This paper presents an updated stock assessment for the Patagonian toothfish (Dissostichus eleginoides) fishery of the Kerguelen Island EEZ, CCAMLR Division 58.5.1. It includes commercial fishery data up to the end of the season 2021/2022. The updated assessment model is based on the best available data and includes abundance estimates from random stratified trawl surveys (POKER, 2006, 2010, 2013 and 2017), longline tag-release and tag-recapture data from 2007 to 2022 and priors and estimates on model parameters such as life traits (e.g. growth, maturity and natural mortality). It also uses commercial data that account for fish removals (fishing mortality and depredation) and support the estimation of year class strength (YCS) and selectivity functions.
Compared to the previous assessment that was presented to WG-FSA 23 (Massiot-Granier et al., 2023c), this assessment accounts for (1) updated catch and biological data (2022/2023), (2) updated age data from an ongoing 4-year otolith reading program, (3) updated priors on YCS and period of estimation (4) and updated depredation rate and (5) updated tag recapture data. All model runs were conducted using Casal2.
The updated model leads to a lower estimate of the virgin spawning stock biomass SSB0 than in 2023 with an estimate of 188 460 tonnes (95% CI:175 690 – 203 010). The estimate of the current SSB status of the stock is 56,4% (95% CI: 54,2% - 60,2%) and the current catch limit (CL) of 4610 tonnes complies with the CCAMLR decision rules, under the assumption that the entire historical recruitment time series is representative of future recruitment
Alternative scenarios were presented this year as well, presenting catch limit with the assumption that recent recruitments are more likely to be representative of future recruitment.
Additionally, alternative harvest control rules (HCRs) on exploitation rates, developed during WG-SAM 2024, were tested.
This paper also introduces a method to account for spatial changes in fishing effort when estimating abundance using the Chapman estimator. Preliminary results indicate a minimal impact from this bias.