Comments on Monitoring Methodologies: Tanzania Moldova Brazil Winrock International Training Seminar for BioCarbon Fund Projects

Monitoring Methodology for: TIST (Tanzania)

Purpose of Methodology Designed for measurement of afforestation/reforestation activities where the project boundary delineates many discrete areas

Comment on Scope  The TIST project promotes development by giving an additional income stream to villagers plus the incentive, instruction and encouragement to improve practices  Tree plantings are on the land of individual villagers who are project participants  Monitors have limited education and are non-expert in forestry

Comment on Scope  Methodology should be limited to tropics  And to situations where the very limited income from carbon finance is sufficient to make a difference to individual small landowners  In more developed areas this methodology would not be the most efficient

Extraneous Inclusions  Criticism from A/R working group and expert reviewers for non-focused methodology Inclusion of eligibility requirements Inclusion of positive leakage (currently not allowed under CDM) Application to temperate scenarios Application to scenarios where measurements are of volume instead of DBH

Monitoring Baseline  Claim is of a zero carbon baseline Argument of continued deforestation in country  Baseline is within project boundaries  So carbon in agricultural crops and fallow vegetation should be measured

Measurement Methods – core methods  Two options for measuring project boundary # of trees x spacing of trees Subject to HUGE error especially as spacing is only measured in one area of planting GPS tracking of boundary Should be chosen as sole method with methods to track error on GPS such as comparison of repeated measurements, comparison with topographic map

 Non-expert monitor: Counts number of trees Measures circumference of 20 trees per planting, systematically selected  But All trees counted including trees below minimum DBH for measurement Factor applied to estimate this proportion but assumes linear relationship between proportion of trees non-eligible and proportion of biomass Mean DBH calculated and allometric equation applied to this Correct methodology is to calculate the biomass for each measured tree and average that – IS NOT A LINEAR RELATIONSHIP BETWEEN DBH AND BIOMASS Measurement Methods – core methods

TIST-specific Issues TIST unusual in:  The large stake that landowners have in a relatively few trees Make it impossible to mark trees Will be treated differently by villagers  Many non-expert monitors produce data Can’t select random trees at each planting at each measurement to be measured A more technical approach would make it more difficult for non-experts to implement and more subject to errors

 Reviewer Gonzalez simply wrong to state that trees have to be marked to monitor growth and to verify measurements  TIST should include examples to show that the level of effort is sufficient to record to within 10 % of the mean with 95 % confidence TIST-specific Issues

Extraneous Methods  Calculation of biomass from biomass of just bole/stem This method would be used by foresters, it is unrealistic to assume that a forestry operation would fit under the TIST scenario Creates more complication and opens methodology up for more criticism

Allometric Equation  We suggested that TIST harvest trees where possible to create a region specific equation  As an alternative we provided an equation TIST incorrectly listed the equation in the methodology

 If TIST wants to use a generic equation it is necessary to verify its applicability  This can be done by harvesting a limited number of trees across the expected size range Allometric Equation

Belowground Biomass  Criticism from reviewers for using single ratio factors for calculation of belowground biomass  Equations exist (Cairns et al 1997) that co-vary belowground biomass with aboveground biomass. One equation is specifically for the tropics Must not be used on a tree by tree basis but on a per hectare carbon density

Summing through Time  TIST approach creates complications for calculating uncertainty  At each measurement a mean and a 95 % confidence interval  To calculate confidence interval on the increment will require Monte Carlo simulation Time 1 and Time 2 are entirely dependent  Could use principle of conservatism instead

Leakage  Project proposes that there will be leakage associated with travel of participants-this is part of project activities and needs to be monitored (not leakage)  However no indication of measurements of potential for: Increased income leading to more livestock and more fertilizer Displaced farmland – scrub/shrubs/trees cut to replace farmland lost to afforestation  These possibilities must be tracked or a strong case made that they are not likely

Uncertainty  QA/QC plan exists includes blind resampling of 5 % of plantings Difference between measurements could be expressed as a % measurement error  95 % confidence intervals should be reported for all measurements

Conclusions  We would advise Tightening of methods to include just the specific conditions under which it will be applied Removal of extraneous details Tightening of methods and illustration that sampling level is enough to produce very high precision  It is ‘good practice’ and it greatly improves the chances of success if the IPCC Good Practice Guidance is repeatedly referred to

Monitoring Methodology for: Restoration of Degraded Lands through Afforestation/Reforestation (Moldova Project)

Purpose of Methodology  Designed for monitoring of afforestation/reforestation activities: Project boundary delineates many discrete areas Degraded lands – Baseline assumed to be zero

Conditions of methodology  Land becoming more degraded over time – e.g. carbon stocks declining over time  Degradation permits only use of less intense land use to restore productivity  Project entities sufficiently organized

Overall Strengths and Weaknesses:  Can only be applied to areas of zero or negative baseline  Methodology is simple, easy to follow, relatively well organized  Brings up issue: Should NMM include step-by step methods, or just outline?  All leakage issues not addressed  Suggested additions are in orange

Section B. Proposed new methodology:  Overall, good methodology  The interaction between field measurements and CO2FIX model unclear Need to state that model is for projections only  Methodology steps: Project area delineation Field survey Stratification Sampling design Selection of plot size and number Monitoring and measuring Quality assurance

