PCS MA 001 Forestry Methodology_v1.0

Document Control

Document identification

• Document code: PCS-MA-001

• Title: Forestry Methodology

• Scope: Forestry and land-based ecosystem projects on non-wetland lands, including afforestation, reforestation, revegetation, forest restoration, improved forest management (IFM), and enhancement of carbon stocks, subject to applicability conditions.

• Crediting outcome: Net greenhouse gas emission reductions and/or removals (tCO₂e), expressed as PCS-issued units per program rules, after accounting for baseline, project emissions, leakage, uncertainty, and non-permanence risk.

Version history and change log

Table DC-1. Revision history

Version	Date	Status	Summary of changes	Prepared by	Approved by
v1.0	TBD	Draft	Release for public consultation	PCS	TBD

Superseded versions

No superseded versions for v1.0.

Governance note on versioning and archiving

Only the latest approved version of this methodology shall be used for new project registrations. Superseded versions shall be archived and retained for traceability and audit purposes, including for projects registered under earlier versions where applicable, consistent with PCS governance rules.

Acronym Table

Acronym	Full Term	Definition / Relevance to PCS
AGB	Above-Ground Biomass	Biomass of all living vegetation above soil, including stems, branches, leaves.
AFOLU	Agriculture, Forestry and Other Land Use	IPCC sector covering land-based emissions and removals.
BGB	Below-Ground Biomass	Biomass of living roots below soil surface.
BEF	Biomass Expansion Factor	Ratio converting merchantable volume to total biomass.
CA	Corresponding Adjustments	Adjustments required under Article 6 to avoid double counting.
CF	Carbon Fraction	Proportion of biomass that is carbon.
CV	Coefficient of Variation	Statistical indicator of variability used in sampling design.
DBH	Diameter at Breast Height	Tree diameter measured at 1.3 m above ground.
ESS	Environmental and Social Safeguards	PCS safeguard standard ensuring protection of people and ecosystems.
FPIC	Free, Prior, and Informed Consent	Rights-based requirement when working with Indigenous communities.
GIS	Geographic Information System	Spatial data platform used for mapping boundaries and strata.
GHG	Greenhouse Gas	Includes CO₂, CH₄, and N₂O relevant to forestry accounting.
HWP	Harvested Wood Products	Wood materials with long-lived carbon storage (IFM projects).
IFM	Improved Forest Management	Activities increasing forest carbon stocks through better management.
IPCC	Intergovernmental Panel on Climate Change	Provider of global GHG accounting guidelines used by PCS.
LULUCF	Land Use, Land-Use Change and Forestry	UNFCCC sector used for baseline and scenario definitions.
MR	Monitoring Report	Required PCS document reporting each monitoring cycle.
MRV	Measurement, Reporting, and Verification	Core system ensuring integrity of carbon accounting.
PCS	Planetary Carbon Standard	Standard under which the methodology operates.
PCU	Planetary Carbon Unit	The carbon credit issued under PCS.
PSP	Permanent Sample Plot	Field plot used repeatedly for biomass and carbon measurements.
QA/QC	Quality Assurance / Quality Control	Procedures ensuring reliability of field, lab, and analytical data.
R/S Ratio	Root-to-Shoot Ratio	Ratio used to estimate BGB from AGB.
SOC	Soil Organic Carbon	Carbon stored in soil as organic matter.
SR	Stratification	The process of dividing project areas into homogeneous units.
TA	Technical Annex / Tool	PCS-approved tools that support calculations (e.g., SOC, burning).
tC	Tonnes of Carbon	Unit used for biomass carbon stocks.
tCO₂e	Tonnes of Carbon Dioxide Equivalent	Standard unit of GHG reductions/removals.
UNFCCC	United Nations Framework Convention on Climate Change	International body governing carbon and land-use accounting.
VVB	Validation and Verification Body	Independent accredited body verifying PCS projects.

Chapter 1 - Introduction And Scope

1.1 Purpose of the Methodology

1. The purpose of PCS-MA-001 is to provide a standardized, scientifically robust, and verifiable approach for quantifying greenhouse gas (GHG) emission reductions and removals resulting from forestry project activities implemented on non-wetland lands. This methodology enables Project Developers to estimate carbon stock changes, monitor forest regeneration and management impacts, and report results in accordance with the Planetary Carbon Standard (PCS) Framework, PCS Project Standard (PCS-PS-003), and PCS Validation & Verification Standard (PCS-VVS-004).

2. Forestry projects under PCS may generate removals through increases in biomass, soil carbon, and ecosystem recovery, or reduce emissions through avoided degradation and improved forest management. This methodology ensures that all credited outcomes are measurable, conservative, and additional relative to business-as-usual land-use practices.

1.2 Applicability of the Methodology

1. PCS-MA-001 applies to forestry and land-based ecosystem projects implemented on non-wetland lands, including degraded, marginal, or previously forested areas where vegetation growth can be enhanced or restored.

2. The methodology covers the following eligible project activities:

Table 1: Eligible Forestry Project Types Under PCS-MA-001

Project Type	Description
Afforestation	Establishment of forests on lands that have not been classified as forest for at least 50 years.
Reforestation	Re-establishment of forest cover on lands that were historically forested but currently lack tree cover.
Revegetation	Planting and management of trees, shrubs, or perennial vegetation to restore ecosystem function.
Forest Restoration	Activities that restore degraded forests through assisted natural regeneration or enrichment planting.
Improved Forest Management (IFM)	Implementation of sustainable management practices that increase carbon stocks above the baseline scenario.
Enhancement of Carbon Stocks	Activities that improve tree growth, stand density, or ecological resilience beyond business-as-usual conditions.

This methodology does not apply to mangroves, peatlands, wetlands, tidal forests, or blue carbon ecosystems. These are addressed under PCS-MA-002 and future wetland methodologies.

1.3 Project Location and Land Eligibility

1. Projects may be implemented in tropical, subtropical, temperate, and boreal regions, provided the land meets PCS eligibility requirements. Land must be free of legal disputes, demonstrate clear ownership or use rights, and be accessible for monitoring activities.

2. Land eligibility must be demonstrated through:

• historical land-use records,

• satellite imagery,

• field surveys,

• government classifications, and

• evidence of degradation or non-forest status where applicable.

A stratified approach may be used where the project area consists of multiple land-use histories.

Table 2: Land Eligibility Criteria Summary

Criterion	Requirement
Land status	Must be classified as non-wetland land.
Forest cover history	Demonstrated absence or reduction of forest cover consistent with the selected project type.
Tenure and rights	Legal authorization to implement the project and claim carbon benefits.
Exclusion zones	Lands under active dispute, significant ecological disturbance unrelated to the project, or areas reserved for conservation without intervention.

1.4 GHG Accounting Boundary

1. The methodology accounts for carbon stock changes and emissions within the geographical boundary of the project, as well as emissions that occur outside the boundary but result directly from project activities (leakage).

Carbon Pools Considered

1. Several carbon pools may be monitored, depending on the project type and materiality.

Table 3: Carbon Pools Included in PCS-MA-001

Carbon Pool	Included	Notes
Above-ground biomass (AGB)	Yes	Required for all project types
Below-ground biomass (BGB)	Yes	Estimated using root-to-shoot ratios
Deadwood	Yes	Required where deadwood is a significant pool
Litter	Optional	Included if material within ecosystem
Soil organic carbon (SOC)	Yes	Required for long-term projects
Harvested wood products (HWP)	Optional	Included for IFM projects when applicable

GHG Sources Considered

GHG Source	Included	Notes
CO₂ removals from growth	Yes	Primary project benefit
CO₂ from biomass burning	Yes	Estimated using PCS-TA-001
CH₄ & N₂O from burning	Yes	Required for activities involving fire
Fertilizer emissions	As applicable	Using PCS-TA-003
Fuel consumption	Yes	If material

This boundary ensures a complete, conservative representation of all relevant emissions and removals.

1.5 Temporal Scale of the Project

1. A PCS forestry project consists of:

• a crediting period of up to 40 years, renewable once;

• a monitoring interval of 5 years (unless justified otherwise);

• a risk assessment cycle aligned with PCS buffer requirements.

Changes in land use, forest structure, and biomass accumulation must be monitored throughout the project duration.

1.6 Additionality Requirements

1. Projects must demonstrate that carbon benefits would not occur in the absence of the PCS intervention. Additionality must be shown through:

1

Regulatory additionality

The activity is not legally required.

2

Financial additionality

The activity is not financially attractive without carbon revenue.

3

Barrier analysis

The project faces technological, institutional, or social barriers.

4

Common practice analysis

Similar lands in the region do not undertake the same activities.

Evidence must be credible, documented, and verifiable.

1.7 Safeguards and Co-Benefits Requirements

1. All forestry projects must follow the PCS Environmental & Social Safeguards Standard (PCS-ESS-005) and the PCS Sustainability/SDG Integrity Standard (PCS-SDG-006). The safeguards ensure:

• no negative social or environmental impacts,

• free, prior, and informed consent (FPIC) where required,

• biodiversity protection,

• community benefit-sharing,

• respect for traditional land-use rights.

1. Projects are encouraged to demonstrate measurable co-benefits, such as improved soil fertility, habitat restoration, water retention, and livelihood enhancement.

1.8 Relationship to Other PCS Documents

1. This methodology must be read in conjunction with:

• PCS-PS-003 – Project Standard_v1.0

• PCS-VVS-004 – Validation & Verification Standard_v1.0

• PCS-ESS-005-Environmental & Social Safeguards Standard_v1.0

• PCS-SDG-006-Sustainability & SDG Integrity Standard_v1.0

Together, these documents ensure methodological consistency across all phases of the project cycle: registration, validation, monitoring, verification, issuance, and renewal.

Chapter 2 - Project Boundary

2.1 Purpose of the Project Boundary

1. The project boundary establishes the spatial, temporal, and accounting framework within which all greenhouse gas emissions and removals attributable to the project must be quantified. Its role is to define what land is included, which carbon pools are assessed, which gases are accounted for, and what temporal limits govern measurement. A clearly defined boundary ensures methodological consistency, avoids double-counting, and provides a verifiable basis for monitoring and reporting throughout the duration of the project.

2.2 Geographical Boundary

1. The geographical boundary represents the physical area within which the project activities take place. This area must be mapped with sufficient precision using geospatial tools such as high-resolution satellite imagery, cadastral maps, digital elevation models, or GPS/GNSS-based surveys. The boundary must reflect the actual extent of afforestation, reforestation, forest restoration, or improved management practices undertaken. It must also identify exclusion areas where no carbon benefits can be claimed, including existing settlements, non-project land, bodies of water, and wetland ecosystems.

2. The project area may consist of multiple discrete parcels, but all must be mapped consistently and supported by verifiable land-use records. Over time, changes in canopy cover, stand development, or land classification may require refinement of the mapped boundary, though such adjustments must maintain the integrity of the original project design.

Table 4. Requirements for Defining the Geographical Boundary

Requirement	Description
Mapping resolution	High-resolution (10–30 m) or better
Coordinate accuracy	Within 5 m when derived from GPS
Documentation	Maps, shapefiles, metadata, and imagery sources
Land classification	Must correspond to the selected project type
Exclusion areas	Settlements, wetlands, infrastructure, water bodies

2.3 Stratification of the Project Area

1. Stratification divides the project area into homogeneous units based on ecological and management characteristics. The purpose of stratification is to improve the accuracy of carbon stock estimates, reduce sampling uncertainty, and ensure that similar forest conditions are grouped together. Examples of stratification variables include forest type, age class, degradation status, soil characteristics, and evidence of past disturbance.

2. Stratification must be established during project design and may be updated during monitoring as the forest develops or new information becomes available. Each stratum must be described clearly, mapped spatially, and associated with specific sampling requirements.

Table 5. Commonly Used Stratification Variables

Variable	Purpose
Vegetation type	Determines appropriate biomass models
Age class	Influences growth rate patterns
Degradation level	Distinguishes restoration zones
Soil type	Relevant to SOC estimation
Topography	Influences accessibility and biomass density

2.4 Carbon Pools Included in the Boundary

1. The methodology requires the inclusion of all carbon pools that are expected to change materially due to project activities. These pools typically include above-ground and below-ground biomass, soil organic carbon, deadwood, and litter. The inclusion of harvested wood products may be appropriate for improved forest management projects where timber extraction results in long-lived carbon storage.

2. If a pool is excluded, the Project Developer must justify that the pool is either not expected to change or that any change would be negligible relative to the total project impact.

Table 6. Carbon Pools and Their Inclusion Status

Carbon Pool	Inclusion Status	Notes
Above-ground biomass	Required	Primary contributor to removals
Below-ground biomass	Required	Derived using established ratios
Deadwood	Required when material	Significant in degraded forests
Litter	Optional	Included when ecologically relevant
Soil organic carbon	Required	Important long-term reservoir
Harvested wood products	Optional	Applicable to IFM projects

2.5 Greenhouse Gas Sources and Sinks

1. Within the project boundary, the methodology accounts for all major greenhouse gas sources and sinks resulting from project activities. These include sequestration in tree biomass and soils, emissions from biomass burning, and emissions associated with fertilizers or fossil fuel use. The gases accounted for typically include carbon dioxide, methane, and nitrous oxide, depending on the specific activities undertaken and the likelihood of each gas being emitted or removed.

