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Concepts: Trees in Landscapes

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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

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

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  • The basic concept of RHA is integrating stakeholders’ knowledge. That is knowledge of local, public or policy makers as well as hydrologist or research community. Through integration of the various stakeholders knowledge, we will be able to have a comprehensive understanding on the hydrological situation in a given watershed.
  • Fossil fuel CO2 emissions continued to grow strongly in 2008 at 2% per year. This growth lead to an all time high of 8.7 PgC emitted to the atmosphere (1 Pg = 1 billion tons or 1000 x million tons), 29% above emissions in 2000, and 41% above the Kyoto reference year 1990. Coal is now the largest fossil-fuel source of CO2 emissions. Over 90% of the growth in coal emissions results from increased coal use in China and India. Global emissions per capita reached 1.3 tonnes of carbon but the developed countries still lead.   CO2 emissions from fossil fuel and other industrial processes were calculated by the Carbon Dioxide Information Analysis Center of the US Oak Ridge National Laboratory. For the period 1958 to 2006 the calculations were based on United Nations Energy Statistics and cement data from the US Geological Survey, and for the years 2007 and 2008 the calculations were based on BP energy data. Uncertainty of the global fossil fuel CO2 emissions estimate is about ±6%. Uncertainty of emissions from individual countries can be several-fold bigger.
  • The current financial crisis had a small but probably discernable impact on the emissions growth rate in 2008 (growth rate of 2.0% down from 3.4% per year average over the previous 7 years). Despite this slowdown, fossil fuel emissions continue to track the average of the most carbon-intensive scenario of the Intergovermental Panel on Climate Change. In 2009, we project emissions to decline to levels observed in 2007 with negative growth of -2.8%. Positive growth is expected return in 2011 as the change in global Gross Domestic Product goes positive. We have estimated emissions for 2009 based on the projection of -1.1% GDP growth rate provided by the International Monetary Fund (October 2009) and assuming a continue global decline in the carbon intensity of the GDP as seen over the last 30 years (-1.7% per year).
  • The biggest increase in emissions has taken place in developing countries (with close to 6 billion people) while developed countries (with less than 1 billion people), on average, show rather steady emissions for the last decade. About one quarter of the recent growth in emissions in developing countries resulted from the increase in international trade of goods and services produced in developing countries but consumed in developed countries. The largest regional shift in 2008 was India overtaking Russia as the third largest CO2 emitter. China and the US remain in first and second position. From a historical perspective, developing countries with 80% of the world’s population still account for about 20% of the cumulative emissions since 1751; the poorest countries in the world, with 800 million people, have contributed less than 1% of these cumulative emissions. Uncertainty of emissions from CO2 fossil fuel is large in some countries and about ±0.5 PgC globally.
  • Increasingly, more developed countries are net importers of carbon embedded in products and services provided by developing countries. In other words, developed countries are partially outsourcing their emissions to developing countries. Examples of this emissions imbalance created by import/export are: US (1997-2004): Within country emissions went up by 6%; Consumption based emissions went up +17%. Part of this differences is Sweden (1992-2004): Within country emissions – 5%; Consumption based emissions +12% China (2002-2005): Production of Exports was responsible for 50% of the emissions growth; 30% total emissions.
