Logged to Protected Forest v1.0

1.0

Introduction

This Module provides the requirements and procedures for the calculation of net carbon dioxide equivalent (CO₂e) removal from the atmosphere through improved forest management (IFM) practices that protect forests from planned logging operations. This Module addresses scenarios where forests with active timber concessions or legal harvest allocations would undergo logging under baseline conditions but are instead maintained as intact, protected forests under the Project.

Commercial timber harvest encompasses a range of silvicultural systems employed globally to extract merchantable wood products from forests. Harvest practices include selective logging, clear-cutting, keyhole rotation, shelterwood systems, seed tree systems, group selection, and various hybrid approaches adapted to site-specific conditions, market demands, and regulatory frameworks¹^,².

While timber harvest systems vary substantially in their ecological outcomes, all forms of commercial harvest result in short-term carbon stock reductions relative to undisturbed forest conditions. Clear-cutting operations remove nearly all aboveground biomass from harvest areas, creating temporary non-forest conditions before regeneration³ on rotation cycles of 25-120 years⁴. Selective logging, while it maintains continuous forest cover through rotation cycles⁵, generates carbon emissions through direct extraction of merchantable timber, collateral damage to residual stands⁶^,⁷, the establishment of forestry infrastructure (e.g., roads, skid trails, landing areas), and altered forest structure that impacts the regeneration dynamics and future carbon accumulation rates of the forest⁸^,⁹. Shelterwood and seed tree systems cumulatively remove the majority of original stand biomass while managing for specific regeneration outcomes¹⁰, often requiring additional maintenance which increases GHG emissions¹⁰^,¹¹.

Forest protection from commercial timber harvest — regardless of the specific silvicultural practice(s) employed — delivers multiple climate, community, and ecological benefits. Protected forests maintain their capacity for continued carbon sequestration and storage, maintain soil carbon pools otherwise degraded by harvest operations, and sustain the forest structural integrity and biodiversity that enhance ecosystem resilience to climate change¹²^,³^,⁸^,⁹. Research demonstrates that forest-based natural climate solutions can provide over two-thirds of the 11.3 gigatons CO₂e per year of cost-effective mitigation needed by 2030 to stabilize warming below 2°C, with forest conservation and improved management representing pathways with additional co-benefits¹³^,¹⁴.

However, forest protection projects have traditionally faced substantial methodological challenges in credibly quantifying carbon benefits. Legacy standards and methodologies have relied on static baselines of projected harvest schedules over multi-decadal time periods, introducing considerable uncertainty around harvest timing and intensity, operational efficiency, and collateral impacts. These uncertainties have led to systematic concerns about baseline accuracy and over-crediting in past improved forest management carbon projects¹⁵^,¹⁶.

This Module addresses these methodological challenges by taking a scientifically rigorous approach that combines legal and operational validation of baseline harvest scenarios with a dynamic baseline approach that compares project forests to similar reference forests within the same region undergoing commercial timber harvest operations, accounting for variations in forest type, forest structure, species composition, operational accessibility, regulatory environment, economic context, management history, and site conditions. The Module employs advanced remote sensing technology, including LiDAR-enhanced forest inventories, to monitor carbon accumulation with high precision across The Project while maintaining rigorous standards for measurement, reporting, and verification. This Module thus ensures accurate quantification of additional carbon benefits and reduced field-based verification costs while easing the technical burden on Project Proponents through continuous change detection owned jointly by Isometric and The Project Proponent.

To ensure high ecological fidelity, project crediting durations are established based on the expected maturity of the specific forest types, with a required ongoing monitoring period to ensure meaningful carbon storage duration.

This Module accounts for the quantification of the gross amount of CO₂e removed via enhanced carbon storage in forest biomass, as well as all cradle-to-grave life-cycle Greenhouse Gas (GHG) emissions associated with the implementation process. This Module is developed to adhere to the requirements of ISO 14064-2: 2019 – Greenhouse Gasses – Part 2: Specification with guidance at the Project level for quantification, monitoring, and reporting of greenhouse gas emission reductions or removal enhancements.

The Module ensures:

Consistent, accurate procedures are used to measure and monitor forest carbon accumulation through standardized methodologies appropriate for commercial-scale implementation;
All net CO₂e removal claims are verified through robust field work and/or LiDAR-enhanced monitoring systems and third-party validation;
Forest management practices maintain ecological integrity through conservation measures;
Removals are additional through the use of dynamic assessments of the counterfactual that account for regional management practices and other guardrails set forth in the Isometric Standard;
Comprehensive leakage accounting through Global Timber Model implementation addresses both activity-shifting and market-mediated leakage with a minimum 10% deduction;
Comprehensive risk management through buffer pools and optional insurance mechanisms protects against potential reversals while ensuring transparent Credit delivery;
Economic viability for landowners through guaranteed revenue sharing and appropriate contract terms; and
Technology-enabled monitoring reduces transaction costs while maintaining high standards for carbon accounting and environmental integrity.

Throughout this Module, the use of "must" indicates a requirement, whereas "should" indicates a recommendation.

