Rate and Causes of Deforestation in
Indonesia:
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GUIDELINES FOR THE DETERMINATION OF RATES
AND CAUSES In the foregoing we have seen that past attempts to discover the rate of change and causes of deforestation have been hampered by:
We suggest that future efforts to determine rates and causes of forest cover change be based on the following guidelines.
Rates of forest cover change Rates of forest cover change should be based on comparison of satellite imagery of land cover at two (or more) points in time. [30] The method of image creation should be matched, so as to avoid misinterpreting differences of resolution, texture or colour as forest cover change. Ideally, the past image(s) should be sufficiently old for differences of forest cover to be perceived clearly, and the new image should be sufficiently recent so that the measure of change captures relevant new phenomena. The definitions of key terms must be clear and applied consistently across all aspects of the rate measurement. We recommend use of the definitions for "forest" and "deforestation" employed by FAO (1996) in their Forest Resources Assessment 1990: Survey of Tropical Forest Cover and Study of Change Processes. [31] "Forest" is defined as "natural forest" (including both continuous and fragmented forests); "non-forest" refers to "other wooded lands" (including shrubs and short fallow); and "man-made woody vegetation" includes plantations (both forest and agricultural) (p. 20). The study uses three-tiered definitions of "forest" and "forest cover change" in view of the varying purposes of researchers. "Forest" is defined either as: "closed forest"; "closed + open + 2/3 fragmented forest"; or as "closed + open forest + fragmented forest + long fallow" (p. 20). "Forest cover change" is defined as follows (p. 22):
We recommend close consultation of the methodology and technical specifications in the FAO (1996) study, both because they are a considerable improvement on past practice, and also because a uniform methodology offers the possibility of cross-regional and cross-national comparisons of trends. Finally, we urge that analysis of the extent and rate of forest cover change give proportionate attention to the issue of degradation. Past studies have tended to emphasise deforestation to the exclusion of degradation. This tendency ignores the fact that degradation (in which the timber industry has a large role) is often a precursor to deforestation (defined as permanent forest cover removal) by other forms of agency.
Causes of forest cover change Determination of the cause of forest cover change poses large conceptual and methodological challenges. Ascertaining cause is difficult because it involves demonstrating linked patterns of cause and effect through time, and there are often few data to prove these linkages. As we have noted earlier, several forms of agency may operate in the same location, making it difficult to disaggregate the effect of one from the other. We suggest the following guidelines for the improvement of determination of cause of forest cover change. Levels of causation Causation should be specified at three levels of explanation: agent; immediate cause; and underlying cause. [33] The agent refers to the people or organisations (e.g., smallholders, logging companies, plantations) that have a physical role and/or a proximate decision-making role in forest cover change. The immediate causes of forest cover change are those decision parameters that have a direct influence on the behaviour of the agents. Examples of such parameters are: relative prices; relative access to resources and markets; availability of technology; rules regarding resource use; and cultural traditions. The underlying causes of forest cover change are those overarching national, regional, or international forces that can govern the influence of decision parameters. Examples of such forces are social structures, power relations, patterns of capital accumulation, terms of trade, and demographic and technological changes. Observe in Table 1 that early assessments of causation focused on agency, whereas later formulations gave attention to agency and to underlying causes. Interaction or independence of agents As mentioned earlier, it is possible for various kinds of agents to operate in the same location. It is also possible for agents to operate in separate locations and to have little contact with one another. It is important to specify these forms of interaction or independence in assessing causation. In cases where different agents operate in the same location, there are likely to be important interaction effects that either increase or decrease forest cover change. Increased change might happen in cases where competition for access to land increases land rents and weakens customary land rights, as has happened in Riau province, Sumatra (Angelsen 1995: 1722-1724). Decreased change might happen in cases where (for example) shifting cultivators successfully defend their traditional forests against encroachment by loggers. [34] Conversely, in cases where forms of agency operate independently of one another, there may be factors that facilitate or inhibit forest cover change. For example, there may be forest dwellers whose lands are relatively well protected from encroachment because they live in remote primary forests on hilly terrain that are relatively inaccessible to timber companies. Little is known about the geographical distribution of forms of agency and their interactive (or synergistic) effects on forest cover change. Information on this subject is sketchy and may be out of date. Weinstock and Sunito (1989: 50) say 39.8% of shifting cultivation is taking place "on lands of critical concern to the management of production forests". Sutter (1989: 13) estimates 85% of annual deforestation occurs in conversion and production forests (but agency is not specified). World Bank (1990: 6) data show there is a larger area of open forest canopy in production forests (both "limited" and "regular") compared to reserves and protection forests, but here again there is not sufficient information to know the cause. It will be useful to achieve a greater understanding of these effects, especially in view of increasing competition for access to land in the outer islands, and the growing role of estates and plantations in forest cover change. Satellite imagery/GIS assistance In certain cases, satellite imagery and GIS mapping can assist in determining patterns of causation. For example high resolution imagery (accompanied by ground truthing) can document a change from natural forest cover to a monoculture oil palm plantation. In this case the "cause" (defined here in the sense of ultimate non-forest land use) is clear. However there are many cases where the change from closed to fragmented natural forest conveys little visual information about cause, even in cases where high-resolution imagery is available. In these cases, social science research is necessary to achieve a full understanding of the reasons for forest cover change. It is important to know the capabilities and limitations of imagery and GIS technology in undertaking research on causation. Macro-economic causation Indonesia is presently noted for the relative stability and resilience of its economic situation. Macro-economic restructuring policies have been implemented since the 1970s in response to world-wide oil shocks that affected the economy dramatically and that have had repercussions until the present. Indonesia is viewed as a case of successful macro-economic adjustment, inasmuch as the overall policy of deregulation, export diversification and currency devaluations are credited with maintaining high rates of economic growth. It is not known what net effects these policies have had - whether positive or negative - on forest cover in the country. These adjustment policies and other macro-economic conditions (prices of key commodities, level of debt, terms of trade of agriculture and the rural sector) have not yet been studied adequately in relation to the livelihoods of people in forest communities and forest condition. [35] Modelling exercises by Jepma and Blom (1992) and Thiele (1995) make interesting inroads on this topic. Future research should examine the net effect of various macro-economic conditions on forest cover, via their effect on smallholders (migration patterns and farming system choices), large farmers (investment decisions at the forest frontier) and concessionaires (incentives for long-term management of primary forests). |