Age, growth and maturity of the pelagic thresher Alopias pelagicus and the scalloped hammerhead Sphyrna lewini

Journal of Fish Biology (2015) 86, 333–354

doi:10.1111/jfb.12586, available online at wileyonlinelibrary.com

Age, growth and maturity of the pelagic thresher Alopiaspelagicus and the scalloped hammerhead Sphyrna lewini

M. Drew*†, W. T. White‡, Dharmadi§, A. V. Harry‖ andC. Huveneers*¶

*School of Biological Sciences, Flinders University, Bedford Park, Adelaide, SA 5043,Australia, ‡CSIRO Oceans & Atmosphere Flagship, Hobart, Tas 7000, Australia, §Research

Centre for Capture Fisheries, Agency for Marine and Fisheries Research, Department ofMarine Affairs and Fisheries, Jl, Pasir Putih I, Ancol Timur, Jakarta Utara 14430, Indonesia,‖Centre for Sustainable Tropical Fisheries & Aquaculture and School of Earth &

Environmental Sciences, James Cook University, Townsville, Qld 4811, Australia and¶Threatened, Endangered, and Protected Species subprogram, South Australian Research and

Development Institute – Aquatic Sciences, West Beach, Adelaide, SA 5024, Australia

(Received 10 September 2014, Accepted 16 October 2014)

Indonesia has the greatest reported chondrichthyan catches worldwide, with c.110,000 t caught annu-ally. The pelagic thresher (Alopias pelagicus) and scalloped hammerhead (Sphryna lewini) togethercomprise about 25% of the total catches of sharks landed in Indonesia. Age and growth parameterswere estimated for A. pelagicus and S. lewini from growth-band counts of thin-cut vertebral sections.Alopias pelagicus (n = 158) and S. lewini (n = 157) vertebrae were collected from three Indonesianfish markets over a 5 year period. A multi-model analysis was used to estimate growth parameters forboth species. The models of best fit for males and females for A. pelagicus was the three-parameterlogistic (L∞ = 3169 mm LT, k = 0⋅2) and the two-parameter von Bertalanffy models (L∞ = 3281 mmLT, k = 0⋅12). Age at maturity was calculated to be 10⋅4 and 13⋅2 years for males and females, respec-tively, and these are the oldest estimated for this species. The samples of S. lewini were heavily biasedtowards females, and the model of best fit for males and females was the three-parameter Gompertz(L∞ = 2598 mm LT, k = 0⋅15) and the two-parameter Gompertz (L∞ = 2896 mm LT, k= 0⋅16). Age atmaturity was calculated to be 8⋅9 and 13⋅2 years for males and females, respectively. Although numer-ous age and growth studies have previously been undertaken on S. lewini, few studies have been able toobtain adequate samples from all components of the population because adult females, adult males andjuveniles often reside in different areas. For the first time, sex bias in this study was towards sexuallymature females, which are commonly lacking in previous biological studies on S. lewini. Additionally,some of the oldest aged specimens and highest age at maturity for both species were observed in thisstudy. Both species exhibit slow rates of growth and late age at maturity, highlighting the need for are-assessment of the relative resilience of these two globally threatened sharks at current high levelsof fishing mortality throughout the eastern Indian Ocean.

© 2014 The Fisheries Society of the British Isles

Key words: von Bertalanffy; chondrichthyan; fishing; Gompertz; growth models; Indonesia.

INTRODUCTION

Indonesia has the world’s largest recorded chondrichthyan fishery, with an average of13% of the total global recorded catch between 2000 and 2007, representing c. 110 000 t

†Author to whom correspondence should be addressed. Tel.: +61 8 8207 5376; email: [email protected]

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© 2014 The Fisheries Society of the British Isles

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caught annually (Lack & Sant, 2006, 2011). Two of the most commonly landed chon-drichthyan species from the Indonesian fisheries are the pelagic thresher Alopias pelag-icus Nakamura 1935 (White, 2007a, b; White et al., 2008) and the scalloped ham-merhead Sphyrna lewini (Griffith & Smith 1834). These species are both targeted bythe small-scale longline fishery, and caught as by-catch in the tuna Thunnus spp. andswordfish Xiphias spp. longline fishery, the Thunnus spp. gillnet fishery and variousother small-scale artisanal fisheries. Alopias pelagicus and S. lewini catches repre-sented 12⋅7 and 12⋅5%, respectively, of the total biomass of sharks recorded duringa five-year market survey of Indonesian fisheries (White, 2007b; White et al., 2008).

Alopias pelagicus is an epipelagic, wide-ranging species predominantly foundoffshore over deep water in the tropical and subtropical waters of the Indo-Pacific (Liuet al., 1999; Compagno et al., 2005; Last & Stevens, 2009). The biology and ecologyof A. pelagicus is poorly known with relatively limited studies on age and growth,reproductive characteristics and demographic analyses (Liu et al., 1999, 2006; Cortés,2002; White, 2007b; Tsai et al., 2010). The only previous age and growth study in thenorth-west Pacific Ocean described A. pelagicus as exhibiting K-selected life-historycharacteristics and having a asynchronous reproduction (Liu et al., 1999), whileA. pelagicus was found to have a non-seasonal reproductive cycle in Indonesian waters(White, 2007b). Demographic analysis suggested a slow annual population rate ofincrease of 2–4% in north-west Pacific waters (Liu et al., 2006). The low reproductivepotential of A. pelagicus and intensive fishing mortality have led the species to declinein the eastern Indian Ocean (Camhi et al., 2009), and to be considered over-exploitedin north-west Pacific waters (Tsai et al., 2010). The epipelagic habitat of A. pelagicusalso makes the species directly vulnerable to several unregulated and unmanagedhigh seas fisheries (Liu et al., 1999; Camhi et al., 2009). As a result, A. pelagicushas been globally listed as vulnerable under the IUCN’s Red List of ThreatenedAnimals (Reardon et al., 2009). Alopids have also been identified as one of the sevenmost threatened chondrichthyan families (Dulvy et al., 2014). The recognition of thevulnerability of alopids to overfishing and increased international concerns for theconservation status of this group of sharks led the Indian Ocean Tuna Commission(IOTC) to adopt a ban on fishing for all species of alopids.

