运用生物量动态模型评估印度洋长鳍金枪鱼资源

生物量动态模型因所需数据量少、结构较为简单,是常用的渔业资源评估模型。多年来,这类模型一直被用于评估大西洋和印度洋的金枪鱼鱼类资源。然而,这些评估均未考虑模型的重要结构即剩余产量模式和模型拟合标准对资源评估结果的影响。运用典型的非平衡生物量动态模型-ASPIC模型,以渔获量和标准化CPUE为主要数据,评估印度洋长鳍金枪鱼(Thunnus alalunga)资源,重点比较FOX与LOGSITIC两种剩余产量模式、最小残差平方和(SSE)与最小残差绝对值和(LAV)对资源评估的影响。结果显示,剩余产量模式和拟合标准的选用对渔业管理生物学参考点估计(包括MSY、FMSY、BMSY)有明显影响,且总体而言,前者的影响更大;但在资源开发状态的定性判断上(即过度捕捞与否),上述选用未有明显影响。研究表明,在生物量动态产量模型运用中,应根据鱼种和渔业特点,考虑剩余产量模式和模型拟合标准这两个不确定性因素。

Stock assessment of albacore (Thunnus alalunga) in the Indian Ocean using biomass dynamics model

Biomass dynamics models are the commonly used methods in fishery stock assessment, because of simple model structure and light need of data. This type of models has been used in tuna stock assessments in the Atlantic and Indian Oceans. However, the potential impacts of the shape of surplus production model and fitting criteria were not often investigated in these applications. In this study, we assessed the Indian Ocean albacore (Thunnus alalunga) using ASPIC (A Surplus Production Model Incorporating Covariates), a typical biomass dynamics model using catch and abundance index as the main data. We focused on comparing the results of selecting different surplus production models (FOX and LOGISTIC) and model fitting criteria (Least Sum of Squared Errors or SSE and Least Sum of Absolute Errors or LAV). The results showed that the selection of surplus production models and model fitting criteria obviously impacted the estimates of biological reference points (MSY, F_MSY, and B_MSY). Overall, the former influenced more greatly than the latter. However, the results did not show much difference in the determination of stock status in terms of overfishing or overfished. This study highlights the importance of serious consideration of surplus production model shape and fitting criteria in the applications with biomass dynamics models, based on the fishery and biological characteristics of stock.