Managing the Miombo Woodlands of Southern Africa Policies, incentives and options
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4.2Household use of forest resources – survey results4.2.1Livelihood income sources in rural areasThe household survey shows the variability in livelihood income sources across the study sites (Figure 1). On average, agriculture production is the main source of income accounting for 45 percent of total household income, followed by forest income (c. 20%) and trading (c. 20%). Formal and informal wage income together account for nearly 10 percent and the rest comes from remittances, gifts and transfers including food-for-work programs. Forest income is the dominant source of income in Ndola Rural accounting for 47.6 percent of the total household income, but agriculture is the main source of income in six study sites, with trading as the most important source of income in one site (and in this site, it is a forest-derived product – honey beer - that is a main source of trading). Forest income is the first or second most important income source in five of the eight study sites. Our results are comparable with those obtained from case studies in some neighboring countries by Cavendish (1999), Campbell et al. (2001) and Fisher (2004), who reported forest incomes of about 20 percent of the total household income. 
Figure 1: Source of total household income (including cash income and consumption) for eight sites in three provinces of Zambia 4.2.2Main forest productsTable 5 gives the average values of forest production of user households in the eight study sites, as well as the percentage of households producing or harvesting each product. Table 6 gives the percentages of households selling each product and the value of these sales. As expected, there is little variation across sites for firewood, with the majority of households collecting in all villages, except Lwitikila (Table 5), and few households selling firewood (Table 6). In communities where forests are in good condition, households collect deadwood, whereas when firewood is scarce, household cut down trees for firewood and markets for firewood are slowly emerging. The latter may explain why the average percentage of households collecting firewood in our survey (73.3%) is slightly lower than the reported percentage of rural households using firewood in the National Census in 2000 (87.7%), though it could also reflect the particular villages that we sampled. The average household consumes 100 kg of dry wood per month. Charcoal is a source of cash income for almost half of the households in Katanino, which is near large urban centers such as Ndola and Kitwe (Table 6). In Paul Kalemba only 10% of the households sell charcoal, but on average they earn ZMK1,889,250 with this activity, which is 77% of the average total household income in that area. In the other areas, less than about 10% of house holds produce charcoal for sale and the farm-gate prices are lower due to the distance to urban markets. About 20% of all the households interviewed use charcoal, mainly for space heating, cooking and baking of snacks. Following wood-fuels, construction materials (i.e. thatching grass and poles) are the most popular forest products, collected by more than 40% of the households in all the sites (Table 5). However, these are collected mainly for subsistence use (>90%). Timber is collected by few or no households in most sites. Lutale is the main commercial timber area and 16% of the households earn on average ZMK606,250 per year from these sales. However, households in Paul Kalemba and Nseluka make even better money with timber production: ZMK4.5 million and ZMK1.4 million respectively, though only a few households are involved. Wild foods, which are common in different vegetation types, such as tubers, fruits and mushrooms are also collected by many households in all the villages. Selling wild fruits is not very common in all the villages (<10%), although in Nseluka households earn on average ZMK108,000 from the sale of fruits (Table 6). Mushrooms are collected by more than half of the households in all the areas, but very few households sell them (<10%). Selling mushrooms is most profitable in Katanino, where they fetch ZMK30,000 per 25 kg bag and selling households earn on average ZMK300,000. This is likely to be related to the access to urban markets in Ndola and Kitwe. The prices of tubers were higher in village markets around Kasama and Mpika than in Ndola Rural and Mumbwa. This variation is mostly related to differences in tuber species harvested and sold by households in these areas. Whereas chikanda (see above) is the most commercially valuable tuber harvested by rural households in Kasama and Mpika, households in Mumbwa harvest busala (eaten as a snack) for own consumption and for sale in local and district markets. Because of the high demand and over-exploitation, populations of chikanda have been depleted in most wetlands where they occur. As a result, the local and urban price of chikanda has increased significantly over the last decade and this trend is expected to continue to increase until households domesticate the tuber. Caterpillars, on the other hand, are limited to certain areas, being most commonly collected in Kopa and Lwitikila, where more than three quarters of the households collect chipumi caterpillars (Table 5). Moreover, chipumi caterpillars (popular and high priced in urban markets) provide cash income for 58% and 62% of the households in Kopa and Lwitikila, respectively (Table 6). Caterpillars are very seasonal and are only collected in November and December, providing households on average more than ZMK300,000 per season in cash. In the other villages few or no households collect caterpillars, rarely chipumi and mostly for own consumption. Table 5: Average value of gross production of forest products for user households in eight villages (Zambian Kwacha. Values in brackets are the percentages of user households in total population)4
Table 6: Average value of sales of forest products for user households in eight villages (Zambian Kwacha5. Values in brackets are the percentage households trading each product, in total population)
Collecting wild honey or keeping bees is practiced by on average about 20% of the rural households, with most honey produced in Mumbwa district, where up to half of the households are involved (Table 5). This study did not include Northwestern province where an estimated 70% of the countries beekeepers live. Revenues from honey sales at household level are highest in Mumbwa district and Katanino: between ZMK325,000 and ZMK450,000 per year (Table 6). Selling reed mats is the most profitable forest-based activity in Nalusanga and Kopa, where selling households earn on average ZMK913,000 and ZMK450,000 per year, respectively, although very few households are involved (Table 6). Similarly, woodcarving may be quite profitable (i.e. in Nseluka and Chibuluma) but it is not practiced on a large scale anywhere. 4.2.3Who benefits from dry forests?In this section, we analyze how dry forests benefit the poor and the not-so-poor, and the determinants of forest income. It is clear that income earned by households in the top wealth quartile from forest gathering is three times higher than that earned by poorer household (Table 7). The top quartile also stands out in terms of much higher values for agriculture, wage employment and trading than the three lower quartiles. It is particularly important that 64.5 percent of income is forest income for the poorest quartile but only about 12.1 percent for the richest quartile. The share of income from employment and remittances to total household income was relatively small for all quartiles.
We further examined how non-forest income and differences in household socioeconomic and demographic variables affect forest income. We did this by using the Tobit model and regressing total value of forest products harvested on a set of household and market variables. The regression results in Table 8 indicate that age of household head and household size are significantly and negatively correlated with forest income (P-values 0.07 and 0.0002, respectively). This suggests that the elderly and households with larger families depend less on forests as their primary source of income. The coefficient of non-forest income is positive and statistically significant and the square of non-forest income is negative and statistically significant. These results suggest that as non-forest income increases a household will initially increase harvests of forest products, but further increase in non-forest income reduce household’s dependence on forests. These results have implications for policy makers, as programs that lead to increased household income outside forests are likely to reduce pressure on forests.
We examined factors that influence household dependence on forest resources (Table 9). We obtained a negative relationship between forest dependence and non-forest income. Although the coefficient on the squared term has a negative sign, it is not significant. This implies that increases in household income lead to a substantial reduction in household dependence on forest resources. These findings correspond with results from Chileshe (2005) in Northern Province who found that poorer households consumed wild foods more frequently, and also collected them to trade with wealthier households for agricultural crops.
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