Sphyrna lewini is a large, coastal-pelagic and semi-oceanic species that has a circum-global distribution in tropical and warm–temperate waters (Compagno et al., 2005;Last & Stevens, 2009). Sphyrna lewini is a target or by-catch species in a wide varietyof fisheries throughout its range and substantial population declines are suspected tohave occurred in many areas as a result of high fishing pressure (Dudley & Simpfendor-fer, 2006; Ferretti et al., 2008; Hayes et al., 2009). Numerous age and growth studieshave previously been undertaken on S. lewini, although none within Indonesian waters(Chen et al., 1990; Tolentino & Mendoza, 2001; de Bruyn et al., 2005; Piercy et al.,2007; Tolentino et al., 2008; Harry et al., 2011; Kotas et al., 2011). Few studies havebeen able to adequately obtain samples from all components of a population, with sexand life-stage bias commonly occurring within S. lewini populations (Klimley, 1987;White et al., 2008; Harry et al., 2011). Studies in the western-north and central AtlanticOcean indicate that populations of S. lewini have declined in abundance by 89% since1986 (Baum et al., 2003; Hayes et al., 2009). Indonesian populations of S. lewini areexploited at all life-history stages due to the diversity of fisheries in the region, whichoperate in all of the habitats utilized by this species (White et al., 2008). Juveniles withtotal lengths (LT) between 480 and 1100 mm are caught in large numbers as by-catch

© 2014 The Fisheries Society of the British Isles, Journal of Fish Biology 2015, 86, 333–354

AG E A N D G ROW T H O F T W O L A R G E S H A R K S P E C I E S 335

in inshore gillnet fisheries presumably within their juvenile nursery areas (White et al.,2008). In contrast, sub-adults and adults with LT between 1100 and 3200 mm are tar-geted by offshore longline fisheries and also form part of the by-catch from the Thunnusspp. and Xiphias spp. longline fisheries (White et al., 2008). This high level of exploita-tion across all life stages is potentially occurring at an unsustainable level, thus leadingto overexploitation of S. lewini in this region (White et al., 2008; Blaber et al., 2009).As a result of the observed declining S. lewini abundance, its low reproductive poten-tial and extensive susceptibility to various fisheries, S. lewini was globally classifiedas endangered under the IUCN red list (Baum et al., 2007) and was recently listed inthe CITES Appendix III, requiring signatory countries to impose stricter conditions onexport of this species. In 2012, the Australian state of New South Wales also listed S.lewini as endangered in coastal waters.

Until recent surveys of Indonesian fishing catch composition (White, 2007b; Whiteet al., 2006, 2008), no detailed research had been undertaken on Indonesian chon-drichthyans for more than 100 years (White et al., 2006). Market surveys indicated thatmost species are targeted and exploited throughout their life-history stages, becausethey are targeted by a range of multi-gear and multi-regional fisheries. Surveys alsopointed to the disappearance of several species coupled with declining catch ratesin others (White et al., 2006, 2008). Achieving a sustainable fishery in the world’slargest chondrichthyan fishery will clearly be challenging. An integral first step in suc-cessful management is the collection of baseline life-history information of the targetspecies. Growth rates and age determination, in particular, are key components of fish-eries research (Cailliet & Goldman, 2004) and are required for most fisheries stockassessments based on age-structured population models (Pauly, 1987). Inaccurate agedetermination can lead to major errors in stock assessment and incorrect estimations ofresilience to fishing pressure, which could lead to over or under-exploitation of a stock(Officer et al., 1996; Campana, 2001; Goldman, 2004; Cailliet & Goldman, 2004). Dataon growth are particularly important for long-lived and slow-growing species that arelikely to be most vulnerable to exploitation and high fishing mortality (Cailliet & Gold-man, 2004; Goldman, 2004). Geographic variation in life-history parameters, includingage and growth, has been reported in several chondrichthyan fisheries highlightingthe need for region-specific life-history data (Parsons, 1993; Lombardi-Carlson et al.,2003; Driggers et al., 2004; Carlson et al., 2006; White & Sommerville, 2010). Age atmaturity is also a critical life-history parameter and a key determinant of the biologicalproductivity of a species (Smith et al., 1998).

This study aimed to describe the growth and maturity characteristics of A. pelagicusand S. lewini, two exploited and economically important large shark species caughtoff eastern Indonesia. Specifically, age was determined by counting growth bandsdeposited on sectioned vertebral centra and six deterministic growth models were fittedto the resulting length-at-age data and compared. Finally, using previously publishedreproductive data, the relationship between maturity stage and age was determinedusing logistic regression analysis (White et al., 2006, 2008).

MATERIALS AND METHODS

S A M P L E C O L L E C T I O NVertebrae were opportunistically collected between April 2001 and March 2006 from sharks

landed at one of the three Indonesian fish landing sites. Sampling was conducted throughout


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the Indonesian dry season (March to October). Each site was visited for 1–7 days on 21 occa-sions over the five-year sampling period. The landing site locations were Cilacap (Central Java),Kedonganan (Bali) and Tanjung Luar (Lombok) (White et al., 2006, 2008). Capture locationcould not be recorded as many boats did not use any location devices. All catches were fromIndonesian waters in the southern portion mostly adjacent to the Australian exclusive economiczone. Further information about the fish market sampling is provided in the studies of White(2007b), White et al. (2008) and White & Sommerville (2010). A vertebral section, consistingof two to six caudal vertebrae (centra), was collected from the region below the first dorsal-finof each specimen. The LT to the nearest mm, sex, stage of maturity (where possible) and methodof capture, e.g. longline or gillnets, were also recorded (White et al., 2008). Where LT could notbe recorded, precaudal (LPC) or fork lengths (LF) were measured and used to calculate LT usinglinear regressions obtained from previous LT measurements (White et al., 2008).

V E RT E B R A E P R E PA R AT I O N

The collected vertebrae were frozen until further processing and analysis. In the laboratory,vertebrae were thawed, excess muscle, connective tissue and neural and ventral arches wereremoved and individual centra were separated using a knife (Cailliet & Goldman, 2004; Gold-man, 2004; Cerna & Licandeo, 2009). Individual centra were soaked in a solution of 5% sodiumhypochlorite (bleach) for periods ranging from 15 to 120 min depending on the size of the verte-brae, to aid in the removal of intervertebral cartilage connective tissue on the corpus calcareum(Carlson & Baremore, 2005; Piercy et al., 2007), and then rinsed thoroughly under tap water.The cleaned vertebrae were then left to air dry for 1 day.

One whole centrum from each individual was embedded in clear casting resin for strengthand support when sectioning. The embedded centra were sectioned sagittally, cutting throughthe focus of the vertebrae (Cailliet & Goldman, 2004), using a low speed Gemmasta lapidary saw(www.shell-lap.com.au) fitted with a 150 mm × 0⋅06 mm pro-slicing diamond encrusted blade.The c. 0⋅6 mm section was washed in fresh water and then cleaned and wiped with alcohol. Thesection was then fixed to a clear glass slide using Permabond 720 (www.permabond.com) lowtemperature fast curing bonding adhesive. Each fixed section was then sanded and polished with240, 400 and 1200 grades of wet-and-dry sand paper. The average thickness of the post-sandedsections was 0⋅3 mm. The thin-cut sections were then viewed under a dissecting microscope(Olympus SZ-PT; www.olympus-ims.com) using transmitted light with varying magnifications(×1⋅0–×6⋅3) to accommodate the varying size range of the sections (Fig. 1).

