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Forest Definition [MGD Sections]

Carbon Pools [MGD Sections]   Activity data x emission/removal factor frameworks Previous topic Parent topic Child topic Next topic

In general activity data x emission/removal factor methods(1) are more suitable in landscapes with few sequential changes through time. As the number of potential changes and classes increases, the efficiency of using this approach decreases and the potential for bias increases. The cost of developing numerous EFs can eventually become greater than the cost of developing a Tier 3 system to account for the many factors affecting emissions and removals such as disturbance type, disturbance intensity, other management actions and site and climate conditions. Emission/removal factor based systems are challenged by repeated transitions between land-use categories. By default the IPCC guidelines assume a 20-year transition period but if subsequent land-use changes occur within this period, the emission/removal factor based systems typically do not have appropriate emission/removal factors to accommodate multiple transitions. The IPCC does not provide explicit guidance on how to apply emission/removal factors when there are multiple changes within the transition period. Though logically if a linearized 20 year transition to a known after-change carbon density(2) is interrupted, and a new land use or management regime established with a new after-change carbon density, the emissions and removals from the land in question could be calculated by keeping track of the land in question, and using an emission/removal factor equal to the difference between the partially completed carbon density change, and the new after change carbon density, annualized over 20 years. This is an example of a rule referred to in Box 5. A more sophisticated approach would replace the linearized change with an exponential transition with empirically established time constants for carbon loss or gain.
In countries where there are multiple clearing and regrowth cycles (shifting agriculture being an example) it will be necessary to not only estimate emissions from the initial clearing, but to also estimate the removal and subsequent future emissions during repeated cycles of clearing and regrowth. Unless a manageable number of statistically representative strata can be identified, representing such patterns of growth rates can become complex, especially where there are other factors involved such as multiple forest types and types of disturbance (i.e. commercial timber harvest or shifting cultivation). Complex patterns of degradation or other multiple changes on single units of land, such as degradation prior to deforestation, can also be difficult to account for using simpler tools due to the sheer number of possible permutations. The complexity increases as more strata and disturbance types need to be included. Even if applying Tier 1 or 2 approaches it may be worth using the more advanced, fully integrated tools to manage the large number of transitions and resulting combination of stock changes.

These method are referred to as Tier 1 and Tier 2 methods
For example in the case of mineral soils use calculated by use of reference carbon density under native vegetation and application of the relative carbon stock change management factors.