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ORIGINAL RESEARCH article
Front. Mar. Sci.
Sec. Marine Fisheries, Aquaculture and Living Resources
Volume 11 - 2024 |
doi: 10.3389/fmars.2024.1458257
This article is part of the Research Topic Challenges in Fishery Assessment Methodologies View all 6 articles
Estimating fish stock biomass using a Bayesian state-space model: accounting for catchability change due to technological progress
Provisionally accepted- 1 Japan Fisheries Research and Education Agency (FRA), Yokohama, Japan
- 2 Pacific Community (SPC), Noumea, New Caledonia
The assessment of trends in fish stocks using long-term time-series data is important for effective fisheries resource management. Despite technological advancements in recent decades, the resulting increase in fisheries catch potential with applied effort is often not adequately considered in stock assessments. To address this gap, we developed a framework for simultaneously estimating catchability and biomass using a state-space population model. This model allows for the flexible integration of the timing and functional form of the uptake of technological innovations that are assumed to influence catchability. Our objective was to test the effectiveness of this framework by applying it to 48 years of skipjack pole-and-line fishery data in Japanese waters. We utilized two population models, the Ricker-type and Gompertz-type, under three different scenarios of technology-driven catchability changes: constant, exponential, and S-shaped. The results indicate that the calculations converged for the constant and S-shaped scenarios, and that both the Ricker and Gompertz models performed almost equally well in terms of the goodness of fit and prediction accuracy under the S-shaped scenario, which assumes time-varying catchability. Although timevarying catchability poses challenges for accurate biomass estimation due to the large range of uncertainty, the decreasing trend in stock status is still detected. The estimated recent decline in the skipjack stock around Japan provides a warning for stock assessments that do not incorporate technological progress, despite the species' high natural population growth rate and presumed stable stock status. Our methodology, based on publicly available archived catch records (catch and effort), can be applied to other species with known timelines of technological innovation.
Keywords: Fish stock management, Hierarchical Bayesian Model, population model, Skipjack, uncertainty, catchability, Technology creep
Received: 02 Jul 2024; Accepted: 09 Dec 2024.
Copyright: © 2024 NISHIMOTO, Yoshinori, Matsubara, Hamer and Tsuda. This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.
* Correspondence:
MAKOTO NISHIMOTO, Japan Fisheries Research and Education Agency (FRA), Yokohama, Japan
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