Growth bands were counted on one half of each vertebral section. A single growth band wasdefined as including one fully formed opaque band and one fully formed translucent band (Gold-man, 2004) (Fig. 1). The angle of change along the corpus calcareum, which identifies a changein growth rate, was considered the birth mark for both species. As both species are known todeposit their first translucent band shortly after parturition, the first translucent band followingthe angle of change was considered as zero (Liu et al., 1999; Piercy et al., 2007). In Indone-sia, A. pelagicus does not have a synchronous cycle (White, 2007b). Consequently, birth canoccur throughout the year, and assuming synchronous deposition of growth bands (Liu et al.,1999), the age at first band (BAAF) is unknown. To account for the effects of non-seasonal repro-duction, the individual-adjusted analysis developed by Harry et al. (2010) was used to estimateBAAF. The first growth increment (IFG), or distance from the birth mark (B) to the first band, wasmeasured for all individuals with at least one completed band pair. The 97⋅5th percentile of theIFG distribution was assumed to represent the maximum extent of growth possible before the firstband is formed. The BAAF for individual animals was then calculated as BAAF = IFG IFGmax

−1,where IFGmax is the maximum extent of growth possible in the first year. The BAAF was thenadded to the counted number of growth bands. For S. lewini, which has a seasonal, synchronousreproductive cycle in Indonesia (White et al., 2008), partial ages were estimated by adjustingthe date of capture in relation to a theoretical birth date (Branstetter, 1987; Piercy et al., 2007;Kneebone et al., 2008). Since the birth date of S. lewini in Indonesian waters was estimated tobe between October and November (White et al., 2008), a theoretical birth date of 1 Novemberwas assigned for age estimations. To calculate partial age, date of capture and theoretical birthdate were converted to Julian days. The date of capture was subtracted from the 1 November(305 Julian days) and then divided by 365⋅25 days, giving a fraction of the final year, then added



(a) (b)

Fig. 1. Image of vertebral thin-cut section of (a) Alopias pelagicus (8 years old) and (b) Sphyrna lewini (11 yearsold) ( , translucent growth bands; , the birth band or age 0 years).

to the growth counts. If >1 year of age and if the date of capture was before the date of birth,one was added to the growth-ring count to allow for a length of growth after the last band.

Growth bands were counted by two readers on two occasions each, after being chosen at ran-dom, and without knowledge of the size, sex or maturity of the specimen (Bishop et al., 2006).Prior to undertaking the final two growth-band counts and to ensure reproducible counts, bothreaders independently counted the number of growth bands from a sub-set of at least 50 vertebraeuntil their average per cent error (APE) was considered constant, when subsequent counts didnot produce APE> 0⋅5% higher or lower than the previous APE (Beamish & Fournier, 1981).The final counts of both readers were then used for determining bias in counts between readers.In the final reading, counts that disagreed by ≥3 years between readers were read again. If finalcounts differ by >4 years and both readers could not agree on an appropriate age, the samplewas classified as unreadable and discarded. Most counts agreed to within 2 years and up to 4years age estimation difference between readers was considered acceptable in fishes aged 20years and above (Bishop et al., 2006). The final count of the primary reader was used as thefinal age estimate and to obtain growth rate parameters from the various growth models (Bishopet al., 2006).

P R E C I S I O N A N D B I A S

Several methods were used to estimate precision and bias according to Cailliet & Goldman(2004). The precision of band counts and reproducibility was calculated for all counts using theAPE (Beamish & Fournier, 1981) and the coefficient of variance (c.v.) (Chang, 1982). Withinand between reader bias was determined from per cent agreement (%A) (Cailliet, 1990), where%A= 100 nagreed nread

−1, and %A plus or minus 1 year (%A=±1 year) for LT groups of 10 cmto evaluate precision (Conrath & Musick, 2002). Bowker’s test of symmetry was used to testfor bias between intra- and inter-reader counts for both species (Hoenig et al., 1995; Evans &Hoenig, 1998).

V E R I F I C AT I O N

Two techniques of post-capture verification were used to measure the temporal periodicity ofthe band formation on the vertebrae (Goldman, 2004). Marginal increment ratio (RMI) is a ratioof the width of the last band to the outer edge of the centrum divided against the width of the


338 M . D R E W E T A L.

last fully formed growth band (Conrath & Musick, 2002). The measurements of growth bandswere made using a stage micrometer measuring 0⋅01 mm increments. Specimens under the ageof 1 year were not used for increment analysis because of the lack of fully formed growth bands(Goldman, 2004). Temporal variation of RMI was statistically tested using analysis of variance(ANOVA) or Kruskal–Wallis test, depending on whether the data were normally distributed andvariances were homogeneous, as determined by a Levene test. The centrum edge analysis (CEA)was used as an additional tool to verify the timing and frequency of growth band deposition(Goldman, 2004). During age determination, the edge of each centrum was classified as eitheropaque or translucent (Kusher et al., 1992).The proportion of opaque and translucent bands wasplotted against the month of capture for both species to determine seasonal changes in growth.

G ROW T H M O D E L SA multi-model inference (MMI) information theoretical approach was used to determine the

most appropriate growth model for each species (Burnham & Anderson, 2002; Katsanevakis &Maravelias, 2008). An a priori set of six candidate models were fitted to the LT-at-age data forS. lewini and A. pelagicus. The candidate set consisted of the traditional three-parameter vonBertalanffy (VBGM; von Bertalanffy, 1938), Gompertz (Gompertz, 1825; Ricker, 1975) andlogistic growth models (Ricker, 1979), along with their respective two-parameter (2P) equiv-alent (2P VBGM; 2P Gompertz; 2P logistic). In the two-parameter growth models, the LT atbirth (L0) and point of inflection (𝛼) was fixed at 1400 mm LT for A. pelagicus and 500 mm LTfor S. lewini, based on published LT at birth and the observed smallest recorded shark for theseregions (White, 2007b; White et al., 2008). Model parameters were estimated by non-linearleast squares in the statistical package R assuming additive normal error structure (R Devel-opment Core Team; www.r-project.org) and model performance was evaluated using the smallsample, bias adjustment form of the Akaike’s (1973) information criterion (AICc) (Burnham &Anderson, 2002; Katsanevakis & Maravelias, 2008). The best model was the one with the lowestAICc value. For model comparisons, the ΔAICc (ΔAICc) and Akaike’s weights (wi) were calcu-lated (Burnham & Anderson, 2002). Models with ΔAICc of 0–2 had substantial support, whilemodels with ΔAICc of 3–7 had considerably less support and models with ΔAICc > 10 hadessentially no support. Akaike’s weights (wi) represent the probability of choosing the correctmodel from the set of candidate models. The 95% c.i. around the best fit parameter estimateswere derived from 10 000 re-sampled data sets using the bias-corrected accelerated boot-strapmethod (Harry et al., 2011).

