Economics of ecosystem services and resource utilisation in selected water catchment ecosystems in Kenya

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dc.contributor.author Eregae, Justus Ekuwom
dc.date.accessioned 2023-11-17T13:18:13Z
dc.date.available 2023-11-17T13:18:13Z
dc.date.issued 2023-11-17
dc.identifier.citation EregaeJE2023 en_US
dc.identifier.uri http://localhost/xmlui/handle/123456789/6194
dc.description Doctor of Philosophy in Environmental Management en_US
dc.description.abstract Water catchment ecosystems (WCE) are critical in the provision of goods and services that are essential to societal well-being worldwide. This study assessed the stock and flow of ES drawn from the selected water catchment ecosystem (Elgeyo and Nyambene), aimed at making visible their monetary values to enhance awareness creation and advocate for improved WCE conservation. The socio-cultural aspect of the study targeted a population of 400,000 (Elgeyo), and 700,000 (Nyambene) together with state and non-state actors in the two WCE. Household survey employed stratified and simplified random sampling approach, where it sampled 373 and 402 HH for Elgeyo WCE and Nyambene WCE, respectively. Ecological aspect employed geographical information systems (GIS) and remote sensing, supported by field assessments, laboratory analysis, and literature reviews. Forest biomass mapping employed a stratified-systematic cluster approach with nested concentric design, with 48plots (Elgeyo) and 32plots (Nyambene) sampled. Historical river flow data for three sub-basins (Moiben, Ura and Thangatha) sourced from the Water Resources Authority (WRA) database were used for hydrological dynamic modelling. The economic aspect employed conventional valuation techniques, such as market pricing, stated preferences, and benefit transfers (unit and function) to assign monetary value. Data was collected using a mobile application which was transferred to Microsoft Excel, the Statistical Package for Social Sciences (SPSS) version 24 and STATA for processing and analysis. Descriptive statistics were used to summarise the socio-cultural attributes, forest product extraction, and other quantitative data. The data was subjected to a normality test to check for normal distribution. Both parametric and non-parametric were employed for significant difference and similarity testing. Logistical regression was used to determine the forest's community dependency. Generalised linear model (GLM) was considered in land-based biomass assessment, while VAR was utilised in river flow dynamics assessment models. The study estimates the total ES value at KES 58.8 billion (USD 549.7 million) and KES 39.4 billion (USD 368.4 million) for the Elgeyo and Nyambene WCE, respectively. This translates to KES 542,793.97 (USD 5,072.84) and KES 1,3 million (USD 12,152.99) ha-1 year-1. Overall, disaggregating the total value on a per capita income, it corresponds between KES 42,416.67 (USD 396.42) and 53,230.77 (USD 497.48) equivalent to 19.4% and 24.4% of Kenya's per capita income. The study estimates indirect use values at KES 90,042.89 (USD 841.52) and KES 48,803.48 (USD 456.11) HH-1 year-1, respectively. This translates to between 33% and 35% of the forest community's household income thus high forest dependency. Notably, forest dependency is largely influenced by household socioeconomic and cultural attributes. For instance, low-income communities, larger households, and large-scale herders heavily depend on forest resources. These findings imply that the WCE contribute over 30% to rural household income and between 10% and 25% to national gross domestic production (GDP). Equally, the study shows that land cover change impacts on stock and flow of ES as exhibited in assessment of forest biomass and river flow dynamics. For instance, the decrease in forest cover per year results in decline in base flow by between 1mm3/sec and 10mm3/sec while increasing peak flows to between 16mm3/sec and 70mm3/sec. Likewise a unit change in forest species diversity, forest cover, and stem volume attributed land cover change would reduce unit forest biomass by a factor of 1.1, 2.2, and 1.2 on average, respectively. This demonstrate that, a conversion of forest to other land uses, would impact negatively on stock and flow of ecosystem goods and services. Also, the study found out that tree cover change can be a good predictor for river flows changes in sub-basin with minimal anthropogenic pressure. However, it may not be a good predictor basin with facing anthropogenic pressure since its impact becomes insignificant in influencing hydrological flow dynamics. Overall, the outcome of the study, though not absolute, has shown potential monetary values of ES drawn from forested catchment ecosystems in the country. This is thus critical in complementing other conservation efforts that would guide decision-making, since every decision-making process involves trade-offs. Therefore, ES monetary units would be fundamental if a society endeavours to pursue, argue, and justify the need for sustainable water catchment ecosystem conservation in Kenya and beyond. Further research can consider expanding the scope of ES to include economic value on seed dispersal, pest and diseases control among others. To reduce pressure on state forest and enhance stock flow of ES, conservation actors can advocate for farm forestry and enforcement of 10% woodlot establishment policy. Similarly, governments can consider incorporating the economic values of ES into future national accounting and planning processes. en_US
dc.description.sponsorship Dr. Paul Mwangi Njogu, PhD JKUAT, Kenya Dr. Rebecca Karanja, PhD KU, Kenya Dr. Moses Kirega Gichua, PhD JKUAT, Kenya en_US
dc.language.iso en en_US
dc.publisher JKUAT-IEET en_US
dc.subject Economics of ecosystem en_US
dc.subject Resource utilisation en_US
dc.subject Ecosystems en_US
dc.subject Water catchment ecosystms en_US
dc.title Economics of ecosystem services and resource utilisation in selected water catchment ecosystems in Kenya en_US
dc.type Thesis en_US


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