Abstract
Understanding temporal variation in population productivity is critical for effective assessment and management of pelagic fish stocks under a changing climate. In this study, we applied a stochastic surplus production model in continuous time (SPiCT) with time-varying parameters to evaluate the productivity dynamics of yellowfin tuna (Thunnus albacares) in the western and central Pacific Ocean and to examine the influence of environmental variability on productivity. Multiple time-varying parameterization scenarios were explored to characterize uncertainties in productivity estimates and associated biological reference points. Generalized additive models were subsequently used to quantify the relationships between environmental variables and time-varying productivity. Results indicate that productivity estimates exhibit consistent temporal patterns across alternative modeling scenarios, while their magnitude and associated uncertainty are sensitive to model structure. Among the environmental factors examined, the Pacific Decadal Oscillation (PDO) and mixed layer thickness (MLT) showed consistent and statistically significant associations with maximum net productivity. Higher PDO values and greater MLT were both positively associated with population productivity. Overall, the results highlight the importance of environmental variability in shaping time-varying productivity of yellowfin tuna and demonstrate the feasibility of incorporating key environmental indicators into a state-space model. This approach provides a complementary framework for interpreting stock dynamics and supports the development of ecosystem-based fisheries management strategies in the western and central Pacific.