A relatively new concept in the literature on rural household incomes is that of income from forests and from environment services. Forest income is defined as income from forest produce (other than plantations) including produce collected for fuel, food, fodder, construction, medicine, and other uses.  Environment income “refers to extraction from non-cultivated sources,” or non-forest natural environments (Angelsen et al. 2014). For example, fish from rivers in forests are counted as forest income while minerals extracted from forests are counted as non-forest environment incomes. Total environmental incomes are defined as “the sum of incomes (incash or kind) obtained from the harvesting of resources provided through natural processes not requiring intensive management (CIFOR 2007 cited in Angelsen et al. 2014).”

A new, large, interesting, village-based data set on household incomes that includes incomes from forests and environment incomes is the Poverty Environment Network or PEN data base. The study from which the data derive was coordinated by the Center for International Forestry Research (CIFOR), a CGIAR institution.

With partners in different sites all using a uniform methodology, data were collected for about 8000 households in 333 villages (33 study areas) in 24 tropical and sub-tropical countries. As the objective was to estimate incomes from forests, all the sites were located in forested or semi-forested areas. The selection of villages is not explained fully but clearly was purposive. In India, the selected site was in Gujarat but there is as yet no published work on these data (that is, information on the study villages is not available on the website).

The data collection methodology is probably unique. In each site, a village-level questionnaire was canvassed at the start of the project and at the end (12 months later). Two household-level surveys were conducted that collected information on household demography, assets, and access to forests (it is not clear these were sample or census-type surveys, although, given the small size of the total data set, they were porobably sample surveys). Finally, four quarterly household income surveys with a 1-3 month recall period were conducted. Questionnaires and other information on coding, cleaning, etc., are available on the website. While the methodology requires further study, this is clearly an important data set for all those interested in rural livelihoods.

The main finding of the study is that incomes from forests account for about one-fifth (22 per cent) of total household incomes when the data across sites are pooled. If income from non-forest environment services is added, the share goes up to over a quarter. In fact, the share of income from forests and environment services accounts for 27 per cent of total household income – only marginally less than the share of crop income (28 per cent).  Further, dependence on forest incomes does not vary much across income quintiles. In other words, it is not just the poor that depend on incomes from forest. All households in a semi-forested or forested region draw on incomes from forests and the environment. Cash income from forests was more important for the relatively well-off households while subsistence incomes were more important for the poor households.

There are huge problems with pooling data in this manner, but the point raised by this study that is worth noting is the critical importance of forests for the livelihoods of people living in semi-forested and forested regions.

The Foundation’s recent surveys in Tripura as part of the Project on Agrarian Relations in India can be used to study the contribution of forests to rural household incomes and livelihoods.

Reference

Arild Angelsen, Pamela Jagger, Ronnie Babigumira, Brian Belcher, Nicholas J. Hogarth, Simone Bauch, Jan Borner, Carsten Smith-Hall and Sven Wunder (2014), “Environmental Income and Rural Livelihoods: A Global-Comparative Analysis,” World Development, 64, pp S12-28.