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Apr 4, 2011 - Charles F. Cotton. A,D. , R. Dean Grubbs. B .... C. F. Cotton et al. ..... estimates on the first dorsal fin spine (Cotton 2010). This is because the ...
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Marine and Freshwater Research, 2011, 62, 811–822

Age, growth and reproduction of a common deep-water shark, shortspine spurdog (Squalus cf. mitsukurii), from Hawaiian waters Charles F. CottonA,D, R. Dean GrubbsB, Toby S. Daly-EngelC, Patrick D. LynchA and John A. MusickA A

Department of Fisheries Science, Virginia Institute of Marine Science, College of William and Mary, P.O. Box 1346, Gloucester Point, VA 23062, USA. B Florida State University Coastal and Marine Laboratory, 3618 Highway 98, St. Teresa, FL 32358, USA. C University of Arizona, 1140 E. South Campus Dr Forbes 410, Tucson, AZ 85721, USA. D Corresponding author. Email: [email protected]

Abstract. About half of the extant shark species occur only in deep waters (defined as .200 m depth), yet few published studies on sharks include these taxa. As fisheries worldwide enter deeper waters, the provision of biological data for these little-known taxa is critical to management and conservation. The shortspine spurdog, Squalus cf. mitsukurii, is an abundant shark on the insular slopes of the Hawaiian Islands. We assigned ages by counting growth bands on the enamel caps of both dorsal fin spines. Age estimates ranged from 3 to 26 years for females and from 6 to 23 years for males. Growth was modelled with multiple length-at-age models, fitted using maximum likelihood estimation and nonlinear least-squares methods. For female data, the logistic model yielded the most biologically cogent parameter estimates (LN ¼ 126 cm (total length, TL) and k ¼ 0.080 year1). The two-parameter von Bertalanffy Growth Model yielded optimal model fit and realistic parameter estimates for males (LN ¼ 72 cm (TL) and k ¼ 0.080 year1). Maturity ogives suggested that females and males mature at 64-cm TL (15 years) and 47-cm TL (8.5 years), respectively. Fecundity ranged from 3 to 10 embryos; mating appeared to be aseasonal. We reveal a conservative life history, common among deep-water elasmobranchs, and provide further evidence of geographic variation in reproductive and growth parameters in this nominal species. Additional keywords: fecundity, geographic variation, growth models, squaloid, von Bertalanffy.

Introduction The global harvest of deep-water sharks has increased, primarily owing to collapses in some near-shore fisheries, the advent of more efficient fishing technology and the increased ex-vessel price of shark flesh and liver oil (Irvine 2004; Kyne and Simpfendorfer 2007). This recent increase in fishing effort comes in spite of a considerable body of literature indicating that sharks, particularly deep-water sharks, are highly ‘K-selected’ (MacArthur and Wilson 1967; Musick 1999), characterised by slow growth, high longevity, late maturity and low fecundity (Hoenig and Gruber 1990; Musick 1999; Kyne and Simpfendorfer 2007). As a result of this type of life history, these deep-water species are prone to overexploitation and localised depletion (Musick et al. 2000; Stevens et al. 2000; Morato et al. 2006). To properly manage long-lived animals, such as deep-water sharks, managers need basic taxonomic information, relative species abundances and species-specific information on critical habitats, reproduction, age structure and growth rates (Camhi et al. 1998). The dearth of information available for most deep-water shark species precludes formulation of proper management Ó CSIRO 2011

plans, potentially exacerbating the long-term effects of exploitation at current levels of fishing. The shortspine spurdog, Squalus mitsukurii, is a mediumsized dogfish with a cosmopolitan, but patchy distribution throughout warm waters (Last and Stevens 1994; Compagno et al. 2005). This dogfish inhabits continental and insular shelves and upper slopes, as well as seamounts and ridges, usually in depths 100–500 m. The shortspine spurdog is a hightrophic-level predator, feeding primarily on cephalopods, teleosts and caridean shrimp (Ebert et al. 1992; Corte´s 1999; R. Grubbs, unpubl. data). As with many of the deep-water fishes, little is known about the biology of this species, but a few studies of age, growth and reproduction are reported in the literature (e.g. Litvinov 1990; Wilson and Seki 1994; Fischer et al. 2006). Based on morphometric, meristic and molecular data, previous authors have claimed that the taxon S. mitsukurii represents a species complex (Last and Stevens 1994; Compagno et al. 2005; Last et al. 2007b; White et al. 2007). Taxonomic investigation of this species is ongoing and the identifications of specimens collected for this study remain unverified. As 10.1071/MF10307

