The effects of ageing biases on stock assessment and management advice: a case study on Namibian horse mackerel

  • MR Wilhelm National Marine Information and Research Centre, Ministry of Fisheries and Marine Resources, PO Box 912, Swakopmund, Namibia; Current address: Marine Biology Research Centre, Department of Zoology, University of Cape Town, Rondebosch 7701, South Africa
  • MD Durholtz Marine and Coastal Management, Department of Environmental Affairs and Tourism, Private Bag X2, Rogge Bay 8012, South Africa
  • CH Kirchner National Marine Information and Research Centre, Ministry of Fisheries and Marine Resources, PO Box 912, Swakopmund, Namibia

Abstract

We explore the influence of age-estimation errors on the results of the age-structured production model (ASPM) used for horse mackerel stock assessment in Namibia for the period 1961–2003. The analysis considered age data from eight readers collected during an otolithreading workshop. Four scenarios of age-estimation errors were assumed: Case 1 — a reference age computed as the modal age of estimates obtained by the four most experienced readers; Case 2 — age readings from a precise and experienced (Namibian) reader of horse mackerel otoliths; Case 3 — age estimates from a reader that displayed positive bias compared with the reference ages; and Case 4 — age estimates from a reader that displayed negative bias compared with the reference ages. The age–length key of each case was applied to length distributions of survey, pelagic fleet and midwater fleet landings (1991–2003) to obtain catch-at-age data. These data were then used in the ASPM. Results obtained from Case 3 differed most significantly from the others and appeared to be unrealistic in terms of the state of the stock and negative log-likelihood estimates. The conclusion is that more resources need to be directed towards age determination, because management recommendations are highly sensitive to errors in ageing. Most effort should be placed into age estimation of age groups 3–5 (20–30 cm total length), but significant effort needs to be devoted to age estimation of midwater commercial samples. Finally, the extent of sampling and the raising strategy of length frequencies should be improved.

Keywords: age-structured production model; ageing error; ageing precision; sampling effort; Trachurus capensis

African Journal of Marine Science 2008, 30(2): 255–261
Published
2008-10-20
Section
Articles

Journal Identifiers


eISSN: 1814-2338
print ISSN: 1814-232X