This document discusses a VCS REDD methodology for mosaic deforestation areas that involves participatory biomass inventories and community-based monitoring. Key points include: the methodology's applicability criteria around drivers and project actions; how the baseline is established using historical remote sensing and land use modeling; accuracy discounting and inclusion of degradation; ex-ante credit estimation; and addressing leakage and implementing community-based monitoring with strict QA/QC.

1. a VCS Mosaic REDD Methodology
and Participatory Biomass
Inventories
Steven De Gryze
Leslie Durschinger

2. Acknowledgements
• Forestry Administration, Cambodia
• Community Forestry International
• PACT Cambodia
• Clinton Climate Initiative
• Technical Working Group on Forests and the
Environment, Cambodia
• Children’s Development Association, Cambodia
• Buddhist Monk’s Association, Oddar Meanchey,
Cambodia
• Communities of Oddar Meanchey Province, Cambodia
• MacArthur Foundation
• DANIDA, Denmark
• Clinton Climate Initiative, USA

3. Applicability of VCS methodology
• Main applicability criteria
– Mosaic deforestation, defined using
• Minimal population density
• Minimal road network
• Minimal historical deforestation rate
– Data must be available on historical
deforestation/forest degradation
– Allowable drivers and project actions are defined
– No commercial timber logging before or after project
starts
• Allows the exclusion of long-lived wood products
• Logging for domestic is still allowed
• Illegal logging may have occurred in the baseline
– Agricultural intensification only on land that is already
under agriculture

4. Main Drivers and Actions
Project Actions
Strengthening Sustainable Forest Fuel-efficient Agricultural Assisted
land-tenure forest use protection woodstoves intensification Natural
plans Regeneration
Fuel-wood ✔ ✔ ✔
collection
Forest fires ✔
Crop-land ✔ ✔ ✔ ✔
conversion
Settlement ✔ ✔ ✔
conversion
Drivers
Illegal logging ✔ ✔
Logging of ✔ ✔
timber for
domestic use

5. Baseline
• Baseline is based on combination of historical
remote sensing analysis (fixed number of images
and intervals) and a land-use change model
• Includes deforestation/reforestation as well as
degradation/regeneration
• Historical rates determined
in a reference region Size of the Minimal Size of the
Project Area Reference Region
< 25,000 20 ×
25,000 – 50,000 10 ×
50,000 – 100,000 5×
• Similarity Test > 100,000 2×
– Same drivers of deforestation are present
– Similar landscape features (slope, aspect, etc.)
– Similar land-tenure and land policies

6. Accuracy Discounting and Inclusion of
Degradation
• Credits are discounted according to lower
confidence interval (alpha=5%)
• Credits from deforestation, forest degradation
and assisted natural regeneration have different
accuracy, and therefore different discounting
• Including forest degradation is optional and may
be included after project start
– Forest degradation must be detected with a minimal
accuracy
– Initial income from carbon can be used to purchase
the necessary high-resolution imagery

7. Ex-ante Credit Estimation
Relative importance Effectiveness of Annual rate of
of drivers project activities project activities
Annual rate for activity 5: Fuel-efficient
Stoves
100%
80%
60%
40%
20%
0%
1
2
3
4
5
6
7
8
9
10
12
13
14
15
16
17
18
19
20
22
23
24
25
26
27
28
29
30
11
21
Project Year
No Reduction in
Def orestation/degradation 100%
Compared to Baseline Rates
90%
Predicted
80%
70%
Deforestation Rates
under Project
Relative Reduction in
Def orestation Rates
60%
50%
40% Scenario
30%
20%
10%
Complete Elimination of
Def orestation/Degradation 0%
2008
2009
2010
2011
2012
2013
2014
2015
2016
2017
2018
2019
2020
2021
2022
2023
2024
2025
2026
2027
2028
2029
2030
2031
2032
2033
2034
2035
2036
Year

8. Leakage
• Leakage divided into
– Activity-shifting within leakage belts (monitored)
– Activity shifting outside of leakage belts (ex-ante factor)
– Market leakage (ex-ante factor)

9. Community-Based Monitoring
• Goals
– Provides employment and education/training to
local communities
– Reinforces integration of communities with the
carbon project
– Theoretically more cost-effective, dependent on
accuracy
• Strict QA/QC is required
– Training
– Re-measurement of 20% of the plots
– Re-visiting of 100% of the plots to check
GPS location
– Requirement to take pictures of GPS device
– Spot-check of 1-2 plots of every crew by
professional team