2  Stock Assessment

The first age-structured stock assessment for South Atlantic Albacore was completed in June 2026, using the Stock Synthesis 3 (SS3) framework (Methot and Wetzel 2013). The assessment output was used as the basis for the Reference (Chapter 3) and Robustness (Chapter 4) operating models.

This chapter provides a brief overview of the assessment. For full details, see the Report of the 2026 ICCAT Albacore Stock Assessment Meeting and the Report of the 2026 ICCAT Albacore Data Preparatory Meeting.

The assessment model integrated total catches, standardized indices of abundance, and length-composition data covering the period 1956 – 2024.

2.1 Fleet Structure and Fishery Data

Five fishing fleets were defined by aggregating catch and length composition data for fishing fleets with similar properties (Table 2.1; Figure 2.1; Figure 2.2).

Five standardized CPUE indices were used in the Base Case assessment (Table 2.2; Figure 2.1; Figure 2.3).

The catch and CPUE data are imported into the Reference (Chapter 3) and Robustness (Chapter 4) operating models, and made available to the candidate management procedures (Chapter 7).

Table 2.1: Fleet structure, data and time periods to be used in the South Atlantic albacore Stock Synthesis model. Adapted from Table 11 in the Data Preparatory Report.

Fleet	Definition (FlagName and Gear Group)	Catch	Size composition data
Fleet 1	Chinese Taipei (LL), Korea (LL)	1964-2024	up to 2024
Fleet 2	Japan (LL), China (LL), EU-Spain (LL), EU-Portugal (LL), USA (LL), Philippines (LL), St Vincent and Grenadines (LL), Vanuatu (LL), Honduras (LL), NEI (LL), Côte D’Ivoire (LL), United Kingdom (LL), Seychelles (LL), UK.Sta Helena (LL), Angola (LL), Senegal (LL), Trinidad and Tobago (LL)	1956-2024	1956-2024
Fleet 3	Brazil (LL, SU), Uruguay (LL), Namibia (LL), Panama (LL), South Africa (LL, UN), Argentina (LL, TW, UN), Belize (LL), Cambodia (LL), Cuba (LL, UN)	1959-2024	1969-2024
Fleet 4	South Africa (BB, HL, PS, RR, SP)	1973-2024	1980-2024
Fleet 5	All others	1961-2024	1961-2024

Table 2.2: CPUE indices and time periods to be used in the South Atlantic albacore Stock Synthesis model. Adapted from Table 11 in the Data Preparatory Report.

Index Name	Definition	Years
Indx_CTP-LL_TB1	Chinese Taipei longline, time block 1	1970-1980
Indx_CTP-LL_TB2	Chinese Taipei longline, time block 2	1981-2024
Indx_JPN-LL_TB2	Japan longline	1979-2017
Indx_BR_URY-LL	Brazil/Uruguay longline	1978-2024
Indx_ZAF-BB	South Africa baitboat	2003-2024

Figure 2.1: Overview of the data used in the 2026 stock assessment.

Figure 2.2: Time series plot of the total catch data used in the 2026 assessment.

Figure 2.3: Time series plot of the five CPUE indices used in the Base Case 2026 assessment.

2.2 Biological Parameters

The assessment model assumed age-specific natural mortality modelled with the Lorezen function (Lorenzen et al. 2022), mean length-at-age described by the von Bertalanffy growth model, and the stock-recruitment relationship modelled with the Beverton-Holt equation, parameterized with the ‘steepness’ (h) formulation.

Recruitment variability \(\left(\sigma_R\right)\) was fixed at 0.4 and h at 0.75. Maturity was specified as an at-age schedule with fish reaching 50% maturity at age 5 years and full maturity at 6 years.

See Table 5 in the Data Preparatory Report for a full list of the life-history parameters used in the model.

Uncertainty in the biological parameters was focused on alternative mean length-at-age and naturality mortality-at-age schedules. A set of nine models were developed combining three alternative growth parameterizations and three alternative natural mortality estimates corresponding to the 25th, 50th, and 75th percentiles of the distributions agreed at the Data Preparatory Meeting.

These nine models are used to create the Reference OM Grid (Chapter 3). The central model of this grid (model 5, referred to as S05) was used considered the Base Case assessment model and is used in the MSE as the Reference OM.

Lorenzen, Kai, Edward V. Camp, and Taryn M. Garlock. 2022. “Natural Mortality and Body Size in Fish Populations.” Fisheries Research 252 (August): 106327. https://doi.org/10.1016/j.fishres.2022.106327.

Methot, Richard D., and Chantell R. Wetzel. 2013. “Stock Synthesis: A Biological and Statistical Framework for Fish Stock Assessment and Fishery Management.” Fisheries Research 142 (May): 86–99. https://doi.org/10.1016/j.fishres.2012.10.012.