Workshop on South‐South collaboration on REDD demonstration

1. Workshop South south
Cooperation for REDD activities
Manaus 16-19 mars 2009

2. Madagascar key facts
• One of the main source of green house gas
emissions is deforestation
• > 75% of the population of 18 million is rural and
dependent on the land and its natural resources
• Very high number of endemic species
• Unparalleled levels of endemism at the genus
Madagascar
and family levels:
Key facts • 25 endemic families;
• 209 plant genera; 6 families
• 34 bird genera; 5 families
• 15 mammal genera; 5 families

3. 2005
2000
1990
1950

4. National REDD process
• Climate change platform created
• REDD Committee in place
• R-Plan :REDD Readiness plan being established
• National Institution for national data and carbon
monitoring: ONE
• National methodology for monitoring
• Integrating SWAP process
• Linked with tripling surface of protected areas
• Integrating PES approach
• Reform of land tenure policy

5. What deforestation is
occurring in Madagascar?
Total area 59.2 (million ha)
Total natural forest (million ha)
1990 : 10.6
2000 : 9.7
2005 : 9.4
Rate of deforestation
40,000 hectares per year
(0.53% per year)

6. Madagascar’s experiences of forest
carbon
• The Mantadia corridor: Makira
– Ankeniheny-Zahamena Protected
Area (425,000 hectares)
– Mantadia reforestation area (3,020
hectares of habitat restoration) Ankeniheny-Zahamena
• Makira protected area (400,000
hectares)
• Fandriana-Vondrozo corridor Mantadia
(250,000 ha)
• REDD/FORECA project to develop
REDD methodology Fandriana Vondrozo
• Many small scale afforestation
initiatives

7. National baseline
approach
• National approach:
– 3 sites: biomass inventory,
methodology, socio-economic
studies to know factors, actors
and causes of deforestation and
degradation
– Moving towards national
approach
– National baseline
• Local approach
– 4 sites: biomass and socio-
economic studies
– Local baseline
REDD FORECA PROJECT
18.03.09
MADAGASCAR -

8. Sites 1. Haute Ramena: 42 000
ha, PCD, TGRN, Tavy
2. Manompana: 40 000 ha
3. Mariarano: 2000 ha,
PCD, TGRN, Tavy
4. Tsinjoarivo: 15 000 Ha,
PCD, TGRN, Tavy
5. Tapia Arivonimamo –
Ambatofinandrahana: 40
000ha, PCD, TGRN, Feux
6. Corridor Sud: 40 000 ha,
PCD, TGRN, forest inventory,
illegal logging
7. Tsimanampetsotsa: 43 200
ha, Protected Area, PCD,
REDD FORECA PROJECT
18.03.09
MADAGASCAR - TGRN 8

9. Pilot projects

12. 50% to communities for improved land stewardship
25% to forest management
15% to Ministry monitoring
5% to verification
5% to marketing

14. Ankeniheny Zahamena
Corridor Project
• One of the most important areas for
biodiversity in Madagascar with 40-50% of all
species in Madagascar
•At least three species are entirely limited to
the corridor
•The lowland forest contains the richest reptile
community in Africa, and many species of
plants from endemic Malagasy families.

15. Location of the CAZ Project
Zahamena
National Park
REDD: A new
protected area
Restoration
Mantadia
National Park

16. Principal land uses = causes of Deforestation
(Tavy) (Savoka) Eucalyptus
Slash-and-burn Natural Forest
Fallow plantations
agriculture
• Principal economic activities
• Agriculture
• Charcoal production
• Forest exploitation
• Mines

17. Deforestation in CAZ
Corridor Total area Forest 2005 Forest
loss(Ha/year)
Ankeniheny- 444,516 Ha 382,193 Ha 2026
Zahamena

18. REDD Component

19. Challenges for REDD projects
• Start-up costs
• Classic protected areas issues:
– Finding appropriate alternatives
– Ensuring community benefits and
involvement in the management of
natural resources
• Monitoring of deforestation:
– Availability of land cover data
– Expense of monitoring
– Capacity to monitor

20. Objectives of the REDD project
•Reduce emissions from deforestation through the
creation of the 425,000 hectares NPA
Generate Voluntary Carbon Units (VCUs) from RED
through the Voluntary Carbon Standard (VCS),
featuring as one of the first RED initiatives in Africa.
The project expects to produce a total amount of Voluntary Carbon Units
(VCUs) equivalent to approximately 47,400,000 tons of carbon dioxide
equivalent (tCO2e),including CO2 and non-CO2 emissions reductions.
•Through the marketing and sale of VCUs from the
project, the Government of Madagascar intends to
partially finance the management of the protected
area and expand economic opportunities for local
communities.

21. Main project activities
Objetives of RED Project
Target loss Deforest tCO2e/Ha tCO2 avoided Revenue
(Ha/year) avoided (tCO2e/year) ($5/tCO2e)
(Ha/year)
420 1605 549 881 262 4 406 310

22. Governance and Management Structure
. Decision-making group: MEFT(leader,
carbon aggregator, signs agreements with
landholders ), COS and PLACAZ
. PA Management unit: develop and implement
PA’s workplan…
. Various local sector groups. This structure
has been derived according to discussion
amongst members of the technical group.

