Kuskokwim River Harvest Prediction Tools

Real-time information is critical to successful management of in-season Pacific salmon (Oncorhynchus spp.)

fisheries. In response to this need in the lower Kuskokwim River subsistence salmon fishery, an in-season

monitoring program was initiated to rapidly report estimated effort and harvest of Chinook (O. tshawytscha),

chum (O. keta), and sockeye (O. nerka) salmon arising from short-duration (generally 12 hours) openers. Aerial

survey and completed trip interview data from 40 drift gillnet openers (mid-June – mid-July, 2016-2023) were

re-analyzed using consistent analytical methods and compiled into centralized and easily accessible data formats.

A validation analysis comparing annual total estimates from the in-season program to a long-term post-season

monitoring program (corrected to apply to the same gear, areas, and time periods) indicated high correlation

(>0.75 for all species, 0.91 for Chinook salmon) and a general lack of directional discrepancies. Predictive

models were then constructed to enable proposing a future opener (e.g., date, time of day, etc.) and current run

conditions (i.e., recent Bethel Test Fishery statistics) and receiving predictions of trips/day, total salmon

catch/trip, and percent species composition. Cross-validation suggested sufficient predictive reliability to be

useful for informing management decisions: strongly systematic directional errors were not identified and leaveone-

out median absolute percent errors implied relatively high precision in response variables (15-30% for

trips/day, catch/trip, and species composition, averaged across all years and periods within years) as well as in

the harvest implied by their product (31%, 52%, and 34% for Chinook, chum, and sockeye salmon,

respectively). Finally, an interactive web application was constructed to increase accessibility to these data sets

and predictive. Application of the predictive models developed in this project may reduce outcome uncertainty

in the in-season aspects of lower Kuskokwim River subsistence salmon fishery management.

The overarching intent of this proposed project is to bring the historical in-season harvest and effort data into greater focus for in-season decision-making, to the extent justified by the data. Rather than viewing the in-season harvest monitoring data as having primary utility for the season in which they are collected, there is a strong possibility that they could additionally be used to develop predictive models to reduce uncertainty when considering alternative fishing strategies for the rest of the season. The primary research question of this proposed project is whether the three key quantities for predicting harvest (effort, catch rate, and species composition) can themselves be reliably predicted from variables readily available in-season. This overarching question is made up of many “sub-questions” and hypotheses. For example, we have reason to believe that the catch rate of the fishery should be related somehow to the in-river abundance of salmon, and the specific hypothesis would be that with more salmon in the river, more salmon will be captured by each individual fisher. The analysis will test this hypothesis (and many like it) for whether it is likely to be true, quantify the relationship, and conduct further calculations to determine whether the strength of the relationship is informative enough to be useful for prediction. If useful relationships can be identified, then it is critical that the data and estimated relationships can be readily accessed, updated, and used by non-technical users; these will be other intents of the project.