A Proactive Assessment Framework for Underutilized Species: Evaluating the Bigeye Cigarfish in the Indian Ocean Using a Bootstrap-Coupled Length-Based Bayesian Model

The bigeye cigarfish (Cubiceps pauciradiatus) is a common bycatch species in Indian Ocean fisheries, yet its stock status remains largely unevaluated despite its potential as a future “backup” fishery resource. Here, we develop an integrated assessment framework that couples a Bootstrap based growth estimation tool (fishboot) with the Length based Bayesian biomass (LBB) model. Using length frequency data collected from 2023 to 2025, fishboot quantified uncertainty in asymptotic length (L∞) and growth rate (K), yielding estimates of L∞ = 175 mm and K = 0.92 year−1 that reflect a fast-growing, medium-bodied life history. This L∞ was then supplied as an informed prior to the LBB model. Results indicate that the stock maintained a relatively stable resource status throughout the study period, with its baseline biomass remaining healthy (B/Bmsy > 1) and no alarming early warning signals detected (F/M < 1). The modest biomass fluctuation observed is likely attributable to the species’ status as a common bycatch rather than to systematic overfishing pressure. The fishboot–LBB framework provides a robust approach for proactively assessing data limited and bycatch stocks, thereby extending fisheries research beyond traditional target species to support ecosystem-based management in the region.