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specimens collected for the present study differ in several characters (e.g. head length, interdorsal length; R. Grubbs, unpubl. data) from published morphometric data from the holotype (Last et al. 2007a), we refer to the specimens investigated in the present study as Squalus cf. mitsukurii. Squalus cf. mitsukurii is abundant around the Hawaiian Islands and is taken as by-catch in the lutjanid bottomfish fishery around the main Hawaiian Islands (Daly-Engel et al. 2010). However, these sharks are not harvested and resultant mortality is likely minimal. During 1967–1984, Japanese and Soviet fishing fleets developed an intense trawl fishery for slender armorhead (Pseudopentaceros wheeleri) around the junction of the Emperor Seamount Chain and the Hawaiian Ridge Seamount Chain (Uchida and Tagami 1984; Wilson and Seki 1994). Surveys of the armorhead stock showed that S. mitsukurii was taken as by-catch in the armorhead trawl fishery (Uchida and Tagami 1984). The armorhead fishery ceased more than two decades ago, and that fishery never extended eastward into the main Hawaiian Islands. For these reasons, we assume the population around Oahu has likely undergone minimal historical exploitation. Landings data for S. mitsukurii worldwide are sparse. Last and Stevens (1994) state that ‘small quantities’ of S. mitsukurii are sold in the fish markets of Australia; however, Graham et al. (2001) showed a precipitous decline of this species between 1976–77 and 1996–97 in Australian waters, largely a result of unreported by-catch in other deep-water fisheries in the area. Elsewhere globally, fishing effort for S. mitsukurii is likely to be minimal, but possibly underestimated owing to unreported by-catch and/or misidentification (Cavanagh and Lisney 2003). Accurate information about population age structure and individual growth rate is necessary to understand fish life history and provide data for fisheries management (e.g. growth models, yield per recruit models and stock assessment models). In this

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study, age estimates were obtained from dorsal fin spines to model the growth dynamics of S. cf. mitsukurii. The technique of ageing squaliform sharks by counting enamel growth bands on dorsal fin spines has been well-documented in several studies of a congener, S. acanthias (Kaganovskaia 1933; Holden and Meadows 1962; Nammack et al. 1985; Tribuzio et al. 2010). Formation of these enamel cap growth bands is caused by alternating periods of fast and slow growth coincident with seasonal fluctuations in water temperature, photoperiod and/or food availability (Goldman 2005). Knowledge of reproductive biology, specifically size and age at maturity, fecundity and reproductive seasonality and periodicity, is especially important for the proper management of sharks (Camhi et al. 1998). In the present study, we reported size and age at maturity, apparent periodicity of spawning and fecundity. These parameters were also compared with published data for this species. By determining the growth and reproductive parameters of S. cf. mitsukurii, we can assess whether this species exhibits conservative life history characteristics consistent with other deep-water sharks. Additionally we compared S. cf. mitsukurii life history parameters from Oahu, Hawaii to those reported in the literature from other locales. Such information may be useful in establishing regional management plans, as well as in determining whether the reported variability in life history parameters is locally mediated (e.g. differences in productivity or thermocline depth) or attributable to different species within a species complex. Methods We collected most specimens by demersal trotlines set on the insular slope around the Hawaiian island of Oahu (Fig. 1). We fished 24 trotline sets between 250- and 450-m depth from

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Fig. 1. Map of the Hawaiian archipelago showing locations of Squalus cf. mitsukurii collections and the number of specimens collected at each location (n). Image adapted from Daly-Engel et al. (2010), used with permission.

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January 2005 to November 2008. Lines were fished for 12–14 h, and usually set at dusk and hauled at dawn. Commercial fishermen also provided specimens collected near Oahu and the North-west Hawaiian Islands (NWHI). In total, 124 female and 30 male S. cf. mitsukurii were collected, measured for precaudal, fork and ‘stretched’ total lengths (PCL, FL, and TL, respectively), weighed and dissected. We also removed reproductive tracts, collected vertebrae and intact first (D1) and second (D2) dorsal fin spines and weighed the livers. For male specimens, we measured inner and outer clasper lengths and inspected the vas deferens for coiling. For females, we measured the diameter of the largest oocyte, noted maternity status and counted and measured any visible embryos. Embryos not clearly visible upon inspection (,0–10-mm TL) were assigned a size of 0 mm. Maturity designation in males was determined by the presence of a fully coiled vas deferens and fully calcified, elongated claspers. Maturity designation in females was usually noted by the presence of embryos, but in a few cases by the presence of a stretched (postpartum) uterus or fully enlarged oocytes and oviducal glands. Cleaned vertebral centra were inspected for the presence of growth bands, but visibility was too poor to discern banding in either whole or sectioned centra. Staining vertebral centra with a solution of saturated alizarin red in 1% potassium hydroxide (1 : 9, v/v) did not improve band clarity. Therefore age estimates were obtained solely from dorsal fin spines. Spines were collected and cleaned using trypsin and hot water (,40 g L1) as described in Cotton (2010). Two readers independently assigned ages by counting growth bands on the enamel caps of each cleaned fin spine. Spines were viewed under a low-power dissecting microscope with a bifurcated, episcopic, fibre-optic light source. Any spine yielding an age estimate that differed by more than 2 years was re-examined by both readers jointly, and age was assigned by consensus between both readers. For those age estimates that differed by 2 years or less, the mean value of the two estimates was assigned and used in growth models. Notations were made for damaged or eroded spines. Heterogeneous variability in the weight–length relationship indicated multiplicative error structure and was accounted for using a log-transformed version of the weight–length model (sensu Quinn and Deriso 1999): lnðWi Þ ¼ lnðaÞ þ b  lnðLi Þ þ ei ;

ð1Þ

where Wi is weight, a is condition factor, b represents the curvature of the relationship, Li is length and ei is a random error term. Akaike’s Information Criterion (AIC) was used to evaluate whether growth was isometric (W ¼ aL3) or allometric (W ¼ aLb, b 6¼ 3). Hepatosomatic index (HSI ¼ liver weight/ bodyweight) was calculated and compared by maturity stage using a t-test. An age bias plot was constructed using the means and 95% confidence intervals of reader estimates per age class (Campana et al. 1995). A chi-square test of symmetry was used to look for evidence of systematic disagreement between readers (Hoenig et al. 1995; Campana 2001). As recommended by Cailliet et al. (2006), we fitted multiple growth models to the length-at-age data. Three forms of the

