Effects of Deliberative Policy Approach on Management of Common Pool Resource in Mau Forest, Kenya

Abstract

The study sought to fill the existing knowledge gap in the use of deliberative policy approach in the management and conservation of common pool resources with a biased focus on Mau Forest in Kenya. It aimed at exploring effects of deliberative policy approach in the management of common pool resources. The study was based on the view that there has been a growing interest both in deliberative methods and in common-pool resource management. Empirical researches across the world have indicated that co-management of common pool resources and deliberative democracy relate to one another. However, few references have been made on how deliberative democracy has impacted the management of common pool resources. To establish how inclusion of major policy actors affects the management of Mau Forest, to assess how information sharing among major policy actors affects management of Mau Forest and to explore how consultative forums with major policy actors affects management of Mau Forest were main study objectives. Due to the nature of the study, descriptive case study design was adopted in exploring the effects of deliberative policy approach on the management of Mau Forest. The study targeted communities adjacent to Maasai Mau forest in Naisoya village, Lower Melili sub-location of Narok County. Lower Melili sublocation has a total projected population of 6256 with a total number of 1043 based on 2009 census results. A sample of 71 households, 3 CFA officials within Maasai Mau region, 1 Kenya Forest Service officer at Maasai Mau ecosystem conservancy in Narok, Lower Melili location Chief and 2 village elders were selected through purposive and simple random sampling techniques to participate in the study. The study adopted the use of questionnaires, interviews schedules, observation checklist and existing secondary data as the main data collection techniques. Semi-structured questionnaires coupled with structured interview schedules were used to gather primary data from the selected respondents. Collected data was then analyzed through computation of both descriptive and inferential statistics.