Comparison of methods to derive reference levels for REDD
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Comparison of methods to derive reference levels for REDD

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Presentation by Michael Huettner, Max-Planck-Institute for Biogeochemistry Jena/Germany ...

Presentation by Michael Huettner, Max-Planck-Institute for Biogeochemistry Jena/Germany
Measuring and monitoring, baselines and leakage, Forest Day 3
Sunday, 13 December 2009
Copenhagen, Denmark

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  • 1. Comparison of methods to derive reference levels for REDD Forest Day 3 Learning Event Measuring and monitoring, baselines and leakage 12/13/2009 Michael Huettner Max-Planck-Institute for Biogeochemistry Jena / Germany
  • 2. Definition • The UNFCCC SB 28 decision describes Reference Emissions Levels (REL) as follows: “Means to establish reference emission levels, based on historical data, taking into account, inter alia, trends, starting dates and the length of the reference period, availability and reliability of historical data, and other specific national circumstances.”
  • 3. Importance of RL • Reference emission levels (ideally) determine the scale and duration of emissions occuring without REDD activities  to determine ambition of REDD measures • shape the environmental and economic performance for REDD, but also influence the willingness of parties to join such mechanism
  • 4. RL options (1) • Historical baseline (retrospective): – Method: historical extrapolation of forest cover data (RS; e.g. Landsat) – Based on: Santilli et al (2005): Compensated conservation – Examples: Brazil, Indonesia
  • 5. RL options (2) • Projected baseline (prospective): – Method: historical forest cover data and assumption of future driver development combined – Based on: Soares-Filho et al (2006, SimAmazonia); Brown et al (2006, GEOMOD), etc… – Examples: State of Amazonia, Noel Kempff Climate Action project in Bolivia
  • 6. RL options (3) • Historical adjusted baseline (hybrid) – Method: putting national (historical extrapolated) baselines in relation (to a global baseline / remaining forest cover) – Based on: Mollicone et al (2007), Strassburg et al (2009) – Examples: COMIFAC, (CfRN)
  • 7. National adjustment • Historical REL+ individual accounting of national circumstances / development adjustment factor • Adjustment based on : – Remaining usable forest area? – Socio-economic indicators? – Forest trajectories? – Negotiation  Danger of „Political bargaining“
  • 8. Role of drivers in setting REDD baselines • Historical deforestation pathways have very limited predictive power - Example • Additionality – an issue for REDD? • Hot air threat: Forest transition (Costa Rica) • Underfinancing threat: Land-use increase (Congo basin states) • Irreducible complexity of subjective drivers (policy decisions, oil price, security, etc.)
  • 9. Main RL requirements • Environmentally effective: Additionality of emission reductions • Practically applicable: flexible and robust for different country situations • Transparent and politically fair • Economically attractive • Adaptive: reviewed and adjusted over time
  • 10. Indicator importance rating
  • 11. Weighted multi-criteria analysis
  • 12. Thank you for your attention
  • 13. Example • Extrapolated forest area change in Costa Rica Source: based on FAO FRA 2005
  • 14. Trends in deforestation Land use sector undeveloped 100% Reforestation / Deforestation Afforestation Forest transition Forest Cover Forest depletion Source: modified from World Bank (2007) 0% Time
  • 15. Deforestation rates 2000-2005 against relative forest cover in 2000 Climate (according to FAO): Tropical countries Forest area 2000 (1000ha) (Binned) Annual change rate 2000-2005 (%) no plantations 2,00 <= 1000 1001 - 2000 0,00 2001 - 3000 3001 - 4000 4001 - 5000 5001 - 6000 -2,00 6001 - 7000 7001 - 8000 8001 - 9000 -4,00 9001 - 10000 10001+ -6,00 Nigeria -8,00 -10,00 Source: FAO FRA (2005) -12,00 0,00 20,00 40,00 60,00 80,00 100,00 Forest area 2000 (% of land area) no plantations