813

von Bertalanffy Growth Function were used: the original form (VBGF; von Bertalanffy 1938; Cailliet et al. 2006): Lt ¼ L1  ðL1  L0 Þekt ;

ð2Þ

where Lt is the predicted length at age t, LN is the asymptotic or theoretical maximum mean length (t ¼ N), L0 is length-atbirth (t ¼ 0) and k is the rate constant; a modified (conventional) form (VBGFmod: Beverton and Holt 1957; Cailliet et al. 2006):  ð3Þ Lt ¼ L1 1  ekðtt0 Þ where t0 ¼ theoretical age when length equals zero; and a twoparameter form with fixed length-at-birth (VBGF2par): Lt ¼ L1  ðL1  23:3Þekt ;

ð4Þ

where the L0 term from the VBGF has been replaced by 23.3 cm, the mean length of term embryos observed in this study. Other growth models included a form of the Gompertz model (Ricker 1975; Mollet et al. 2002; Carlson and Baremore 2005):   ð5Þ Lt ¼ L0 e G 1  ekt ; where G ¼ ln(LN/L0); and the logistic function (Ricker 1979; Carlson and Baremore 2005):  ð6Þ Lt ¼ L1 = 1 þ ekðtaÞ ; where a represents the inflection point of the curve (expressed as t0 in Ricker 1979). Growth models were fitted using both nonlinear leastsquares (LS) and maximum likelihood estimation (ML) using R software (R Development Core Team 2009). Growth model selection was based on AIC. For ML-fitted models, we used a variant of AIC (AICc) developed for small-sample bias adjustment (Burnham and Anderson 2002): AICc ¼ 2 lnðLð^ yÞÞ þ 2k þ ð2kðk þ 1ÞÞ=ðn  k  1Þ; ð7Þ where Lð^ yÞ represents the likelihood estimate, k is the number of model parameters and n is the sample size. For LS-fitted models, we used a variant of AIC developed for nonlinear least-squares methods (Kimura 2008), with the small-sample bias adjustment term from the previous equation: AICc ¼ nð1 þ lnð2p  RSS=nÞÞ þ 2k þ ð2k ðk þ 1ÞÞ=ðn  k  1Þ;

ð8Þ

where RSS is the residual sum of squares of the model. Concordance of model parameter estimates with empirical evidence was also considered for model selection. Maturity and maternity ogives were constructed with SigmaPlot 2000 using logistic regression with male data binned in 2-cm size class intervals and female data binned in 5-cm size class intervals. Male clasper lengths were also fitted with logistic regression using SigmaPlot 2000. The inflection points of the curves were determined visually from each plot.

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Results Somatic growth Length relationships (PCL, FL and TL, Table 1) of S. cf. mitsukurii were nearly identical for both sexes, indicating no sexual dimorphism in the caudal region (see Accessory Publications A, B). Bodyweight of male and female S. cf. mitsukurii followed similar, approximately cubic relationships with length (Table 1 and Accessory Publications C, D). Mature females exhibited a significantly lower HSI than immature females (t95 ¼ 3.2725, P ¼ 0.0015). Similarly, the slope of the regression of bodyweight and liver weight was 0.049 (95% confidence interval (CI) ¼ 0.033–0.066) for mature females and 0.106 (95% CI ¼ 0.096–0.116) for immature females, indicating that the proportional mass of the liver decreased significantly after reaching maturity (Fig. 2). Owing to the small sample size of immature males (n ¼ 4), no test was conducted to determine differences in HSI for males. However, the four values of liver weights for immature males closely align with the regression for mature males, suggesting that differences Table 1. Equations for length and weight relationships in Squalus cf. mitsukurii Length was expressed as total length (TL), fork length (FL) and precaudal length (PCL) and measured in cm. Bodyweight (W) was also calculated in terms of TL and measured in g Conversion type

Sex

Length conversions

r2

Variable Equation

Female TL FL TL Male TL FL TL Weight conversions Female W Male W

1.2160(PCL) þ 2.2200 1.0930(PCL) þ 0.7688 1.1116(FL) þ 1.4150 1.2132(PCL) þ 2.0997 1.0974(PCL) þ 0.4536 1.1050(FL) þ 1.6250 0.0007  TL3.45 0.0022  TL3.13

0.9972 0.9987 0.9969 0.9908 0.9961 0.9937 0.9750 0.9369

in HSI between mature and immature males is not likely to be significant (Fig. 3). Age determination Overall readability was similar between fin spines for both sexes. Sexual dimorphism of fin spines was observed, with mature male fin spines bearing a proximal constriction of the enamel cap on the anterior surface of each spine (Fig. 4). For this reason, mature male spines were more difficult to interpret. Immature male fin spines resembled female fin spines. Eroded and broken fin spines did not present problems in ageing, as has been found in S. acanthias (Nammack et al. 1985). Erosion, when present, was usually confined within the first annulus and therefore did not require a correction factor for age assignment. The incidence of broken spine tips was low in both sexes, and usually occurred so far distally that age determination was not affected in most cases. Of the total number of female fin spines aged (n ¼ 244), 31 spines were broken (D1 ¼ 16, D2 ¼ 15) and for males (n ¼ 60 spines aged) 7 spines were broken (D1 ¼ 5, D2 ¼ 2). Age estimates ranged from 3 to 26 years for females and 6 to 23 years for males (Fig. 5). Reader agreement was 0–2 years for 255 of 303 (84.2%) spines (Table 2), and for 48 spines (15.8%), reader agreement was .3 years; none of these came from sharks younger than 10 years. For most age classes, Reader 1 recorded age estimates higher than Reader 2, resulting in a slight nonlinear bias in the inter-reader agreement (Table 2, Fig. 6). We rejected the hypothesis of symmetry between ages assigned by both readers (x2 ¼ 112.66, P , 0.001, d.f. ¼ 61), indicating that disagreement between readers was systematic and not owing to random error. Growth models Growth models were fitted to length-at-age data for each sex independently (Fig. 5). For females, the LS-fitted VBGF and VBGFmod models did not converge. Otherwise, parameter estimates were generally similar among models (Tables 3, 4), 90

