1. 1 Methodologies of Carbon Estimation By Zahabu, E & Malimbwi, R.E Department of Forest Mensuration and Management (SUA)

2. 2 Introduction  Carbon trade involves the sale of carbon credits.  There are two main types of Carbon Trading Schemes that are operating globally to-date:  Voluntary Carbon Trading (VCT), and  The official Kyoto Protocol Carbon Trading Mechanisms.  Carbon benefit of any forest carbon project = carbon changes to known levels of precision.  Determination of carbon changes requires baselines

3. 3 Baselines  Baseline: historical trends against which additional carbon benefits as a result of carbon project can be determined.  Baseline and monitoring schemes  individual project,  regional e.g Eastern Arc, and  national levels  Requires reliable data on forest extent and stocking.

4. 4 What Should be Measured?  Forest Extent  Forest Stocks in Five IPCC pools:  aboveground,  belowground,  litter,  dead wood and  soil organic carbon  Widely accepted forest inventory procedures recommended by IPCC Good Practice Guide (IPCC, 2003)  CDM Approved LULUCF methodologies.

5. 5 Measurable Carbon changes  Sequestration/Enhancement  increases of forest biomass within areas of existing forest  Conservation  maintenance of a steady level of forest area and biomass density,  relate to forests that are already properly managed, e.g  protective forest reserves and  national parks  could be rewarded through a special “conservation” under REDD.  Reduction in emissions from deforestation  i.e. based on comparisons of rates of change of forest area over time,  Reductions in emissions from degradation  reductions in biomass/carbon stock in the forest without loss of forest area,

6. 6 Principles of Baseline Construction  Net-net accounting:  compares emissions or removal in the commitment period to those of a reference scenario i.e historical base year (e.g. 1990) or base period (e.g. 1990- 2000),  Gross-net accounting:  Measurements of change of carbon stock are compared only over the commitment period itself.  Measure stock at the beginning of the project and compares this to the future

7. 7 Baseline for Deforestation  Principle:  a reference scenario from a historical period and net-net accounting.  Based on remotely sensed data over a historical period which shows change in area covered by forest.  Then data on carbon stock in different types of forest are used to calculate the change in terms of tons of carbon.  May be projected into the future and used to credit the additional mitigation benefit of the project  Challenges:  Setting reference base year  Carbon stock data highly variable: national forest inventory not undertaken  Assumes carbon stock per unit area is constant

8. 8 FAO: FRA 2005  Tanzania used satellite imagery interpreted data of:  1984 (Millington and Towsend, 1989) and compared these with  1995 Hunting Technical Services (1997) for the determination of land cover changes in the country.  Annual deforestation = 412,000 ha  Average stocking 36 m3/ha from CEEST, (1999)  Carbon data are reported with their statistical confidence intervals (expressed as  values) at known precision level.  Most previous studies had low precision levels due to low sampling intensity adopted.  Moreover, they cover only a few forests.

9. 9 Baseline for Degradation  Look at rates of biomass loss within the forest  This is not visible in remote sensing  Need ground measurements: No previous quality data  Possible to use one of the following techniques:  advanced remote sensing techniques (LiDAR),  harvesting estimates from the local people,  harvesting estimates from stumps counts,  default values (rule of thumb)/modelling, or  harvesting estimates from control sites.  Will be captured together with enhancement under gross-net accounting

10. 10 Degradation Recover toward the threshold Normal growth pattern Time (years) Growth Start of mgt Forest Degradation & Enhancement Baselines Baseline Degrd. Present stock Productive For Present stock Protective for. Start Measurements  No previous data on forest degradation & enhancement  Protective forest: to determine the rate of recovery  Productive forests: to determine the rate of degradation

11. 11 Establishment of Baseline at National Level  Carryout national forest inventory to establish deforestation rates and stocking levels  Determine land use cover changes for the period of 1975 to 1990 to 2000 to 2007 using Landsat TM (FAO, 2007)  Conduct case studies to quantify emission factors for different forest types  Identify drivers of deforestation  Training on national forest inventories and remote sensing  Development of tools for assessment and monitoring of deforestation  Monitoring in PSP/LiDAR technology to capture forest enhancement and/or degradation levels.

12. 12 Establishment of Baselines at Projects Level  Review and synthesize existing studies on degradation/ growth rates  Development and testing of methodologies to measure and monitor enhancement and/or forest degradation  Development of tools, guidelines and manual for degradation assessment and monitoring  Carryout assessment and monitoring of forest degradation in demonstration projects for establishing historic degradation emission factors including cost implications, and accuracy level

13. 13 Carbon Assessment & Monitoring by Local Communities  This is a strategy to involve local communities in order to reduce the transaction costs of measuring carbon  Local communities were trained and tasked to conduct the measurements  Techniques were developed to measure and monitor carbon stock.  They are: User friendly to the users - i.e.to the communitiesUser friendly to the users - i.e.to the communities reliable andreliable and presented in a format acceptable to the scientific communitypresented in a format acceptable to the scientific community

14. 14 The equipment Consists of:  A handheld computer with ArcPad TM 6.0 software and connected to GPS  It is easy to use  Is used to locate:  forestry boundaries  sample plots and  recording measurement data  With a step-by-step guide to the procedures, local communities were trained in a short time and were able to use the system effectively

15. 15 Steps in Carbon Assessment i.Forest mapping/stratification ii.Pilot survey to estimate variance and number of sample plots iii.Locate the sample plots on the ground iv.Measure the dbh of all trees v.Set out the sub-plots for the grasses, herb and litter data vi.Take soil samples randomly within the plot

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18. 18 Locating sample plots on ground

19. 19 Measurements taken from the plot

20. 20 Other forest types

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22. 22 Data analysis The following trees stand parameters were computed: Density i.e. the number of stems per ha (N) Basal area per hectare (Dominance)(G) Volume per ha (V) and Dry biomass / carbon (tones per ha)   Trees volume and biomass were computed using tested local existing allometric functions for the areas.   Computation were fitted on Ms Access database

23. 23 Results With Project Case Vegetation type Location Average annual increment (t/ha/yr) Average annual increment (t/ha/yr) CO2 sequestration (tCO 2 /ha/yr) Forest Area (ha) Total sequestration (tCO 2 /ha/yr) WoodlandsKitulangalo2.85.36003,180 Ayasanda1.73.25501,760 LowlandLudewa4.48.328.5237 MontaneMgambo5.29.81561,760 Without Project case Vegetation type Location Average biomass loss (t/ha/yr) Average biomass loss (t/ha/yr) Average CO 2 Emissions (t/ha/yr) Average CO 2 Emissions (t/ha/yr) Forest Area (ha) Total CO 2 Emissions (tCO2/ha/yr) WoodlandKitulangalo 11.86001014 MontaneMgambo3.56.51561080

24. 24 Conclusions & Recommendations  Methods exists to assess and measure forest carbon, however these are complex to the users  More studies are required for the Development of user friendly tools for the assessment and monitoring forest carbon

25. 25 The End! Thank You!!! Ahsanteni Sana!!!