Bioeconomic analysis of chambo (oreochromis spp.) and kambuzi (small haplochromine spp.) fish stocks of Lake Malombe

Abstract: 
A study to establish bioeconomic options for economic exploitation of Chambo (Oreochromis spp.) and Kambuzi (small Haplochromine cichlids) fisheries of Lake Malombe was conducted between 2010 to 2012. Three models, logistic regression, Univariate Autoregressive Integrated Moving Average and Gordon Schaefer bioeconomic models were used to test the research hypotheses. Primary data from resource users were collected using a pretested semi structured questionnaire. Time series data on catch, effort, fish price and costs from 1976 to 2011 were generated from the Traditional Fishery Data Base at Fisheries Research Station in Monkeybay. The logistic regression analysis showed that from thirteen predictor variables, six predictor variables were significant. Autoregressive Integrated Moving Average models for forecasting showed that catches for Chambo will decline to -1,111.80 tons in 2021 from 4,118 tons valued at MK1.318 million in 1976, but Kambuzi catches will increase to 4,224 tons in 2021 from 93 tons valued at MK175 thousand in 1976. Gordon Schaefer dynamic models estimated a maximum economic yield of MK2.148 million as compared to MK1.533 million for maximum sustainable yield for Chambo and MK2.172 million maximum economic yield as compared to MK0.715 million maximum sustainable yield for Kambuzi. The study concludes that there are high economic rents associated with maximum economic yield than maximum sustainable yield. It is recommended that Chambo and Kambuzi fisheries be managed at maximum economic yield, which implies reducing fishing effort. One way of achieving this is to introduce a rights based fisheries regime, which should be based on the intertemporal preferences.
Language: 
English
Date of publication: 
2013
Country: 
Region Focus: 
Southern Africa
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University/affiliation: 
Collection: 
RUFORUM Theses and Dissertations
Licence conditions: 
Open Access
Form: 
Web resource
ISSN: 
E_ISSN: 
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