Using Spatial Information to support decision making in national REDD+ strategies
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Using Spatial Information to support decision making in national REDD+ strategies by Valerie Kapos
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This presentation, by Valerie Kapos, was given at the Global Landscapes Forum 2014, in a discussion session titled "Using spatial information to support decision making in national REDD+ strategies". The discussion forum explored the role of spatial information in planning for REDD+ and wider landscape management, drawing on national experiences associated with the UN-REDD Programme or the REDD-PAC project. Key questions addressed: Which benefits and risks of REDD+ and alternative land uses are most amenable to planning approaches based on spatial information? Which issues are less suited to using spatial information and planning approaches? How can the wide range of different sectors and stakeholders affected best be engaged in, and encouraged to provide information for planning and decision making for REDD+ and other land use policies?
Transcript of Using Spatial Information to support decision making in national REDD+ strategies
Using Spatial Information to support decision making in national REDD+ strategies
by Valerie Kapos
Contents
• REDD+ strategies & associated information needs
• Spatial data applications
• Forest distribution & change• Potential benefits• Risks• Feasibility
• From data to decisions
• Going further
National REDD+ strategies
One of 4 elements specified in Warsaw framework as needed for results based payments
Outlines policies and actions for achieving REDD+ outcomes, including what, how, and . . . where
1. National REDD+ strategy or action plan
2. National forest reference emission level and/or reference level
3. National forest
monitoring system
4. Safeguard Information System
National REDD+ strategies
Which actions are most appropriate for REDD+ implementation depends on
Drivers of deforestation and forest degradation
Potential for social and environmental benefits and the priority attached to them
Potential risks
. . .
Many of these factors vary spatially
Spatial data on forest cover and change
• Inform development of country definitions of forest and deforestation
Natural forest?
LULC map dfn• Montane & lowland forest
National dfn of forest-TZ(10% canopy c + 2 m height)•Montane & lowland forest•Woodland•Mangrove•Bushland (>2m)•Thickets (>2m)
FAO FRA + NAFORMA(10% canopy c + 5 m height)•Montane & lowland forest•Woodland•Mangrove
Spatial data on forest cover and change
• Inform development of country definitions of forest and deforestation
• Help to identify drivers of deforestation and vulnerable areas and therefore where different types of action are needed and appropriate
• Past deforestation
• Modelled future deforestation
Where is forest under pressure?Modelled future deforestation in Panama - low impact scenario (SCNBI) - DINAMICA-EGO model
Potential Benefits from REDD+ vary spatially
Biomass carbon stocks Importance for biodiversity
Importance for soil erosion controlImportance for tourism
Biodiversity and ecosystem services are distributed unevenly; spatial data help identify areas important for different benefits and combinations of benefits
Where can REDD+ action help to deliver benefits in addition to mitigation?
Potential risks e.g. restricting access to NTFPs
Feasibility and costs
Feasibility and costs of different REDD+ actions vary with factors that vary spatially including:
• Local management regimes
• Local priorities
• Alternative land uses
• Agriculture
• Mining and other concessions
From data to decisions
Combining information on forest distribution, drivers of change, potential benefits, feasibility - Forest restoration opportunities, Paraguay
From data to decisions
Combining information can help identify priority areas
Involving a wide range of stakeholders can increase ownership of results
Going further
• Including economic information
• Including scenario assessments• Exploring how drivers, benefits, risks and context will change
into the future
• Can range from using participatory scenario development and conceptual models to
• Complex economic models
• Using scenarios and modelling for spatially explicit assessment of impacts of different policy options
• Integrated land use planning
