Fisheries Research 129 130 (2012) 46 60

Contents lists available at SciVerse ScienceDirect

Fisheries Research

jou rn al h om epa ge: www.elsev ier .com

Age-ba proScombe ter

Stephen Western Austra of We

a r t i c l

Article history:Received 14 FeReceived in reAccepted 8 Jun

Keywords:Sectioned otolithsFishing mortalityKimberleyPilbaraGascoyneScombridaeProductivityFisheries man

mers thisure a(WA)orma

is formed each year. Juvenile S. commerson of undifferentiated sex (n = 67; 58709 mm FL) ranged inage from 23 days to 350 days. Males (n = 1239; 3011381 mm FL) ranged in age from 80 days to 22 yrs,and females (n = 1273; 3961720 mm FL) ranged in age from 122 days to 18 yrs. Signicant differentialgrowth was evident between sexes, with females attaining a larger size-at-age than males. Initial growthof S. commerson is rapid with both sexes reaching maturity within 1.5 yrs of age. Growth parametersalso differed among regions. The instantaneous rate of natural mortality (M) was estimated to be in therange of 0.160.20 yr1. The instantaneous rate of total mortality (Z) estimated from catch at age data

1. Introdu

Spanish ish mackervaluable, trthroughoutational and2001). In Auof commerjurisdiction(WA) coast,of latitude (15 and 200

In WA, Sally marketusually fres

CorresponE-mail add

0165-7836/$ http://dx.doi.oagement for fully recruited age classes, was different between sexes and among regions. Signicant differences indemography, age structure and otolith readability among management regions support earlier studiesthat have documented meta-population structure in S. commerson and underpin the regional manage-ment regime for this species in Western Australia. Populations of S. commerson have a high productionpotential given their rapid initial rate of growth and low age at maturity. Despite this high productionpotential, productivity of this species in WA is relatively low compared to related sheries throughoutthe Indo-Pacic region.

Crown Copyright 2012 Published by Elsevier B.V. All rights reserved.

ction

mackerel (often referred to as narrow-barred Span-el), Scomberomorus commerson (Lacepede) are large,opical pelagic sh in the Scombridae that are targeted

the Indo-West Pacic region by commercial, recre- artisanal shers (Collette and Nauen, 1983; Collette,stralian waters, S. commerson is the main target speciescial and recreational troll-based sheries spanning 4s (3 states and 1 territory). Along the Western Australian

S. commerson is widely distributed across more than 16

1329). They inhabit coastal waters at depths between m (Collette, 2001).. commerson is a highly valued food sh that is gener-ed as frozen llets, or as trunks (headed and gutted)h on ice depending on the region where it is caught. It is

ding author. Tel.: +61 8 9203 0111; fax: +61 8 9203 0199.ress: Stephen.Newman@sh.wa.gov.au (S.J. Newman).

transported from regional centres in the northern part of the Stateto wholesale markets in local capital cities (Perth and Darwin) andinterstate to markets on the east coast of Australia. In the Mack-erel Fishery of WA that extends across three management regions(Area 1 Kimberley; Area 2 Pilbara; Area 3 Gascoyne/WestCoast; Fig. 1), S. commerson is the main target species and in 2010comprised over 96% (284 metric tonnes) of the total landed catchof mackerel (Molony et al., 2011).

A plethora of demographic parameter estimates are avail-able for S. commerson (Devaraj, 1981; Kasim and Ameer Hamsa,1989; McPherson, 1992; Grandcourt et al., 2005; McIlwain et al.,2005; Ballagh et al., 2006; Shojaei et al., 2007). Divergent esti-mates of demographic parameters among studies are largely dueto the method of age estimation (e.g. length frequency Kasimand Ameer Hamsa, 1989; Shojaei et al., 2007; whole otoliths Devaraj, 1981; McPherson, 1992; sectioned otoliths Buckworth,1998; Grandcourt et al., 2005; McIlwain et al., 2005; otolith back-calculations Ballagh et al., 2006). Validation of annual growthincrements consisting of alternating translucent and opaque bandsin thin otolith sections has been reported by Grandcourt et al.

see front matter. Crown Copyright 2012 Published by Elsevier B.V. All rights reserved.rg/10.1016/j.shres.2012.06.006sed demography and relative sheries romorus commerson (Lacepede) in Wes

J. Newman , Michael C. Mackie, Paul D. Lewislian Fisheries and Marine Research Laboratories, Department of Fisheries, Government

e i n f o

bruary 2012vised form 6 June 2012e 2012

a b s t r a c t

Spanish mackerel, Scomberomorus comout the Indo-West Pacic region. Incomprehensive study of otolith structregions along the Western Australian a single annual peak in opaque zone f/ locate / f i shres

ductivity of Spanish mackerel,n Australia

stern Australia, P.O. Box 20, North Beach, WA 6920, Australia

on, is a species of economic and artisanal importance through- study a total of 2973 S. commerson were examined in and demographic characteristics across multiple management

coast. Marginal increment analysis of sagittal otoliths showedtion indicating that one opaque and translucent band (annuli)

ASUSHighlight

S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60 47

Fig. 1. Biolog

(2005) and for managebias in the e

Despite forms severregion. Acrostocks of S. res Strait sto2007). Thes(Indonesia)2011). Aparother distinarchipelago2011). Wallfrom Sulawstrongly imrating S. comOvenden, 2

Althoughadult populments and spatial scalet al., 2007merson acrmetapopulahomogeneoat least, condemes) tha(Lester et aNewman etern of mixAustralia (Wmetapopulademograph

sustainable management arrangements for Scomberomorus sh-eries in Western Australia.

The objective of this study was to determine the age-specicraphy of S. commerson among management regions along

coa and

ers oecic

struemeantif

parose

teria

llect

plesariouackery b CaFig. ionamend recrnenturvend (is anpled

mm)an watus hodsemovical sample collection regions and areas around Western Australia.

McIlwain et al. (2005). In order to derive accurate advicement, sectioned otoliths should ideally be used to avoidstimation of age-based demographic parameters.being a highly mobile pelagic species, S. commersonal distinct genetic stocks throughout the Indo-Pacicss northern Australia there are three distinct genetic

demogthe WAgrowthin watThe spthe agemanag(iii) qu(iv) comwith th

2. Ma

2.1. Co

Samfrom vWA mTerritoCoast Coast; recreattournacial ancompocatch-cyses; aanalys

Sam(FL) inand cletive stto metwere rcommerson; a northern/western Australia stock, a Tor-ck, and an east coast Australian stock (Buckworth et al.,e stocks were all distinct from a TimorWest Papua

stock (Buckworth et al., 2007; Fauvelot and Borsa,t from these distinct genetic stocks of S. commerson,ct stocks have been identied in the Indo-Malay-Papua, Bali-Java and New Caledonia (Fauvelot and Borsa,aces Line (i.e. separating Borneo, Philippines and Bali,esi, Lombok, New Guinea and Australia) has beenplicated as a major biogeographical boundary sepa-merson populations across Australasia (Sulaiman and

010). there is a single northwestern Australian genetic stock,ations within this genetic stock exhibit limited move-represent functionally distinct assemblages over nees (Lester et al., 2001; Moore et al., 2003; Buckworth; Newman et al., 2009). The stock structure of S. com-oss northern Australia can therefore be dened as ation; that is, although the populations are relativelyus genetically, the northern/western Australia stocksists of a mosaic of small assemblages (substocks or

t, during the adult phase at least, show little mixingl., 2001; Moore et al., 2003; Buckworth et al., 2007;t al., 2009). This is in contrast to the extensive pat-ing that S. commerson exhibits on the east coast ofilliams and Lester, 2006). The northern Australian

tion structure thus predicates a need for region-specicic parameters to be derived in order to underpin

to storage was subseqposterior toThe left otoFor counts taining thediamond bmordium athickness 1collection aLewis and M

2.2. Interpr

Terminolows that ogrowth incrsame readethe primording (Fig. 2awas made. of the two cdiffered by average miyear to allo

Annual nating opaThe primast. This study is the rst detailed investigation of the age, mortality characteristics of populations of S. commersonff the coast of WA using thin sectioned sagittal otoliths.

aims of this study were to (i) describe and comparecture and growth rates of S. commerson between thesent regions; (ii) validate the nature of growth increments;y mortality rates for each region using catch curves; ande the relative productivity of this species in WA watersof related sheries in the Indo-Pacic region.

ls and methods

ion and processing of samples

of S. commerson were collected between 1998 and 2002s locations within three management regions in the

rel shery (Kimberley east of 120E to the Northernorder, Pilbara 114E to 121E, and Gascoyne/Westpe Leeuwin to 114E, hereafter referred to as West1). Fresh samples were collected onboard commercial,l and research vessels, and from recreational shingts. Frozen samples were also collected from commer-eational shers. Sampling effort involved three primarys; (i) sampling to collect representative samples for

analysis; (ii) monthly sampling for otolith margin anal-iii) targeted collection of juveniles for daily incrementd growth curve estimation.

sh were measured (total length (TL) and fork length and, where possible, weighed to 0.1 kg (whole weighteight [viscera and gonads removed]). Sex and reproduc-were determined by examination of gonads according

described by Mackie and Lewis (2001). Sagittal otolithsed from the skull, rinsed in freshwater and dried prior

in vials within labeled envelopes. One whole sagittaeuently weighed (0.1 mg) and measured (total length,

anti-rostrum length and width at the core; 0.01 mm).lith (where possible) was embedded in a resin block.of micro-increments a single 300450 m section con-

otolith core was removed using a low speed saw andlade. These sections were then polished until the pri-nd micro-increments could be discerned (approximate50 m). Complete details of the methods used in thend processing of S. commerson otoliths are described inackie (2003).

etation of otolith structure

logy used in the description of S. commerson otoliths fol-f Kalish et al. (1995). Micro-increments (putative dailyements) were counted on two separate occasions by ther (PDL), with the rst discernible micro-increment afterium assumed to have been formed on the day of hatch-). When these counts differed by 10%, a third countFor all otoliths the nal age assigned was the averageounts that differed by less than 5%. If the three countsmore than 5% the otolith was not used for ageing. Thecro-increment counts were converted to fractions of aw for growth parameter estimation.ages were based on adjusted counts of annuli (alter-que and translucent bands) from sectioned otoliths.ry reader (PDL) examined each otolith on two