23. Project design: stakeholders
Government of Madagascar ERPA
•Project Manager Emissions reduction
Funders Grants •Designated National Authority Purchase Agreements World Bank
(USAID, CI, WB, (DNA) (Biocarbon Fund)
others) •Carbon owner VER,s)
•Registry of offsets
Conservation International Local NGO's Local Local government
•Project design •Protected area Communities •Protected area
•Technical support management •Land owners management
•Facilitate marketing •Forest Restoration •Community
•Funding activities •Training in improved management within
livelihood activities protected area
•Employment
REDD activities Restoration activities Livelihoods activities

24. Costs and Investment
Project implementation costs financed by CI,
USAID and others;
World Bank’s BioCarbon Fund has bought
430,000 tCO2.
Other buyers in the voluntary market have
shown high interest in the project.

25. Part 4:
Project status
and next steps

26. Project Methodology
BioCF’s RED Mosaic Deforestation methodology is used
- CI responsible for PDD preparation, with BioCF support
• Forest carbon density data being collected at present
• Baseline. Land use modeler used to project future
deforestation (based on deforestation rate of past 15
years).

28. Main steps?
• Analysis of historical Land use and Land cover
change in the reference region, leakage belt
and project boundaries
• Based of historic deforestation rates and local
variables, future deforestation rates and
location were determined using the module
“Land Change Modeler” LCM of the IDRISI
software. Identification of forest classes in the
areas that will be deforested under the
Business As Usual and the land use classes
that is going to replace them
• Projection of the rate and location of future
deforestation
• Ex ante estimation of carbon stock change
under the project scenario
Deforestation during the historical reference period, 1990 to
2000 to 2005. Tan = non-forest in 1990, green = forest in 2005,
red = deforestation from 1990 to 2000, purple = deforestation
from 2000 to 2005, blue = water.

29. What factors were taken into
account in establishing the
baseline/what data sources
• Most of the factors that have a
possibility to interfere with the land
use dynamics were analysed :
roads, pathways, railways, rivers,
altitude, slope, proximity to a city,
city size, distance from forest edge,
etc…
• Most of the data comes from
national databases, available from
the National Cartography Institution
(FTM), Office National de
l’Environnement (ONE). Forest
cover change data comes from
national analysis done by CI for the
last 15 years

30. • What is the monitoring strategy? What kind of remote sensing is
being used vs. ground-based measurement? Sample-based or wall-to-
wall?
• The extent of forest was derived from mid resolution imagery (Landsat 5
and 7). We then collected ground sample of carbon stocks, using allometric
equation to determine the amount of carbon based on tree diameter for the
original forest and we used destructive sampling (cut and weight) for the
future land use stocks. Sample plots were distributed randomly in the
project area.
• Quantification estimates?
• we modeled the future carbon emission based on forest cover change
dynamics under the baseline scenario. The module “Land Change Modeler”
of IDRIS software were used for the prediction (see step n.2 in the
methodology above)
• How often will measurements be repeated?
• (our plan was to do the forest cover change monitoring every 5 years…)
• What are the plans for verification of emission estimates?
• Through the monitoring process, we can give the exact amount of emission.

31. Baseline deforestation during the project term
Predicted distribution of deforestation for the project
implementation period in five-year increments, using
the assumed total rate of deforestation of 0.63
percent per year.

32. Potential contribution of REDD
to protected area financing
National Protected Areas Funding gap: approximately $7 million/year
~$7m REDD?
~$22m
~$15m
Climate Change funding could have an important role

33. Restoration Component

34. Challenges for habitat restoration
• Research and development
of appropriate restoration
techniques
• Training of local associations
in nursery and planting
techniques
• Land tenure (title needs to be
clear)
• Funding (investment costs)
• Coordination of logistics,
administration and amongst
multiple stakeholders

35. Restoration of unique threatened
habitat
• 7 local associations running
tree nurseries and planting
• 500,000 seedlings of 120 native
species
• 110 hectares (of 3,020 ha) have
been planted on government
owned land
• Land tenure rights will be
Pale green: restoration area clarified for communities in the
Dark green: Existing forest region
Red line: Protected Area boundaries
Yellow line: Project Area boundaries Habitat restoration/ reforestation is
expected to produce 800,000 tCO2e of
Emissions Reductions

36. Sustainable Livelihoods: addressing leakage, and sustaining communities
• Improved use of fallow land (Savoka
gardens)
• Intensification of agricultural practices to
reduce slash and burn
• Agroforestry techniques (1,261 hectares)
• Woodlots (660 hectares)
• Links to ecotourism activities in the same
area
• These activities provide both immediate
and long term benefits

37. • MISAOTRA TOMPOKO
• OBRIGADO
• THANK YOU
• MERCI