2.0

Sources and Reference Standards and Methodologies

This Module relies on and is intended to be compliant with the following standards and protocols:

The Isometric Standard
Improved Forest Management v1.0, Isometric
ISO 14064-2: 2019 - Greenhouse Gases - Part 2: Specification with guidance at the project level for quantification, monitoring, and reporting of greenhouse gas emission reductions or removal enhancements

Additional reference standards that inform the requirements and overall practices incorporated in this Module include:

ISO 14064-3: 2019 - Greenhouse Gases - Part 3: Specification with Guidance for the verification and validation of greenhouse gas statements
ISO 14040: 2006 - Environmental Management - Lifecycle Assessment - Principles & Framework
ISO 14044: 2006 - Environmental Management - Lifecycle Assessment - Requirements & Guidelines

Additional principles that were considered in the development of this Module and aligned with, where feasible, include:

The Core Carbon Principles of The Integrity Council for the Voluntary Carbon Market, v1.1, ICVCM, 2024
Criteria for High-Quality Carbon Dioxide Removal, Carbon Direct & Microsoft, 2025

3.0

Future Versions

This Module was developed based on the current state of the art, publicly available science regarding IFM activities and long-term monitoring of forest carbon projects. This Module aims to be scientifically stringent and robust. We recognize that some requirements may exceed the status quo in the market and that there are numerous opportunities to improve the rigor of this Module as new approaches and techniques enter the Voluntary Carbon Market.

Additionally, this Module will be reviewed when there is an update to published scientific literature, government policies, or legal requirements which would affect net CO₂e removal quantification or the monitoring guidelines outlined in this Module, or at a minimum of every 2 years.

4.0

Applicability

In addition to the requirements outlined in Section 4 of the Improved Forest Management Protocol, Projects are subject to the following applicability requirements, which must be demonstrated in the Project Design Document (PDD).

4.1

Viability of the Project and Determination of the Project Area

In order to maintain ecological integrity and ecosystem function, demonstrate additionality, and ensure trust and transparency, it is incumbent upon Projects to adhere to the requirements below, which must be demonstrated and reported in the Project Design Document.

4.1.1

Land Enrollment and Determination of the Project Area

To ensure accurate carbon sequestration claims and facilitate Validation and Verification, Projects registered under this Module must register a singular or grouped Site(s) — sets of parcels subject to similar bioclimatic, regulatory, and geographic conditions.

For grouping multiple Sites under one Project, all Sites must be within the same RESOLVE Biome and country.
Sites must consist of enrolled land parcels — discrete commercially-harvestable stands.
Contiguous parcels and/or parcels on the same harvest rotation within 10-kilometers of each other should be grouped into a single Site. Discontinuous parcels beyond 10-kilometers and/or those on different harvest rotations must be enrolled as separate Sites.
Each Site — and every constituent parcel — within a Project must independently meet all applicable eligibility criteria within this Module, which must be evidenced in the PDD.
Carbon quantification will be calculated at the Site level (see Section 9).

The Project Proponent(s) must adhere to the following additional requirements for parcel and Site enrollment:

All Sites must be greater than 10 hectares.
All parcels must have road or navigable waterway access.
- Exceptions to this rule apply under extenuating circumstances — such as the presence of an easement or prior commercial harvest history — and can only be claimed after consultation with Isometric, and must be justified in the Project Design Document.

4.1.1.1

Integrity of Enrolled Land

To ensure the credibility of the climate impact of project activities, non-additional areas of The Project must be excluded, as set out by various requirements in Section 4.1 of the Improved Forest Management Protocol and Section 4.1.2 of this Module.

It is vital to the integrity of The Project that no other areas within each parcel may be excluded from project activities. Project Proponents must enroll all eligible areas of a parcel. This requirement prevents the selective enrollment of areas that are less desirable for harvest. Land can only be excluded for reasons stated within this Module or the Improved Forest Management Protocol, and these excluded areas must be documented and mapped within the PDD in accordance with and to fulfill the cumulative impact assessment requirements of the IFM Protocol (see Section 4.1.2) — with sufficient justification of the legal, financial, or operational restrictions on harvest.

4.1.2

Ecological and Operational Feasibility of Harvest

Project activities must demonstrate additionality by accounting for Site-specific constraints that limit harvesting feasibility under baseline conditions. If ecological and Site conditions would render harvesting unlikely under baseline conditions, these areas within the Project Boundary cannot be claimed as additional and must be excluded from the Project Boundary. Soil saturation, permanent water bodies, slope gradients, and proximity to dwellings and other structures create natural and regulatory limitations on harvesting activities that must be evaluated when determining eligible project areas.

Project Proponents must identify and exclude from Crediting (see Section 4.1.1.1) any areas within the Project Boundary where economic, physical or regulatory constraints make harvesting highly unlikely under baseline management scenarios based on the guidance and requirements below.

4.1.2.1

Soil Drainage Limits

Historically, harvesting operations in waterlogged soils occurred primarily during periods of prolonged freezing temperatures, which provided ground stability for heavy timber equipment. Climate change has reduced the predictability and duration of these freezing periods, particularly in temperate and polar regions, making winter harvesting increasingly unreliable. Consequently, harvest avoidance in these soil types does not constitute additional management activity beyond what would occur under baseline conditions.

