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Effects of Variation in Local Governance on Community Attitudes, Ecological Outcomes and Ecosystem Services in Mt

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Effects of Variation in Local Governance on Community Attitudes, Ecological Outcomes and Ecosystem Services in Mt Effects of variation in local governance on community attitudes, ecological outcomes and ecosystem services in Mt. Kenya forest Agatha M. Nthenge Thesis submitted for degree of Doctor of Philosophy School of Environmental Sciences, University of East Anglia 30th September 2019 ©This copy of the thesis has been supplied on condition that anyone who consults it is understood to recognise that its copyright rests with the author and that use of any information derived therefrom must be in accordance with current UK Copyright Law. In addition, any quotation or extract must include full attribution. Abstract Many countries in the tropics have decentralised forest management to incorporate local communities in decision making, referred to as community-based forest management (CBFM). A paradigm shift from state control, CBFM has been receiving considerable attention in conservation due to success in restoring degraded forestlands. However, successful forest outcomes are largely inferred from comparisons with other governance regimes e.g. state management. Effective governance is a prerequisite for positive conservation outcomes but little attention has been paid on local governance and in particular variability of local governance between local communities and its effect on forest outcomes. Additionally, CBFM provides insufficient benefits, particularly economic benefits, yet sufficient net benefits are crucial for winning support of local communities. Using a globally relevant CBFM programme, this thesis examines variation in local governance between communities and its effects on ecological outcomes. Factors influencing communities’ attitudes towards forest conservation and ecosystem service preferences important for locals’ livelihoods and well-being are examined. Local governance at grassroot community institutions – community forest associations (CFAs) was assessed qualitatively from CFAs documentation and quantitatively from respondents’ perceptions of CFAs governance using principles of good governance. Forest structure and outcomes were examined in CFAs plots through ground measurement of forest parameters, field observation and in-depth interviews. Local attitudes, livelihoods, ecosystem services and preferences, PFM processes and activities were examined through a combination of mixed methods in social research. Strongly-governed CFAs plots had better forest outcomes; species diversity, carbon biomass and lower forest disturbance than weakly-governed plots. Further local’s attitudes were influenced by strong governance, higher economic benefits and capacity building. CBFM provided multiple ecosystem services with contrasting perceptions to preferred ecosystem services influenced by socio-demographic factors. Co-management programmes must devise mechanisms for strengthening governance and offer sustainable solutions for enhancing flow of benefits (economic and non-economic) to improve conservation effectiveness. 1 Access Condition and Agreement Each deposit in UEA Digital Repository is protected by copyright and other intellectual property rights, and duplication or sale of all or part of any of the Data Collections is not permitted, except that material may be duplicated by you for your research use or for educational purposes in electronic or print form. You must obtain permission from the copyright holder, usually the author, for any other use. Exceptions only apply where a deposit may be explicitly provided under a stated licence, such as a Creative Commons licence or Open Government licence. Electronic or print copies may not be offered, whether for sale or otherwise to anyone, unless explicitly stated under a Creative Commons or Open Government license. Unauthorised reproduction, editing or reformatting for resale purposes is explicitly prohibited (except where approved by the copyright holder themselves) and UEA reserves the right to take immediate ‘take down’ action on behalf of the copyright and/or rights holder if this Access condition of the UEA Digital Repository is breached. Any material in this database has been supplied on the understanding that it is copyright material and that no quotation from the material may be published without proper acknowledgement. Contents Abstract 1 Acknowledgements 3 Chapter 1 Introduction 5 Chapter 2 Impact of local forest governance and benefits on 44 communities’ attitude towards conservation of Mt. Kenya forest Chapter 3 Effect of variation in local forest governance on Mt. Kenya 96 forest structure and carbon storage Chapter 4 Does community-based forest management deliver ecosystem 143 services and livelihoods in Mt Kenya forest? Chapter 5 Key findings and discussion 180 Appendices 206 2 Acknowledgements My greatest thanks and appreciation goes to my supervisors, Paul Dolman and Adrian Martin. Greatest credit for the success and completion of this study goes to them for their immense support, invaluable guidance and positive criticism throughout the study period. Additionally, I am indebted to Paul Dolman who introduced me to quantitative data analysis through which I have learnt invaluable skills on statistical data analysis and interpretation. To Adrian Martin, thank you very much for your support and guidance on qualitative data analysis. Thank you once again for transforming me into who I am and I am very grateful to have had Paul and Adrian as my supervisors and mentors. The local communities living in close proximity to Mt. Kenya forest played a fundamental part of this research. I am grateful to the many residents who participated in the research activities, surveys, focus group discussions, in depth interviews and for those who hosted the research team in their homes. A big thank you also goes to key informants from the national administration, CFA officials and members, Kenya Forest Service (KFS) and Kenya Wildlife staff. I am very much grateful for support accorded by KFS and KWS staff for providing security during data collection in the forest. Many a times we bumped into herds of elephants and the KFS and KWS wardens were always there providing securing and advice. The study also benefited from an able research team that supported data collection during the entire period; Mwenda thank you very much for your invaluable support on tree identification and age of trees stumps. To Dorothy, Steven, Arnold and Martin great appreciation for persevering long walks and covering long distances to respondents’ homes, while also making the best out of some difficult situations by cracking jokes which made work more fun and enjoyable. I appreciate you all. I am also thankful to UEA and institutions in Kenya that granted permission for data collection including Kenya Forest Service, National Commission for Science, Technology and Innovation (NACOSTI), the county governments of Meru, Chuka, Embu, Nyeri and national administration including chiefs and assistant chiefs. A special thanks to the funders of my PhD research, commonwealth scholarship commission (CSC) who funded my study at the University of East Anglia (UEA) and also met costs for my field work. This study would not have been possible without your financial and moral support. I am also indebted to CSC for many opportunities accorded to attend and develop professional skills on different aspects. This will go a long way in shaping my career progression in future. 3 At UEA, I am indebted to my peers who provided immense support and company during my study period. Claire Buchan, thank you very much for introducing me to data analysis; the world of coding in R! The first code you wrote me provided baby steps needed in learning R. By having you in the same office, you supported me through and never tired from answering my data analysis questions, no matter how frivolous they seemed. I still remember the words from my office mates; ‘you need to learn R’, and you became the saviour guiding me through difficult periods in the world of data analysis in R. Thank you very much. To Anderson Saldanha Bueno, thank you very much for your patience, trying to understand my research and offering advice on the best analysis to undertake. John Burnside and Rob Hawks provided invaluable support and advice on simple and complex issues of my study especially on graphs. I am also indebted to Valentina Zini, Marta Acácio, Kate Rogerson and Solomon Udoch for your friendship and moral support. To my housemates, Alia, Hang, Annastacia and Chris, thank you for the morning hellos, delicious dinners and sometimes gossips during our homestay. You all provided support needed to complete my research but most importantly friendship and company, to which I am ever grateful. To the strangles colleagues, thanks also for many opportunities accorded to discuss my research, some which seemed extremely difficult but which you offered invaluable suggestions and advice. Thank you to the Almighty God for blessings, love, strength and guidance to keep going even in difficult. I found solace in the word of God and prayers which kept me going. Lastly, my appreciation goes to my mother, sister, cousins and uncle who have been behind me, at every stage of my study and I am extremely thankful for their support and prayers. Last but not least, thanks to my grandmother for understanding my absence while at the same time having never ending questions as to why I never had leave days to visit as I previously used to. 4 Chapter 1 Introduction Vegetation in Mt. Kenya forest 5 Introduction 1. Introduction 1.1. Forest resources Globally, forests are among the most biologically
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