An assessment of inland fisheries in South Africa using fisheries-dependent and fisheries-independent data sources
- Authors: McCafferty, James Ross
- Date: 2012
- Subjects: Fisheries -- South Africa , Fishery management -- South Africa , Fisheries -- Economic aspects -- South Africa , Food security -- South Africa , Poverty -- South Africa , Economic development -- South Africa , Fishing -- South Africa , Fisheries -- Catch effort -- South Africa , Fish stock assessment -- South Africa , Fish populations -- South Africa , Linear models (Statistics)
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5229 , http://hdl.handle.net/10962/d1005072 , Fisheries -- South Africa , Fishery management -- South Africa , Fisheries -- Economic aspects -- South Africa , Food security -- South Africa , Poverty -- South Africa , Economic development -- South Africa , Fishing -- South Africa , Fisheries -- Catch effort -- South Africa , Fish stock assessment -- South Africa , Fish populations -- South Africa , Linear models (Statistics)
- Description: The role of inland fisheries as contributors to local and national economies in developing African countries is well documented. In South Africa, there is increasing interest in inland fisheries as vehicles for achieving national policy objectives including food security, livelihoods provision, poverty alleviation and economic development but there is surprisingly little literature on the history, current status, and potential of inland fishery resources. This lack of knowledge constrains the development of management strategies for ensuring the biological sustainability of these resources and the economic and social sustainability of the people that are dependent on them. In order to contribute to the knowledge base of inland fisheries in South Africa this thesis: (1) presents an exhaustive review of the available literature on inland fisheries in South Africa; (2) describes the organisation of recreational anglers (the primary users of the resource); (3) compiles recreational angling catch records and scientific gill net survey data, and assesses the applicability of these data for providing estimates of fish abundance (catch-per-unit effort [CPUE]); and finally, (4) determines the potential for models of fish abundance using morphometric, edaphic, and climatic factors. The literature review highlighted the data-poor nature of South African inland fisheries. In particular information on harvest rates was lacking. A lack of knowledge regarding different inland fishery sectors, governance systems, and potential user conflicts was also found. Recreational anglers were identified as the dominant user group and catch data from this sector were identified as potential sources of fish abundance and harvest information. Formal freshwater recreational angling in South Africa is a highly organised, multi-faceted activity which is based primarily on angling for non-native species, particularly common carp Cyprinus carpio and largemouth bass Micropterus salmoides. Bank anglers constituted the largest number of formal participants (5 309 anglers affiliated to formal angling organisations) followed by bass anglers (1 184 anglers affiliated to formal angling organisations). The highly structured nature of organised recreational angling and dominant utilisation of inland fisheries resources by this sector illustrated not only the vested interest of anglers in the management and development of inland fisheries but also the role that anglers may play in future decision-making and monitoring through the dissemination of catch data from organised angling events. Generalised linear models (GLMs) and generalised additive models (GAMs) were used to standardise CPUE estimates from bass- and bank angling catch records, which provided the most suitable data, and to determine environmental variables which most influenced capture probabilities and CPUE. Capture probabilities and CPUE for bass were influenced primarily by altitude and conductivity and multiple regression analysis revealed that predictive models incorporating altitude, conductivity, surface area and capacity explained significant (p<0.05) amounts of variability in CPUE (53%), probability of capture (49%) and probability of limit bag (74%). Bank angling CPUE was influenced by conductivity, surface area and rainfall although an insignificant (p>0.05) amount of variability (63%) was explained by a predictive model incorporating these variables as investigations were constrained by small sample sizes and aggregated catch information. Scientific survey data provided multi-species information and highlighted the high proportion of non-native fish species in Eastern Cape impoundments. Gillnet catches were influenced primarily by species composition and were less subject to fluctuations induced by environmental factors. Overall standardised gillnet CPUE was influenced by surface area, conductivity and age of impoundment. Although the model fit was not significant at the p<0.05 level, 23% of the variability in the data was explained by a predictive model incorporating these variables. The presence of species which could be effectively targeted by gillnets was hypothesised to represent the most important factor influencing catch rates. Investigation of factors influencing CPUE in impoundments dominated by Clarias gariepinus and native cyprinids indicated that warmer, younger impoundments and smaller, colder impoundments produced higher catches of C. gariepinus and native cyprinids respectively. A predictive model for C. gariepinus abundance explained a significant amount of variability (77%) in CPUE although the small sample size of impoundments suggests that predictions from this model may not be robust. CPUE of native cyprinids was influenced primarily by the presence of Labeo umbratus and constrained by small sample size of impoundments and the model did not adequately explain the variability in the data (r² = 0.31, p>0.05). These results indicate that angling catch- and scientific survey data can be useful in providing predictions of fish abundance that are biologically realistic. However, more data over a greater spatial scale would allow for more robust predictions of catch rates. This could be achieved through increased monitoring of existing resource users, the creation of a centralised database for catch records from angling competitions, and increased scientific surveys of South African impoundments conducted by a dedicated governmental function.
