Measuring and monitoring forest degradation for REDD : Implications of country circumstances

Forest degradation is a major source of greenhouse gas emissions. In the Brazilian Amazon it is responsible for 20 per cent of total emissions (Asner et al. 2005). In Indonesia, the forest stock is decreasing by a rate of six per cent a year, only one-third of which is due to deforestation (Marklund and Schoene 2006). In Africa, the annual rate of degradation is almost 50 per cent of the deforestation rate (Lambin et al. 2003). In 2007, the Conference of the Parties (COP 13) to the United Nations Framework Convention on Climate Change (UNFCCC) acknowledged the importance of degradation and included it in the proposed mechanism for reducing emissions from deforestation and forest degradation (REDD). Addressing degradation has other important benefits, since it reduces the forest’s capacity to adapt to climate change and their ability to provide ecosystem and livelihood services.

Including forest degradation (along with • deforestation) in a REDD agreement will make it more e ective in accounting for carbon emissions and more equitable by encouraging additional countries to participate.
Degradation should be viewed as a di erent • process from deforestation with di erent actors and drivers.
Changes in carbon stocks from forest • degradation can be monitored using the 'stockdi erence' and 'gain-loss' methods.The choice of method will depend largely on countries' data availability and capacity.
The stock-di erence method allows local • communities and forest users to monitor the carbon stock changes of their own forest activities; the gain-loss method is primarily intended to use secondary data already available at national level.
The inclusion of degradation in a REDD • agreement should permit exibility in the development and application of methodologies, allowing countries to build on their existing capacities and circumstances.

Implications of country circumstances
Daniel Murdiyarso, Margaret Skutsch, Manuel Guariguata, Markku Kanninen Cecilia Luttrell, Pita Verweij and Osvaldo Stella Why include degradation in a REDD agreement?
Forest degradation is a major source of greenhouse gas emissions.In the Brazilian Amazon it is responsible for 20 per cent of total emissions (Asner et al. 2005).
In Indonesia, the forest stock is decreasing by a rate of six per cent a year, only one-third of which is due to deforestation (Marklund and Schoene 2006).In Africa, the annual rate of degradation is almost 50 per cent of the deforestation rate (Lambin et al. 2003).
In 2007, the Conference of the Parties (COP 13) to the United Nations Framework Convention on Climate Change (UNFCCC) acknowledged the importance of degradation and included it in the proposed mechanism for reducing emissions from deforestation and forest degradation (REDD).Addressing degradation has other important benefits, since it reduces the forest's capacity to adapt to climate change and their ability to provide ecosystem and livelihood services.
Forest degradation often has different driving forces than deforestation, and degradation is not necessarily a precursor to deforestation.Forests can remain degraded for a long time, never becoming totally deforested.So addressing deforestation does not automatically reduce rates of degradation.Failing to include degradation in a REDD agreement could leave considerable amounts of forest-based emissions unaccounted for.For example, a healthy primary forest (e.g. with a crown cover of 70 per cent) could be degraded to 15 per cent of crown cover and still be classified as 'forest' without any accounting for increased emissions.This brief focuses on the implications of the methods used to specifically measure and monitor forest degradation and discusses them in terms of costefficiency, effectiveness in emission accounting, and international equity issues that arise from differing country circumstances.

De nition and causes of forest degradation
As Apart from selective logging, little analysis has been made of the impacts of these processes on the loss of forest biomass and the time needed for regrowth.Further, almost all studies have focused on humid tropical forests.However, degradation of dry forests by extraction of fuelwood is often more pronounced than by commercial timber harvesting (Skutsch and Trines 2008), and this is important since dry forests are generally more heavily populated than rainforest.While the carbon content of dry forests is much lower than that of humid forests, dry forests account for 42 per cent of the tropical forest area (Murphy and Lugo 1986).