48 S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60

Fig. 2. Sectiondorsal) showiof microincrem22 annuli. Nottral portion ofarrow) preced(arrow head),

independena random suotolith was2 = poor; 3 margin or margin (i.e.3 = wide tratranslucent

Annuli creader agreand accepteotolith wasto date of coat-age datavariation inDeVries andThe age of owith a margthus allowinbut not yetand Februato include Scommencemcide with twas then m

1 September (i.e. the start of the spawning season; Mackie et al.,2005). The nal age of otoliths sampled between this birth dateand the end of the spawning season (SeptemberFebruary) wasnot altered, whereas the age of otoliths sampled during the next

nth precage pmetring th

lidat

sistemmetervormaspection onual

regiar. Th

yrs)

owth

mate lenve dsix-moThe

of averof symfollow

2.3. Va

Conin S. cotime indaily fmorus Validathe anPilbarathe yeand 6+

2.4. Gr

Estiing the(putati views of S. commerson otoliths giving orientation (V-ventral, D-ng (a) juvenile otolith with core, radial striae, and regular pattern

ents, (b) the oldest sh (a male) collected during the study, withe the abnormal outgrowth on the ventral surface (arrow), (c) ven-

an adult with three annuli (white dots) showing radial striae (largeing the ventral bump and associated broad secondary opaque zoneand parallel pair of secondary and primary annuli (small arrows).

t occasions, while a secondary reader (MCM) examinedb-sample of the otoliths on one occasion (n = 200). Each

also categorized by a readability score (1 = unreadable;= fair; 4 = good; 5 = perfectly readable) and by otolithedge type (1 = opaque margin; 2 = narrow translucent

150% the width of the previous translucent margin);nslucent margin (i.e. 51100% the width of the previous

margin)), as dened in Lewis and Mackie (2003).ounts were accepted if both counts by the primaryed. If not a third count was made by the primary readerd if in agreement with an earlier reading, otherwise the

rejected. Counts were subsequently adjusted in regardllection and birth date to improve resolution of length-

(Lewis and Mackie, 2003). Adjustment for individual the formation of annuli was based on methods used by

Grimes (1997) for the congener Scomberomorus cavalla.toliths sampled during the period of annuli formationin status of 3 were assigned the annuli count plus one,g for the annulus that was about to form or was forming

visible. Annuli formation peaked between Novemberry (see Section 3), although this period was extendedeptember and October because of a potential lag in theent and appearance of the opaque margin, and to coin-

he spawning period (Mackie et al., 2003). Adjustmentade to account for an assumed birth date for all sh of

(mm day1

juvenile sCandida

S. commersBertalanffy(1981). Thedata using nlength (FL, length, K (yLt approachis zero).

The four

Lt = [Lb1 + (Lted to lengtrelating to gyoungest aestimable pand 2 resp

The thremodel (Sch(16)(18) inThe Akaike(AICc) was the best appThe AICc wnumber of data group2004). Themodel whethe next low

The molength at afor each relength at ain a poor reof undifferesh) samplperiod (MarchAugust) was increased by 0.5 yr.ision of age estimates was determined using the indexercent error (IAPE; Beamish and Fournier, 1981). A testy was used to examine potential biases in age estimatese method described by Hoenig et al. (1995).

ion of otolith increment periodicity

ncy in the width and appearance of micro-incrementsrson otoliths indicates that they are formed at regularals. This temporal periodicity was not determined, but ation was assumed based on studies of other Scombero-ies (e.g. Shoji et al., 1999; Peters and Schmidt, 1997).f the annual nature of growth increments was based onpattern evident in the margin type categories from theon where it was possible to obtain samples throughoutis data was pooled into 3 age groups (12 yrs, 35 yrs

prior to analysis.

and mortality models

s of juvenile growth rates were determined by divid-gth of each sh by the otolith microincrement countaily growth increments). These juvenile growth rates) provide an estimate of the average growth of eachh since birth.te models explored for describing the growth of adulton were the von Bertalanffy growth model (VBGF; von, 1938) and the more versatile growth models of Schnute

VBGF: Lt = L(1 expK[tt0]) was tted to length at ageon-linear least squares estimation (where Lt is the meanmm) of sh at age t (yr), L is the asymptotic meanr1) is a rate constant that determines the rate at whiches L, t0 (yr) is the theoretical age at which mean length

parameter growth model of Schnute (1981), Schnute 1:b2 Lb1)(1 ea(t1))/(1 ea(21))]

1/b, was also t-

h at age data, where a and b are estimable parametersrowth curvature, 1 and 2 are values representing the

nd oldest sampled ages respectively, and L1 and L2 arearameters representing the lengths of sh at ages 1ectively.e other lower-parameter variations of the Schnute 1nute 2, Schnute 3 and Schnute 4), formulated as Eqs.

Schnute (1981) were also tted to length at age data.s Information Criterion corrected for small sample sizescalculated for determining which candidate model wasroximating type of model for describing growth trends.as used because the ratio of the sample size (n) to theparameters plus one (k) was below 40 for some of thes (Burnham and Anderson, 1998; Posada and Buckley,

lowest AICc value identied the best approximatingre a difference of greater than 2 existed between it andest AICc value (Burnham and Anderson, 1998).

re complex Schnute 1 growth models were tted toge data sampled for each sex within each region andgion (ignoring sex). As shery-dependent sampling ofge data from the Kimberley and West Coast resultedpresentation of younger, smaller sh, those juvenilesntiated sex (which develop into either male or femaleed from the Pilbara were appended to Kimberley and

S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60 49

West Coast datasets for describing growth at the level of region.This assumed that the early growth of S. commerson was the sameamong regions (and sexes).

We also compared AICc values to assess whether the addi-tion of extrto separateto the poolapproximatwith the hyachieved wdata groupeffect of datThe Pooled best approxof that typeings. Similaon the desctage of asseregion on grplexity, is thsignicanceavoided (Po

Estimatewere made catch curvesamples reprandomly oThe loge of tsamples wathe slope oclasses (froma sample frewere as oldwere also fvalid repreand that varis negligible

Estimateyr1) were oM = exp(1.4The Hoenigmate total regression method proimum age iexploited pfrom an underived from(overoptimshing mor

Estimatesion equatiHowever, aestimates omore reliabthey were anot conside

3. Results

The otoland 2288 s1278 were juveniles. Bfrom 62 to 1

The sagittal otoliths were elongate, fragile structures with aslightly concave distal surface. An alternating series of opaque andtranslucent zones were discernable towards the posterior mar-gin of whole otoliths when viewed with reected light. In cross

therly spnslu

distie foincre

in t in thincredary). Thbseqs this

for nto oe tra

ason

lithshoutal dos co. Otber

er mcentanua

fromarycenth to d of sneraloast

statn otoares

age an

yrs e of

icro-

lithsectio

prim = 63PE whe crsonf agry reere aof thd bes weost oin oteadas, wha parameters to t a selected type of growth model data groupings (Separate Data model), as opposeded dataset (Pooled Data model), resulted in a betterion of the data. The Separate Data model was consistentpothesis that a better approximation of the data washen the selected type of growth model tted to each

separately. Accordingly, this would indicate that thea grouping on the description of growth was important.Data model was consistent with the hypothesis that theimation of the growth trend was obtained from the t

of growth model to data pooled across the data group-rly, this would indicate that the effect of data groupingription of growth was not important. One key advan-ssing the relative importance of factors such as sex andowth, by evaluating associated increases in model com-at issues associated with selecting appropriate testing

levels, as required for classical hypothesis testing, aresada and Buckley, 2004).s of the instantaneous rate of total mortality (Z; yr1)for each region and sex using standard linear regression

analysis (Ricker, 1975; Beverton and Holt, 1957). Onlyresentative of the landed catch-at-age distribution or abtained portion of the catch were used in these analyses.he relative number of sh in each age class within theses plotted against age, with estimates of Z obtained fromf the descending regression for the fully recruited age

the modal age group to the oldest age group prior toquency of zero). This analysis assumed that all sh that

as, or older than some fully recruited age to the sheryully selected by the gear, that the samples provide asentation of the relative abundance of each age classiability from annual recruitment and natural mortality

or constant across each fully recruited age class.s of the instantaneous rate of natural mortality (M;btained using the empirical equation of Hoenig (1983):

6 1.01 ln(tmax)); where tmax = maximum age (yr). (1983) equation described above is a method to esti-mortality (Z), even though some of the data in hiswere sourced from lightly exploited populations. Thevides an estimate of M only when the estimate of max-s obtained from an unexploited population or from anopulation when the maximum age is similar to thatexploited population. Therefore, the estimates of M

this method in this study are likely to be overestimatesistic), as they likely include an unknown component oftality (F).s of M were also derived from the empirical regres-ons of Pauly (1980) and Brey (1999) for comparison.s they resulted in estimates of M noticeably above thef Z derived from catch curves, which were consideredle estimates (e.g. Newman et al., 1996; Hall et al., 2004),ssessed as unrealistic and inappropriate and thus werered further.

iths of 2973 S. commerson were weighed and measuredectioned for analyses. Of those sectioned for analysis,females, 842 males, 96 of unknown sex and 67 wereody length (TL) of sh with sectioned otoliths ranged780 mm.

sectionregulaand tratainedfrom thmicro-changebumpmicro-(secon(Fig. 2cthan suotolithtinuedfused ithan th

3.1. Se

OtothrougseasonpatternmarginNovemsummtransluyear (Jperiod(Februtransluthrougthe enbut geWest C

