The effects of salmon abundance and run timing on the performance of management by emergency order

2015 ◽  
Vol 72 (10) ◽  
pp. 1518-1526 ◽  
Author(s):  
Milo D. Adkison ◽  
Curry J. Cunningham

We examine the effect of uncertainty in salmon run abundance and run timing on the ability of managers to achieve escapement goals using in-season regulation of fishery openings using a detailed model of the arrival of salmon and operation of the fishery, the information available to managers, and managers’ behavior. We supplement this management strategy evaluation by examining historical management performance of sockeye salmon (Oncorhynchus nerka) fisheries from Bristol Bay, Alaska. We find that uncertainty about run timing exacerbates the effects of uncertainty about salmon abundance. Early-arriving small runs and late-arriving large runs are especially problematic, as they produce in-season data that mimic that of a typically sized run with average run timing. Managers faced with an early-arriving small run will tend to overharvest the fish, particularly the earliest-arriving component. Managers faced with a late-arriving large run will tend to underharvest the fish, and harvest the latest-arriving components at a higher rate. This differential harvest of early or late components of the run is important because it might reduce the genetic diversity of the stock, thus reducing its future productivity.

2019 ◽  
Vol 76 (9) ◽  
pp. 1669-1683 ◽  
Author(s):  
Curry J. Cunningham ◽  
Christopher M. Anderson ◽  
Jocelyn Yun-Ling Wang ◽  
Michael Link ◽  
Ray Hilborn

Bristol Bay, Alaska, is home to the largest sockeye salmon (Oncorhynchus nerka) fishery in the world, harvesting an average of 25 million fish with an ex-vessel value exceeding US$100 million annually. Daily fishing effort is adaptively managed to achieve stock-specific escapement goals. Traditional methods for defining these goals relied on stock–recruitment analysis; however, this approach often ignores three fundamental sources of uncertainty: estimation error, implementation uncertainty, and time-varying recruitment dynamics. To compare escapement goal alternatives, we conducted a management strategy evaluation that simulated time-varying recruitment across production regimes and replicated the daily in-season management process. Results indicate (i) implementation uncertainty can be reasonably approximated with simple rules reflecting fishery managers’ daily decision process; (ii) despite implementation uncertainty, escapement goals are likely to be realized or exceeded, on average; and (iii) management strategies targeting escapement levels estimated by traditional methods to produce maximum sustainable yield may result in lower catch and greater variability in fishing opportunity compared with a strategy with defining high and low escapement goals that are targeted depending on assessed run size, which may maximize future catch while reducing the frequency of extremely low harvests.


2006 ◽  
Vol 63 (7) ◽  
pp. 1564-1577 ◽  
Author(s):  
Lucy Flynn ◽  
André E Punt ◽  
Ray Hilborn

The goal of spreading the annual catch of a Pacific salmon (Oncorhynchus spp.) run proportionally across all segments of the migration is rendered difficult or impossible because of the interannual variability in both run size and run timing. This problem is particularly acute in the case of the fishery for sockeye salmon (Oncorhynchus nerka) in Bristol Bay, Alaska, for which traditional run reconstruction models are not applicable because of the extreme temporal compression of the run. We develop a run reconstruction model appropriate for sockeye salmon in Bristol Bay by accounting for the hierarchical structure of the problem and by including process error. Our results indicate that the hierarchical structure is, in fact, not necessary, whereas the process error parameters are needed to fit the data. We suggest further model development without the hierarchical structure, including incorporating in-river test fishing data. The results of our method can be used to address questions regarding environmental or intrinsic drivers of run timing and the possibility of artificial selection on run timing.


2019 ◽  
Vol 76 (1) ◽  
pp. 153-167 ◽  
Author(s):  
Jocelyn Yun-Ling Wang ◽  
Christopher M. Anderson ◽  
Curry J. Cunningham ◽  
Ray Hilborn ◽  
Michael R. Link

We develop an economically sophisticated management strategy evaluation for four sockeye salmon (Onchorhynchus nerka) fishing districts in Bristol Bay, Alaska, to evaluate whether proposed increases in escapement goals — the number of fish allowed up each river to spawn — could improve fishery outcomes for the industry and the region. Higher escapements increase average runs toward biological maximum sustainable yield, but this is driven by infrequent years of very abundant runs. Our economic model shows processors do not add capacity in response to infrequent abundant runs. Therefore, interannual variance in district-specific catch increases because years with little or no fishing become more frequent to meet higher escapement in low-run years, but industry cannot capture greater value in the high-run years. In abundant runs, processors shift available labor to focus on high-volume, lower-margin products; in very abundant years, insufficient processing capacity allows additional fish to escape. Mobile driftnet vessels that can move to rivers experiencing high runs each year benefit, but district specialists in the small boat and set-net fleets are more vulnerable to years with little or no catch.


2021 ◽  
Author(s):  
Margaret C. Siple ◽  
Laura E. Koehn ◽  
Kelli F. Johnson ◽  
André E. Punt ◽  
T. Mariella Canales ◽  
...  

2013 ◽  
Vol 26 (4) ◽  
pp. 365-379 ◽  
Author(s):  
Dorleta Garcia ◽  
Agurtzane Urtizberea ◽  
Guzman Diez ◽  
Juan Gil ◽  
Paul Marchal

2019 ◽  
Vol 76 (9) ◽  
pp. 1653-1668 ◽  
Author(s):  
T.R. Carruthers ◽  
A.R. Hordyk

A new indicator is described that uses multivariate posterior predictive data arising from management strategy evaluation (MSE) to detect operating model misspecification (exceptional circumstances) due to changing system dynamics. The statistical power of the indicator was calculated for five case studies for which fishery stock assessments have estimated changes in recruitment, natural mortality rate, growth, fishing efficiency, and size selectivity. The importance of the component data types that inform the indicator was also calculated. The indicator was tested for multiple types of management procedures (e.g., catch limits by stock assessment, size limits, spatial closures) given varying qualities of data. The statistical power of the indicator could be high even over short time periods and depended on the type of system change and quality of data. Statistical power depended strongly on the type of management approach, suggesting that indicators should be established that rigorously account for feedbacks between proposed management and observed data. MSE processes should use alternative operating models to evaluate protocols for exceptional circumstances to ensure they are of acceptable statistical power.


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