Abstract:
Background. Gillnets of mesh sizes (6.9 to 12.7 cm) are used in individual boats in Sri Lankan reservoirs targeting exotic cichlid species, Oreochromis mossambicus (Peters, 1852) and Oreochromis niloticus (Linnaeus, 1758), which dominate the fisheries. The mesh composition of gillnets varies from boat to boat and from season to season making catch samples in individual boats are under the influence of different selectivity patterns. As such, the conventional procedure of correcting length frequency samples using the overall mean selectivity pattern in the fishery is not precise in estimating growth parameters. The presently reported study aimed at assessing cichlid stocks in three tropical reservoirs accounting for gillnet selectivity of individual sampled boats.
Materials and methods. Length frequency data obtained from each boat were corrected for the combined selectivity of the fleet of gillnets of different mesh sizes used in the boat during the sampling occasion. For predicting optimal fishing strategies using a yield-per-recruit approach, probabilities of capture determined from the array of fishing mortality in the length-structured virtual population analysis was incorporated.
Results. Length frequency data corrected for overall gillnet selectivity in sampled boats gave reliable estimates of von Bertalanffy growth parameters. Based on these estimates, mortality parameters were determined and the overall gear selection pattern was deduced from the array of fishing mortality in the length-structured virtual population analysis. Optimal fishing strategies were determined incorporating overall probabilities of capture in the relative yield-per-recruit (Y′ × R–1) analysis.
Conclusion. The overall gillnet selection pattern of a sampled boat offers a methodology for reliable estimation of growth parameters. Although both cichlid species are caught in gillnets simultaneously, Y′ × R–1 analyses predicted increase of exploitation rate for one species while its decrease for the other species perhaps due to influence of other factors such as fish behaviour and fishers’ choice of specific areas for fishing. This analysis provides a methodology of a more precise length-based stock assessment in future research.
