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Fishery Bulletin 108(2) 
of the effect of total fishing mortality on biomass and 
an investigation of spiny dogfish life history character- 
istics in Alaska. 
Biological reference points (e.g., B MS Y , F 35% ) are 
benchmarks against which stock abundance or fishing 
mortality rates can be compared to determine stock 
status. Most commonly used reference points are func- 
tions of stock productivity, such as growth, recruitment, 
and natural mortality (Bonfil, 2005); thus accurate es- 
timates of age and growth are important. For instance, 
estimates of age and the growth coefficient (k) are criti- 
cal for estimating natural mortality (M), where a lack 
of data prevent direct estimation of M, abundance, and 
appropriate harvest rates. In the GOA, biological refer- 
ence points, such as those from age and growth models, 
have yet to be determined for spiny dogfish. 
Extension of life history parameters from other re- 
gions to Alaska may be inappropriate because age and 
growth characteristics of spiny dogfish vary widely over 
its geographic range. For example, maximum age in the 
northwest Atlantic Ocean is 35-40 years (Nammack 
et al., 1985), but in the eastern North Pacific, spiny 
dogfish have been aged to over 80 years (Saunders and 
McFarlane, 1993). Growth characteristics also vary 
widely throughout the North Pacific and North Atlantic 
oceans (Ketchen, 1975; Nammack et al., 1985). Even 
within the North Pacific basin, biological parameters, 
such as k, can vary with latitude (Vega, 2006). 
The selection of an appropriate growth model is im- 
portant when estimating regionally specific parameters. 
Elasmobranch age and growth studies have generally 
focused on fitting length-at-age data to the von Berta- 
lanffy (vB) growth equation, irrespective of goodness- 
of-fit or alternative growth models (Carlson and Bare- 
more, 2005). Despite its common use, the vB growth 
equation may not be the best-fit growth model for all 
elasmobranch species. For example, the logistic model 
fitted best among four models tested for the spinner 
shark ( Carcharhinus brevipinna, Carlson and Baremore, 
2005), and a two-phase vB model fitted best among five 
models for the piked spurdog ( Squalus megalops, Brac- 
cini et al., 2007). A model that is not the best descriptor 
of a species’ growth could have compounding effects on 
demographic analyses, stock assessment, and fishery 
management. 
Typical growth models involve parameters of asymp- 
totic length (L^), k, and t 0 (Cailliet et ah, 2006). The t 0 
parameter is biologically difficult to interpret because 
it is not measurable and testable in wild animals (Be- 
verton and Holt, 1957). This parameter is the age at 
which the animal is of zero length and is based on an 
assumption of a fixed growth curve from fertilization 
through life (Beverton and Holt, 1957). It is generally 
interpreted to represent the period of gestation in tele- 
ost fish species, but this assumption is violated for elas- 
mobranchs (Driggers et al., 2004). For instance, when 
considering males and females separately, models will 
estimate different t 0 values. If f 0 is truly representative 
of gestation time, then it leads to the incorrect infer- 
ence that male and female pups have different gestation 
periods. For these reasons, growth models that use size 
at birth (L 0 ) instead of t 0 may be more appropriate for 
elasmobranchs (Cailliet and Goldman, 2004). 
The purpose of this study was to estimate best-fit 
growth models for male and female spiny dogfish in 
the GOA. Resultant growth equations provide critical 
parameters for a better understanding of spiny dogfish 
biology, estimation of biological reference points includ- 
ing indirect estimates of M, improved stock assess- 
ments, and development of sound fishery management 
plans for this species in waters off Alaska. 
Materials and methods 
Sample collection 
Spiny dogfish were collected by targeted sampling 
cruises, state and federal assessment surveys, and oppor- 
tunistic fishery bycatch samples between July 2004 and 
April 2007 across the GOA (Fig. 1, Table 1 (delete bold 
font after placing tables). All spiny dogfish were sexed 
and length was measured to the nearest centimeter 
(total length extended=T , L ej .,; total length natural^TL^; 
precaudal length=PCL; and fork length=FL; Tribuzio et 
al., 2009). Here, length measurements are reported as 
total length extended (TL ext ). The posterior dorsal spine 
was removed and stored frozen for laboratory analyses. 
In the laboratory, spines were cleaned by thawing, by 
boiling briefly, and the loose tissue was scraped free. 
Spines were allowed to dry overnight and then stored in 
individual paper envelopes for subsequent age reading. 
Sampling bias was examined because we sampled 
with multiple gear types in different locations. To test 
for potential bias, a chi-squared (x 2 ) test was conducted 
to test for statistically significant (P<0.05) differences 
in the mean length at age by sex for each gear (trawl, 
setnet, longline, rod and reel) and region (Cook Inlet, 
Prince William Sound, Yakutat Bay, and Gulf of Alas- 
ka). Statistically significant differences among different 
gears would provide evidence of sampling bias. However, 
statistically significant differences among different geo- 
graphic areas would provide equivocal evidence of bias 
because the possibility of true underlying differences in 
size distributions by area could not be dismissed. 
Age determinations 
The posterior dorsal spines were read in the laboratory 
according to the methods of Ketchen (1975) and Beamish 
and McFarlane (1985). Each band pair (hereafter termed 
“band”), consisting of one dark and one light band, was 
counted as one year or annulus (Cailliet et al., 2006). 
Aging was conducted by two scientists at the Washington 
Department of Fish and Wildlife’s age laboratory and by 
the lead author at the University of Alaska Fairbankans. 
Ease of age reading was categorized from 1 (easiest) to 3 
(most difficult). Spines were photographed on a lxl mm 
grid to standardize measurements. All measurements 
were rounded to the nearest 0.01 mm by using Bersoft 