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Fig. 2. Relationship of liver weight to total weight for female Squalus cf. mitsukurii collected around Oahu, Hawaii. Measurements for immature and gravid females are represented by closed and open circles, respectively. Data for five mature, non-gravid females are indicated by inverted triangles and were not used to generate either regression.

0

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Fig. 3. Relationship of liver weight to total weight in male Squalus cf. mitsukurii collected around Oahu, Hawaii. Measurements for immature and mature males are represented by closed and open circles, respectively. Since data were available for only four immature individuals, no regression was generated for those data.

Shortspine spurdog age, growth and reproduction

with the exception of LN, which varied considerably among models and with respect to method of model fitting. For males, both methods of model fitting (LS and ML) yielded similar estimates of growth parameters with all models. Analysis of residuals verified the assumption of a normal error structure and homoscedasticity for length-at-age data of both sexes. The AICc for females varied considerably with the ML-fitted Gompertz model and the LS-fitted VBGF2par yielding the lowest AICc values for each method of model fitting. However, for males, AICc values were generally similar for all growth models, irrespective of method of model fitting, with the logistic model yielding the lowest AICc value. All growth model estimates of length at birth (L0) for both sexes were similar to the observed mean size of term embryos (23.3 cm). Growth model parameters estimated in the present study were compared with those published in the literature for this species (Table 5). Reproduction Elongation of male claspers slowed considerably after the onset of maturity at ,50-cm TL (Fig. 7c). This corroborates the male maturity ogive, which shows that 50% of the males sampled were mature at 47 cm (Fig. 7a). The estimate of size-at-maturity is tentative owing to the small number of males encountered in the present study (4 immature, 25 mature). Approximately 50% of females sampled were mature at 64 cm, with size-at-maturity spanning 56–75 cm (Fig. 7a). Approximately 50% of females sampled were pregnant at 70.5 cm, and 100% of females sampled were pregnant at sizes .80 cm, suggesting a continuous

Marine and Freshwater Research

reproductive cycle (Fig. 7b). Oocyte diameter in pregnant females increased throughout embryonic development until parturition, further indicating that the reproductive cycle is continuous in this species (Fig. 7d). The largest oocyte observed in a mature, non-gravid female was 40.5 mm, approximately the same size observed in females with near-term embryos. There was no relationship between embryo size and month of capture, indicating an asynchronous reproductive cycle (see Accessory Publication E). There was a positive relationship between maternal size (TL) and fecundity, with an apparent maximum fecundity of 10 embryos (Fig. 8). Discussion Somatic growth The relationship of weight to length was nearly cubic for both sexes, similar to most other fishes (Helfman et al. 2009). Data for immature females fit the regression very closely, but pregnant females exhibited more variability, owing to variation in fecundity and stages of embryonic development. The allometric model (AIC ¼ 165.02) yielded a better fit than an isometric model (AIC ¼ 107.23) with cubic growth. For males, AIC values indicated substantial support for either the allometric (AIC ¼ 43.82) or isometric model (AIC ¼ 45.07) with cubic growth. Changes in liver weights (HSI) of mature females can reflect the large energy demands of pregnancy. In this study, we found a significant decrease in HSI after females reached maturity. Walker (2005) reported a different trend for Galeorhinus galeus,

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Fig. 4. Dorsal fin spines of (a) mature female and (b) mature male Squalus cf. mitsukurii. Black arrows represent annual growth bands on the spines of this 12-year-old female and 15-year-old male. Growth bands are evident as faint smudges on the surface of the enamel cap. The bases of both female spines were damaged during sampling, hence the diagonal shape of the D2 base and shorter TSL of both spines. Scale bar, 10 mm.

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may compensate any loss in buoyancy caused by the decreased HSI in gravid females. For males, there was no apparent reduction in HSI observed after maturity, likely because males do not undergo a similarly energy-taxing process as female pregnancy.

