1. Mutune, J.M’1, Wahome, R1 and Lund, J.F2
ANALYSING FOREST ACCESS AND LIVELIHOODS IN MAU FOREST COMPLEX: WITH DECENTARLISED FOREST MANAGEMENT IN KENYA
Mutune, J.M’1, Wahome, R1 and Lund, J.F2
1University of Nairobi, 2University of Copenhagen
Introduction:
More than 15 million people in Sub-Saharan Africa earn their income from forest-related enterprises such as firewood and charcoal sales, small-scale saw-milling, commercial hunting, and handicraft production (Kaimowitz, 2003). To enhance these forest values, the Government of Kenya (GOK) ratified a new Forests Act. The FA 2005 advocates for decentralised forest management a departure from prior practice where the government assumed full management responsibility of gazetted forest reserves (World Bank, 2005) and alienated other stakeholders (Thenya et al, 2008). there is an expectation that PFM can bring substantial benefits in terms of livelihood security and poverty reduction possibly by increasing bargaining power and producer prices (Kajembe et al ,2003; Lund and Treue, 2008; Matiku et al, 2012).The community forest associations (CFAs) formed by user groups gives the members user rights. But user rights do not directly translate to benefits derived. The benefits associated to more than 10 CFAs in Mau forest Complex are tree seedlings nurseries, Prunus africana bark herbal products, bee keeping and ecotourism(Koech et al, 2009; Nakuru District Development Plan, 2009). However empirical information, particularly in Kenya, is lacking to support the expectations of the PFM. Who gains and who losses and under what processes are they able to do so remains precisely known. Rigorous impact evaluation methods such as propensity score matching will used to associate livelihood outcomes to the policy intervention (Caliendo, 2008; Ferraro, 2009; Rosenbaum and Rubin 1983)
Expected output
Through household surveys, the study is expected to reveal positive or/and negative impacts of PFM on livelihood and give in depth understanding of the means employed by households to derive benefits from the forest resources. Therefore, the study will provide recommendations on areas of intervention in relation to livelihoods in stabilising forest related conflicts. The study will document findings by writing a thesis and publish least three papers.
To interrogate mechanisms that households employ to benefit from forest resources
Hypotheses
Households in possession of assets such as skills, tools, money derive more forest related benefits than their counterparts.
Relational mechanisms among households such as gender, group membership, kinship, power profoundly affect households’ access to forest resources.
Households in subsistence use of the forest are more adversely affected by rules and regulations of forest use than commercial users.
The CFA has pushed the households into other livelihoods and technologies hence need not access the common forest resources
Conceptual Framework
Context
FA 2005
Social relations
CFA (governance structure, composition)
Livelihood components
Forest related
Non-forest related
Categories
Poor, rich, commercial, subsistence, CFA & non-CFA members, educated & not educated, indigenous, immigrants
Relational mechanisms
Social identity- gender, ethnicity, class, kinship
Structural mechanisms
Access to- authority, markets &assets (knowledge, technology, land-size, finances etc)
Livelihood outcomes
Access, income, PFM related-IGAs, technologies & livelihoods)
KFS
Licences/fee & Revenues accrued
CBOs/User- groups
Research Questions
What are the influences of social relations such as ethnicity, kinship, gender and class on households’ livelihood activities?
How d1o institutions such as laws, rules, norms and markets influence household decisions on livelihood activities?
How has households’ forest access hence income changed with PFM?
How do forest derived income compare with total income among households?
How does the governance structure of forest related institutions such as CFAs affect access to forest resources?
Has PFM pushed households into other technologies and livelihood activities?
What are the livelihood potentials among households?
Objectives
The overall objective is to analyse households’ livelihood outcomes and forest access mechanisms under participatory forest management so as to identify areas of intervention in regard to livelihoods for stabilising forest related conflicts in the rural of Mau Forest Complex Kenya.
Specific Objectives
To analyse the impacts of CFAs on households’ access to and income from forest resources
Hypotheses:
Among CFA members, poor households have experienced comparatively more adverse impacts with regard to their forest access and income relative to rich households.
Non-member households have experienced comparatively less positive impacts with regard to their forest access and income relative to member households.
The membership of CFAs and consequent household level impacts on forest access and income differ along lines of ethnicity. `
References:
Caliendo, M and Kopeinig, S (2008) Some Practical Guidance for the Implementation of Propensity Score Matching. Journal of Economic Surveys Vol. 22, No. 1, pp. 31–72. Blackwell Publishing Ltd
Ferraro, P. J. (2009). Counterfactual Thinking and Impact Evaluation in Environmental Policy. In M. Birnbaum & P. Mickwitz (Eds.), Environmental Program and Policy Evaluation. New Directions for Evaluation, 122, 75–84.
Ferraro, P. J, Pattanayak SK (2006) Money for Nothing? A Call for Empirical Evaluation of Biodiversity Conservation Investments. PLoS Biol 4(4): e105. doi: /journal.pbio
Kajembe, G. C., Mbwambo, L. Katani, J. Z and Dugilo, N, M (2002). Impacts of Decentralisation of Forest Management: Evidences from Tanzania. Arusha, Tanzania
Koech, C.K., Ongugo P.O., Mbuvi, M.T.E. and Maua, J.O. (2009). Community Forest Associations in Kenya: Challenges and Opportunities. Kenya Forestry Research Institute
Matiku, P., Mireri, C and Ogol, C (2012) Does participatory forest management change household attitudes towards forest conservation and management? African Journal of Environmental Science and Technology Vol. 6(5), pp
Lund and Treue (2008). Are We Getting There? Evidence of Decentralized Forest Management from the Tanzanian Miombo Woodlands. World Development Vol. 36, No. 12, pp. 2780–2800
Rosenbaum, P and Rubin, D (1983). The Central Role of the Propensity Score Observational Studies for Causal Effects. Biometrika, 70, 41-55
Schreckenberg, K., Luttrell, C and Moss, C (2006). Forest Policy and Environment
Programme: Grey Literature Participatory Forest Management: an overview