A multi-model approach for estimating fisheries reference points for the sustainable management of frigate tuna (Auxis thazard) in the northern Arabian Sea

Fishery management is a paramount to ensuring the sustainable utilization of marine resources, particularly in data-limited regions where scientifically grounded assessments are increasingly prioritized. The current study addresses the urgent need to evaluate the biomass status of frigate tuna and establish fisheries reference points (FRPs) for sustainable management. Using the catch-maximum sustainable yield (CMSY) and Bayesian Schaefer model (BSM), complemented by abundance MSY (AMSY), autoregressive integrated moving average (ARIMA), and data envelopment analysis (DEA), the study forecasts trends and assesses fleet efficiency. CMSY estimated an intrinsic growth rate (r) of 0.053 (95% credibility intervals (CI): 0.025–0.112), carrying capacity (k) of 535 000 (248 000–1 156 000) metric tons (MT), and MSY of 7 160 MT. BSM yielded conservative values (r=0.030, k=667 000 MT, MSY=5 150 MT), with both models signaling overfishing (F/F_MSY=1.81) and biomass depletion (B₂₀₂₁/B_msy=0.791). AMSY corroborated these findings, revealing severe overexploitation (F/F_Msy=2.05, B/B_msy=0.491). ARIMA (0, 2, 0) projections indicate stabilized catches (11 180–11 387 MT) by 2026 under current fishing practices, however continued exploitation at these levels could accelerate biomass erosion and risk stock collapse. DEA exposed systemic overcapacity, with fleet effort exceeding sustainable threshold by 25%–40% in 2021 and catch efficiency peaking at 1.69 (2020), indicating persistent over-deployment and suboptimal harvest practices. Overall results underscore the critical overexploitation of frigate tuna stocks, necessitating immediate regulatory measures, including effort reduction, catch quotas, and fleet optimization. This study highlights the imperative of science-driven strategies to balance ecological recovery and economic variability in data-poor fisheries, emphasizing FRPs and adaptive management as cornerstone of sustainable fisheries governance.