Table 7. GHG Sources and Sinks

Source or Sink	Included	Reference
CO₂ uptake from biomass growth	Yes	Annex A & B equations
CO₂ from burning of biomass	Yes	PCS-TA-001
CH₄ and N₂O from burning	Yes	PCS-TA-001
N₂O from fertilizer application	When applicable	PCS-TA-003
Changes in soil carbon	Yes	PCS-TA-002
Fossil fuel combustion emissions	When material	PCS default factors

2.6 Baseline Boundary

1. The baseline boundary defines the carbon pools and GHG sources that would change in the absence of the project. It mirrors the project boundary in structure, ensuring that comparisons between baseline and project conditions are consistent and comparable. These baseline conditions may reflect ongoing degradation, lack of regeneration, conventional forest management, or other business-as-usual land uses.

The baseline boundary must be supported by historical land-use evidence, field observations, remote sensing data, and plausible future projections.

2.7 Leakage Boundary

1. The leakage boundary extends beyond the project area to include any regions where project activities may indirectly cause increases in greenhouse gas emissions. For example, restrictions on timber harvesting within the project boundary may shift extraction to nearby forests; similarly, agricultural displacement may affect surrounding lands. The leakage boundary must therefore be defined in a manner that captures such potential displacement effects.

2. Leakage assessment must consider community fuelwood dependence, regional land-use pressures, and commodity market effects. The spatial extent of this boundary must be justified with evidence and described clearly in supporting documentation.

Table 8. Leakage Boundary Components

Leakage Category	Description
Activity-shifting leakage	Displacement of land-use practices into nearby areas
Market leakage	Increased production elsewhere due to market shifts
Fuelwood leakage	Increased harvesting outside the project area
Grazing displacement	Movement of livestock into adjacent lands

2.8 Temporal Boundary

1. The temporal boundary establishes the period over which carbon benefits can be claimed and monitored. It includes the start date of project activities, the beginning and end of the crediting period, and subsequent monitoring cycles. A typical crediting period may extend up to forty years and may be renewed once under PCS rules. Monitoring intervals are generally conducted every five years unless more frequent reporting is required due to specific project conditions.

Table 9. Temporal Boundary Elements

Element	Requirement
Project start date	When activities begin
Crediting period	Up to 40 years
Monitoring interval	Generally 5 years
Baseline renewal	Every 10 years or as required

2.9 Conditions for Adjusting Boundaries Over Time

1. Project boundaries may require revision during the crediting period. Adjustments may arise from improved mapping data, changes in land ownership that remain within eligibility criteria, altered forest conditions resulting from disturbances, or the correction of documented errors. Any modification must be transparently justified and must not create opportunities for double counting. Adjustments must be validated by a VVB before being incorporated.

2.10 Documentation Requirements

1. All boundary-related information must be documented comprehensively. This includes the mapped project area, boundary coordinates, stratification descriptions, carbon pool inclusion decisions, GHG source identification, temporal boundary definitions, and leakage assessments. The documentation must be internally consistent across all PCS project cycle documents such as the Project Submission Form, Monitoring Report, and Validation Report.

Chapter 3 - Baseline Methodology

3.1 Purpose of the Baseline Methodology

1. The baseline methodology establishes the reference scenario against which project impacts are measured. It represents the most plausible set of land-use practices, vegetation dynamics, and carbon stock changes that would occur in the absence of the project. A robust baseline ensures that credited removals or emission reductions are real, measurable, and attributable solely to the project intervention. This chapter outlines the requirements for baseline selection, carbon stock estimation, land-use history assessment, and demonstration of additionality, all of which must conform to the principles of transparency, conservativeness, and verifiability.

3.2 Establishing the Baseline Scenario

1. The baseline scenario must reflect the continuation of existing land-use practices or the most likely alternative land use had the project not been implemented. The selection must be based on empirical evidence, including documented management regimes, historical land-use records, and socioeconomic drivers influencing land users’ decisions. The baseline must not speculate about extreme scenarios but must represent the realistic pathway that landowners or managers would pursue.

2. Historical trends in forest degradation, harvesting intensity, land abandonment, natural regeneration, or conversion pressures should inform the baseline. Scenarios that presume sudden, uncharacteristic changes in land use without justification may not be accepted.

Table 10. Illustrative Baseline Scenarios by Project Type

Project Type	Typical Baseline Condition
Afforestation / Reforestation	Continued non-forest land use with limited natural regeneration
Forest Restoration	Persistent degradation, slow or absent natural recovery
Improved Forest Management	Continuation of current harvesting intensity or unmanaged exploitation
Carbon Stock Enhancement	Stock stagnation due to insufficient regeneration or low-density stands

3.3 Historical Land-Use and Forest Condition Assessment

1. A baseline must be grounded in a clear understanding of the land’s historical condition. This includes examining the status of forest cover, disturbances, management practice, and ecological trends over a period of at least ten years. Satellite imagery, archival maps, and government land-use classifications may be used to reconstruct land history, supplemented by field verification where necessary.

2. The historical assessment must identify the degree of degradation, presence or absence of canopy cover, trends in biomass accumulation or loss, and evidence of exploitation. For areas planned for afforestation, the historical assessment should confirm that the land has not been forested for at least fifty years, or another period defined by national regulations.

Table 11. Sources of Evidence for Historical Land Assessment

Source	Description
Satellite imagery	Time-series data showing land cover transitions
Aerial photographs	High-resolution representation of disturbances
Land registry	Legal or administrative land classification
Field surveys	Confirmation of vegetation structure and regrowth potential
Community or stakeholder inputs	Local knowledge regarding land-use history

3.4 Baseline Carbon Stock Estimation

1. Baseline carbon stocks represent the quantity of carbon stored within each pool under the baseline scenario. Estimation may draw upon field measurements, established allometric equations, remote sensing datasets, soil sampling, or default values aligned with IPCC guidelines. The approach selected must correspond to the stratification used in the project boundary.

2. Baseline stocks must be quantified separately for each carbon pool. Where the baseline scenario involves continued forest degradation or biomass loss, carbon stocks may exhibit declining trends over time. Conversely, non-forest areas with limited natural regeneration might show stable or slowly increasing biomass levels, depending on local ecological conditions.

Table 12. Carbon Pools and Baseline Estimation Approaches

Carbon Pool	Baseline Estimation Method
Above-ground biomass	Plot measurements, remote sensing, or default growth curves
Below-ground biomass	Derived using root-to-shoot ratios
Deadwood	Field measurement or decay class models
Litter	Field sampling for material pools
Soil organic carbon	Soil sampling or default regional SOC values

All baseline carbon stock estimates must be transparently reported, including uncertainty ranges and stratified values.

3.5 Baseline Emissions and Carbon Stock Change Dynamics

1. Beyond static carbon stocks, the baseline must describe expected carbon stock change trajectories. These may show continued decline in forests under unmanaged exploitation, slow biomass accumulation in regenerating areas, or stable carbon stocks in non-forest land. The temporal evolution of baseline carbon stocks must be modeled for the entire crediting period or until the next baseline update.

2. Baseline emissions may arise from continued biomass burning, agricultural activities, or fuel use associated with conventional land management. These emissions must be quantified using the appropriate PCS methodological tools and excluded from project crediting.

3.6 Additionality Demonstration

1. A project is considered additional when its climate benefits would not occur without the incentive provided by PCS. Demonstrating additionality is a central component of baseline establishment. The demonstration must show that the baseline scenario represents a continuation of activities that would have occurred in the absence of carbon finance.

1

Regulatory additionality

Confirms the activity is not mandated by law.

2

Financial additionality

Demonstrates the project is not independently profitable without carbon finance.

3

Institutional and barrier analysis

Identifies limitations in resources, capacity, or technical barriers that the project overcomes.

4

Common practice analysis

Shows the activity is not widely implemented in the region.

1. All arguments must rely on objective, verifiable data rather than subjective assumptions.

3.7 Selection of Baseline Growth Curves and Allometric Models

1. When baseline conditions involve forested areas or regenerating stands, growth curves may be required to estimate future biomass accumulation. These curves must be regionally appropriate and derived from scientific literature, national forest inventories, or other peer-reviewed sources. Allometric equations used to estimate tree biomass must be suitable for the species and ecological zones represented in the project area.

2. The methodology encourages the use of species-specific models where available, although generalized allometric models may be acceptable when variability across species is low. The selection process must be documented clearly and justified scientifically.

3.8 Baseline for Soil Organic Carbon

1. Soil carbon dynamics are strongly influenced by land-use history, soil type, climate, and management practices. In many degraded landscapes, SOC may remain stable without project intervention; in others, continued soil disturbance may lead to gradual losses. Baseline SOC must therefore be estimated using a combination of soil sampling, default regional values, or predictive models.

2. Repeated SOC sampling in both baseline and project scenarios must follow PCS-TA-002 guidelines, ensuring consistent sampling depths, lab procedures, and stratification across monitoring cycles.

3.9 Baseline for Deadwood, Litter, and Non-Tree Vegetation

1. In areas subject to ongoing degradation, deadwood and litter pools may decline as decomposition proceeds without replenishment. For lands undergoing natural regeneration without intervention, these pools may show modest recovery. Baseline conditions must account for such trends using field data or literature-based assumptions consistent with ecological reality.

3.10 Baseline Leakage Assessment

1. Although leakage is primarily assessed under the project scenario, the baseline should include qualitative consideration of leakage risks. For example, where land is currently harvested, restricting harvesting under the project may cause displacement to other areas. The baseline therefore provides a reference point for evaluating whether such leakage effects are project-induced or part of existing land-use patterns.

2. Leakage calculations themselves are conducted under the project scenario using PCS tools, but understanding baseline drivers is essential for determining project relevance.

3.11 Conservativeness and Uncertainty in Baseline Selection

1. Baseline determination must adhere to the principle of conservativeness. Where data gaps or uncertainties exist, assumptions must err toward underestimating baseline emissions or overestimating baseline carbon stocks to avoid inflating project benefits. All uncertainty assessments must be quantified and reported, and if uncertainty exceeds PCS thresholds, corrective measures such as increased sampling intensity may be required.

3.12 Baseline Renewal and Update

1. Baseline conditions may evolve over time due to changes in market forces, ecological patterns, or land-use trends. PCS requires baseline renewal at intervals defined by the Project Standard, typically every ten years. The renewal process must reassess land-use drivers, carbon pool conditions, and all assumptions underlying the original baseline. Updated baselines must be validated by a VVB before implementation.

Chapter 4 - Project Scenario Calculations

4.1 Purpose of Project Scenario Calculations

1. Project scenario calculations quantify the carbon stock changes and greenhouse gas emission reductions that occur as a direct result of project activities. These calculations form the foundation of the net climate benefit and must be based on conservative, transparent, and verifiable methods. All calculations must correspond to the carbon pools and GHG sources identified in the project boundary and must reflect actual field measurements or scientifically robust models.

2. The project scenario represents how carbon stocks evolve under improved management, restoration, revegetation, or newly established forest cover. The results must be disaggregated by stratum to ensure accuracy and account for ecological heterogeneity.

4.2 Overview of Project Scenario Components

1

Above-ground biomass

Estimation of AGB changes due to planting, regeneration, or management.

2

Below-ground biomass

Estimation of BGB typically via root-to-shoot ratios applied to AGB.

3

Deadwood and litter

Quantification of coarse woody debris and litter accumulation or loss.

4

Soil organic carbon

Assessment of SOC dynamics influenced by project activities.

5

Harvested wood products

Accounting for HWP where IFM projects produce long-lived products.

6

Project-related emissions

Inclusion of emissions from fuel use, fertilizers, burning, or machinery.

1. The net project carbon stock is the sum of all pools at each monitoring interval. To ensure methodological alignment with PCS standards, the project must apply consistent measurement protocols, apply conservative assumptions, and incorporate uncertainty analysis.

Table 14. Carbon Pools and Their Project-Relevant Dynamics

Carbon Pool	Typical Project Influence
Above-ground biomass	Increases due to planting, regeneration, or management
Below-ground biomass	Increases proportionally with above-ground biomass
Deadwood	Increases during restoration; stabilizes under sustainable management
Litter	Gradually builds as vegetation matures
Soil organic carbon	Accumulates slowly; depends on land-use history
Harvested wood products	Stores carbon based on product type and lifespan

4.3 Above-Ground Biomass (AGB) Calculations

1. Above-ground biomass represents the largest contributor to carbon removals. AGB must be estimated using tree measurements collected in permanent sample plots. Required field data include diameter at breast height (DBH), tree height (if needed), and species or functional group classification. Biomass is then calculated using allometric equations appropriate for the species or region.

2. The methodology encourages species-specific equations where available. If not available, generalized models (e.g., Chave et al. for tropical forests, Chapman-Richards curves, or regional AFOLU equations) may be used.

3. The AGB of each tree is summed across all trees in a plot, averaged per hectare, and then extrapolated to the stratum. Carbon content is calculated by applying a carbon fraction, typically 0.47 to 0.50 depending on species or literature.

Table 15. Allometric Equation Selection Guidance

Forest Type	Recommended Equation Sources
Tropical moist	Chave et al., pantropical models
Temperate forests	Jenkins et al., national forest inventories
Boreal forests	Species-group equations, low-height adjustments
Mixed or unknown species	Generalized biomass equations

All assumptions, coefficients, and sources must be documented clearly for verification.

4.4 Growth Modelling for AGB Accumulation

1. When direct measurements are not available for every year of the project, biomass accumulation must be estimated using validated growth models. These may include stand-level yield tables, growth-and-yield models, or empirically derived relationships based on permanent plots.

2. Growth modelling must respect local ecological conditions and must not exceed biologically plausible ranges. Where uncertainty is significant, conservative growth curves should be selected.

