70 
Fishery Bulletin 106(1 ) 
the idea that abalone growth is likely to be determined 
by local site-specific influences in addition to regional 
scale influences (McShane and Naylor, 1995; Naylor 
et ah, 2006). Thus, although sites within the Actaeon 
region were variable, similarities were evident between 
sites located in distant regions (e.g., in the southwest 
and Bruny Island). This variability in growth has ob- 
vious implications for the confidence with which it is 
possible to conduct stock assessments for abalone over 
large areas. The description of growth in size-structured 
models is so influential that the interpretation of any 
model outputs would need to be made with great atten- 
tion paid to any potential biases brought about by us- 
ing an under- or over-productive description of growth. 
Estimates of productivity derived from the inverse- 
logistic description of growth would be expected to lie 
somewhere between that predicted by the von Berta- 
lanffy curve and the Gompertz curve. The von Berta- 
lanffy curve predicts very rapid early growth and so, 
all other things being equal, would predict the highest 
productivity levels, whereas the Gompertz curve pre- 
dicts very slow early growth and thus would predict 
the lowest productivity. These differences are why the 
selection of the most appropriate model of growth is 
critical for stock assessments. For blacklip abalone in 
Tasmania the inverse-logistic model provides the most 
realistic representation of the dynamics of growth. 
Acknowledgments 
The authors thank the array of divers who contributed 
to the field work, especially S. Dickson, J. Bridley, T. 
Karlov, C. Jarvis, and M. Porteus. Some of the diving 
was undertaken from off the RV Challenger, crewed by 
M. Francis and J. Gibson. We also thank F. Helidoniotis 
for assistance when preparing the map. 
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