Title: Stock assessment of the offshore Mauritian banks using dynamic biomass models and analysis of length frequency of the Sky emperor (Lethrinus mahsena)

Type:
Final project
Year of publication:
2005
Publisher:
UNU-FTP
Place of publication:
Reykjavík
Number of pages:
61
Supervisors: Jon Solmundsson
Keywords:
MSY; fMSY; dynamic biomass models; bootstrap; hind-casting trials; Saya de Malha; Nazareth; Lethrinus mahsena; TAC; banks fishery; Mauritius.

Abstract

The main objective of this study was to determine MSY reference points for the Saya de Malha and the Nazareth banks north of Mauritius. As no catch at age data is available to perform analytical age structured stock assessment, catch and effort data from 1989 to 2004 were analysed. Surplus production/dynamic biomass models were used to determine stock status through estimation of MSY, fMSY, absolute biomass, relative biomass and relative fishing mortality. Bootstrapping for bias correction on estimates, setting of confidence limits and projection with set catch levels were conducted. Lower limits (95%) of the MSY using the Logistic model were estimated at 2,531 and 1,623 t, and the fMSY was estimated at 40,390 and 32,280 fishermandays for the Saya de Malha and Nazareth banks, respectively. Hind casting trials suggest that the model was relatively stable when more than 12 years were included in the analysis. Results should be interpreted carefully given the assumptions of the dynamic biomass models and potential limitations of the input data. Length frequency data of Lethrinus mahsena from Saya de Malha bank were also analysed to estimate growth parameters and mortality rates. As expected, L. mahsena was found to be a slow growing and long-lived species. The main recommendations from this study are that TAC should be reintroduced for the banks fishery and fishery-independent stock indices should be used in future analysis. The basis for the application of age structured models should be laid immediately, not as a substitute but as a complement to dynamic biomass models.

Documents and links