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Fig. 5. Growth models fitted to size-at-age data for (a) female and (b) male Squalus cf. mitsukurii collected around Oahu, Hawaii.

in which liver weight increased concurrently with vitellogenesis. This is likely because G. galeus and S. cf. mitsukurii have different reproductive cycles. The ovarian cycle in G. galeus is triennial, with vitellogenesis occurring mainly in the absence of embryonic development. Therefore, females of that species are able to sequester large energy reserves in the liver after parturition to support vitellogenesis. However, in S. cf. mitsukurii, the reproductive cycle is continuous and the entire ovarian cycle occurs while the female is carrying embryos in utero. Therefore, females of this species do not have the opportunity to build energy reserves in the liver after parturition because vitellogenesis is essentially a continuous, energy-taxing process (Fig. 7d). How this HSI reduction in mature females affects buoyancy remains unclear. The net effect of numerous large, positively buoyant ovarian oocytes, along with numerous embryonic livers,

Age determination Both readers had prior experience in ageing confamilial species (i.e. S. acanthias and Cirrhigaleus asper), but found S. cf. mitsukurii fin spines to be considerably more difficult to read. Thus, age determination required a great deal of effort to examine each spine at many angles, under varying degrees of light intensity. Age estimates obtained from the two fin spines (D1 and D2) were similar for males, but females often yielded higher age estimates on the first dorsal fin spine (Cotton 2010). This is because the enamel cap of the first dorsal fin spine is longer and wider in older females, offering a greater surface area for band visualisation. The spines of mature males presented difficulties in reading owing to the proximal constriction of the enamel cap on the anterior surface of the spine. Growth bands deposited on the small, constricted surface of the enamel cap after maturation were tightly spaced and often difficult to discern. Of the 48 spines with the largest age discrepancies (.2 years), 18 were from mature males (30% of 60 male spines examined) and 30 were from females (12% of 243 female spines examined). Thus, males were disproportionately represented, owing to the difficulty in interpreting growth bands on mature male spines. Though reader bias was evident, it is likely that it did not pose a problem in the present study. Most of the discrepancies in age were limited to 1- or 2-year differences, and because mean age estimates were used in these instances, the final effects of such differences were likely to be negligible (0.5–1 year). In cases of larger age discrepancies, the readers reviewed the spines together and reached a consensus on age assignment. Growth models Overall, growth models showed that males grow faster, mature earlier and reach a smaller maximum size than females, a common pattern in elasmobranchs. Cailliet et al. (2006) recommended fitting age data to multiple growth models, so we used five common models, with two different techniques of model fitting (LS and ML). Overall model fit was better for male size-at-age data than for female data, as shown by the lower RSS (LS) and s (ML) values. In the case of female size-at-age data, optimisation was more efficient using maximum likelihood estimation than leastsquares, possibly owing to limitations posed by the lack of an asymptote in the curve. Two of the LS-fitted models did not converge and only the LS-fitted logistic model yielded plausible parameter estimates for female S. cf. mitsukurii. Estimates of female LN (both LS and ML-fitted) were unrealistically high in most models, probably owing to a lack of older individuals being sampled (Cailliet and Tanaka 1990). Wilson and Seki (1994) found only two individuals older than 20 years around Hancock Seamount and attributed the lack of older individuals to extensive harvest that occurred before their collections in 1986. This explanation is unlikely in the present study as Hancock Seamount is .2500 km from Oahu, Hawaii. The differences in growth and reproductive parameters suggest that individuals from Oahu and Hancock Seamount

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Table 2. Consistency in age estimates between readers of anterior (D1) and posterior (D2) dorsal fin spines of male and female Squalus cf. mitsukurii The total number of spines aged was 303; three spines were missing, one spine was deemed unreadable by Reader 1 and one spine was deemed unreadable by Reader 2 Consistency of age estimates

D1 female

D1 male

D1 total

D2 female

D2 male

D2 total

Grand total

Reader 1 ¼ Reader 2 Reader 1 . Reader 2 þ1 year þ2 years þ3 years þ4 years þ5 years þ6 years Total Reader 1 , Reader 2 1 year 2 years 3 years 4 years 5 years Total

36 (11.9%) – 30 16 9 2 1 0 58 (19.1%) – 14 10 1 2 1 28 (9.2%)

6 (2.0%) – 4 6 4 2 0 1 17 (5.6%) – 4 1 1 0 1 7 (2.3%)

42 (13.9%) – 34 22 13 4 1 1 75 (24.8%) – 18 11 2 2 2 35 (11.6%)

26 (8.6%) – 28 22 5 0 0 1 56 (18.5%) – 19 12 3 4 1 39 (12.9%)

5 (1.7%)

31 (10.2%)

73 (24.1%)

3 10 6 0 0 1 20 (6.6%) – 3 0 2 0 0 5 (1.7%)

31 32 11 0 0 2 76 (25.1%) – 22 12 5 4 1 44 (14.5%)

65 54 24 4 1 3 151 (49.8%) – 40 23 7 6 3 79 (26.1%)

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Fig. 6. Age bias plot showing means and 95% confidence intervals of age estimates from Reader 1 for each age class determined by Reader 2.

are isolated, with independent, site-specific life history parameters. Taniuchi et al. (1993) and Taniuchi and Tachikawa (1999) showed a high degree of intraspecific variability in biological parameters of this species (or possibly species complex) across the north-central and north-western Pacific Ocean. A few specimens in the present study (n ¼ 8), including the largest female, were from commercial fishermen operating around the NWHI (Fig. 1). Although no genetic differences exist between individuals from Oahu and the NWHI (DalyEngel et al. 2010), individuals from the NWHI may have slightly different, locally influenced growth parameters compared with those taken around Oahu. Both methods of model fitting (LS and ML) performed comparably with the male size-at-age data. All models (LS and ML) that included an L0 term yielded estimates that were