Thecycle iwas cle12 yrsformedthan 5becaus

3.2. M

Otowere sotolithcent (ntheir IA

At tcommelevel oprimarages wfor 15 rejecteotolithage. Mences (poor rregion otoliths of small sh exhibited a concentric series ofaced micro-increments, each comprised of an opaquecent zone (Fig. 2a). Sectioned otoliths of larger sh con-nct annuli (Fig. 2b). Striae (McPherson, 1992) radiatingcus often extended for 34 months of growth (based onment counts), and were usually followed by a markedhe deposition of the otolith material that resulted in ae ventral margin between about the 110th and 150thments (Fig. 2c). This was often associated with a false) annulus, with the true annulus following soon afteris rst annulus was generally broader and less distinctuent annuli and was often difcult to identify. In some

pattern of closely associated true and false annuli con-several years. In other otoliths they appeared to havene broad opaque zone, which could be 34 times widernslucent zone.

al pattern of otolith growth

with opaque and translucent margins were sampled the year, although there were distinct patterns in theminance of each margin type category (Fig. 3). Thesenrm a single annual cycle of growth at the otolitholiths with opaque margins were common betweenand March in the Pilbara region, and dominated theonths of December and January. Otoliths with a thin

margin (category 2) were common for most of therySeptember), and were dominant for a six month

the end of summer through to the middle of winterJuly). The cycle was completed by otoliths with a wide

margin (category 3), which were common from JulyDecember and thus were dominant from late winter topring (AugustNovember). This pattern is less distinctly similar for otoliths sampled from the Kimberley and

regions (Fig. 3).us or type of the otolith margin also exhibited an annualliths of sh within each age group (Fig. 4). This patternt for the 35 yrs age group, but was also evident in the

group despite the decreased number of otoliths that hadopaque margin. The less distinct pattern for sh olderis likely due to difculties in interpreting the marginthe closeness of annuli.

increment and annuli counts

from 72 S. commerson ranging from 58 to 781 mm FLned, mounted and read for micro-increment counts. Theordium was located in 95% of these. Eighty-eight per-) of these counts were within 10% of each other, andas 2.9%.

ompletion of the rst two readings of the sectioned S. otoliths, two were rejected as being unreadable. Theeement between the initial two counts of annuli by theader was 77% (n = 1540). This increased to 79% whendjusted for the margin status category. Annuli countse 456 sections re-read a third time were subsequentlycause they differed from previous counts. Only 1% ofre rejected as being unreadable or of indeterminabletolith sections were fair or good to read (93.1%). Differ-olith readability were also minor between the Pilbarability 3.9%) and West Coast (poor readability 3.8%)ereas those from the Kimberley region were noticeably

50 S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60

more difcult to interpret (poor readability 14.8%). Noticeably,otoliths from the Kimberley region were characterized by poorerreadability compared with otoliths from the other managementregions.

The IAPE between the two initial counts of annuli and betweenthe adjusted ages (see below) was 4.4% and 3.7%, respectively. Thetest of symmetry indicated a signicant difference between thetwo annuli counts (Chi-squared = 49.7, d.f. = 30, p = 0.015) but notbetween the adjusted ages (Chi-squared = 41.4, d.f. = 33, p = 0.17).Further investigation of the source of bias, based on tests of sym-metry for selected age groups, revealed that the counts for sh

S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60 51

Fig. 4. Monthfrom the Pilba

readers to 5of symmetr

3.3. Compa

Compariotoliths wation had a rof the whoment betweto 75.5% forcounts wasly percentages of each otolith marginal increment category for S. commerson within (a) 1ra region. Data for each sex were pooled with the number of samples for each month giv

1.8% but removed the signicant bias evident in the testy.

rison of sectioned and whole otolith annuli counts

son of counts of annuli from sectioned and wholes undertaken using 292 otolith pairs in which the sec-eadability of 2 or better. Counts were possible for 97.6%le otoliths compared to 96.6% of the sections. Agree-en the two whole otolith counts was 75.1% compared

the two section counts. The IAPE for the whole otolith 3.8% and the test of symmetry showed that there was

no signicathe sectionwas non-sig

Fifteen (an annuli cwas 61.0% and sectionpared. The 6.3%, with tbetween thp = 0.003), pd.f. = 11, p =2 yrs age-classes, (b) 35 yrs age-classes, and (c) 6+ year age-classesen in brackets.

nt difference between these two readings. The IAPE fored otoliths was 4.4% and similarly the test of symmetrynicant.

5.1%) of the 292 otoliths compared could not be assignedount by either the whole or sectioning method. Thereagreement between the adjusted ages of each wholeed otolith pair for the 277 otoliths that could be com-IAPE between whole and sectioned adjusted ages washe test of symmetry indicated a signicant differencee whole and sectioned ages (Chi-square = 71.57, d.f. = 41,articularly in sh less than 4 yrs old (Chi-square = 40.9,

0.001). There were no consistent differences among

52 S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60

Fig. 5. Compamerson otolithpoints overlap

methods apsh older thwhole and symmetry bnot signicto the sampages were the otolith status categsignicant (sum = 53.7

3.4. Age an

Ages of otolith micrange = 58calculated tseveral of tin July and incrementswas 396 mm

Estimatethe Kimberand 22, andof male andpositively sthan 15 yrs

Juvenileaverage daiJuveniles cagrowth (4.2June tendedaily growt500 mm FL.of juvenile prior to anotolith mat

Annual was much reach of thespecic datconsistentlyto length a

ge-frequency distributions of male and female S. commerson caught fromberley (a), Pilbara (b), and West Coast (c) regions.rison of the adjusted ages given to each whole and sectioned S. com-, with equal ages indicated by the tted line. Note that many data

(particularly in the younger age-classes (n = 275)).

parent in the ageing of these sh, except perhaps foran 12 yrs (Fig. 5), and the median difference betweensectioned otolith ages was 0 for both sexes. A test ofetween whole and sectioned ages of sh >12 yrs was

ant, probably because of the low power of this test duele size (n = 25). Discrepancies between the two sets of

due at least in part to differences in interpretation ofedge, with only 44% agreement between the marginories assigned to whole and sectioned otoliths, and aeffect of method detected from the test of symmetry, d.f. = 3, p = 0.001).

d growth analysis

juvenile and immature sh estimated from counts ofro-increments ranged from 23 to 391 days (n = 72, FL781 mm). Birth-dates for most of these sh were back-o the period between November and January althoughhe older juveniles were estimated to have been bornAugust. The smallest male aged from counts of micro-

was 284 mm FL and 80 days old. The smallest female FL and 122 days old.s of maximum age of male and female S. commerson inley, Pilbara and West Coast regions was 12.5 and 11, 18

17.5 and 18.5 yrs, respectively (Fig. 6). Age distributions female S. commerson overlapped considerably and were

Fig. 6. Athe Kimkewed (Fig. 6). Seventy three percent of the 37 sh olderwere male.

growth was most rapid up to 300500 mm FL when thely growth rate peaked at around 34 mm day1 (Fig. 7).ptured in March and April had the fastest average daily

mm day1), whereas those of similar size captured ind to grow at a slower rate. The average cumulativeh rate decreased to 22.5 mm day1 for sh larger than

The nonlinear relationship between fork length and agesh indicates that growth slowed after 100 days, just

observed change in the pattern of deposition of newerial (Fig. 8).growth declined considerably after the rst year andeduced after 5 yrs (Fig. 9). Goodness of t statistics for

growth models tted to each of the region and sex-asets are presented in Table 1. The Schnute 1 model

provided the equivalent best or best approximating tt age data (Table 1). Parameter estimates for the t of

Fig. 7. Average growth rate of juvenile S. commerson by month of capture. The lengthdivided by otolith microincrement count was used to estimate average growth sincebirth of each sh.

S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60 53

Table 1Model ts to fork length (mm) at age (yr) data grouped by sex and region, evaluated using Akaikes information criterion for small sample sizes (AICc). Cells in bold identify themodel resulting in the lowest AICc, indicating the best approximating t. Cells with shading identify models with the best approximating or equivalent best approximatingt as determin

Region

Kimberley KimberleyKimberley Pilbara Pilbara PilbaraWest CoastWest CoastWest Coast 838.5 856.7 1006.1

a Consistent

Fig. 8. Lengthments.

the Schnutemodel resut, particula

Comparifrom the Scmodel direcwas consistVBGF modethe K (yr1)determinesa paramete1. Howeverthese datascomparablecalculating representatmodel at thcorrespondmodel to Kifor the t obecause thewere closerest. Of noteacross malemates of L(i.e. West Cwas availaban asymptothe Schnuteed from calculated AICc values.

Sex VBGF Schnute 1a

Males 920.2 921.9 Females 954.2 953.1 All 2253.1 2228.7 Males 1007.6 978.4 Females 1320.5 1309.3 All 2695.2 2647.4Males 205.0 204.8 Females 337.4 336.2 All 824.8 805.5

best approximating model for all datasets (see Section 2). at age of young S. commerson based on counts of otolith microincre-

1 model are presented in Table 2. Visually, the Schnutelted in a more even distribution of residuals about therly for older-aged sh (see Fig. 9).son of the derived estimates of the VBGF parametershnute model with those estimated by tting the VBGFtly revealed a consistently higher L, and that the t0ently closer to zero for the Schnute model than for thel (Table 3). Growth curvature, which is represented by

parameter of the VBGF model (i.e. the rate constant that the rate at which Lt approaches L) is equivalent to ther of the Schnute 1 model only where the b estimate is, K could not be calculated from the Schnute model forets because b was consistently higher than 1 (Table 2). A

average rate of growth was therefore approximated bythe slope of the tangential line to the function at threeive lengths by evaluating the derivative of the Schnuteose lengths. The slope values at L1 and L2 bracketed theing K estimates from the VBGF, except for the t of themberley males. Values for the slope at L1 were very highf the model at the level of region, pooled across sexes,

corresponding 1 values for model ts to those datasets to the origin, where the rate of growth is typically high-, there is a north-south progression in estimates of Ls, females and all sh combined (Table 2) with esti-increasing with increasing latitude of sample region

oast L > Pilbara L > Kimberley L). No estimate of Lle for female S. commerson from the West Coast becausetic length was not achieved for the sampled data using

model.

Fig. 9. Length(converted toshown.

