Forest dependence is more than forest income: Development of a new index of forest product collection and livelihood resources

Across the tropics, in both forested and agricultural landscapes, many households are highly dependent on forest resources. Small-holder farmers, many with few alternatives, collect fuelwood, building materials, wild foods, medicinal plants, and other forest products for subsistence or sale. Given continued tropical forest loss coupled with household forest dependence, quantifying levels of forest dependence is important for informing approaches to poverty alleviation and forest conservation. Forest dependence is largely measured using a relative forest income (RFI) approach, notably in the global analysis by the Poverty Environment Network of the Center for International Forestry Research. This approach ascribes monetary values to forest products, which may be unsuitable for contexts where households primarily consume rather than sell forest goods, and which does not address other burdens on households of relying on forest products (e.g., time use). In this paper, we introduce a new Forest Dependence Index (FDI), which measures (at the household level) forest products collected, effort involved in forest product collection, asset-based relative wealth, and non-forest livelihood strategies. Using a case study in Malawi, a country with high rates of poverty and forest ecosystem change, we: 1) demonstrate the FDI and its application; 2) compare the FDI to RFI; and 3) assess how the sub-indices contribute nuance to the FDI values. We calculate the FDI for agricultural communities in southern Malawi using household surveys that we conducted on income, assets and use of all forest products (e.g., amounts collected, walking time to collection sites). We show that the majority of households had intermediate FDI but low RFI values. We demonstrate how households can have the same RFI yet varying FDI values. Ultimately, we show that the FDI provides insight into multiple livelihood aspects of dependence and is a valuable addition to the RFI method for informing forest-based poverty alleviation strategies. (C) 2019 The Authors. Published by Elsevier Ltd.