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

Abstract

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.

Multivariate Models of Adult Pacific Salmon Returns

“…The multivariate techniques we used resulted in two important products: a pre-season forecast of adult salmon returns, primarily for management of the fisheries, and a measure of indicator importance, which can improve understanding of ocean ecology and guide future marine research. Moreover, the pre-season estimates obtained through these analyses can be used as a starting point for more detailed in-season management adjustments [30], [31].…”

Cloudy with a chance of sardines: forecasting sardine distributions using regional climate models

“…These aspects of ocean currents and temperatures are forecast by the CFS-ROMS system developed here, and the observed ecology of these species can similarly be tested against model predictions. The value of seasonal forecasts for fisheries management has been demonstrated for salmon fisheries in Alaska's Bristol Bay salmon fishery (Hyun et al, 2005). Most promisingly, in Australia a predictive ocean-atmosphere model (Spillman and Alves, 2009) somewhat similar to J-SCOPE has been applied to predict distributions of tuna (Hobday et al, 2011;Eveson et al, 2015).…”

Integrated forecasts of fall Chinook salmon returns to the Pacific northwest

“…The most time-consuming part of the reporting process is reading scales to determine fish age, but even this step could be completed within a few days. Scale samples from a test fishery for Alaska Bristol Bay sockeye salmon are processed and read within three or four days, allowing for in-season forecasts (R. Hilborn, University of Washington Alaska Salmon Program, Seattle, WA, USA, personal communication; Hyun et al, 2005). If this same processing time were achieved in the Southeast Alaska ocean commercial fishery, and then our model could be used for forecasting on a real-time basis during the ocean fishery.…”

“…In this paper, the term of "return" indicates the number of fish that return to natal rivers (i.e., terminal return). Generally preseason forecasts are made about six months before fish arrive at natal rivers, and in-season forecasts are made on a daily or weekly basis once fish enter the natal rivers (Hyun et al, 2005).…”