Fitting thData modelength at agfor each regtant factor demonstratby the slopeto a larger aSchnute 2 Schnute 3 Schnute 4

920.6 922.1 961.1956.0 953.4 1004.3

2278.3 2345.0 2660.31014.4 995.9 1140.51325.0 1312.1 1434.82735.8 2830.3 3206.0206.0 204.2 227.9338.1 335.8 347.8 at age of S. commerson based on counts of annuli and microincrements annual ages). Schnute growth functions tted to the data are also

e Schnute 1 model to data for separate sexes (Separatel) was shown to provide a better approximation of thee trends than tting to pooled data (Pooled Data model)ion, demonstrating that sex was consistently an impor-identied for describing growth (Table 4). Males wereed to grow at an equal or faster mean rate, as indicated

of the Schnute 1 model at L50 and the VBGF K, and growverage asymptotic length, L, than females (Table 3).

54 S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60

Table 2Parameter estimates from the t of the best approximating growth model (Schnute1) to length-at-age data for S. commerson (lengths are fork length in mm; SE is thestandard error of tted parameter estimates).

Region Sex Parameter Estimate SE n r2

West Coast All a 0.347 0.036 209 0.94West Coast All b 2.19 0.09West Coast All L1 22.40 80.17West Coast All L2 1256.37 23.83West Coast F a 0.208 0.094 89 0.82West Coast F b 6.66 1.46West Coast F L1 643.75 48.27West Coast F L2 1618.53 55.40West Coast M a 0.138 0.079 54 0.87West Coast M b 4.24 1.20West Coast M L1 603.32 36.91West Coast M L2 1259.34 34.71Pilbara All a 0.389 0.020 694 0.91Pilbara All b 2.20 0.07Pilbara All L1 18.12 79.36Pilbara All L2 1251.65 8.52Pilbara F a 0.114 0.033 350 0.84Pilbara F b 4.11 0.33Pilbara F L1 426.34 50.00Pilbara Pilbara Pilbara PilbaraPilbara KimberleyKimberley Kimberley KimberleyKimberley KimberleyKimberley KimberleyKimberley Kimberley KimberleyKimberley

The effecfor region females, indation in groregion was well to the of region wshow an image data bu

Explorint of Separpaired grou

over the Pooled Data model when tted to (i) Pilbara and WestCoast data and (ii) Kimberley and West Coast data groupings offemale length at age data (Table 4). By inference, this indicated thatthe effect of region was important for modelling female growthwhen these groupings of region were made; suggesting that thegrowth trend for West Coast females was different to the growthtrends for females in the other regions. Females from the WestCoast were observed to have a larger L and a much lower averagerate of growth than females in the Kimberley and Pilbara (Table 3).Importantly, asymptotic growth was not apparent from the t ofthe Schnute model to female length at age from the West Coastregion, as it was from the other regions (Table 3). Comparison ofthe modelled average length at the oldest observed age, 2, (i.e. L2)was therefore useful for providing further information about dif-ferences in length at age among regions for older sh. Accordingly,the L2 for West Coast females was more than 200 mm larger thanestimated for Pilbara females and was more than 270 mm largerthan estimated for Kimberley females (Table 2).

In contrast, the Pooled Data model was supported over the Sep-arate Data model when tted to Kimberley and Pilbara length at age

r females (Table 4). This means that the addition of param-o expapprhis intely t

was

ortal

instcurv

Table 3Values calculathe formulas ito show the ra

Region

Kimberley Kimberley Kimberley Pilbara Pilbara Pilbara West Coast West Coast West Coast

a The lengthestimates fromF L2 1411.16 23.75M a 0.155 0.024 277 0.89M b 4.41 0.26M L1 286.75 49.47M L2 1250.87 13.87All a 0.452 0.028 593 0.90All b 2.06 0.08All L1 20.46 73.78All L2 1186.65 10.73F a 0.157 0.077 257 0.76F b 3.60 0.83F L1 569.92 63.18F L2 1339.74 30.93M a 0.248 0.122 269 0.74M b 3.06 1.91

data foeters tbetter ence, tseparaPilbara

3.5. M

Thecatch M L1 695.78 28.96M L2 1145.75 22.55

t of region was more variable. The Separate Data modelwas found to be the better approximating model foricating that there was some important regional vari-wth for females. However, the Separate Data model foralso found to represent length at age data equivalentlyPooled Data model for males, indicating that an effectas not important for males. By inference, these resultsportant effect of region for modelling female length att an equivocal effect of region for modelling male data.g this apparent effect of region for females further, theate Data and Pooled Data models were compared forpings of region. The Separate Data model was supported

(Table 5). Inevident duethis region.recruited in

The instthe Hoenigof 0.160.2managememaximum estimates oshing moages of 0.4sh in the female and0.020.06 y(Table 5).

ted from the t of the best approximating Schnute 1 model that correspond to von Bertan Schnute (1981). Since a = K where b = 1 and b > 1 for all model ts (Table 2 the slope of thnge and approximate average rate of growth.

Schnute 1

Sex L Slope L1 Slope L50 a Slope

Males 1161.4 0.31 0.27 0.003Females 1399.5 1.06 0.27 0.007All 1188.7 958.85 1.51 0.001Males 1260.6 24.18 2.55 0.001Females 1467.9 4.41 0.28 0.005All 1251.8 1968.33 1.30 0.000Males 1284.4 0.77 0.58 0.003Females NA 0.83 0.08 0.033All 1257.3 1083.97 1.16 0.000

at 50% maturity, which was 628 mm LF for males, 809 mm LF for females, and the media the t of the von Bertalanffy model are shown alongside for comparisonlain an effect of region for females did not result in aoximation of the growth trends for these data. By infer-dicates that the variation between growth curves ttedo female length at age data from the Kimberley and the

not important.

ity

antaneous rate of total mortality (Z) estimated fromes was consistently higher for females than males

the Kimberley region, much higher estimates of Z are to the relatively low number of older sh sampled from

The catch curves indicated that S. commerson were fullyto the shery in each region by 2 yrs of age (Fig. 10).antaneous rate of natural mortality (M) estimated using

(1983) equation was estimated to be in the range0 yr1 (for the oldest sh sampled across each of thent regions). The estimates of mortality derived fromages indicate no sex-specic patterns. Utilising thesef M result in estimates of the instantaneous rate ofrtality (F) from catch at age data for fully recruited00.44 yr1 and 0.240.28 yr1 for female and maleKimberley region, 0.090.13 yr1 and 00.01 yr1 for

male sh in the Pilbara region, and 0.180.22 yr1 andr1 for female and male sh in the West Coast region

lanffy growth model parameters. Values for L and t0 derived usinge tangent at three representative lengths), L1, L50, L2 were calculated

VBGF

L2 t0 L K t0

0.45 1135.6 0.37 2.19 0.24 1304.1 0.36 1.52 0.06 1151.7 0.70 0.27 0.21 1197.5 0.42 1.31 0.28 1333.9 0.36 1.49

0.06 1213.3 0.64 0.34 0.20 1229.8 0.33 1.83

0.32 1833.4 0.10 4.85 0.06 1169.7 0.70 0.26n of these estimates for males and females combined (All); original

S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60 55

Table 4Model ts to fork length (mm) at age (yr) data, evaluated using AICc, to assess whether the addition of extra parameters to t the Schnute 1 model to separate data groupings(Separate Data model), as opposed to the pooled dataset (Pooled Data model), resulted in a better approximation of the data. Cells in bold identify the model resulting inthe lowest AICc, indicating the best approximating model. Cells with shading identify equivalent best approximating models.

Data

Kimberley PilbaraWest Coast Males Coast Females Coast FemalesFemalesFemales

a If the best ffect oopposed to its

Table 5Estimates of to timateof M (0.160.2

Region

Kimberley 0Pilbara 0West Coast 0

4. Discussi

The macwaters is hreefs, shoalmeta-popuunderpins tThe existenacross northdent assessmanagemenare facing indene demimproved ustudy repregrowth ratemerson acrothin section

4.1. Validat

The annotoliths waing an annuThorrold (2priate whefeasible. Ththat has be2005; McIlwined in ranwere collecresults obtacondence.S. commers(e.g. Devarabe attributaregions andtechniques

sentual bsent.ion oe be) waondant tas an

annther

in la opahersPooled Data model Groups

1967.69 Males, Females 2377.88 Males, Females 548.73 Males, Females

2104.38 Kimberley, Pilbara, West 2597.74 Kimberley, Pilbara, West 2256.97 Kimberley, Pilbara1652.00 Pilbara, West Coast 1289.39 Kimberley, West Coast

approximating model is the Separate Data model, this factor, which is the added e omission) and, by inference, is therefore determined to be an important effect

tal mortality (Z, yr1) from catch curves (using data from unbiased samples) and es0 yr1) obtained from maximum age estimates using Hoenig (1983).