Project Proponents must identify and exclude from Crediting any areas within the Project Boundary with soils classified as "very poorly drained" or "inundated" according to the U.S. Soil Taxonomy classification system, or similarly classified soils in equivalent authoritative sources if a Project occurs outside of the United States of America.

Exceptions to this rule can be made if the Project Proponent demonstrates all requirements in Section 4.1.2.1.1.

4.1.2.1.1

Operability Exception

Project Proponents may include areas with soils classified as "very poorly drained" or "inundated" within the Project Boundary where evidence demonstrates that baseline harvesting operations remain economically viable despite soil drainage limitations.

Areas with waterlogged soils may be included when the Project Proponent demonstrates:

Baseline harvesting activities in the region commonly occur during predictable seasonal windows when soil conditions permit equipment access, as evidenced by regional timber market data, harvesting permits, or forestry operation records covering a minimum of the prior 10 years;
Specialized harvesting equipment or techniques (such as winter harvesting, low ground-pressure machinery, or helicopter logging) are established practice in the region for similar soil conditions, demonstrated through equipment rental availability, contractor specialization, or documented use in comparable forest stands; and
The proposed IFM activities constitute a measurable departure from baseline management that would otherwise occur despite drainage constraints.

To include these areas, The Project must also demonstrate additionality of these waterlogged soils through financial analysis showing that baseline harvesting remains economically feasible despite drainage-related operational constraints, and that the carbon revenue represents a necessary incentive for the proposed management changes.

4.1.2.2

Proximity to Water Bodies

Project Proponents must identify and exclude from the Project any areas within the Project Boundary that fall within management buffers around permanent water bodies as defined by applicable governmental regulations or voluntary Best Management Practices, i.e., BMPs (see Appendix B of the Improved Forest Management Protocol).

Project Proponents must provide documentation of applicable governmental regulations and BMPs governing management buffers around water bodies, along with mapping of permanent water bodies and associated buffer zones within the Project Boundary.

4.1.2.3

Geographical Constraints

Project Proponents must provide evidence of common harvesting practices and equipment availability within the relevant wood basket to demonstrate whether steep-slope operations are feasible under baseline management scenarios. Changes in carbon stocks in areas that are too steep to reasonably harvest would not be considered Additional.

Project Proponents must include a spatially-explicit topographic analysis of slope gradients within the Project Boundary.
Project Proponents must include a regional assessment of harvesting capabilities on steep terrain, collated from industry, government, or NGO reports and/or scientific literature.
Project Proponents must document the selection of the relevant wood basket.
- Project Proponents should ascertain the relevant wood basket by: (1) examining scientific literature; (2) evaluating governmental, regulatory, NGO, and industry databases; and/or (3) identifying the regional catchment of the timber product(s) of their harvests. In the absence of this information, Project Proponents should generate wood baskets as the Thiessen polygons of mills which intersect with the project boundary.
Project Proponents must exclude from crediting calculations areas with sustained slopes exceeding 30% over 30 meters in regions where specialized steep-slope harvesting equipment is not commonly deployed¹⁷.
- The U.S. Forest Service has found that harvest equipment encounters significant limitations on slopes of 25% to 35%, with severe constraints on slopes exceeding 35%¹⁸. Areas with sustained slopes above these thresholds represent natural barriers to conventional harvesting operations.

4.1.2.4

Proximity to Dwellings and Other Structures

Regulations or BMPs may prohibit harvesting within a certain proximity of built structures.

Project Proponents must exclude from crediting calculations any areas within 15 meters of permanent structures, or within larger buffers if required by applicable regulations or BMPs (see Appendix B of the Improved Forest Management Protocol).

Project Proponents must document any applicable governmental or BMP buffer requirements which would prohibit harvesting around dwellings and structures.
Project Proponents must include a spatially-explicit vector-based map of all permanent structures within and adjacent to the Project Boundary.

4.1.2.5

Merchantibility to Markets

Project Proponents must demonstrate that each Site contains sufficient merchantable stocking in a market where harvests would be economically viable in the baseline scenario. This merchantable stocking determination will establish which areas of The Project contain timber that would be economically attractive for harvest under common practice, thereby demonstrating the additionality achieved through placing the forest into protection.

Project Proponents must exclude all areas from the Project which do not meet the requirements in Sections 4.1.2.5.1 and 4.1.2.5.2.

4.1.2.5.1

Economic Viability Analysis

For each Site, the Project Proponent(s) must demonstrate economic viability through a Site-specific financial analysis accounting for all revenues and costs associated with timber harvest operations under baseline management scenarios.

