To date, two approaches have been used and proposed to monitor leakage. One approach involves determining the appropriate spatial area in which to monitor project effects; the other involves identifying key indicators of leakage on the basis of demand that drives land-use change and management.
Monitoring by Area: Leakage may be monitored by expanding the project's boundary. The monitoring area may be larger than the area on which project activities are implemented (Brown, 1997; Trexler and Associates, 1998). Potential monitoring boundaries for leakage are at the project level, the local/regional level, or the global level:
Monitoring by Key Indicators: Alternately, it has been proposed that leakage be monitored by determining key indicators for demand that drives land-use patterns or management that leads to carbon emissions (such as demand for timber, fuelwood, or agricultural land) (Brown et al., 1997). The key indicator is the output of the product demanded. A project that reduces output or access to resources without offering alternatives is likely to result in leakage because people within the project area will move elsewhere to find other sources of resource supply. A review at the project level has suggested that leakage indicators can be developed by determining whether the project has displaced activities that lead to carbon emissions, rather than replacing or substituting for them (Brown et al., 1997). For example, to monitor leakage potential for a project that seeks to replace conventional logging with reduced-impact logging, timber output would be the key indicator to be monitored. If timber output from the project area decreases while prices and demand for wood products remain the same, the project could have leakage. The assumption would be that additional areas would be logged to compensate for the timber loss (Brown et al., 1997). Under this method, it would be unnecessary to track global markets or the harvest intensity of nearby timber concessions; instead, the key indicator of output would be used to monitor the leakage potential. Similarly where demand for agricultural land is driving land-use change: If conversion of forest to agricultural land is halted but agricultural productivity is not increased on existing lands, the project is likely to result in leakage.
Several projects have developed leakage indicators. In the Noel Kempff Mercado project, for example, the government of Bolivia used carbon mitigation funds to compensate forest concessionaires for giving up logging rights on government-owned forest lands and expand the park boundaries (Box 5-3). A legally binding "leakage agreement" was signed by the logging companies, obliging them not to invest the funds they received in logging elsewhere. The key indicators are the use of received carbon funds and the harvesting rates in the concessions. The concessionaires will be monitored to ensure that they do not increase production elsewhere because of the project funding (Brown et al., 2000).
Box 5-3. Carbon Inventorying and Monitoring of the Noel Kempff Climate Action Project (NKCAP), Department of Santa Cruz, Bolivia
The project area of approximately 634,000 ha is located within the newly expanded western region of the Noel Kempff Mercado National Park. Prior to the initiation of the NKCAP, much of the forest in the expansion area had been high-graded over a period of about 15 years. In addition to logging, this area was also under pressure for conversion to agriculture (for further details, see Brown et al., 2000). The forests in the expansion area were divided into six strata for sampling: tall evergreen, liana, tall inundated, short inundated, mixed liana, and burned forest.
The project design for inventorying and monitoring the carbon pools in the with-project case is based on the methodology and protocols in MacDicken (1997a). The carbon inventory of the area was based on data collected from a network of 625 permanent plots; the number of plots sampled in a given strata was based on the variance of an initial sample of plots in each strata and the desired precision level (±10 percent) with 95-percent confidence. A fixed-area, nested-plot design was used, and carbon stocks were measured or calculated for each of the following pools in each plot: all trees with diameter at breast height >5 cm, understory, fine litter standing stock, standing dead wood, and soil to 30-cm depth. Root biomass was estimated from root-to-shoot ratios given in Cairns et al. (1997). The total amount of carbon in the park expansion area was about 115 million t C, most of which was in aboveground biomass of trees (60 percent), followed by soil to 30-cm depth (18 percent), roots (12 percent), and dead wood (7 percent); the understory and fine litter accounted for about 3 percent of the total. The 95-percent confidence interval of the total carbon stock was ±4 percent, based on sampling error only; regression and measurement error were not included.
The carbon benefits from this activity result from halting the removal of commercial timber and eliminating damage to the residual stand. Estimates of changes in major carbon pools from logging and projections of timber extraction if logging had been allowed to continue over the project life were assessed to generate the without-project baseline. The main carbon pools considered in this activity are aboveground tree biomass, dead biomass, and wood products. Bolivia recently enacted a new forestry law and developed new regulations for forest harvesting. This information is used to predict how much forest area in the project area would have been harvested in a given year for each year over the length of the project. From data provided by logging concessionaires, and analysis of concessionaire management plans in areas nearby, the likely quantity of wood (in cubic meters per hectare) extracted per year is also estimated.