near the observed size at birth (23.3 cm) for both sexes. These results suggest that when size-at-age data yield a good model fit, either method of model fitting (LS or ML) generates similar parameter estimates. However, when size-at-age data are limited (e.g. lacking an asymptote), maximum likelihood estimation may provide more robust parameter estimates. Model selection was based on the lowest DAICc value, while factoring the agreement of model parameter estimates with observed values of maximum size and size-at-birth. For females, the logistic model was selected as the best model because the DAICc values were low for each method of model fitting and the estimates of LN were closest to the observed maximum size of 101-cm TL. The maximum size reported for this species is 125 cm and only one species (S. acanthias) in the family Squalidae exceeds 125-cm TL (Compagno et al. 2005). The logistic model estimate of LN (126 cm) therefore provided a more reasonable estimate than all the other models. Model parameter estimates for males were nearly identical across models, irrespective of method of model fitting (LS or ML), and the VBGF2par was selected as the best model. Although the AICc value for the logistic model was lowest for males, this model was rejected because the estimate of LN (64.81 cm) was lower than the maximum size (67 cm) observed in the present study. The parameter t0 has no biological meaning when modelling age and growth of elasmobranchs (Cailliet et al. 2006) and other species with large offspring, and therefore will not be discussed here. Comparing model parameter estimates from this study with those of previous studies of S. cf. mitsukurii is not straightforward, given the variety of models used in the present study, the problematic estimates of female LN generated by our models, and the possibility that multiple populations or species were involved in these studies. Hancock Seamount is geographically closer to Oahu than the other sampling sites listed in Table 5, yet the growth parameters (particularly k) reported from that region are quite different to those of our study, suggesting these studies involved a different species to that used in the present study.

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Table 3. Estimates of model parameters (6s.e.), standard deviation (r, for ML-fitted models), residual sum of squares (RSS, for LS-fitted models), model likelihood values (2ln(L), for ML-fitted models), and model selection statistics (AICc and DAICc) for length-at-age data for female Squalus cf. mitsukurii Empirical mean length-at-birth (L0 ¼ 23.3 cm) was used in the VBGF2par model. The VBGF and VBGFmod models failed to converge using nonlinear leastsquares, as indicated by ‘–’ Model Maximum likelihood estimation VBGF VBGFmod VBGF2par Gompertz Logistic Least-squares VBGF VBGFmod VBGF2par Gompertz Logistic

LN (cm TL)

k (year1)

L0 (cm TL)

t0 (year)

s

RSS

ln(L)

AICc

DAICc

208.32  24.97 164.59  13.25 203.84  20.62 150.71  22.41 126.16  12.36

0.02  0.00 0.02  0.00 0.02  0.00 0.04  0.01 0.08  0.01

23.89  1.20 NA NA 27.71  1.36 NA

NA 6.34  0.58 NA NA 14.83  2.52B

4.70  0.29 4.80  0.30 4.73  0.29 4.65  0.29 4.71  0.29

– – – – –

388.60 391.62 388.92 387.10 388.70

785.51 791.57 784.03 782.53 785.73

2.98 9.04 1.50 0.00 3.20

– – 318.69  120.13 170.50  31.80 127.75  13.18

– – 0.01  0.00 0.04  0.01 0.08  0.01

– NA NA 27.82  1.37 NA

NA – NA NA 15.16  2.68B

– – – – –

– – 2850.81 2827.70 2897.56

– – – – –

– – 781.45A 782.51A 785.71A

– – 0.00 1.06 4.26

LS models used k þ 1 parameters in the AICc calculation to standardise LS AICc and ML AICc, since ML models estimate one extra parameter (s). This value represents the variable ‘a’ in the logistic equation, or the inflection point of the growth curve, not t0.

A B

Table 4. Estimates of model parameters (6s.e.), standard deviation (r, for ML-fitted models), residual sum of squares (RSS, for LS-fitted models), model likelihood values (2ln(L), for ML-fitted models), and model selection statistics (AICc and DAICc) for length-at-age data for male Squalus cf. mitsukurii Empirical length-at-birth (L0 ¼ 23.3 cm) was used in the VBGF2par model Model Maximum likelihood estimation VBGF VBGFmod VBGF2par Gompertz Logistic Least-squares VBGF VBGFmod VBGF2par Gompertz Logistic

LN (cm TL)

k (year1)

L0 (cm TL)

t0 (year)

s

RSS

ln(L)

AICc

DAICc

71.92  4.49 71.83  4.38 72.13  4.52 72.91  3.98 64.81  1.88

0.08  0.01 0.08  0.01 0.08  0.01 0.13  0.01 0.18  0.02

23.08  1.10 NA NA 23.08  1.08 NA

NA 4.75  0.64 NA NA 3.25  0.50B

2.94  0.34 2.94  0.34 2.95  0.34 2.89  0.34 2.84  0.33

– – – – –

92.45 92.46 92.47 91.71 91.14

194.16 194.16 191.67 192.67 191.52

2.64 2.64 0.15 1.15 0.00

71.98  4.42 71.97  4.92 72.13  4.85 67.33  2.86 64.81  2.01

0.08  0.02 0.08  0.02 0.08  0.02 0.13  0.02 0.18  0.02

23.08  1.15 NA NA 23.09  1.12 NA

NA 4.76  0.71 NA NA 3.25  0.53B

– – – – –

320.73 320.73 321.06 308.08 298.67

– – – – –

194.16A 194.16A 191.67A 192.67A 191.52A

2.64 2.64 0.15 1.15 0.00

LS models used k þ 1 parameters in the AICc calculation to standardise LS AICc and ML AICc, as ML models estimate one extra parameter (s). This value represents the variable ‘a’ in the logistic equation, or the inflection point of the growth curve, not t0.

