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Revised estimates of abundance of South African sardine and anchovy from acoustic surveys adjusting for echosounder saturation in earlier surveys and attenuation effects for sardine de Moor, C.L.; Butterworth, D.S.; Coetzee, J.C. (2008). Revised estimates of abundance of South African sardine and anchovy from acoustic surveys adjusting for echosounder saturation in earlier surveys and attenuation effects for sardine. Afr. J. Mar. Sci. 30(2): 219-232 In: African Journal of Marine Science. NISC/Taylor & Francis: Grahamstown. ISSN 0257-7615; e-ISSN 1814-2338

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Trefwoorden

Acoustic surveys Anchovy fisheries Attenuation Regressions Sardine fisheries Saturation South Africa Engraulis encrasicolus (Linnaeus, 1758) [WoRMS]; Sardinops sagax (Jenyns, 1842) [WoRMS] South Africa [Marine Regions] Marien/Kust

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Auteurs		Top
de Moor, C.L. Butterworth, D.S. Coetzee, J.C.

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Abstract

Hydro-acoustic surveys have been used to provide annual estimates of May recruitment and November spawner biomass of the South African sardine Sardinops sagax and anchovy Engraulis encrasicolus resources since 1984. These time-series of abundance estimates form the backbone of the assessment of these resources, and consequently the management of the South African sardine and anchovy is critically dependent on them. Upgrades to survey equipment over time have resulted in recent surveys providing more accurate estimates of abundance, yet in order to maintain comparability across the full time-series, estimates of biomass mimicking the old equipment were used for a number of years. In this paper we develop a method to revise the earlier part of the time-series to correct for receiver saturation in the older generation SIMRAD EK400 and EKS-38 echo sounders and to account for attenuation in dense sardine schools. This is applied to provide a revised time-series of biomass estimates for the South African sardine and anchovy resources with associated variance- covariance matrices. Furthermore, the time-series presented here are based on updated acoustic target strength estimates, making this the most reliable time-series currently available for both resources.

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