The change in carbon stocks from logging activities is measured in a nearby proxy forest concession. Permanent plots are established to measure the amount of dead biomass produced during the felling of a tree and associated activities, as well as the rate of regrowth after harvesting. Dead biomass results from the crown and stump of the felled timber tree and damage to other trees. Total production of dead biomass carbon per unit of harvested biomass carbon is determined from these plots.
C benefits from averted logging = Dlive biomass C + Ddead biomass C + Dwood product C
where D is the difference in carbon stocks between the with- and the without-project case. The annual benefits are calculated from a carbon accounting model that tracks all of the changes in these pools from a scenario that is based on the annual area logged, log extraction rates, and logging damage.
Dlive biomass C = (biomass C from logging damage + C in timber extracted) x growth factor
To estimate the change in live biomass, one could measure the live biomass in the proxy concession before an area was logged and then again after it was logged; the difference would give the change in the live biomass C. One main problem with this approach, however, is that two large carbon stocks are being subtracted; although the error on each stock could be small, the error on the difference, expressed as a percentage, will be much larger. To overcome this problem, the change in live biomass was measured directly. The change in live biomass between the with- and without-project cases is a result of the extraction of timber and damage to residual trees from logging activities (the quantity in parentheses). The quantity in parentheses, expressed on an area basis, multiplied by the area logged per year gives the total change in live biomass without adjustment for logging effects on the growth of the residual stand (the growth factor). It is not clear if harvesting stimulates or reduces regrowth in recently logged areas. The logging of large trees and damage to residual trees may be enough to actually reduce net biomass growth of the stand per unit area for several years after logging rather than stimulate it. For projects that prevent or modify logging, this effect of logging on the growth of the residual trees must be determined. Monitoring of paired permanent plots in logged and unlogged areas of the proxy concession is under way to establish the sign and magnitude of the growth factor over the length of the project.
Ddead biomass C = (dead biomass from logging damage x decomposition factor)
In projects that are related to preventing or reducing logging, dead wood cannot be ignored because it is a long-lived pool, and logging increases the size of this pool. Thus, stopping logging has the effect of reducing the dead biomass carbon stock, and the dead biomass carbon in the with-project case is less than in the without-project case. The change in the dead biomass pool has to be corrected for decomposition, however. Estimates of the decomposition correction factor are taken from the literature (Delaney et al., 1998), but field measurements are under way to improve this factor.
Dwood products C = (timber extracted x proportion converted to long-lived products)
Stopping logging reduces the long-term wood product pool because the input of new products is reduced; thus, the change in the wood products pool is negative. The harvested timber in the Santa Cruz area is from a small number of speciality tree species; a reduction in their supply may not be supplied from elsewhere. In the NKCAP, the proportion of harvested roundwood that goes into long-term wood products was obtained from literature sources for Brazil (Winjum et al., 1998). The project assumed that wood waste generated at each stage of the conversion of timber to products (50 percent was converted to sawdust in the first milling stage) was oxidized in the year of harvest.
The difference between the with- and the without-project case is that the with-project case has more carbon in the live biomass pool and less carbon in the dead biomass and wood product pools than the without-project case.
Averted Conversion to Agriculture
The carbon benefits from this activity result from the elimination of carbon loss in forest biomass and soil. The without-project baseline for this component was established by using projected human demographics in areas adjacent to the project area. The two factors affecting conversion of forestlands to agriculture in the area surrounding the NKCAP are increasing human populations and the resulting demand for farmland. In constructing the deforestation scenario, it was assumed that migration into the area will fuel continued demand for agricultural land, as in other areas nearby the NKCAP.
C benefits from averted forest conversion = Dtotal biomass C + Dsoil C
Carbon loss from a change in biomass is calculated as the product of the projected area cleared and the difference between carbon in forest biomass (the sum of trees, understory, litter, dead wood, and roots) and agriculture crop biomass. Changes in soil carbon are estimated as the product of area cleared, weighted average forest soil carbon, and an average soil oxidation rate for converted tropical forest soils obtained from Detwiler (1986).
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