto a streamlined shape that could be towedwith the lowest possibleresistance yet would float upright (Fig. 2). A weighted model of thetag was tested in water to assess the stability of the design anddemonstrated that the floating tag was not stable when upside downand would turn the right side up. Further tests of the design undertowed conditions revealed some instability in the initial designassociatedwith the back ‘keel’ of the tag and the forward placement ofthe antenna. The centre of gravity in this design was shifted forwardas a result of the placement of the antenna, resulting in the tag tendingto lean forward creating instability under towed conditions. This also

across a range of angles in the roll and pitch planes.

rom truedegrees

Deviation from truelongitude in degrees

Distance from truelocation in km

.0001 0.0002±0.0002 0.03±0.02

.0001 0.0001±0.0001 0.02±0.02

.0195 0.0017±0.0103 0.29±2.46

.0104 0.0036±0.0260 0.34±2.41

.0017 0.0002±0.0004 0.05±0.19

.0003 0.0002±0.0002 0.03±0.03

.0302 0.0027±0.0234 0.44±3.86

.0002 0.0002±0.0002 0.03±0.03

.0761 0.0209±0.0956 2.76±11.49

12 K. Evans et al. / Journal of Experimental Marine Biology and Ecology 398 (2011) 9–17

increased drag associated with the towing of the tag, which was sub-optimal for animal deployment. The design was re-worked into ashape that more resembled a ‘boat-like’ configuration with theantenna towards the back of the tag. Further tests under towedconditions were conducted to confirm stability and resistance of thetag as it was towed through the water. The final design of the tag was15 cm in length, 5 cm at its widest point (midway through the GPSantenna), 4 cm deep and weighed 120 g in air (Fig. 1). This is incomparison to a Mk10 PAT which is 17 cm in length, 2 cm wide in thetag body, 4 cm wide in the tag float and 77 g weight in air.

2.3. Prototype tag deployments

Ten prototype towed body PSATs with Fastloc™ GPS capabilitieswere deployed in the western Tasman Sea across the months ofFebruary to December 2008. Fish were caught during commerciallongline operationswith those considered in good condition (hooked inthe lip or upper mouth, lively and not bleeding) and of a large size andweight (N150 cmOFL and N50 kgwetweight so that the tag constituted~0.2% or less of additional weight to the animal) lead alongside thevessel to a position near the sea door. The anchor of each tag wasinserted into the dorsal musculature of the fish in a position just ventralto the primary dorsal fin using a customised tagging pole similar to thatdescribed in Chaprales et al. (1998). The fish was then either cut fromthe line or the hook removed from themouth and the fish then allowedto swim away from the vessel. The deployment position of all tagreleases was recorded using the vessels' onboard GPS system.

A custom made stainless steel floy-type anchor was used as aprimary anchor for each tag. The leader comprised a combination of400 lb monofilament looped through the thimble protecting thecorrodible pin and attached to a customised swivel, the opposite sideto which was attached 1.6 mm coated stainless steel wire which wasthreaded through the anchor. In ideal placement, this resulted in atether of ~10 cm in length trailing from surface of the tagged animal.The primary monofilament leader on all tags was fitted with a depthrelease device (RD-1800, Wildlife Computers, Redmond USA),designed to cut the tag off the fish at a depth of 1800 m, therebypreventing implosion of the tag at depth. Each tag was printedwith anidentification number, information about a reward offered and whereto return the tag.

All tags were programmed to sample GPS constellation signals attwominute intervals when the saltwater switch indicated the tag wasdry at the water surface. Those tags with light, pressure andtemperature sensors were programmed to collect light, depth andtemperature at 10 s intervals. Data were summarised into 1 h timeperiods prior to transmission via Argos. All tags were programmed torelease from tagged fish after 60 days.

