The 2020 stock assessment of pāua (Haliotis iris) for PAU 5A

The present study conducted a Bayesian length-based stock assessment for pāua (Haliotis iris) in pāua quota management area PAU 5A. The assessment model used the same population dynamics model as previous assessments, but the data models that linked the population dynamics (process) model with different data types were significantly updated using changes that were first introduced for PAU 5D in 2018: unlike previous assessments for this area, the present model used only model-derived inputs and did not fit directly to data. It, therefore, represents a Bayesian synthesis of available information rather than an integrated model that fits to data directly. This development is most significant for the growth process as represented in the model, which previously relied on fitting directly to available data from particular quota management areas. In this model, growth information was given in the form of a rather vague prior, and the model used this information with other inputs to estimate stock-level growth. In addition, recruitment variation was not estimated prior to robust commercial shell length frequency data being available in 2001, to avoid the introduction of artefacts by large estimated early recruitment events which appear inconsistent with more recent data.

The assessment was run as a single and multi-area assessment over smaller research strata; however, as all multi-area runs led to near-identical conclusions as the single-area model, the latter was selected to provide a base case and key sensitivity for the assessment. The base case suggested healthy stock levels near 50% of unfished biomass, with slow declines over recent decades. The key sensitivity differed from the base case in that it allowed for increasing efficiency in the fishery. This assumption led to estimates of slow increase in efficiency early in the fishery (pre 2000), but a more substantial increase since 2001, with estimates of stock status at near 40% of unfished biomass, but with more positive recent trends. Projections for both models suggested little change from current stock status over the next three years and into the future at current catch levels, corresponding with previous assessments and management procedure evaluations.