The 2023 stock assessment and management procedure evaluation for pāua (Haliotis iris) fisheries in PAU 5D

Management procedures for the pāua (Haliotis iris) fishery in quota management area (QMA) PAU 5D have been based on harvest control rules determined by catch-per-unit-effort (CPUE) since 2016. Although the previous stock assessment in 2018 suggested a stock status near the interim management target for pāua, the control rule was aimed at improving biomass levels. The present project updated the stock assessment for PAU~5D and tested control rules to achieve fishery aims of slow rebuilding of catch towards the Total Allowable Commercial Catch.

We fitted the stock assessment to length-composition and CPUE data from the period starting in the fishing year. Length-composition data were standardised using a model-based approach based on measured numbers-at-length, which attempted to derive more accurate characterisation of uncertainty for length compositions for PAU 5D, for which sampling has not been representative.

The CPUE was derived in a number of ways to account for potential differences between Pāua Catch Effort Landing Return (PCELR) and Electronic Reporting System (ERS) data. The latter showed shorter fishing duration for PAU 5D than PCELR-reported effort, and a number of sensitivities, including omitting fishing duration and deriving CPUE as catch-per-day, were attempted.

In contrast to the previous stock assessment, CELR data were omitted from the analysis. This change had a considerable effect on estimated biomass levels, which were markedly lower than biomass levels estimated in the 2018 stock assessment. The current assessment suggested stock levels near the soft limit in the early 2000s and around 2015, with reductions in catch since 2015 leading to a rebuild in biomass. The estimated rebuild in the model was determined by increasing recent CPUE. We tested sensitivities to recent CPUE trends by fitting to model to CPUE with and without fishing duration as the effort measure. None of the sensitivities we tested showed a qualitatively different trend from the trend for the base model. The latter suggested that the stock has been rebuilding and is now as likely as not to be at the interim management target.

The harvest control rule that had been in place in PAU 5D since 2016 was updated to include a lag year on increases and a maximum 5% limit on year-on-year increases. The resulting rule was slightly more conservative (i.e., it led to lower average catch) than the rule implemented in 2016. The updated rule maintained steady harvest rates on average, even under the least productive model assumptions, leading to low short- to medium-term risk if the rule was applied to determine catch. In view of potentially changing ocean conditions influencing growth and recruitment in some areas, it is recommended that the assessment and control rule are reviewed in five years’ time to ensure it remains a safe option to manage the fishery.