Table 2Deployments of prototype Mk10-Fs on broadbill swordfish in the western Tasman Sea, 200

Tag Releases

Date Latitude (°S) Longitude (°E) Estimaweight

07A0889b 28 Feb 2008 29.36 159.60 7007A0890b 23 Mar 2008 25.98 156.96 13507A0894b 25 Mar 2008 25.95 156.82 24008A0103 25 May 2008 29.07 154.03 7008A0098 19 Jun 2008 28.71 154.04 10007A0893b 6 Nov 2008 24.75 155.46 6008A0071 8 Nov 2008 25.55 155.65 5008A0101 12 Dec 2008 25.73 156.09 14508A0096 13 Dec 2008 25.73 156.24 16508A0100 15 Dec 2008 25.89 155.36 170

TAL: time at liberty. Note tags first transmit 48 h after pop-up.a Estimated weight is based on the weight after the fish has been gilled and gutted.b Did not incorporate a light sensor into the design.

2.4. Position estimation

GPS locations were determined using a software developed inassociation with the Fastloc™ GPS firmware to process the acquiredconstellation data (GPS Solver version 1.0.53.0, Wildlife Computers,Redmond). Light-based geo-positions from those tags with lightsensors were calculated using two methods: (i) the template fitmethod (Hill and Braun, 2001) via proprietary software supplied bythe tag manufacturer (WC-GPE version 1.02.0005, Wildlife Computers,Redmond) to calculate longitudecoupledwithSSTmatching to calculatelatitude as per Patterson et al. (2008) and (ii) the state-space modeldescribed in Nielsen and Sibert (2007) and implemented using the Rsoftware package “trackit” (available at: www.soest.hawaii.edu/tag-data/trackit) to calculate amostprobable trackandassociated estimatederror. The template fit method with SST matching (light/SST geoloca-tion) produced one position estimate for each day, while the state spacemodel generated a position estimate associated with each dawn anddusk event for each day. The total number of positions and the interval(in days) between position estimates for each of the position estimationmethodswascalculatedandcompared. Position estimates generatedviathe threemethodswere thenmapped inManifold System8.0 (ManifoldNet Ltd) and visually compared.

3. Results

The ten prototype tags were deployed on swordfish estimated at50–240 kg (mean±SD: 121.0±61.0 kg) between February andDecember 2008 (Table 2). Deployments ranged 8–60 days with sixof the ten tags achieving full deployments of 60 days. Data werereceived from all tags.

3.1. Position estimation

Initial results from the output of the software used to calculate GPSpositions identified a number of problems. The model used tocalculate GPS position was structured around high numbers ofsatellite acquisitions collected close in space and time. It also assumedminimal tag clock drift. Acquisitions collected by tags on swordfishhowever, were often associated with substantial clock drift (32–90 s),were widely separated in time (0–25 days), and therefore often inspace, and typically associated with 4–6 satellites (mean±SD: 5.56±1.39; range: 4–9). The low number of satellite signals resulted fromtags receiving sub-millisecond ranges from the satellites instead of thefull 20–25 ms required to receive higher numbers of satellite signals.The nature of these acquisitions resulted in a lack of convergencewithin the model and the production of obvious erroneous positionestimates. As a result, several parameters within the model needed tobe adjusted. Firstly, the time search window was reduced and

8.

Pop-up transmissions

ted(kg)a

Date Latitude (°S) Longitude (°E) TAL(days)

9 Mar 2008 28.12 160.39 423 Apr 2008 23.56 161.84 2923 May 2008 36.28 151.77 572 Jun 2008 29.81 153.82 617 Aug 2008 21.83 159.06 574 Jan 2009 15.91 158.27 5721 Nov 2008 25.42 157.55 1109 Feb 2009 33.24 156.45 5710 Feb 2009 32.82 159.24 5712 Feb 2009 34.77 153.94 57

Table 3Number of positions and mean (±SD) interval (in days) between position estimates calculated from prototype Mk10-Fs using light-based geolocation with sea surface temperaturematching, state space model and Fastloc™ GPS methods.

Tag Light-based geo-positions State space model positions Fastloc™ GPS positions

Number %of TAL Interval Number %of TAL Interval Number % of TAL Interval

07A0889 – – – – – – 0 0.00 –

07A0890 – – – – – – 5 17.24 3.25±2.2107A0894 – – – – – – 19 33.33 2.94±1.9808A0103 1 16.67 – 5 83.33 1.50±0.58 0 0.00 –

08A0098 0 0.00 – 9 15.79 6.22±8.53 1 1.75 –

07A0893 – – – – – – 5 8.77 3.75±1.7108A0071 2 18.18 5.00 8 72.72 0.86±0.90 3 18.18 1.00±0.0008A0101 0 0.00 – 14 24.56 3.31±5.14 10 17.54 6.22±7.1408A0096 2 3.51 14.00 4 7.02 3.00±5.20 1 1.75 –

08A0100 1 1.75 – 18 14.04 2.41±3.97 4 7.02 13.00±11.14

TAL: time at liberty. Note tags first transmit to Argos 48 h after pop-up.