M AT U R I T YAge at maturity was calculated using maturity data published by White (2007b) and White

et al. (2008). Estimates of age at maturity were calculated as separate sexes (male and female)

using a logistic regression model (Walker, 2005): Pa =[1 + e− ln 19 (a−a50) (a95−a50)−1

]−1, where

Pa is the proportion of the population mature at age, a, where a50 and a95 are fitted parameterswhich correspond to the ages at which 50 and 95% of individuals are mature. A generalizedlinear model (GLM) with a binomial error structure and logit-link function was used to estimateparameters a50 and a95.

RESULTS

S A M P L E C O L L E C T I O N

Vertebral centra were collected from 159 A. pelagicus comprising 89 males(1400–3232 mm LT) and 70 females (1521–3252 mm LT ), and from 158 S. lewinicomprising 27 males (504–2399 mm LT), 128 females (498–2994 mm LT) and twounsexed individuals (2026–2829 mm LT). The number of bands could not be agreedon for three A. pelagicus and one S. lewini vertebrae and were, therefore, discarded.



P R E C I S I O N A N D B I A S

For A. pelagicus, the APE, c.v. and %A± 1 between the two counts of the primaryreader were 4⋅8, 6⋅8 and 83⋅3%, respectively. For S. lewini, the two counts of theprimary reader were more accurate, with an APE, c.v. and %A± 1 values of 1⋅7, 2⋅4and 98⋅7%, respectively. The Bowker’s test of symmetry showed no significant biasbetween the final counts of the primary reader for A. pelagicus (=61⋅7, P > 0⋅05) andS. lewini (=23⋅4, P > 0⋅05). For A. pelagicus, the APE, c.v. and %A± 1 values betweenthe final counts of both readers were 5⋅5, 7⋅8 and 80⋅5%, respectively. In S. lewini,the APE and c.v. values of 4⋅8 and 6⋅8 suggested a higher level of precision than in A.pelagicus. The %A± 1 (70⋅3%) of S. lewini was, however, lower than in A. pelagicus,but %A± 2 was high at 94⋅4%. The Bowker’s test of symmetry showed no signifi-cant bias between readers for A. pelagicus (=47⋅3, P > 0⋅05) and S. lewini (=33⋅0,P > 0⋅05).

V E R I F I C AT I O N

The homogeneity of variances for the RMI calculation was not significantly differentfor A. pelagicus (Levene test: F6,146 = 1⋅29, P> 0⋅05) or for S. lewini (Levene test:F8,142 = 1⋅62, P> 0⋅05). The RMI did not differ significantly between months for A.pelagicus (ANOVA: F6,146 = 0⋅68, P> 0⋅05) or for S. lewini (ANOVA: F8,142 = 1⋅19,P> 0⋅05) [Fig. 2(a), (b)]. CEA for A. pelagicus showed that the months with the mostvertebrae having a translucent or opaque last band were March (50%) and May (100%),respectively. For S. lewini, the month with the most vertebrae having a translucent lastband was April (20%), and the months with the most opaque last band were December(100%) and March (100%) [Fig. 2(c), (d)]. For both species, RMI values and centrumedge analysis were not obtained for several months due to a lack of vertebrae collectedfor these months. Additionally, a small number of vertebrae (e.g. one or three) wereonly collected for some months precluding a thorough investigation of the periodicityof growth band deposition. In the absence of a conclusively verified banding patternfor A. pelagicus and S. lewini, growth analysis proceeded with the assumption of anannual cycle (Liu et al., 1999; Piercy et al., 2007; Harry et al., 2011). The implicationsof this are examined further.

G ROW T H M O D E L S

The highest age estimation for male and female A. pelagicus was 24 years (3166 and3250 mm LT, respectively) [Fig. 3(a)–(c)]. The model of best fit to the length-at-ageestimations for both sexes combined was the three-parameter Gompertz model[Fig. 3(a), (b)] (Table I). The three-parameter logistic and VBGMs also providedstrong support to the length-at-age estimations with ΔAICc values of <2 and Akaike’sweight of 31 and 28%, respectively [Fig. 3(a) and Table I]. The strong support fromall the three-parameter growth models suggests no clear model of best fit (Table I).In both sexes and sexes combined, the three-parameter growth function fitted the databetter than the two-parameter model with fixed length at birth at 1400 mm LT, whilethe L0 estimated by the three-parameter models was over 1500 mm LT. The estimatedL∞ was similar to the observed maximum LT for the males and slightly higher for thefemales (Table I).


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Fig. 2. (a, c) Mean (•)± s.e. monthly marginal increment analysis (RMI; numbers at top of figure represent samplesizes) and (b, d) centrum edge analysis plotted against month of capture for (a, b) Alopias pelagicus and (c,d) Sphyrna lewini ( , monthly percentage of translucent centrum edge; , monthly percentage of opaquecentrum edge).

For S. lewini, the highest age estimate for males and females was 19 and 35 years,respectively (2399 and 2773 mm LT) [Fig. 3(d)–(f)]. The two and three-parameterGompertz growth models provided the best fit to the length-at-age estimations for thecombined sexes and females, with an Akaike’s weight of 49 and 63%, respectively,for the two-parameter model [Table II and Fig. 3(d)–(f)]. For males, the model of bestfit was the three-parameter Gompertz growth model (AICc weight= 52%) with lesssupport shown by other models [Fig. 3(f) and Table II]. The small number of samplesfor males prevented statistically testing for differences between sexes. The growthcurves of each sex, however, suggested some evidence of sexual dimorphism, withfemales over c. 10 years old being larger than males of the same age [Fig 3(f)]. Due tothe small number of males sampled, growth coefficient (k) and L∞ for the combinedsexes were mostly driven by female samples. The estimated L∞ for sex combined andfemales (2896 mm LT) was similar to the observed maximum length and biologicallyrealistic. The estimated k and L∞ for males were 0⋅15 and 2598 mm LT, and was lowerthan for females and combined sexes, but must be treated with uncertainty due to thelow sample size.

M AT U R I T Y

The LT, age and maturity data for A. pelagicus were available for 82 (1400–3232 mmLT) and 24 (1637–3212 mm LT) males and females. The youngest mature male and


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Fig. 3. Six growth models (based on total length, LT) for combined sexes of (a) Alopias pelagicus and (d) Sphyrnalewini. Model of best fit for (b) A. pelagicus (three-parameter Gompertz) and (e) S. lewini (two-parameterGompertz). Growth curve ( )with 95% c.i. ( ) and 95% prediction limits ( ) are presented. Male( ) and female ( ) growth curves from models of best fit for (c) A. pelagicus and (f) S. lewini.

female had estimated ages of 12 (2633 and 2969 mm LT) years for both sexes (White,2007b). The estimated age of the oldest immature male and female A. pelagicus was 17and 13 (3055 and 2825 mm LT) years. The estimated a50 and a95 for males were 10⋅4and 16⋅2 years and for females were 13⋅2 and 15⋅0 years [Fig. 4(a), (b) and Table III](White, 2007b).

