The Use of Fishing Gears and Role of Beach Management Units in the Nyando Wetland
DOI:
https://doi.org/10.2200/aerj.v2i2.173Keywords:
Wetlands, Fisheries,, Fisheries Management, Fishing CommunityAbstract
There has been a decrease in total fish production especially in Kisumu East, Nyando and Nyakach districts and consequently a decline in socio-economic benefits derived from the lake and the Nyando River wetlands. The department of fisheries introduced BMUs in 2004 in an effort to deal with the problem. The study focuses on the use of fishing gear and role of beach management units in the Nyando wetland in the three districts; Kisumu East, Nyando and Nyakach districts, in the Nyando River Wetlands. The study was conducted in 5 landing beaches four with BMUs and one beach without a BMU. Primary data was collected using Focus group discussions, key informants’ interviews, field observations and a household survey. Secondary data were gathered from government reports and various other sources. Descriptive statistics were used to understand the socio-economic characteristics of fisher folks who utilize the Nyando River Wetlands. Overall family size mean was 6 members and 63% of the respondents were male, while the age of the respondents varied from16 years to 75 years, with a mean of 40 years. The study found that beach leadership is dominated by men who prefer using gill nets and long lines. Reasons given for the preference of gill net and long line include cost, assessment of risk and income received from the fishery. Fishers use illegal gears because of lack of enough resources, their availability and high cost of legal gears. The role BMU played in the last one year (2009-2010) includes enforcement of fisheries rules, improved sanitation, and also resolving disputes. It was also found that 79% of fishers use legal fishing gill nets while 21% do not, thus BMU’s helps in ensuring compliance to fisheries regulations on the use of legal fishing gears. A Cobb-Douglas production function was used to establish the factors that influence fish catch. The results show that household age, household size, household income, level of education, boat ownership, presence of employees, experience of the fisher and presence of BMU are positively correlated with fish catch. Fish catch is also negatively correlated with the sex of the household head, age of boat, method of propulsion, non-income level and the type of household. The study recommends promotion of community participation in management, carry out a socio-economic survey and also provision of credit to improve quality of the fishery.
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