Diversity of land use trajectories and implications for redd+


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  • A qualitative read, up to debate
  • A qualitative read, up to debate
  • A qualitative read, up to debate
  • A qualitative read, up to debate
  • A qualitative read, up to debate
  • A qualitative read, up to debate
  • A qualitative read, up to debate
  • Diversity of land use trajectories and implications for redd+

    1. 1. Diversity of Land-Use Trajectories and Implications for REDD+ Daniel Müller© Mertz COP18 (29 November 2012)
    2. 2. Contents1. Understanding drivers2. Regime shifts in land use3. Implications for FRL4. Key messages
    3. 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. 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. 5. Empirical example: Causes and Processes ofLand-Use Change in Southeast Asia © Sun
    6. 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. 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. 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. 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. 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. 11. Regime Shifts in Land Use Stable land-use regimes
    12. 12. Regime Shifts in Land Use Stable land-use regimes Periods of rapid change
    13. 13. Regime Shifts in Land Use Thresholds Stable land-use regimes Periods of rapid change
    14. 14. Regime Shifts in Land Use Thresholds
    15. 15. Regime Shifts in Land Use - 1985
    16. 16. Regime Shifts in Land Use - 2012
    17. 17. Regime Shifts in Land Use - 2020
    18. 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. 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. 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. 21. Thank you.Acknowledgements:Zhanli Sun (IAMO)Ole Mertz (Uni Copenhagen)Other I-REDD+ collaboratorsContact:Daniel Müllermueller@iamo.dewww.iamo.dewww.geographie.hu-berlin.dewww.hu-berlin.de/~muelleda