Age-at-maturity for S. lewini was estimated from data consisting of 23(504–2399 mm LT) males and 72 (982–2994 mm LT) females. The youngest maturemale and female had estimated ages of 8 and 11 years (1761 and 2205 mm LT) (Whiteet al., 2008). The estimated age of the oldest immature male and female S. lewini was8 and 16 (1700 and 2305 mm LT) years . The estimated a50 and a95 for males were 8⋅9and 9⋅6 years and for females was 13⋅2 and 18⋅4 years [Fig. 4(c), (d) and Table III](White et al., 2008).


342 M . D R E W E T A L.

Tab

leI.

Six

grow

thm

odel

sfit

toto

tal

leng

th(L

T)-

at-a

geda

taof

Alo

pias

pela

gicu

sfr

omth

eea

ster

nIn

dian

Oce

an.

Mod

elof

best

fit(b

old)

has

the

low

estv

alue

ofA

kaik

ein

form

atio

ncr

iteri

on(A

IC)

Sex

Mod

elA

ICΔ

w(%

)R

.S.E

.L∞

c.i.

L0

95%

c.i.

𝛼95

%c.

i.k

95%

c.i.

Com

bine

dse

xV

B3

1960

0⋅55

828⋅0

814

3⋅8

3308

(320

4–

3434

)15

16(1

423

–15

97)

0⋅11

5(0⋅0

96–

0⋅13

7)n=

153

VB

219

644⋅

63⋅

7214

6⋅2

3244

(316

2–

3340

)0⋅

133

(0⋅1

17–

0⋅14

9)G

OM

319

590

37⋅1

114

3⋅6

3236

(314

3–

3347

)15

48(1

459

–16

27)

0⋅15

1(0⋅1

27–

0⋅17

2)G

OM

219

699⋅

624

0⋅3

148⋅

731

68(3

105

–32

41)

0⋅17

9(0⋅1

62–

0⋅19

7)L

OG

I319

590⋅

378

30⋅7

714

3⋅8

3187

(312

1–

3275

)15

75(1

496

–16

50)

0⋅18

7(0⋅1

63–

0⋅21

1)L

OG

I219

7616⋅4

90⋅

0115

231

17(3

056

–31

80)

0⋅23

(0⋅2

11–

0⋅24

9)M

ale

VB

310

730⋅

857

24⋅0

612

9⋅3

3267

(315

8–

3456

)15

16(1

422

–16

15)

0⋅12

7(0⋅0

97–

0⋅15

4)n=

85V

B2

1076

3⋅90

55⋅

2413

2⋅4

3213

(312

7–

3311

)0⋅

145

(0⋅ 1

26–

0⋅16

9)G

OM

310

720⋅

233

32⋅8

512

8⋅8

3209

(312

5–

3327

)15

46(1

455

–16

31)

0⋅16

3(0⋅1

35–

0⋅19

0)G

OM

210

797⋅

578

0⋅84

135⋅

231

55(3

083

–32

39)

0⋅19

1(0⋅1

71–

0⋅21

5)L

OG

I310

720

36⋅9

212

8⋅6

3169

(309

9–

3262

)15

70(1

481

–16

59)

0⋅2

(0⋅1

73–

0⋅22

8)L

OG

I210

8411⋅8

50⋅

113

8⋅7

3115

(305

3–

3178

)0⋅

241

(0⋅2

18–

0⋅26

9)Fe

mal

eV

B3

886⋅

20⋅

391

23⋅0

715

7⋅7

3359

(317

0–

3725

)15

13(1

323

–16

68)

0⋅10

4(0⋅0

66–

0⋅14

2)n=

68V

B2

885⋅

80

28⋅0

515

8⋅4

3281

(313

9–

3497

)0⋅

121

(0⋅0

97–

0⋅14

7)G

OM

388

6⋅3

0⋅54

821⋅3

315

7⋅9

3273

(312

9–

3498

)15

54(1

396

–16

89)

0⋅13

7(0⋅1

03–

0⋅17

5)G

OM

288

82⋅

178

9⋅44

161

3183

(307

5–

3318

)0⋅

167

(0⋅1

45–

0⋅19

4)L

OG

I388

6⋅9

1⋅09

416⋅2

315

8⋅6

3218

(309

5–

3417

)15

90(1

433

–17

31)

0⋅17

(0⋅1

33–

0⋅21

5)L

OG

I289

1⋅2

5⋅40

11⋅

8816

4⋅8

3120

(303

2–

3226

)0⋅

218

(0⋅1

93–

0⋅24

5)

n,sa

mpl

esi

ze;w

(%),

AIC

cw

eigh

ts;Δ

,ΔA

ICc

valu

es;R

.S.E

.,re

sidu

alst

anda

rder

ror;

L∞

,asy

mpt

otic

LT;L

0,L

Tat

birt

h;𝛼

,poi

ntof

infle

ctio

nfo

rth

elo

gist

icm

odel

s;k,

grow

thco

effic

ient

;V

B(2

and

3pa

ram

eter

),vo

nB

erta

lanf

fy;G

OM

(2an

d3

para

met

er),

Gom

pert

z;L

OG

(2an

d3

para

met

er),

logi

stic

.



Tab

leII

.Si

xgr

owth

mod

els

fitto

leng

th-a

t-ag

eda

taof

Sphy

rna

lew

inif

rom

the

east

ern

Indi

anO

cean

.Mod

elof

best

fit(b

old)

has

the

low

estv

alue

ofA

kaik

ein

form

atio

ncr

iteri

on(A

IC)

Sex

Mod

elA

ICΔ

w(%

)R

.S.E

.L∞

95%

c.i.

L0

95%

c.i.

𝛼95

%c.

i.k

95%

c.i.

