The Problem: Inability of forest communities to measure and monitor forest carbon stock changes and obtain funds under the Reduced Emissions from Deforestation and Forest Degradation in Developing Countries (REDD) mechanism
The solution: Empower forest communities to measure changing forest stock using standard forest inventory methods and mapping techniques based on handheld Information and Communications Technologies (ICT) tools and applications
Project description:
The objective of the project was to empower forest communities to measure changing forest stock using standard forest inventory methods and mapping techniques based on handheld Information and Communications Technologies (ICT) tools and applications and use the monitorable results to seek funds under the REDD mechanism. The project was carried out in 34 sites in six countries (India, Nepal, Tanzania, Senegal, Mali, and Guinea Bissau), of which 28 were under community management and the remaining 6 were control sites (which had similar forest in the vicinity of the project villages but not part of the CFM area). The control sites were measured in exactly the same way as the project sites, with the aim of estimating the ´business-as-usual´ degradation rate in the absence of forest management, since no such data were available from the managed sites themselves before they were taken into management. In selecting the 28 sites sites with the risk of leakage were avoided (i.e. the possibility that activities such as firewood or poles harvesting, formerly causing degradation in the now-managed areas, have simply shifted to what was selected as control areas). Data were collected at most sites for four or five years, though in some cases for only three years during the period 2004 through 2009.
IT tools and applications used:
A hand held computer linked to a GPS was programmed with a standard GIS program (ArcPad), and a georeferenced base map or satellite image (O.S. or similar) was uploaded.
The process:
The process consisted of the following steps:
1. Boundary mapping. Since many forest areas managed by communities are not marked on maps, but simply set out on the ground with fences or painted stones, their areas are not accurately recorded and their boundaries are not geo-referenced. These are essential if carbon credits are to be issued.
How this was done by community members?
A team of villagers from the community were trained (one day) in the basic use of the hand held computer. Boundary mapping was carried out by walking around the edge of the forest area with the hand-held computer with map and GPS function on, with contact with the satellites maintained. The trajectory of the walk appears on the map as one moves (in cases where dense forest interferes with reception, a separate GPS was found to work better). At points of interest along the route, including corners, the screen is clicked with a stylus, and notes were recorded. When the circuit is completed, the boundaries were fixed on the map and geo-referenced, and the area was automatically calculated.
2. Identifying strata. Most community forests are heterogeneous and need to be stratified for the purposes of carbon counting. The team walks through the forest and identifies areas which are clearly of different types, on the basis of: dominant tree species, stocking density, age, and aspect (slopes, orientation). Similarly, areas with different types of community management are also identified and located. The boundaries of the strata are added to the base map using the same technique (walking the boundaries of each stratum).
3. Pilot survey for variance estimation was carried out to determine the number of permanent sample plots required. Several circular pilot plots (their size will depend on density of forest) are set out in each stratum and the first training on how to do the biomass inventory is carried out on these plot. The team is first taught how to mark the central point and lay out the sampling circle; data are then collected from each sample plot on the dbh (‘diameter at breast height’), and in some cases height, of all trees over 5cm dbh, are either recorded in a notebook or entered directly into the PDA using a tailor-made database. Each tree is identified by species name, using local terminology. Quadrants may be used for the shrub and herb layers and for litter. This inventory protocol follows standard procedures in basic forestry practice as presented e.g. in the Winrock field manual (MacDicken, 1997) and as recommended in the IPCC Good Practice Guidance (IPCC 2003), and the exercise took about 2-3 days. Local suitable allometric equations, ideally species specific, are required to convert dbh (and height) variables into biomass mass estimates. For each stratum the variance in biomass in each of the carbon pools (trees, shrubs and herbs, litter) is calculated and from this, the sample size needed to achieve a maximum of 10% error in the estimate of the mean, using standard statistical equations.
4. Permanent plots laid out: Once the number of plots required in each stratum was known, the central points were marked in the field, and their locations marked on the computer base map using parallel transects running across the area to spread the plots as evenly as possible over the stratum. The starting point of the first transect is established at a random point on the boundary so that the sample is random. This work was done by the supporting NGO with the help of the village team.
