RESTORE+: Addressing Landscape Restoration for Degraded Land in Indonesia and Brazil Picture credit Stora Enso
IMPORTANCE OF RESTORATION Bonn Challenge and Global Partnership on Forest Landscape Restoration aim at restoring 150 million hectares of deforested and degraded land by 2020, and additional 200 million hectares by 2030. Means to achieve the CBD Aichi Target 15, the UNFCCC REDD+ goal, the Rio+20 land degradation neutrality goal, the Sustainable Development Goal 15 Picture credit Stora Enso 2
WHAT TO RESTORE? UNEP Global Assessment of Soil Degradation (GLASOD): 1,2 billion ha FAO's Global Assessment of Lands Degradation and Improvement project (GLADA): 2,7 billion ha FAO Terrastat (Bot et al, 2000): 6 billion ha Global estimates of total degraded area vary from less than 1 billion ha to over 6 billion ha, with equally wide disagreement in their spatial distribution. (Gibbs and Salmon, 2015) Picture credit Stora Enso 3
FOREST LANDSCAPE RESTORATION (FLR) is an ongoing process of regaining ecological functionality and enhancing human well-being the majority of restoration opportunities are found on or adjacent to agricultural or pastoral land. In these situations, restoration must complement and not displace existing land uses. cross-sectoral, multi-stakeholders and cross-jurisdiction requires a bottom-up approach e.g. Restoration Opportunities Assessment Methodology (ROAM) by IUCN and WRI 4
How do we assess large scale (i.e. national or regional) landscape restoration potential? Are current targets realistically ambitious (together with the expected co/multiple benefits)? How should we formulate operational restoration policies that ensure environmental integrity and social benefits? Picture credit Stora Enso 5
THE RESTORE+ PROJECT: QUICK FACTS Countries of Implementation Indonesia and Brazil (with limited activities in the Congo Basin area) Project duration 5 years (2017-2022) Type of activities Capacity Building (enhancement of methods, datasets and institutional capacity) Funding support Partner institutions in countries of implementation Project partners Indonesia: Ministry of National Development Planning/BAPPENAS, Ministry of Environment and Forestry Brazil: Brazilian Cooperation Agency (Foreign Office), Ministry for the Environment 6
RESTORE+ METHODOLOGY: A SYSTEMS PERSPECTIVE Identifying degraded land: Exploring possible definitions of degraded land including social and biophysical consideration Assess land degradation through analysis of high resolution (satellite) imagery Big earth observation data analysis Crowdsourcing and grass-root engagement Assess implication of using different degraded land definitions in: Vegetation modelling to project carbon stock, potential yield under different restoration measures etc. Biodiversity assessment (priority areas, species, biodiversity modelling) Assess sectoral interaction of Food-Land-Energy nexus: Projection scenarios for production and trade of forestry and agriculture (food) commodities Land use/cover projection scenarios based on spatially explicit bottom-up informed economic models Assess bioenergy supply chain in its interaction with the overall energy system Assess market support for sustainability safeguards 7
REMOTE SENSING LIMITATION IN IDENTIFYING DEGRADED LAND RESOURCES Biomass map by Saatchi et al. (2011) better corresponds to land cover in Cameron 4 00 N 9 50 E (right side) Biomass map by Baccini et al. (2012) better recognizes water bodies in Congo 3 41 S 10 59 E (left side) Detecting degradation from remotely sensed data, especially with the most commonly used forms of medium spatial resolution data, is difficult because the scale at which the degradation takes place is often at sub-pixel resolution. (FAO, 2016) 8
ENGAGING GRASS ROOT ACTORS Visualization of land cover data sets, suitability maps, land use information, biomass, etc. Crowdsourcing of land cover analysis Creation of Hybrid Land Cover Maps Citizenempowered Scientific Assessment Validation of Land Cover Maps In-situ Data validation using mobile apps Serious Games (Cropland Capture) 9
REALISTIC ESTIMATES OF LAND AVAILABILITY USING CROWDSOURCING Cai et al., 2011 1107 mil. ha Fritz et al., 2013 375 mil. ha Fritz et al, 2013, Environmental Science and technology 10
BIOPHYSICAL VEGETATION MODELLING (1) Biophysical forest modelling Provides annual harvestable wood (for sawn wood and other wood) Forest management (rot/spec) Forest Carbon stock Harvesting costs Forest area change Spatially explicit Total Cabon Production / Maximum Carbon Production 0.0 0.2 0.4 0.6 0.8 1.0-0.1-0.3-0.5-1 -3-10 0.0 0.2 0.4 0.6 0.8 1.0 Age / Max Age Input Data Sets NPP Population Density Land cover Agricultural suitability Forest Biomass Price level Discount rate Money efficiency Product use 11
BIOPHYSICAL VEGETATION MODELLING (2) Biophysical agriculture model Weather Hydrology Erosion Carbon sequestration Crop growth Crop rotations Fertilization Tillage Irrigation Drainage Pesticide Grazing Manure Rain, Snow, Chemicals Below Root Zone EPIC Surface Flow Evaporation and Transpiration Subsurface Flow Major outputs Crop yields, Environmental effects (e.g. soil carbon, ) 20 crops (>75% of harvested area) 4 management systems High input, Low input, Irrigated, Subsistence 12
ECONOMIC LAND USE DECISIONS 13
EXAMPLE: FOREST PROJECTIONS Business as usual (400 Mha) Forest Code (430 Mha) 14
ACCESSIBILITY AND SPATIAL OPTIMIZATION Power plants Bioenergy contribution in an optimized energy system 15
LAND-ENERGY NEXUS Geothermal contribution in 23% renewable energy target scenario TWh Geothermal contribution when excluding primary forests TWh 16
LAND-ENERGY NEXUS Biomass harvesting in 23% renewable energy target scenario MWe Biomass harvesting when excluding primary forests MWe 17
CONTRIBUTION TO POLICY FORMULATION Brazil INDC presented at COP-Paris 2016 On 28 September 2015 Brazil announced an unconditional target of a 37% reduction of greenhouse gas emissions by 2025 below 2005 levels including LULUCF. The INDC also contains a subsequent indicative contribution of 43% below 2005 levels by 2030. Picture credit Stora Enso Potential contribution to Indonesia s National Development Plan 18
RESTORE+ METHODOLOGY: FROM INDONESIA AND BRAZIL TO THE TROPICS Identifying degraded land Assess implication of using different degraded land definitions Assess sectoral interaction of Food-Land-Energy nexus 19
RESTORE+: Addressing Landscape Restoration for Degraded Land in Indonesia and Brazil Picture credit Stora Enso