Com

bine

dse

xV

B3

2021

14⋅6

500⋅

0316

8⋅6

3113

(298

3–

3282

)44

8(3

69–

524)

0⋅09

0(0⋅0

79–

0⋅10

1)n=

154

VB

220

2114⋅1

700⋅

0416

8⋅9

3141

(301

7–

3305

)0⋅

086

(0⋅0

77–

0⋅09

5)G

OM

320

070⋅

393

40⋅6

116

129

18(2

816

–30

25)

542

(480

–60

4)0⋅

152

(0⋅1

38–

0⋅16

7)G

OM

220

070⋅

000

49⋅4

316

1⋅3

2896

(280

9–

2989

)0⋅

159

(0⋅1

49–

0⋅16

8)L

OG

I320

103⋅

224

9⋅86

162⋅

528

21(2

747

–29

00)

613

(554

–67

3)0⋅

219

(0⋅2

01–

0⋅23

7)L

OG

I220

2215⋅0

600⋅

0316

9⋅4

2761

(268

9–

2833

)0⋅

251

(0⋅2

39–

0⋅26

0)M

ale

VB

330

3⋅4

3⋅71

28⋅

1975⋅4

730

50(2

733

–35

22)

519

(454

–56

9)0⋅

075

(0⋅0

57–

0⋅09

5)n=

26V

B2

301⋅

82⋅

111

18⋅ 2

374⋅4

529

89(2

689

–33

41)

0⋅07

9(0⋅0

64–

0⋅09

7)G

OM

329

9⋅7

0⋅00

052⋅3

870⋅2

725

98(2

442

–27

95)

568

(512

–61

4)0⋅

155

(0⋅1

35–

0⋅18

1)G

OM

230

4⋅6

4⋅91

64⋅

4878⋅5

824

81(2

339

–26

25)

0⋅18

0(0⋅1

63–

0⋅20

4)L

OG

I330

22⋅

285

16⋅7

173⋅4

324

46(2

331

–26

03)

608

(565

–65

0)0⋅

235

(0⋅2

08–

0⋅26

6)L

OG

I231

6⋅4

16⋅6

700⋅

0198⋅5

222

98(2

192

–24

14)

0⋅29

6(0⋅2

72–

0⋅32

3)Fe

mal

eV

B3

1663

11⋅1

100⋅

2417

4⋅4

3075

(294

0–

3245

)43

9(3

26–

546)

0⋅09

5(0⋅0

83–

0⋅10

8)n=

126

VB

216

6210⋅2

000⋅

3817

4⋅5

3097

(295

9–

3248

)0⋅

091

(0⋅0

83–

0⋅10

2)G

OM

316

541⋅

520

29⋅1

616

7⋅9

2909

(279

8–

3016

)53

2(4

42–

625)

0⋅15

6(0⋅1

41–

0⋅17

7)G

OM

216

520⋅

000

62⋅3

516

7⋅5

2896

(281

7–

2990

)0⋅

161

(0⋅1

52–

0⋅17

2)L

OG

I316

564⋅

288

7⋅31

169⋅

828

23(2

743

–29

10)

613

(534

–69

8)0⋅

222

(0⋅1

99–

0⋅24

3)L

OG

I216

629⋅

412

0⋅56

173⋅

927

73(2

698

–28

52)

0⋅25

2(0⋅2

42–

0⋅26

4)

n,sa

mpl

esi

ze;w

(%),

AIC

cw

eigh

ts;Δ

,ΔA

ICc

valu

es;R

.S.E

.,re

sidu

alst

anda

rder

ror;

L∞

,asy

mpt

otic

LT;L

0,L

Tat

birt

h;𝛼

,poi

ntof

infle

ctio

nfo

rth

elo

gist

icm

odel

s;k,

grow

thco

effic

ient

;V

B(2

and

3pa

ram

eter

),vo

nB

erta

lanf

fy;G

OM

(2an

d3

para

met

er),

Gom

pert

z;L

OG

(2an

d3

para

met

er),

logi

stic

.


344 M . D R E W E T A L.

1·0 (a)

(b) (d)

(c)

Prop

ortio

n m

atur

e0·8

0·6

0·4

0·2

0

1·0

0·8

0·6

0·4

0·2

0

Age (years)5 10 15 20 25 30 350 5 10 15 20

Fig. 4. Maturity curves of (a) male and (b) female Alopias pelagicus and (c) male and (d) female Sphyrna lewini.Logistic curve ( ) with 95% c.i. ( ) are presented.

DISCUSSION

This study provides age, growth and age-at-maturity estimates of two commerciallyimportant large shark species, A. pelagicus and S. lewini, and represents the firstestimates for populations from the eastern Indian Ocean. This study estimated andcompared growth parameters from three growth models, and used AIC to identifythe most parsimonious model. The findings suggest that both species are likely to belong-lived and relatively slow growing for medium-sized shark species (Cailliet &Goldman, 2004). This study showed that A. pelagicus and S. lewini populations from

Table III. Estimated age at maturity (a50 and a95) for Alopias pelagicus and Sphyrna lewinifrom the eastern Indian Ocean compared with published length-at-maturity (L50 and L95) data

for both species in the eastern Indian Ocean (White, 2007b; White et al., 2008).

Species Sex a50 95% c.i. a95 95% c.i. L50 95% c.i. L95 95% c.i.

A. pelagicus Male 10⋅38 (9⋅17–11⋅63)

16⋅23 (13⋅02–19⋅65)

2648 (2601–2685)

2802 (2773–2870)

Female 13⋅24 (12⋅15–14⋅28)

14⋅99 (12⋅23–16⋅61)

2853 (2764–2900)

2976 (2795–3045)

S. lewini Male 8⋅92 (6⋅45–10⋅43)

9⋅60 (6⋅76–10⋅67)

1756 (1731–1798)

1762 (1738–1804)

Female 13⋅15 (11⋅96–14⋅44)

18⋅42 (15⋅19–21⋅60)

2285 (1781–2332)

2339 (1797–2402)



the eastern Indian Ocean have similar growth trajectories to shark populations fromother regions, it also included the oldest samples of A. pelagicus and S. lewini yetrecorded (Liu et al., 1999; Piercy et al., 2007; Harry et al., 2011). The inclusion of oldsharks within the sample increased confidence in the accuracy of the growth trajecto-ries by making it possible to empirically determine the age at which asymptotic growthis reached. Additionally, this study provided the first statistically derived estimates ofage at maturity of both sexes of A. pelagicus and female S. lewini. The slow life-historyparameters obtained from this study, coupled with evidence of declines in other partsof their range (Baum et al., 2003; Liu et al., 2006), indicate that A. pelagicus and S.lewini from this region could be susceptible to overexploitation. This is of concernconsidering the magnitude of catches of both species from the eastern Indian Oceanregion (White, 2007b; White et al., 2008) and lack of specific management measuresfor elasmobranch fisheries (Blaber et al., 2009).

A L O P I A S P E L AG I C U S

The highest observed growth counts were estimated for A. pelagicus, with estimatedages of 24 years for both males and females. The estimated bias was low and precisionin repeatable counts was high between and within readers. The RMI for A. pelagicusshowed no significant monthly variation, and the pattern of band deposition did notsuggest clear annual growth bands formation. A previous study, however, identifiedannual band deposition in June and July (Liu et al., 1999). This discrepancy wasprobably due to the difficulty in classifying the edges of the corpus calcareum, andthe small sample sizes in any particular month, with samples not obtained for somemonths of the year (Cailliet, 1990). The RMI analysis is best performed on sharkswith well-defined banding patterns or on a younger age class (Campana, 2001), oftenresulting in the removal of older sharks with tight band cluster on the outer edge of thecentrum from the sample set (Allen & Wintner, 2002). It has also been recommendedthat RMI calculations be done on juveniles <4 years old only (Killam & Parsons, 1989;Neer & Thompson, 2005). Due to the limited number of vertebrae available, this wasnot feasible in this study.

