The deep demersal snapper-grouper fishery in Indonesia is a data-poor fisheries resource that provides food security and a source of income to millions globally. Owing to an ongoing crew-operated data recording system implemented in Indonesia since 2015, the stocks of this fishery can now be assessed using length-frequency data and updated life-history parameters. Here, we use two length-based methods, one that is fishery-specific and another that is more generalized, to assess the status of Indonesian stocks. Specifically, we develop a literature-based assessment method based on a patchwork of conventional approaches but tailored to the studied stocks, and compare it with a newly established and broadly applicable length-based Bayesian biomass estimation method (LBB). The methods were applied to 16 stocks from 4 Indonesian Fisheries Management Areas and were compared based on simulations, as well as the convergence of the resulting stock status classification and uncertainty of the results. Analyzing the effect of using the literature-based species/family-specific life-history parameter values for asymptotic length (L_inf) and relative natural mortality (M/K) in LBB showed that different values do affect the estimated biomass indicator. Nevertheless, in more than half the cases, the stock status classification did not differ between the two methods, while LBB results became more reliable with narrower confidence limits. Simulations, as well as similar status indicators between the two models support the value of the literature-based approach as an assessment methodology for the Indonesian deep demersal fisheries. Narrower confidence ranges highlight the importance of using fishery-specific information when applying generalized stock assessment methods. While most catches had few immature fish, half of the assessed stocks were consistently shown to have low biomass, indicating that important Indonesian stocks are at high risk of overfishing.

印度尼西亚的深底鲷鱼-石斑鱼渔业是一种数据匮乏的渔业资源，为全球数百万人提供粮食安全和收入来源。由于自 2015 年以来在印度尼西亚实施了持续的船员操作数据记录系统，现在可以使用长度频率数据和更新的生活史参数评估该渔业的种群。在这里，我们使用两种基于长度的方法来评估印度尼西亚种群的状况，一种是针对渔业的方法，另一种是更普遍的方法。具体来说，我们开发了一种基于文献的评估方法，该方法基于传统方法的拼凑，但适合研究的种群，并将其与新建立的、广泛适用的基于长度的贝叶斯生物量估计方法 (LBB) 进行比较。这些方法应用于来自 4 个印度尼西亚渔业管理区的 16 个种群，并基于模拟进行比较，以及由此产生的种群状况分类的收敛性和结果的不确定性。分析使用基于文献的物种/家族特定生活史参数值对渐近长度 (L) 的影响_信息) 和 LBB 中的相对自然死亡率 (M/K) 表明不同的值确实会影响估计的生物量指标。尽管如此，在超过一半的情况下，两种方法之间的种群状态分类没有差异，而 LBB 结果变得更可靠，置信限更窄。模拟以及两个模型之间的类似状态指标支持基于文献的方法作为印度尼西亚深层渔业评估方法的价值。更窄的置信范围强调了在应用广义种群评估方法时使用特定渔业信息的重要性。虽然大多数渔获物几乎没有未成熟的鱼，但一半的评估种群始终显示生物量低，这表明重要的印度尼西亚种群面临过度捕捞的高风险。