The effects of ageing biases on stock assessment and management advice: a case study on Namibian horse mackerel
| dc.contributor.author | Wilhelm, M R | |
| dc.contributor.author | Durholtz, M D | |
| dc.contributor.author | Kirchner, C H | |
| dc.date.accessioned | 2018-01-19T09:27:23Z | |
| dc.date.available | 2018-01-19T09:27:23Z | |
| dc.date.issued | 2008 | |
| dc.date.updated | 2016-01-22T10:04:55Z | |
| dc.description.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 otolith-reading 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. | |
| dc.identifier | http://dx.doi.org/10.2989/AJMS.2008.30.2.6.556 | |
| dc.identifier.apacitation | Wilhelm, M. R., Durholtz, M. D., & Kirchner, C. H. (2008). The effects of ageing biases on stock assessment and management advice: a case study on Namibian horse mackerel. <i>African Journal of Marine Science</i>, http://hdl.handle.net/11427/26843 | en_ZA |
| dc.identifier.chicagocitation | Wilhelm, M R, M D Durholtz, and C H Kirchner "The effects of ageing biases on stock assessment and management advice: a case study on Namibian horse mackerel." <i>African Journal of Marine Science</i> (2008) http://hdl.handle.net/11427/26843 | en_ZA |
| dc.identifier.citation | Wilhelm, M. R., Durholtz, M. D., & Kirchner, C. H. (2008). The effects of ageing biases on stock assessment and management advice: a case study on Namibian horse mackerel. African Journal of Marine Science, 30(2), 255-261. | |
| dc.identifier.ris | TY - Journal Article AU - Wilhelm, M R AU - Durholtz, M D AU - Kirchner, C H AB - 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 otolith-reading 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. DA - 2008 DB - OpenUCT DP - University of Cape Town J1 - African Journal of Marine Science LK - https://open.uct.ac.za PB - University of Cape Town PY - 2008 T1 - The effects of ageing biases on stock assessment and management advice: a case study on Namibian horse mackerel TI - The effects of ageing biases on stock assessment and management advice: a case study on Namibian horse mackerel UR - http://hdl.handle.net/11427/26843 ER - | en_ZA |
| dc.identifier.uri | http://hdl.handle.net/11427/26843 | |
| dc.identifier.vancouvercitation | Wilhelm MR, Durholtz MD, Kirchner CH. The effects of ageing biases on stock assessment and management advice: a case study on Namibian horse mackerel. African Journal of Marine Science. 2008; http://hdl.handle.net/11427/26843. | en_ZA |
| dc.language.iso | eng | |
| dc.publisher.department | Department of Biological Sciences | en_ZA |
| dc.publisher.faculty | Faculty of Science | en_ZA |
| dc.publisher.institution | University of Cape Town | |
| dc.source | African Journal of Marine Science | |
| dc.source.uri | http://www.tandfonline.com/loi/tams20 | |
| dc.subject.other | age-structured production model | |
| dc.subject.other | ageing error | |
| dc.subject.other | sampling effort | |
| dc.subject.other | Trachurus capensis | |
| dc.subject.other | ageing precision | |
| dc.title | The effects of ageing biases on stock assessment and management advice: a case study on Namibian horse mackerel | |
| dc.type | Journal Article | |
| uct.type.filetype | Text | |
| uct.type.filetype | Image |