Author(s)

Elmi Nure Negewo, Zeleke Ewnetu, Yemiru Tesfaye

Hawassa University, Wondo Genet College of Forestry and Natural Resources, Hawassa, Ethiopia.

The study was carried out to determine the economic value of forest conserved by local community for carbon sequestration in the Humbo District, Ethiopia. The contingent valuation method (CVM) using the double bounded bivariate probit econometric method was employed to estimate WTP for sustainable forest management. Household survey was randomly conducted in 218 respondents purposively selected from three forest development cooperatives. The bivariate probit model was run to estimate mean WTP and to identify the determinant factors for farmers’ WTP for forest conservation. Thus, the mean WTP with covariates was estimated to be 104.38 Ethiopian Birr (ETB) and 55.73 ETB¹ per year for the initial bid and for the follow-up bid amount, respectively. The result also indicated that respondents’ level of education, marital status, years of membership in the cooperatives, second bid amount, distance of residence from forest of interest, and net family income were significantly related to WTP for forest conservation. The study showed that even the poor households were willing to pay the average values in terms of cash contribution to maintain the forest management responsibility following the withdrawal of the NGO. In conclusion, whereas CVM can be applied to determine WTP for forest conservation, local people recognize and give value to the environmental services of the forest and are willing to maintain those benefits. The study also indicates the potential for sustainable forest management through community-based approach.

Contingent Valuation Method, Sustainable Forest Management, Carbon Sequestration

Negewo, E. , Ewnetu, Z. and Tesfaye, Y. (2016) Economic Valuation of Forest Conserved by Local Community for Carbon Sequestration: The Case of Humbo Community Assisted Natural Regeneration Afforestation/Reforestation (A/R) Carbon Sequestration Project; SNNPRS, Ethiopia. Low Carbon Economy, 7, 88-105. doi: 10.4236/lce.2016.72009.