Z from Catch Curves

Female (n) Male (n) Combined

0.5958 (182) 0.4392 (208) 0.5402 0.2933 (108) 0.1729 (67) 0.2479 0.3786 (144) 0.2214 (97) 0.3165

on

kerel shery for S. commerson in Western Australianighly valued and is located in coastal areas arounds and headlands across more than 16 of latitude. Thelation structure of S. commerson in Western Australiahe regional management boundaries for this species.ce of separate stocks both in Western Australia andern Australia indicates that each requires an indepen-ment of demographic processes in order to underpint arrangements. Furthermore, these coastal regionscreased development pressures and it is important to

ographic characteristics of S. commerson to provide annderstanding of their susceptibility to exploitation. This

the prean annbe preformatsagittatraliancorrespimportstudy ondaryand furannulia broad

McP

sents the rst detailed investigation of the age structure,s and mortality characteristics of populations of S. com-ss three management zones off the coast of WA usinged sagittal otoliths.

ion and formation of annuli

ual periodicity of increment formation in S. commersons validated from cycles in otolith margin type, indicat-al cycle of opaque increment deposition. Campana and001) considered this form of validation to be appro-n validation attempts using other methods were notis form of age validation represents the only methoden successful for this species (e.g. Grandcourt et al.,ain et al., 2005). As samples in this study were exam-

dom order with no knowledge of when the samplested, and almost 2 complete cycles were assessed, theined from this validation method can be applied with

Previous studies have concluded that the otoliths ofon may form one or two or more annuli per yearj, 1981; McPherson, 1992; Govender, 1994). This mayble to differences in environmental regimes between/or methodological differences in otolith processingand interpretation (Grandcourt et al., 2005). Regardless,

opaque andin the percemarginal inotoliths. Thmargin in Sformation ogreatest incMarch. Otoeleven monfrom the Un

Formatispawning aever, a revand Wilsonbetween spopaque zonfrom Octobing water tein otolith grtemperaturotolith or iprocesses r

AlthougcommersonFactora Separate Data model

Sex 1884.52Sex 2293.67Sex 538.59Region 2103.00Region 2594.36Region 2260.55Region 1643.21Region 1286.84

f data grouping, is supported for inclusion in the nal model (i.e., as

s of shing mortality (F, yr1) derived from subtracting the estimates

F (Z M)

Female Male Combined

.3960.436 0.2390.279 0.3400.380

.0930.133 00.013 0.0480.088

.1790.219 0.0210.061 0.1170.157

study clearly indicated that in WA waters they form onasis, although sometimes secondary false annuli may

McPherson (1992) and Govender (1994) also note thef a narrow secondary opaque zone in S. commerson

tween January and May in Queensland (Eastern Aus-ters, and during May in South African waters, whichs with the timing of this secondary zone in WA. It iso note these secondary zones were not counted in thisnuli. Lewis and Mackie (2003) demonstrate how sec-uli appear as a ne line between the broad annual bands

note that these secondary annuli can combine with trueter increments (3+) for some individuals, thus creatingque band and a thin translucent zone.on (1992) attempted to validate the annual nature of translucent growth increments from the distinct peakntage of whole otoliths with opaque margins and fromcrement analysis made from measurements of wholee JulyOctober occurrence of otoliths with an opaque. commerson from QLD (McPherson, 1992) indicates thatf the opaque zone occurs earlier than in WA, where theidence of opaque margins occurred from November toliths with an opaque margin were also found duringths of the year in samples of king mackerel (S. cavalla)ited States (Johnson et al., 1983).

on of the opaque zone in otoliths has been linked toctivity in S. cavalla (Sturm and Salter, 1990). How-iew of sh species (including S. cavalla) by Beckman

(1995) suggested that there was no clear associationawning and opaque zone formation. In WA the peak ine formation coincided with the main spawning perioder to January, which in turn is associated with increas-mperatures, a parameter thought likely to be importantowth (Beckman and Wilson, 1995). Whether the watere and other environmental inuences act directly on thendirectly through their impact on other physiologicalemains unknown (Fowler, 1995).h the temporal periodicity of the micro-increments in S.

otoliths has not been validated, those of S. maculatus

56 S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60

Fig. 10. Log trsamples from sions used to eincluded in reg

(Peters andet al., 1999icity of S. cthat juvenilas estimatecapture.

4.2. Assignm

The criteand tests ofbetween unto that reco67%), altho(Buckworthilar latitudethose of shnal differenotoliths of wand readabregional dif

separate and distinct adult populations in each of the managementzones that is supported by both parasite and otolith stable isotopestudies (Lester et al., 2001; Newman et al., 2009).

venil

wth FL

500 mtain sh t

rsry w, 199also cnd land fspawohnster m

chan opaimat

ult g4.3. Ju

Gro300 mmabout not obolder ing themay va(Pepincould early astudy ain the later (Jing winrates, ondaryapprox

4.4. Adansformed number of S. commerson in each age group from unbiasedthe Kimberley (a), Pilbara (b) and West Coast (c), with tted regres-stimate total mortality (Z). Data indicated by hollow circles were notression analyses.

Schmidt, 1997) and Scomberomorus niphonius (Shoji) are known to form on a daily basis. Daily period-ommerson micro-increments is supported by the factes appear to have hatched during the spawning period,d by back calculations of birth dates from the date of

ent and reliability of ages

ria used to adjust ages improved the agreement, IAPE symmetry between counts compared to comparisonsadjusted counts. The IAPE of 3.7% was low comparedrded for S. commerson from the Northern Territory (NT,ugh the otoliths of these NT sh were difcult to read, 1998). Otoliths of sh from the Kimberley region (sim-

to the NT) also tended to be more difcult to read than from the more southern regions, suggesting latitudi-ces possibly related to water temperatures since thearm water coral reef sh species often vary in clarity

ility (Fowler, 1995; Marriott and Mapstone, 2006). Theferences in otolith readability also support the notion of

Rapid grlife concursMcPhersonferences in and are alsority is obtaare sexuallybeen estim628 mm FLUsing the i50% sexual males. As sufemales whet al., 2003,

The keyin L. Femmales thro1992; Buckthe relatedlandicus, an1998; Camesouthern Uand Grimeslength andparametersmerson in Wto other stuFL (e.g. Gov

Female larger body1998). As i12.5 yr old fold female (11 yrs (with1998). McIlmaximum maximum mum ages ain the Pilbaaddition, S.e growth

rate of juvenile S. commerson was most rapid up to about(ca. 80 days) before it slowed and then decreased afterm FL (ca. 160 days). Although Dudley et al. (1992) did

S. commerson in this age range, they note from data forhat growth was also most rapid in Oman waters dur-t 3 to 5 months of life. Early growth of S. commersonith water temperature as shown for other sh species1), and thus vary among temporal and spatial scales. Thisause differences in growth rate between sh hatchedte in the reproductive season, as indicated in the presentor king mackerel (S. cavalla) in which sh hatched earlyning season had faster growth rates that sh hatchedon et al., 1983). The decrease in water temperature dur-ay also be a causal factor for the sudden drop in growth

ge in otolith growth and formation of the broad sec-que zone in the otoliths that occurs after the sh areely six months old.

rowth

owth by S. commerson in WA for the rst two years of with data from related studies (Dudley et al., 1992;, 1992; Govender, 1994; Grandcourt et al., 2005). Dif-growth rates are evident between male and female sh,

reected in differences in the age at which sexual matu-ined. The mean length at which 50% of S. commerson

mature (data for all regions combined) has previouslyated at 809 mm FL 9.8 SE (898 mm TL) for females and

13.8 SE (706 mm TL) for males (Mackie et al., 2005).nverse form of the VBGF, the estimated mean age atmaturity is therefore 1.4 yrs for females and 0.8 yrs forch, most males mature before they are one year old anden they are around one and a half years of age (Mackie

2005). consistent difference between sexes in this study wasale S. commerson exhibit a larger L in comparison toughout the waters of northern Australia (McPherson,worth, 1998). Sexual differences in L also occurs in

congeneric species Scomberomorus munroi, S. queens-d S. semifasciatus in Queensland waters (Begg and Sellin,ron and Begg, 2002), and S. cavalla and S. maculatus in

nited States waters (Peters and Schmidt, 1997; DeVries, 1997), although the sex with the greatest asymptotic/or growth rate differs between species. The growth

estimates from the Schnute growth model for S. com-A waters indicate a range of lower L values compareddies, in which these values were generally >1300 mmender, 1994; Grandcourt et al., 2005).S. commerson have previously been shown to attain a

size and age than males (McPherson, 1992; Buckworth,n the Kimberley region, where the oldest sh was aemale, the oldest sh in Queensland waters was a 14 yrMcPherson, 1992), and the oldest sh in NT waters was

no apparent difference between the sexes; Buckworth,wain et al. (2005) indicated that this species reached aage of 20 yrs in Oman and Grandcourt also reported aage of 16.2 yrs in the Southern Arabian Gulf. The maxi-nd tendency for males to dominate the older age groupsra and West Coast regions are similar to these studies. In

cavalla, which like S. commerson is a larger member of

S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60 57

this genus, also reach over 20 yrs of age (Collins et al., 1988; DeVriesand Grimes, 1997).

Nevertheless, Fauvelot and Borsa (2011) contend that the levelof nucleotide divergence between the north-western Indian Ocean(Persian Gulf/Oman Sea) populations and those of the Indo-WestPacic Ocean indicate the likely occurrence of a sister species(nucleotide diversity is also higher than the genetic divergencegenerally observed at the interspecic level in shes), thus sug-gesting the possibility of cryptic speciation in S. commerson. Thegenetic stocks in the Persian Gulf and Oman Sea identied byvan Herwerden et al. (2006) and Hoolihan et al. (2006) are there-fore likely to be that of a separate species to the AustralasianS. commerson. As such, comparisons with demographic studiesfrom the Persian Gulf and Oman Sea need to be treated withcaution.

Signicant differences in growth parameter estimates amongeach of the management regions indicate that it may be appropri-ate to consider each of these areas as a separate management unit(or stock). These differences may also reect the different exploita-tion histories within each of the management regions. For instance,the differences in demography at the regional management scalecould reect phenotypic responses to or impacts from differing lev-els of shing along the WA coast. Thus, the signicant differencesin demography, age structure and otolith readability among man-agement regions evident in this study supports earlier studies thathave documented population subdivision and meta-populationstructure in S. commerson (Moore et al., 2003; Buckworth et al.,2007; Newman et al., 2009), and support the regional manage-ment regime for this species in Western Australia. Accordingly, theregional scale is the appropriate spatial scale that should be con-sidered for sustainable management, monitoring and assessmentof S. commerson in WA.

4.5. Mortality

The instantaneous rate of total mortality (Z) estimated fromcatch at age data for fully recruited ages, was 0.60 yr1 for femalesand 0.44 yr1 for males in the Kimberley region, 0.29 yr1 forfemales and 0.17 yr1 for males in the Pilbara region and 0.38 yr1

for females and 0.22 yr1 for males in the West Coast region. Ourestimates of Z are low relative to other studies, although Govender(1994) used similar age-based catch curves for S. commerson inSouth African waters, but his analyses was based on the unvalidatedassumption that two opaque bands were laid down annually. Theestimates of Z for South African sh were much higher than thatfound in the present study (0.75 yr1) (Govender, 1994). High ratesof total and shing mortality for S. commerson have been reportedin Oman (McIlwain et al., 2005) and the southern Arabian Gulf(Grandcourt et al., 2005). The total mortality rate estimated for S.cavalla in South Eastern US waters, a species that has similar ageand growth characteristics to S. commerson, are most comparablein the range 0.320.42 yr1 (Johnson et al., 1983).

