The relationships between environmental factors and fish density are closely related, and species distribution models (SDMs) have been widely used in exploring these relationships and predicting the spatial distribution of fishery resources. When exploring the prediction of the spatial distribution of species in different seasons, the method of choosing the appropriate approach to the season will help to improve the predictive performance of the model. Based on data collected from 2015 to 2020 during a survey off southern Zhejiang, the Tweedie-GAM was used to establish the relationship between the density of Decapterus maruadsi and environmental factors at different modeling approaches. The results showed that water temperature, salinity and depth were the main factors influencing D. maruadsi, and they operated through different mechanisms and even resulted in opposite trends of density in different seasons. Spatially, the two modeling approaches also differed in predicting the spatial distribution of D. maruadsi, with the seasonal model showing a higher density trend in inshore waters than in offshore waters in spring but showing the opposite trend in summer and autumn, which was more consistent with the actual spatial distribution of the resource. By analyzing the effects of two different approaches on the prediction of fishery resources, this study aims to provide research ideas and references for improving the predictive performance of SDMs.

Effective fishery management in coastal waters requires accurate assessments of species–environment relationships, particularly in data-rich but zero-inflated contexts (i.e., datasets with an excess of zero catches). Here, we used fishery-independent trawl survey data collected from 2018 to 2019 in the offshore waters of southern Zhejiang Province of China to investigate the spatio-temporal distribution of Setipinna taty (scaly hairfin anchovy) and its environmental determinants. Given the high frequency of zero catches, we fitted both zero-inflated Poisson (ZIP) and zero-inflated negative binomial (ZINB) models and selected the best-performing approach using the Akaike information criterion (AIC). Cross-validation indicated that the ZINB model (RMSE: 199.1, R²; 0.25) outperformed ZIP model (RMSE: 239.4, R²; 0.23). Temperature, depth, and salinity were key predictors of S. taty abundance, which generally occurred at depths of 20–40 m and salinities of 26–34 psu. We then applied the optimal ZINB model to predict S. taty distributions in spring, summer, and autumn of 2020. The predictions indicated a summer peak in abundance and a nearshore-to-offshore decreasing gradient, and were broadly consistent with the spatial distribution trends observed in the 2020 survey data. The highest predicted densities were located in nearshore areas off Wenzhou and Taizhou, west of 122° E. By clarifying the key environmental factors shaping S. taty distribution and applying zero-inflated count models to account for an excess of zero catches, which occur more frequently than expected under standard negative binomial models, this study provides an improved basis for effective conservation and sustainable utilization of S. taty resources in the southern offshore waters of Zhejiang; nevertheless, predictive performance could be further improved by incorporating additional environmental and biotic covariates together with extended spatio-temporal data.

Freshwater lakes worldwide are undergoing rapid degradation, raising concerns about the effectiveness of recent large-scale conservation interventions. China’s ‘10-year fishing ban’ represents one of the world’s most ambitious fishery moratoria, yet its ecosystem-level consequences remain poorly quantified. Using data from the two seasonal surveys conducted in Dongting Lake in 2019, we applied a mass-balanced Ecopath with Ecosim model to evaluate how fishing closure, and its combination with multi-species stock enhancement, affects trophic structure, energy flows, and system stability from 2021 to 2030. Simulations show that the closure-only scenario nearly doubles total ecosystem production, yet yields limited improvement in maturity indicators, reflecting a slow recovery of food web complexity. Across the tested closure-plus-enhancement scenarios, the highest projected system omnivory index occurred under scenario S5 (from 0.24 to 0.27), whereas the highest projected Shannon diversity index (from 0.59 to 0.64) and total transfer efficiency (from 10.80% to 11.12%) occurred under scenario S1, relative to the 2019 baseline. Based on the level-wise responses of the L9 treatments, a recommended combined scenario consisting of 1.04 t bighead carp, 4.30 t grass carp, and 1.14 t silver carp, with no additional black carp stocking, was constructed. Under this scenario, the model projected enhanced biomass recovery and a shorter restructuring period for key functional groups. Our study provides a reference for predicting ecosystem responses following the ‘10-year fishing ban’ and also provides data for ecosystem-based assessments for stock enhancement.