Ecosystem Service Valuation along Landscape Transformation in Central Ethiopia

Abera Assefa Biratu, Bobe Bedadi, Solomon Gebreyohannis Gebrehiwot, Assefa M. Melesse, Tilahun Hordofa Nebi, Wuletawu Abera, Lulseged Tamene and Anthony Egeru
Additional contact information
Abera Assefa Biratu: Africa Centre of Excellence for Climate Smart Agriculture and Biodiversity Conservation, Haramaya University, Dire Dawa P.O. Box 138, Ethiopia
Bobe Bedadi: Africa Centre of Excellence for Climate Smart Agriculture and Biodiversity Conservation, Haramaya University, Dire Dawa P.O. Box 138, Ethiopia
Solomon Gebreyohannis Gebrehiwot: Ethiopian Institute of Water Resource, Water and Land Resource Center, Addis Ababa University, Addis Ababa P.O. Box 3880, Ethiopia
Assefa M. Melesse: Department of Earth and Environment, Institute of Environment, Florida International University, Miami, FL 33199, USA
Tilahun Hordofa Nebi: Melkassa Agricultural Research Center, Ethiopian Institute of Agricultural Research, Adama P.O. Box 436, Ethiopia
Wuletawu Abera: International Center for Tropical Agriculture (CIAT), Addis Ababa P.O. Box 5689, Ethiopia
Lulseged Tamene: International Center for Tropical Agriculture (CIAT), Addis Ababa P.O. Box 5689, Ethiopia
Anthony Egeru: Department of Environmental Management, Makerere University, Kampala P.O. Box 7062, Uganda

Land, 2022, vol. 11, issue 4, 1-18

Abstract: Land degradation and discontinuation of ecosystem services (ES) are a common phenomenon that causes socio-economic and environmental problems in Ethiopia. However, a dearth of information is known about how ES are changing from the past to the future with regard to land use land cover (LULC) changes. This study aimed at estimating the values of ES based on the past and future LULC changes in central Ethiopia. Maximum likelihood classifier and cellular automata-artificial neuron network (CA-ANN) models that integrate the module for land use change evaluation (MOLUSE) were used to classify and predict LULC. The CA-ANN model learning and validation was employed to predict LULC of 2031 and 2051. Following LULC change detection and prediction, the total ES values were estimated using the benefit transfer method. Results revealed that forests, wetlands, grazing lands, shrub-bush-woodlands, and water bodies were reduced by 9755 ha (37%), 4092 ha (38.4%), 21,263 ha (81%), 63,161 ha (25.7%), and 905 ha (1%), respectively, between 1986 and 2021. Similarly, forests, wetlands, grazing lands, shrub-bush lands, and water bodies will experience a decline of 1.5%, 0.5%, 2.6%, 19.6%, and 0.1%, respectively. Meanwhile, cultivated lands, bare-lands, and built-up areas will experience an increase between 1986 and 2051. The estimated total ES values were reduced by US$58.3 and 85.4 million in the period 1986–2021 and 1986–2051. Food production and biological control value increased while 15 other ES decreased throughout the study periods. Proper land use policy with strategic actions, including enforcement laws for natural ecosystems protection, afforestation, ecosystems restoration, and conservation practices, are recommended to be undertaken to enhance multiple ES provision.

Keywords: landscape transitions; ecosystem services; ecosystem service valuation; CA-ANN; MOLUSE (search for similar items in EconPapers)
JEL-codes: Q15 Q2 Q24 Q28 Q5 R14 R52 (search for similar items in EconPapers)
Date: 2022
References: View references in EconPapers View complete reference list from CitEc
Citations: View citations in EconPapers (5)

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