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+ initiativesby tree cover change analysis

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

2

Performance assessmentReference levels vs. Before-After/Control-Intervention

B A C I

C IB A

B A

B A

𝐵𝐴𝐶𝐼 𝑟𝑎𝑡𝑖𝑜 𝛽 = 𝑥𝐴𝐼 − 𝑥𝐵𝐼 − 𝑥𝐴𝐶 − 𝑥𝐵𝐶

𝑤𝑖𝑡ℎ 𝑥𝐴𝐼 =1

𝑛𝑎

𝑖=1

𝑛𝑎

𝑥𝑖

𝑤ℎ𝑒𝑟𝑒 𝑥𝐴𝐼 𝑟𝑒𝑝𝑟𝑒𝑠𝑒𝑛𝑡𝑠 𝑡ℎ𝑒 𝑎𝑣𝑒𝑟𝑎𝑔𝑒 𝑎𝑛𝑛𝑢𝑎𝑙 𝑑𝑒𝑓𝑜𝑟𝑒𝑠𝑡𝑎𝑡𝑖𝑜𝑛 𝑟𝑎𝑡𝑒𝑖𝑛 𝑡ℎ𝑒 𝑝𝑒𝑟𝑖𝑜𝑑 𝑎𝑓𝑡𝑒𝑟 𝑡ℎ𝑒 𝑖𝑛𝑡𝑒𝑟𝑣𝑒𝑛𝑡𝑖𝑜𝑛 𝑠𝑡𝑎𝑟𝑡𝑒𝑑;𝑎𝑛𝑑 𝑛𝑎 𝑖𝑠 𝑡ℎ𝑒 𝑛𝑢𝑚𝑏𝑒𝑟 𝑜𝑓 𝑦𝑒𝑎𝑟𝑠 𝑖𝑛 𝑡ℎ𝑒 𝑝𝑒𝑟𝑖𝑜𝑑 𝑎𝑓𝑡𝑒𝑟 𝑡ℎ𝑒𝑖𝑛𝑡𝑒𝑟𝑣𝑒𝑛𝑡𝑖𝑜𝑛 𝑠𝑡𝑎𝑟𝑡𝑒𝑑

3

• Global Forest Change2000–’14 (Hansen et al., Science 2013)

• Forest definition10% tree cover (FAO)

• Relative change focus

Input dataTree cover and tree cover change

4

Resultsdifference 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 ratein intervention area (initiative)

Average annual deforestation ratein control area (district)

bias

Intervention > control

Deforestation frontier(Brazil_3)

Average annual deforestation ratein intervention area (initiative)

Average annual deforestation ratein 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 deforestatione.g. Brazil_3 & Indonesia_3

Increased but avoided deforestatione.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 Biaso Low absolute deforestationo 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

ContactAstrid Bosastrid.bos@wur.nl

More info www.cifor.org/gcs

LiteratureSills 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 you13