4.5 Below-Ground Biomass (BGB) Calculations

1. Below-ground biomass is typically estimated by applying a root-to-shoot ratio to the above-ground biomass. Ratios vary by forest type, tree species, and ecological zone. IPCC default values may be used when local data are unavailable.

2. Ratios generally range from 0.20 to 0.30 in tropical and temperate forests, and up to 0.40 in some boreal systems. The selected ratio must reflect site-specific conditions whenever possible.

Table 16. Typical Root-to-Shoot Ratios

Forest Type	Ratio
Tropical evergreen	0.24
Tropical dry	0.28
Temperate	0.26
Boreal	0.40

All BGB values must be converted to carbon content using the same carbon fraction applied to AGB.

4.6 Deadwood Carbon Calculations

1. Deadwood accumulates as trees grow, self-thin, or experience mortality. Under restoration or improved management, deadwood may increase as the forest structure matures. Deadwood must be quantified using field sampling methods such as line-intersect sampling, fixed-area plots, or decay-class models.

2. Values must reflect the volume of coarse woody debris, adjusted by wood density and carbon fraction. In degraded areas transitioning toward restoration, deadwood dynamics may shift from declining (baseline) to increasing (project), depending on natural regeneration and management.

4.7 Litter Carbon Calculations

1. Litter accumulates gradually as vegetation matures. While often a small pool, it can be significant in certain forest types. Litter must be measured using standard sampling techniques such as quadrat sampling or depth-based sampling, depending on the ecological zone.

2. Litter carbon may be excluded if evidence shows immateriality; however, justification must be provided.

4.8 Soil Organic Carbon (SOC) Calculations

1. SOC changes slowly and must be estimated over longer timeframes. Project-induced SOC increases may occur due to reductions in soil disturbance, increased organic matter inputs, and improved forest cover. SOC must be measured using soil sampling protocols aligned with PCS-TA-002.

2. Sampling depth must be consistent across baseline and project measurements. Laboratory analysis must follow standardized procedures with documented QA/QC. SOC values may be modelled conservatively between sampling cycles if annual estimates are needed.

Table 17. Key Parameters for SOC Estimation

Parameter	Requirement
Sampling depth	Typically 0–30 cm unless justified otherwise
Bulk density	Required for SOC stock calculation
Carbon concentration	Measured through dry combustion or equivalent
Stratification	SOC must reflect soil type variations

4.9 Harvested Wood Products (IFM Projects Only)

1. For improved forest management projects involving timber harvest, carbon stored in harvested wood products may be credited if products have long life spans. The calculation requires classification of harvested material into product categories such as sawnwood, plywood, paper, or short-lived products.

2. Each category is associated with a decay rate, which determines carbon retention over time. Only the long-lived fraction is eligible for crediting. All product estimates must be supported by harvest records and conversion factors.

4.10 Project Emissions

1. Project emissions include all emissions directly generated by project activities. These may include emissions from fuel use during planting, thinning, or transport of materials. Fertilizer-related emissions must be quantified if fertilizers are applied. Biomass burning emissions must be estimated using PCS-TA-001.

Emission factors must be consistent with PCS-approved values or national GHG inventories where available.

4.11 Total Project Carbon Stock Change

1. The total project carbon stock change for each monitoring period is the sum of changes in all included pools. For each stratum, the carbon stock at the beginning of the monitoring period is compared with the carbon stock at the end.

Carbon stock change = (AGB + BGB + Deadwood + Litter + SOC + HWP) at time t₂ Minus (AGB + BGB + Deadwood + Litter + SOC + HWP) at time t₁.

All results must be aggregated across strata to produce project-wide totals.

4.12 Conservativeness in Project Calculations

1. Conservative assumptions must be applied whenever uncertainties exist, including selecting low-end biomass estimates, moderate growth curves, or discounting results when measurement error is high. The intent is to avoid overestimation of carbon benefits. Any instance where conservativeness is applied must be explained in the monitoring report.

4.13 Documentation Requirements

1. All project scenario calculations must be supported by complete datasets including raw field measurements, lab analysis results, equation sources, growth model parameters, and geospatial records. Documentation must be sufficiently transparent to allow independent replication by a Verification Body.

Chapter 5 - Leakage Assessment

5.1 Purpose of Leakage Assessment

1. Leakage refers to the increase in greenhouse gas emissions or the reduction in carbon stocks occurring outside the project boundary as a result of project activities. In forestry projects, leakage may arise when land uses or economic activities displaced from the project area shift to neighbouring zones or when market responses induce changes in harvesting, land conversion, or fuelwood demand elsewhere.

2. The purpose of this chapter is to define how leakage must be identified, quantified, and incorporated into net emission reduction calculations. A robust approach ensures that climate benefits are not overstated and that credited removals reflect the true net impact of the project.

5.2 Types of Leakage Relevant to Forestry Projects

1. Forestry projects may produce several forms of leakage depending on local land-use dynamics, livelihood patterns, and market conditions. Leakage can result from displacement of subsistence activities, shifting of commercial timber harvesting, or indirect market responses. Understanding the baseline drivers of land use is essential for determining whether leakage is likely.

2. Leakage can generally be grouped into three primary categories: activity-shifting leakage, market leakage, and displacement of energy or grazing demands. Each type must be assessed for relevance based on project characteristics, social context, and ecological setting.

Table 18. Primary Leakage Types Considered in PCS-MA-001

Leakage Type	Description
Activity-shifting leakage	Occurs when land-use activities such as agriculture, grazing, fuelwood collection, or timber harvesting shift outside the project boundary.
Market leakage	Results from changes in supply of forest products leading to increased harvesting in other areas to meet market demand.
Grazing or fuelwood displacement	Arises when communities relocate grazing or wood collection to areas outside the project boundary.

5.3 Activity-Shifting Leakage

1. Activity-shifting leakage is the most common form of leakage in afforestation, reforestation, and forest management projects. It occurs when project activities restrict access to land previously used for subsistence or commercial purposes, resulting in those activities relocating to nearby forests or grasslands.

2. The likelihood of activity-shifting leakage depends on local dependency on forest resources, availability of alternative land, and the degree to which the project alters land-use patterns. To assess potential leakage, the project must evaluate local socio-economic conditions, patterns of resource use, and existing land tenure arrangements.

3. Quantification of activity-shifting leakage may involve estimating the area and carbon density of displaced activity and calculating any associated emissions or foregone removals. Where feasible, field surveys and community consultations should inform these assessments.

5.4 Market Leakage

1. Market leakage arises when project activities reduce the supply of timber, woodfuel, or other forest products, thereby causing increased production elsewhere to satisfy demand. This effect is common in improved forest management projects where harvesting intensity is reduced or in restoration projects where degraded lands previously supplying fuelwood are rehabilitated.

2. Market leakage must be assessed using regional or national production and consumption data. The objective is to determine whether project-induced changes in supply are significant enough to influence broader markets. If evidence suggests that displacement may occur, the project must estimate the associated emissions by applying conservative leakage factors derived from national inventories, published literature, or PCS-approved defaults.

5.5 Grazing and Fuelwood Displacement

1. In rural landscapes, communities may rely on fuelwood or grazing resources within the project area. Restrictions introduced by the project may cause grazing to move to adjacent areas or fuelwood extraction to occur in forests outside the boundary. These shifts must be assessed based on community resource use patterns, alternative livelihoods, and availability of sustainable substitutes.

2. Where the project provides alternative energy sources or designated grazing areas, leakage may be reduced. The degree of leakage depends on the balance between displaced activities and mitigation measures implemented by the project.

5.6 Determining Whether Leakage Is Significant

1. Leakage must be quantified when project activities materially affect land uses beyond the project area. Significance should be assessed using evidence such as household surveys, land-use mapping, resource use studies, and baseline socio-economic assessments. Projects located in remote areas with limited economic linkage to broader markets may exhibit lower leakage potential, whereas projects in densely populated or economically integrated regions may show higher risk.

2. If leakage is determined to be negligible based on evidence, justification must be provided. However, the decision must be conservative and backed by verifiable data.

5.7 Quantifying Leakage Emissions

1. Quantification of leakage must follow a structured and transparent approach. For activity-shifting leakage, quantification involves estimating the carbon stocks in the areas affected by displacement and calculating the emissions resulting from the new land-use activities. This may include conversion of land to agriculture, increased fuelwood extraction, or expansion of grazing.

2. For market leakage, quantification may rely on established leakage factors that represent the proportion of reduced harvest or supply that is likely to be compensated by increased extraction elsewhere. These factors should be derived from national or regional statistics, empirical studies, or internationally recognized sources.

Table 19. Approaches for Quantifying Leakage

Leakage Type	Quantification Approach
Activity shifting	Area estimation, carbon stock measurement, and emission calculation in affected zones
Market leakage	Application of leakage factors derived from production-consumption dynamics
Grazing displacement	Estimation of emissions due to land conversion or increased biomass removal
Fuelwood displacement	Estimation of reduced carbon stocks in external harvesting zones

All quantification methods must be conservative and documented clearly for verification.

5.8 Leakage Prevention and Mitigation Measures

1. Projects are encouraged to implement measures that reduce leakage risk. Such measures may include providing alternative livelihoods, supporting sustainable energy initiatives, establishing community-managed woodlots, or improving soil fertility and agricultural practices in non-project areas. Social engagement, benefit-sharing, and participatory land-use planning are also effective tools for reducing displacement risks.

2. Mitigation measures should be described in the Project Design Document and monitored periodically to assess their effectiveness. Where leakage mitigation efforts demonstrably reduce leakage, this must be documented and reflected in calculations.

5.9 Monitoring Leakage Over Time

1. Leakage is dynamic and may change as project activities evolve or community behavior shifts. Therefore, leakage must be monitored throughout the project’s crediting period. Monitoring may involve community surveys, resource use assessments, land-use change detection through satellite imagery, and market trend analysis.

2. Evidence must be compiled and presented in each Monitoring Report to demonstrate whether leakage occurred during the monitoring period and whether mitigation measures remained effective.

5.10 Conservativeness and Uncertainty in Leakage Estimation

1. Leakage estimates often involve significant uncertainties due to variability in socio-economic behavior, market responses, and land-use drivers. To maintain environmental integrity, conservative assumptions must be applied throughout the leakage assessment process. This may include selecting upper-bound leakage factors, using cautious estimates of displaced areas, or discounting uncertain impacts.

2. Uncertainty must be quantified wherever feasible and discussed transparently in the Monitoring Report. If uncertainty exceeds PCS thresholds, adjustments or higher mitigation measures may be required.

5.11 Integration of Leakage Into Net Emission Reductions

1. The quantified leakage emissions must be deducted from the gross project carbon benefits to determine the net greenhouse gas reductions or removals. This ensures that only genuine climate benefits are credited. The methodology requires a clear reconciliation of all leakage components and transparent reporting in all verification cycles.

Chapter 6 - Net Greenhouse Gas Emission Reductions And Removals

6.1 Purpose of Net GHG Calculations

1. The purpose of this chapter is to specify how net greenhouse gas (GHG) emission reductions and removals attributable to the project must be calculated. Net GHG benefits represent the difference between the baseline scenario and the project scenario, after accounting for leakage and project emissions. These calculations determine the volume of Planetary Carbon Units (PCUs) the project is eligible to generate during each monitoring period.

2. The estimation process must follow principles of accuracy, conservativeness, completeness, and verifiability, ensuring that credited removals reflect genuine climate benefits.

6.2 Structure of Net GHG Accounting

Net GHG accounting requires the separate calculation of the following components for each carbon pool and stratum before aggregation:

1

Baseline carbon stock change

Change in carbon pools under business-as-usual conditions.

2

Project carbon stock change

Change resulting from project activities.

3

Leakage emissions

Emissions outside the project boundary caused by project activities.

4

Project emissions

Emissions generated within the project boundary due to project operations.

1. These components must be calculated separately for each carbon pool and each stratum before aggregation to the project level. The period of calculation corresponds to the monitoring interval defined in the temporal boundary.

Table 20. Components of Net GHG Accounting

Component	Description
Baseline carbon stock change	Change in carbon pools under business-as-usual conditions
Project carbon stock change	Change resulting from project activities
Leakage emissions	Emissions outside the project boundary
Project emissions	Emissions generated within the project boundary

6.3 Baseline Carbon Stock Change (∆C_baseline)

1. Baseline carbon stock change represents how carbon stocks would evolve in the absence of the project. This may include stagnation of biomass growth in non-forest lands, continued degradation in disturbed forests, or modest natural regeneration. Baseline carbon stock changes must be estimated for each carbon pool and stratum.

2. The change is calculated as the carbon stock at the end of the monitoring period minus the carbon stock at the beginning of the monitoring period for the baseline scenario. These values may rely on growth curves, field measurements, or ecological models.

3. For each pool, the baseline carbon stock change is expressed as:

Baseline carbon stock change for pool i = Carbon stock (baseline, end of period) – Carbon stock (baseline, start of period)

Values must be aggregated across pools and strata to generate the total baseline carbon stock change.

6.4 Project Carbon Stock Change (∆C_project)

1. Project carbon stock change represents the increase (or decrease) in carbon stocks due to project interventions such as planting, assisted regeneration, thinning, sustainable harvesting, or improved forest management. The calculation uses field measurements, allometric equations, soil sampling data, and modelling approaches consistent with Chapter 4.

2. For each carbon pool:

Project carbon stock change for pool i = Carbon stock (project, end of period) – Carbon stock (project, start of period)

Project carbon stock changes must be stratified geographically to ensure accuracy. After quantifying each carbon pool, the project sums them to obtain the total project carbon stock change.

