Agenda 25-5-09

• Welcome• Introductions• Plan for the week• Overview of project• Where we are now with the EU• Project Operation

– Project Management Team– Programme Advisory Committee– Matched funding– Annual Project Meeting – COP-15, Copenhagen?– Logo– Website– Communication issues within the project?– Risk management

• Workplans

Key questions

• What scales should we focus on?• Linkage to the negotiation process?• What do we mean by anthropogenic emissions –

e.g. natural peatlands?• Who are the relevant actors that we need to

identify?• What policy information is useful for modelling?• How do we take into account leakage,

permanence, additionality within the project?• How do disseminate results wider than just the

case study countries?

WP1

WP2

• C stock estimation – uncertainty• Mitigation costs – marginal abatement cost

curves• Good knowledge from Indonesia, need to find out

more about other study countries• Vietnam – GHG, forestry inventory, allometric

equations, monitoring forest change – RS data

WP3

• Quantifying GHG emissions from forest cover change• Most focus so far on AGB – will improve CO2 emissions

estimations from soil, particularly sub-soil (>30cm depth) – all field sites

• Improve methodologies for non-CO2 gases – N2O emissions depends on intensity of subsequent land use (fertiliser use) – focus on Jambi

• Literature review• Relatively simple models• Need: detailed land use maps, soils maps if possible –

site selection; Jambi - land use history (burning, etc.)• Forest fire – major CO2 loss• Deep peat soils (>16m) – subsidence, relative

importance of CH4/CO2/N2O

WP4

• REDD hasn’t come out of the blue• Forest policy architecture – how do REDD policies

relate to others?• What policy options have worked in the past?• Provide policy options/scenarios for modelling

work• Local level impacts?• Integrate global/local levels?• Identification of relevant actors, and their

networks• Peter Minang will be ICRAF representative in this

WP.

WP6

• Fairness vs. efficiency• Relationship to COP15?• Hotspots• Discussion tools – needs to be a combination of fairness

and efficiency• Forest use rights for local community• Improvements in governance in landscape may be more

important than REDD benefits• REDD issues may need presenting in other contexts –

different ‘languages’• Value chains• REDD ‘projects’ not feasible – need to be higher scales

(additionality, etc.) – what about international leakage?• Certainty at different scales varies• How are national level agreements translated into sub-

national agreements?

REDD-ALERT: Reducing Emissions from Deforestation & Degradation

through Alternative Land Uses in the Rainforests of the Tropics

Robin MatthewsClimate Change Theme Leader

Macaulay InstituteAberdeen AB15 8QH

United Kingdom

REDD-ALERT Kick-off workshop, May 25, 2009

REDD-ALERT

• Macaulay Land Use Research Institute, United Kingdom

• Université Catholique de Louvain, Belgium

• Vrije Universiteit Amsterdam, Netherlands

• Georg August University of Göttingen, Germany

• World Agroforestry Centre, Kenya

• Centre for International Forestry Research, Indonesia

• International Institute of Tropical Agriculture, Nigeria

• Centro Internacional de Agricultura Tropical, Columbia

• Indonesian Soils Research Institute, Indonesia

• Research Centre for Forest Ecology and Environment, Vietnam

• Institut de Recherche Agricole pour le Développement, Cameroon

• Instituto Nacional de Investigacion y Extension Agraria, Peru

EU-FP7 ProjectREDD-ALERT

Reducing Emissions from Deforestation and Degradation through Alternative Landuses in

Rainforests of the Tropics

Linking global agreements to local action

Overall goal: To contribute to the development and evaluation of mechanisms and the institutions needed at multiple levels for influencing stakeholder behaviour to slow tropical deforestation rates and hence reduce GHG emissions

Project objectives

• Documenting the diversity in social, cultural, economic and ecological drivers of forest transition and conservation, and the consequences, in the contexts of selected case study areas in Indonesia, Vietnam, Cameroon, and Peru as representative of different stages of forest transition in Southeast Asia, Africa and South America.

• Quantifying rates of forest conversion and change in forest carbon stocks using improved methods.

• Improving accounting (methods, default values) of the consequences of land use change for GHG emissions in tropical forest margins including peatlands.

• Identifying and assessing viable policy options addressing the drivers of deforestation and their consistency with policy approaches on avoided deforestation currently being discussed in UNFCCC and other relevant international processes.

• Analysing scenarios in selected case study areas of the local impacts of potential international climate change policies on GHG emission reductions, land use and livelihoods.

