Demographic and risk analyses of spiny dogfish (Squalus suckleyi) in the Gulf of Alaska using age- and stage-based population models
Cindy A. Tribuzio A B C and Gordon H. Kruse A
+ Author Affiliations
- Author Affiliations
A University of Alaska Fairbanks, School of Fisheries and Ocean Sciences, Fisheries Division, 17101 Point Lena Loop Road, Juneau, AK 99801, USA.
B Present address: Auke Bay Laboratories, Alaska Fisheries Science Center, National Marine Fisheries Service, NOAA, 17109 Point Lena Loop Road, Juneau, AK 99801, USA.
C Corresponding author. Email: cindy.tribuzio@noaa.gov
Marine and Freshwater Research 62(12) 1395-1406 https://doi.org/10.1071/MF11062
Submitted: 16 March 2011 Accepted: 21 August 2011 Published: 2 November 2011
Abstract
Demographic models are useful tools for assessing data-limited species and may be an appropriate alternative to cohort analyses for sharks due to their long-lived, slow-growing nature. In this study, age- and stage-based demographic analyses were conducted to examine the intrinsic rebound potential (r) and potential risk of fishing for spiny dogfish (Squalus suckleyi) in the Gulf of Alaska. Monte Carlo simulations were conducted to incorporate input parameter uncertainty. For an unfished population, r was estimated to be 0.02–0.03 year–1. Fishing mortalities (F) of F = 0.04 and 0.03 (age- and stage-based models respectively), resulted in r = 0, indicating that populations fished at higher F are not sustainable. Harvest strategies targeting juveniles (age-based model) and subadults (stage-based model) caused the highest risk of the population falling below defined thresholds (BMSY, B40% and B50%) after 20 years. The age- and stage-based models provided similar estimates of r and sustainable fishing mortality, suggesting that the stage-based model is an appropriate substitute for the age-based model in this case. S. suckleyi and the closely related S. acanthias are often harvested around the world and this modelling approach could be useful to the management of these species and other sharks where data is limited.
Additional keywords: elasmobranch, Leslie models, model comparison, shark.
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