Meereswissenschaften: Forschung und Entwicklung

Abstrakt

Standardization of Fishing Effort in Qatar Fisheries: Methodology and Case Studies

Stamatopoulos C and Abdallah M

Regular statistical monitoring of fishing activities is a prerequisite for effective fisheries management. In the case of artisanal fisheries such a monitoring is often exercised by means of sample-based fisheries surveys in which catch and fishing effort (along with other basic variables) are estimated on the basis of samples relating to landings and boat-gear activity. In most cases the fishing fleet is heterogeneous and hence partitioned into boat-gear categories in each of which fishing units have similar characteristics and performance. Under this scheme catch/effort estimates are computed for each boat-gear category separately and independently of each other. It can then be assumed that in each boat-gear category fishing mortality is proportional to the total fishing effort exerted by all of its fishing units operating together. When it comes to measure the combined effect of the fishing operations of the entire fleet to the exploitation of a fish stock, it becomes apparent that adding together effort exerted by different boat-gear categories is not always meaningful without first applying effort adjustment to increase its comparability. There are various techniques for addressing such situations, the commonest of which is known as “standardization of fishing effort”. In Qatar the National Fisheries Information System (NFIS) has recently incorporated effort standardization routines that combine elements of the normalized relative effort (used by the North Sea Round Fish Working Group, ICES, 1980) with those of relative fishing power developed by Robson (1966). The document presents the methodology in use by NFIS for effort standardization as well as case studies using commercial catch/effort data directly obtained from NFIS. It is envisaged that the selected approach will be further refined in order to increase the role of catch/effort data in research and stock assessment applications.