Shojaei et al. (2007) reported levels of shing mortality(F = 0.98 yr1) far in excess of precautionary target and limit bio-logical reference points, indicating that the S. commerson resourcein Iran was heavily over-exploited. In addition, both Al-Hosni andSiddeek (1999) and Govender et al. (2006) report order of magni-tude declines in commercial sheries landings of S. commerson inOman as a result of recruitment overshing and overexploitation.These studies reveal that S. commerson can be overexploited, butalso that they are relatively robust to shing pressure if individ-uals below the size at maturity are not harvested. Any mismatchbetween age-at-entry to a shery and size at maturity can resultin overexploitation and substantial reduction in future catch levels(see also Table 6).

Table 6Comparison of the relative productivity of S. commerson sheries in terms of landings in Australian waters and those of related sheries in the Indo-Pacic region (t = tonnes).

Fishery locat Reaschanappl

Indo-PacicFiji IslandsIndia Indonesia Iran Omanc Over

explOmanc OverOmanc

Emirate of APakistan PhilippinesSaudi ArabiaSri Lanka Within AustWestern Aus Peak

2003Northern Te Peak

2006

Queensland Peak2008

Torres Strait Peak2005

Queensland Peak2002

a Estimatedb Estimatedc Possibly reion Historicalproduction (t)

Currentproduction(t)

2296 (1999) 469 (2007)36,545 (2000) 38,914 (2007) 67,534 (1999) 120,410 (2007) 4520 (1999) 9658 (2007) 27,762 (1988) 3265 (1993)

27,834 (1988) 2559 (2001) 27,834 (1988) 3158 (2007)

bu Dhabic 885 (2003) 297 (2008) 12,232 (1998) 7411 (2007) 18,266 (1983) 21,914 (2007)

c 10,851 (1994) 4961 (2007) 3897 (1990) 2537 (2007)

raliatralia 492 (2003) 284 (2009)

rritory 409 (2006)170 (1995)a

233 (2009)

Gulf of Carpentaria 289 (2008) 190 (2009)

249 (2005) 101 (2009)

East Coast 783(20022003)415 (2005)b

308 (20082009)

recreational catch. recreational catch from the East Coast and Gulf of Carpentaria combined.presents a sister species (see Fauvelot and Borsa, 2011).on forge (ificable)

Reference

FAO (2010)FAO (2010)FAO (2010)FAO (2010)

-oitation

Al-Hosni and Siddeek (1999)

shing Govender et al. (2006)FAO (2010)Grandcourt et al. (2005) and Anon. (2009)FAO (2010)FAO (2010)FAO (2010)FAO (2010)

catch in Molony and Lai (2010)

catch in Handley (2010)

catch in DEEDI (2010) commercial catch unlessindicated otherwise

catch in Marton et al. (2010)

catch in2003

DEEDI (2009) commercial catch unlessindicated otherwise

58 S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60

In this study the instantaneous rate of natural mortality (M) wasestimated to be in the range 0.160.20 yr1. Similar values of Mfor S. commerson have been reported by Grandcourt et al. (2005;M = 0.26 yr1) using reliable age based approaches. In contrast,most valuegenerally raand Pauly, 1In Australiabeen based(Buckworth

In Westepopulation et al., 200genetic stotions (Bucksimilar genevary due to cation of agof differinglikely to bemately catcshing presshing morpotential toKimberley rcommerciareefs. The a10-yr perioof 109 t yr

Despite for this spe(McIlwain distinct (setions of S. cat least 20 yspecic esthave adoptments (e.g.on the oldeapplicationimportant tstudy are lilikely to inc

Fisheries(Vetter, 198of the spawment of shthis study efor both sexfor both sexof shing mpled from eolder than West Coastage were repopulationsexploited u

The validnating tranprovides thof S. commbetween seregions neestructure ohigh longevprevious st

region is higher than in other management zones. However, devel-opment activities across all management zones particularly inrelation to the expansion of oil and gas projects has the potentialto contribute to increasing levels of shing effort. In addition, the

f sho beng ef

man

lativ

ches thanlia (Tilar tableo-Pammred t

mar Kimate tce oof prupwey et ain Culian olewy an

as tling s

leven. Thters

ity antivelm fo.ulatitheirwev

lia ret thaof pos wil

effotherm

coasn therategve inty. Aen ag

or se).

wled

authch aork wcal smenmers of M for S. commerson vary from 0.351.23 yr1, andnge between 0.4 and 0.6 yr1 (Govender, 1994; Ingles984; Al-Hosni and Siddeek, 1999; Dudley et al., 1992).n waters, stock assessments in the NT and QLD have

on estimates of M of either 0.26 yr1 and/or 0.34 yr1

, pers. comm.; ONeill, pers. comm.).rn Australian waters, S. commerson comprise a meta-(Moore et al., 2003; Buckworth et al., 2007; Newman9). This meta-population is composed of the sameck with larval exchange among distinct adult popula-worth et al., 2007). Thus, these sub-populations all havetic characteristics, although phenotypic expression canenvironmental conditions. What does differ is the trun-e structure and this is likely to be associated with levels

total mortality rates among regions, which are most attributed to differing levels of shing effort and ulti-h. The variation in life expectancy among regions due tosure (e.g. progressive removal of older sh arising fromtality across all fully selected age groups) clearly has the

inuence the robust estimation of M. For example, theegion has always been the primary area shed by thel eet due to the higher number of accessible islands andverage annual catch from the Kimberley sector for thed up to 2002 was 178 t yr1 compared to an average1 in the Pilbara and 69 t yr1 in the West Coast.this, longevities of at least 20 yrs have been reportedcies in both Australia (this study) and the Persian Gulfet al., 2005). While these populations are geneticallye Fauvelot and Borsa, 2011), it suggests that popula-ommerson have the potential to reach a longevity ofrs of age. Regrettably, no data is available on region-

imates of M in WA. In the face of this uncertainty, weed a precautionary (lower) estimate of M in our assess-

by deriving M using the Hoenig (1983) method basedst maximum age across all regions). This approach has

to future assessments for this species. In addition, it iso be cognizant that the estimates of M derived in thiskely to be overestimates (overoptimistic), as they arelude an unknown component of shing mortality (F).

assessment models are sensitive to estimates of M8). In addition, direct estimates of F and the relative sizening stock are important considerations in the manage-eries. Noting the uncertainty in estimates of F and M,stimated F to be higher than M in the Kimberley regiones, whereas F was approximately equal to or less than Mes in the Pilbara and West Coast region. These estimatesortality are supported by the numbers of older sh sam-ach region. For example, in the Kimberley region no sh13 yrs of age were exposed. This is in contrast to the

and Pilbara regions where sh up to 18 and 22 yrs ofvealed (see Figs. 6 and 9). These results indicate that the

in the Pilbara and West Coast regions were only lightlyp to 2002, compared to the Kimberley region.ation of annual growth increments consisting of alter-slucent and opaque bands in otolith thin sectionse basis for detailed robust age-structured assessmentserson populations in WA waters. Variation in growthxes and differences in biological attributes betweend to be incorporated into future assessments. The agef adult populations of S. commerson suggests relativelyity and low rates of natural mortality compared withudies. The level of shing pressure in the Kimberley

level olikely tin shiin each

4.6. Re

Catat lessAustraare simtaria (Tthe Indof S. cocompa

Thein themodersequenlevels quent MolonLeeuwAustraruns pGodfre2008),upwel

LowductioWA waductivin relano rooshery

Popgiven rity. HoAustrasuggesstatus regionshing

Furby anyareas ivest stselectimaturibetweble agecaptur

Ackno

TheResearThis wLogistiGovernthe nuing pressure in each of these management regions is also driven by increases in population growth. If increasesfort are realized, the status of S. commerson populationsagement zone will need to be re-assessed.

e productivity and comparison with related sheries

of S. commerson in Western Australia waters are modest 500 tonnes per annum compared to the east coast ofable 6). Despite an extensive coastline, catches from WAo those of the Northern Territory and the Gulf of Carpen-

6). The relative productivity of S. commerson sheries incic region is summarized in Table 6. Australian catcheserson are in general globally modest, especially wheno Oman, India, Indonesia and the Philippines (Table 6).ine ecosystems of Western Australia, including thoseberley and Pilbara regions are classied as being ofo low productivity (Molony et al., 2011). This is a con-f old weathered terrestrial systems coupled with lowimary and secondary production with small and infre-lling systems (Pearce et al., 2000; Lenanton et al., 1991;l., 2011; Langlois et al., 2012). The southward owingrrent dominates the oceanography along the Westernshelf (Lenanton et al., 1991). This low-nutrient currentard and limits the productivity of shelf waters (e.g.d Ridgway, 1985; Caputi et al., 1996; Muhling et al.,here is an absence of large, predictable, nutrient richystems (Pearce, 1991).ls of primary and secondary productivity limit sh pro-e consequence is that the sheries for S. commerson in

are based on marine ecosystems with low levels of pro-d thus the stock sizes are relatively small. This resultsy low levels of sustainable catches. As such, there isr any large-scale development of the WA S. commerson

ons of S. commerson have a high production potential rapid initial rate of growth and low age at matu-er, the low productivity marine ecosystems of Westernsult in low levels of sustainable catch. These attributest the sustainable catches along WA will be low. Thepulations of S. commerson in each of the managementl need to be re-assessed in response to any increase inrt and/or change in efciency of shing gears.ore, juvenile S. commerson may be adversely impacted

tal or nearshore developments that affect recruitment vicinity of mangrove systems and reef structure. Har-ies for populations of S. commerson need to be size

order to limit mortality of sh below the size-at-s such, there is a need to minimise any mismatche-at-rst capture and age-at-maturity (i.e. where possi-ize-at-maturity should be below the age or size-at-rst

gments

ors gratefully acknowledge funding from the Fisheriesnd Development Corporation (FRDC) for this project.as undertaken as part of FRDC Project No. 1999/151.

upport was provided by the Department of Fisheries,t of Western Australia. The authors are thankful toous commercial and recreational mackerel shers of

S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60 59

Western Australia who kindly provided samples and support forthis project. We are indebted to Dr. Ross Marriott who kindlyassisted with statistical growth analyses. We also appreciativelythank two anonymous reviewers and the Associate Editor, Dr.Andre Puntthe manusc

References

Al-Hosni, A.H.SSpanish mManage. E

Ballagh, A.C., Beast coastcalculation

Beamish, R.J., Fage determ

Beckman, D.Wotoliths. Inin Fish Oto

Begg, G.A., Selqueenslandwaters wit

Beverton, R.J.HMinistry o1533.