13K. Evans et al. / Journal of Experimental Marine Biology and Ecology 398 (2011) 9–17

adjusted for clock drift and secondly the search area was modified toperform numerous radial searches that incremented to accommodateacquisitions collected sporadically over large areas. Once updatedwith these corrections, all tagswere then re-run through the software.

Fig. 3. (A) Ten day archival record of diving behaviour of a swordfish from a recovered Mk102008 and 18 November 2008 are marked with arrows; (B) temperature–depth profile dat08 November (left) 18 November (right).

GPS positions were attained by eight of the tags deployed (Table 3;Fig. 2). The number of positions calculated from each tag ranged 0–19(mean±SD: 4.77±5.89). In comparison, fewer position estimates(mean±SD: 1.00±0.89; range: 0–2) based on light/SST geolocation

PAT-F. The times at which Fastloc™ GPS position data were obtained on 08 Novembera associated with the 12 h period around GPS locations collected from the same tag:

Fig. 4. Fastloc™ GPS position data collected by Mk10 PAT-Fs deployed on broadbillswordfish in the western Tasman Sea.

14 K. Evans et al. / Journal of Experimental Marine Biology and Ecology 398 (2011) 9–17

were calculated. The state space model estimated similar numbers ofposition estimates to those produced using Fastloc™ GPS technology(mean±SD: 9.83±5.38; range: 4–18). The interval betweenGPS position estimates varied 0–25 days, while the interval betweenlight-based position estimates based on light/SST geolocation varied5–14 days and those derived from state space model methods varied0–24 days (Table 3). The maximum number of GPS positionscalculated within a day was six, although in the majority of cases(81%) only one location was calculated within each day. GPSconstellation signals were acquired mostly at night with 31.51% ofsignals acquired during daylight hours and 68.49% acquired at night(Fig. 3).

Table 4Comparison of position estimates calculated on the same day using template fit light-basedmethods (Note local time is GMT+10 h).

Tag Date Template fit & SST matching State

Time Lat Long Time

08A0096 2/02/2009 06:1418:28

08A0071 18/11/2008 08:2418/11/2008 15:2118/11/200819/11/2008 08:09

08A0101 18/01/2009 09:0731/01/2009 09:07

08A0100 19/12/2008 average for dawn/dusk −25.89 155.68 08:3818:00

3.2. Movement patterns

Movement as determined from GPS tags was varied amongstindividuals with a number of fish demonstrating substantive north–south movements of up to ~1,250 km straight line distance (Fig. 4).North–south movements did not necessarily occur concurrentlybetween fish with some individuals moving south when othersmoved north (Fig. 4). Movements of an east–west nature were lesssubstantive (up to a maximum of ~550 km straight line distance); thefurthest east an individual was recorded at was 162.5°E and allmovements were restricted to the Coral and Tasman Seas.

Position estimates derived from light/SST geolocation in somecases deviated substantially from position estimates derived fromboth state-space model methods utilising light data and Fastloc™ GPSmethods (Table 4, Fig. 5). Position estimates derived from state spacemodel methods produced tracks that were more comparable to thoseproduced using Fastloc™ GPS methods (Fig. 5), although there wasstill some deviation in the trajectory of tracks and the smoothingradius used in the model sometimes resulted in position estimation incoastal regions placing positions on land. Position estimates calculat-ed by the three methods rarely occurred on the same day and in allinstances were offset by a number of hours (Table 4); comparisons ofestimated tracks were confounded by temporal offsets in positionestimates as a consequence. Fastloc™ GPS position estimates differedfrom state space model position estimates on average 1.58±2.35°latitude and 1.38±2.39 longitude (Table 4). Position estimatescalculated using light/SST geolocation methods and Fastloc GPSmethods did not occur on the same day and therefore were not ableto be compared.

