In his seminar at ICRAF on Nov 28, Meine van Noordwijk, describes “Concepts, methods and experience with supporting negotiations and incentives for trees in multifunctional landscapes

1. ICRAF Seminar, Nairobi 27 November, 2009 Concepts, methods and experience with supporting negotiations and incentives for trees in multifunctional landscapes Meine van Noordwijk

3. Sustainagility supporter Diversity in contexts, Common goal & vision Science quality at

4. Boundary objects Boundary agents

5. http://www.fotocommunity.com/pc/pc/mypics/1307401/display/15930189 food security according to Desi

7. CC as source of conflict: Adaptation & mitigation as peace keeping

8. Artist Impression of the Human Perturbation of the Carbon Cycle

9. The Bali roadmap (2006): focus on ‘Nationally Appropriate Mitigation Actions (NAMA)’. Which form of RED/REDD/REDD + /REDD ++ would be a NAMA for Indonesia ? 4 th most popu-lous country, high per-capita emissions, mostly due to AFOLU … occur in between sectoral responsibilities Large parts of emissions … are ‘planned’ for development … are in breach of rules AFOLU = Agriculture, Forestry and Other Land Use … High vulnera-bility of coastal zones Need for adaptation, due to … Landslides, floods and droughts … Still rural, primary resource-based economy … Discrepancies in wealth and power

10. Agroforestry falling through the cracks of the UNFCCC forest definition in REDD?

11. intensive agriculture natural forest integrated, multifunctional landscape: crops, trees, meadows and forest patches Tree plan- tations intensive extensive conservation protection production Agroforestry Agriculture Forestry Segregate Integrate functions Current legal, institutional & educational paradigm Current reality ‘ deforestation’ ‘ loss of forest functions’

12. Zomer et al. (2009) Trees on Farm: Analysis of Global Extent and Geographical Patterns of Agroforestry. ICRAF Working Paper no. 89. Nairobi, Kenya: World Agroforestry Centre. 60pp 50% of ‘agricul-tural land’ has >30% tree cover in SEA & CA

13. Relative agricultural function (RAF) - provisioning Relative ecological function (REF) D Trade-off REF/RAF: convex, concave, win-win after lose-lose A Initial use B Degra- dation C Rehabilitation EU Critical loss of ecological functions

14. Low Low Agricultural productivity Degrading agricultural landscapes High Core wilderness/ natural forest terra incognita Polyculture attractors High Intensive agroecosys-tem domain Agroforest domain Degraded, aban-doned land Low external input agro-ecosystems Biodiversity & associated ecosystem services Current dominant trend Biodiversity-ba-sed alternative pathway Landscape position

15. Land use intensification & domestication of biota Wilderness Animal husbandry Plant husbandry 100 67 33 0 100 67 33 0 0 33 67 100 ‘ Forest’ Protected area Game ranches NTFP-zone Selective logging Agroforest Fastwood plantation Open field crops Leys Off-farm Cut&carry Feed-based bioindustry Timber-enriched forest On-farm Cut&carry ‘ Forest’ Animal production Crop production Nature conservation Agroforestry Centrifugal forces towards ‘pure’ conservation, intensive animal, annual & tree-crop production ‘ Forest’ world pulled towards 2 opposites Multifunctionality attractor?

16. Smallholder far- mer/agroforester here and now Gene Product value chains Patch/field Organism Population Farm Land-scape Desakota network Globe National economy Community Watershed Nation Global institutions National institutions  time Persistence Change Efficiency  space  institutions

17. Gene Product value chains Patch/field Organism Population Farm Land-scape Desakota network Globe National economy Community Watershed Nation Global institutions National institutions  time  space  institutions Persistence Change Efficiency

21. Properties of a system that sup-port actors to cope with change, to be adaptive and resilient. Sustainability: providing for current without compromising future needs Sustain agility