Site-level financial analysis should include gross timber revenues calculated using: (a) stumpage values taken from regional market pricing and/or forest-type pricing from Isometric's implementation of the Global Timber Model (GTM); and (b) merchantable volumes by, if feasible, product class at the time of enrollment into The Project.
Project Proponents should include — to best approximation — cost enumeration taken from Isometric's implementation of the GTM (Section 8.2or developed from estimates of: (a) logging and processing; (b) access infrastructure; (c) transportation from the parcel to a processing facility; (d) equipment mobilization; (e) post-harvest obligations; (f) administrative and regulatory costs; and (g) property carrying costs during harvest operations.
Project Proponents must apply discount rates appropriate to landowner classification accordingly:
- Commercial Orientation (6%)
- Smallholder - Commercial Orientation (5%)
- Smallholder - Subsistence/Mixed Objectives (4.5%)
- Community Forest (4%)
- Indigenous Land(s) (3%) The selected rate will be assigned by Isometric upon parcel enrollment based on documented ownership characteristics, management objectives, and regional economic conditions — with higher rates indicative of greater commercial orientation.
For each Site, the Project Proponent must report the: (a) merchantable volumes, ideally by species and product class; (b) revenue calculations with price sources and dates and/or revenue estimates generated by Isometric's implementation of the GTM (Section 8.2); (c) complete cost enumeration with supporting data and/or cost estimates generated by Isometric's implementation of the GTM; (d) NPV or IRR worksheets showing discount rate application; and (e) sensitivity analysis demonstrating impacts of ±20% parameter variations on viability.
A Site shall be classified as economically viable for harvest in the baseline scenario if:
- The Net Present Value (NPV) is greater than zero at the applicable discount rate, or
- The Internal Rate of Return (IRR) is greater than or equal to the minimum acceptable rate for the ownership class and net stumpage value ≥ 0.
Sites which fail to meet one of these thresholds must be excluded from The Project.
Economic viability must be re-evaluated at re-enrollment of the Site(s). When triggered, the Project Proponent must update economic parameters, recalculate parcel viability, and adjust classifications as warranted. This re-evaluation is prospective, with changes affecting current and future baseline projections without retroactive adjustment to historical Credit issuance.

4.1.2.5.2

Market Capacity Assessment

In addition to Site-level economic analysis, Project Proponents must evaluate whether sufficient regional market capacity exists to absorb timber volumes from enrolled Sites under baseline harvest scenarios.

For each Site classified as economically viable, the Project Proponent must identify and/or confirm:
- All processing sites (e.g., sawmills, pulp mills, biomass facilities, and specialty processors) within economic hauling distance; and
- The road and/or waterway distance from the parcel to each facility, with maximum hauling distances established by regional standards.
For each Site classified as economically viable, the Project Proponent should identify and/or confirm:
- The current annual processing capacity by product type within the identified scope, using mill surveys, published reports, or direct facility operator communication; and
- That facilities accept the Site’s species composition and actively procure these species for timber products; or, for roundwood products,
- The economic viability and costs associated with roundwood export, the anticipated market for roundwood export, and the historic export pricing and transportation costs of roundwood.
The Project Proponent must assess whether aggregate baseline harvest volumes from all economically viable project Sites would exceed regional processing capacity by:
- Summing the projected annual harvest volumes across all project Sites within the applicable region; and
- Comparing aggregate volumes by product class to total facility capacity within economic hauling distance; or for roundwood,
- Summing the projected annual harvest volumes across all enrolled parcels within the applicable region; and
- Comparing aggregate roundwood volumes to average regional export levels.
Project Proponents must account for existing non-Project timber supply as part of this analysis.
Where appropriate, Project Proponents may consider temporal market dynamics to justify the additionality of the Project, such as:
- Historical timber price trends for species over the previous 5-10 years to ascertain any significant fluctuations;
- Processing facilities that have opened, closed, or changed capacity in the past five years and likelihood of similar changes during the Crediting Period; and
- Whether competing timber supply sources may affect market capacity or pricing.
Where significant market changes are documented or reasonably anticipated, the Project Proponent should adjust merchantability classifications or apply appropriate discount factors to baseline projections.
When market capacity is exceeded by The Project, Project Proponents must remove some Site(s) until the aggregate baseline harvest volumes from all economically viable project Sites is less than the regional processing capacity.
Market capacity determinations must be re-evaluated upon re-enrollment of the Site(s). During re-evaluation, the Project Proponent must update market capacity assessments, recalculate regional absorption capacity, and adjust Site merchantability classifications as warranted. This re-evaluation is prospective, with changes affecting current and future baseline projections without retroactive adjustment to historical Credit issuance.

4.2

Harvest Consistency

In order to prevent manipulation of the dynamic baseline and ensure additionality, it is incumbent upon Projects to demonstrate that harvest intensity by the Project Proponent and/or prior landowner did not increase above historical rates after consideration of enrollment into a carbon project (under Isometric or another Standard).

Projects must demonstrate for each Site that carbon stocks at the most recent harvest have not differed from historical averages.

For each Site, Projects must identify all known harvest events. Acceptable forms of evidence include:
- Commercial harvest records (e.g. Cut and Sold reports)
- Using remote sensing data indicative of historical disturbance history (e.g., Hansen Global Forest Change Product)
For each harvest event, Projects must provide an estimate of the total biomass removed. Acceptable forms of evidence include:
- Commercial harvest records (e.g. Cut and Sold reports)
- Forest growth curves calculated using peer-reviewed data and methods such as national or sub-national forest inventory plots, chronosequence sampling, and/or regionally-calibrated growth and yield models (e.g., FVS, ORGANON)
  - Project Proponents must provide the data and code used to generate the growth curve(s), along with justification for the selected approach (e.g. FVS, Chapman-Richards, etc.)

Any Sites where the total biomass removed during the most recent harvest event was greater than the historical average by more than one standard deviation are ineligible for inclusion in this Module.