4. Discussion

The development of electronic tag technology, and in association,geolocation methods over the past decade has resulted in an ability todetermine movement in animals that remain completely submerged(Smith and Goodman, 1986; Metcalfe and Arnold, 1997; Hill andBraun, 2001; Hunter et al., 2003; Teo et al., 2004; Andersen et al.,2007; Ekstrom, 2007; Neuenfeldt et al., 2007; Nielsen and Sibert,2007; Lam et al., 2008). This has, and is, of particular importance forinforming the structure of particular stocks of marine animals,determining the degree of mixing between these stocks, definingfisheries management areas, determining habitats of importance atboth the individual and population level and identifying howindividuals interact with their environment (Wilson et al., 2005;Southall et al., 2006; Teo et al., 2007; Gore et al., 2008; Patterson et al.,2008; Bestley et al., 2009). However, for those species that are almostexclusively pelagic and demonstrate extensive diel behaviour,determining movement using light-based geolocation methods is

geolocation with sea surface temperature matching, state space model and Fastloc GPS

space model Fastloc™ GPS Difference

Lat Long Time Lat Long Lat Long

−31.58 161.22−31.68 161.34 16:05:42 −25.89 155.68 5.79 5.66−25.71 157.11−25.72 157.18 16:21:00 −25.05 156.92 0.67 0.26

20:30:02 −25.07 156.95−25.62 157.26 10:05:00 −25.15 157.00 0.47 0.26−27.29 157.74 01:09:40 −26.90 158.13 0.39 0.39−30.42 156.52 21:22:58 −29.83 156.84 0.59 0.32−26.99 155.74 1.10 0.06−27.10 155.77

Fig. 5. Comparison of position estimates derived from template fit geolocation with sea surface temperature matching; state space modelling and Fastloc™ GPS methods from lightdata collected from two Mk10 PAT-Fs deployed on broadbill swordfish in the western Tasman Sea.

15K. Evans et al. / Journal of Experimental Marine Biology and Ecology 398 (2011) 9–17

still problematic. The development of a pop-up archival tagincorporating Fastloc™ GPS capabilities provides the potential forthe collection of complimentary higher resolution position data fromsuch species.

Fastloc™ GPS position estimates provided by these tags substan-tially increased the number of position estimates able to bedetermined compared to traditional light/sst matching geolocationmethods, vastly increasing the ability to estimate the spatial dynamicsof swordfish. While the tags produced similar numbers of positionestimates at comparable temporal scales to state-space modelmethods of determining position estimates in this species, unlikestate space model methods, which at best can produce only twoposition estimates per day (one at dawn and dusk), multiple Fastloc™GPS position estimates were able to be calculated for each day,thereby providing greater spatial resolution of position estimatesalong estimated tracks. The smaller spatial error associated withFastloc™ GPS position estimates also served to avoid potentialplacement of position estimates on land, which the state spacemodel is prone to do in coastal and inshore areas. Higher temporalresolution of position estimation provides the potential for investi-gating movement rates and association of movements with oceano-graphic features (e.g. Sims et al., 2009a).

In tags that collect both light and Fastloc™ GPS data such as thetags developed here, GPS position estimates could be used to informcurrent state space models incorporating light data in a similarfashion to start and end points of deployments. This would allow formovement models to incorporate a number of ‘corrections’ along theestimated track, ultimately resulting in a more realistic estimation ofmovement and a reduction in the error associated with position

estimates. In turn, this would allow for the determining of habitats ofimportance, migratory corridors and the responses of individuals tospatial environmental variability at finer scales than previouslypossible. It is also possible that in those areas where swordfish areknown to bask such as the Mediterranean and the eastern PacificOcean (Ward et al., 2000), larger numbers of position estimates maybe possible, further increasing the resolution at which movement andhabitat interactions are possible.

