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Degradation Accounting Methods Katie Goslee Program Officer, Ecosystem Services Unit Winrock International Measuring.

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Presentation on theme: "Degradation Accounting Methods Katie Goslee Program Officer, Ecosystem Services Unit Winrock International Measuring."— Presentation transcript:

1 Degradation Accounting Methods Katie Goslee Program Officer, Ecosystem Services Unit Winrock International kgoslee@winrock.org www.winrock.org Measuring and Monitoring Forest Degradation Across Asia

2 Presentation Overview  Overview of activity- and land-based accounting  Examples of each accounting method  Rationale for deciding which to use 2

3 Activity- and Land-based Accounting  Methods described by IPCC  Activity-based considers specific human activities leading to forest degradation, and estimates emissions separately for each activity.  Land-based estimates the change in carbon stocks in a specified area of land, regardless of activities occurring. 3

4 4 Land-Based AccountingActivity-Based Accounting Full accounting of all land-based emissions. Emissions combined across activities. Can capture net effect of emissions and sinks across large areas. Where multiple activities occur, it may be difficult to verify emissions. Difficulty to distinguish between effects of multiple activities. Inherently distinguishes between activities. Requires large amounts of data that are expensive to collect. Cost effective approach; complexity of methods based on each activity Measurement resolution will likely miss many localized small-scale impacts. Small scale impacts can be included by activity if deemed significant. May simplify tracking net emissions and removals from place to place or year to year. Requires development of emission or removal factors for each activity in each region.

5 Activity-based Full accounting of all land-based emissions. Can capture net effect of emissions and sinks across large areas. Difficult to distinguish between effects of multiple activities. Requires large amounts of data that are expensive to collect. Measurement resolution will likely miss many localized small- scale impacts. May simplify tracking net emissions and removals from place to place or year to year. Emissions combined across activities. Where multiple activities occur, it may be difficult to verify emissions. Inherently distinguishes between activities. Cost effective approach; complexity of methods based on each activity Small scale impacts can be included by activity if deemed significant. Requires development of emission or removal factors for each activity in each region. 5 Land-based

6 Activity-based accounting - Guyana  Limited existing biomass data  No reliable data on land use change  Most degradation from logging and small scale mining  Field work focused on areas most impacted by degradation  Some activities have yet to be included 6

7 Land-based accounting - Vietnam  National Forest Inventory with extensive biomass data  Existing data on forest cover change over 20 years Including degradation of timber stocks  Not clear which activities result in emissions from degradation  High uncertainty in areas/forest types with few plots 7

8 Rationale for accounting system  Are there existing data on forest biomass?  Is extent of land use change quantified?  Is degradation occurring across the landscape, rather than in specific areas?  Activity-based is common and cost-effective approach to degradation accounting 8

9 Monitoring Forest Degradation Emissions  Need to know magnitude and cause to design a system for degradation Difficult to detect areas of degradation with Remote Sensing Emissions estimated with emission factors and activity data Not all agents of degradation can be monitored with same approach Can use government and other statistics or social surveys  Procedures for estimating impact on C stocks already exist under IPCC for some forms, such as logging  Other forms require development of procedure 9

10 Developing a monitoring system  Simple  Based on existing systems  Affordable  Replicable & Upscaleable  Focus on areas likely subject to degradation  Include spot checking and allow some error  Verifiable 10

11 Challenges  Data consistency  Consistency of implementation  Financial resources  Technical capacity  Replicability 11

12 1. Key Concepts: C fluxes from selective logging

13 Timber harvesting  TEF = ELE + LDF + LIF Where: TEF = total emission factor resulting from timber harvest (t C m -3 ) ELE = extracted log emissions (t C m -3 extracted) LDF = logging damage factor—dead biomass carbon left behind in gap from felled tree and incidental damage (t C m -3 extracted) LIF = logging infrastructure factor—dead biomass carbon caused by construction of infrastructure (t C m -3 ) 13

