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Participatory Forest Management (PFM) in Tanzania aims to improve forest condition, livelihoods for local people and natural resources governance at the village level. Using data collected from 12 villages and forest areas with (n=10) and without (n=2) participatory forest management across eastern Tanzania we aim to assess how livelihoods of villagers compare between forest management regimes. Data show that most villagers across the study sites are poor, with small numbers of wealthier people. There is little overall income variation across forests under PFM, but there is considerable variation of benefits from the PFM forest between village wealth classes. Richer village members are able to secure preferential access to the PFM forest and utilise it (or benefit from issuing licences) for livestock keeping (in drier forests), charcoal production (close to access routes to towns), and harvesting (where high value timber remains). Data suggest that the PFM approach has made certain sectors of the community more wealthy, typically those setting the rules and enforcing them. But they also indicate that the overall impacts across the community are marginal – and may be negative for the poorest community members.

Rapid Rural Appraisal techniques are frequently used for wealth-ranking of households in rural communities. The main justifications of such approaches are that they are fast, allow prestratification of households in preparation for surveys and that they have been shown to have at least some empirical validity as means of stratifying households by socio-economic status. Sometimes, however, the participatory process may fail to produce consistent wealth categories, or people refuse to accept labels such as ‘poor’ and ‘rich’ and/or are reluctant to assign such categories to households within their village. A household survey in Tanzania was conducted in 12 villages across eastern Tanzania in 2008-2010. In all villages a participatory wealth ranking exercise was conducted and used for stratification of households. Sample households (n=40 per village) were allocated proportionally to wealth categories. The structured household survey emphasized assets, income, and perceived effects of Participatory Forest Management. The value of individual non-productive assets was estimated through a follow-up survey and combined with results from the household survey to estimate total value of assets for each household. In this study the original, partly inconsistent wealth ranking is examined and compared with estimated incomes and asset values. Next, alternative wealth classification rules are introduced and resulting classification outcomes are examined and discussed.

Thousands of surveys on rural livelihoods in developing countries are being done every year. Unfortunately, many suffer from weaknesses in methods and problems in implementation. Quantifying households' dependence on multiple environmental resources (forests, bush, grasslands and rivers) is particularly difficult and often simply ignored in the surveys. The results therefore do not reflect rural realities. In particular, 'the hidden harvest' from natural resources is generally too important to livelihoods for development research, policies and practice to ignore. Fieldwork using state-of-the-art methods, and in particular well-designed household questionnaires, thus becomes an imperative to adequately capture key dimensions of rural welfare. This book describes how to do a better job when designing and implementing household and village surveys for quantitative assessment of rural livelihoods in developing countries. It covers the entire research process from planning to sharing research results. It draws on the experiences from a large global-comparative project, the Poverty Environment Network (PEN), to develop more robust and validated methods, enriched by numerous practical examples from the field. The book will provide an invaluable guide to methods and a practical handbook for students and professionals.