22. Sustainable livelihoods somewhere on the globe Sustainable livelihoods at current location Sustainable farms at current location Sustaina b ility of current farming system Sustaina b ility of current trees/crops/animals Sustaina b ility of current cropping system Sustaina g ility E: human migration Sustaina g ility D: shift to non-ag sectors Sustaina g ility C: other farming system Sustaina g ility B: other cropping system Sustaina g ility A: other trees/crops/ animals

23. Meeting today’s needs without compromising the future 10. Earth system re- source governance 9. Natural resource ma- nagement institutions 8. Agri-food systems 7. Rural landscapes 6. Desakota liveli- hood networks 5. Agroecosystems 4. Farms, forests 3. Populations, fields 2. Organism during its life cycle 1. Access to genetic diversity SustG10: New global deals (S) SustG_9: New environmentality (H,S) SustG_8: New food securities (H,I,S,F,N) SustG_7: New landscape value chains (N,S,H,I,F) SustG_6: New livelihood systems (H, S, F, I, N) SustG_5: New interdependencies for lateral flows (N, H) SustG_4: New farming systems and farm-scale resource management (N,H) SustG_3: New cropping/AF systems and associated knowledge (N,H) SustG_2: New crop/tree/animal management techniques (N,H) SustG_1: New crop/tree/animal types domesticated on farm or accessible from external sources (N, H, S) Sustainable global agreements Sustainable iNRM institutions Sustainable value chains Sustainable Ecosystem Service incentives Sustainable livelihoods Sustainable agro-ecosystems Sustainable farming systems Sustainable soil fertility management Sustainable cropping systems and practices Sustaining genebanks releasing robust varieties

25. The view is better if I go a little further High efficiency (the place provides a nice view on a neighbouring waterfall) Sustainability is ok, (1 m of supporting services…) Sustainagility question-able, don’t jump around...

26. 4 months after Tsunami in Aceh

29. Hutan Desa Partial answer to the issues of local use rights and tenure security?

31. Local Govt, foreign investors (Korea, Taiwan), local investors Govt MoF APP, Local Govt, MoF, Central Govt ICRAF, WARSI WARSI BirdLife, WARSI Local govt, NGO MoF, WARSI Intensified rubber Oil palm (farmer) Mining Road Transmigration HTR HTI Illegal logging Community forest, old RAF Rubber - sisipan Certified logging Protected and customary forest National Park More ES Less ES Conservation concession Transmigration Oil palm (company) Farmer, CIFOR, ICRAF, WARSI, RUPES Local govt Local govt Ideal Zone Less income More income Q1 Q2 Q3 Q4 Govt, BRI through agric. revitalization program National and Malaysian investors, Govt

32. Globally Appropriate Mitigation Actions (GAMA) Nationally Appropriate Mitigation Actions (NAMA) Locally Appropriate Mitigation Actions (LAMA)

33. Negotiation Support Systems Landscape mosaic resource interactions new components & technologies spontaneous change agreed changes performance indicators actors, stake-holders Negotiations process Plots (land use s.s.) Matrix (filter) Roads/streams (channel)

35. the ‘Universal Soil Loss Equation’ can predict what happens in such plots but not what happens here... Landscape-scale assessment of water and sediment flows: Filter effects in the valleys Or where the sediment at the dam comes from 1. Local conflict resolution in forest margin in Sumberjaya (Lampung, Indonesia) the ‘Universal Soil Loss Equation’ can predict what happens in such plots

36. Myth-use of forest hydrology for maintaining political control over land 1 4 2 3 5 => Political reality Hydrological <=

37. First farmer-forest agreements (HKM) Location-specific boundary object – can be replicated in similar circumstances based on ‘policy precedent’ effect Landscape mosaic resource interactions new components & technologies spontaneous change agreed changes performance indicators actors, stake-holders Negotiations process Plots (land use s.s.) Matrix (filter) Roads/streams (channel)

38. Generic boundary object – can be repli-cated in similar circum-stances based on stepwise protocol Rapid/replicable Appraisal Tools (6 months, 5-10 k$) integrating 3 types of knowledge Local Ecological Knowledge Public/Policy Ecological Knowledge Hydrologist Ecological Knowledge