14 Data for timber harvesting emissions 14 Type of dataSpecific data needsSources for Tier 1 dataSources for Tier 2 & 3 data Activity Data Timber extraction data (volume per hectare or total volume) on an annual basis FAO Global Forest Resources Assessment Government statistics, timber concession reporting, mill reporting Area of logged forest per year Limited availability in FAO Global Forest Resources Assessment (often total area of produciton forests only) Government statistics, timber concession reporting, remote sensing data Area of logging roads, skid trails, logging decks Not available Government statistics, timber concession reporting, high resolution remote sensing data Emission Factors Measurements of logged trees (ELE) Pearson et al (2014) Pearson et al (2014) correlation; Fieldwork/REDD+ NFMS Extent of incidental damage (LDF)Pearson et al (2014) Pearson et al (2014) correlation; Fieldwork/REDD+ NFMS Extent of infrastructure (LIF)Pearson et al (2014)Fieldwork/REDD+ NFMS

15 Fire emissions  To estimate GHG emissions from fire (L fire ), need: Biomass available for combustion (M B, t ha -1 ) Proportion that actually burned, combustion factor (C f ) Factor to convert to CO2e, = emission ratio (G ef, g kg -1 ) L fire = M B * C f * G ef * 10 -3 15

16 Fire emissions  L fire = M B * C f * G ef * 10 -3 Where: L fire = amount of greenhouse gas emissions from fire, t ha -1 of each GHG ha -1 e.g., CO 2, CH 4, N 2 O M B = biomass of fuel available for combustion, t ha -1. This includes biomass in all selected pools, excluding belowground biomass as this it is unlikely to burn. C f = combustion factor (proportion of pre-fire biomass that burns; from Table 2.6 IPCC 2006 GL), dimensionless. G ef = emission ratio, g kg -1 dry matter burnt (from Table 2.5 IPCC 2006 GL) for each GHG as follows: 1580 for CO 2, 6.8 for CH 4, and 0.20 for N 2 O 16

17 Data for fire emissions 17 Type of data Specific data needs Sources for Tier 1 data Sources for Tier 2 & 3 data Activity Data Total area and location of fire Global datasets Medium to high resolution RS data, field surveys Emission Factors Biomass in all relevant pools (M B ) Default valuesNFI, REDD+ NFMS Combustion factor and emission ratios (C f & G ef ) Default values Specific values if available

18 Fuelwood emissions  WISDOM approach (Tier 2) Maps woodfuel demand and supply Determines non-renewable biomass needed to meet existing demand. GHG emissions = combustion emissions and CO 2 sequestered by renewable portion of harvested woodfuel.  VCS method (Tier 3) Volume of fuelwood collected Wood density Emissions from fossil fuel combustion and biomass burning 18

19 Data for fuelwood emissions 19 Type of data Specific data needs Sources for Tier 1 data Sources for Tier 2 & 3 data Activity Data Total amount of fuelwood collected Global datasets WISDOM analysis, field surveys, statistics Emission Factors Biomass in all relevant pools Default values WISDOM analysis, NFI, REDD+ NFMS

20 Grazing emissions 20

21 Data for grazing emissions 21 Type of data Specific data needs Sources for Tier 1 data Sources for Tier 2 & 3 data Activity Data Total area and location of overgrazing Default values, literature Government statistics, field surveys Emission Factors Carbon stocks by area/forest type, before and after grazing Default values NFI, REDD+ NFMS

22 Shifting cultivation emissions 22

23 Shifting Cultivation  Pioneer shifting cultivation - deforestation  Rotational shifting cultivation Steady state if fallow period is unchanged Degradation if fallow period is shortened Enhancement if fallow period is lengthened  Monitor length of fallow RS imagery Community surveys 23

24 Data for shifting cultivation emissions 24 Type of dataSpecific data needs Sources for Tier 1 data Sources for Tier 2 & 3 data Activity Data Area of land under cultivation Local records, interviews Remote sensing (medium or high resolution), ground truthing Emission Factors Live tree carbon stocks by forest type Default valuesField inventory Carbon stocks for other forest pools, by forest type Default valuesField inventory Carbon stocks for fallow period/agriculture Default valuesField inventory

25 Thank You Katie Goslee Ecosystem Services Unit Winrock International kgoslee@winrock.org www.winrock.org 25

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