Table 21. Carbon Pools Included in Project Carbon Stock Change

Carbon Pool	Treatment
Above-ground biomass	Mandatory
Below-ground biomass	Mandatory
Deadwood	Required where material
Litter	Optional unless material
Soil organic carbon	Mandatory
Harvested wood products	Applicable to IFM projects only

6.5 Calculation of Net Carbon Stock Change (∆C_net)

1. Net carbon stock change is the difference between the project scenario and the baseline scenario. This represents the gross climate benefit before accounting for leakage or project emissions.

2. For each monitoring period:

Net carbon stock change = Project carbon stock change – Baseline carbon stock change

If the baseline scenario represents declining carbon stocks and the project scenario represents increasing stocks, net carbon stock change will be positive. Negative values may occur in rare cases but must be justified and may affect crediting eligibility.

6.6 Leakage Emissions (LE)

1. Leakage emissions quantified in Chapter 5 must be deducted from net carbon stock change. Leakage may originate from activity shifting, market effects, or resource displacement and must be expressed in tonnes of CO₂ equivalent.

2. Leakage emissions must be calculated for each significant leakage source and aggregated into a single value representing the total leakage effect for the monitoring period.

Table 22. Summary of Leakage Components

Leakage Type	Quantified Effect
Activity shifting	Emissions from displaced land use
Market leakage	Induced harvesting or land conversion
Fuelwood displacement	Biomass loss outside boundary
Grazing displacement	Land conversion or biomass removal

All leakage estimates must be supported by evidence and conservative assumptions.

6.7 Project Emissions (PE)

1. While forestry projects primarily generate removals, some project activities may produce emissions. These emissions arise from fuel used during planting, site preparation, transport of seedlings, fertilizer application, controlled burning, or machinery used for forest management.

2. Project emissions must be included if they materially influence net emission reductions. Fuel emissions may be estimated using PCS default emission factors. Fertilizer emissions and combustion-related emissions must use PCS methodological tools.

Total project emissions = Sum of all emissions associated with project implementation.

If project emissions are negligible, the project must provide justification.

6.8 Total Net GHG Emission Reductions and Removals

1. The final calculation of net GHG emission reductions and removals follows directly from the components defined above. For each monitoring period:

Net GHG Emission Reductions and Removals = (Net carbon stock change) – (Leakage emissions) – (Project emissions)

This value represents the total climate benefit attributable to the project and determines the volume of PCUs eligible for issuance.

Table 23. Summary of Net GHG Accounting Structure

Component	Symbol	Included?
Project carbon stock change	∆C_project	Yes
Baseline carbon stock change	∆C_baseline	Yes
Leakage emissions	LE	Yes
Project emissions	PE	Yes
Net GHG reductions/removals	NER	∆C_project – ∆C_baseline – LE – PE

The net result must be positive to qualify for issuance. If net removals are negative, no issuance is permitted for that monitoring cycle.

6.9 Uncertainty Considerations

1. Uncertainty affects all components of net GHG accounting, including field measurements, biomass models, SOC sampling, baseline projections, and leakage estimates. PCS requires uncertainty quantification for each major component and encourages approaches that reduce uncertainty through improved sampling, stratification, and measurement practices.

2. If combined uncertainty exceeds PCS thresholds, discount factors may be applied to ensure conservativeness. The Monitoring Report must include a detailed uncertainty assessment and document measures taken to reduce uncertainty in future monitoring cycles.

6.10 Presentation of Net GHG Calculations in Monitoring Reports

1. All calculations must be clearly presented in the Monitoring Report using structured tables. These tables must include stratum-level results, carbon pool estimates, leakage details, and aggregated totals. The report must ensure transparent traceability from field data to final net GHG values. Any assumptions, estimation methods, or deviations from standard practice must be explained clearly.

Chapter 7 - Monitoring Requirements

7.1 Purpose of Monitoring

1. Monitoring provides the empirical foundation for calculating project removals and emission reductions. It ensures that project carbon benefits are based on verifiable data collected through structured field measurements, remote sensing technologies, laboratory analysis, and consistent reporting practices.

2. Monitoring must be conducted in accordance with PCS principles of completeness, accuracy, consistency, comparability, transparency, and conservativeness. Data collection procedures must be replicable and must enable Validation and Verification Bodies (VVBs) to independently confirm all reported carbon stock changes and emissions. The outcomes of monitoring feed directly into the Monitoring Report for each verification cycle.

7.2 Monitoring Frequency and Periodicity

1. The project must conduct a monitoring cycle at intervals not exceeding five years, although shorter intervals may be used for operational or commercial purposes. Each monitoring cycle must include the collection of field data, analysis of satellite imagery, updated stratification (if required), and recalculation of all carbon pools included in the project.

2. Monitoring frequency must reflect ecological conditions. In rapidly growing tropical systems, more frequent monitoring is often appropriate; in slow-growing temperate or boreal systems, five-year intervals typically suffice. Soil organic carbon monitoring may follow longer cycles unless significant land-use change suggests more frequent sampling.

Table 24. Typical Monitoring Frequencies by Carbon Pool

Carbon Pool	Recommended Frequency
Above-ground biomass	Every 5 years or more frequently if justified
Below-ground biomass	Same as AGB
Deadwood	Every 5 years; after disturbances as needed
Litter	Every 5 years if included
Soil organic carbon	Every 10 years unless change is expected sooner
Harvested wood products	At each harvest event for IFM projects

7.3 Stratification Updates During Monitoring

1. Stratification must be reassessed at each monitoring cycle to reflect changes in forest structure, species composition, disturbance patterns, or management practices. New strata may be introduced when forest conditions diverge significantly within existing strata. Conversely, strata may be merged when ecological differences diminish. Changes in stratification must be justified with evidence and documented through updated maps and metadata.

7.4 Field Measurement Protocols

1. Field measurements form the basis of biomass estimation. Permanent sample plots (PSPs) must be established in a statistically robust design that ensures representative coverage of all strata. The number, size, and spatial distribution of PSPs must reflect the variability of forest conditions and must be sufficient to achieve PCS uncertainty thresholds.

2. Each permanent plot must have clearly defined boundaries, precise georeferencing, and a consistent measurement protocol. All trees above the minimum diameter threshold must be measured during each monitoring cycle. Measurements must follow standardized forestry techniques to ensure comparability over time.

Table 25. Typical Plot Dimensions and Measurement Ranges

Forest Type	Plot Size	Measurement Threshold
Tropical & temperate forests	500–1,000 m²	DBH ≥ 5–10 cm
Boreal forests	400–600 m²	DBH ≥ 5 cm
Degraded lands in early stages	250–500 m²	DBH ≥ 2–5 cm

Plot size may vary depending on expected tree density and growth patterns.

7.5 Measurement of Above-Ground Biomass

1. Tree measurements must include diameter at breast height (DBH) for all eligible trees. Height measurements may be required depending on the allometric equation applied. Tree species or species groups must be recorded, as species-specific equations improve accuracy.

2. Field teams must adhere to rigorous QA/QC procedures, including independent remeasurement of a subset of trees, calibration of equipment, and documentation of measurement conditions. Plots must be maintained consistently across monitoring cycles to prevent boundary drift or measurement inconsistencies.

3. Allometric equations selected for biomass estimation must be documented clearly in the Monitoring Report, including sources, parameter values, and justification for their use.

7.6 Monitoring of Below-Ground Biomass

1. Below-ground biomass is estimated indirectly using root-to-shoot ratios applied to the above-ground biomass estimates. These ratios must be selected based on literature appropriate to the ecological zone, species composition, and forest type. Monitoring does not require additional field measurements unless species composition changes significantly.

2. When major ecological shifts occur that may alter root-to-shoot relationships, justification and updated ratios must be provided.

7.7 Monitoring of Deadwood Carbon

1. Deadwood is monitored using standard forestry protocols such as fixed-area sampling of standing deadwood and line-intersect sampling of fallen deadwood. Each sampled piece must be categorized based on decay class, diameter, length, and density class. Deadwood measurements must reflect both coarse and fine debris where material.

2. Monitoring must ensure that changes in deadwood stocks, whether from natural mortality, thinning, self-pruning, or disturbance events, are accurately captured.

7.8 Monitoring of Litter Carbon

1. Litter monitoring involves sampling the forest floor using quadrats or core samples. Litter may be included as a carbon pool if it is expected to change significantly due to project activities. Sampling must follow standardized procedures with consistent depth, area, and material collection to allow comparability across cycles.

7.9 Monitoring of Soil Organic Carbon

1. Soil organic carbon (SOC) must be measured in accordance with PCS-TA-002. This requires collecting soil cores at consistent depths, determining bulk density, and conducting laboratory analysis for carbon concentration. SOC must be monitored within each stratum unless evidence demonstrates that soil types are uniform across strata.

2. Sampling must follow consistent spatial locations or randomized but stratified approaches. SOC represents a long-term pool, and monitoring intervals may be extended unless project activities strongly influence soil processes.

Table 26. Key SOC Monitoring Parameters

Parameter	Description
Sampling depth	Must remain consistent across cycles
Bulk density	Required for stock calculation
Carbon concentration	Measured through laboratory tests
Stratification	SOC must reflect soil variability

7.10 Monitoring of Harvested Wood Products (IFM Only)

1. Projects involving harvesting under improved forest management must record all harvest data, including volume extracted, species composition, product categories, and conversion factors. Harvested wood must be classified into categories such as long-lived products (e.g., sawnwood) or short-lived products (e.g., pulp). Each category must be associated with decay factors that determine its contribution to long-term sequestration.

Records must include logbooks, weighbridge receipts, product allocation tables, and any relevant processing documentation.

7.11 Monitoring of Project Emissions

1. Project emissions from fuel use, fertilizer application, controlled burning, or machinery operation must be monitored and quantified if material. Fuel consumption records, fertilizer application logs, and operational activity logs must be maintained. Emissions must be estimated using PCS-approved emission factors or national GHG inventory values where appropriate.

7.12 Remote Sensing and Geospatial Monitoring

1. Remote sensing technologies must be used to supplement field data, verify forest cover, detect disturbances, confirm stratification, and ensure consistent boundary management. Satellite imagery with adequate spatial and temporal resolution must be used to monitor canopy cover changes, detect fires, identify illegal encroachment, and support land-use classification updates.

2. Geospatial analyses must follow recognized processing standards, including classification accuracy assessments and documentation of algorithms used. All imagery sources must be cited, and image metadata must be included in the Monitoring Report.

Table 27. Recommended Remote Sensing Sources

Source	Resolution	Ideal Use
Sentinel-2	10 m	Forest cover, disturbance detection
Landsat 8/9	30 m	Long-term trend analysis
PlanetScope	3–5 m	High-frequency monitoring
LiDAR	<1 m	Biomass calibration and canopy structure

7.13 Quality Assurance and Quality Control (QA/QC)

1. Monitoring programs must integrate QA/QC procedures throughout fieldwork, laboratory analysis, and data processing. This includes calibration of measurement devices, remeasurement of a subset of sample plots, supervision of field teams, review of data entry, and verification of geospatial datasets.

2. Laboratory QA/QC must include duplicate samples, standard reference materials, and documentation of analytical procedures. All QA/QC outcomes must be transparently reported and retained for verification.

7.14 Data Management and Recordkeeping

1. All monitoring data must be stored in a structured, secure system that ensures traceability, archival integrity, and accessibility for verification. Raw data, processed data, spatial files, laboratory reports, field forms, and metadata must be maintained for the duration of the project and any required post-crediting period.

2. Documentation must allow independent replication of results by a VVB and must demonstrate consistency across all monitoring cycles.

7.15 Monitoring Report Requirements

Each monitoring cycle must produce a Monitoring Report containing the following core components presented for clarity and stepwise review:

1

Boundary and stratification

Updated project boundary maps and stratification updates.

2

Field measurements

Sampling descriptions, plot data, and measurement protocols.

3

SOC analysis

Soil sampling results and laboratory reports.

4

Remote sensing

Imagery used and geospatial analyses.

5

Carbon stock estimates

Updated estimates per pool and stratum.

6

Leakage monitoring

Evidence and quantification of leakage.

7

Project emissions

Records and calculations for operational emissions.

8

Statistics and uncertainty

Uncertainty analysis and QA/QC documentation.

9

QA/QC documentation

Calibration records, remeasurements, and lab QA/QC.

10

Supporting annexes

Maps, raw data files, shapefiles, and supporting evidence.

The Monitoring Report must follow the PCS Monitoring Report template and present information in a transparent and verifiable manner.

Chapter 8 - Uncertainty And Conservativeness

8.1 Purpose of Uncertainty Treatment

1. All measurements and estimates in a forestry project carry some degree of uncertainty. Tree measurements, allometric models, soil sampling, remote sensing, baseline projections, and leakage estimates can each introduce error. The purpose of this chapter is to ensure that such uncertainties are recognized, quantified where possible, and treated conservatively so that the net greenhouse gas benefits credited under PCS are unlikely to be overstated.

2. Uncertainty management under PCS is not intended to penalize projects but to protect environmental integrity and confidence in issued units. It also provides incentives for better data, improved sampling design, and stronger monitoring systems over time.

8.2 Sources of Uncertainty in Forestry Projects

1. Forestry projects face several distinct types of uncertainty. Some arise from measurement processes, such as errors in diameter or soil sampling. Others arise from model selection and assumptions, such as choice of allometric equations, growth curves, or root-to-shoot ratios. Additional uncertainty can arise from natural variability within strata, spatial heterogeneity, or incomplete information on land-use history and leakage drivers.