39. RHA Guideline Fig. 6 7 stages in development of RUPES reward mechanism ES Reward support for action RHA Awareness RHA Identifying partners Monitoring Action Plans Negotiations RHA Scoping Beneficiaries, buyers of ES Interme - diaries Providers, sellers of ES Stage II I III IV V VI VII

40. Implementation, Monitoring and Learning: unified K  unified A (or reverting to (K  K)  (A  A) Negotiation: (K  K)  (A  A), aiming for (unified K  unified A) Conditional Stakeholder identifi-cation: A  A Voluntary Scoping: K  K Realistic

41. 2. Emergence of Payments for Watershed Servi-ces in Singkarak (W. Sumatra, Indonesia) Context Issue Salience/PEK Legitimacy/LEK Credibility/MEK Impact on stakeholder action Key to success Ombilin river Solok town Paninggahan Coffee enclave Padang Bukittinggi Maninjau Singkarak PLTA Kesempatan pengembangan CDM CDM opportunities

42. RHA = Rapid hydrological appraisal Based on ‘categories’ Based on ‘processes’ direct ‘observables’ includes balance sheets Laws City folks Local govt National govt Economist Engineers Foresters Ecohydro- logist women men women men lowland upland Three main types of K and associated A Private sector Local Ecological Knowledge Modellers’ Ecological Knowledge Public/Policy Ecological Knowledge

44. 3. Adjustments in China’s Sloping Land Conver-sion Program (SLCP) in Baoshan Context Issue Salience/PEK Legitimacy/LEK Credibility/MEK Impact on stakeholder action Key to success Sloping land conversion program (1998) not based on trees farmers want, and does not allow for intercropping in the early years of tree growth Participatory technology development with farmers and forestry officials actively involved finds that there are trees with real value for farmers, while intercropping with locally domesticated medicinals opens the door for food crop intercropping as well Through local forest department, the success starts to spread, higher level authorities do at least tolerate, some support Trust between researchers & village, researchers & forestry officials => trust between village a& forestry staff

45. 4. Global debate on forests and floods The forest ‘myth’ is sometimes benign and can be left unchallenged, in other cases leads to mis-investment and conflict

46. 5. Emerging global policies for Reducing Emis-sions from Deforestation and Degradation (REDD) and their inconvenient truths Context Issue Salience/PEK Legitimacy/LEK Credibility/MEK Impact on stakeholder action Key to success AFOLU AGG peat restock Agroforest Trees out-side forest REDD Sustainable forest manage-ment Soil C CH 4 N 2 O Net GHG emissions Attempts to broaden the target to emissions from all land use to increaseplatform Challenge current ‘framing’ Solid data + Politics Opportunity cost ana-lysis for REALU 1. Forest definition too broad, yet many avoidable emissions not covered 2. Indigenous people’s claim on forest rights need respect Avoidable GHG emissions from land use change, linked to ‘forest’ drivers co-benefits rights

47. Fossil Fuel Emissions and Cement Production Le Quéré et al. 2009, Nature-geoscience; CDIAC 2009 [1 Pg = 1 Petagram = 1 Billion metric tonnes = 1 Gigatonne = 1x10 15 g] CO 2 emissions (PgC y -1 ) 9 8 7 6 1990 2000 2010 Growth rate: 1.0% per year Growth rate: 3.4% per year 2008 : Emissions: 8.7 PgC Growth rate: 2.0% 1990 levels: +41% 2000-2008 Growth rate: 3.4%

48. Fossil Fuel Emissions: Actual vs. IPCC Scenarios Raupach et al. 2007, PNAS, updated; Le Quéré et al. 2009, Nature-geoscience; International Monetary Fund 2009