• Developing new negotiation support tools and using these with stakeholders at international, national and local scales to explore a basket of options for incorporating REDD into post-2012 climate agreements.

Project components

WP7: Overall project management

WP5: Integration and modelling

WP6: Development of REDD Negotiation Support System

WP1: Understanding the drivers of

land use change

WP3: Quantifying

GHG emissions from land use

change

WP2: Quantifying

and monitoring land use change

WP4: Policy options

addressing tropical

deforestation

WP7: Overall project management

WP5: Integration and modelling

WP6: Development of REDD Negotiation Support System

WP1: Understanding the drivers of

land use change

WP3: Quantifying

GHG emissions from land use

change

WP2: Quantifying

and monitoring land use change

WP4: Policy options

addressing tropical

deforestation

WP5: Integration and modelling

WP6: Development of REDD Negotiation Support System

WP1: Understanding the drivers of

land use change

WP3: Quantifying

GHG emissions from land use

change

WP2: Quantifying

and monitoring land use change

WP4: Policy options

addressing tropical

deforestation

Site locations

Ucayali, Peru Southern Cameroon Indonesia Vietnam

WP1: Drivers of deforestation

• Humid tropics: combination of:– commercial wood extraction– conversion to cropland– livestock development– extension of overland transport infrastructure

• Southeast Asia– timber concessions, plantations (paper, palm oil)– slash-and-burn agriculture

• Latin America– road building followed by migrant settlers practising

S&B– pasture creation for cattle

• Africa (Congo Basin)– smallholder agriculture– commercial logging– fuelwood (Geist & Lambin, 2002)

WP1: Forest transitionsF

ore

st c

ove

r (%

)

time

Undisturbedforests

Forest frontiers

Forest, agricultural

mosaics

Forest, agricultural mosaics, plantations

Cameroon Benchmark sites

Vietnam

Indonesia, Peru

?

?

?

WP2: Measuring and monitoring D&D

• C stocks = f(forest area, C density)

• What is a forest?– Continuum forced into

binary classification– ‘Forest without trees’,

‘trees outside forest’• Institutional definition of

a forest – e.g. intent to replant

• Agroforestry, e.g. rubber agroforests

– Hierarchical legends: ‘forest’, ‘tree-based systems’, ‘open-field agriculture’, but possibly more to minimise uncertainty

WP2: Carbon densities

• C densities – degradation more serious than deforestation?– Degradation: 300 to 50 t

C ha-1 250 t C ha-1 lost– Deforestation: 50 to 0 t C

ha-1 50 t C ha-1 lost– C density data for

hierarchical categories update databases

• Need to incorporate soil changes: time-averaged C stock

• Limiting factor is time series data rather than spatial resolution

(from F. Achard, JRC)

WP3: GHG emissions from D&D

• Tier 1 focus on changes in C stocks in above-ground biomass – plan to quantify root biomass also (to 3 m)

• Soil C – most studies only in top 30 cm – plan to quantify to 3 m

• Significant CO2 and N2O released from soil following conversion of forest

– Measurement and modelling of GHG emissions from ‘hotspot’ land use change – oil palm plantations, deforested peatlands

• Methodologies to extrapolate to larger spatial and temporal scales

– Controlling variables: N availability, soil aeration status

– Can proxy variables be used? e.g. C/N ratio of litter, δ15N signatures of litter & soil

– Large soil variability: infra-red spectral analyses of the soils as covariates in the model

WP4: Policy and governance issues

• Previous attempts have not always been positive due to:– ‘Politics of scale’, i.e. decisions/concerns at global level don’t

translate to those at a local scale– Lack of synergy at all levels between forestry and other

policies

• Looking for win-win policies – beneficial for GHG emissions reduction as well as local communities

• Aim to synergise the interests of different actors at different levels into a coherent multi-level policy framework

• Analyse trade-offs between CC policies (e.g. biofuels, C sequestration) and the larger goal of sustainable forestry

• Develop a menu of viable policy options to tackle REDD under the international climate regime

WP4: Policy framework

Policy incentives

Human activity

Drivers & barriers

Reduced deforestation

Policy design

Forestry regime

Climate regime

National policy

Policy incentives

Human activity

Drivers & barriers

Reduced deforestation

Policy design

Forestry regime

Climate regime

National policy

Forestry regime

Climate regime

National policy

WP5: People and Landscapes Model

• Household agents– decision-making– inter-household interactions

• imitation of successful strategies

• buying/selling commodities• Patches on a landscape

– CENTURY soil organic matter model

– Ritchie water balance model– DSSAT crop models– Trees model

• Livestock model

Papers• Matthews, R.B., 2002. Chapter 15 in Crop-Soil Simulation Models: Applications in Developing Countries (R.B. Matthews &