  • How the global carbon budget is put together: Atmospheric CO2 . The data is provided by the US National Oceanic and Atmospheric Administration Earth System Research Laboratory. Accumulation of atmospheric CO2 is the most accurately measured quantity in the global carbon budget with an uncertainty of about 1% or about 0.04 PgC of the 4PgC per year accumulated on average since 2000. Emissions from CO2 fossil fue l. CO2 emissions from fossil fuel and other industrial processes were calculated by the Carbon Dioxide Information Analysis Center of the US Oak Ridge National Laboratory. For the period 1958 to 2006 the calculations were based on United Nations Energy Statistics and cement data from the US Geological Survey, and for the years 2007 and 2008 the calculations were based on BP energy data. Uncertainty of the global fossil fuel CO2 emissions estimate is about ±6% (currently ±0.5 PgC). Uncertainty of emissions from individual countries can be several-fold bigger. Emissions from land use change . CO2 emissions from land use change were calculated by using a book-keeping method with the revised data on land use change from the Food and agriculture Organization of the United Nationals Global Forest Resource Assessment. Emissions after 2005 were extrapolated from the previous 25-year trend of 1.5 PgC per year.. We used fire emissions from the Global Fire Emissions Database vs.2 over tropical forests to provide inter-annual variability on emissions over the last three years. Uncertainty of the global estimate of land use emissions is large and considered to be ±0.7 PgC in this analysis. Emission uncertainties at the country level can be large. Ocean CO2 sink. The global ocean sink was estimated using an ensemble of four ocean general circulation models coupled to ocean biogeochemistry models. Models were forced with meteorological data from the US national Centers for Environmental Prediction and atmospheric CO2 concentration.  Recent trends in regional CO2 sinks in the Southern Ocean, North Atlantic, and Pacific oceans were detected directly from repeated observations. Land CO2 sink . The terrestrial sink was estimated using an ensemble of 5 global vegetation models forced by observed CO2 concentration and a combination of meteorological data from the Climatic Research Unit and US National Centers for Environmental Prediction. Redidual : It is the mismatch between the sum of the sources minus all the sinks estimated independently.
  • http://www.globalcarbonproject.org/carbonbudget/08/hl-brief.htm
  • Transcript

    • 1. ICRAF Seminar, Nairobi 27 November, 2009 Concepts, methods and experience with supporting negotiations and incentives for trees in multifunctional landscapes Meine van Noordwijk
    • 2. Preview of contents
      • Science quality: the challenges of food security and climate change, REF and RAF
      • Sustainagility
      • Agroforestry falling through the cracks?
      • 5 INRM examples
      • K2A and boundary work
      • Multi-scale ES incentives to bring sustainability and sustainagility into the efficiency sphere
    • 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
    • 6. Climate change and science
      • How many Nobel prizes have been awarded for climate change related science?
      None for Physics, Medicine, Economics * , Literature One for Chemistry (early atmospheric chemistry: Crutzen) One for PEACE (CC communication and IPCC) * 2009 Economics price to Prof. Eleanor Ostrom is based on her work on institutional economics of the commons*
    • 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
    • 18.
      • Resilience according to the most popular WWW sources: :
      • The physical property of a material that can return to its original shape or position after deformation that does not exceed its elastic limit
      • an occurrence of rebounding or springing back
      • Resilience in psychology is the positive capacity of people to cope with stress and catastrophe.
      • The positive ability of a system or company to adapt itself to the consequences of a catastrophic failure caused by power outage, a fire, a bomb or similar event
      • Resilience is a 4 piece punk rock group from Santa Rosa, California, United States.
      • Resilience is the ability to provide and maintain an acceptable level of service in the face of faults and challenges to normal operation
      • In ecology, resilience is the rate at which a system returns to a single steady or cyclic state following a perturbation
      • The mental ability to recover quickly from depression, illness or misfortune
      beyond resilience to status quo... the world wants or cannot avoid
    • 19. Adaptive capacity, according to Wikipedia, is
      • the capacity of a  system  to adapt if the environ-ment where the system exists is changing.
      • In human social systems, it is determined by :
      • the ability of  institutions  and  networks  to  learn , and store  knowledge  and experience.
      • creative   flexibility  in  decisionmaking  and  problem solving
      • the existence of  power structures  that are responsive and consider the  needs  of all  stakeholders
      • In ecological systems, it is determined by :
      • genetic diversity  of  species
      • biodiversity  of particular  ecosystems
      • heterogeneous   ecosystem  mosaics as applied to specific  landscapes  or  biome  regions
    • 20.
      • Agility is the ability to change the body's position efficiently, and requires the integration of isolated movement skills using a combination of balance , coordination , speed , reflexes , strength , endurance ,and stamina.
      • In sports , agility is described in terms of response to an opposing player, moving target, as seen in field sports and racket sports. Sheppard and Young (2006) define agility as "a rapid whole body movement with change of velocity or direction in response to a stimulus."