2. In practice, uncertainty affects both the baseline and project scenarios. A sound methodology must therefore capture uncertainty in carbon stocks, changes in those stocks over time, and the emissions that accompany project implementation or leakage.

Table 28. Main Sources of Uncertainty

Category	Description
Measurement	Errors in DBH, height, plot area, soil bulk density, carbon concentration
Model	Choice of allometric equations, growth models, root-to-shoot ratios
Sampling	Limited number of plots, non-representative sampling, spatial variability
Temporal	Extrapolation of trends between measurement points
Baseline	Assumptions about land-use continuation and degradation patterns
Leakage	Estimation of displaced activities or market responses

8.3 Quantification of Measurement and Sampling Uncertainty

1. Projects must quantify uncertainty associated with field measurements and sampling where feasible. For biomass, this typically involves calculating variance across sample plots within each stratum and translating that variance into confidence intervals for mean carbon stocks. For soil organic carbon, uncertainty arises from sample-to-sample variation in carbon concentration and bulk density.

2. Statistical methods such as standard error of the mean, confidence intervals, and error propagation must be applied. When strata differ widely in variability or sample size, uncertainty must be calculated at the stratum level and then combined using appropriate weighting based on area.

3. The Monitoring Report must present, at minimum, estimates of the uncertainty around key carbon pool estimates at a defined confidence level, typically 90 or 95 percent.

8.4 Model and Parameter Uncertainty

1. Model uncertainty arises when different allometric equations, growth curves, or root-to-shoot ratios could plausibly apply to the same forest type or species group. Projects must select models that are scientifically credible and appropriate to local conditions, preferring equations developed for the same ecological zone and species.

2. Where multiple plausible models exist, the project must either justify the selected model based on evidence or adopt a conservative approach such as selecting lower-bound biomass estimates or applying downward adjustments to results. When using default values from international guidelines, the project must ensure these are not applied outside their intended domain.

8.5 Baseline and Leakage Uncertainty

1. Baseline uncertainty stems from assumptions about how carbon stocks would change without the project. This includes assumptions regarding ongoing degradation, natural regeneration, and land-use shifts. Leakage uncertainty arises from difficulty in predicting the exact magnitude and location of displaced activities or market responses.

2. While some baseline and leakage uncertainties are difficult to quantify precisely, projects must use conservative assumptions and established literature to limit the likelihood of overstating net benefits. For example, where multiple plausible baseline degradation rates exist, the project should select a rate that does not exaggerate baseline emissions. Similarly, where leakage factors come with ranges, upper-bound values may be used to ensure conservative accounting.

8.6 Combining Uncertainty Across Components

1. The total uncertainty in net emission reductions arises from combining uncertainty across different components: biomass estimates, soil carbon, baseline, leakage, and project emissions. Projects must combine these uncertainties using recognized methods such as error propagation or Monte Carlo simulation where appropriate.

2. The combined uncertainty must be expressed as a percentage of the net greenhouse gas benefit. If total uncertainty exceeds the threshold specified by PCS (for example, a 15 or 20 percent relative margin at a defined confidence level), additional measures such as increasing sampling intensity, improving stratification, refining allometric or growth models with local data, or strengthening leakage assessment may be required.

Table 29. Illustrative Steps in Uncertainty Combination

Step	Description
1	Quantify uncertainty for each major pool and component
2	Convert to consistent units (e.g., tonnes CO₂e)
3	Combine uncertainties using accepted statistical methods
4	Express total uncertainty as a percentage of net benefits
5	Compare against PCS thresholds and decide if discounting is needed

8.7 Conservativeness as a Risk Management Principle

1. Conservativeness is applied whenever uncertainty cannot be fully resolved or quantified. In such cases, assumptions must be made such that any bias favours underestimation of benefits rather than overestimation. Conservativeness may be applied in several ways, including:

• adopting lower biomass estimates where variability is high,

• capping growth rates at conservative levels,

• applying downward adjustments to soil carbon gains where sampling is sparse,

• using higher leakage factors within plausible ranges,

• excluding marginal pools when their inclusion would rest on highly uncertain data.

1. The rationale for each conservative decision must be documented clearly in the Monitoring Report. Conservativeness does not replace the obligation to collect good data; rather, it operates as a safeguard where uncertainty cannot be fully eliminated.

8.8 Uncertainty Thresholds and Corrective Actions

1. PCS may prescribe maximum allowable uncertainty thresholds for net emission reductions. If combined uncertainty surpasses these thresholds, the project must undertake corrective actions. These may include increasing the number of sample plots, improving stratification, refining allometric or growth models with local data, or strengthening leakage assessment.

2. Corrective actions must be implemented in subsequent monitoring cycles and described in project documentation. Where uncertainty remains high, PCS may require the application of discount factors that reduce the volume of PCUs eligible for issuance to maintain environmental integrity.

8.9 Documentation and Reporting of Uncertainty

1. The Monitoring Report must contain a dedicated section on uncertainty and conservativeness. This section must describe:

• the main sources of uncertainty,

• the methods used to quantify them,

• the combined uncertainty estimate for net benefits,

• any conservative assumptions applied,

• and any corrective measures implemented or planned.

1. Documentation must be presented in a form that allows VVBs to review calculations, replicate results, and assess whether conservativeness has been appropriately applied.

Table 30. Minimum Uncertainty Documentation Elements

Element	Description
Description of uncertainty sources	Narrative explanation by component
Numerical uncertainty estimates	Confidence intervals or relative errors
Methods used	Statistical techniques and data sources
Combined uncertainty	Overall percentage for net GHG benefits
Conservativeness measures	Adjustments and rationale
Corrective actions	Steps to reduce uncertainty over time

8.10 Role of Uncertainty in Verification

1. During verification, VVBs will scrutinize how uncertainty has been treated. They will review sampling designs, model selection, statistical methods, and the logic behind conservative assumptions. Where VVBs identify weaknesses, they may request additional analyses, recommend increased sampling, or propose adjustments to ensure that credited benefits remain robust.

2. Uncertainty treatment is therefore both a methodological and governance requirement, reinforcing confidence in PCS-certified forestry projects.

Chapter 9 - Safeguards, Co-Benefits, And Non-Permanence Risk

9.1 Purpose and Role of Safeguards

1. Safeguards ensure that forestry projects contribute positively to environmental and social wellbeing without creating adverse impacts. Forestry interventions alter land use, natural habitats, resource access, and local livelihoods; therefore, they must be implemented responsibly. PCS requires all projects to comply with the PCS Environmental and Social Safeguards Standard (PCS-ESS-006), which establishes mandatory performance criteria on biodiversity, labour rights, land tenure, cultural heritage, gender equity, and community engagement.

2. This chapter describes how safeguard compliance must be integrated into methodological application, monitored across the project lifetime, and documented transparently for validation and verification.

9.2 Safeguard Screening and Eligibility

1. Before registration, every project must undergo a safeguard screening to determine whether it poses material social or environmental risks. The screening must evaluate whether the project respects legitimate land tenure rights, protects vulnerable populations, and avoids conversion or degradation of natural ecosystems. Any project that risks involuntary resettlement, significant habitat loss, or violation of indigenous rights is not eligible unless adequate mitigation and consent processes are implemented.

2. The screening outcome must be documented in the Project Submission Form and validated by an accredited VVB.

Table 31. Key Safeguard Screening Elements

Safeguard Area	Screening Requirement
Land tenure	Demonstration of legal or customary rights and absence of major disputes
Biodiversity	Evidence that activities do not degrade natural habitats
Community impacts	Assessment of potential livelihood impacts
Indigenous peoples	Confirmation of FPIC where required
Cultural heritage	Assurance that cultural sites are not threatened

9.3 Free, Prior and Informed Consent (FPIC)

1. Where project lands overlap with territories used or claimed by indigenous peoples or traditional communities, FPIC is required. FPIC must be a documented process demonstrating that affected groups were fully informed of project implications, engaged without coercion, and agreed to the project freely before activities began. This process must be ongoing, allowing communities the opportunity to express concerns or negotiate participation throughout the project lifetime.

2. Verification bodies will review FPIC documentation during validation and each monitoring cycle where community circumstances have changed.

9.4 Biodiversity and Ecosystem Safeguards

1. Forestry projects must enhance, or at minimum maintain, the ecological integrity of the project area. Activities must not replace native ecosystems with monoculture plantations unless such plantations demonstrably restore ecosystem function, protect soil, and improve long-term resilience.

2. Projects must identify high conservation value (HCV) areas and avoid interventions that could harm rare or threatened species. If degraded HCV areas exist within the boundary, restoration must be prioritized. Natural regeneration should be promoted whenever ecologically appropriate.

3. Monitoring must track changes in vegetation structure, habitat conditions, and early indicators of ecological stress. Remote sensing and field biodiversity assessments may be used to support evaluations.

9.5 Social Safeguards and Community Wellbeing

1. Forestry projects interact closely with local communities, and safeguarding social wellbeing is a core PCS requirement. Projects must assess their potential impacts on livelihoods, resource access, employment, and social dynamics. Where impacts are expected, projects must design and implement mitigation plans that ensure no community is made worse off as a result of project activities.

2. Projects must promote equitable benefit-sharing, involve local residents in planning and monitoring activities, and establish grievance redress mechanisms accessible to all stakeholders. Documentation of community consultations, participation programs, and grievance handling must be maintained and submitted during monitoring.

9.6 Co-Benefits and Sustainable Development Contributions

1. In addition to climate benefits, forestry projects often generate co-benefits such as enhanced biodiversity, improved soil fertility, increased water retention, and livelihood opportunities for local communities. PCS encourages robust identification, monitoring, and reporting of these co-benefits.

2. Co-benefits may relate to:

• increased ecosystem stability;

• habitat restoration;

• diversified income streams;

• reduced pressure on natural forests;

• gender-inclusive employment opportunities;

• improved access to sustainable energy sources.

1. The PCS SDG Integrity Standard (PCS-SDG-007) outlines how projects should document contributions to Sustainable Development Goals. Monitoring of SDG outcomes must rely on measurable indicators rather than anecdotal claims.

Table 32. Examples of Forestry Co-Benefits and Relevant Indicators

Co-Benefit	Indicator
Biodiversity recovery	Species richness, canopy structure, habitat continuity
Soil improvement	SOC trends, erosion reduction, ground cover density
Water regulation	Streamflow stability, improved infiltration
Community benefits	Employment records, income diversification data
Energy substitution	Reduction in fuelwood demand

9.7 Non-Permanence Risk and Buffer Requirements

1. Forestry projects are vulnerable to non-permanence risks such as fire, pest outbreaks, illegal harvesting, storms, droughts, and institutional failure. PCS requires every forestry project to conduct a comprehensive risk assessment using the PCS Non-Permanence Risk Tool (PCS-TA-005). This assessment produces a risk score used to determine the buffer contribution, which is a percentage of the project's carbon benefits placed into a reserve buffer to insure against reversals.

2. The risk assessment must be updated at each monitoring cycle. Changes in forest condition, enforcement systems, stakeholder dynamics, or regional disturbance patterns may increase or decrease the risk of reversal. Buffer contributions may therefore vary over time.

9.8 Identification of Natural and Anthropogenic Risk Factors

1. Risk factors include both natural and human-induced threats. Natural risk factors involve fire regimes, climatic variability, pest prevalence, and extreme weather events. Human-induced factors include illegal logging, encroachment, land-use conflict, political instability, and inadequate project governance. The risk assessment must characterize each relevant factor, estimate its likelihood and potential severity, and document mitigation measures.

Table 33. Examples of Non-Permanence Risk Factors

Risk Category	Examples
Natural	Wildfires, drought, storms, pests, landslides
Anthropogenic	Illegal harvesting, land tenure conflicts, weak enforcement
Management	Insufficient maintenance, poor monitoring systems
Socio-economic	Market pressures, resource dependence, migration

9.9 Mitigation Measures for Non-Permanence Risks

1. Projects must implement strategies to reduce the likelihood and severity of reversals. These may include establishing fire breaks, enhancing patrol systems, conducting community awareness programs, managing fuel loads, diversifying species composition, improving governance arrangements, and maintaining continuous stakeholder engagement. Where mitigation measures reduce risk, documentation must show how these improvements were achieved.

9.10 Buffer Account Contribution

1. The buffer contribution represents the percentage of calculated net removals that must be deposited into the PCS Buffer Pool. The percentage is determined by the results of the risk assessment tool. A higher risk score results in a higher buffer contribution. Projects do not own buffer units; these serve as insurance for the system as a whole. The VVB must verify the correctness of the risk assessment and buffer calculation before any issuance occurs.

9.11 Monitoring of Safeguards and Risk Factors

1. Safeguards and risk factors must be monitored throughout the project duration. Monitoring must include documentation of community interactions, biodiversity assessments, land-use change detection through remote sensing, evaluation of governance mechanisms, and regular assessment of fire or pest risks. Each monitoring report must summarize safeguard compliance, risk trends, and the performance of mitigation strategies.

2. Safeguard breaches must be reported in accordance with PCS processes and may lead to suspension of issuance until resolved.

9.12 Documentation and Verification

1. All safeguard assessments, co-benefit analyses, and non-permanence risk evaluations must be documented and submitted with the Monitoring Report. Verification bodies will assess whether:

• safeguard processes were implemented correctly;

• community engagement was meaningful and inclusive;

• biodiversity and ecological safeguards were respected;

• SDG claims are substantiated with measurable evidence;

• risk assessments are accurate and conservative;

• buffer account contributions are correctly calculated.

