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Bio-economic modeling of fishing activities in Kenya: the case of Lake Naivasha Ramsar site

  • B. N. ObegiEmail author
  • I. Sarfo
  • G. N. Morara
  • P. Boera
  • E. Waithaka
  • A. Mutie
Article

Abstract

Lake Naivasha fishery has been one of the most known sources of protein for most fringe communities in and around Naivasha. About 4000 livelihoods depend on the lake’s fishery resource, both directly and indirectly, thus pose concerns on the future sustainability. The ultimate aim of this study was to explore efforts, costs and optimum levels of fishery exploitation in Lake Naivasha. The study relied on fish landings and fishing effort statistics recorded between 1980 and 2017 by Fisheries Department. Data was analyzed using Gordon Schaefer’s model and excel operating software. A regression model was run to develop graphs that explained the relationship between total costs, total revenues, harvests and number of boats. Consequently to the main aim, the study sought to determine the total costs of fishing along with revenues generated. Findings show an increase in number of operational boats from twenty-six (26) in 1980 to fifty boats (50) in 2013. Thereafter, fishing boats increased significantly to one hundred and seventy-six (176) by 2017. Such a significant and unprecedented increase in efforts adversely affected natural fish stock and brooders of the major fish species in the fishery. Information in this paper will inform decisions on resource economics and management of fishing activities in Lake Naivasha, Kenya.

Keywords

Bio-economic modeling Maximum sustainable yield Maximum economic yield Total cost (TC) Effort (E) Harvest (H) Catch per unit effort (CPUE) Poverty Lake Naivasha 

Notes

Acknowledgements

We are highly indebted to the Fisheries Department and Staff of Kenya’s Marine and Fisheries Research Institute who provided relevant data and information used in this paper.

Compliance with ethical standards

Conflict of interest

Authors declare no conflict of interest or whatsoever.

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Copyright information

© Springer Science+Business Media, LLC, part of Springer Nature 2020

Authors and Affiliations

  1. 1.Kenya Marine and Fisheries Research InstituteNaivashaKenya
  2. 2.Research Institute for History of Science and TechnologyNanjing University of Information Science and TechnologyNanjingChina
  3. 3.School of Agriculture and Natural Resource ManagementKisii UniversityKisiiKenya

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