Drivers of deforestation and forest degradation from Montreal to Canada
Drivers, forest transitions and setting baselines at sub-national level
1. Drivers, forest transitions and setting
baselines at sub-national level
Sonya Dewi
with
Meine van Noordwijk,
Peter Minang
2. OUTLINE
• Reference Emission Levels (REL) in the
context of REDD and land based NAMAs
(Submission to SBSTA UNFCCC, February 28 2012)
• Experiences and lessons learnt from
Indonesia
3. REL IN THE CONTEXT OF
REDD+ AND LAND-BASED
NAMA
4. Key points
• The forest transition’concept can be operationalized as typology of
subnational entities within a large country; an example for
Indonesia
• Different REL calculation techniques apply to different stages of
forest transition, at (sub)national level, to fulfill fairness and
efficiency principles
• Evaluation of existing (pre‐REDD discussion) planned
deforestation’provides an indication of feasible emissions, as
regards infrastructure, labour and capital requirements for
conversion
• The concept of reference level’of deforestation is non‐ operational
unless a stringent ‘natural forest’definition can be agreed upon
internationally; for example Indonesia's recent deforestation rate
varies from ‐0.5 to 3% depending on the forest definition used.
• Linear temporal and spatial extrapolation of historical emission
trends is neither a realistic nor a fair basis for determining REL
5. Local circumstances
• Variation within a country regarding land
use changes and drivers of land use
changes, and therefore emissions in the
past
• Variation wrt poverty, HDI, population
density, regional income – needs for
economic growth and equity
• Variations in land and forest resources –
stock
6.
7. 60% Undisturbed forest; deforestation are lowest
20% Undisturbed forest; half LOF; degradation is highest
<20% UF, degraded forest and estate; deforestation is highest
10% natural forest; 30% mixed tree, 15% estate and crop:
deforestation >degradation, but lower than the above
10% natural forest; 30% estate, 15% crop land and mixed tree
40% crop land, small fraction of NF in PA, 20% estate, 15%
mixed tree and settlement
Forest transitions
From landcover 1990, 2000, 2005
13. Example: Spatially explicit model
of land use change
• Modelling with Neural
Network (Multilayer
Perceptron) in IDRISI
• Scope: Berau and East
Kalimantan
• Period: 2000 – 2020
• Proximate drivers: land
suitability, elevation, spatial
plan, distance to road,
river, settlement, logging
concession, forest
plantation, distances to
forest and changed area,
population density
15. Key points
• The forest transition’concept can be operationalized as typology of
subnational entities within a large country; an example for
Indonesia
• Different REL calculation techniques apply to different stages of
forest transition, at (sub)national level, to fulfill fairness and
efficiency principles
• Evaluation of existing (pre‐REDD discussion) planned
deforestation’provides an indication of feasible emissions, as
regards infrastructure, labour and capital requirements for
conversion
• The concept of reference level’of deforestation is non‐ operational
unless a stringent ‘natural forest’definition can be agreed upon
internationally; for example Indonesia's recent deforestation rate
varies from ‐0.5 to 3% depending on the forest definition used.
• Linear temporal and spatial extrapolation of historical emission
trends is neither a realistic nor a fair basis for determining REL
16. Ex: Linear projection:
historical rate of LULCC
0
2000
4000
6000
8000
10000
12000
T0 T1 T2 T3 T4 T5 T6 T7 T8 T9 T10
Forest
(ha)
Year/period
Deforestation rate = 0.1
Deforestation rate = 0.1
Area of 10,000 ha of forest over 10 year or 10 time periods
17. Key points
• The forest transition’concept can be operationalized as typology of
subnational entities within a large country; an example for
Indonesia
• Different REL calculation techniques apply to different stages of
forest transition, at (sub)national level, to fulfill fairness and
efficiency principles
• Evaluation of existing (pre‐REDD discussion) planned
deforestation’provides an indication of feasible emissions, as
regards infrastructure, labour and capital requirements for
conversion
• The concept of reference level’of deforestation is non‐ operational
unless a stringent ‘natural forest’definition can be agreed upon
internationally; for example Indonesia's recent deforestation rate
varies from ‐0.5 to 3% depending on the forest definition used.
• Linear temporal and spatial extrapolation of historical emission
trends is neither a realistic nor a fair basis for determining REL
23. Lessons learnt
• Trainings were conducted with variable success rates nation-wide at
province level
• Progressive provinces have more initiative in collecting data and
building capacities in setting baseline beyond historical projection
• Parallel processes in developing provincial strategies of REDD+ in
pilot provinces were hard to reconcile from the beginning but
converge toward the end
• Unsupported national action plan for mitigation is soon to be
submitted as the Indonesian NAMA
• There are still confusion between LAMA-NAMA nesting due to
political consideration
• Due to attribution, the direct activities and enabling conditions are
mixed up
• Scope of land-based NAMA coincides with REDD+: REL and MRV
should be common between the two mechanisms
24. Recommendations
• District level action planning should take place in
the next round, since it is at the district level
where the real on-the-ground implementation
will be happening
• Design iterative review and revise processes
• Guidelines from the government is necessary to
avoid confusion, including the nesting processes
• Data improvement
• Monitoring, Evaluation and Reporting as part of
MRV system