Methods for estimating emissions from forest degradation
The IPCC (2003b) defines five carbon pools to be monitored for deforestation and degradation: aboveground biomass, below-ground biomass, litter, dead wood and soil organic carbon.The most practical method is to monitor only above-ground biomass.
However, degradation processes such as logging and fires can significantly influence other carbon pools such as dead wood and litter.
The IPCC (2003b) also provides three tiers for estimating emissions, with increasing levels of data requirements and analytical complexity and therefore increasing accuracy: with high-resolution optical imagery, it is hard to detect under-canopy changes: advanced methods such as radar, which do have this potential, are only applicable in small areas.
One possible way of dealing with this problem is to use a probabilistic approach.This involves stratifying forest by risk of degradation, based on observation of past trends and related to proxy variables such as accessibility (e.g., density of road networks, distance from settlements) (Schelhas and Sanchez-Azofeifa 2006).The parameters in this kind of modelling would be different for different types of degradation processes (e.g., selective logging, fuelwood collection) (Iskandar et al. 2006).
Changes in average carbon stocks per unit area per forest type can be monitored using various methods, including secondary datasets and estimations from IPCC (2003b), as well as in situ forest inventories and sampling using permanent plots.To measure changes in carbon stocks for degradation, IPCC ( 2006) recommends two options: the stock-difference method and the gain-loss method (see Figure 1).
The stock-difference method builds on traditional forest inventories to estimate sequestration or emissions.The gain-loss method is built upon an ecological understanding of how forests grow and upon information on natural or anthropogenic processes producing carbon losses.With the stock-difference method, carbon stocks in each carbon pool are estimated by measuring the actual stock of biomass at the beginning and end of the accounting period.With the gain-loss method, biomass gains are estimated on the basis of typical growth rates in terms of mean annual increment (MAI) minus biomass losses estimated from activities such as timber harvesting, logging damage, fuelwood collection and overgrazing as well as from fire.
If the forest is stratified into areas subject to different degradation processes, and these are well understood, it may be possible to estimate with some accuracy the quantity of wood products extracted in a given period.
Table 1 compares the stock-difference method with the gain-loss method, both of which could be used for degradation assessment using IPCC Tiers 2 and 3.The choice of method will depend largely on the availability of data and resources to collect additional data (GOFC-GOLD 2008).Countries experiencing significant forest degradation may want to develop national and local databases and models to estimate the impact of these changes on different carbon pools in order to use the gain-loss method.Estimates by Hardcastle and Baird (2008) suggest that adding degradation to the cost of Tier 3 reporting only increases the set-up costs by 10 per cent for Democratic Republic of Congo, 11 per cent for Indonesia and 13 per cent for Brazil, with similar percentage increases in recurrent costs.However, these calculations assume that the country is already reporting at Tier 3 and will therefore have a robust sample system (covering a minimum of three per cent of land surface and six strata) in place.
Figure 1.Estimating emissions from forest degradation: comparing the stock-di erence and gain-loss methods

Stock-di erence
The di erence between carbon stocks gives carbon emissions

Gain-loss
Carbon emissions are calculated from gain minus loss

Implications of country circumstances
The cost of measuring and monitoring degradation depends on country circumstances, which include factors such as: The extent of forest cover.

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The level of forest stratification (for example, • Democratic Republic of Congo has only one major forest type whereas Indonesia and Mexico have four or more forest eco-types).
The tier of carbon accounting applied.

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Countries are also at different points on the forest transition curve (Figure 2), reflecting the dynamics of agriculture and forest rents over time (Angelsen, 2007).As a result, degradation is a more critical issue in some countries than others.For example, some have halted deforestation, but may be losing biomass in the remaining forests.Thus the location of a country on the forest transition curve will influence its motivation for investing in degradation accounting and the suitability of the measurement and monitoring option.
Forest transition theory suggests four categories of countries: 1. Countries and regions with low deforestation and high forest cover such as the Congo Basin and Guyana.Here, forests are relatively undisturbed, but increasing deforestation and degradation may occur in the future.These countries are likely to have the most interest in accounting for degradation because they are less likely to benefit from 'avoiding

Large-scale forest res
Reference data from undisturbed forest can be used for the pre-• re situation, but forest inventory would be needed to measure post-re biomass.
Losses due to re can be estimated from • the area burned and emission factors used to estimate the emissions based on the biomass lost.

Harvesting of fuelwood and nontimber forest products
Pre-harvesting biomass levels could be estimated from typical • levels in undisturbed forest, but in practice much of the forest subject to these uses will already be partially degraded at the start of the accounting period.
In areas already under individual or community management, • pre-and post period forest inventories can be carried out by forest users.
Data on losses e.g., registers of commercial • wood-based products, estimates of fuel wood use) may be available.Fuel wood o -take could also be calculated

Conclusions
The definition and MRV of degradation are more complex for degradation than for deforestation (IPCC 2003a) and require more proxy factors.The IPCC provides useful guidance through the stock-difference and gain-loss methodologies (IPCC 2006) and the use of tiers (IPCC 2003b).Where data is limited, the MRV of forest degradation could start with simple methods with default values (Tier 1) and proxies to account for emissions from different degradation activities.The uncertainties related to using simpler approaches require 'discounting' of credits, and this would provide a direct incentive to countries to upgrade their measuring and monitoring methods.
Overcoming the methodological challenges in this way enables forest degradation to be realistically included in a REDD agreement, thus making REDD more effective by accounting for a wider range of forest greenhouse gas emissions.It also increases the international equity of the REDD mechanism by encouraging participation by a wider range of countries, many of them in Africa.
It is therefore important that decisions about the details of the MRV framework for degradation allow for a diversity of circumstances through permitting flexibility in designing, developing and applying methodologies.

Table 1 .
Comparison of stock-di erence and gain-loss methods for estimating emissions from di erent types of degradation Angelsen, 2007)f forest transition (adapted from:Angelsen, 2007)