Updated July 1999
< from Part 1
Once established for a sample location, matrices can be aggregated, enabling assessments e.g. by geographic region, or by ecological zone. Prior to that, the matrices must be mathematically standardized for the exact period 1980-1990 on the basis of the annual class-to-class transition probabilities observed in each matrix.
An example is supplied by the following table (Figure 5), which synthesizes the changes assessed for the tropical areas as a whole, based on measurements done in 117 sample units - 47 in Africa, 30 in Asia and 40 in Latin America (FAO 1996).
The class-to-class changes reported in this table illustrate the complexity of the dynamics involved. As expected from the consideration of such a large and diversified area, almost all the possible class-to-class changes are represented. However, most of the area changes are located above the diagonal, implying a loss of forest area or cover, fragmentation etc.
This table also shows that thinking only in terms of deforestation is too simplistic. Deforestation is a multifarious phenomenon involving complex processes. It is important to consider all the aspects of those processes, i.e. the patterns of class-to-class changes. The changes observed in a given class are read along the respective rows, e.g. closed forest:
From the above table it appears that the most common class of destination of the changes - the one that gained most - is other land cover (mainly through a shift to cattle ranching and permanent agriculture), followed by short fallow and fragmented forest. The most important class-to-class transitions are: closed forest --> other land cover; closed forest --> short fallow; and shrubs --> other land cover.
The data of change matrices can also be presented in the graphic form of flux diagrams that afford a quick view of the relative importance of the various types of change: Figure 6 thus illustrates the pan-tropical transition matrix. The vertical ranking of land cover classes in the diagram corresponds to lesser and lesser woody biomass down the column (see scale on the left). Changes to a lower-ranking class (reported on the right side of the diagram) correspond to a loss of biomass and degradation of the cover: hence the label 'negative'. An examination of the said diagram shows that:
The change from closed forest to open forest is mostly the effect of fuelwood exploitation, grazing and related fire practices, and selective logging. Population dynamics (e.g. population growth, migration flows, urbanization) plays a role in these phenomena:
The change to other land cover corresponds to the development of permanent agriculture and pastures, meaning that during the period observed the forest has been replaced by permanently cultivated fields or by ranches. As the period of observation (about 10 years) is relatively short as compared to the time frame of change in agricultural systems, the fact that there has not been a transition through the long and short fallow stages suggests either massive immigration or - more commonly - investment through planned operations, usually to develop commercial agriculture . The change to plantations, of course, also indicates a similar pattern of planned operations. These two types of transition are evident in Latin America and in Asia, and to a much lesser extent in Africa (see Annex 2).
The change to fragmented forest results from partial deforestation by clearing of small patches of forest, which creates a mosaic of forest and non-forest cover; in turn, fragmented forest mainly changed to "other land cover", meaning that fragmentation is an intermediate stage towards permanent agriculture.
Overall, population pressure is an important factor in vegetation loss, especially in areas with scarce land reserves and limited sources of energy. To this extent, the close statistical association of population growth with deforestation easily leads to foresee further loss of forest cover in the wake of projected population growth. For instance the FRA 1990 report (FAO 1993) noted that the population of the developing regions was expected to grow from 4 to 7 billions during 1990-2020, concluding that "as a result, the risk of deforestation in the developing countries remains very high".
Such a statement probably holds at the broad geographical level to which it refers - i.e. developing countries as a whole - because local variations in the form and intensity of the population-deforestation linkage tend to offset one another, so that the overall correlation can be expected to change only slowly. But at country level - and a fortiori at the local level - a closer look at the linkages is required, because the mix of factors that impinge on forest futures varies considerably. We shall now look into this question.
Figure 7 provides a good illustration of this aspect of the population-deforestation relationship. That large tracts of forest have been cleared is evident, but the aspect of major interest here is that three different types of human impact can be distinguished:
In a situation such as the one illustrated above, a view on the future of deforestation - magnitude of the risks, assessment of the pros and cons, means to counter it - requires more than sound data on population trends (natural growth and migration). It is important to take into account the nature of the activities undertaken by the population in question.
Policy-wise, seeking to minimize ecological damage would entail hard choices between land use changes that bring about very different economic outcomes (e.g. with regard to output value or potential foreign currency benefits) but benefit very different groups of population (in nature and size). Of course, economic policy measures proper are required. For instance shifting cultivation - the main factor in deforestation world-wide - uses several times more land per unit of produce than permanent agriculture does, but permanent agriculture requires inputs that some rural populations cannot afford. In this case, fiscal or price policies might be justified.
From the scientific viewpoint, the above information highlights the value of analysing population-deforestation linkages at several geographical levels, in order to combine complementary angles of analysis and avoid misconceptions and simplifications. The close statistical association at global and regional level revealed by the FRA 1990 report has its usefulness, but admittedly embodies more complex linkages. Consequently, geographically more detailed analyses are crucial when it comes to understanding and intervening on processes at the national or sub-national level. Besides population characteristics and dynamics, relevant elements in such analyses are land tenure, local political institutions, and the market relations in which local producers are engaged. This may have to include international markets which, as illustrated by the example above, can have an indirect but strong impact on the local environment.
