Title: Artisanal fisheries statistics in Sierra Leone, collection methods, analysis and presentation

Author(s): Sellu Mawundu
Type:
Final project
Year of publication:
2011
Publisher:
UNU-FTP
Place of publication:
Reykjavík
Number of pages:
30
Keywords:
Sierra Leone; artisanal fisheries; co-management; stakeholders; data collection.

Abstract

Fisheries statistics and the management system of the artisanal fisheries of Sierra Leone were critically reviewed. Suggestions are made for new approaches to data collection, data analysis and presentation of results. The current data collection system, though well established in a policy statement is not adequately implemented in the artisanal sector. For the artisanal fisheries, catch assessment data are collected, but little or no biological data are gathered, which prevents the application of most stock assessment models on these data. No socio-economic data are sampled either. Total annual catches of fish in the artisanal sector increased steadily from 2001-2006. Available data on length frequency suggest 2-3 year classes of the most dominant landed species (Ethmalosa fimbriata) in the artisanal catch. The management and development of the artisanal fishery sector in Sierra Leone has been devolved to the local councils under the 2004 local government ACT moving the responsibility of management of the small-scale artisanal fisheries to the local councils. It is here suggested that data collection be consistent and catch assessment data synchronised with local survey data, harbour masters and boat owners should be a part of the data collection, data collection should have well focused objectives with respect to data use, and management policies and objectives should be well defined and intended models for management stated. For the short term, data analysis and policies should not be too complex and be consistent with the data collection potential. Schaefer and Fox production models currently used to analyse industrial fisheries data could be applied to artisanal fisheries data in the near future.

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