49. Le Qu é ré et al. 2009, Nature-geoscience; CDIAC 2009 CO 2 Fossil Fuel Emissions Annex B (Kyoto Protocol) Developed Nation Developing Nations Non-Annex B 1990 2000 2010 5 4 3 2 CO 2 emissions (PgC y -1 ) 55% 45%

50. Balance of Emissions Embodied in Trade (BEET) Peters and Hertwich 2008, Environ, Sci & Tech., updated Year 2004 developed countries are partially outsourcing their emissions to developing countries MtC BEET Warm colors  Net exporters of embodied carbon Cold colors  Net importers of embodied carbon

51. Human Perturbation of the Global Carbon Budget atmospheric CO 2 ocean land fossil fuel emissions deforestation 7.7 1.4 4.1 3.0 (5 models) 2000-2008 PgC CO 2 flux (PgC y -1 ) Sink Source Time (y) 0.3 Residual 2.3 (4 models) Global Carbon Project 2009; Le Quéré et al. 2009, Nature-geoscience

52. http://www.globalcarbonproject.org/carbonbudget/08/hl-brief.htm Land use change was responsible for estimated net emissions of 1.5 PgC per year over the last 15 years. In 2008, estimated emissions declined to 1.2 Pg C. Wet La Niña con­ditions probably contributed to limited fire use and deforestation rate in Southeast Asia. Emissions from Brazil and Indonesia account for 61% of all emissions from land use change. The contribution of land use change emissions to the total emissions from human activities was 12% in 2008, down from 20% in the 1990s. Emissions from land use change

53. Energy use land use and land use change global climate change Net GHG emissions Oceans Construction & manufacture, Transport, Heating/cooling, Food processing, Waste treatment, …, … Fossil fuel com-bustion Industry Industry  Human welfare Energy use land use and land use change  Human welfare Atmosphere A/R CDM CDM CDM REDD

54. Energy use land use and land use change global climate change Net GHG emissions Oceans Construction & manufacture, Transport, Heating/cooling, Food processing, Waste treatment, …, … Fossil fuel com-bustion Industry Industry Construction & manufacture, Transport, Heating/cooling, Food processing, Waste treatment, …, …  Human welfare Energy use land use and land use change  Human welfare Atmosphere REALU CDM CDM

55. Deforestation is often measured in ‘football fields per hour’; is football compatible with avoided deforestation? For example, “ Amazon destruction has accelerated to record le-vels, according to figures released by the Brazilian government. The annual rate has reached 26,130 square km, the second highest ever - an area equivalent to about six football fields a minute are destroyed. http://www.greenpeace.org/international/news/amazon-destruction

56. Avoided deforestation?

57. Is the goal achievable? Is the playing field level? Are the lines clearly marked? What is the ball? Is one tree + 30% grass enough to qualify as forest? The white-man referee in the shade? Who is watching on the sideline? Who are the defenders? Made from cer-tified wood? Who is at play?

58. … .are included under forest, as are areas normally forming part of the forest area which are temporarily unstocked as a result of human intervention such as harvesting or natural causes but which are expected to revert to forest; [FCCC/CP/2001/13/Add.1] Signs of deforestation?

59. Temporarily unstocked… tree-cover-based forest “ FORESTers Forest” – the FAO definition Land spanning more than 0.5ha with trees higher than 5m and a canopy cover of more than 10%, or trees able to reach these thresholds in situ. It does not include land that is predominantly under agricultural or urban land use . trees on farm protected areas Agri- Agro- Forest culture forestry tree crops trees outside forest urban trees urban forest homegardens

60. Forest without trees Non-forest without trees Trees outside forest Forest with trees Forest definition based on insti-tutions & intent Forest definition based on X% canopy cover Total land area Defores- tation? Including e.g. agroforests, oil palm plantation Clearfelling/ re-plant is accep-ted as forest; no time-limit on ‘replant’