Brey, T., 1999NAGA, ICL

Buckworth, R.tory Narroand Develhttp://ww

Buckworth, R.The Stock SReport, FiDepartmeernment, A

Burnham, K.P.Informatio

Cameron, D.S.AustralianDevelopm

Campana, S.E.comprehe3038.

Caputi, N., Fleton the recrMar. Fresh

Collette, B.B., 2and wahoGuide for FPacic. VoSea Turtle

Collette, B.B., world. FAO

Collins, M.R., Smackerel, Fish. Bull.

DEEDI, 2009. Ahttp://wwASR-09.pd

DEEDI, 2010. pp., http:/ASR-Gulf.p

Devaraj, M., 1commerson

DeVries, D.A., Gking mack

Dudley, R.G., APacic Spa1743.

FAO, 2010. FAOItaly, http:

Fauvelot, C., Bpelagic sson). Biol.

Fowler, A.J., 1Secor, D.HResearch.

Godfrey, J.S., Rowing Lewind stres

Govender, A., 1994. Growth of the king mackerel (Scomberomorus commerson) offthe coast of natal, South Africa- from length and age data. Fish. Res. 20, 6379.

Govender, A., Al-Ou, H., Mc Illwain, J.L., Claereboudt, M.C., 2006. A per-recruitassessment of the kingsh (Scomberomorus commerson) resource of Oman withan evaluation of the effectiveness of some management regulations. Fish. Res.

), 239urt, Enary akerel, 290.., Hesncies . Can., A.J., t DepJ.M., 1. (U.S.)J.M., Mdeterm368.

n, J.P., ow-batic sto

J. Man, R.Cent o114.

, Pauly shes, A.G., y of kes. FisM., Beanli,tolithents ip. 723.M., A

sh Sentralarch aochin, T.J., Rrick, s in aine ea.D., MInter

mersort 14httprese

.J.G., T of na338M.C

s andgy on,

Dep://ww

reseM.C., ed Spl ReporojectM.C., Luency(Scom.) 103,, R.J., Mision

tropi N., Wkerel us Repan Goreau on, J.L.,tion ital waon, G(Scomrs. Au

B., Lher, W whose comments and suggestions helped to improveript.

., Siddeek, M.S.M., 1999. Growth and mortality of the narrow-barredackerel, Scomberomorus commerson (Lacepede), in Omani waters. Fish.col. 6, 145160.egg, G.A., Mapleston, A., Tobin, A., 2006. Growth trends of Queensland

Spanish mackerel (Scomberomorus commerson) from otolith back-s. Mar. Freshw. Res. 57 (4), 383393.ournier, D.A., 1981. A method for comparing the precision of a set ofinations. Can. J. Fish. Aquat. Sci. 3, 982983.., Wilson, C.A., 1995. Seasonal timing of opaque zone formation in sh: Secor, D.H., Dean, J.M., Campana, S.E. (Eds.), Recent Developmentslith Research. University of South Carolina, Columbia, SC, pp. 2743.lin, M.J., 1998. Age and growth of school mackerel (Scomberomorusicus) and spotted mackerel (S. munroi) in Queensland east-coasth implications for stock structures. Mar. Freshw. Res. 49, 109120.., Holt, S.J., 1957. On the Dynamics of Exploited Fish Populations. U.K.f Agriculture and Fisheries, Fisheries Investigations (Series 2) (19), pp.

. A collection of empirical relations for use in ecological modelling.ARM Q. 22, 2428.C., 1998. Age Structure of the Commercial Catch of Northern Terri-w-Barred Spanish Mackerel. Final Report to the Fisheries Researchopment Corporation, Fishery Report No. 42. 28 pp., Available at:w.nt.gov.au/d/publications/index.cfm?fm=Fish%20Report.C., Newman, S.J., Ovenden, J.R., Lester, R.J.G., McPherson, G.R., 2007.tructure of Northern and Western Australian Spanish Mackerel. Final

sheries Research and Development Corporation Project 1998/159.nt of Primary Industry, Fisheries and Mines, Northern Territory Gov-ustralia. Fishery Report 88, ivi, 225 pp., Anderson, D.R., 1998. Model Selection and Inference: A PracticalnTheoretic Approach. Springer-Verlag, New York, USA, 353., Begg, G.A., 2002. Fisheries Biology and Interaction in the Northern

Small Mackerel Fishery. Final Report to the Fisheries Research andent Corporation, Canberra. Project No. 92/144 and 92/144.02., Thorrold, S.R., 2001. Otoliths, increments, and elements: keys to ansive understanding of sh populations? Can. J. Fish. Aquat. Sci. 58,

cher, W.J., Pearce, A., Chubb, C.F., 1996. Effect of the Leeuwin Currentuitment of sh and invertebrates along the Western Australian coast.w. Res. 47, 147155.001. Scombridae. Tunas (also albacore, bonitos, mackerels, seershes,o). In: Carpenter, K.E., Niem, V.H. (Eds.), FAO Species Identicationishery Purposes. The Living Marine Resources of the Western Centrall. 6: Bony Fishes Part 4 (Labridae to Latimeriidae), Estuarine Crocodiles,s, Sea Snakes and Marine Mammals. FAO, Rome, pp. 37213764.Nauen, C.E., 1983. FAO species catalogue. Vol. 2: Scombrids of the

Fish. Synopsis 125, 1137.chmidt, D.J., Waltz, C.W., Pickney, J.L., 1988. Age and growth of kingScomberomorus cavalla, from the Atlantic coast of the United States.(U.S.) 87, 4961.nnual Status Report 2009 East Coast Spanish Mackerel Fishery, 13 pp.,w.dpi.qld.gov.au/documents/Fisheries SustainableFishing/ECSM-f.Annual Status Report 2010 Gulf of Carpentaria Line Fishery, 14/www.dpi.qld.gov.au/documents/Fisheries SustainableFishing/2010-df.981. Age and growth of three species of seershes, Scomberomorus, S. guttatus, and S. lineolatus. Ind. J. Fish. 28, 104127.rimes, C.B., 1997. Spatial and temporal variation in age and growth of

erel, Scomberomorus cavalla, 19771992. Fish. Bull. (U.S.) 95, 694708.ghanashinikar, A.P., Brothers, E.B., 1992. Management of the Indo-nish mackerel (Scomberomorus commerson) in Oman. Fish. Res. 15,

Fishstat 19502008. Statistics and Information Service FAO, Rome,//www.fao.org/shery/statistics/software/shstat/en.orsa, P., 2011. Patterns of genetic isolation in a widely distributedh, the narrow-barred Spanish mackerel (Scomberomorus commer-J. Linn. Soc. 104, 886902.995. Annulus formation in otoliths of coral reef sh a review. In:., Dean, J.M., Campana, S.E. (Eds.), Recent Developments in Fish OtolithUniversity of South Carolina, Columbia, SC, pp. 4563.idgway, K.R., 1985. The large-scale environment of the poleward-euwin Current, Western Australia: longshore steric height gradients,ses and geostrophic ow. J. Phys. Oceanogr. 15, 481495.

77 (2Grandco

limimac277

Hall, N.Gsistelatus

Handleymen

Hoenig, Bull

Hoenig, age 364

HoolihanarrgeneICES

LenantoCurr101

Ingles, J.pine

JohnsontalitStat

Kalish, J.H., Pfor oopmSC, p

Kasim, HseerIn: CRese1), C

LangloisKendshe(onl

Lewis, Pand comRepoat: 2010

Lester, Rture59, 8

Mackie, temBiolomerspp., http2010

Mackie, barrFinaon P

Mackie, freqerel (U.S

Marriottpreclarge

Marton,macStattrali Bu

McIlwaivariacoas

McPherserel wate

Molony,Fletc247..M., Al Abdessalaam, T.Z., Francis, F., Al Shamsi, A.T., 2005. Pre-ssessment of biology and shery for the narrow-barred SpanishScomberomorus commerson in the southern Persian Gulf. Fish. Res. 76,

p, S.A., Potter, I.C., 2004. A Bayesian approach for overcoming incon-in mortality estimates using, as an example, data for Acanthopagrus

J. Fish. Aquat. Sci. 61, 12021211.(Ed.), 2010. Fishery Status Reports 2009. Northern Territory Govern-artment of Resources. Fishery Report No. 104. 168 pp.983. Empirical use of longevity data to estimate mortality rates. Fish.