Isometric reserves the right to audit submitted harvest data via earth observation remote sensing systems, and compare these results against the submitted harvest claims.

4.3

Intent to Protect

As the purpose of this Module is to transition commercially logged forests into mature forests which store carbon, it is vital that Projects ensure the sequestration of carbon through means of enforceable protection. The term “protection” constitutes different meanings across different countries and regulatory landscapes. For the purposes of this Module, the IUCN definition of a protected area is used:

“A clearly defined geographical space, recognised, dedicated and managed, through legal or other effective means, to achieve the long-term conservation of nature with associated ecosystem services and cultural values”.¹⁹

Projects must demonstrate an intent to protect the project area.

If formal agreements to place the project area into protection by the end of the Crediting Period are not in place at Validation, Project Proponents must describe in their PDD how they intend to protect the forest after Crediting. At each Verification without a formal agreement in place, Project Proponents must contribute an additional 5% to the buffer pool (see IFM Protocol Section 10).

Governance of protected areas may be private, governmental, and/or by indigenous peoples and local communities. Examples of what is considered an eligible protected area include but are not limited to:

Wildlife management areas
Forest reserves
Conservation easements
Community conservancies

To avoid potential conflicts of regulatory additionality, formal protection must not begin until the end of the Crediting Period (see IFM Protocol Section 7.7.2).

4.4

Other Requirements

In the transition from historical logging to forest protection, the planting of new trees cannot be the primary method to achieve forest cover. Project Proponents must limit new planting only to facilitate regeneration of healthier stands through planting of understory species²⁰, fill in gaps in existing patches of degraded forests, and/or to regenerate small areas — less than 1 hectare — of otherwise forested land.

The Project Proponent must disclose this planting, as well as the justification for it, within the PDD for initial Validation and follow all biodiversity requirements as set forth in the IFM Protocol (see IFM Protocol Section 6.4).
Any new planting after Validation must be reported to Isometric before the next verification event.

5.0

Project Timelines

5.1

Project Commitment Period

The timeline for Projects crediting under this Module is described by a Project Commitment Period. The Project Commitment Period encompasses two distinct periods, the Crediting Period plus a minimum 40-year Ongoing Monitoring Period which commences after the end of the Crediting Period.

For grouped Projects or Projects where there is a mixture of initial stand ages within the project area such that there is variation in the timing of individual Crediting Periods and Ongoing Monitoring Periods, the overall Project Commitment Period must reflect the collective start and end dates for all areas within The Project (i.e., the start of the first Crediting Period through the end of the last Ongoing Monitoring Period).

5.2

Crediting Period

The length of the Crediting Period under this Module must reflect the anticipated time to forest maturity within the project area. The underlying data and/or modeling for these estimates must be provided in the PDD and demonstrate that they are informed by harvesting history/stand age, forest growth factors, and tree biology within the project area.

For project areas where there is a mixture of initial stand ages (e.g., as a result of staggered harvesting history), this may result in distinct Crediting Period durations across the project area. In this scenario, the PDD must report how the project area will be divided into areas with distinct Crediting Periods and provide evidence for the length for each individual area.

The Project must then set the overall Crediting Period length for The Project to the maximum of these Site-specific Crediting Periods.

5.3

Reporting Period

The Crediting Period consists of subsequent Reporting Periods (see IFM Protocol Section 5.2). Under the IFM Protocol, the minimum length of a Reporting Period is 1 year and the maximum length is 5 years.

5.4

Ongoing Monitoring Period

The Ongoing Monitoring Period commences at the end of the Crediting Period. The Ongoing Monitoring period must be a minimum of 40 years and a maximum of 100 years. The durability of Credits are determined by the duration of the Ongoing Monitoring Period. Throughout the Ongoing Monitoring Period, Isometric will conduct monitoring for Reversals. If a Reversal is detected, the Project Proponent is responsible for conducting Reversal Reporting (see IFM Protocol Section 10.5.2). Reversals during the Ongoing Monitoring Period are compensated by the Buffer Pool (see IFM Protocol Section 10.4).

5.5

Example Project Timeline

A project has a Project Commitment Period of 100 years composed of a 40 year Crediting Period followed by 60 year Ongoing Monitoring Period. Credits issued have a 60+ year durability. Monitoring for quantification is conducted by the Project Proponent through the Crediting Period, and the reported activities are verified by a Validation and Verification Body (VVB) for each Reporting Period. At the end of the Crediting Period, maintenance of carbon stocks and monitoring for Reversals occurs for the remaining 60 years of the Project Commitment Period.

6.1

Forest Management Activities

Project Proponents must develop and report a forest management plan (FMP) for each Site.

The FMP(s) should be developed in consultation with an expert forester

Additionally, certain forest management activities must also be disclosed by the Project Proponent, such as Stand Improvement Activities, subject to the requirements set forth by Isometric in this Module, the IFM Protocol (Section 6.5), and the Isometric Standard.

6.1.1

Stand Improvement Activities

Project Proponents may engage in Isometric-approved stand-improving activities. These activities must be approved in consultation with Isometric to ensure that the volume of harvested wood does not exceed the volume of issued Credits.