      • In business , agility means the capability of rapidly and cost efficiently adapting to changes. Recently agility has been applied e.g. in the context of agile software development and agile enterprise
      • wikipedia
    • 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
    • 24. Ecosystem Services: The benefits people obtain from ecosystems
      • Regulating
      • Benefits obtained from regulation of ecosystem processes
      • • climate regulation
      • • disease regulation
      • • flood regulation
      Provisioning Goods produced or provided by ecosystems • food • fresh water • fuel wood • genetic resources Cultural Non-material benefits from ecosystems • spiritual • recreational • aesthetic • inspirational • educational Supporting Services necessary for production of other ecosystem services • Soil formation, • Nutrient cycling, • Primary production Innovation options resources necessary for new goods & services Current efficiency tradeoffs Sustainability time scale Sustainagility time scale RAF REF
    • 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
    • 27.
      • As the weather lost its discipline…
      So must we Art: c Desi Suyamto
    • 28.
      • Govt plans to rehabilitate 2.5 million hectares of forest
      • The Jakarta Post ,  Jakarta   |  Thu, 11/26/2009 6:24
      • Forestry Minister Zulkifli Hasan says the government will reha-bilitate 2.5 million hectares of critical forest area over the next five years through a program that involves local residents  Under the community forest program, a family will be granted the right to manage up to 15 hectares of forest area for a maximum 35 years. The family will be allowed to cultivate plants of their choice, including rubber trees .
    • 29. Hutan Desa Partial answer to the issues of local use rights and tenure security?
    • 30.  
    • 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)
    • 34. 5 case studies
      • 1. Local conflict resolution in forest margin in Sumberjaya (Lampung, Indonesia)
      • 2. Emergence of Payments for Watershed Servi-ces in Singkarak (W. Sumatra, Indonesia)
      • 3. Adjustments in China’s Sloping Land Conversion Program (SLCP) in Baoshan
      • 4. Global debate on forests and floods
      • 5. Emerging global policies for Reducing Emis-sions from Deforestation and Degradation (REDD) and their inconvenient truths
      Lessons for R&D institutions
    • 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
    • 43. Impacts 2 years after RHA Singkarak
      • Before RHA Singkarak
      • Deforestation seen as the main culprit of all problems, including blackouts
      • Tree planting as main solution
      • Village with most tree cover should get highest share in royalties
      • Problems with the Ikan bilih fish linked to deforestation
      • After RHA + disc.
      • Focus on lake & its water quality; adjust scale of institution
      • More awareness of climatic dependence
      • Less blaming the upland deforestation for blackouts
      • Less focus on ‘tree planting’ as the only or main solution
      • More care in planning coffee re-intensification: Kopi Ulu
      • Ikan bilih problem is about breeding grounds & overfishing
      New LGU forum Now with ICCRI support Riparian tree focus
    • 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
    • 63. Replicable Processes: Boundary objects Independence: Boundary organizations TRUST Boundary agents
      • Local conflict resolution in forest margin in Sumberjaya
      • 2. Emergence of Payments for Watershed Services in Singkarak
      • 3. Adjustments in China’s Sloping Land Conversion Program (SLCP)
      • 4. Global debate on forests and floods
      • 5. Emerging global policies for REDD and their inconvenient truths
      Local ecological knowledge Modelers Ecological knowledge Public/policy ecological knowledge LEK MEK PEK Context , Mechanism , Consequence , outcome Saliency Legitimacy Credibility Lessons for R&D institutions: science quality Knowledge
    • 64. Context + Mechanism => Outcome Concepts, ideas, logical relations: “ how does it work?” Achieving goals: “ so what…” Space-time variation: “ when,where,what” Stakeholder knowledge and preferences: Local (LEK) and Policy (PEK)
