Knowl. Manag. Aquat. Ecosyst.
Number 423, 2022
Ecosystem services and economics
|Number of page(s)||9|
|Published online||23 August 2022|
Estimating willingness to pay for the conservation of wetland ecosystems, Lake Victoria as a case study
Peoples' Friendship University of Russia (RUDN University), 6 Miklukho-Maklaya St, Moscow 117198, Russian Federation
2 Department of Physics and Mathematics, Technical University of Mombasa, Mombasa, Kenya
* Corresponding author: firstname.lastname@example.org
Accepted: 20 July 2022
Wetlands are critical habitats for human health, well-being, ecological integrity, and national development. Freshwater ecosystems supply a variety of products and services, yet they are frequently underappreciated. Long-term economic viability necessitates an understanding of the role that finite natural resources play in economic activity and production, as well as the connection people have with, and the value they place on, those natural resources. The purpose of this study was to determine peoples' Willingness to Pay (WTP) for the maintenance of the Lake Victoria Ecosystem. The research was conducted in the Kenyan counties of Migori, Siaya, Busia, Kisumu, and Homa Bay. Using the Statistical Package for Social Sciences (SPSS), the gathered data were coded, cleaned, and analyzed. According to the findings, 40.9% of locals were prepared to spend roughly KES 500 for the conservation initiative. From the study, Lake Victoria ecosystem in Kenya had a total WTP of KES 616,279,069 each year. According to the findings, those who benefitted directly from the lake's resources were more inclined to pay for the program. This empirical research is a helpful input for identifying market segments among inhabitants, which may aid in generating more cash for biodiversity conservation in the Lake Victoria Basin.
Key words: Willingness to pay / wetland ecosystem / contingent valuation method / resources valuation / Lake Victoria / Africa
© M. Mamboleo and A. Adem, Published by EDP Sciences 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License CC-BY-ND (https://creativecommons.org/licenses/by-nd/4.0/), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. If you remix, transform, or build upon the material, you may not distribute the modified material.
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