82, 898902.organ, M.J., Brown, C.A., 1995. Analysing differences between twoination methods by tests of symmetry. Can. J. Fish. Aquat. Sci. 52,

Anandh, P., van Herwerden, L., 2006. Mitochondrial DNA analyses ofrred Spanish mackerel (Scomberomorus commerson) suggest a singleck in the ROPME area (Arabian Gulf, Gulf of Oman and Arabian Sea).

r. Sci. 63, 10661074..J., Joll, L., Penn, J., Jones, G.K., 1991. The inuence of the Leeuwinn coastal sheries of Western Australia. J. R. Soc. West. Aust. 74,

, D., 1984. An atlas of the growth, mortality and recruitment of Philip-. ICLARM Techn. Rep. 13, 1127.Fable, W.A.J., Williams, M.L., Barger, l.E., 1983. Age, growth and mor-ing mackerel, Scomberomorus cavalla, from the southeastern Unitedh. Bull. (U.S.) 81, 97106.amish, R.J., Brothers, E.B., Casselman, J.M., Francis, R.I.C.C., Mosegaard,

J., Prince, E.D., Thresher, R.G., Wilson, C.A., Wright, P.J., 1995. Glossary studies. In: Secor, D.H., Dean, J.M., Campana, S.E. (Eds.), Recent Devel-n Fish Otolith Research. University of South Carolina Press, Columbia,729.meer Hamsa, K.M.S., 1989. On the shery and population dynamics ofcomberomorus commerson (Lacepede) off Tuticorin (Gulf of Mannar).

Marine Fisheries Research Institute Bulletin: National Symposium onnd Development in Marine Fisheries Sessions I and II 1987, 44 (Part, India, pp. 4653.adford, B.T., Van Niel, K.P., Meeuwig, J.J., Pearce, A.F., Rousseaux, C.S.G.,G.A., Harvey, E.S., 2012. Consistent abundance distributions of marinen old, climatically buffered, infertile seascape. Global Ecol. Biogeog.rly).ackie, M.C., 2003. Methods Used in the Collection, Preparation

pretation of Narrow-Barred Spanish Mackerel (Scomberomorusn) Otoliths for the Study of Age and Growth. Fisheries Research3. 31 pp., Dept of Fisheries, Perth, Western Australia, Available://www.sh.wa.gov.au/Documents/Pre%202010%20Publications/Pre-arch reports and research contract reports.pdf.hompson, C., Moss, H., Barker, S.C., 2001. Movement and stock struc-rrow-barred Spanish mackerel as indicated by parasites. J. Fish Biol.42.., Lewis, P.D., 2001. Assessment of Gonad Staging Sys-

Other Methods Used in the Study of the Reproductiveof Narrow-Barred Spanish Mackerel, Scomberomorus com-in Western Australia. Fisheries Research Report 136. 25t of Fisheries, Perth, Western Australia, Available at:w.sh.wa.gov.au/Documents/Pre%202010%20Publications/Pre-arch reports and research contract reports.pdf.Gaughan, D.J., Buckworth, R.C., 2003. Stock assessment of narrow-anish mackerel (Scomberomorus commerson) in Western Australia.rt to the Fisheries Research and Development Corporation (FRDC)

No. 1999/151. 242 pp.ewis, P.D., Gaughan, D.J., Newman, S.J., 2005. Variability in spawning

and reproductive development of the narrow-barred Spanish mack-beromorus commerson) along the west coast of Australia. Fish. Bull.

344354.apstone, B.D., 2006. Geographic inuences on and the accuracy and

of age estimates for the red bass, Lutjanus bohar (Forsskal 1775): acal reef sh. Fish. Res. 80 (23), 322328.oodhams, J., Mazur, K., 2010. Torres Strait nsh sheries (Spanishand reef line). In: Wilson, D.T., Curtotti, R., Begg, G.A. (Eds.), Fisheryorts 2009: Status of Fish Stocks and Fisheries Managed by the Aus-vernment. Australian Bureau of Agricultural and Resource Economicsf Rural Sciences, Canberra, Australia, pp. 284293, 535 pp.

Claereboudt, M.R., Al-Ou, H.S., Zaki, S., Goddard, J.S., 2005. Spatialn age and growth of the kingsh (Scomberomorus commerson) in theters of the Sultanate of Oman. Fish. Res. 73, 283298..R., 1992. Age and growth of the narrow-barred Spanish mack-beromorus commerson Lacepede, 1800) in north-eastern Queenslandst. J. Mar. Freshw. Res. 43, 12691282.ai, E., 2010. Mackerel managed shery report: statistics only. In:

.J., Santoro, K. (Eds.), State of the Fisheries and Aquatic Resources

60 S.J. Newman et al. / Fisheries Research 129 130 (2012) 46 60

Report 2009/10. Department of Fisheries, Government of Western Australia,Perth, Australia, pp. 190191, 321 pp.

Molony, B.W., Newman, S.J., Joll, L., Lenanton, R.C.J., Wise, B., 2011. Are WesternAustralian waters the least productive waters for nsh across two oceans? Areview with a focus on nsh resources in the Kimberley region and North CoastBioregion. In: Brocx, M., Meney, K. (Eds.), Symposium on Kimberley Marine andCoastal Science. J. R. Soc. West. Aust. 94 (2), 323332.

Moore, B.R., Buckworth, R.C., Moss, H., Lester, R.J.G., 2003. Stock discrimination andmovements of narrow-barred Spanish mackerel across northern Australia asindicated by parasites. J. Fish Biol. 63, 765779.

Muhling, B.A., Beckley, L.E., Gaughan, D.J., Jones, C.M., Miskiewicz, A.G., Hesp, S.A.,2008. Spawning, larval abundance and growth rate of Sardinops sagax off south-western Australia: inuence of an anomalous eastern boundary current. Mar.Ecol. Prog. Ser. 364, 157167.

Newman, S.J., Williams, D.M., Russ, G.R., 1996. Age validation, growth and mortal-ity rates of the tropical snappers (Pisces: Lutjanidae) Lutjanus adetii (Castelnau,1873) and L. quinquelineatus (Bloch, 1790) from the central Great Barrier Reef,Australia. Mar. Freshw. Res. 47, 575584.

Newman, S.J., Buckworth, R.C., Mackie, M., Lewis, P.D., Wright, I.W., Williamson,P.C., Bastow, P.D., Ovenden, J.R., 2009. Spatial subdivision among assemblagesof Spanish mackerel, Scomberomorus commerson (Pisces: Scombridae) acrossnorthern Australia: implications for sheries management. Glob. Ecol. Biogeogr.18 (6), 711723.

Pauly, D., 1980. On the interrelationships between natural mortality, growth param-eters, and mean environmental temperature in 175 sh stocks. J. Conseil ConseilInt. Explor. Mer 39, 175192.

Pearce, A.F., 1991. Eastern boundary currents of the southern hemisphere. J. R. Soc.West. Aust. 74, 3545.

Pearce, A., Helleren, S., Marinelli, M., 2000. Review of Productiv-ity Levels of Western Australian Coastal and Estuarine Watersfor Mariculture Planning Purposes. Fisheries Research Report No.123. Department of Fisheries, Western Australia, Available at:http://www.sh.wa.gov.au/Documents/Pre%202010%20Publications/Pre-2010 research reports and research contract reports.pdf.

Pepin, P., 1991. Effect of temperature and size on development, mortality, and sur-vival rates of the pelagic early life history stages of marine sh. Can. J. Fish. Aquat.Sci. 48, 503518.

Peters, J.S., Schmidt, D.J., 1997. Daily age and growth of larval and early juvenileSpanish mackerel, Scomberomorus maculatus, from the South Atlantic Bight. Fish.Bull. (U.S.) 95, 530539.

Posada, D., Buckley, T.R., 2004. Model selection and model averaging in phylogenet-ics: advantages of Akaike Information Criterion and Bayesian approaches overlikelihood ratio tests. Syst. Biol. 53, 793808.

Ricker, W.E., 1975. Computation and interpretation of biological statistics of shpopulations. Bull. Fish. Res. Board Can. 191, 1382.

Schnute, J., 1981. A versatile growth model with statistically stable parameters. Can.J. Fish. Aquat. Sci. 38, 11281140.

Shojaei, M.G., Motlagh, S.A.T., Seyfabadi, J., Abtahi, B., Dehghani, R., 2007. Age, growthand mortality rate of the narrow-barred Spanish mackerel (Scomberomerus com-merson Lacepde, 1800) in coastal waters of Iran from length frequency data.Turk. J. Fish. Aquat. Sci. 7, 115121.

Shoji, J., Maehara, T., Tanaka, M., 1999. Short-term occurence and rapid growth ofSpanish mackerel larvae in the central waters of the Seto Inland Sea, Japan. Fish.Sci. 65, 6872.

Sturm, M.G.de.L., Salter, P., 1990. Age, growth and reproduction of the king mack-erel, Scomberomorus cavalla (Cuvier), in Trinidad waters. Fish. Bull. (U.S.) 88,361370.

Sulaiman, Z.H., Ovenden, J.R., 2010. Population genetic evidence for the east-westdivision of the narrow-barred Spanish mackerel (Scomberomorus commer-son, Perciformes: Teleostei) along Wallaces Line. Biodivers. Conserv. 19,563574.

Vetter, E.F., 1988. Estimation of natural mortality in sh stocks: a review. Fish. Bull.(U.S.) 86, 2543.

van Herwerden, L., Mcllwain, J., Al-Ou, H., Al-Amry, W., Reyes, A., 2006. Develop-ment and application of microsatellite markers for Scomberomorus commerson(Perciformes; Teleostei) to a population genetic study of Arabian Peninsulastocks. Fish. Res. 79, 258266.

von Bertalanffy, L., 1938. A quantitative theory of organic growth (inquiries ongrowth laws II). Human Biol. 10, 181213.

Williams, R.E., Lester, R.J.G., 2006. Stock structure of Spanish mackerel Scombero-morus commerson along the Australian east coast deduced from parasite data. J.Fish Biol. 68, 17071712.

Age-based demography and relative fisheries productivity of Spanish mackerel, Scomberomorus commerson (Lacepede) in Wester...1 Introduction2 Materials and methods2.1 Collection and processing of samples2.2 Interpretation of otolith structure2.3 Validation of otolith increment periodicity2.4 Growth and mortality models

3 Results3.1 Seasonal pattern of otolith growth3.2 Micro-increment and annuli counts3.3 Comparison of sectioned and whole otolith annuli counts3.4 Age and growth analysis3.5 Mortality

4 Discussion4.1 Validation and formation of annuli4.2 Assignment and reliability of ages4.3 Juvenile growth4.4 Adult growth4.5 Mortality4.6 Relative productivity and comparison with related fisheries

AcknowledgmentsReferences