Session 66: Evaluating the impacts of REDD+ interventions on forests and people
ATBC 23 June 2016
Astrid Bos
Valerio Avitabile, Martin Herold, Amy Duchelle, Shijo Joseph, Claudio de Sassi,
William Sunderlin, Erin Sills, Arild Angelsen, Sven Wunder
Assessing the effectiveness
of subnational REDD+ initiatives
by tree cover change analysis

CIFOR Global Comparative Study on REDD+
Module 2: subnational initiatives in 6 countries
2

Performance assessment
Reference levels vs. Before-After/Control-Intervention
B A C I
C IB A
B A
B A
𝐵𝐴𝐶𝐼 𝑟𝑎𝑡𝑖𝑜 𝛽 = 𝑥 𝐴𝐼 − 𝑥 𝐵𝐼 − 𝑥 𝐴𝐶 − 𝑥 𝐵𝐶
𝑤𝑖𝑡ℎ 𝑥 𝐴𝐼 =
1
𝑛 𝑎
𝑖=1
𝑛 𝑎
𝑥𝑖
𝑤ℎ𝑒𝑟𝑒 𝑥 𝐴𝐼 𝑟𝑒𝑝𝑟𝑒𝑠𝑒𝑛𝑡𝑠 𝑡ℎ𝑒 𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑎𝑛𝑛𝑢𝑎𝑙 𝑑𝑒𝑓𝑜𝑟𝑒𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒
𝑖𝑛 𝑡ℎ𝑒 𝑝𝑒𝑟𝑖𝑜𝑑 𝑎𝑓𝑡𝑒𝑟 𝑡ℎ𝑒 𝑖𝑛𝑡𝑒𝑟𝑣𝑒𝑛𝑡𝑖𝑜𝑛 𝑠𝑡𝑎𝑟𝑡𝑒𝑑;
𝑎𝑛𝑑 𝑛 𝑎 𝑖𝑠 𝑡ℎ𝑒 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑦𝑒𝑎𝑟𝑠 𝑖𝑛 𝑡ℎ𝑒 𝑝𝑒𝑟𝑖𝑜𝑑 𝑎𝑓𝑡𝑒𝑟 𝑡ℎ𝑒
𝑖𝑛𝑡𝑒𝑟𝑣𝑒𝑛𝑡𝑖𝑜𝑛 𝑠𝑡𝑎𝑟𝑡𝑒𝑑
3

• Global Forest Change
2000–’14 (Hansen et al., Science 2013)
• Forest definition
10% tree cover (FAO)
• Relative change focus
Input data
Tree cover and tree cover change
4

Results
difference Before-After & Before-After/Control-Intervention ratio
good 7 30.4%
neutral 7 30.4%
poor 9 39.1%
good 8 34.8%
neutral 9 39.1%
poor 6 26.1%
good 9 40.9%
neutral 4 18.2%
poor 9 40.9%
good 11 50.0%
neutral 8 36.4%
poor 3 13.6%
5

Results explained (1) Bias in before period
Intervention < control
Conservation area
(Indonesia_4)
Average annual deforestation rate
in intervention area (initiative)
Average annual deforestation rate
in control area (district)
bias
Intervention > control
Deforestation frontier
(Brazil_3)
Average annual deforestation rate
in intervention area (initiative)
Average annual deforestation rate
in control area (district)
bias
B A
B A
B A
B A
bias
bias
B A C I
C IB A
B A
B A
6

Results explained
(2) Low absolute deforestation
small differences  high uncertainty  big influence on score
(e.g. Tanzania_1)
B A C I
C IB A
B A
B A
7

Results explained (3) Peak years
Tanzania_1 control area (district)
• In before period (in control area)
 “better” Before-After score for control
 “poorer” BACI
(e.g. Brazil_1/Tanzania_1/Tanzania_6)
Tanzania_5 intervention area (initiative)
• In after period (in intervention area)
 Poor performance?
 REDD+ not addressing big
event drivers
(e.g. Tanzania_5)
B A C I
C IB A
B A
B A
8

Results explained
(4) Limited additionality
Decrease in deforestation, but limited additionality
(control area performs even better than intervention villages)
Brazil_2 intervention (villages) Brazil_2 control (villages)
B A C I
C IB A
B A
B A
9

Results explained
(5a) good performance
Reduced deforestation
e.g. Brazil_3 & Indonesia_3
Increased but avoided deforestation
e.g. Indonesia_6 (both site & village level)
B A C I
C IB A
B A
B A
10

Results explained
(5b) poor performance
High deforestation in 3 consecutive years in after period
(e.g.Vietnam_1, Tanzania_06)
Vietnam_1 ceased project in 2012
B A C I
C IB A
B A
B A
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Conclusions
• Performance measure itself has implications on results
• For result-based finance, it is important to understand
causes of change
• Which measure is more “climate-friendly”?
• Overall, most REDD+ sites perform relatively well when
compared to control units, especially on village level
(here: only relative change is analysed)
• Causes of “poor” & “good” BACI scores vary widely
– Random/contextual factors
o Bias
o Low absolute deforestation
o Peaks (is REDD+ influencing big drivers?)
– Additionality
– Poor/good performance
• Next: link to specific REDD+ interventions
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Credits photographs in this presentation:
CIFOR & WUR
Contact
Astrid Bos
astrid.bos@wur.nl
More info www.cifor.org/gcs
Literature
Sills et. al (2014)
www.cifor.org/redd-case-book
Financial
support for
GCS REDD+
Norwegian Agency for Development Cooperation,
Australian Agency for International Development,
European Commission, UK Department for International
Development, German International Climate Initiative,
CGIAR Forests, Trees and Agroforestry (FTA) Programme
Thank you
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