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

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 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 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 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 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 ),  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 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 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 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 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 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 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 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 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 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

16

17

18 Locating sample plots on ground

19 Measurements taken from the plot

20 Other forest types

21

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 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) WoodlandsKitulangalo ,180 Ayasanda ,760 LowlandLudewa MontaneMgambo ,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 MontaneMgambo

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 The End! Thank You!!! Ahsanteni Sana!!!