A degradation reference scenario on the other hand is much more difficult to establish because most degradation cannot be detected from remote sensing imagery. There is therefore no historical record of the spatial pattern of degradation (which areas are being degraded), and because of lack of forest inventory data in most developing countries, there is no detailed information on the rate at which carbon stock is being lost in the areas that are subject to degradation.
Degradation is caused by a variety of activities as shown in Table 1 in Sub-Section 2.2.1.
These include: selective logging; unsustainable rates of extraction of timber and non-timber products by local communities, mainly for their own use, with possibly some minor commercial benefit (sale of firewood or charcoal to cities); and slash and burn agriculture, of a nature which exceeds the natural regeneration capacity of the areas concerned. Also fire, in regions in which it is not a natural occurrence.
With no previous data on the intensities of these activities, it is possible to use one of the following techniques: advanced remote sensing techniques, harvesting estimates from the local people, harvesting estimates from stumps counts, default values (rule of thumb), modelling using estimated rate of off-take, or harvesting estimates from control sites. These techniques are shortly described below.
2.4.2.1 The use of advanced remote sensing techniques
As pointed out in Sub-Section 2.3.2 it is possible to use advanced high resolution imagery such as IKONOS to detect forest degradation. However, these new technologies are limited in their application due to the fact that the imageries are available only since 1999, and in developing countries, moreover, due to high costs and low human capacity. In the future however, these technologies might be readily available and therefore useful for forest degradation studies in developing countries.
2.4.2.2 The use of harvesting estimates from the local people
The processes responsible for degradation are strongly correlated with population dynamics.
At low levels of population density, neither off-take of forest and non-forest products, nor shifting cultivation in the forest will result in long term loss of carbon stock, as the forest can regenerate naturally. It is only when the population density per hectare of available forest rises that the effects will be seen. Given that the per capita volumes of extraction of forest and non-forest products, and the per capita areas taken for shifting cultivation have probably not changed over the last 20-25 years, it might be possible, for rural populations in forest areas, to make an estimate of the current per capita impact of these activities (in terms of tons forest carbon per capita per year), and using census data, back-cast to estimate absolute loss rates of carbon in the past, and project forwards given, a reasonable assumption about
future population growth. Using mean annual increment rates of forest, it might be possible to establish a reference scenario, although clearly it would be a rather rough estimate.
However such estimations of losses due to forest use by local people rest on the assumption that per capita extent of forest use and shifting cultivation have not changed over 20-25 years which is not the case for a country like Tanzania which has experienced a lot of macro-economic policy changes over this period7. Secondly this option requires the use of mean annual increment rates of forests which are in general not available. These shortfalls together with the fact that most of the activities that cause degradations are carried out illegally (see Sub-Section 2.2.1) means that it is very difficult to get utilization data from local people.
2.4.2.3 The use of harvesting estimates from stump counts
With no record of harvested wood it is also possible to estimate degradation by a count of stumps in a given forest. Luoga et al., 2002 was able to estimate wood volume of ‘newly’
harvested (stumps harvested within the last year) and ‘old’ harvested stumps (stumps harvested more than a year previously) for the miombo woodlands of eastern Tanzania. Such extraction rates can be modelled for the estimation of the degradation patterns. However, the procedure fall short in determining the actual time and purposes at which the trees were harvested, and moreover, it does not take into account lopping of branches. This makes it difficult to estimate the annual off-takes.
2.4.2.4 The use of default values and modelling
Default values are crude estimates based on broader generalization and expert judgements.
They are therefore not much accurate. Because of this inaccuracy, conservative lower end values of confidence limits are estimated to allow for the uncertainty. The use of default value therefore means less carbon benefits.
7 Since 1980’s, Tanzania has been implementing policy reforms such as Structural Adjustment Programme in order to attain macroeconomic balance by bringing national expenditure in line with national income. In order to realise this, the government has been controlling credit and has removed subsidies on food items and agricultural inputs; liberalised trade; and has reduced government expenditure by retrenching employees and by introducing cost sharing measures in the education and health sector. As a coupling mechanism most of the people who lost their jobs in towns went to rural areas and the result of this was increased forest extraction and expanded subsistence agriculture (Monela et al., 2001).
Modelling utilize default values, previous data or just one point measurements to predicts carbon stock changes over time. However, this requires a well elaborated study on the forest stand growth habit that can only be obtained from continuous monitoring from permanent sample plots. The use of default values estimated from expert judgement will always result to conservative estimates.
2.4.2.5 The use of harvesting estimates from control sites
Control sites are unmanaged forests with conditions similar to those of managed forests.
Permanent sample plots could be established in the control sites to determine the ‘business as usual’ scenario in which degradation could be captured. Countries that wish to access REDD funding will need to carry out periodic forest inventories in order to get detailed information on the rate at which carbon stock is being lost in the areas that are subject to degradation.
This should in fact be a major activity under the so-called ‘readiness’ mechanisms that are being proposed, e.g. by the World Bank under the new Forest Carbon Partnership Facility, as well as in demonstration activities for REDD that may be carried out between 2008 and 2012.
With such data, at any accounting time the difference between the carbon emissions or removals of the control site and the carbon emissions or removals of managed forests at the start of project represent the carbon benefit (Figure 3).
Figure 3. Reference scenario for avoidance of forest degradation.
Baseline (control site)
Starting stock
Emission avoidance
Start of the project (Year 0)
Time yrs
Forest biomass