A statistical model for in-season forecasts of sockeye salmon (Oncorhynchus nerka) returns to the Bristol Bay districts of Alaska

2005 ◽  
Vol 62 (7) ◽  
pp. 1665-1680 ◽  
Author(s):  
Saang-Yoon Hyun ◽  
Ray Hilborn ◽  
James J Anderson ◽  
Billy Ernst
Keyword(s):  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Bayesian Probability ◽  
Bristol Bay ◽  
Age Composition ◽  
Information Sets ◽  
Information Set ◽  
Fishery Data ◽  
Highest Posterior Density ◽  
Return Data

We developed a model for in-season age-specific forecasts of salmon returns using preseason return forecasts, age composition of in-season returns, cumulative in-season returns by fishing district, and age composition and an index of abundance from an in-season test fishery. We apply this method to the sockeye salmon (Oncorhynchus nerka) fishery in the Bristol Bay districts of Alaska. The model generates point estimates and Bayesian probability distributions for return numbers by age and river, and it provides an integrated framework for including all of the major data sources currently used in in-season forecasting. We evaluated model performance using early-season data from 1999–2001 and compared the effects of four information sets on forecast accuracy. The four information sets were as follows: I, district-specific inshore return data; II, inshore return data and test fishery data; III, inshore return data and preseason forecasts; IV, inshore return data, test fishery data, and preseason forecasts. Forecasts from information sets II, III, and IV were less biased than those from information set I. However, in terms of the forecast interval, forecasts from information set II were best because the 95% highest posterior density regions of forecasts from information set II covered the actual returns most frequently.

Test fishery indices for sockeye salmon (Oncorhynchus nerka) as affected by age composition and environmental variables

2004 ◽  
Vol 61 (1) ◽  
pp. 80-92 ◽  
Author(s):  
Lucy Flynn ◽  
Ray Hilborn
Keyword(s):  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Average Error ◽  
Fishing Gear ◽  
Migration Route ◽  
Catch Per Unit Effort ◽  
Age Classes ◽  
Age Composition ◽  
Fishery Data ◽  
Average Body

In this paper, we explore sources of variability in test fishing indices for sockeye salmon (Oncorhynchus nerka) and illustrate potential solutions. For our analysis, we use the Port Moller test fishery in Bristol Bay, Alaska. The traditional model used to forecast run size using Port Moller test fishery data is based on a simple linear regression of total returns to the fishing districts against the cumulative test fishery catch-per-unit-effort (CPUE) index on a given date. We show that much of the inaccuracy of recent forecasts based on test fishery indices is due to the variable age composition of sockeye runs and the unequal vulnerability of respective age classes to the test fishing gear. We also illustrate solutions to the problems presented by variability in migration route and variability in return timing. In warmer years, we found that there was an increase in effective vulnerability to the test fishing gear and that the strength of this relationship increased linearly with the average body length of age classes. Retrospective analysis shows that correcting for age composition, migration route, and timing provides an in-season index of abundance with an average error of 6.7 million fish or 21%, compared with 33% for previous models.

Inseason Forecasting of Bristol Bay, Alaska, Sockeye Salmon (Oncorhynchus nerka) Abundance Using Bayesian Probability Theory

1988 ◽  
Vol 45 (5) ◽  
pp. 850-855 ◽  
Author(s):  
Stephen M. Fried ◽  
Ray Hilborn
Keyword(s):  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Probability Model ◽  
Forecast Accuracy ◽  
Difficult Problem ◽  
Bayesian Probability ◽  
Size Estimation ◽  
Bristol Bay ◽  
New Information ◽  
Formal Framework

A Bayesian probability model was developed for the Bristol Bay, Alaska, sockeye salmon (Oncorhynchus nerka) fishery to examine potential benefits of using a formal framework for incorporating several independent run size estimators into a single "best" estimate of total run size. To simulate performance of the technique, a hindcasting procedure was used for the years 1980–87. The Bayesian composite forecast was always more accurate than the least accurate individual forecast and was sometimes more accurate than the most accurate individual forecast. Since forecast accuracy for each independent method varied greatly both among and within years, the Bayesian method avoided the difficult problem of selecting the most accurate individual forecast and allowed forecasts to be easily revised each day of the season as new information became available. The documentation provided by our method should make it easier to evaluate and improve inseason run size estimation procedures and should allow for smoother transitions when management staff changes occur.

