Forest Carbon Accounting for REDD+ Readiness at District and FMU Level Experiences from Kalimantan

Transcription

1 Indonesian-German Forests and Climate Change Programme (FORCLIME) Forest Carbon Accounting for REDD+ Readiness at District and FMU Level Experiences from Kalimantan Jakarta, Franz-Fabian Bellot GIZ FORCLIME

2 Content 1 The context deforestation and degradation in Indonesia 2 Forests and Climate Change Programme (FORCLIME) 3 Forest Carbon Accounting at district and FMU level 4 Examples and use of FCA results 5 Conclusions, challenges and outlook

3 Deforestation in Indonesia Source: NFMS, Ministry of Forestry, 2014

4 Problem Tree - Drivers of Deforestation & Degradation in Indonesia Principle of sustainable development Lack of leadership SPATIAL PLANNING Lack of data and information Unitegrated sectoral planning Land tenure conflict TENURIAL ISSUES Low stakeholder participation Unclear forest area boundary Indigenous people s rights unrecognized Limited livelihood options FOREST MANAGEMENT Insufficiency of forest management Low performance of FMU Low integrity and capacity of human resources DEFORESTATION Economic growth target Gap of supply and demand Planned Deforestation Unplanned Deforestation Illegal Logging Forest Fires Low of participation transparancy and accountability Lack of effectiveness and efficiency Lack of coordination Corruption and collusion Lack of law enforcement Overlapped legal basis Contradictive and unclear laws AND DEGRADATION GOVERNANCE LAW ENFORCEMENT

5 The key question: How to set up efficient framework conditions, governance structures and capacities for emission reduction from land use sector (REDD+/NAMA)?

6 Forests and Climate Change Programme 3 districts in Kalimantan (Kapuas Hulu 1, Berau 2, Malinau 3 ) Objective: Reduction of emissions from the forestry sector Conservation of forest biodiversity within HoB Implementation of sustainable forest management Partner: KLHK Duration:

7 FORCLIMEs multilevel approach towards CC mitigation actions by setting up the REDD+ architecture at district level (e.g. Kapuas Hulu) Macro level: Support district governments in setting up a district wide FREL & MRV team and benefit sharing scheme Meso level: Support Forest Management Units (FMUs) as smallest permanent and jurisdictional unit responsible for climate change mitigation activities in the forest sector Micro level: Set up REDD+ demonstration activities (DA) as pilots for project based forest carbon accounting, MRV and performance based payment

8 FORCLIME s Solution Tree for improved forest governance SPATIAL PLANNING TENURIAL ISSUES FOREST MANAGEMENT REDD+ Strategy National GHG Reducion Plan (RAN-GRK) Forest Sector Reform (FMU) Participatory Land Use Planning (PLUP) Carbon Stock Maps Land tenure conflict resolution mechanisms Participatory Mapping Village Forest utilization rights Alternative livelihood options (NTFPs /agroforestry) Reduced impact logging (RIL) Strengthening FMU organization Improved capacities for good local forest governance at FMU and DA level Increased cooperation between FMUs CSO, private sector and communities Land Cover Maps Set up MRV Teams Community Transparent Forest Patrolling Financial Management Schemes for FMUs (BLUD) FMU Patrolling Revision of Forest Regulations Community Based Forest Management (afforestation/ rehabilitation) Sustainable forest management, climate change mitigation (REDD+), biodiversity conservation livelihood improvement GOVERNANCE LAW ENFORCEMENT

9 FORCLIME Carbon Accounting Methodology Land cover driven approach with wall-to-wall coverage at district level Comparable and integratable into other FCA systems Image acquisition Pre-processing of satellite images Develop land cover classification scheme Ground truthing Object-based classification Accuracy assessment Carbon accounting LC change and deforestation analysis Identification of drivers of deforestation

10 FORCLIME Carbon Accounting System Defining the historic REL (IPCC Tier-2) Based on Landsat imagery (30m resolution) Object based classification and change detection Emission factors (EF) from literature (from Indonesian archipelago) Main Outcomes: -> Land cover maps for 1990, 2000, 2005, > Land cover change maps -> Analysis of drivers of deforestation and degradation -> Quantification of historic and future emissions

11 Getting to IPCC Tier 3 LiDAR flights Satellite images RapidEye imagery Field inventory Modeling Land cover classification Upscaling Stratification Carbon stock map

12 Development of carbon stocks in Kapuas Hulu ( )

13 Deforestation, drivers and emissions in Malinau

14 Differentiation of deforestation by forest function in Berau

15 Quantification of emission reduction potential in Berau Forest Cover: ha Status 2010 Forest cover Clouds Other land cover

16 Quantification of emission reduction potential in Berau APL: ha KH: ha SKH942 APL HL, HP, HPK, HPT

17 Quantification of emission reduction potential in Berau Forests on APL: ha Pri. Sec. Hill/Sub-montane Dipterocarp Forest Lowland Dipterocarp Forest Mangrove

18 Quantification of emission reduction potential in Berau Conservation of Primary Forests on APL 144,77 Mt CO2 Conservation of Secondary Forests on APL 47,54 Mt CO2

19 Conclusions FORCLIME FCA system serves different conceptual MRV approaches (e.g. REDD+, NAMA/LAMA) and allows: Quantify rates of deforestation, degradation, carbon emissions Identify drivers of DD and drivers of carbon emissions Set up of a district based MRV for land-based emissions (LULUCF) -> Tier 3 Provide data and information for low carbon development activities including land swap and sustainable forest management Requirements for integration on different levels (e.g. upscaling, consistency with NAMA): Baseline time period must be the same Classification must satisfy national and international requirements Agreed national Emission Factors must be used when sub-national data is integrated into national reporting

20 Challenges Carbon accounting and forest inventory Cloud cover -> acquisition of remote sensing data Limited accessibility -> ground truthing Expensive and time consuming Technical expertise not always available Reference Emission Level (REL) Determination of key REL components High implications on emission reduction targets Measurement, Reporting, Verification (MRV) Datasets with different topologies Setup and data structure unclear Institutional responsibilities unclear

21 Further support towards Indonesia s REDD architecture Provide lessons learnt from district REL/MRV experiences to national level Support districts in setting up local FREL & legalization in line with national FREL Support capacity development of district MR(V) teams & institutions Promote FMUs as REDD+ vehicle for improved forest governance and MRV Development of a methodology to compare RIL Emissions to BAU

22 Thank you!. Danke.Terima kasih! FORCLIME Forests and Climate Change Programme Technical Cooperation (TC Module)