Social and Economical Aspects of Miombo Woodland Management in Southern Africa: Options and Opportunities for ResearchPeter A. Dewees |
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Economics of the household, and woodland use and managementThe scope of household studies It is suggested above that rural households gain four principal types of benefits by relying on woodlands: foods, soil nutrient inputs, fodder and browse for livestock, and wood products (such as construction wood, firewood, and so on). Benefits accrue to these households principally because of interactions between sectors, for example, because woodlands provide dry season browse for cattle, which in turn provide manure and draught animal power for crop production. While there is a growing body of information about these types of benefits and interactions between sectors, their impact at the household level is very poorly understood. Precisely how tree resources are used (and are able to be used) ultimately determines their impact on household productivity. Direct benefits (woodfuels, wild foods, construction timber and so on) feature importantly in meeting subsistence household demands. Direct woodland benefits can also be bought and sold, generating badly-needed income, the lack of which has in some areas limited access to food crops which households may be otherwise unable to produce. Indirect benefits (the use of woodlands as a grazing resource, leaf litter transferred from woodlands to fields, and so on) are also considerable and there are few viable substitutes to be found in the market. Partly because of this, and because of limited purchasing power throughout much of rural southern Africa, indirect benefits feature even more prominently in household subsistence production strategies, and are less commonly bought and sold. Some studies have suggested important differential impacts of woodland use. Wilson (1990), Scoones (1990) and McGregor (1991), in their studies which considered woodland use by communal area households in Zimbabwe, all strongly indicated that poorer households are often much more heavily dependent on woodlands and on trees for food, soil nutrient inputs, income, and so on. There is, of course, a strong association between rural poverty and food security. Household food production can be constrained by small plot sizes, poor quality soils, and low rainfall. The problem of poverty is worsened by the lack of access to credit and problems of labor supply. The burden of farm labor is provided by women. An increased workload on women is symptomatic of labor constraints, and both compromises the nutritional status of women and predisposes newborn children to malnutrition (Tagwireyi 1990). Some research suggests that problems of food security are distinct from problems of poverty. Jackson and Collier (1988) showed in Zimbabwe that low-income households with a range of income sources were less prone to collapse into acute hunger than low-income households with limited access to assets and with a narrower range of income sources. Risk spreading in this way reduces household exposure to the impacts of drought. The capability to spread risk is perhaps greatest amongst those households which are able to exploit resources in a range of microenvironments, such as in patchy woodland areas (Wilson 1991, Scoones 1989). Especially with regard to the use of woodland resources, risk spreading is partly a function of the seasonality of access and use. Particularly during the late dry season, and before the harvest, woodlands can provide rural households with critical and badly needed inputs. Woodland resources may be viewed as assets which can be used during difficult times, as a means of diversifying crop production and income (from the sale of woodland products), and as buffer stocks of food, browse, and fodder during times of drought. The differential impacts of woodland use at the household level in terms of risk spreading, poverty, and food security are poorly understood. Tree resources play an unclear role in household allocative processes in terms of affecting patterns of labor use and employment, land use, and income and expenditure. Most studies about tree and woodland use in southern Africa (outside of the commercial sector) which could be construed to have an `economic' content are fundamentally lacking in analysis. Generally, they consist of extensive tables of descriptive statistics which emphasize only that rural people use and manage trees. They seldom explore causal factors, and there are few studies which seek to link broader patterns of agricultural production and household economics with tree-related land-use choices. Nor do these types of studies address the differential impact of the use of woodlands across groups of households. If meaningful analyses of trees and woodland resources are to be undertaken, they must necessarily focus on the household and the community, for example, not that a certain percentage of households are dependent on these resources, but which households, when, and under what conditions. As we have suggested, household differentiation and a dependence on woodland resources are closely linked. This has important implications for who undertakes woodland management and how they are to be managed. For example, there is some evidence which suggests that poorer households are more dependent on wild fruits than better off households. Seasonal access to wild fruits is important, and has been shown to reduce malnutrition rates among small children. The extent to which fruit trees are planted is linked to the extent to which wild fruit trees have been left in fields, and this is in turn linked to the species composition of woodlands which were cleared prior to cultivation (Wilson 1990). Household studies, then, must firstly consider the extent of dependence on woodland resources. A number of baseline surveys have taken this approach (see, for instance, du Toit et al 1984). As we have suggested, more substantive economic studies are needed which consider
All of these elements suggest the need for an approach which considers a great diversity of factors affecting farming households. Valuation The need for better `valuation' of woodlands and their products has been a recurrent theme in much of the literature about miombo use and management in southern Africa. There are different audiences for these types of studies, and these are discussed in greater detail in Section 7.3 of this paper. Environmental values can be derived in part by looking at three particular markets: conventional markets, artificial markets, and implicit markets. Conventional markets reflect the real or replacement value of a product (or of a service) which is the next-best option. [1] Artificial markets can be constructed using techniques such as contingent evaluation to determine consumer preferences for woodland products. Finally, woodland values are also thought to be reflected implicitly in markets for land where these operate without distortion. [2] At the household level, valuation, derived from consumers' own preferences, is of some interest because it should (in theory at least) tell us what woodlands are worth, based on the consumers `willingness to pay'. A key constraint, however, is that most methods of valuation rely on imputing values for specific woodland products rather than for the woodlands themselves. Campbell et al. (1991) for instance, calculated farm-gate values of specific woodland products on the basis of household use per year. Willingness-to-pay, assessed through a contingent valuation exercise in the same study, also considered the value of woodland products per household. Four particular variables must be considered in establishing the value of benefits from woodlands: the number of households who can exploit them, the density of woodland cover, species diversity and woodland productivity, and (if farm gate prices are to be used) the presence of some markets where woodland benefits could be bought and sold. [3] The first two of these can be considered jointly, and evaluated in terms of woodland canopy cover per person or `woodland dependency.' Studies which have