5. Re-finding the permanent plots and measuring biomass in each of them. The village team carried out this work, once per year, with some supervision from the NGO for the first samples. The locations of the plots were found using the hand-held computer with GPS (this brought the team within a few meters of the plot; the centre could be found visually from the marker). The biomass inventory is carried out as described in Step 3. Data were recorded either in a notebook (and then transcribed into the database by the NGO), or directly into the PDA in the field, depending on how well the village team could work with the equipment. A drop down menu opens for each entry, with multiple choice for data such as species and condition, while numeric data are entered using the keyboard. Most community teams found no difficulty in using the PDA in this way. The database is set up such that every tree is recorded separately in a file for each plot, and all the plots in one stratum are held in one file. Allometric equations are linked to the database for each species to facilitate calculations, and statistical manipulations (means, standard deviations, confidence interval) are pre-programmed.
6. Weight of shrubs and herbs, and litter layers. The samples taken from the quadrants are dried and weighed to estimate the total weight over the whole plot site.
7. Estimating below ground carbon. Carbon in tree roots is estimated using a locally appropriate expansion factor. The reliability of the carbon estimates made by communities was tested by hiring independent professional foresters to re-survey three of the sites used in this project. (one each in India, Nepal and Tanzania). The results of these inventories were found to be within 5% of the communities´ estimates in every case.
Costs:
The cost of the local inventory carried out by the community was between 50% and 30% of the cost of the professional survey. The costs include: the time for the community members involved (about $2 per day), the time and expenses of the NGO during training and supervision, and a proportional share of the costs of the equipment and software (based on expected lifetime and the sharing of PDAs by a number of communities. Economies of scale play a considerable role in the costs of the community-based inventory. Depending on the growth conditions (wetter versus drier sites); the project team estimated the cost per ton of CO2 between $0.33 and $0.2 in a large forest unit (500ha) and between $0.83 and $0.45 in a small forest unit (50ha).
3. Results: Degradation and forest enhancement under CFM . In 24 of the 28 managed sites, there were steady gains in biomass over the years in which they were measured. In the remaining 4, not degradation, but deforestation was the reason for losses: parts of the forest area were encroached and cleared, usually by actors from outside the community. The community was apparently not in a position to prevent this. In each of these cases the ´attack´ occurred only in one year, causing a drop in the total biomass, after which steady growth resumed. The observed increases in biomass are net increases after the off-take by the communities of allowed quotas of forest products such as firewood, fodder and poles, since these forests are managed on the basis that sustainable off-take of such products is permitted. The estimates of degradation avoided are based on the losses in biomass measured in the control sites. Biomass levels have been converted into tons of carbon dioxide equivalent. (See table 1).
| Observed increase in biomass (tons/ha/year), net of off-take of fuel wood and poles | Annual increase in CO2 stock (tons/ha) due to growth of stock | Estimated annual CO2 emissions saved (tons/ha) by preventing degradation | Total CO2 benefit tons/ha/year | |
| Dry forest and savanna woodlands | 0.8 – 3.0 | 1.5 – 5.5 | 1.5 – 3.5 | 3.0 -9.0 |
| Temperate woodlands and mountain forest | 3.0 – 6.5 | 5.5 – 11 | 1.5 – 3.5 | 7 – 14.5 |
The results indicate that in dry forests and savanna woodland, improved community management results in a CO2 benefit of between 3 and 9 tons per hectare per year and in temperate woodland and mountain forest, between 7 and 14.5 tons. One main observation is that the gains due to increased stock in the forest are in general higher than the gains due to avoiding degradation. This has serious implications for the way a reward system (payment for carbon credits) is set up. If only the reduced degradation is credited, as was first proposed under REDD, the community would ´earn´ on only a small part of the real carbon benefit. In order to provide a stronger incentive to communities, it would be advisable to credit also the increase in carbon stock (forest Enhancement).
Future plans:
Since the data was gathered in the six countries, new technological opportunities have been investigated with a view to simplify the work at the community level. FAO is working in Mexico on re-aligning the community stock assessment and monitoring of biomass carbon by using Google Earth and Cyber Tracker software, in place of expensive and complicated satellite imagery and GIS software (this is expected to result in considerable reductions in the cost estimates presented above). The method being developed involves downloading Google Earth2 images from the Web whenever possible, as source material for the forest maps. This is combined with new mapping software applications for forest and carbon, using the user-friendly interface and icons of Cyber Tracker.
Source: Content from FAO publication: Case Studies on Measuring and Assessing Forest Degradation. Community Measurement of Carbon Stock Change for REDD. FAO.2009.www.fao.org
For more information, contact: Margaret M. Skutsch, Michael K. McCall, Bhaskar Karky, E. Zahabu, Graciela A Peters-Guarin at FAO.
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