in unskilled paid work or occupations outside of agriculture. However, when households do engage in outside employment, they tend to migrate only temporarily and for short distances. Permanent migration over long distances for work is rare for most poor rural households (Banerjee and Duflo 2007). Thus, given the lack of ownership of assets by the rural poor, and their tendency to stay where they are located, it is not surprising that the livelihoods of the "asset-less" poor are often the most dependent on their surrounding natural environments.

The scale of this dependence may be very extensive in some developing regions. For example, in Southern Malawi households derive 30 percent of their income on average from exploiting “common” forests (Fisher 2004). Households that are especially lacking in land, education, and goat holdings are more reliant on “low return” forest activities, such as sales of “forest-based” crafts (bamboo baskets and mats, grass brooms, and wood-fired pots), roof thatching and brick-burning, sales of prepared foods and drink, sales of firewood and bamboo, and traditional medicines. Similarly, in both Cameroon and South Africa, the poorest households used more non-timber forest products, such as fuelwood, wild fruits, edible herbs and grass hand brushes, per capita than wealthier households (Gbetnkom 2008; Shackleton and Shackleton 2006). Such findings appear to be consistent with studies of income diversification across Africa, which show that the “asset-less” poor diversify into low-return activities based on exploiting common property environmental resources, but with little hope of escaping the “poverty trap” (Barrett et al. 2001; Dercon 1998).

This link between asset poverty, lack of income opportunities and resource extraction as insurance may be very significant in many tropical forest regions, where the livelihoods of the poor often depend on the extraction of biological resources in fragile environments (Adhikari 2005; Coomes et al. 2011; McSweeney 2005; Shone and Caviglia-Harris 2006; Pattanayak and Sills 2001; Sunderlin et al. 2008; Takasaki et al. 2004; Vedeld et al. 2004; Wunder 2001). For example, Vedeld et al. (2004) conduct a meta-analysis of 54 case studies globally of rural communities that live in or near tropical forests, and find that on average 22% of household income in these communities depends on forest resources. However, the proportion of forest income was significantly higher for poorer households (32%) compared to the nonpoor (17%). Similarly, López-Feldman and Wilen (2008) find that non-timber forest product use is mainly conducted by households in Chiapas, Mexico with low opportunity costs of time and fewer income generation opportunities. And, in Palawan (the Philippines), hunting pressure on fauna was shown to be inversely related to farm size and agricultural productivity, but positively correlated with labor availability (Shively 1997).

The state of the local environment may also affect how the poor utilize their resources, and in turn, their livelihood strategies. In India, Narain et al. (2008) find that, in villages surrounded by good quality forests, the poorest households depend on forest resources for as much as 41% of their income compared to 23% for the richest households. In areas where the forests are in a poor state, both the rich and poor’s use common resources decline, but more so for the poor; both types of households depend on forests for only around 9 to 14% of their income. In West Bengal, almost 10% of the time of the average household is spent on gathering fuel, either for use at home or for sale (Banerjee and Duflo 2007). In general, throughout many tropical forested regions, there appears to be a relatively high dependence on forests for livelihoods in areas of high forest cover and high poverty, as poor households depend on the forests for both supporting their economic livelihoods and as a source of new land (Coomes et al. 2011; Sunderlin et al. 2008).

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