Any inconsistencies or gaps must be resolved before PCUs can be issued.

Chapter 10 - Reporting Requirements

10.1 Purpose of Reporting Requirements

1. Reporting requirements ensure that all information necessary to evaluate project performance, monitor carbon stock changes, and verify environmental and social integrity is documented clearly and transparently. The Monitoring Report is the central mechanism through which the Project Developer communicates project results to the PCS Secretariat, Validation and Verification Bodies (VVBs), stakeholders, and the public via the PCS Registry.

This chapter outlines the minimum documentation that must accompany each monitoring cycle, ensuring traceability from raw field data through to the final net greenhouse gas results.

10.2 Structure of the PCS Monitoring Report

1. The Monitoring Report must follow the PCS standard template and be consistent with the methodology, the PCS Monitoring Standard, and the PCS Validation & Verification Standard. The report must present information logically and in sufficient detail for independent verification.

Table 34. Core Components of the Monitoring Report

Section	Description
Project description	Summary of project objectives, activities, and location
Boundary confirmation	Updated maps, strata, and land eligibility evidence
Monitoring period	Start and end dates of the reporting interval
Methodological application	Description of how each methodology requirement was implemented
Field data	Raw and processed measurements for each carbon pool
Remote sensing	Imagery used, classification methods, interpretation
Carbon stock changes	Results for each pool and stratum
Leakage monitoring	Evidence and quantification of leakage effects
Project emissions	Fuel use, fertilizer application, or other emissions
Risk assessment	Updated non-permanence risk evaluation
Safeguard performance	ESS compliance and community engagement
SDG contributions	Measurable co-benefit indicators
Uncertainty analysis	Estimation and justification of combined uncertainty
Supporting documentation	Annexes, data files, tables, and shapefiles

All claims in the Monitoring Report must be supported by evidence that a VVB can independently evaluate.

10.3 Reporting on Project Boundaries and Stratification

1. The Monitoring Report must include updated geospatial files illustrating the project boundary and any adjustments made since the last monitoring period. Maps must reflect current land cover, forest structure, and any newly defined or revised strata. If boundaries or strata have changed, the report must include a justification consistent with PCS rules.

2. Maps must include a legend, scale, north arrow, coordinate reference system, and footnote describing the imagery source and acquisition dates. Shapefiles must be submitted in standard GIS formats.

10.4 Reporting on Field Measurements

1. The report must include a detailed description of all field measurements performed during the monitoring period. This includes:

• the measurement protocol;

• plot locations;

• measurement thresholds;

• plot condition summaries;

• tree-level data (diameter, height, species);

• deadwood and litter sampling results;

• SOC sampling and lab analysis information (dates, methods, QA/QC practices).

1. A summary table must present key statistics such as mean carbon stock per pool and per stratum, number of plots measured, and sampling intensity.

Table 35. Example Summary Table for Field Data

Stratum	Plots Measured	AGB (tC/ha)	BGB (tC/ha)	Deadwood (tC/ha)	SOC (tC/ha)

All raw data files must be provided as machine-readable attachments.

10.5 Reporting on Remote Sensing and Geospatial Analyses

1. The Monitoring Report must describe all geospatial analyses undertaken during the reporting period. This includes:

• imagery sources and acquisition dates;

• classification approaches;

• algorithms or processing tools used;

• accuracy assessments;

• disturbance detection outcomes;

• validation against field data.

1. Projects must demonstrate how remote sensing information supports boundary confirmation, strata updates, disturbance assessments, and validation of forest growth trends.

Imagery files and classification outputs must be archived and made available for verification.

10.6 Reporting Carbon Stock Estimates and Changes

1. The report must present carbon stock estimates for all carbon pools and strata at the beginning and end of the monitoring period. Changes in carbon stocks must be shown clearly, with separate tables for baseline, project, and net values.

Table 36. Example Carbon Stock Change Summary

Stratum	Pool	Start Stock (tC)	End Stock (tC)	Change (tC)

Where project activities involve harvesting (IFM projects), harvested wood product carbon stocks and decay adjustments must be included.

Allometric equations, growth models, carbon fraction values, root-to-shoot ratios, and SOC calculation methods must be described in narrative form.

10.7 Reporting on Leakage

1. Leakage must be reported with supporting evidence demonstrating whether displacement of land use, fuelwood harvesting, grazing, or market effects occurred during the monitoring period. Where leakage is detected, the report must quantify leakage emissions in accordance with the methodology.

2. A narrative explanation must describe the causes of leakage, the areas affected, mitigation measures taken, and how values were calculated.

Table 37. Example Leakage Reporting Table

Leakage Type	Evidence	Affected Area (ha)	Emissions (tCO₂e)

10.8 Reporting Project Emissions

1. Where emissions occur due to project operations, the Monitoring Report must quantify these emissions using PCS-approved emission factors. Records of fuel use, fertilizer application, controlled burning, or other emission sources must be included. Emission factors must be cited, and calculations must be clearly presented.

10.9 Reporting Safeguards Compliance

1. Safeguard monitoring results must be presented in a dedicated section of the report. This section must describe:

• activities conducted to ensure ESS compliance;

• community engagement events;

• documented grievance processes;

• any safeguard-related incidents and resolutions;

• biodiversity monitoring outcomes;

• FPIC maintenance for indigenous communities if applicable.

1. Safeguard evidence must be consistent with the PCS-ESS requirements and include supporting documents.

10.10 Reporting Sustainable Development Contributions

1. The project must describe measurable contributions to sustainable development using indicators aligned with PCS-SDG-007. Claims must rely on quantifiable data, such as employment figures, water retention indicators, biodiversity metrics, or improvements in household energy sourcing.

2. Where co-benefits have expanded or changed, the project must document these developments and provide appropriate evidence.

Table 38. Example SDG Reporting Table

SDG Category	Indicator	Measurement Result	Verification Evidence

10.11 Reporting Non-Permanence Risk and Buffer Contribution

1. The Monitoring Report must include an updated non-permanence risk assessment using PCS-TA-005. Any changes to risk scores, mitigation measures, or governance arrangements must be documented. The associated buffer contribution must be recalculated and presented.

2. If reversals occurred due to fire, storm, disease, or human activity, the project must describe the event, quantify the carbon loss, and outline corrective actions. These reversals may trigger buffer withdrawal or other mitigation actions as specified by PCS.

10.12 Reporting Uncertainty Analysis

1. The Monitoring Report must include a complete uncertainty analysis covering measurement error, model uncertainty, sampling variance, baseline projection uncertainty, and leakage estimation uncertainty. Combined uncertainty must be presented as a percentage of net GHG benefits.

2. If combined uncertainty exceeds PCS thresholds, the report must include a justification and describe measures planned to reduce uncertainty in future monitoring cycles.

10.13 Final Presentation of Net GHG Emission Reductions and Removals

1. The concluding section of the Monitoring Report must present the final net GHG emission reductions and removals after applying:

• baseline adjustments;

• leakage deductions;

• project emissions;

• uncertainty considerations;

• buffer contributions.

1. The final numbers must be presented in both tCO₂ and PCUs eligible for issuance.

Table 39. Final Net GHG Accounting Summary

Component	Value (tCO₂e)
Project carbon stock change
Baseline carbon stock change
Leakage emissions
Project emissions
Net GHG removals
Buffer deduction
PCUs eligible for issuance

All values must match the supporting calculations provided throughout the Monitoring Report.

Annex A - Carbon Pool Measurement Equations

1. Annex A provides the standardized equations and calculation frameworks required to estimate carbon stocks and carbon stock changes for all pools included in this methodology. The equations presented here must be applied consistently across all monitoring periods to ensure methodological integrity, comparability, and transparency.

2. Where applicable, the equations align with established principles from IPCC 2006 Guidelines (AFOLU), UNFCCC A/R CDM methodologies, and recognized peer-reviewed biomass science. Any alternative equations or parameters must be justified scientifically and approved during validation.

A.1 Above-Ground Biomass (AGB)

1. AGB represents the largest and most dynamic carbon pool in forestry projects. It is estimated using allometric equations that convert tree measurements (typically diameter at breast height and, in some cases, height) into biomass estimates.

2. The general structure of an allometric equation is:

AGB_tree = a × (DBH)^b × (H)^c × (ρ)^d

Where:

• a, b, c, d = species or region-specific coefficients

• DBH = diameter at breast height (cm)

• H = tree height (m), if required

• ρ = basic wood density (g/cm³)

If height or species-specific equations are not available, height-based or multi-species generalized equations may be used.

Table A-1. Examples of Accepted Allometric Equation Forms

Forest Type	Equation Structure	Notes
Tropical moist	AGB = 0.0673 × (ρ × DBH² × H)^0.976	Widely used pantropical form (Chave et al.)
Tropical dry	AGB = exp(−1.996 + 2.32 × ln(DBH))	Height-independent form
Temperate forests	AGB = a × DBH^b	Species-group equations
Boreal forests	AGB = exp(a + b × ln(DBH))	Suitable for conifers

Total AGB per plot is the sum of tree-level AGB estimates, scaled to a per-hectare basis.

AGB_plot (t/ha) = (Σ AGB_tree within plot) / Plot area (ha)

Carbon fraction (typically 0.47–0.50) is applied to convert biomass to carbon.

A.2 Below-Ground Biomass (BGB)

1. BGB is estimated using root-to-shoot ratios applied to AGB. Ratios vary by ecological zone and must be selected based on credible literature.

BGB = AGB × R

Where R is the root-to-shoot ratio for the species or forest type.

Table A-2. Typical Root-to-Shoot Ratios

Forest Type	Ratio (R)
Tropical evergreen	0.24
Tropical dry	0.28
Temperate	0.26
Boreal	0.40

Carbon fraction must also be applied to convert BGB to carbon.

A.3 Deadwood Carbon

1. Deadwood consists of standing dead trees, fallen logs, and coarse woody debris. The volume of each piece must be estimated and converted to biomass using species- or region-specific wood densities.

For downed deadwood using line-intersect sampling:

Volume = (π² × Σ (diameter_i²)) / (8 × L)

Where L is the total length of transect sampled.

Biomass_deadwood = Volume × Wood density

C_deadwood = Biomass_deadwood × Carbon fraction

Standing deadwood uses taper functions or height-class adjustment factors.

A.4 Litter Carbon

1. Litter biomass is estimated through destructive sampling within defined quadrats.

Biomass_litter = (Dry weight of sample / Sample area)

C_litter = Biomass_litter × Carbon fraction

If carbon fraction is not measured directly, a default of 0.40–0.45 may be applied depending on material type.

A.5 Soil Organic Carbon (SOC)

1. Soil organic carbon stock is calculated per depth interval using:

SOC_stock = Bulk density × Carbon concentration × Depth × Conversion factor

Where:

• bulk density = g/cm³

• carbon concentration = %C

• depth = cm

• conversion factor = 0.1 (converts g/cm² to tC/ha)

Table A-3. SOC Calculation Parameters

Parameter	Units	Description
Bulk density	g/cm³	Mass of soil per volume, measured in lab
Carbon concentration	%	Dry combustion or equivalent method
Depth	cm	Sampling depth must be consistent across cycles
Conversion factor	—	Standard factor converting SOC to tC/ha

SOC for each layer is summed to produce total SOC per hectare.

A.6 Harvested Wood Products (HWP)

1. Applicable only to improved forest management (IFM) projects.

For each product category:

C_HWP = Harvested biomass × Conversion factor × Remaining fraction(t)

Where the remaining fraction is derived from decay functions.

Product categories include:

Product	Typical Half-Life
Sawnwood	35–50 years
Panels	20–30 years
Paper	2–5 years

Decay must follow first-order decay equations.

A.7 Carbon Conversion Factors

1. Biomass-to-carbon conversion must use scientifically credible values.

Table A-4. Conversion Factors

Parameter	Default Value	Notes
Carbon fraction of woody biomass	0.47	May vary by species (0.46–0.50)
Carbon fraction of litter	0.40–0.45	Material dependent
Wood density (ρ)	Species-specific	Defaults applied with justification

Wood density values must be obtained from region-relevant databases or peer-reviewed sources.

A.8 Aggregation of Plot-Level Carbon to Stratum and Project Level

1. For each carbon pool:

2. Calculate carbon stock per plot.

3. Average across plots in the same stratum.

4. Multiply by the area of the stratum.

C_stratum = Mean C_per_plot × Area_stratum

Total project carbon stock is:

C_project = Σ C_stratum across all strata

A.9 Carbon Stock Change

1. For any carbon pool i and stratum s:

ΔC_i,s = C_i,s (t₂) – C_i,s (t₁)

Project-wide carbon stock change is the sum of all strata and all pools.

Annex B - Allometric Models And Parameters

1. Annex B provides guidance on selecting, justifying, and applying allometric equations and related parameters used to estimate above-ground and below-ground biomass in forestry projects. Allometric models are fundamental to biomass estimation and therefore must be chosen with care, reflecting scientific rigor, ecological relevance, and applicability to the project area’s forest types and species compositions.

B.1 Principles for Selecting Allometric Models

1. Allometric equations convert measurable tree attributes—primarily DBH, height, and wood density—into estimates of tree biomass. PCS requires that the selection of allometric models be based on empirical studies appropriate to the:

• ecological zone,

• species or functional groups,

• size range of trees,

• forest conditions (mature, secondary, degraded),

• measurement methods available to the project.