taken this approach have shown large differences in rates of woodland dependency, suggesting that woodlands would have to be valued quite differently from area to area (Bradley 1990). Evaluating the impact of species diversity and productivity on woodland value is even more problematic. Miombo woodlands, for instance, have a much greater diversity than many other woodland types. Fruit trees are as much as 4 times more abundant in these areas than in mopane woodlands (Campbell 1987). While the total value of products which could be derived from a fixed area of miombo woodland could be quite high compared to mopane woodland, the marginal utility of additional production could be quite low simply because of the relative productivity of these woodlands. In contrast, while the total value of products derived from a fixed area of mopane woodland could be quite low, the marginal utility of additional production could be quite high, particularly if there are large populations dependent on limited resources. Most valuation studies have not considered the marginal value of production. [4] There is no generalizable model about how much woodland is needed to produce what households consume. This will vary depending on the benefit under consideration, and whether or not production is from clearfelling or from the harvesting of yields. The large range of variables affecting woodland production and use makes it difficult to infer much about the `value of woodlands' and empirically sound woodland valuation still eludes most researchers. The desire to focus on this approach is partly rooted in the assumption that individual or household values can be aggregated in a way which should guide social choice. As we have suggested, methodological limitations currently prevent economic or policy analysts from doing so in a way which is empirically rigorous. This is not to say that valuation research should be discarded altogether, but rather to suggest that it must be more carefully focused at the household, and at the relationship between imputed values for woodland products and the household economy. This line of research could be a tremendously fruitful one, as it could help to clarify the tradeoffs between woodland management and other household resource allocation strategies. Concerns about methodology Particularly amongst researchers in fields other than economics, there is a concern that the need for statistical validity in analyzing data from household studies and surveys obscures larger and more fundamental issues which are seldom captured in household survey work. While this is an increasing concern of researchers more generally, there is special relevance for household research about natural resource use and management because of the large number of variables which influence household decision making about resource and woodland use. The problems of large surveys and sample sizes, the overcollection of data, and burdensome survey instruments are well known. At the other extreme, there is a concern that more interactive `rapid appraisal' types of research approaches seldom provide adequate information for informed policy making in a way which is intellectually rigorous. There is clearly much truth in both of these views. A view which is gaining increasing currency is that neither of these approaches should be a substitute for the other. Rapid appraisal can be extremely useful for focusing research on critical issues, which can be further developed in a way which is intellectually rigorous in household survey work. There is a very real need to focus more critically in household survey work, and rapid appraisal can be a very useful tool in doing this. The concern is somehow that something will be missed. Researchers argue that the marginal costs of additional information collected in survey work is low, and that a failure to ask sufficient questions in survey work will result in critical oversights during analysis. Statistical validity is another concern. The development of proxies in survey work for different indicators is a useful direction. Household composition and the structure of labor supply, for instance, can be a useful substitute for intensive time studies. Simply because of the degree of variation across households, qualitative indicators can sometimes provide a better picture of how households are making resource allocation decisions. There are statistical and econometric tools for dealing with qualitative indicators. The analysis of decision-making, reflected in dichotomous variables for instance, is possible with different types of regression analysis. This allows the analyst to model binary choices (rich or poor, labor constrained or not, woodland scarce or not, and so on) from a set of discrete variables. The most difficult task for the analyst is deciding what minimum data set will be necessary and sufficient for addressing the questions posed. Economic research needs to be much more creative if it is going to be successful at addressing serious policy issues in a way which is both intellectually rigorous and which considers the constraints posed by intensive household survey work. In some respects, however, it is less a question of rigor and more one of who needs the information in the first place. Different groups of policymakers and analysts have different information needs. The choice of the method for collecting and analyzing data ultimately needs to be determined by the requirements of the user. These differences should help to clarify the tradeoffs between data quality and timeliness, short and long term data requirements, participatory research and the need for rigor. A further challenge for researchers will be to evaluate the influence of spatial variables (such as the extent of and access to forest, grazing, and water resources) on social and economic variables at the household level. Increasingly, household research must capture how agricultural production decisions are influenced by the household's physical location in the landscape. An even greater challenge will be to identify the impact of temporal changes in physical, social, and economic variables on the natural resource base (Scherr and Vosti 1993). n any event, social and economic research at the household level about natural resource use must be clearly drawn into, and driven by, the policy process. For instance, possible research themes might focus on the impact of structural adjustment on woodland management. Conceivably, economic devaluations and liberalizations would increase the costs of chemical fertilizers to farmers, and this would result in greater pressures on woodlands for organic nutrients. In valuation studies, this would greatly increase the value of leaf litter collected from woodlands, and make a stronger case for their management and conservation. For most sectors, economic research at the household level has seldom been driven by such concerns, and more conventional themes have, for the most part, dominated. In summary then, research about the role of woodland products in the household economy is a high priority. This research must increasingly focus on how households allocate different productive factors, particularly land, labor, and capital, in ways which affect woodland use and management. There is a real need for research at the household level, with substantive economic content, which considers the role and impact of differentiation on woodland use, risk and the diversification of inputs into the farming system, seasonality of access and use, food security, and the balance between subsistence demands for woodland products and their sale in the market. Valuation studies should be more carefully designed to explore decision-making at the household level vis-a-vis real or imputed values for woodland products. In characterizing the scope and nature of household studies, research should have clear policy links, and should be increasingly focused on questions of relevance to a broad range of policies. Finally, careful design of these types of studies is essential to address some of the methodological problems of past research.
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