Very much like biological growth processes, deforestation has been observed to proceed relatively slowly at initial stages, much faster at intermediate stages, and slowly again at final stages. Using this analogy, forest area change can be represented by a differential equation of the form:
dy/dp = b1 Y b2 - b3 Y  where y is the percentage forested in a given area,A high correlation between population density and forest cover was found using a logarithmic transformation. Measuring population density in persons by square kilometre, P is defined as:
dy/dp is the derivative of y with respect to population density,
and b1, b2 and b3 are parameters.
P = logn (1 + population density)The change model structure can be briefly described as follows:
(i) dy/dp : Dependent variable. It is the ratio between population density change and forest area change, representing the response 'dy' to a given change of population pressure 'dp'. The higher the value of the ratio, the higher the change in forest cover per unit of population change. dy/dp is a function of the 'size' of the forest (Y in equation ) and of the following parameters:
(ii) b1 : This parameter can be taken to represent productivity - or site quality, to follow on the analogy with yield modelling. In fact in the present model formulation it is a function of bio-climatic parameters. The meaning of b1 is that the same population growth rate has different effects in different ecological conditions. If time series of forest cover and population are available, the b1 parameter can be computed from the observed values.
(iii) b2 : This parameter represents the culmination point of the derivative function. In the State Model curve (see below) it is the inflection point of the curve, where the deforestation rate culminates and start to decrease.
(iv) b3 : This parameter is related to the maximum possible deforestation, represented by the asymptotic value of Y where an additional population increase has no effect on forest cover, which remains stable in time. This parameter can be related to accessibility (both physical and legal) of forest resources and to land suitability of forest areas for transfer to other land uses.
|y = a0 (1- a1 e -a 2 P) a3  State model|
The cumulative growth curve defined by this equation has a sigmoid shape and an upper asymptote. The function gives the estimated forest area for a given population density level. The following system of equations defines the four model parameters:
a1 = 1 - (y0 / ym) (1 - b2)
a2 = (1 - b2) b1 ym (b2 - 1)
a3 = 1 / (1 - b2)
where ym = maximum possible non-forested area
y0 = non-forested area for P = 0
b1 and b2 are parameters of the change model
It can be noticed that an additional variable y0 is needed to solve the state model equality . Y0 represents the initial condition of the site, i.e. the state of forest cover for a zero population density.
As new information and data become known, such models can be improved; FAO is in effect working to refine this model.
The effects of rural population pressure are very clear in Africa where the single most dominant transition has been closed forest --> short fallow (small-scale subsistence farming) and where many transitions have been represented with similar frequency; the sequences closed forest --> open forest --> fragmented forest --> other land cover are typical and they represent clearly the various progressive stages of forest depletion.
In Asia this type of pressure is mainly represented by the sequences closed forest --> long fallow --> other land cover and closed forest --> short fallow --> other land cover, reflecting the expansion and intensification of shifting cultivation (classes Long Fallow and Short Fallow) in the hills of South East Asia. Abandoned shifting cultivation areas are represented by the positive transition long fallow --> closed forest. The difference between the forest area going into long fallow and the area of long fallow reverting to forest shows how unbalanced this originally sound practice has become.
In Latin America this type of change was less common but still visible in the transition closed forest --> short fallow, largely the effect of small-scale farming in Amazonia and/or Yucatan. The effects of centrally planned operations are evident in Latin America and in Asia but to a much lesser degree in Africa. The typical transitions have been closed forest --> other land cover or, relevant in Asia only, closed forest --> plantation. Typical land uses related to these processes were: large areas of deforestation owing mainly to cattle ranching in the Brazilian Amazon, large resettlement and plantation programmes in South East Asia and, to a lesser degree, in West Africa..
2. This section is based on the results of collaborative activities jointly identified by the Population Programme Service and the Forest Resources Assessment Programme, funded by the former and conducted by Rudi Drigo (FAO 1998).
3. The 'Legal Amazon' comprises nine federated States, some of which (Amazonas, Para) are almost three times the size of France.
4. This section is largely based on FAO (1993).
5. Source for the diagram and comments: FAO (1996). Annex 2 presents the three respective diagrams, with comments, for the major developing regions, namely Africa, Asia and Latin America.
6. This section is based on FAO (1996) and Marcoux (1995).
7. Forest clearing for pastures is comparatively a minor factor on a global scale, but it is important in certain countries. It is driven by demand for animal products rather than by population growth, but its intrinsic impact (say by consumer concerned, or by calorie produced) appears to be much greater than that of other possible uses of cleared land. Section 2.3 illustrates this issue.
FAO. 1995. Forest resources assessment 1990 - Global synthesis. Forestry Paper 124. Rome.
FAO. 1996. Forest resources assessment 1990 - Survey of tropical forest cover and study of change processes. Forestry Paper 130. Rome.
FAO. 1998. Population in deforestation assessment. Development of demographic data at sub-state level and study of relation between population and deforestation in Brazil. Final report.
Marcoux, Alain. 1995. Population and the environment: a review of issues and concepts for population programme staff - II. Population and land degradation. FAO.
United Nations. 1992. Agenda 21 - The United Nations Programme of Action from Rio. New York.