1. Diversity of Land-Use Trajectories
and Implications for REDD+
Daniel Müller
© Mertz
COP18 (29 November 2012)

2. Contents
1. Understanding drivers
2. Regime shifts in land use
3. Implications for FRL
4. Key messages

3. Distant Drivers - Local Impacts
• Land-use change and resulting
emissions take place at local level
• Success of REDD+ manifests locally
• Underlying drivers for land-use
change often originate at national or
global levels
• Similar drivers can lead to grossly
different local land-use outcomes
→ Understanding local responses to
underlying drivers is paramount for
REDD+
© Müller

4. Importance of Causal Understanding
• Decide on what to monitor
• Prioritize actions and policies
• Adjust BAU baselines for national circumstances
(beyond historic developments)
• Anticipate future developments
→ A causal understanding of drivers of land-use change
is fundamental to develop forest reference levels
→ Prerequisite to move beyond Tier-1
© Müller © Müller © Sun

5. Empirical example:
Causes and Processes of
Land-Use Change in Southeast Asia
© Sun

6. Data Collections
• Several villages per country
– China (Xishuangbanna), Laos (Houaphan),
Indonesia (Kutai Barat), Vietnam (Nghe An)
• Qualitative and quantitative data
on land use, socioeconomics and
forest carbon
– Participatory mapping and satellite analysis © Sun
– Surveys, focus groups, direct observations
© Sun
© Müller © Müller © Sun

7. China (Xishuangbanna) Vietnam (Nghe An)
Rubber plantation Selective logging
Processes
of land-use
© Sun © Pflugmacher
change
Laos (Houaphan) Indonesia (Kutai Barat)
are very
Oil palm expansion diverse
Shifting cultivation
© Müller © Sun

8. China (Xishuangbanna) Vietnam (Nghe An) Village
Fast increase of land-use
rubber plantations End of shifting cultivation, trajectories
forest plantation, (1990-2012)
forest degradation,
Laos (Houaphan) Indonesia (Kutai Barat)
Shifting cultivation,
Oil palm expansion,
forest degradation
deforestation
Source:
Data from I-REDD+
fieldwork in 2-3
villages per country

9. China (Xishuangbanna) Vietnam (Nghe An)
Rapid past change,
now stable
Off-farm work, Different
selective logging historic
and future
dynamics
Laos (Houaphan) Indonesia (Kutai Barat)
More oil palm
Gradual past change,
expansion,
plantation crops
future of shifting
start emerging
cultivation unclear

10. Land-Use Trajectories in Southeast Asia
• Shifting cultivation dominated land-use patterns across
Southeast Asia in the past
• Land-use pathways diverged in last two decades
– Rapid deforestation in Indonesia
– Forest degradation dominates in mainland Southeast Asia
– Dynamic development of cash cropping in China and Indonesia
– Gradual change in Vietnam and Laos
 Change often non-linear and rapid
 Underlying drivers are similar, but result in contrasting
land-use outcomes

11. Regime Shifts in Land Use
Stable land-use regimes

12. Regime Shifts in Land Use
Stable land-use regimes
Periods of rapid change

13. Regime Shifts in Land Use
Thresholds
Stable land-use regimes
Periods of rapid change

14. Regime Shifts in Land Use
Thresholds

15. Regime Shifts in Land Use - 1985

16. Regime Shifts in Land Use - 2012

17. Regime Shifts in Land Use - 2020

18. Diversity in Land-Use Trajectories
• Land-use changes are not always smooth and gradual
• Similar underlying drivers may result in very different
land-use trajectories
• Regime shifts are difficult to anticipate; thresholds are
often unknown
• Reversal of regime shifts is difficult
 REDD+ needs to guide land use towards desirable
regimes, or avoid undesired regime shifts

19. Consequences for Developing
Forest Reference Levels
 Anticipating future BAU is
necessary to ensure
additionality of carbon
payments
• Historic changes are not necessarily Angelsen 2008
best predictors for future change
• Inclusion of regime shifts in future BAU challenging
• Historical commitment (reference) period may or may
not include the period of rapid change

20. Take-Home Messages
• Definition of BAU baseline remains key challenge
– Particularly in complex landscapes
• Effects of underlying drivers (e.g., commodity prices,
policies) difficult to anticipate
– Effects are often non-linear, rapid and surprising
• Important to identify thresholds of future regime shifts
– Surpassing thresholds may alter land-use regimes
• Low opportunity costs in regimes with low land rents
may provide window of opportunity for REDD+
– Opportunity costs likely rise over time

21. Thank you.
Acknowledgements:
Zhanli Sun (IAMO)
Ole Mertz (Uni Copenhagen)
Other I-REDD+ collaborators
Contact:
Daniel Müller
mueller@iamo.de
www.iamo.de
www.geographie.hu-berlin.de
www.hu-berlin.de/~muelleda