The effect of stock enhancement on increasing biomass is not well understood and is highly controversial because released fish might have a competitive impact on wild stocks. Quantitative assessments exploring the possible impacts of stock enhancement on population dynamics are rare, especially in data-limited fisheries. We developed a state-space production model incorporating stock enhancement to evaluate the impact of stock enhancement at a population scale. Since observation and process errors impair the accuracy of parameter estimation and biomass prediction, we investigated whether prior biomass reference information could improve analytical performance of the state-space production model. We compared the performance of maximum likelihood (ML) and maximum a posterior (MAP) estimation in a special case of a state-space Pella-Tomlinson model or in a state-space Schaefer model, for three simulated levels of process and observation errors. We found that the MAP parameter estimation with valid prior biomass reference data was generally superior to the ML parameter estimation. As a case study, we applied the extended state-space Pella-Tomlinson model to disentangle the impacts of stock enhancement for the Japanese flounder (Paralichthys olivaceus) in the Seto Inland Sea using long-term fishery data. The results showed a limited contribution of stock enhancement to Japanese flounder in the Seto Inland Sea, suggesting that most released flounder replaced the wild fish niche. Given the number of fish released in 2018, future projections for the next ten years under three different fishing pressures showed that stock enhancement was more effective at augmenting biomass when fishing pressure was higher, but that total biomass decreased simultaneously. Catch increase (decrease) in 30% resulted in a 9% decrease (8% increase) in the biomass and a 28% increase (15% decrease) in the net biomass augmentation from stocking. Therefore, a balance between stock enhancement and exploitation is important to obtain sustainable production and efficient stocking, especially facing global climate change which possibly influences the carrying capacity. Our results suggest that a state-space production model can be used to evaluate the impact of stock enhancement and implement better fishery management.

种群增强对增加生物量的影响尚不清楚，并且存在很大争议，因为释放的鱼可能对野生种群产生竞争影响。探索种群增加对种群动态可能影响的定量评估很少见，尤其是在数据有限的渔业中。我们开发了一个包含库存增强的状态空间生产模型，以评估库存增强在人口规模上的影响。由于观察和过程误差会影响参数估计和生物量预测的准确性，我们研究了先验生物量参考信息是否可以提高状态空间生产模型的分析性能。我们比较了最大似然 (ML) 和最大后验 (MAP) 估计在状态空间 Pella-Tomlinson 模型或状态空间 Schaefer 模型的特殊情况下的性能，用于三个模拟级别的过程和观察误差。我们发现使用有效的先前生物量参考数据的 MAP 参数估计通常优于 ML 参数估计。作为一个案例研究，我们应用扩展的状态空间 Pella-Tomlinson 模型来解开库存增加对日本比目鱼的影响（牙鲆) 在濑户内海使用长期渔业数据。结果表明，种群增加对濑户内海日本比目鱼的贡献有限，这表明大多数被释放的比目鱼取代了野生鱼类生态位。考虑到 2018 年放流的鱼类数量，未来十年在三种不同捕捞压力下的预测表明，当捕捞压力较高时，种群增加在增加生物量方面更有效，但总生物量同时下降。捕获量增加（减少）30% 导致生物量减少 9%（增加 8%），放养后的净生物量增加增加 28%（减少 15%）。因此，库存增加和开发之间的平衡对于实现可持续生产和高效库存非常重要，尤其是面临可能影响承载能力的全球气候变化。我们的结果表明，状态空间生产模型可用于评估种群增加的影响并实施更好的渔业管理。