      • Market value
      • chains (input &
      • output)
      • Farming praxis & experimentation
      • Negotiated re-
      • source access
      • Policy reform &
      • implementation
      Previous solutions Monitoring & evaluation Boundary objects
    • 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
    • 66. Context + Mechanism => Outcome Concepts, ideas, logical relations: “ how does it work?” Achieving goals: “ so what…” Space-time variation: “ when,where,what” Stakeholder knowledge and preferences: Local (LEK) and Policy (PEK) Models, specific hypotheses: MEK K - sharing MEK production Experi-ments Surveys & maps Controlled variability Biophysical, socio-economic variation Packaged technology Tools Q-con-trol
      • Market value
      • chains (input &
      • output)
      • Farming praxis & experimentation
      • Negotiated re-
      • source access
      • Policy reform &
      • implementation
      K-map-ping Next issue Previous solutions Monitoring & evaluation 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)
    • 69. ‘ Nested Baseline ’
      • CO 2 benefits: reducing emis-sions that are due to:
      • Planned change
      • Legitimate local actions
      • ‘ Illegal’ activities
      CO-benefits: Sustainable livelihood op-tions for the longer term, enhancing buffering of water flows and conser-vation of biodiversity Actual emissions (or chan-ges in stock) in relation to Reference Emission Level Additionality : difference with ‘business as usual’ development pathway Leakage : effects on emissions elsewhere Permanence : effects on future emissions (~ insu-rance & spreading risk) certification Registry and ‘rights to in-vest’, attribution Sale and use as off-sets Local actors (incl private sector, NGO’s,CBO’s) Dis- trist & provin-ce govt Natio-nal Interna-tional Independent verification Rules of the game, eligibility of types of emission reduction rights to land use Fairness& effi-ciency change in development pathway C REDD Transac-tion costs
    • 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…
    • 73.
      • Farmer
      • benefit
      Discount rate for future harvests =
      •  (Price . Volume).(1-Risk)
      •  Price . Input
      • + REF . (Local + (1-t).PES external )
      Harvested products Climatic risk Biotic risk Eviction risk HH labour risk Labour, Fertilizer, Pesticides, Drainage/ irrigation, Machinery Transaction cost Transfer/ compensation *#^&$   ^&  !!! *#^&$   ^&  !!! Area * Yield *#^&$   ^&  !!! Efficiency scale economics with REF appreciation *#^&$   ^&  !!! Demand & control Persuasion Direct incentives Farmer benefit  (Price . Volume).(1-Risk) -  Price . Input +ESeffect . (Local + (1-t).PES external ) =
    • 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.
    • 77. Recap of contents
      • Science quality: the challenges of food security and climate change, REF and RAF
      • Sustainagility
      • Agroforestry falling through the cracks?
      • 5 INRM examples
      • K2A and boundary work
      • Multi-scale ES incentives to bring sustainability and sustainagility into the efficiency sphere
    • 78.  
    • 79.
      • Meine van Noordwijk and Peter Akon Minang ETFRN Newsletter 50(2009): 5-10
      • “ If we cannot define it, we cannot save it” Fuzzy forest definition as a major bottleneck in reaching REDD agreements at and beyond Copenhagen COP15
      Meine van Noordwijk, Delia C, Catacutan, William C. Clark, 2009. Linking scientific knowledge with policy action in Natural Resource Management. ASB Policy Brief. http://www.asb.cgiar.org/publications/ view.asp?Pub_ID=1084
    • 80.
      • Meine van Noordwijk and Beria Leimona
      • Co-investment in natural capital or payments for environmental ser­vices? Paradigms, criteria and indicators for fairness and efficiency. Ecology and Society (under review)
      • Meine van Noordwijk, Jianchu Xu, Delia Catacutan, Rodel Lasco, Beria Leimona, Laxman Joshi, Ken E. Giller and Ujjwal Pradhan. Sustainagility science: A knowledge system for conservation, agricultural development and multifunctionality. PNAS (under review)
    • 81.
