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Estimating Farmers’ Stated Willingness to Accept Pay for Ecosystem Services Case of Lake Naivasha wetershade payment for Ecosysytem Services Scheme- Kenya

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dc.contributor.author Nyongesa, J. M.
dc.contributor.author . Bett, H. K
dc.contributor.author Lagat, J. K.
dc.contributor.author Ayuya, O. I.
dc.date.issued 2016-05
dc.date.accessioned 2021-07-13T11:23:42Z
dc.date.available 2021-07-13T11:23:42Z
dc.identifier.uri http://41.89.96.81:8080/xmlui/handle/123456789/2672
dc.description.abstract Introduction: Lake Naivasha watershed is recognized for its contribution to Kenya’s national gross domestic product from the export of horticultural products. Commercial horticultural investment downstream depends mainly on the Lake’s water. The fresh water lake lacks surface outflow, and its recharge depends on river Malewa flowing from upper catchment in Aberdare ranges. However, unsustainable land use practices in the upper catchment has led to increasing sediment loading and pollution in river Malewa which affects water quality in the Lake downstream. Payment for Environmental Services (PES) scheme has been initiated as an alternative incentive approach to motivate upstream smallholder farmers adopt sustainable land use practices for conservation of watershed services. This paper analyzes willingness to accept pay (WTA) as proxy economic measure of environmental service (ES) value and determines socio-economic factors influencing farmers WTA for watershed conservation. We analyzed the WTA and characterized WTA underlying socio-economic determinants in two PES intervention sites in Kenya. Methods: The objective of this study was to estimate WTA and determine socio-economic factors influencing WTA. Semi-structured questionnaire was used to collect data from 200 PES farmers through face-to-face interview. We applied contingent valuation (CV) and logistic regression for data analyses to elicit farmer’s WTA estimates to implement PES farm practices and determine socio-economic factors influencing WTA, respectively. Results: Results revealed over 90 % of respondents were farmers and 60 % had primary level of education. Average household farm size was 2.305 acres and family size was six members on average. We recorded a monthly marginal household increase in gross income from Kshs. 6891.96 9 (US$68.92) before PES to Kshs. 11,011.48 (US$110.12) with PES interventions. The estimated annual lowest and highest WTA for PES farm practices were at Kshs. 8835 (US$88.35) for grass strip and Kshs. 21,847.500 (US$218.48) for fallowing. Household socio-economic characteristics had significant influence on WTA among farmers. Conclusions: The study revealed heterogeneity in WTA estimates among PES implementing farmers. The WTA reflects opportunity cost to farmers. We recommend PES mechanism as a policy tool to internalize negative watershed externalities to provide ecosystem services. Keywords: Conservation, Ecosystem services, Livelihoods, Payment for Ecosystem Services, Practice, Watershed, Willingness to accept pay en_US
dc.language.iso en en_US
dc.publisher Egerton University en_US
dc.subject Accept pay for ecosystem services en_US
dc.title Estimating Farmers’ Stated Willingness to Accept Pay for Ecosystem Services Case of Lake Naivasha wetershade payment for Ecosysytem Services Scheme- Kenya en_US
dc.type Article en_US


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