Before implementing resource management measures, it is essential to establish the goals of fisheries resource management by assessing the current biomass status and the level of fishing effort. This study aims to compare surplus production models, i.e., process-error and state-space models, based on how they fit the observed data. The effects of the Sandfish Stock Rebuilding Plan are analyzed using a bioeconomic model. The analytical results show that the least error is between the estimated and observed catch per unit effort using the state-space model. Therefore, the analysis results obtained using the state-space model are considered as the most reliable. The total allowable catch for Korean sandfish is set at 2196 tons per year. However, if we increase the current management regulation standard for available annual catch by 50%, the sandfish resource could be depleted. Furthermore, NPV decreased to 172,599 thousand won after ten years, in 2029. Therefore, a recommendation of this study is that when management policies for sandfish stock prioritize recovery, this would facilitate fisheries rebuilding.

The standardization of catch per unit effort (CPUE) is essential for accurate stock assessment in fisheries management. This study focuses on CPUE standardization for red snow crab (Chionoecetes japonicus) in South Korea, incorporating both spatiotemporal and socioeconomic factors into a generalized additive model (GAM) framework. Using fishery-dependent data from 2009 to 2023, we analyzed the influence of variables such as the proportion of live catch, oil prices, global export prices, and the COVID-19 pandemic on CPUE trends. To quantify the contribution of each variable, a stepwise exclusion analysis was conducted. The results show that excluding socioeconomic variables leads to a more stable CPUE trajectory, indicating that nominal CPUE fluctuations are partially driven by economic conditions rather than changes in biological abundance. These findings highlight the importance of accounting for external drivers, particularly socioeconomic factors when standardizing CPUE. By doing so, the year effect extracted from the model can more accurately reflect relative stock abundance. The approach presented here offers a practical solution for improving CPUE estimates in data-limited fisheries and supports adaptive, evidence-based fisheries management.

This study aimed to evaluate the stock status of the Japanese flying squid (Todarodes pacificus), a critical fishery resource in the waters of Korea, China, and Japan. To achieve this objective, we employed the Bio-Economic Stock Assessment (BESA) model, which integrates catch and market price data to estimate the biological and economic parameters of Japanese flying squid biomass. The assessment results indicated that the current biomass level of Japanese flying squid is below the biomass at Maximum Sustainable Yield ($B_{\mathrm{MSY}}$), suggesting that the stock is overfished. Moreover, the findings from the BESA model were consistent with results obtained from the Monte Carlo Method (CMSY) and Bayesian State-Space (BSS) models, both of which also indicated a collapsed status. Unlike the CMSY and BSS models, which rely on catch and catch per unit effort (CPUE) data, the BESA model utilizes market price data from National Statistics and the Food and Agriculture Organization (FAO), thereby eliminating the need for CPUE standardization. Consequently, the BESA model presents an alternative framework that complements existing assessment methods and enhances the reliability of fishery stock evaluations through its integrated approach, suggesting its potential applicability to the stock assessment of Japanese flying squid in Korea.