The Project Proponent must disclose all planned stand-improvement activities in the Project Design Document prior to Validation and at each subsequent Verification, and must inform Isometric of any changes to these plans immediately and report these changes prior to the next Verification.

Only stand-improvement activities defined by the USDA NRCS guidance are permitted.
All stand-improvement activities must comply with applicable environmental and social safeguards set out in the IFM Protocol (seeIFM Protocol Section 6).

Credits will not be issued until the forest biomass within the Site recovers above the Site’s most recent pre-stand-improving-activity carbon stock baseline.

Project emissions associated with stand improvement activities must be reported according to the requirements in the IFM Protocol (see IFM Protocol Section 9.5).

6.1.2

Pre-Existing Forest Management Plan

Project Proponents must disclose all pre-existing forest management or traditional stewardship plans for any enrolled Site(s).

Plans which expire during the Crediting Period but after Validation fulfill this requirement.
For Indigenous landowners practicing traditional forest stewardship: Where principles of traditional land use are not documented in a formal plan, demonstration may include oral histories, cultural practices documentation, or traditional ecological knowledge (TEK) assessments that evidence ongoing forest engagement and resource use patterns informed by traditional practices.

These plans must specify likely or planned harvest(s), or traditional forest stewardship activity, during the Crediting Period.

6.2

Safeguarding of Communities

6.2.1

Stakeholder Engagement

Given the inherent economic nature of forest management activities, the impacts of The Project extend beyond landowner(s) to local economies. Giving these stakeholders early notice of planned changes in timber harvest enables market adaptation and prevents job losses in any local timber-based economy.

In addition to stakeholder engagement requirements specified in the IFM Protocol (see IFM Protocol Section 6.6.1) the Project Proponent must notify local authorities and loggers, mills, or other parties with existing formal or informal offtake agreements of the contracted change in harvest volume and/or schedule of timber upon enrollment into The Project.

Project Proponents should also provide similar information to any and all requesting entities/individuals — e.g., municipal authorities, research groups, or reporters.

6.2.2

Community Impacts and Well-Being

Given the relationship between forests and local communities, it can be anticipated that some logging activities provide direct benefits or subsidies to local communities. For the purposes of this Module, any local communities who had received direct benefits or subsidies from logging activity are defined as community beneficiaries.

Project Proponents must disclose in the PDD any historical disbursement of direct benefits or subsidies to local communities from the timber operations now ceased by The Project.
- Project Proponents must report disbursements for each identified community beneficiary.

In addition to the requirements set forth in the IFM Protocol (see IFM Protocol Section 6.6.2), the Project Proponent must disburse to community beneficiaries revenues generated from Credits issued to The Project, which match or exceed historical direct benefits or subsidies. Eligible forms of revenue sharing include:

Direct payments
Equipment and/or infrastructure

Projects with community beneficiaries must provide details of the systems which will be used for the disbursement of revenue and how the disbursement will be tracked (e.g., digital payment records, other documentation in absence of formal financial systems).

These systems must include a mechanism for community beneficiaries to report any grievances or disputes related to revenue sharing, and for the tracking of the response and resolution of these issues.
Any non-monetary, in-kind compensation must involve a transfer of ownership to community beneficiaries.

Revenue sharing percentages should also be made public, including percent revenue or Credits divided among each party (e.g., Project Proponent, community beneficiaries, insurance provider(s), and other documented parties listed in the PDD).

Project Proponents must provide an anticipated timeline of revenue sharing disbursement over the duration of each contract.

At every Verification, Project Proponents must provide evidence demonstrating progress against this plan, including proof of revenue disbursement, and report any grievances raised by community beneficiaries, and the subsequent responses and resolution by the Project Proponents.
- Projects which fail to report or provide sufficient evidence may be required to undergo an audit by an independent certified financial auditor.
- If at any Verification the cumulative revenue disbursement has fallen >20% below the original projected level for that timepoint, the Project Proponent must submit an updated revenue disbursement plan and timeline to demonstrate how The Project will meet the revenue sharing requirement of this Module.
  - This new plan will be used for benchmarking at any future Verification(s).

7.0

Relation to Isometric Standard

7.1

Additionality

In addition to the eligibility and applicability requirements set out in Section 4, Projects must meet the following requirements to ensure all claimed environmental impacts demonstrate the four pillars of additionality described in the Isometric Standard (Section 2.5.3).

7.1.1

Intent of Harvest

In order to ensure additionality, Projects must demonstrate a pre-existing intent to harvest trees within the Project Boundary and prove a demonstrable history of commercial harvesting and/or traditional forest stewardship within enrolled Site(s). These requirements must be robustly evidenced by data of the following types:

A written attestation that the Project Proponent or previous landowner(s) intended to harvest, would accept harvest offers, and/or conduct traditional stewardship activities during the Crediting Period.
If applicable, this attestation must include reference to the pre-existing forest management plans disclosed in Section 6.1.2.
Historical satellite imagery that clearly shows evidence of commercial harvesting and/or indicators of traditional forest stewardship activities during the Project Proponent’s and/or previous landowner’s tenure.
- For traditional forest stewardship, indicators include, but are not limited to, patterns of selection harvesting for cultural or subsistence purposes, traditional fire management practices, or other sustainable use consistent with established Indigenous land management practices.
This evidence should prioritize high-resolution historical imagery with clear sourcing information and acquisition dates. Preferred sources include: the USDA’s NAIP, the USGS's NHAP programs, and/or private data providers (e.g., Planet).
- In cases where high-resolution imagery is unavailable, Sentinel-2 or Landsat imagery may be used as an alternative, which must be accompanied by spectral analysis showing patterns consistent with harvest activities and a detailed explanation for why high-resolution imagery could not be obtained.