A B

Alternately, the apparent disparity in growth parameters could be a result of differences in sampling. Taniuchi and Tachikawa (1999) collected data in 1973, a period of intense harvest of the pelagic armorhead (and by-catch of S. mitsukurii), whereas Wilson and Seki (1994) collected data in 1985–88, after the fishery had effectively ceased and a moratorium was in place. Additionally, Taniuchi and Tachikawa (1999) may have experienced data limitations, as the depth range they sampled around Hancock Seamount was quite narrow (263–290 m). Furthermore, growth parameters reported in the present study are as similar to those from the Ogasawara Islands as they are to those from Hancock Seamount (Taniuchi and Tachikawa 1999). Differences in growth parameters between Oahu, where most samples in the present study were collected, and Hancock Seamount could be

owing to latitudinal variation between Oahu (218270 N) and Hancock Seamount (308180 N), or possibly to site-specific growth rates controlled by the local productivity within these areas. Differences in growth parameters in our study and those reported from Japan (Choshi and Ogasawara: Taniuchi and Tachikawa 1999) and the South Pacific (Sala-y-Gomez seamounts: Litvinov 1990) might be a result of intraspecific geographic variation, or more likely these studies involved a different species than the present study. Another explanation for the observed differences in growth model parameters could be that none of these prior studies examined multiple growth models for parameter estimation, which can vary substantially, as indicated by our results. The rate constant k was low for both sexes in all models. The values of k estimated by the Gompertz and logistic models for

Shortspine spurdog age, growth and reproduction

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Table 5. Comparisons of growth model parameters reported in various studies of Squalus cf. mitsukurii The variables tmax and tmat represent maximum observed age and observed age at maturity, respectively. All model parameters were estimated using the LSfitted VBGFmod (Eqn 3), except those labelled as ‘best growth models’ Location and source

Sex

Sala-y-Gomez (Litvinov 1990)

~ # ~ # ~ # ~ # ~ # ~ # ~ #

Hancock Seamount (Wilson and Seki 1994) Hancock SeamountC (Taniuchi and Tachikawa 1999) Ogasawara Islands, Japan (Taniuchi and Tachikawa 1999) Choshi, Japan (Taniuchi and Tachikawa 1999) Present study (VBGFmod) Present study (best growth models)D

LN (cm TL)

k (year1)

t0 (year)

tmax (year)

tmat (year)

104A 100A 107 66 83 65 111 88 163 109 165 72 126 72

– – 0.041 0.155 0.103 0.252 0.051 0.060 0.039 0.066 0.020 0.080 0.080 0.080

– – 10.09 4.64 2.94 0.43C 5.12 5.57C 5.21 5.03 6.34 4.75 14.83 NA

15 14 27 18 17 12 27 21 21 20 26 23 26 23

6–15B – 15 4 14–16 6–7 15–17C 9–10C 19–20C 10–11 15 8.5 15 8.5

A

Values are maximum observed length (Lmax), not LN. Estimated from length-at-age curve. C Transcriptional and typographical errors were reported in Cailliet and Goldman (2004). Parameter estimates reported here are corrected. ‘SE Hancock Seamount’ was referenced previously as ‘Japan, SE Harbor’. D Best model parameters: females, logistic model; males, VBGF2par model. B

females (0.04–0.08) are among the lowest reported growth coefficients for any elasmobranch species (Cailliet and Goldman 2004). With such slow growth rates, this species is not resilient to extensive harvest and is therefore prone to overexploitation and localised depletion in those areas where harvested in abundance (Hoenig and Gruber 1990; Kyne and Simpfendorfer 2007). Age validation has been performed using multiple techniques on a congeneric species, S. acanthias (Beamish and McFarlane 1985; Tucker 1985; Campana et al. 2006). Although we were unable to validate the periodicity of growth band formation in this study, we assumed that S. cf. mitsukurii deposits growth bands in the same manner and with the same frequency as S. acanthias. Squalus acanthias is a high-latitude, shallower-dwelling species that experiences more variation in temperature seasonally. However, temperature is only one of the major factors controlling growth, others being food quality and abundance. Although S. cf. mitsukurii may not experience similar magnitudes of seasonal temperature fluctuations, this species probably experiences seasonal variation in food availability, as the food web responds to seasonal pulses of marine snow (Billett et al. 1983; Karl et al. 1996). Ziemann (1975) also noted seasonal changes in distribution of oplophorid shrimp, one of the primary components of the diet of S. cf. mitsukurii (R. Grubbs, unpubl. data). These seasonal changes in primary production and prey availability could result in alternating periods of fast and slow growth coincident with the formation of growth bands on the dorsal fin spines (Goldman 2005). Reproduction According to the maturity ogives, females of this species reach sexual maturity at ,64 cm, or 63% of the maximum observed size (101-cm TL) and 15 years, or 58% of the maximum observed age (26 years). Males mature at ,47 cm, or 70% of