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- Date Issued: 2012
Contribution towards the development of a management plan for the baitboat and sport fishery for tuna in South Africa
- Authors: Newcombe, Hylton Cecil
- Date: 2012
- Subjects: Tuna -- South Africa , Tuna fishing -- South Africa , Fishery management -- South Africa , Fishery management -- Economic aspects -- South Africa , Tuna fisheries -- Catch effort -- South Africa , Tuna fisheries -- Economic aspects -- South Africa
- Language: English
- Type: Thesis , Masters , MSc
- Identifier: vital:5249 , http://hdl.handle.net/10962/d1005092 , Tuna -- South Africa , Tuna fishing -- South Africa , Fishery management -- South Africa , Fishery management -- Economic aspects -- South Africa , Tuna fisheries -- Catch effort -- South Africa , Tuna fisheries -- Economic aspects -- South Africa
- Description: Tuna are of significant global economic importance and a prime food source. Increased levels of fishing have resulted in many stocks being under threat and a number of species are considered to be overfished. The South African tuna industry has had limited management attention from the South African fisheries management agency. A recent development has been an increase in the number of tuna caught by small vessels that target the fresh tuna market in South Africa and overseas. This has highlighted the importance of developing a holistic management plan for the sector and creating an awareness, among vessel owners, of the importance of compliance with initiatives such as the Marine Stewardship Council (MSC). The South African tuna fishery comprises three sectors: baitboat, sport and longline, all of which are currently in need of acquiring more biological and fisheries data. This project was initiated to collate existing information and to collect additional information where possible. This encompassed a qualitative and quantitative assessment of the size and shape of the tuna fishing industry, which included estimates of total catch, effort, catch-per-unit-of-effort (CPUE) and stock structure (obtained through comparative estimates of age and growth), as well as socio-economic and economic information. A technique involving an examination of specific vertebrae was used to obtain age-growth information for T. albacares. These data were used to estimate von Bertalanffy (VBGF) growth parameters: F 2 1. , k 0.1 , and t₀ -0. 1 year. No significant differences in growth parameters were found in yellowfin tuna (Thunnus albacares) from different localities around the South African coast, i.e. from the south eastern Atlantic and the south western Indian Ocean. In addition, growth did not differ between South Africa and other regions (Draganic and Pelzcarski 1984, Fonteneau 1980, Gascuel et al. 1992, LeGuen and Sakagawa 1973, Lehodey and Leroy 1999, Lessa and Duarte-Neto 2004, Shuford et al. 2007, Stequert et al. 1996, Wild 1986, Yang et al. 1969). Further substantiation of the above-mentioned observations was found by recording differences in the sizes of fish caught in the inshore (baitboat and sport fishery vessels) and offshore (large pelagic longline vessels) sectors of South African tuna fisheries. A significant difference between the regions — in terms of the size of fish caught inshore — was noted, with mostly-juvenile fish being caught in KwaZulu-Natal (5.4 ± 3.5kg), sub-adult fish in the Eastern Cape (26.2 ± 13.4kg), and adult fish in the Western Cape (42.3 ± 14.4kg). Since mostly-adult fish were caught offshore by longliners, with no significant differences between regions, it is however possible th at adult fish predominantly inhabit the offshore region. Yellowfin tuna caught by the large pelagic longline fishery in the three managerial zones (A, B and C) were predominantly adult fish of similar size, namely Zone A: 38.9 ± 6.9kg; Zone B: 28.7 ± 4.6kg, and Zone C: 36.0 ± 5.1kg. The recreational ski boat sport fishery has remained stable, in terms of participation, consisting mostly of white middle aged males in the top 25% of household income distribution, having either permanent occupational status or being retired. Fishers within this sector are willing to incur great expense to partake in the fishery and they provide an important economic contribution to coastal towns, particularly in the Eastern Cape. The total catch (of 83t) of yellowfin tuna by the competitive sport fishery within the Western and Eastern Cape regions was considerably lower than that of commercial tuna baitboat catches, which amounted to 186t, and the large pelagic longline sector that caught t in 200. It is however likely that the