1. Preference must be given to models developed from destructive sampling in regions ecologically similar to the project location. Models that include wood density and height improve accuracy, but height-independent models may be used when height measurement is not feasible or where validated equations exist.

B.2 Recommended Allometric Equation Sources

1. The following sources are considered scientifically robust and widely accepted for large-scale biomass estimation:

Table B-1. Primary References for Allometric Model Selection

Region / Context	Source	Notes
Pantropical moist forests	Chave et al. (2005, 2014)	Standard reference models with wood density
Temperate forests	Jenkins et al. (2003)	Widely used species-group equations
Boreal forests	Lambert et al., Penman et al.	Suitable for conifer-dominated stands
National Forest Inventories	Country-specific	Preferred when locally developed
Mixed species or unknown	Generalized equations	Must be justified and conservative

Projects may use equations outside these references only when ecological similarity and methodological robustness are demonstrated.

B.3 Pantropical Allometric Models (Chave et al.)

1. For tropical regions, pantropical equations provide reliable estimates across diverse species groups by incorporating wood density. These equations are preferred when local species-specific models are unavailable.

Table B-2. Pantropical Allometric Equations

Forest Type	Equation Structure	Parameters
Moist forest	AGB = 0.0673 × (ρ × DBH² × H)^0.976	DBH ≥ 5 cm
Dry forest	AGB = exp(−1.996 + 2.32 × ln(DBH))	Height not required
Wet forest	AGB = 0.0509 × ρ × DBH² × H	Suitable for tall-canopy forests

Where:

• ρ = wood density (g/cm³)

• DBH = diameter at breast height (cm)

• H = height (m)

Wood density values must be species-specific or taken from harmonized databases such as the Global Wood Density Database.

B.4 Temperate Forest Allometric Models

1. Temperate forests often rely on species-group equations developed from destructive sampling across major forest types. The equations are typically of the form:

AGB = a × DBH^b

Table B-3. Examples of Temperate Forest Allometric Parameters

Species Group	a	b
Hardwood broadleaf	0.0509	2.54
Softwood conifer	0.0280	2.68
Mixed temperate species	Varies	National forest inventory datasets

Where national forest inventory models exist, these are preferred over generalized models.

B.5 Boreal Forest Allometric Models

1. Boreal forests exhibit distinct growth patterns and wood densities. Allometric equations commonly used include exponential DBH functions.

Table B-4. Example Boreal Allometric Models

Species	Equation Structure	Notes
Spruce	AGB = exp(a + b × ln(DBH))	Species-specific
Pine	Similar exponential forms	Must use regional parameters
Mixed boreal stands	Generalized models	Conservative model selection recommended

Projects must ensure that boreal-specific high root-to-shoot ratios are applied for below-ground biomass estimation.

B.6 Wood Density Values (ρ)

1. Wood density strongly influences biomass estimates. Projects must use species-level wood density values whenever possible; genus-level values may be used when species-level data are unavailable. If neither exists, functional-group or regional averages may be applied conservatively.

Table B-5. Examples of Wood Density Ranges

Species Group	Density Range (g/cm³)
Tropical hardwood	0.55–0.80
Tropical pioneer species	0.30–0.50
Temperate softwood	0.35–0.45
Boreal conifers	0.38–0.45

Wood density values must be referenced to their original dataset, including sampling methodology.

B.7 Height-Diameter Relationships

1. Where tree height is required for the allometric model but cannot be measured for every tree, height-diameter models may be applied. These models must be developed from local data or regional forestry research.

Example form:

H = α + β × ln(DBH)

Where α and β are parameters derived from local height measurements.

Height-diameter models must be recalibrated if stand structure changes significantly over time.

B.8 Allometric Model Validation Requirements

1. Projects must demonstrate that selected models are appropriate by:

• citing the ecological similarity between source studies and the project area;

• showing species or functional group alignment;

• confirming applicability across the DBH range observed;

• validating with project-specific biomass studies where available.

VVBs may request sensitivity analyses comparing alternative plausible models.

B.9 Application of Allometric Models in Mixed-Species Stands

1. In stands with numerous species where species-specific models cannot be applied, the project may:

• classify trees into functional groups (e.g., light-wood, medium-wood, hardwood);

• apply generalized pantropical or regional models;

• apply species-average wood density values.

The approach must minimize the risk of systematic bias and favour conservativeness.

B.10 Below-Ground Biomass Equations

1. Below-ground biomass is calculated using root-to-shoot ratios as described in Annex A. These ratios should reflect the forest type, tree age, and ecological conditions. Where research supports species-specific ratios, these may replace general defaults.

Root biomass equations directly estimating below-ground biomass (e.g., for mangrove or coastal forest species) may be used if validated and appropriate.

B.11 Documentation Requirements for Allometric Models

1. Projects must provide the following for each model used:

• the equation and coefficient values;

• the reference source (full citation);

• ecological zone of the source study;

• species representativeness;

• measurement thresholds used;

• any deviations from source conditions;

• justification for applicability.

Table B-6. Example Documentation Template

Element	Required Information
Equation	Full equation with variables
Source	Author, year, publication, region
Forest type	Ecological zone of origin
Species coverage	Species or functional group represented
DBH range	Applicability limits
Wood density	Source and values used
Justification	Explanation of model suitability

This ensures transparency and verifiability across all monitoring cycles.

Annex C - Default Values For Biomass And Soil Carbon Estimation

1. Annex C provides standardized default values that may be applied when project-specific measurements or species-specific parameters are unavailable. Default values may only be used when justified, and their applicability must be consistent with ecological zone, forest type, and species composition. Projects must apply default values conservatively and document all assumptions.

2. The values in this annex originate from IPCC 2006 Guidelines, the IPCC Emission Factor Database, global wood density datasets, peer-reviewed allometric studies, and recognized forest carbon assessments.

C.1 Default Carbon Fraction Values

1. The carbon fraction represents the proportion of biomass that is carbon. While the precise ratio varies by species, wood type, and material, the following default values may be used in the absence of more specific estimates.

Table C-1. Default Carbon Fraction Values

Biomass Component	Carbon Fraction	Notes
Woody biomass (AGB/BGB)	0.47	Applicable across most species
Hardwood species	0.48–0.50	Use 0.47 if uncertain
Softwood species	0.45–0.47	Use 0.47 unless species data exist
Litter	0.40–0.45	Use lowest value unless measured
Deadwood	0.47	Assumed consistent with biomass
Harvested wood products	0.47	For long-lived products

C.2 Default Wood Density Values

1. Wood density (ρ) plays a major role in biomass estimation. When species-level values are unavailable, genus-level or functional group values may be applied. If still unknown, regional defaults should be used conservatively.

Table C-2. Example Default Wood Density Values by Species Group

Species Group	Default Density (g/cm³)	Notes
Tropical hardwood	0.60	Use for dense, slow-growing species
Tropical mixed species	0.50	General-purpose default
Tropical light-wood species	0.40	Pioneer or fast-growing species
Temperate hardwood	0.56	Broadleaf species; moderate density
Temperate softwood	0.42	Conifer species
Boreal conifer	0.40	Spruce, pine, fir group
Mangroves (if spillover)	0.65	Included for completeness; not used in this methodology

Projects must reference the Global Wood Density Database or national forest datasets where available.

C.3 Default Root-to-Shoot Ratios

1. Root-to-shoot ratios allow estimation of below-ground biomass when direct root measurements are not feasible. The ratios below reflect IPCC biome defaults.

Table C-3. Default Root-to-Shoot Ratios

Forest Type	Root-to-Shoot Ratio
Tropical moist forest	0.24
Tropical dry forest	0.28
Tropical montane forest	0.20
Temperate forest	0.26
Boreal forest	0.40
Degraded secondary forest	0.25–0.30

When strata contain mixed-age or mixed-species stands, a conservative ratio should be selected at the upper end of the plausible range.

C.4 Default Biomass Expansion Factors (BEFs)

1. In some IFM projects, merchantable timber volume may be measured rather than direct biomass. Biomass Expansion Factors (BEFs) convert merchantable volume to total above-ground biomass, accounting for branches, leaves, and non-commercial components.

Table C-4. Default BEFs

Forest Type	BEF	Notes
Tropical broadleaf	1.60	Applies to humid tropics
Tropical dry forest	1.40	Lower branch mass
Temperate hardwood	1.30	Typical regional default
Temperate softwood	1.20	Conifers have lower BEFs
Boreal conifers	1.15	Conservative application advised

BEFs must be used only when volume-based measurements are justified and documented.

C.5 Default Biomass-to-Carbon Conversion Factors

1. Where biomass is converted to carbon directly, the following defaults apply unless species-specific data exist.

Table C-5. Biomass-to-Carbon Conversion Values

Material	Conversion Factor
Woody biomass	0.47
Bark	0.45
Roots	0.47
Leaves	0.42
Litter	0.40

C.6 Default Soil Organic Carbon (SOC) Values

1. SOC varies widely across soil types, climate zones, and land-use histories. In the absence of direct sampling, default values may be applied only for preliminary assessments and must later be replaced with measurements. However, for degraded systems with well-documented SOC characteristics, defaults may be acceptable when justified.

Table C-6. SOC Defaults by Soil Type (Top 30 cm)

Soil Type	SOC Stock (tC/ha)	Notes
Tropical mineral soils	35–65	Lower end for degraded areas
Temperate mineral soils	60–100	Varies by moisture
Boreal mineral soils	80–140	Cold climates preserve SOC
Volcanic soils	150–250	High SOC potential
Sandy soils	20–40	Low retention capacity
Clay-rich soils	60–120	Stable SOC fractions

Projects must not rely solely on SOC defaults beyond the first monitoring cycle.

C.7 Default Deadwood Density Values

1. Deadwood carbon depends on density and decay class. If direct measurement is unavailable:

Table C-7. Default Deadwood Density Values

Decay Class	Density (g/cm³)
Class 1 (fresh)	0.50
Class 2	0.40
Class 3	0.30
Class 4	0.20
Class 5 (highly decayed)	0.15

Carbon fraction of deadwood uses default biomass carbon ratios unless measured.

C.8 Default Values for Harvested Wood Product (HWP) Lifetimes

1. HWPs store carbon for varying durations. For IFM projects, the following half-life defaults apply:

Table C-8. Half-Lives for HWP Categories

Product Category	Half-Life (Years)
Sawnwood	35–50
Plywood	20–30
Panels	15–25
Paper products	2–5
Bioenergy	Immediate oxidation

These half-lives are used with first-order decay models to estimate remaining carbon.

C.9 Default Fuel Emission Factors

1. Where project emissions are based on fuel consumption, default emission factors may be used.

Table C-9. Diesel and Gasoline Emission Factors

Fuel Type	Default Emission Factor (kg CO₂e/L)
Diesel	2.68
Gasoline	2.31
Biodiesel	1.90 (varies by blend)

Projects may use national inventory values when more accurate.

Annex D - Sampling Guidelines And Plot Design

1. Annex D establishes the minimum standards for sampling design, plot layout, field measurement procedures, and data handling required to estimate carbon stocks and carbon stock changes with sufficient accuracy. These guidelines ensure that sampling is statistically robust, repeatable across monitoring cycles, and auditable by Validation and Verification Bodies (VVBs).

2. Sampling must follow a statistically sound framework that reflects the spatial heterogeneity of the project area, complies with PCS uncertainty thresholds, and provides confidence in reported carbon benefits.

D.1 Principles of Sampling Design

1. Sampling design must be based on scientific principles that ensure representativeness and minimize sampling error. Stratification, plot distribution, sample size determination, and measurement consistency are critical to generating reliable estimates.

2. The sampling design must:

• reflect ecological variability across strata;

• provide statistically defensible estimates of mean carbon stocks;

• achieve PCS uncertainty thresholds for AGB, SOC, and other pools;

• remain consistent across monitoring cycles;

• avoid bias by ensuring random or systematic plot placement.

1. Sampling plans must be documented before implementation and reviewed periodically as forest conditions evolve.

D.2 Stratified Random Sampling Framework

1. Stratification increases sampling efficiency and reduces variance by grouping areas with similar forest attributes. Each stratum must be sampled independently. The number of sample plots in each stratum must reflect both stratum size and internal variability.

Table D-1. Determinants of Sampling Intensity per Stratum

Determinant	Influence on Sampling Effort
Stratum area	Larger strata require more plots
Variability in biomass	Higher variability increases required sample size
Stage of forest development	Young forests may require more frequent sampling
Ecological heterogeneity	Diverse stands require additional plots

The sampling design must ensure that plots adequately represent each stratum’s characteristics.

D.3 Determining Sample Size

1. Sample size must be calculated such that carbon stock estimates reach the uncertainty levels required by PCS. While exact formulas may vary, a common approach uses:

• the coefficient of variation (CV) within each stratum,

• desired confidence level (typically 90–95%),

• allowable sampling error (as defined in PCS standards).

1. Projects may use statistical tools or established sample size equations to justify plot numbers. All calculations must be included in the Monitoring Report.

D.4 Plot Layout and Design

1. Permanent sample plots (PSPs) must be established within each stratum, using either circular or rectangular shapes. PSPs must remain in place for the duration of the crediting period unless clear justification is provided for adjustments.

Table D-2. Recommended Plot Specifications

Forest Condition	Plot Shape	Plot Size	Notes
Dense mature forest	Circular	500–1,000 m²	Reduces boundary errors
Secondary or regenerating forest	Circular or rectangular	400–600 m²	Adjusted to tree density
Early-stage plantations or afforestation	Rectangular	200–400 m²	Allows sampling uniform rows
Degraded forests	Circular	250–500 m²	Captures patchiness

Circular plots minimize boundary ambiguity, while rectangular plots may be suitable where forest stands or planting rows follow linear patterns.