their maximum observed size (67-cm TL) and 8.5 years, or 37% of their maximum observed age (23 years). The maternity ogive was calculated using a slightly different criterion than that which Walker (2005) used for Galeorhinus galeus. Because reproduction is aseasonal and gestation period is unknown for S. cf. mitsukurii, there was no way of predicting time of parturition in postpartum females or females with term embryos, as Walker (2005) did for G. galeus. Therefore, in the present study, we used the term ‘maternal condition’ to denote only pregnant females. Fecundity ranged mostly from four to ten pups for S. cf. mitsukurii. Although we observed three females with smaller clutches, these small clutch sizes were likely the results of stressinduced abortion. If this species undergoes a two-year reproductive cycle, like S. acanthias, then females may carry only three to seven clutches of pups in a lifetime. Given the maximum observed age, the range of fecundity we present here, and a continuous, asynchronous reproductive cycle, the species might have lifetime fecundity as low as 12–70 pups. The difference in age estimates for maturity and maternity ogives is three years, suggesting that the reproductive cycle might be even longer than that of S. acanthias, which would reduce these estimates of lifetime fecundity. Graham (2005) found a similar range of fecundity in Australian S. mitsukurii, although this study may have been conducted on a different population or species than the present study. Maturity ogives presented by Graham (2005) also indicated larger sizes-at-maturity (female L50% maturity ¼ 81 cm; male L50% maturity ¼ 63 cm) than those of our study. Likewise, Fischer et al. (2006) reported similar fecundity estimates in Atlantic S. mitsukurii from the north-east coast of Brazil, but the maturity ogives also indicated larger sizes-at-maturity (female L50% maturity ¼ 78 cm; male L50% maturity ¼ 65 cm) than those reported in the present study. Lucifora et al. (1999) presented

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C. F. Cotton et al.

(b) 1.0

1.0

0.8

0.8 Proportion mature

Proportion mature

(a)

0.6

0.4

0.2

0.4

0.2

0.0 40

50

60

70 TL (cm)

80

90

0.0

100

40

50

60

70 TL (cm)

80

90

200

250

100

(d )

(c)

50

60

Oocyte diameter (mm)

50 Clasper length (mm)

0.6

40 30 20 10

40

30

20

10

0

0 40

45

50

55

60

65

70

0

50

100

150

300

Embryo TL

TL (cm)

Fig. 7. Reproductive biology of Squalus cf. mitsukurii collected around Oahu, Hawaii. (a) Length-based maturity ogives for females (open circles) and males (closed circles). Size class intervals are 5 cm for females and 2 cm for males. Length at 50% maturity (L50% maturity) for females corresponded to ,64 cm (,15.0 years) and the male L50% maturity was ,47 cm (,8.5 years). (b) Length-based maternity ogives for females. Size class intervals are 5 cm. Length at which 50% of specimens examined were pregnant (L50% maternal) was ,70.5 cm (,18 years). (c) Relationship of inner (closed circles) and outer clasper lengths (open circles) to length (TL) of males. Outer clasper lengths were not recorded for four individuals. (d) Ovarian development concurrent with gestation in pregnant females. Embryos not clearly visible upon inspection (,0–10 mm TL) were assigned a size of 0 mm. Mean observed TL of full-term pups was 233 mm.

8

sizes at maturity from the Uruguayan–Argentine Common Fishing Zone that closely agree with maturity ogives from the present study. It is doubtful, however, that any of these studies were conducted on the same population or species, as these studies were conducted far from Hawaii and the taxon S. mitsukurii comprises a species complex (Last and Stevens 1994; Compagno et al. 2005; Last et al. 2007b).

6

Conclusions

12

Fecundity (# embryos)

10

4

2

0 60

65

70

75

80 85 90 Maternal TL (cm)

95

100

105

Fig. 8. Fecundity versus length (TL) of pregnant female Squalus cf. mitsukurii collected around Oahu, Hawaii.

Squalus cf. mitsukurii exhibits a long-lived life history, characterised by slow growth, high longevity, late maturity and low fecundity (Musick 1999). The maximum age is at least 26 years for females and 23 years for males, and sexual maturity is reached at 58% and 37% (respectively) of the maximum observed age in this study. Estimates of the growth coefficient (k) were very low, and lifetime fecundity is unknown for this species, but conservatively estimated to be between 12 and 70 pups. With such population characteristics and among the lowest genetic diversity reported for any elasmobranch (Daly-Engel et al. 2010), which limits rebound potential, S. cf. mitsukurii cannot

Shortspine spurdog age, growth and reproduction

sustain high levels of fishing mortality. In areas currently experiencing overfishing, this species will require a long recovery time once proper management procedures are in place. Elsewhere, if fisheries are to be developed, it would be advisable to proceed conservatively. The high degree of geographic variability in reproductive and growth parameters reported in the literature for S. cf. mitsukurii is either attributable to variability among isolated populations of a single species that are influenced by local conditions, or possibly a result of the sampling of multiple species within a species complex. A recent taxonomic study in Australia yielded six new species of Squalus, many of which were previously cryptic (Last et al. 2007b). It is likely that cryptic species exist globally within the taxon ‘Squalus mitsukurii’, and these have all been historically identified as the same species. Future taxonomic work is needed within this genus to help resolve these uncertainties. Acknowledgements We thank Kim Holland, Dave Itano, Brian Bowen, Rob Toonen and Michelle Gaither at the Hawaii Institute of Marine Biology for support and assistance in collecting samples. Also, several fishermen (Timm Timoney, Gary Dill, Leonard Yamada, Burt Kikkawa, K. Kawamoto and Stephen Lee) and researchers (Bo Alexander, Chris Kelley) provided specimens for this study. We thank Jason Romine and Henry Mollet for their assistance with growth models, as well as Jose Castro, Tracy Sutton, Michael Vecchione and two anonymous referees for valuable comments on the manuscript. Funding was provided by the Evolution, Ecology, and Conservation Biology Program at the University of Hawaii and the National Shark Research Consortium.

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Manuscript received 7 December 2010, accepted 4 April 2011

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