61. REDD = idem, + (forest) degradation, or the shifts to lower C-stock densities within the forest; details very much depend on the operational definition of ‘forest’ RED = Reducing emissions from (gross) deforestation: only changes from ‘forest’ to ‘non-forest’ land cover types are included, and details very much depend on the operational definition of ‘forest’ REDD + = idem, + restocking within and towards ‘forest’ ; in some versions RED + will also include peatlands, regardless of their forest status ; details still depend on the operational definition of ‘forest’ REDD ++ = REALU = idem, + all transitions in land cover that affect C storage, whether peatland or mineral soil, trees-outside-forest, agroforest, plantations or natural forest. It does not depend on the operational definition of ‘forest’

62. Details of REDD accounting rules and forest definition have a major impact on the volume of ‘eligible’ emission reduction under a RED i + j scheme. Data for 3 provinces of Indonesia show low consistency when partial accounting rules are followed REALU draft material for COP15 AFOLU AGG Peat Restock Agroforest Trees out-side forest REDD Sustainable FOREST management Soil C CH 4 N 2 O Net GHG emissions Sustainable livelihoods

65. Context + Mechanism => Outcome Concepts, ideas, logical relations: “ how does it work?” Achieving goals: “ so what…” Space-time variation: “ when,where,what” Models, specific hypotheses: MEK K - sharing MEK production Experi-ments Surveys & maps Controlled variability Biophysical, socio-economic variation Packaged technology Tools Q-con-trol K-map-ping Next issue Boundary objects

67. Local ecological knowledge Modelers Ecological knowledge Public/policy ecological knowledge Local stakeholders, periphery Scientists Central stakeholders LEK MEK PEK Knowledge Action

68. Globally Appropriate Mitigation Actions (GAMA) Nationally Appropriate Mitigation Actions (NAMA) Locally Appropriate Mitigation Actions (LAMA)

70. RMA RHA RaCSA RABA RaTA PALA Tools for negotiation support: TUL-SEA

71. F,P,N,H,S capital F,P,N,H,S capital Goods&services Investment, payments Country Province Commune World Household At every scale transition we need to consider: Realistic: Is it ‘ additive ’ or non-linear scaling? Voluntary: Does the currency need to change? If so, what exchange rate? Conditional: How to ‘derive’ flow from stock and build up stock through flows? Crossing borders: Passport – legitimacy Currency Language Timezone Trans- action costs

72. Sticks, sermons or carrots? What is the best way for the farmer to get the donkey to move towards the market? Donkey, it is your due role in life to help me move…

74. RUPES-I synthesis *** 'Real' ES, recurrent Proxies, recurrent Plans/ACM, investment Conditionality Paradigm CIS: ‘Co-investment in Stewardship’ and co-manage-ment of land-scapes for redu-cing poverty and enhancing ES, sharing risk and responsibility Paradigm COS: ‘Compensating Opportunities Skipped ’ or paying land users for accepting man-datory or volun-tary restrictions on their use of land Paradigm CES: ‘Commoditized ES’ or markets for commoditized environmental service procure-ment (or land use proxies with periodic full impact study)

75. Annex-I Emissions all sectors Non-Annex-I CDM REDD and SFM PEAT SLM Agricult. intensi-fication Alleviating rural poverty Biofuel, agrocommodities Export of wood Non-accountable footprint A/R

76. REDD REDD+ REDD++ REDD++ = REALU REDD+ Ahead of COP15 negotiations, Indonesia's President Susilo Bambang Yudhoyono has committed cuts of up to 26 percent by 2020, or 41 percent with funding and technological support from developed countries.

82. van Noordwijk M. 2009. Biofuel Emission Reduction Estimator Scheme (BERES): Land use history, current production system and technical emission factors. Bogor, Indonesia. World Agroforestry Centre - ICRAF, SEA Regional Office. van Noordwijk M and Joshi L. 2009. REDD/REALU Site-level Feasibility Appraisal (RESFA). Bogor, Indonesia. World Agroforestry Centre - ICRAF, SEA Regional Office. Dewi S, Khasanah N, Rahayu S, Ekadinata A and van Noordwijk M. 2009. Carbon Footprint of Indonesian Palm Oil Production: a Pilot Study. Bogor, Indonesia.World Agroforestry Centre - ICRAF, SEA Regional Office. Swallow BM and van Noordwijk M. 2009. Agriculture and Climate Change: An Agenda for Negotiation in Copenhagen For Food, Agriculture, and the Environment Direct and Indirect Mitigation Through Tree and Soil Management (Policy Brief). Washington DC, USA. International Food Policy Research Institute (IFPRI).