W. Stephens, Editors), CAB International, Wallingford, UK, pp. 209-230.• Matthews, R.B. & Pilbeam, C.J., 2005. Paper presented at MODSIM05 conference, Dec 9-12, 2005, Melbourne, Australia.• Matthews, R.B. & Pilbeam, C.J., 2005. Agriculture, Ecosystems & Environment 111(1-4):119-139.• Matthews, R.B. et al., 2005. Paper presented at MODSIM05 conference, Dec 9-12, 2005, Melbourne, Australia.• Matthews, R.B., 2006. Ecol. Modelling 194(4):329-343.

WP5: Policy instruments

• PALM model: Combining agent-based and biophysical modelling

• All instruments can encourage land managers to choose low emission options

• But– taxes reduce farmer returns– incentives require external

money

• Combination of taxes and incentives may be cost-neutral

• Feasibility of carbon trading in the land use sector

WP6: Changing peoples’ behaviour

• Challenge is how national level targets will be translated to changes in the behaviour of the people who will be expected to reduce deforestation activities

• Salience (relevance)• Legitimacy – findings by foreign research groups not

necessarily accepted – reconfirmation by local scientists –e.g. CO2 emissions from Indonesia’s peatlands

• Credibility • Synthesise peoples’ perceptions, fears, ambitions &

expectations– Q-methodology and Analytical Hierarchy Process techniques

• Role-playing games to explore benefit-sharing mechanisms

• Negotiation Support System (NSS) approach rather than Decision Support System (DSS)

WP6: Participatory scenario analysis

• narrative conceptual model• agent-based spatial

computational model (ABM)• role-playing game• multiscale GIS

SAMBA-GIS (Vietnam)

(Castella et al., 2005)

• Stakeholders exposed to other viewpoints of same problem

• ‘Buy-in’ and trust in models by participants more important than numerical accuracy- Van den Belt (2004)

Pert diagram

WP1: Mapping forest cover change

WP1: Econometric model of LUC drivers

WP2: Abatement cost analysis

WP2: Spatial C stocks analysis

WP2: Cost/benefit analysis of national monitoring systems

WP3: Soil organic C measurements

WP3: Biomass C measurements

WP3: GHG flux measurements

WP4: Global policy model

WP4: Multi-level policy instruments

WP5: IPCC AFOLU Tier 3 model

WP5: Development of coupled-human-

environment model

WP5: Evaluation of policy instrumentsWP6: Synthesis of local

perceptions of deforestation policies

WP6: Local stakeholder Negotiation Support

System

WP6: National Representative

Negotiation Support System

WP6: Testing stakeholder perceptions of

deforestation policies

WP1: Mapping forest cover change

WP1: Econometric model of LUC drivers

WP2: Abatement cost analysis

WP2: Spatial C stocks analysis

WP2: Cost/benefit analysis of national monitoring systems

WP3: Soil organic C measurements

WP3: Biomass C measurements

WP3: GHG flux measurements

WP4: Global policy model

WP4: Multi-level policy instruments

WP5: IPCC AFOLU Tier 3 model

WP5: Development of coupled-human-

environment model

WP5: Evaluation of policy instrumentsWP6: Synthesis of local

perceptions of deforestation policies

WP6: Local stakeholder Negotiation Support

System

WP6: National Representative

Negotiation Support System

WP6: Testing stakeholder perceptions of

deforestation policies

Management structure

WP1WP coordinator

Task Leader

WP2WP coordinator

Task Leader

Project Advisory

Committee

WP3WP coordinator

Task Leader

WP4WP coordinator

Task Leader

WP5WP coordinator

Task Leader

WP6WP coordinator

Task Leader

Project Management Team

WP7Project Coordinator

Project AdministratorRisk Officer

strategic advice

WP coordinators

risk issuesWP management

day-to-day project

management

strategic decision-making

WP1WP coordinator

Task Leader

WP2WP coordinator

Task Leader

Project Advisory

Committee

WP3WP coordinator

Task Leader

WP4WP coordinator

Task Leader

WP5WP coordinator

Task Leader

WP6WP coordinator

Task Leader

Project Management Team

WP7Project Coordinator

Project AdministratorRisk Officer

strategic advice

WP coordinators

risk issuesWP management

day-to-day project

management

strategic decision-making