competitive sport fishery's total yellowfin tuna catch (of 83t in 2009) of the Eastern and Western Cape competitive sport fishery was considerably less than the total yellowfin tuna catches of the whole South African deep-sea sport fishery. Longfin tuna are the primary target species of South Africa‘s baitboat fisheries, comprising an average of 86% of the total catch and generating ZAR49 million in employment income in 2002. South Africa was responsible for 20% of the total longfin tuna annual yield in 2004 in the southern Atlantic Ocean, behind Taiwan with 59%. However, yellowfin tuna only contributes a small percentage towards total catches (8.4 ± 8.2% between 1995 and 2009), generating ZAR1.3 million in employment income in 2002. Of the four vessel categories comprising the tuna baitboat fishery, ski boats had the highest yellowfin tuna CPUE in 2009 (117 ± 62 kg.vessel⁻¹.day⁻¹) and the lowest effort. The ski boats sector is the most opportunistic fishery as they are only active when either longfin or yellowfin tuna are in high abundance. At such times catches are guaranteed, so can be expected to offset expenses. In 2009 the CPUE for yellowfin tuna for 15–19m vessels and freezer deckboats was 12 ± 20kg.vessel⁻¹.day⁻¹ and 3 ± 6kg.vessel⁻¹.day⁻¹, respectively. These vessels specifically target longfin tuna when they are in abundance. Since the start of the tuna baitboat fishery in 1995, there has been a substantial increase in the number of new entrants. In 2002 this sector had a fleet size of 82 vessels with a capital value of ZAR163 million and a total employment income of ZAR58 million, employing 2 173 fishers, of which 87% were black African. The commercial tuna baitboat fleet has subsequently grown to 200 vessels and 3600 crew, with 110 active vessels fishing for a combined fleet average of 46 days per year. There are a high number of owner-operated vessels. Since 2007 the fishery's profit to cost ratio has been low due to the low abundance of tuna stocks off the coast of South Africa, which has resulted in poor catch returns, placing economic pressure on the fishery. The baitboat industry is a low-profit-margin fishery with a total net catch value worth ZAR90 million in 2009 (Feike 2010). The abundance of yellowfin tuna influences profit margins, with very high profits being made when abundance and catches are high. The large pelagic longline fishery has a total allowable effort of 43 vessels of which only 30 vessels fished during 2009, when a reported 766t of yellowfin tuna were caught, representing a total tonnage far in excess of that obtained by the combined effort of the baitboat and sport fishery. It is, however, assumed that considerable underreporting of catches takes place within this fishery, which means that the estimated total net catch value of ZAR100 million could, in fact, be much higher. Such underreporting of catches is of great concern for this fishery, as is the high bycatch of Chondricthians spp. that significantly outweighs imposed regulatory limits (DEAT 2007). The present study demonstrates the current lack of comprehensive catch and effort data for the sport, baitboat and longline fisheries as well as the serious limitations and flaws associated with current databases. Results from the present study have drawn attention to a number of high-priority research needs, as outlined below. (1) A major lack of comprehensive catch and effort data for the sport fishery, which can be rectified by focussing on obtaining more competition data, as well as high-quality catch and effort and socio-economic information, as opposed to relying on information from non-club anglers (Gartside et al. 1999, Williams 2003, Cass-Calay 2008). Acquisition of such data is relatively inexpensive: the location of organized clubs and their frequent competition meetings provide widespread coverage along the Southern African coastline. Such data acquisition efforts have the potential to provide reliable information on spatial catch trends. (2) Validation of vessel catch return data is required for commercial fisheries and on some recent data that has emerged from studies of catch rates and trends for target species, particularly in the longline fishery. In this context it should be noted that the most recent peer-reviewed publications on this exploratory fishery were published more than a decade ago (Kroese 1999, Penny and Griffiths 1999). Additional studies need to be undertaken and journal articles published on the current stock status of South African catches of yellowfin and bigeye tuna and swordfish.
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- Date Issued: 2012