A Bayesian approach to estimating mortality rates using hazard functions: Application to an Australian halfbeak, Hyporhamphus australis fishery

Abstract

Stock assessments are a key requirement supporting the sustainable harvest of fisheries resources globally. In this study, the population of an important south-eastern Australian halfbeak, Hyporhamphus australis targeted by a lampara-net fishery was assessed via hazard functions within a Bayesian framework (that was also compared to maximum likelihood). Fifteen-years of yield, effort and size-at-age data were used to generate the required population parameters (natural and fishing mortalities, selectivity and catchability) within competing models to derive biomass, recruitment and maximum sustainable yield (MSY). The suitable model included a parameter capturing a legislated change in gear selectivity mid-way through the time series, and with parameter estimates remaining synonymous between Bayesian and maximum likelihood approaches. Notwithstanding likely variable environmental influences, the legislated mesh-size change along with some effort reduction appears to have increased spawning stock biomass (SSB) to ∼112 t larger than that required for MSY (∼78 t per annum), and considerably greater than the current level of exploitation (∼50 t per annum). There was also a close relationship between catch-per-unit-of-effort and SSB, implying that fewer size-at-age data (and associated costs) could be realised without affecting future stock estimates. The results underscore the utility of simple input controls for regulating the exploitation of H. australis, and the chosen analytical approach for quantifying the consequences.