The only previous study estimating age and growth parameters for A. pelagicuswas undertaken using thin-cut sections of vertebrae collected from sharks caught inTaiwanese waters (Liu et al., 1999). Growth curves for sexes combined were similarbetween the two studies [Fig. 5(a)] but the estimated growth coefficients of sharksfrom Taiwan were slightly lower than in this study (Table IV). The L∞ for A. pelagicusfrom Taiwan, especially for females, was also substantially larger than the presentestimate. Growth trajectories between sexes appeared to be similar, concurring withthe north-west Pacific population [Fig. 5(a)] (Liu et al., 1999), and suggests thatsexual dimorphism does not occur in this species. In contrast, growth trajectoriesof other Alopias species suggest some differences in the growth coefficient betweensexes, although these were not statistically tested (Liu et al., 1998; Smith et al., 2008;Gervelis & Natanson, 2013).

The a50 of males and females from the eastern Indian Ocean (10 and 13 yearsfor males and females, respectively) was higher than the a50 of A. pelagicus fromTaiwanese waters (7–8 and 8–9 years for males and females) (Liu et al., 1999).Using life-history characteristics from sharks caught in the north-west Pacific (Liuet al., 1999), A. pelagicus was assessed as having a very low annual rate of population


346 M . D R E W E T A L.

Table IV. von Bertalanffy growth model parameters of (a) Alopias pelagicus and (b) Sphyrnalewini from the present and previous studies

(a)

Author Sex n L∞ (mm) k

Growthband

per year Location

This study Male 85 3267 0⋅127 1 Eastern IndianOcean

Female 68 3359 0⋅104Combined 153 3308 0⋅115

Liu et al. (1999) Male 114 3470 0⋅12 1 North-west PacificFemale 155 3830 0⋅09

(b)

Author Sex n L∞ (mm) k

Growthband

per year Location

This study Combined 154 3113 0⋅09 1 Eastern IndianOcean

Harry et al. (2011) Combined 392 3305 0⋅077 1 Eastern AustraliaKotas et al. (2011) Male 115 2660 0⋅05 1 Southern Brazil

Female 116 3000 0⋅05Tolentino et al.

(2008)Male 65 3640 0⋅12 2 Eastern Pacific,

Sinaloa,Female 44 3760 0⋅1 Mexico

Piercy et al.(2007)

Male 191 2784 0⋅13 1 Western NorthAtlantic and

Female 116 3021 0⋅09 Gulf of MexicoTolentino &

Mendoza(2001)

Male 50 3364 0⋅13 2 Pacific Mexicancoast

Female 51 3533 0⋅16Chen et al. (1990) Male 49 3206 0⋅22 2 North-west Pacific

Female 276 3197 0⋅25Branstetter (1987) Combined 25 3290 0⋅07 1 Gulf of Mexico

n, number of centrum samples; k, growth coefficient; L∞, theoretical maximum total length.

increase of 0⋅033 (Liu et al., 2006; Dulvy et al., 2008) and being ‘extremely vulner-able to overexploitation’ (Tsai et al., 2010). This concurred with a previous studyindicating that the A. pelagicus stock off Taiwan was overexploited under the currentfishing pressure (Liu et al., 2006). Overall, thresher sharks Alopias spp. have beenlisted as Vulnerable globally because of their low resilience to fishing pressure anddeclining populations (Amorim et al., 2009; Goldman et al., 2009; Reardon et al.,2009). Thresher sharks were also ranked at the highest risk of overfishing among 12pelagic sharks and rays investigated (Cortés et al., 2010), while A. pelagicus had thesecond lowest annual rate of population increase out of 11 pelagic species (Dulvyet al., 2008). The recognition of the vulnerability of alopids to overfishing and theincreasing international concerns for the conservation status of this group of sharks



LT (

mm

)

(b)3500

3000

2500

2000

1500

1000

500

0

(c)3500

3000

2500

2000

1500

1000

500

0

Age (years)0 5 10 15 20 25 30 35

3500 (a)

3000

2500

2000

1500

1000

500

0

Fig. 5. Comparison of (a) Alopias pelagicus and (b, c) Sphyrna lewini growth curves (based on total length, LT)from previous and current studies. (a) Liu et al. (1999) von Bertalanffy growth curves for males ( ) andfemales ( ) and growth curves from the eastern Indian Ocean (this study) based on the models of bestfit for males ( ) and females ( ). (b) Growth curves from previous S. lewini age and growth stud-ies converted to assume annual band deposition. Growth curves from previous studies that assume annualband deposition (including this study) ( ) and previous studies that required a modification to assumeannual band deposition ( ) are given. (c) Comparison of growth curves based on the models of best fitfor Australian and eastern Indian Ocean populations for S. lewini: combined sex and region growth curvefor Australia ( ), male temperate growth curve ( ) and the tropical male growth curve ( ). The vonBertalanffy growth curve for combined sexes for the eastern Indian Ocean S. lewini growth curve is alsogiven (—).


348 M . D R E W E T A L.

led the IOTC adopting a ban on fishing for all alopids. The later age at maturity of theeastern Indian Ocean A. pelagicus population is likely to make those sharks even moresusceptible to overexploitation. This coupled with high catches landed in Indonesiahighlights concerns for the status of this species in the eastern Indian Ocean and theneed for monitoring of catches and stock status to ensure the long-term sustainabilityof the fishery.