The application of these tags is not restricted to use on swordfish—

it has wider use in providing complimentary position estimates forother species which demonstrate similar behaviour to swordfish andfor which position estimation is also problematic as a result. Bigeyetuna (Thunnus obesus) tagged away from fish aggregating devicesroutinely display diel diving behaviour, descending to depths of 400–600 m at dawn, and ascending back into surface waters at night(Schaefer and Fuller, 2002; Musyl et al., 2003; Arrizabalaga et al.,2008; Evans et al., 2008). Although regular excursions are made intoshallower waters during the day, capture of light data at those criticaltimes required for light-based geolocation (dawn and dusk) iscompromised due to the diving behaviour of the species. Bigeyetuna have been observed to frequent the top 1 m of water in the westand central Pacific Ocean (Musyl et al., 2003; Evans et al., 2008) andthe top 10 m in the eastern Pacific Ocean (Schaefer and Fuller, 2002)andMediterranean (Arrizabalaga et al., 2008). Deployment of the tagsdescribed here on bigeye may be of use in providing high resolutionposition estimates and thereby resolving movement in this species.

Utilisation of these tags need not be only restricted to those speciesfor which light-based methods are challenging. Deployment of thetags described here on marine fishes for which satellite-based

16 K. Evans et al. / Journal of Experimental Marine Biology and Ecology 398 (2011) 9–17

position estimation has been used or which have been observed tofrequent surface waters such as billfish (Gunn et al., 2003; Hoolihan,2005; Horodysky et al., 2007; Holdsworth et al., 2009), tunas (Block etal., 1997; Lutcavage et al., 2000; Itoh et al., 2003; Kitagawa et al., 2004;Bestley et al., 2009), sharks (Bonfil et al., 2005; Bruce et al., 2006;Southall et al., 2006; Wilson et al., 2006; Weng et al., 2008) sunfish(Sims et al., 2009b) and rays (Riding et al., 2009) would enable thecollection of location data collected at both higher temporal andspatial resolutions, due to the higher sampling frequencies (only oneuplink is required to generate a position in comparison to themultipleuplinks required to calculate Argos positions) and accuracies possiblewith Fastloc™GPS tags. This ultimately would allow the description ofmovement at finer spatial scales than previously possible (e.g. Sims etal., 2009a).

The ability to collect GPS quality location data coupled with oceandata collected by these tags (Fig. 3) provides the potential for anoceanographic instrument capable of collecting high resolutionvertical temperature–depth profiles. Utilisation of such data ispotentially beneficial for a number of reasons: (1) it maximises theuse of data collected by electronic tagging programs; (2) given thespatial extent across which marine pelagic predators move, it has thepotential to enhance oceanographic data for input into ocean/climatemodels from traditionally hard to sample regions (e.g. polar regions,continental shelf regions, semi-enclosed seas); (3) it has the potentialto provide oceanographic data for input into ocean/climate modelsfrom regions with temporally sparse time series and (4) in providingdata to further improve current ocean/climate data products, it canprovide for the development of enhanced tools for understandinganimal behaviour and habitat interactions.

For fish species such as broadbill swordfish, utilisation of methodsthat sensibly combine the best of both light-based geopositions andFastloc™ GPS position estimates have the potential to substantiallyincrease our understanding of themovement patterns,mixing rates andareas of residency, providing important inputs into regional manage-ment of harvested stocks.

Acknowledgements

This research was supported by funding from the AustralianFisheries Management Authority (AFMA). Data management supportwas provided by the CSIRO Electronic Tag Systems Support project. Theauthors would like to acknowledge the support of Aaron Mattner andthe crew of Fortuna II, PavoWalker and the crew of Assassin andMartinWright and the crew of Kendon B in the deployment of tags. GaryHeilmann and Mike Madden of Mooloolaba Fisheries Investments PtyLtd and Steve Hall of AFMA provided considerable logistical support inorganising tagging operations. Thor Carter, MatthewHorsham andMattLansdell are thanked for their assistance on the project both in thelaboratory and at sea. Jason Hartog and Gary Brodin assisted with dataprocessing. All fish were tagged usingmethods approved by the animalethics committee of the Department of Primary Industries, ParksWaterand Environment, Tasmania and under scientific research permits901198, 1000075, 1000129, 1001072 and 1001144 issued by AFMA.Jason Hartog, Marinelle Basson, Graeme Hays and two anonymousreviewers provided constructive comments on earlier drafts of themanuscript. [SS]

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