King Crab Stock Assessments in Alaska

2014 ◽  
pp. 519-538 ◽  
Author(s):  
Jie Zheng ◽  
Gordon Kruse
Keyword(s):  
2012 ◽  
Vol 69 (4) ◽  
pp. 624-634 ◽  
Author(s):  
André E. Punt ◽  
M. S. M. Siddeek ◽  
Brian Garber-Yonts ◽  
Michael Dalton ◽  
Louis Rugolo ◽  
...  

Abstract Punt, A. E., Siddeek, M. S. M., Garber-Yonts, B., Dalton, M., Rugolo, L., Stram, D., Turnock, B. J., and Zheng, J. 2012. Evaluating the impact of buffers to account for scientific uncertainty when setting TACs: application to red king crab in Bristol Bay, Alaska. – ICES Journal of Marine Science, 69: 624–634. Increasingly, scientific uncertainty is being accounted for in fisheries management by implementing an uncertainty buffer, i.e. a difference between the limit catch level given perfect information and the set catch. An approach based on simulation is outlined, which can be used to evaluate the impact of different buffers on short- and long-term catches, discounted revenue, the probability of overfishing (i.e. the catch exceeding the true, but unknown, limit catch), and the stock becoming overfished (i.e. for crab, mature male biomass, MMB, dropping below one-half of the MMB corresponding to maximum sustainable yield). This approach can be applied when only a fraction of the uncertainty related to estimating the limit catch level is quantified through stock assessments. The approach is applied for illustrative purposes to the fishery for red king crab, Paralithodes camtschaticus, in Bristol Bay, AK.


2021 ◽  
Vol 13 (11) ◽  
pp. 6101
Author(s):  
Rishi Sharma ◽  
Henning Winker ◽  
Polina Levontin ◽  
Laurence Kell ◽  
Dan Ovando ◽  
...  

Catch-only models (COMs) have been the focus of ongoing research into data-poor stock assessment methods. Two of the most recent models that are especially promising are (i) CMSY+, the latest refined version of CMSY that has progressed from Catch-MSY, and (ii) SRA+ (Stock Reduction Analysis Plus) a recent developments in field. Comparing COMs and evaluating their relative performance is essential for determining the state of regional and global fisheries that may be lacking necessary data that would be required to run traditional assessment models. In this paper we interrogate how performance of COMs can be improved by incorporating additional sources of information. We evaluate the performance of COMs on a dataset of 48 data-rich ICES (International Council for the Exploration of Seas) stock assessments. As one measure of performance, we consider the ability of the model to correctly classify stock status using FAO’s 3-tier classification that is also used for reporting on sustainable development goals to the UN. Both COMs showed notable bias when run with their inbuilt default heuristics, but as the quality of prior information increased, classification rates for the terminal year improved substantially. We conclude that although further COM refinements show some potential, most promising is the ongoing research into developing biomass or fishing effort priors for COMs in order to be able to reliably track stock status for the majority of the world’s fisheries currently lacking stock assessments.


2021 ◽  
Vol 240 ◽  
pp. 105964
Author(s):  
Cory Lescher ◽  
Noëlle Yochum ◽  
Brad Harris ◽  
Nathan Wolf ◽  
John Gauvin

2021 ◽  
Vol 640 (3) ◽  
pp. 032056
Author(s):  
O V Tabakaeva ◽  
S N Maksimova ◽  
D V Poleschuk ◽  
K K Vereshchagina ◽  
E V Shadrina ◽  
...  

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