S P H Y R NA L E W I N I

The highest growth band counts for S. lewini were estimated, with age estimationsof 35 years for females and 19 years for males. The precision was high and bias wasconsidered low, with no evidence of systematic bias in between or within reader counts.Similar to A. pelagicus, the two post capture forms of verification RMI and CEA couldnot assess the periodicity of growth band deposition. This was also probably due tolimited sample size and absence of samples during parts of the year. The lack of suc-cess in validating the banding patterns for S. lewini hampered the results of previousage and growth studies, leading to uncertainty surrounding growth estimates in thisspecies (Chen et al., 1990; Tolentino & Mendoza, 2001; Piercy et al., 2007, 2010;Harry et al., 2011). Most recent studies (Piercy et al., 2007, 2010; Harry et al., 2011)have, however, assumed annual growth-band deposition based on validation for twoother Sphyrna species using bomb radiocarbon and calcein validation methods (Par-sons, 1993; Passerotti et al., 2010), and evidence for annual bands found in many otherchondrichthyan growth studies, e.g. bonnethead shark Sphyrna tiburo (L. 1758) (Par-sons, 1993; Carlson & Parsons, 1997), blacknose shark Carcharhinus acronotus (Poey1860) (Driggers III et al., 2004), great hammerhead Sphyrna mokarran (Rüppel 1837)(Piercy et al., 2010; Passerotti et al., 2010), tiger shark Galeocerdo cuvier (Péron &LeSeuer 1822) (Kneebone et al., 2008), sandbar shark Carcharhinus plumbeus (Nardo1827) (Romine et al., 2006) and silky shark Carcharhinus falciformis (Müller & Henle1839) (Joung et al., 2008; Hall et al., 2012). Nonetheless, recent validation studieshave also confirmed that bands can form biannually in some species (Wells et al.,2013), irregularly in others (Huveneers et al., 2013) and can in some instances greatlyunderestimate true age (Kerr et al., 2006; Andrews et al., 2011; Natanson et al., 2013;Hamady et al., 2014). Incorrectly specifying the frequency of growth band deposi-tion (e.g. annual instead of biannual) can effectively lead to a halving or doubling of k.This has implications for the accuracy of demographic models that use these estimates,which can then affect the proceeding management and conservation measures. As such,validation of growth in S. lewini should be considered a high priority. A greater samplesize covering all months of the year or validation using fluorescent or bomb radiocar-bon would be necessary to confirm annual band deposition in S. lewini from the easternIndian Ocean. Although this could not be obtained from this study, it is assumed anannual band deposition, following Harry et al. (2011).

Age and growth studies often use samples obtained from commercial fishing oper-ations, which can be biased and poorly represent the targeted population (Thorson &Simpfendorfer, 2009). In many previous studies on S. lewini and other Sphyrna species,strong sex segregation has been evident (Klimley, 1987; Harry et al., 2011). For the firsttime, sex bias in this study was towards sexually mature females, which are commonlylacking in previous biological studies on S. lewini. Although this prevented the useof a statistical test for sexual dimorphism in growth trajectories, growth models were



applied to sexes combined and separated to allow for qualitative comparison betweensexes within the eastern Indian Ocean and with other regions.

If all growth studies on S. lewini are assumed to have annual band formation, interspe-cific growth estimates are relatively similar throughout this species range (Branstetter,1987; Chen et al., 1990; Piercy et al., 2007; Tolentino et al., 2008; Harry et al., 2011)[Fig. 5(b)]. Although Harry et al. (2011) identified dimorphism in growth of male S.lewini from northern and eastern Australia, when samples were pooled between sexes,growth estimates from that study are very similar to this study [Fig. 5(c)]. Direct com-parisons between growth trajectories from this study and Harry et al. (2011) should bemade with care because of the strong opposite sex bias in the two studies.

The estimated a50 of S. lewini from the eastern Indian Ocean of 9 and 13 years formales and females are higher than previously obtained estimates (Chen et al., 1990;Harry et al., 2011). Although age at maturity as low as 3⋅8 for males and 4⋅l for femaleshave been reported from S. lewini caught off Taiwan (Chen et al., 1990), such low val-ues are probably related to the hypothesized biannual band formation that effectivelyhalves age-at-maturity estimations. Doubling their estimates to account for the pre-sumed biannual band formation (7⋅6 and 8⋅2 years for males and females) still result inage at maturity lower than estimates from this study. Age at maturity of male S. lewinifrom tropical Australia is 5⋅7 years (5⋅1–6⋅2, 95% c.i.) (Harry et al., 2011) and does notoverlap with the 95% c.i. from this study (6⋅4–10⋅4). Age at maturity from Indonesiawas, however, based on 23 males, and should be used with caution.

The observed differences in age-at-maturity estimates could be linked to variationsin life-history characteristics between S. lewini populations or through selected lifestrategies (pelagic v. coastal) (Harry et al., 2011). The variability of life-history traitsbetween populations has been demonstrated in a few species, with the increase ingrowth rates, LT or age at maturity and the size of near-term embryos having previ-ously been positively correlated with latitude (Parsons, 1993; Yamaguchi et al., 2000;Horie & Tanaka, 2002; Lombardi-Carlson et al., 2003; Harry et al., 2011) and may, inpart, reflect elasticity of these traits as well as sample size robustness. This highlightsthe importance of establishing life-history parameters for each population, as assump-tions of life-history traits established from other populations could lead to impropermanagement and overexploitation. In the Indo-Pacific populations, molecular evidencesuggests some level of intermixing between stocks of S. lewini from Indonesia andnorthern Australia, but the sampling represented a relatively small part of their distribu-tional range (Ovenden et al., 2009). Further investigation into the genetic partitioningof the Indo-Pacific S. lewini populations is, however, recommended to improve under-standing of the geographic extent of S. lewini populations that fisheries managementneed to account for when monitoring and regulating catches of this species.

Comparison between male growth and maturity suggests considerable variability inlife-history characteristics of the three Indo-Pacific populations sampled [Fig. 5(c)].A striking similarity is noteworthy, however, in von Bertalanffy growth curves from thetwo regions when data from both sexes are combined [Fig. 5(c)]. It is unknown whetherthis similarity in growth is a coincidence, but it is consistent with a genetic studysuggesting that Indonesian and Australian stocks of S. lewini are shared and requirejoint management (Ovenden et al., 2009).

This study provides the first age, growth and age-at-maturity estimates for two com-mercially important large shark species that are targeted along with other large inshoreand pelagic species and suffer high levels of fishing mortality within the eastern Indian


350 M . D R E W E T A L.

Ocean (Blaber et al., 2009; White, 2007b; White et al., 2006, 2008). Both speciesexhibit slow rates of growth and late age at maturity, highlighting the potential vul-nerability of A. pelagicus and S. lewini within the eastern Indian Ocean region, andthe need to assess their resilience to the current level of fishing pressure. The resultsfrom this study will provide crucial information to parameterize demographic mod-els of these species, which is critical considering the high levels of exploitation in theeastern Indian Ocean (Blaber et al., 2009; White & Sommerville, 2010).

The authors would like to thank the Flinders University Marine Ecology research group,particularly P. Fairweather and the Marine Scalefish subprogramme of the South AustralianResearch and Development Institute (SARDI) – Aquatic Sciences for their in-kind support. J.Hildrich is thanked for her assistance with the secondary counts of samples. Samples were col-lected with the help of the Indonesian Department of Marine and Fisheries Affairs. A specialthanks go to Fahmi and J. Giles for their assistance in the field throughout the project. Thanksare also expressed to S. Blaber, P. Last, J. Stevens, J. Salini, R. Pillans, A. Graham, C. Dichmont,O. Kurnaen Sumadhiharga (LIPI) and S. Nurhakim (Research Centre for Fisheries Managementand Conservation) for help in this project. Financial support was provided by the AustralianCentre for International Agricultural Research (ACIAR) and Murdoch University.

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Age, growth and maturity of the pelagic thresher Alopias pelagicus and the scalloped hammerhead Sphyrna lewini