Selective predation by brown bears (Ursus arctos) foraging on spawning sockeye salmon (Oncorhynchus nerka)

2000 ◽  
Vol 78 (6) ◽  
pp. 974-981 ◽  
Author(s):  
Gregory T Ruggerone ◽  
Renn Hanson ◽  
Donald E Rogers
Keyword(s):  
Sockeye Salmon ◽  
Ursus Arctos ◽  
Oncorhynchus Nerka ◽  
The Body ◽  
Upstream Migration ◽  
Selective Predation ◽  
Bristol Bay ◽  
Brown Bears ◽  
Risk Of Predation ◽  
Salmon Population

Selective predation by and predation rates of brown bears (Ursus arctos) foraging on spawning sockeye salmon (Oncorhynchus nerka) in a small shallow creek in the Wood River lake system near Bristol Bay, Alaska, were quantified during 1986 and 1990–1992. Bears killed a high proportion of spawning salmon when few salmon entered the creek (92% of 505 fish) and a much smaller proportion when the spawning population reached a historical high (16% of 15 631 fish). Selective predation on salmon that differed in length, sex, and spawning condition was measured by tagging salmon at the mouth of the creek immediately prior to upstream migration and then recovering dead tagged fish during daily surveys of the entire creek. The relative frequencies of large, medium-sized, and small salmon killed by bears indicated that the risk of predation was more than 150% greater for large than for small salmon. A higher proportion of the male salmon population was killed and a greater proportion of male bodies were consumed than female salmon. Selectivity for male salmon increased as the spawning season progressed, possibly because male salmon weakened earlier and lived longer in a weakened state than female salmon. Male salmon were attacked mostly along the dorsal hump area, whereas female salmon tended to be attacked along the abdomen, where eggs could be exposed. Bears selectively killed female salmon prior to spawning during 1 of the 3 years, but only 6.1–7.8% of the female spawning populations were killed prior to spawning. These data support the hypothesis that selective predation by bears may influence the body morphology of spawning salmon.

A hierarchical model for salmon run reconstruction and application to the Bristol Bay sockeye salmon (Oncorhynchus nerka) fishery

2006 ◽  
Vol 63 (7) ◽  
pp. 1564-1577 ◽  
Author(s):  
Lucy Flynn ◽  
André E Punt ◽  
Ray Hilborn
Keyword(s):  
Hierarchical Structure ◽  
Sockeye Salmon ◽  
Pacific Salmon ◽  
Oncorhynchus Nerka ◽  
Model Development ◽  
Bristol Bay ◽  
Process Error ◽  
The Hierarchical Structure ◽  
River Test ◽  
Run Timing

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.

Erratum: A statistical model for in-season forecasts of sockeye salmon (Oncorhynchus nerka) returns to the Bristol Bay districts of Alaska

2005 ◽  
Vol 62 (10) ◽  
pp. 2423
Author(s):  
Saang-Yoon Hyun ◽  
Ray Hilborn ◽  
James J Anderson ◽  
Billy Ernst
Keyword(s):  
Statistical Model ◽  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Bristol Bay

Patterns of Interannual Variation in Age at Maturity of Sockeye Salmon (Oncorhynchus nerka) in Alaska and British Columbia

1985 ◽  
Vol 42 (10) ◽  
pp. 1595-1607 ◽  
Author(s):  
Randall M. Peterman
Keyword(s):  
British Columbia ◽  
Life Histories ◽  
Sockeye Salmon ◽  
Oncorhynchus Nerka ◽  
Comparative Approach ◽  
Age At Maturity ◽  
Bristol Bay ◽  
Freshwater Environment ◽  
Marine Life ◽  
Alternative Hypotheses