8.0

System Boundary, Project Baseline and Leakage

The carbon pool within the scope of this Module is aboveground woody biomass, as this is the main additional carbon pool affected by converting logged areas to protected areas. Soil carbon is also conservatively excluded CO₂e_Stored,RP. Belowground biomass is also excluded as a conservative measure since evidence indicates that the removal of carbon through the growth of new belowground biomass does not exceed the degradation of pre-logged belowground biomass²¹^,²². For the remainder of the Module, the use of AGB refers to only the living aboveground woody biomass, unless otherwise noted.

8.1

Leakage

This Module requires Projects to account for leakage through the Global Timber Model (GTM), which captures both direct landowner behavioral responses (activity-shifting) and broader market-mediated effects (market leakage) within a unified economic modeling approach. This integration reflects the reality that in improved forest management, activity-shifting behaviors are often driven by the same market signals and economic incentives that drive broader market leakage in response to timber supply restrictions. In this Module, leakage is calculated for distinct species groups for each regional wood basket, which vary by geographic location and forest composition.

Projects may elect to apply an alternative leakage deduction to calculate CO₂e_Leakage,RP provided that the Project Proponent meets all requirements in Section 8.3.

8.1.1

Scientific Justification for a Unified Modeling Framework

Recent scientific literature has highlighted significant challenges in accurately quantifying leakage from forest carbon projects. Studies by Badgley et al. (2021)²³, Haya et al. (2023)²⁴, and others have found systematic over-crediting in forest carbon offset programs, largely due to inadequate accounting for leakage impacts²⁵. This research indicates that traditional approaches to leakage assessment for forest carbon offset programs often underestimate both the magnitude and geographic scope of displacement effects.

The complexity of global timber markets means that reduced harvest in one location can trigger responses across multiple regions and through various economic pathways. Market-mediated leakage can occur through price signals that incentivize increased harvesting in distant locations, while activity-shifting often occurs through landowner responses that extend to other land owned by the Project Proponent or enrolled landowners, but not included in The Project.

This methodology adopts a modeling approach with a minimum 10% leakage deduction, using the Global Timber Model (GTM) to prevent well-documented over-crediting that has resulted from other improved forest management methodologies.

8.1.2

Prohibition on Shifting Activities

The Project Proponent or previous landowner(s) who own or manage forested land outside of the enrolled Site(s) of The Project are prohibited from altering forest management on these lands outside of regular harvests and stand improvement activities such as pre-commercial thinnings. The Project Proponent must provide an attestation that they will not alter forest management on this land outside of the enrolled Site(s) as a result of project activities.

The Project Proponent or previously enrolled landowner(s) should provide documentation of their annual harvest volume(s) for all non-enrolled lands for every year that The Project issues Credits to Isometric prior to each Verification.
Isometric reserves the right to audit future harvests on non-enrolled land(s), including via earth observation remote sensing systems, and compare these harvests against the submitted attestation.

8.2

Global Timber Model Implementation

The Global Timber Model (GTM) was conceptualized by Sohngen et al. (1999)²⁶, and it seeks to re-balance supply and demand in response to market shocks over decadal time periods for forest-type regions.

The GTM has been adopted for carbon projects through an update led by the University of Maine, in collaboration with The Nature Conservancy and the Global Forest Lab at The Ohio State University, as discussed in Daigneault et al. (2025)²⁷. This updated GTM estimates how forest carbon projects in aggregate change trade balances regionally and globally, as a result of both direct and indirect leakage.

Isometric will quantify the leakage deduction for each Reporting Period for Projects based on global runs of leakage rates (Equation 1) for the forest-type using the Global Timber Model (GTM), annualized and weighted by The Project’s basal area. As changes to timber harvest through project activities directly and indirectly impact the balance of supply and demand for decades, and the GTM initiates this predicted response within the same decadal time period as the start of the Crediting Period, the leakage deduction schedule for the percent deduction of a Reporting Period, L_project,RP, will be set at project initiation, and updated as needed by Isometric with the inclusion of any new site(s).

Further information on how Isometric implements the GTM and determines leakage is set forth in Appendix D, which contains additional information on the technical requirements of model implementation and the data sources used for modeling.