84. Ecosystem services Water quan-tity & quality National economy and downstream ES beneficiaries (Goods and Services) Local liveli-hood deficit Biodi-versity deficit C stock defi-cit

86. http://www.globalcarbonproject.org/carbonbudget/

87. China unveils emissions targets ahead of Copenhagen: Re duce &quot;carbon intensity&quot; by 40-45% by the year 2020, this means lower the amount of carbon dioxide emitted for each unit of GDP

88. Brasil + DR Congo + Indonesia contain 50% of total forest C stock, 10 countries contain 2/3 Emissions from deforestation Indonesia + Brasil + Malaysia cause 2/3 of REDD domain emissions Forest-based emissions: a global issue?

89. I LUI = F E R T I L B O N D X Energy (mechanization) Number of crops per year Crop diversity Harvest index (1/organic inputs to soil) Fertilizer use Irrigation Biocides Labour use Non-used refugia and filters in the landscape Invasive exotics R = Time fraction for crop & fallow (Ruthenberg) Intensity of land use: many dimensions Abiotic factors Biotic factors

90. (Sub)Humid Tropics: main C issues & options; main interface with Biodiversity agenda Semi-Arid Tropics: main CC vulnerability Adaptation issues & A/R CDM, not REDD CC Mitigation options CC Adaptation core business Semi-Arid Tropics: (Sub)Humid Tropics CCAFS (Climate Change Agriculture and Food Systems)

91. High human vulnerability to climate change coincides with low diversity parts of the world CCAFS High diversity parts of the world human may be less vulnerable to climate change, but loose diversity under CC

93. http:// portal.iri.columbia.edu/portal/server.pt July 2009 Forecast of El Nino condi-tions: above-average rainfall in Kenya In fact: late start of rains, below-average total as yet Predictability of rainfall at gro-wing-season scale is still low

94. IOD = Indian Ocean Dipole

95. Hydraulic redistribution study in native tree species in an agroforestry parkland of West African dry savanna J. Bayala 1 , L. K. Heng 2 , M. van Noordwijk 3 , S. J. Ouedraogo 1 1 Département Productions Forestières, Institut de l'Environnement et de Recherches Agricoles, Ouagadougou, Burkina Faso, 2 IAEA, Soil and water management and crop nutrition section, Vienna, Austria, 3 World Agroforestry Center, South-East Asia, Bogor, Indonesia Oecologia Plantarum – in press

96. After the harvest of the millet crop, the soil shows the ‘normal’ day/night cycle of rewetting by tree roots (‘hydraulic redistribution’)… but with an upward trend, suggesting that after the crop died off, the tree roots bring up more water at night than they themselves use during the day

97. Uncertainty, bias and its consequences in C accounting Mg C / year Mg C Mg C / ha Mg C / tree Trees / ha = x = x ha / LUtype = d /dt Tree: size (diameter, height,…) shape (allometrics) wood density C-concentration Species ID & lookup tables Forest/Ag patch : frequency distribution . of trees of various types Land area: mosaic of Forest/Ag patches Time series: temporal change in mosaics

98. Fernando Santos Martin: Australian J of Ag and Res Economics (close to being ‘ac-cepted’…) Profitability measures for farmers adopting high-Q trees are flat: no clear benefit… ..while national eco-nomic benefits would increase with more trees on farm Primary reason: Tax & levies on trees, subsidies for fertilizer and maize production;

100. Hydrological Processes, accepted … The predicted changes in buffer indicator for land use + climate change scenarios reach up to 50% of the current (and future) range of inter-annual variability.