Interannual variations in mean age of maturity tend to be positively correlated among 10 stocks of sockeye salmon (Oncorhynchus nerka) which spawn in rivers emptying into Bristol Bay, Alaska. Taking a comparative approach, I utilized data from British Columbia and Alaska sockeye stocks with different life histories to test alternative hypotheses about sources of these variations in mean age at maturity. The hypotheses included freshwater environment, marine environment, and parental influences. Freshwater hypotheses were rejected and while some parental effects do exist, they are small compared with the effect of events in early marine life. Early marine growth rate data do not exist for these stocks but evidence from five other sockeye stocks shows that fast growth during this period tends to lead to earlier age at maturity.

An Estimate of Ocean Mortality of Bristol Bay Sockeye Salmon Three Years at Sea

1968 ◽  
Vol 25 (6) ◽  
pp. 1219-1227 ◽  
Author(s):  
Stephen B. Mathews
Keyword(s):  
Mortality Rate ◽  
Freshwater Fish ◽  
Sockeye Salmon ◽  
Population Estimation ◽  
Bristol Bay ◽  
Age Composition ◽  
Dichotomous Population ◽  
Sea Fish ◽  
Annual Mortality ◽  
High Seas

The method of population estimation based on change in composition of a dichotomous population was applied to Bristol Bay sockeye salmon to estimate the mortality rate of 3-ocean (3 years at sea) fish during their final year in the ocean. A difference in freshwater age composition between 1-ocean immatures in 1964 and 2-ocean immatures in 1965 was evident in samples taken in the high seas. This difference was apparently due to a greater tendency of 2-freshwater fish than 1-freshwater fish to mature after 2 years at sea. The known quantities of these two freshwater categories in the mature 2-ocean run of 1965 enabled an estimate of the population of 2-ocean immatures at sea in 1965. From this estimate and the quantity of 3-ocean matures in the 1966 run, the annual mortality rate was estimated to be.42.

Cross Correlations Between Reconstructed Ocean Abundances of Bristol Bay and British Columbia Sockeye Salmon (Oncorhynchus nerka)

1984 ◽  
Vol 41 (12) ◽  
pp. 1814-1824 ◽  
Author(s):  
Randall M. Peterman ◽  
Fred Y. C Wong
Keyword(s):  
British Columbia ◽  
Sockeye Salmon ◽  
Population Analysis ◽  
Oncorhynchus Nerka ◽  
Survival Rates ◽  
Gulf Of Alaska ◽  
Time Lags ◽  
Bristol Bay ◽  
Reconstruction Methods ◽  
Cross Correlations

Anecdotal reports of a tendency for British Columbia sockeye salmon (Oncorhynchus nerka) to be low when Bristol Bay, Alaska, returns are high prompted a reconstruction of minimum abundances of sockeye resident in the Gulf of Alaska each year from the early 1950s to mid-1970s. This backwards reconstruction using Fry's virtual population analysis was done by using catch, escapement, and age structure data for each area in British Columbia and Bristol Bay. Use of more sophisticated backwards reconstruction methods was precluded by lack of age-specific annual survival rates by stock. Ocean abundances of British Columbia and Bristol Bay sockeye show significant autocorrelations at periods consistent with the cyclic dominant patterns of their largest stocks. Cross correlations at lag 0 between ocean abundances of various ages of fish from these two regions show one case of a significant inverse relation in abundances. In addition, there are significant cross correlations between British Columbia and Bristol Bay ocean abundances at various time lags, showing that cycles in their abundances are out of synchrony. This lack of synchrony persisted longer than would be expected from cyclic dominance patterns and age at maturity of British Columbia and Bristol Bay sockeye, and several alternative explanations of this asynchrony are discussed.

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