Phenomenological and mechanistic modeling of recreational angling behavior using creel data

Fisheries Research
By: , and 

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Abstract

Improved understanding of angling behavior in recreational fisheries can help managers account for partial controllability in systems in which angling effort is not directly regulated. Relevant aspects of angling behavior include fishing participation, site choice, and catch-and-release actions and can be considered at scales of both aggregate fishing effort and individual-decision-making. Using creel survey data collected across eight fishery seasons, we predicted aggregate angling effort (e.g., daily number of boating trips engaged in fishing) and characterized influences of individual trip-based site choice for recreational fisheries acting on fall-run Chinook salmon and coho salmon near the mouth of the Columbia River, United States of America. We applied an overdispersed Poisson likelihood-based generalized linear model with an autoregressive structure to aggregate boating effort and a multinomial logit model to trip-based site choice decisions among separate ocean and estuary fishing zones. Predictive models explained 71% and 79% of out-of-sample and in-sample variability in aggregate effort, respectively, and included the covariates weekend status, Chinook salmon catch rate, tidal range, and pre-season expectations of fish abundance. In addition to reinforcing the importance of Chinook salmon catch rate and tidal range, site choice model selection revealed influences of weather, fishery restrictions, expected fishery season lengths, and the individual-specific characteristics of boat length and guide status on decision-making. Model results provide predictive models for short-term fishery planning, highlight heterogeneity in individual decision-making, and illustrate the value of standardized creel data for evaluating angling behavior.

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Publication type Article
Publication Subtype Journal Article
Title Phenomenological and mechanistic modeling of recreational angling behavior using creel data
Series title Fisheries Research
DOI 10.1016/j.fishres.2022.106235
Volume 249
Publication Date January 22, 2022
Year Published 2022
Language English
Publisher Elsevier
Contributing office(s) Coop Res Unit Seattle
Description 106235, 15 p.
Country United States
State Oregon
Other Geospatial Buoy 10 Fishery, Columbia River
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