      • Ma, X,, Xu, J. and van Noordwijk, M., 2009. Sensitivity of streamflow from a Himalayan catchment to plausible changes in land-cover and climate. Hydrological Processes in press
      • Verbist, B., Poesen, J., van Noordwijk, M. Widianto, Suprayogo, D., Agus, F., Deckers, J., 2010. Factors affecting soil loss at plot scale and sediment yield at catchment scale in a tropical volcanic agroforestry landscape, Catena (2010)
      • van Dijk, A.I.J.M., van Noordwijk, M., Calder, I.R., Bruijnzeel, L.A., Schellekens, Chappell, J.N.A., 2009. Forest-flood relation still tenuous – comment on ‘Global evidence that deforestation amplifies flood risk and severity in the developing world’ by C.J.A. Bradshaw, N.S. Sodi, K. S-H. Peh and B.W. Brook. Global Change Biology 15: 110-115
      • Swallow, B. M., M. F. Kallesoe, U. A. Iftikhar, M. Van Noordwijk, C. Bracer, S. J. Scherr, K. V. Raju, S. V. Poats, A. Kumar Duraiappah, B. O.Ochieng, H. Mallee and R. Rumley. 2009. Compensation and Rewards for Environmental Services in the Developing World: Framing Pan-Tropical Analysis and Comparison. Ecology and Society 14 (2): 26. [online],
      • Leimona, B., Joshi, L. and van Noordwijk, M., 2009. Can rewards for environmental services benefit the poor? Lessons from Asia. International Journal of the Commons, Vol 3, No 1 http://www.thecommonsjournal.org/index.php/ijc/article/viewArticle/121
    • 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).
    • 83.  
    • 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
    • 85. Climate Change Adaptation concepts and definitions
      • Anthropogenic greenhouse gas emissions, due to f ossil fuel use, LU and ‘deforestation’
      Vulnerability : human, biota & ecosystems Adaptation : Shift and change to reduce vulnerability Mitigation : GHG source control, sink enhance-ment Atmospheric change leading to climate change and shifts Primary motivation for action 1 3 2
    • 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
    • 92.
      • We can predict the direction and size of the change, and plan to adjust what we do
      • Uncertainty on di-rection of change but greater variabi-lity: we need to in-crease buffering & resilience: diversity
      In both cases a ‘No regrets’ focus will focus on what makes sense anyway… Limits to adaptation: plans or diversity approach Two basic situations can be distinguished in adaptation:
    • 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;
    • 99.  
    • 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)
    • 103. ‘ Nested Baseline ’
      • CO 2 benefits: reducing emis-sions that are due to:
      • Planned change
      • Legitimate local actions
      • ‘ Illegal’ activities
      CO-benefits: Sustainable livelihood op-tions for the longer term, enhancing buffering of water flows and conser-vation of biodiversity Actual emissions (or chan-ges in stock) in relation to Reference Emission Level Additionality : difference with ‘business as usual’ development pathway Leakage : effects on emissions elsewhere Permanence : effects on future emissions (~ insu-rance & spreading risk) certification Registry and ‘rights to in-vest’, attribution Sale and use as off-sets Local actors (incl private sector, NGO’s,CBO’s) Dis- trict & provin-ce govt Natio-nal Interna-tional Independent verification Rules of the game, eligibility of types of emission reduction rights to land use Fairness& effi-ciency change in development pathway C REDD Transac-tion costs
    • 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
    • 117. Certification in main export crops: cocoa, coffee, rubber, palm oil, biofuels
      • Local concerns:
      • Employment, la-bour absorption
      • Economic growth
      Watershed concerns driving local EES ASB3 OpCost_FCPF REDD/REALU implementation mechanisms: rights, institutions, governance RUPES/PRESA STCDP
      • Global concerns:
      • C stocks & GHG emissions
      • Biodiversity
      Landscapes with: Natural Forest Managed forest Agroforest Tree crops Pasture Food crops … Tropical forest margins Tradeoffs, need for external ES incentives, Negotiation Support Intensification hypothesis rejected unless… ASB1 ASB2 NARS: (Tree) Crop & Forest Management innovation Climate change CIFOR/ICRAF Biodiversity in Landscape Mosaics Amazon Initiative BGBD-GEF 2007 Bali agenda renewal Interface with CC adaptation Site network… 2005 review Policy focus ASB4: ADSB/REALU Eligibility of land-scape-scale ma- nagement for REDD incentives Potential next steps…
    • 118.  
    • 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

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