The Cichlid Fishes of Lake Malawi, Africa
 

Abstract of Publication

Weyl, O.L.F., J. Kazembe, A.J. Booth, and D.S. Mandere. 2004. An assessment of a light-attraction fishery in southern Lake Malawi. African Journal of Aquatic Science 29 (1): 111.  

This study provides the first quantitative assessment of the light-attraction component of a small-scale purse seine, locally known as a chilimira net, fishery in two areas of southern Lake Malawi. For monitoring purposes the shoreline of Lake Malawi is divided into a number of statistical strata. Two strata (2.1 in the southeast arm and 3.1 in the southwest arm of the lake) were selected for this study. Catch per unit effort in stratum 2.1 was generally lower than that recorded in stratum 3.1 but nets in stratum 2.1 fished more frequently, leading to similar annual catches in the two strata. Annual catch was estimated as 19.4 (CI = 15.923.5) tons net1 year1 in stratum 2.1 and 23.5 (CI = 19.528.1) tons net1 year1 in stratum 3.1 respectively. A total of 62 species from 28 cichlid genera, and 13 species from nine non-cichlid genera, were identified from the samples. Of the 37 genera identified, only five; Copadichromis, Dimidiochromis, Engraulicypris, Oreochromis and Rhamphochromis, contributed more than 5% to the total annual catch in either stratum. Their combined contribution to the annual catch was in excess of 85% in both strata. Comparisons showed that catch-composition was dependent on area. Length-frequency distributions of major target species in the catch showed that the fishery targeted juveniles in stratum 2.1, while in stratum 3.1 most individuals were harvested after reaching their length-at-maturity. The dependence of catch-composition and size-selection on area indicates that management interventions for this fishery need to be area-specific. Since the fishery targets a diverse species assemblage, effort limitation or area closure may be the only viable management options, until such time as additional biological and fisheries data are available for the application of stock assessment models.
 

 

 

 

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