Assessment of bycatch species in the Namibia Hake directed bottom trawl fishery (1997-2014)
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Date
2021
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Publisher
University of Namibia
Abstract
One of the main problems faced by fisheries management, is how to manage and mitigate bycatch caught during commercial fishing. The Namibian hake-directed bottom trawl fishery has been an important component of the Namibian fishing industry for decades. Due to the low selectivity of the bottom trawling method, bycatch has been a common feature of this hake-directed fishery. This study examines the spatial distribution of bycatch; monthly and inter-annual variations in the bycatch catch per unit effort (CPUE) (kg/hr); and factors that influence bycatch catch rate of Namibian hake bottom trawl bycatch species. The specific objectives were: to assess the spatial distribution of the bycatch species in the hake-directed bottom trawl fishery; to assess monthly variations of hake bycatch species/ species groups based on catch rate data that spans over 18 years; to assess inter-annual variations of hake bycatch species’/ species groups, catch rate over a period of 18 years and to identify and assess the relative importance of factors (latitude, month and year ) that best explain the variation in catch rates of hake bottom trawl bycatch species. Data were extracted from the database: Fisheries Information Management System (FIMS) at Namibia’s Ministry of Fisheries and Marine Resources, where all commercial information is captured and stored by scientists. The data extracted and used in the study was from 1997-2014. The study covered the whole fishing grounds within the Namibian Economic Exclusive Zone (EEZ), from the Kunene River to the Orange River. Data analysis methods used in this study included: mapping and density plots; Hierarchical Cluster Analysis (HCA); Multidimensional Scaling (MDS); Similarity Percentage (SIMPER) and Analysis of similarity (ANOSIM) to tackle the following objectives: spatial distribution of bycatch and monthly variations of the Namibian hake bottom trawl bycatch species. These analyses are used to find natural groupings and to give statistical significance in groups. In addition, Generalized Additive Models (GAMs) analyses are used for: monthly and inter-annual variations in the bycatch catch per unit effort (CPUE) (kg/hr); and for the significance of factors that influence bycatch catch rates of Namibian hake bottom trawl bycatch species. These analyses are done by incorporating various factors (latitude, month and year) that may have had an influence on bycatch. In this study twenty-four species are recorded as bycatch in the hake-fishery, with a combined catch amounting to about 9120.90 metric tons for the period 1997-2014. Among all bycatch species, the species that had the highest total catch rate was ribbonfish (Trachipterus trachypterus), while blacktail (Diplodus capensis) was the species with the lowest catch rates in the study period. Most bycatch species were caught along the entire Namibian coast, with some species having higher catch rates in the Northern (17°S - 20°59’59” S), Central (21°S - 24°59’59”) and the majority in Southern regions southern (25°S - 29°59’59”). Blacktail (Diplodus capensis) and silver kob (Argyrosomus inodorous) were only encountered in the Northern parts of Namibia while, yellowfin tuna (Thunnus albacores) was only caught in Northern and Central Namibia. Three major bycatch assemblages/groups were identified along latitudes. The three bycatch groups were mostly distributed at around 29°S (A), 22°S (B) and 17°S (C). Kingklip (Genypterus capensis), west coast sole (Austroglossus microlepsis), species belonging to the family Raja (Skates) and large-eye dentex (Dentex macrophthalmus) were the species that contributed most to the dissimilarity in groups for spatial distribution for A, B and C respectively. Variations in monthly CPUE were observed in all bycatch species. Some species had noticeable variations in the trends increasing /decreasing. CPUE was explained by various factors: latitude; month and year that had an influence on it. This was done for all bycatch species. The common factor that influenced the CPUE of most species was latitude while month and year had the least influence on CPUEs of species. Overall, this study shows that bycatch varies considerably between different species. It also shows that hake fishing has the potential to negatively influence the functioning of the Benguela ecosystem on the basis of the number of species that it has an influence on. Bycatch management measures will, therefore, need to be species-specific in order to tackle specific factors that may have an influence on the different bycatch species. Each species has an influence on the structure and function of food web and the ecosystem at large.
Description
A research thesis submitted in fulfillment of the requirements for the Degree of Master of Science in Fisheries and Aquatic Science
Keywords
Bycatch species, Hake