Seasonal Spatio-Temporal Model Improves Refined Stock Assessment and Management of Japanese Sardine (Sardinops melanostictus) in the Northwest Pacific Ocean

Accurate estimation of fish stock abundance and exploitability is critical for effective fishery management; however, fishery-dependent data are often affected by temporal and spatial heterogeneities due to the seasonal migration of fish, posing challenges for refined stock management. Previous studies have largely ignored these spatio-temporal dynamics, assuming static populations. This study develops a seasonal spatio-temporal model for Japanese sardine (<i>Sardinops melanostictus</i>) in the Northwest Pacific Ocean (NPO), using fishery-dependent data from 2014 to 2022. Seasonal standardized abundance indices (spring, summer, autumn, and an overall average) were generated and integrated with the abundance maximum sustainable yield (AMSY) method for stock assessment. The performance of the AMSY method using a spatio-temporal index was compared with the conventional model-based index, showing the superiority of the spatio-temporal approach. Results indicate a gradual increase in sardine abundance, with a significant shift in the center of gravity toward the northeast. The stock is in a sustainable state with a 94.8-99% probability of recovery. Although the stock is recovering, careful management is advised to prevent future declines. This framework offers a novel approach for assessing distant water and coastal fishery resources.