101. Low Low Agricultural productivity Degrading agricultural landscapes High Core wilderness/ natural forest terra incognita Polyculture attractors High Intensive agroecosys-tem domain Agroforest domain Degraded, aban-doned land Low external input agro-ecosystems Biodiversity & associated ecosystem services Diversitas-Agrobiodiversity (in prep.) Jambi Current dominant trend Biodiversity-ba-sed alternative pathway Landscape position

102. Meeting today’s needs without compromising the future 10. Earth system re- source governance 9. Natural resource ma- nagement institutions 8. Agri-food systems 7. Rural landscapes 6. Desakota liveli- hood networks 5. Agroecosystems 4. Farms, forests 3. Populations, fields 2. Organism during its life cycle 1. Access to genetic diversity SustG10: New global deals (S) SustG_9: New environmentality (H,S) SustG_8: New food securities (H,I,S,F,N) SustG_7: New landscape value chains (N,S,H,I,F) SustG_6: New livelihood systems (H, S, F, I, N) SustG_5: New interdependencies for lateral flows (N, H) SustG_4: New farming systems and farm-scale resource management (N,H) SustG_3: New cropping/AF systems and associated knowledge (N,H) SustG_2: New crop/tree/animal management techniques (N,H) SustG_1: New crop/tree/animal types domesticated on farm or accessible from external sources (N, H, S) Sustainable global agreements Sustainable iNRM institutions Sustainable value chains Sustainable Ecosystem Service incentives Sustainable livelihoods Sustainable agro-ecosystems Sustainable farming systems Sustainable soil fertility management Sustainable cropping systems and practices Sustaining genebanks releasing robust varieties Sustainagility science: A know-ledge system for conservation, agricultural development and multifunctionality Meine van Noordwijk 1 , Jianchu Xu 1 , Delia Catacutan 1 , Rodel Lasco 1 , Beria Leimona 1 , Laxman Joshi 1 , Ken E. Giller 2 and Ujjwal Pradhan 1 World Agroforestry Centre (ICRAF); correspondence: [email_address] Wageningen University and Research Centre Proc. Nat Acad. of Sci. (under review)

104. Landscape dynamics Population density, Landscape resources, Cultural preferences Migration Carbon stocks Watershed function, Biodiversity Initial drivers Market access, Infrastructure, LU technology Extension Access to land New feedback mechanisms External consequences Land use & cover change Plot level soil fertility Aggregated household economics Farmers’ decision making & learning Prices

105. External consequences Landscape dynamics Population density, Landscape resources, Cultural preferences Migration Carbon stocks Watershed function, Biodiversity Initial drivers Market access, Infrastructure, LU technology Extension Access to land New feedback mechanisms Land use & cover change Plot level soil fertility Aggregated household economics Farmers’ decision making & learning Land conversion & succession Potential area for expansion Land use& cover change Spatial access & attractiveness Farmers’ decision making & learning Adjusting expected yield (Learning) Labour allocation Financial allocation Learning style ( α ) Land allocation External information ( β ) Plot level soil fertility Soil fertility Crop/plant growth & productivity Yield Weather Aggregated household economics Trade Food consumption Storage Livelihoods (secon- dary consumption) Financial capital Profitability of land & labour

106. Migration Extension Access to land External ES consequences Livelihoods Carbon stocks Watershed function, Biodiversity Prices Plot level soil fertility Soil fertility Yield Weather Land conversion & succession Potential area for expansion Land use& cover change Spatial access & attractiveness Farmers’ decision making & learning Adjusting expected yield (Learning) Labour allocation Financial allocation Learning style ( α ) Land allocation External information ( β ) Aggregated household economics Trade Food consumption Storage Livelihoods (secon- dary consumption) Financial capital Profitability of land & labour Crop/plant growth & productivity