Section B.2.2. Formulas to monitor actual net GHG removals by sinks: PR CO2e = ∑ [{ CPR * (44/12) } *A n – PE CO2e ]  Where: PR CO2e = CO 2 e GHG removals in the project scenario PE CO2e = CO 2 e Carbon emitted by project activities for total area 44/12 = Factor to convert C to CO2e A n = Number of hectares of area 1…, n = Number of strata 1…, n

Section B.2.1 Actual net GHG removals by sinks data: 1.Monitoring frequency 2.Project Boundary Discuss how to determine project boundaries Can be complicated due to large number of small project areas 3.Stratification Aim of creating strata Example of strata types 4.Sampling Design Determination of plot locations e.g. systematic, random, stratified random Creation of permanent vs. temporary sample plots

Section B.2.1 Actual net GHG removals by sinks data: 5.Plot number Determination of number of plots required – via collection of preliminary data Discussion of accuracy + precision required Discuss variation of different pools, degree of precision desired for each pool e.g. size of variation vs. size of pool 6.Sample Frame, Nesting plot sizes Remove detail on techniques, place later in B with other detail 7.Data Collection Creation of Standard Operating Procedures (SOPs)

Section B Description of formula + models used to monitor:  Straight forward methods  Standard practices - IPCC Good Practice Guidance  Need to eliminate project specific information  Lacks Some detailed field and analysis methods Uncertainty Analysis Analysis at 2 nd sampling time period Expansion factors Discussion of fire, disease, extreme events

Section B Description of formula + models used to monitor: 1.Preliminary data to calculate plot number 2.Determination of nested plot sizes ’10 stems’ is a good ‘rule of thumb’ to help determine size of nested plots for trees. Can use rectangular or circular plots 3.Creation of plots Discuss methods used to create permanent plot (if used) 4.Tree Creation of allometric equations Thinned trees - not best guidance Trees will all be small size class Remaining trees may change growth pattern More explicit instructions on creation or verification of existing equations

Section B Description of formula + models used to monitor: 5.Non-tree More explicit on methodologies for measurement 6.Standing dead Dead wood density classes – no description of how collect 7.Lying dead wood Mean density – no description of how to collect 8.Litter Conflicting remarks – send to lab or assume 50%? 9.Soil 10.Data Analysis and Uncertainty Analysis

Section B Formula – Project Emissions PE CO 2e = A * D * ED * + A * G * EG * (11) Where A = Project area – units: ha D = Quantity of diesel – units: L/ha ED = Emission factor for diesel (2.63 kg CO2/l) G = Quantity of gasoline - units: L/ha EG = Emission factor for gasoline (2.40 kg CO2/l) = Factor to convert kg to Mg  Definition of ‘project boundary’ used in strict sense.  Suggestion: put all vehicle emissions in this section

Section B.3. Leakage 1.Diversion of pre-existing A/R activities 2.Shifting of activities 3.Market affects

Section B.4. Description of formula to estimate net GHG removals  Need to subract leakage from equation: NR(t) CO2e = PR(t) CO2e - BR(t) CO2e - PLK CO2e assumes BR(t) CO2e = 0  Where: NR(t) CO2e = Net anthropogenic GHG removals in the monitoring period t(CO2e) PR(t) CO2e = GHG removals in the project scenario in the monitoring period t (CO2e) BR(t) CO2e = GHG removals in the baseline scenario in the monitoring period t (CO2e) t = Indicator for the monitoring period PLK CO2e = Leakage

Conclusions - Moldova  Overall good methodology  Only minor improvements need to made: Expand field and analysis methodology Expand leakage monitoring  Discussion point: What level of detail should NMM contain?

Monitoring Methodology for: Reforestation Project Using Native Species Around AES-Tiete Reservoirs (Brazil Project)

Status of Brazil  Rejected in first round and is presently under major revision

How many monitoring methodologies can there be?  Class by sampling design (3) Single tree as in TIST Systematic versus stratified random Readily stratified into homogeneous units E.g. plantations of native species on flat and sloped lands Highly heterogeneous system Post stratify E.g. planting in islands and natural regeneration

How many monitoring methodologies can there be?  Class by type of sampling plots Systematic versus stratified random Permanent sample plots Temporary sample plots TOTAL NUMBER: FOUR BASIC MONITORING PLANS Permanent sample plots

How many monitoring methodologies can there be?  Other pools can be included or not—make optional with some guidance In most cases dead lying wood will be very small pool and maybe not “worth” the effort (conservative is not monitored and counted)

Leakage monitoring can add some wrinkles  Possible sources of leakage-likely to be more project specific Activity shifting—clearing land elsewhere Very difficult to assume any deforestation in region is due to project Depends on land tenure/ownership Try to handle in project design by providing other sources of livelihoods Could monitor through rate of adoption of alternatives Market effects Identify possible sources of this effect Try to make strong case for limited to no leakage in PDD so no need to monitor  Common mistake in many PDDs —include GHG emissions due to project as leakage because assumed to be outside “project boundary”—this is incorrect

Improve monitoring methodologies  KISS principle and be generic—details come in the application in the PDD  Give step by step methods, following those in the IPCC GPG Ch 4.3 but without great details E.g. Step x. create a plan to locate plots Enough detail for a generic methodology?  Check all equations reported in document with data to make sure get reasonable answers—many NMM have sloppy mistakes and wrong conversion factors

Improve monitoring methodologies  Don’t undermine the QA/QC plan— develop SOPs and include in Appendices  Work together and learn from each other and pool expertise—this is not a competition  If English is not preparers first language, get someone with English to edit it—must communicate methodology succinctly