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Moving on From Experimental Approaches to Advancing National Systems for Measuring and Monitoring Forest Degradation Across Asia Moving on From Experimental Approaches to Advancing National Systems for Measuring and Monitoring Forest Degradation Across Asia June 16-18, 2015 Bangkok Logging (Planned and Unplanned): Activity Data & Emission Factors for an integrated, scalable system Dr. Sandra Brown Senior Scientist Winrock International

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Importance of selective logging to global carbon emissions Gross emissions from timber producing countries significant but poorly known at global scale Ranges from about 7% (e.g. Brazil and Indonesia) to about 40% (e.g. Republic of Congo and Malaysia) of deforestation emissions Under sustainable forest managementemissions exceed regrowth for several decades or more and not C neutral Very difficult to monitor activity data with remote sensing imagery with a high degree of confidence Can obtain higher resolution data but at added cost

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Important direct drivers of degradation From Hosonuma et al., 2012 Proportion of forest degradation drivers Tropical Asia: Commercial timber production about 80-85% of total degradation Latin America: Commercial timber production > 70% of total degradation Africa: Fuel wood collection, charcoal production, followed by timber production

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4 Carbon dioxide Damage is not contiguous Timber extraction decreases the stocks in live biomass and increases the stocks in dead wood. -Skid trails -Roads -Landing decks Collateral damage Wood products Estimating emissions from selective logging LIF LDF ELE

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Hybrid system for estimating emissions from logging Developed an efficient and effective hybrid system based on: field data to estimate carbon losses and Emission Factors volumes of timber produced Activity Data high resolution satellite imagery for infrastructure Activity Data

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Estimating emissions for selective logging Logging components that impact C emissions: Quantity of extracted timber Portions of timber tree left in forest (crown, stump) Incidental damage to surrounding trees (the increase in dead wood resulting from felling and extraction) Logging infrastructure (skids, log landings, and roads) Relate total selective logging carbon emissions to easily measurable parameters Volume of timber extracted (m 3 ) > easier to track Area of roads and decks and lengths of skid trails from imagery

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Strategies for estimating EFs Forest lands undergoing selective logging activities must be identified. Sampling must take place very soon after felling timber treesif possible while timber tree is still in the forest Hard to assess damage if not sampled quickly Avoids miscounting from regrowth Reduces uncertainty for key parameters Sampling plans should be designed to meet a targeted or required level of certainty and to meet international standard of representative, unbiased, consistent, transparent, and verifiable.

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Gross Carbon losses or emission factor due to selective logging are estimated as: EF (t C) = (ELE + LDF)*V T + sum[LIF*A i ] Where: ELE = extracted log emissions (t C/m 3 extracted) LDF = logging damage factordead biomass carbon left behind in gap from felled tree and incidental damage (t C/m 3 extracted) V T = total volume over bark extracted (m 3 ) LIF = logging infrastructure factordead biomass carbon caused by construction of skid trails, roads, decks (t C/ha) A i = area of infrastructure skid trails, roads and decks (ha) Field data are collected from multiple logging gaps and skid trails, and RS data for roads and decks( refer to Pearson et al. 2014 - http://iopscience.iop.org/1748-9326/9/3/034017/article ) http://iopscience.iop.org/1748-9326/9/3/034017/article Estimating EF for selective logging

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Extracted Log Emissions (ELE) Estimate volume extracted (volume of a conical frustum) and convert to biomass =volume *species specific wood density Apply the appropriate allometric equation to the parameters of the felled tree (e.g. DBH, wood density) to estimate aboveground biomass Biomass left in forest = biomass of felled tree-biomass of volume extracted Conical Frustum (cone with top sliced off)

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Measure DBH of all surrounding trees fatally damaged due to timber tree falling Includes snapped and uprooted trees Measure broken branches from surrounding trees Estimate damaged biomass by applying appropriate allometric equations for damaged trees Logging Damage Factor (LDF)

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Sum all dead biomass left in plot: Top+stump+pieces left in forest (biomass of Timber Tree biomass of log) Incidentally damaged trees (snapped + uprooted + broken branches) Repeat for all plots and estimate mean LDF Logging Damage Factor (LDF)

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Estimating Logging Infrastructure Factor (LIF) Use high resolution imagery (e.g. RapidEye) to obtain deforested areas of roads and landing decks (Activity Data) LIF is the C stock of adjacent forest For skid trails Direct measurements of a sample of trails including measures of length and width =Area (Activity Data) Estimate biomass of damaged trees from DBH & species of damaged trees that are snapped, broken, uprooted by skidder using allometric equation

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Example of estimating total emissions C emissions, t C/yr = [vol x ELE)]+[vol x LDF]+[A I x LIF][vol x ELE)][vol x LDF][A I x LIF] C = [(500*10) x 0.36] + [(500*10) x 1.05] + [23 x 190] +[19 x 110] C = 1,800 + 5,250 + 6,460 C = 13,510 t C ~ 49,537 tCO 2 Concession TBD Inc. constructs 19 ha of skid trails and 23 ha of roads to harvest 10 m 3 /ha on 500 ha in 2013. No decks are built as logs are piled alongside wide roads. Assumed factors: ELE= 0.36 t C/m 3 LDF= 1.05 t C/m 3 LIFroad= 190 t C/ha LIFskid= 110 t C/ha