107. Intensive rubber Rubber agroforest

108. Plot Age i Age n Land use system: typical C stock across its life cycle Change in landscape-wide C stock  sequestration/ emission estimate Changing proportions of the different land use systems In the landscape as a whole Life-cycle cash-flow analysis (discounted): Net Present Value Yearly input & output tables Price vectors & wage rate Discount rate Opportunity cost curves P S Business as Usual (BAU) or Alternative Scenario’s C All trees in a sample area  biomass per unit area Single tree record: DBH, Species-ID, Height, … Species-ID  Wood density est. Allo-metric equa-tion:  biomass + understory + litter + soil + roots Bio-economic production model Field data Mixed stand growth model Field data All trees in a sample area  biomass per unit area Single tree record: DBH, Species-ID, Height, … Species-ID  Wood density est. Allo-metric equa-tion:  biomass + understory + litter + soil + roots

109. RED REDD REDD + REDD ++= REALU Concerns Transaction costs1: negotiations Transaction costs2: Monitoring Transaction costs3: Leakage control Avoidable emissions Biodiversity co-benefits Net benefits ? ? ? ? ? ? Analysis of the negotiation options: to be filled with semi-quantitative estimates

110. Jambi (peat lands included) : 31.2 t CO 2 / ha / year, 92.7% below 5$/t CO 2 Huge emissions, but very little 'deforestation' $/t CO 2 t CO 2 / (ha yr)

111. Huge percentage of emissions from luc are associated with low economic benefit Opportunity costs vary from place to place

112. Lampung

113. Jambi

114. Kalimantan Timur

115. Temporarily unstocked… Energy use Construction & manufacture, Transport, Heating/cooling, Food processing, Waste treatment, …, …  Human welfare… Leakage Additionality Permanence REDD tree-cover-based forest Fossil fuel combustion Net GHG emissions Industry Oceans Atmosphere protected areas Forest and non-forest land cover are closely linked at 'driver' level, and cross-sectoral shifts in emission patterns ('leakage') needs to be accounted for in any emission reduction claim.

116. Forest Transition Stages FOREST_CORE FOREST_FRONTIER_1 FOREST_FRONTIER_3 FOREST_MOSAICS_1 FOREST_MOSAICS_2 FOREST_FRONTIER1 FOREST_FRONTIER2 FOREST_MOS_2 FOREST_CORE FOREST_MOS_1

119. REDD  Time A/R CDM Emission outside the REDD scheme Sink outside A/R CDM scheme C-stocks t/ha Fairness: the real conservation cost Market Efficiency: the most real impact Depend on definition Forest Conservation Production Conversion

120. Adapting livelihoods to climate change through multifunctional landscapes with trees A1. CC Adaptation: Basic concepts A2. Multifunctional Landscapes A3. Rural livelihoods and change C4. Rights, institutional review and reform C1. Methods to asses what is ‘Realistic’ C2. Methods to establish ‘condi-tionality’ C3. Methods to create ‘Voluntary’ mechanisms for co-investment Concepts Target Methods B2. Supporting multi-functionality and environmental services B4. Current and future climate variability: global and local B3. Tree growth and climate variability B1. Trees and environmental services

121. Data for five provinces in Indonesia (one each in Sumatra, Kalimantan, Java, Sulawesi and Papua) show that actual tree cover does not differ much between the various ‘land use categories’ – the proportion of ‘non forest lands’ that has tree cover meeting the forest definition is close to that of ‘permanent forest estate’ lands in the same province Source: Data for 2006 analyzed by BaPlan

122. Less trees inside, more outside the 'forest'

123. Realistic Lesson 2

124. Conditional Lesson 4

125. Voluntary Lesson 3

126. Gene Product value chains Patch/field Organism Population Farm Land-scape Desakota network Globe National economy Community Watershed Nation Global institutions National institutions  time  space  institutions GRP1 GRP2 GRP3 GRP4 GRP5 GRP6 Persistence Change Efficiency

127. Indonesia 3rd largest forest country, #1 in EDD? Champion of REDD