Land Use, Land-Use Change and Forestry

Other reports in this collection Approaches for determining baselines

Most projects to date have adopted a two-step approach to determine baselines. First, the likely fate of terrestrial ecosystems within the project boundary is predicted. Second, changes in carbon stocks that would occur as a result of this scenario are estimated.

Specification of the without-project scenario for the project area usually have been based on projections of past trends of land use into the future. These predictions have taken into consideration events that are expected to alter current behavior (changes in legislation related to land use and tenure, changes in market preferences or prices, changes in environmental awareness, etc.). Even a thoroughly investigated without-project baseline, however, is prone to the risk that unexpected social or policy changes will confound predictions over the longer time frame. For example, the baseline for a reduced-impact logging project could change radically if national policy dictated adoption of this practice in all forest concessions. Key factors used in projecting the baselines have included planned land-use decisions of landowners/stakeholders, designation of land by national authorities, and historical patterns of land-use change in the local area.

Different approaches likely would be required, however, for different types of projects operating in different circumstances:

  • Afforestation projects might use simple models that predict zero uptake/emissions without intervention.
  • Projects to conserve forests used by small farmers are likely to need models that reflect local demands for agricultural land, firewood, and timber.
  • Projects aiming to reduce emissions through better forest management may need models that compare technological alternatives.

Different approaches for data collection have been used, including compilations of national/regional statistics, satellite imagery, and interviews with relevant authorities and key stakeholders. There is debate about the level of detail required and the weight given to different criteria (historical trends, available technology, population pressure, etc.) (Busch et al., 1999).

Several approaches have been proposed and/or used during the AIJ Pilot Phase for deciding how to carry out baseline projections. These approaches vary with regard to data requirements and treatment:

  • Simple, logical arguments do not use quantitative methods for predicting changes in current trends (or use simple ones). For example: "Without intervention, the forest concerned will be sold for agricultural development" [Rio Bravo project (Programme for Belize, 1997a)] or "without intervention, loss of aboveground carbon stocks within the area will continue at approximately 1.5 percent per year" [Scolel Té pilot project (Tipper et al., 1998); see also Box 5-2]. Variations of this approach have been used by most projects during the AIJ Pilot Phase [e.g., the NKCAP in Bolivia (Brown et al., 2000); the RIL project in Sabah, Malaysia (Pinard and Putz, 1997); the PAP in Costa Rica (SGS, 1998)].
  • Spatial or social-economic models simulate land-use change processes on the basis of factors such as proximity of towns, roads, and agricultural frontiers; population growth; food requirements; and the productivity of local agricultural technology [e.g., LUCS model (Faeth et al., 1994); Ludeke, 1990; Jepma, 1995). This approach is being used in The Nature Conservancy's project in Guaraqueçaba, Brazil (Brown et al., 1999a,b).
  • Econometric models use an econometric treatment to data factors such as historical series of productivity, price, costs, and so forth. This approach has not been used in the AIJ Pilot Phase, but it has been discussed in a few publications (e.g., Chomitz, 1998).

Simple, logical arguments are not necessarily less accurate in terms of predictive ability. Their applicability will probably be limited, however, to specific areas and contexts. Increasing model complexity is likely to be required to attempt credible predictions across a range of land uses. Such models, however, generally require large amounts of input data and may still be poor predictors of specific local changes. Requirements for complex baseline models could represent a serious barrier to small-scale projects or initiatives in poorer countries unless "umbrella" approaches are adopted (Bass et al., 2000). Procedures for selection or approval of models and a program for model testing and improvement to ensure some degree of consistency and quality would have to be considered.

Box 5-2. Historical and Projected Carbon Storage in an Area of ~300,000 ha in the Highlands of Chiapas, Mexico, based on a Series of Multi-Spectral Scanner (MSS) Images
A series of satellite images, from 1974 to 1996, was used to estimate changes in land use between 12 categories of vegetation/land use for an area of approximately 300,000 ha in the highlands of Chiapas. Measurements of the biomass of each vegetation type were then used to derive an estimate of the change in carbon stocks. Extrapolation of the historical changes of carbon stocks into the future can be used as a basis for without-project baselines. Because the rate of land-use change varied considerably over the 1974 to 1996 period, however, so did the baseline rate of carbon loss over the time period chosen as the reference. The spatial frame of reference used to derive estimates of land-use change is also important. Deforestation activity is often concentrated in particular areas (e.g., along roads and river valleys). The historical rate of change may therefore vary considerably according to the geographical coordinates of the reference area.

Once a baseline scenario for land-use and ecosystem changes has been developed, changes in carbon stocks associated with this scenario must be estimated. Different approaches have been used or proposed during the AIJ Pilot Phase (see examples in Table 5-4), including the following:

  • Quantification of carbon in proxy areas [e.g., the NKCAP (Brown et al., 2000)]
  • Control plots where project activities are not applied, which are set aside for measurement of carbon stocks in the absence of the project intervention [e.g., the RIL project in Sabah, Malaysia (Pinard and Putz, 1997)]
  • Modeling [e.g., the PAP in Costa Rica (SGS, 1998)]
  • Combinations of the foregoing approaches.

Other reports in this collection

IPCC Homepage