D.5 Plot Location and Georeferencing

1. Plots must be located using statistically valid methods (random, systematic-random, or stratified random). Each plot must be precisely georeferenced using GPS/GNSS technology, with recorded accuracy typically within five meters. Plots must be permanently marked with durable markers, and their positions must be mapped in GIS-compatible formats.

2. Maps submitted to PCS must show:

• plot locations;

• strata boundaries;

• exclusion zones;

• major landscape features.

D.6 Measurement Procedures for Trees

1. Tree measurements must follow standardized forestry protocols. All trees above the minimum diameter threshold must be measured. The preferred measurement height is at 1.3 meters above ground (DBH), ensuring consistency across cycles.

2. Measurements must include:

• diameter at breast height (DBH);

• height (if required by the allometric model);

• species or functional group;

• tree condition (live, dead, damaged).

1. Diameter must be measured perpendicular to the stem axis. Irregularities such as buttresses must be addressed by applying adjusted measurement positions following FAO/UNFCCC guidelines.

D.7 Measurement of Deadwood, Litter, and Non-Tree Vegetation

1. Deadwood must be measured using line-intersect sampling for downed logs and fixed-area sampling for standing dead trees. Each piece must be classified by decay class and measured for diameter and, if appropriate, length.

2. Litter must be sampled through destructive collection within defined quadrats. Non-tree vegetation may be included if the project expects significant carbon changes in shrub or understory layers.

D.8 Soil Organic Carbon Sampling

1. SOC sampling must follow PCS-TA-002 and include:

• consistent sampling depth across cycles (commonly 0–30 cm);

• extraction of soil cores using uniform techniques;

• measurement of bulk density for each stratum;

• laboratory analysis of carbon concentration.

1. Composite sampling may be used within narrow strata, but samples must be managed in a way that preserves spatial integrity and variance estimation.

Table D-3. SOC Sampling Requirements

Parameter	Requirement
Depth	Uniform (e.g., 0–30 cm)
Sampling frequency	Every 10 years or per PCS rules
Number of cores	Must reflect variability of soils
Laboratory standard	Dry combustion or equivalent

D.9 Quality Assurance and Quality Control (QA/QC)

1. Projects must implement QA/QC procedures for all sampling steps. These include:

• training field crews;

• calibrating measuring equipment;

• remeasuring a subset of trees;

• validating GPS coordinates;

• checking data entries;

• applying laboratory QA/QC protocols for SOC.

1. The Monitoring Report must describe QA/QC measures and summarize any deviations or issues encountered.

D.10 Handling Disturbances, Missing Plots, and Plot Adjustments

1. If natural or anthropogenic disturbances affect sample plots, the project must document the disturbance type and date and determine whether the plot remains representative of the stratum. In cases of complete plot loss (e.g., due to construction, erosion, or accidental destruction), replacement plots may be established using the same statistical placement method.

2. Missing data must not lead to systematic bias. The project must explain any plot adjustments, including changes in accessibility, boundary corrections, or updated sampling intensities.

D.11 Data Management and Archiving

1. All field data must be recorded using standardized forms or digital devices. Data must be archived in a structured database and retained for the entire crediting period plus any required post-project interval. Records must include:

• raw measurement sheets;

• GPS data;

• laboratory results;

• QA/QC logs;

• plot photographs;

• geospatial files.

VVBs must have access to all raw data for verification.

D.12 Reporting Sampling Results

1. The Monitoring Report must include summaries of sampling efforts, measurement outcomes, variance estimates, and stratum-level carbon estimates. Sample sizes for each carbon pool and stratum must be clearly reported.

Table D-4. Example Summary of Sampling Results

Stratum	Plots Sampled	Mean AGB (tC/ha)	Standard Error	CV (%)	Meets PCS Uncertainty Threshold?

This ensures transparency and facilitates independent verification.

Annex E - Leakage Calculation Examples And Templates

1. Leakage refers to the greenhouse gas emissions that occur outside the project boundary as a direct result of project activities. This annex provides standardized templates and worked examples to support transparent and replicable leakage calculations. These examples illustrate how Project Developers must structure data, document assumptions, and apply conservative quantification methods consistent with Chapter 5 of this methodology.

E.1 Purpose of Leakage Calculation Templates

1. Leakage assessments are often complex, involving socio-economic behavior, land-use displacement, fuelwood demand, or market dynamics. The templates provided in this annex serve three functions:

2. illustrate how evidence is compiled;

3. standardize calculation structures;

4. support VVB review through transparent numerical steps.

5. The examples are illustrative; projects must adapt values to their specific context, supported by local data and literature.

E.2 General Structure of Leakage Calculations

1. All leakage calculations follow this structure:

2. Identify the leakage source and determine relevance.

3. Determine the affected area and change in activity outside the project boundary.

4. Estimate carbon stocks or emission factors for those areas.

5. Calculate total emissions attributable to leakage.

6. Document evidence and conservativeness.

E.3 Example 1 - Activity-Shifting Leakage (Fuelwood Collection)

1. A community previously collected fuelwood inside the project area. The project restricts access, and approximately 20 households relocate fuelwood collection to nearby forest patches outside the boundary.

Step 1 – Determine displaced activity

Household survey indicates each household previously collected 3 tonnes of fuelwood/year from the project area.

Step 2 – Estimate new extraction outside project boundary

New extraction = 20 households × 3 tonnes/year

Total displacement = 60 tonnes of fuelwood/year

Step 3 – Convert biomass to carbon

Assuming wood density = 0.50 g/cm³, carbon fraction = 0.47:

Carbon per tonne biomass = 0.47 tC

Total carbon removed = 60 × 0.47 = 28.2 tC/year

Step 4 – Convert carbon to CO₂

28.2 tC × 3.664 = 103.3 tCO₂/year

Step 5 – Document justification

The Monitoring Report must include the household survey, fuelwood use records, alternative energy availability, and maps of impacted forests.

Table E-1. Fuelwood Leakage Calculation Template

Variable	Value	Unit
Number of households affected	20	households
Fuelwood per household	3	t biomass/yr
Total displaced biomass	60	t biomass/yr
Carbon fraction	0.47	—
Carbon displaced	28.2	tC/yr
Emissions (tCO₂)	103.3	tCO₂/yr

E.4 Example 2 - Grazing Displacement Leakage

1. A degraded forest under restoration previously served as grazing land. When fenced for regeneration, livestock grazing shifts to a nearby grassland patch, causing potential biomass reduction there.

Step 1 – Determine displaced grazing area

Baseline grazing area inside project = 50 ha

Post-project grazing continues on 30 ha outside the boundary.

Step 2 – Estimate biomass loss in new grazing area

Grass biomass reduction estimated at 1.5 t dry matter/ha/year.

Total biomass loss = 30 ha × 1.5 t/ha = 45 t biomass/year

Step 3 – Convert to carbon

Carbon displaced = 45 × 0.45 (carbon fraction for grass) = 20.25 tC/year

Step 4 – Convert to CO₂

20.25 × 3.664 = 74.2 tCO₂/year

Table E-2. Grazing Leakage Calculation Template

Variable	Value	Unit
Displaced area	30	ha
Biomass reduction	1.5	t/ha/yr
Total biomass removed	45	t/yr
Carbon fraction	0.45	—
Carbon loss	20.25	tC/yr
Emissions	74.2	tCO₂/yr

E.5 Example 3 - Market Leakage (Timber Displacement)

1. An improved forest management (IFM) project reduces timber harvesting by 5,000 m³/year compared to business-as-usual. Regional demand remains constant, so part of this reduction is offset by increased harvesting elsewhere.

Step 1 – Determine displaced volume

Assume 30% leakage factor based on national studies.

Displaced volume = 5,000 m³ × 0.30 = 1,500 m³/year

Step 2 – Convert volume to biomass

Assume wood density = 0.55 g/cm³ → 0.55 t/m³

Biomass displaced = 1,500 × 0.55 = 825 t biomass/year

Step 3 – Convert biomass to carbon

Carbon fraction = 0.47 → Carbon = 825 × 0.47 = 387.75 tC/year

Step 4 – Convert to CO₂

387.75 × 3.664 = 1,420.7 tCO₂/year

Table E-3. Market Leakage Template

Variable	Value	Unit
Baseline harvest reduction	5,000	m³/yr
Leakage factor	0.30	—
Displaced harvest	1,500	m³/yr
Biomass density	0.55	t/m³
Biomass displaced	825	t/yr
Carbon displaced	387.75	tC/yr
Leakage emissions	1,420.7	tCO₂/yr

E.6 Example 4 - Agricultural Activity Displacement

1. A reforestation project converts 40 ha of marginal cropland to forest. Farmers shift cultivation to a hillside area that previously had low agricultural activity.

Step 1 – Determine displaced cropland area

Displaced = 40 ha

Step 2 – Estimate SOC loss from new cultivation area

SOC loss rate = 0.5 tC/ha/year

Total SOC loss = 40 × 0.5 = 20 tC/year

Step 3 – Convert to CO₂

20 × 3.664 = 73.3 tCO₂/year

Table E-4. Agricultural Leakage Template

Variable	Value	Unit
Displaced area	40	ha
SOC loss rate	0.5	tC/ha/yr
Total SOC loss	20	tC/yr
Leakage emissions	73.3	tCO₂/yr

E.7 Consolidating Leakage Across Sources

1. Where more than one leakage source applies, total leakage must be summed:

LE_total = LE_fuelwood + LE_grazing + LE_market + LE_agriculture + …

A final table must be included in the Monitoring Report.

Table E-5. Consolidated Leakage Summary

Leakage Source	Emissions (tCO₂/yr)
Fuelwood displacement
Grazing displacement
Market leakage
Agricultural expansion
Other (specify)
Total Leakage	Σ

Annex F - Example Monitoring Tables

1. Annex F provides standardized tables that Project Developers must use when compiling Monitoring Reports. These tables ensure consistent reporting of field measurements, carbon pool estimates, leakage, uncertainty, and net GHG benefits across all PCS forestry projects. Verification Bodies (VVBs) rely on these tables to validate the integrity and completeness of project data.

Tables provided in this annex are examples; projects may expand or adapt them, provided the structure remains fully transparent and all PCS-required data are included.

F.1 Plot Inventory Summary Tables

1. These tables provide an overview of the sampling effort, plot distribution, and raw measurement coverage.

Table F-1. Sample Plot Summary by Stratum

Stratum ID	Area (ha)	Number of Permanent Plots	Plots Measured This Period	Plot Size (m²)	Stocking Characteristics

F.2 Carbon Stock Estimates by Pool and Stratum

1. This table presents the carbon stock estimates at the start and end of the monitoring period for each carbon pool.

Table F-2. Carbon Stock Estimates (tC/ha)

Stratum	Pool	Start of Period (tC/ha)	End of Period (tC/ha)	Change (tC/ha)
Stratum 1	AGB
	BGB
	Deadwood
	Litter
	SOC
Stratum 2	...

F.3 Project Carbon Stock Change (Absolute Values)

Table F-3. Total Carbon Stock Change by Stratum (tC)

Stratum	Area (ha)	AGB Change (tC)	BGB Change (tC)	Deadwood Change (tC)	SOC Change (tC)	Total Change (tC)

F.4 Baseline Carbon Stock Change

Table F-4. Baseline Carbon Stock Change (tC)

Stratum	Baseline AGB (tC)	Baseline BGB (tC)	Baseline SOC (tC)	Total Baseline Change (tC)

F.5 Comparison of Baseline and Project Scenario

Table F-5. Net Carbon Stock Change Before Leakage (tC)

Stratum	Project Carbon Change (tC)	Baseline Carbon Change (tC)	Net Change (tC)

F.6 Leakage Reporting Table

1. This table provides a standardized summary of all leakage emissions quantified during the period.

Table F-6. Leakage Emissions Summary (tCO₂e)

Leakage Source	Description	Evidence Used	Emissions (tCO₂e)
Fuelwood displacement
Grazing displacement
Market leakage
Agricultural expansion
Other (specify)
Total Leakage Emissions			Σ

F.7 Project Emissions Reporting Table

Table F-7. Project Emissions (tCO₂e)

Emission Source	Activity Data	Emission Factor	Total Emissions (tCO₂e)
Fuel consumption
Fertilizer application
Controlled burning
Transport and machinery
Total Project Emissions			Σ

F.8 Net GHG Emission Reductions and Removals

1. This table produces the final value used for PCU issuance.

Table F-8. Final Net GHG Reductions and Removals (tCO₂e)

Component	Value (tCO₂e)
Gross project removals
Baseline emissions
Project emissions
Leakage emissions
Net GHG Reductions/Removals	= Project – Baseline – Leakage – Emissions

F.9 Buffer Contribution Calculation

Table F-9. Non-Permanence Risk and Buffer Allocation

Risk Category	Risk Score (%)	Contribution (%)	Notes
Natural risk
Anthropogenic risk
Management risk
Socioeconomic risk
Total Buffer Contribution	Σ Risk	Final %

The Monitoring Report must multiply the net removals (tCO₂) by the buffer percentage to determine the deduction.

F.10 Final PCU Issuance Table

Table F-10. PCU Issuance Summary

Component	Value (tCO₂e/PCUs)
Net GHG Reductions/Removals
Buffer Deduction
PCUs Eligible for Issuance	Net – Buffer

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End of PCS-MA-001 (v1.0 draft) methodology content.