8.2.1

Regional Leakage Rate Calculation

The average leakage rate, $LR$ , for each forest type-region (see Appendix D3) in 10-year time periods is calculated as:

 $LR_{f,r,t} = \rho \left[ \frac{(PCS_{Project,f,r,t} - PCS_{Counterfactual,f,r,t}) - (GCS_{Project,f,r,t} - GCS_{Counterfactual,f,r,t})}{(PCS_{Project,f,r,t} - PCS_{Counterfactual,f,r,t})} \right]$

(Equation 1)

Where:

$LR_{f,r,t}$ is the average leakage rate per given decade in a forest type-region
$PCS$ indicates the carbon stock within the Project Boundaries, in tonnes of C
$GCS$ indicates global forest carbon stock, in tonnes of C
$f$ is the forest type
$r$ is the region
$t$ is the time period (in decades)
$⍴$ is the discount rate, set at 5%

8.2.2

Project Leakage Calculation

The Project’s leakage for each Reporting Period, CO₂e_Leakage,RP is then calculated using the following equation:

 $L_{Project,t} = \frac{\sum B_{f,r,t} * LR_{f,r,t}}{B_{Project,t}}$

(Equation 2)

Where:

$L_{Project,t}$ is the project leakage for a given decade
$LR_{f,r,t}$ is the average leakage rate per given decade in a forest type-region
$B_{f,r,t}$ is the basal area in each forest type-region in the project area
$B_{Project,t}$ is the basal area in the project area
$f$ is the forest type
$r$ is the region
$t$ is the time period (in decades)

And, $B_{Project,t}$ must equal $B_{f,r,t}$

As the GTM outputs leakage estimates on decadal timesteps, Isometric will then annualize the project leakage, applying a linear interpolation between decadal estimates to derive the leakage deduction for each year within a decade:

 $L_{Project,RP} = L_{Project,0} + \frac{t}{10} \left( L_{10} - L_0 \right)$

(Equation 3)

Where:

$L_{Project,RP}$ is the project leakage rate for a given Reporting Period, RP
$L_{Project,0}$ is the project leakage rate for the first year within a decadal time-step
$L_0$ is the project leakage rate for the first year within a decadal time-step
$L_{10}$ is the project leakage rate for the last year within a decadal time-step
$t$ is the year into the decadal time step for the Reporting Period, $RP$

The final leakage deduction for each Reporting Period, CO₂e_Leakage,RP can then be calculated as a percentage of the sequestered carbon in a Reporting Period, CO₂e_Stored,RP (see Section 9.1).

 $CO_2e_{Leakage,RP} = L_{Project,RP} * CO_2e_{Stored,RP}$

(Equation 4)

If the leakage rate, $L_{Project,RP}$ , is <10%, the minimum annual leakage deduction of 10% will be applied by Isometric. When positive leakage is predicted by a negative leakage rate ( $L_{Project,RP}$ < 0%), it will be subject to the minimum annual leakage deduction of 10%. Positive leakage indicates a model which predicts that restricting supply in the region could increase timber prices, and incentivize more considered forest management or land to be converted to forest.

8.3

Alternative Leakage Deduction

Projects may elect to apply an alternative leakage deduction to calculate CO₂e_Leakage,RP provided that the Project Proponent demonstrates all of the following:

The alternative CO₂e_Leakage,RP is more conservative than the GTM output in Section 8.2;
The alternative approach is a supply-chain-specific analysis that quantifies leakage based on the actual wood products, supply chains, and substitution dynamics relevant to the project concession, as described in Section 8.3.1; and
All activity-shifting monitoring and attestation requirements in Section 8.1.2 are independently satisfied, regardless of whether the alternative approach is applied.

8.3.1

Alternative Supply-Chain Leakage Assessment

Where a Project Proponent elects to apply an alternative leakage deduction, the assessment must meet all of the following requirements. The alternative approach does not replace the GTM calculation in Section 8.2, which must still be calculated and reported for each Reporting Period. The alternative deduction may only be applied where it yields a higher (more conservative) leakage deduction than the GTM output.

8.3.1.1

Conservative Leakage Assumptions

Project Proponents must develop and report in the PDD, for approval by Isometric and the VVB, an alternative approach assessment that demonstrates the following:

The assessment must assume that 100% of the volume of wood products that would have been produced under the baseline scenario is displaced to international or domestic markets.
- No reduction in demand or market absorption may be assumed.
The assessment must identify the most probable supply of substitute wood product based on documented trade flows, regional supply chains, and species-specific product markets relevant to The Project’s historical output.
The assessment must compare the carbon intensity — expressed as carbon stock per unit volume of wood product — between The Project’s merchantable species and operations, and those of the identified substitute supply.
Where the substitute supply sources have lower carbon stock per unit volume than The Project, the leakage deduction must reflect the full substitution volume adjusted by the ratio of substitute to Project carbon intensity.
- Where substitute sources have equal or higher carbon stock per unit volume, no reduction from the 100% displacement assumption is permitted.

8.3.1.2

Data Requirements

The Project Proponent must provide the following for each Reporting Period in which the alternative deduction is applied:

Concession-specific data on the species composition, wood density, and carbon content of the harvested wood products produced under baseline operations;
Identification of the most probable substitute supply, supported by at least two of the following: (a) trade flow data or export/import records; (b) documented procurement relationships or offtake agreements; (c) published market analyses of the relevant wood product sector; or (d) industry or government reports on regional supply dynamics;
Published or peer-reviewed data on the wood density and carbon content of the substitute species, with preference for region-specific values over global defaults; and
A transparent model and calculation showing the derivation of the alternative leakage deduction from the above inputs.
- All modeling must meet requirements in Section 9.5

8.3.1.3

Application Eligibility

The alternative leakage deduction applied for each Reporting Period must be the higher of:

The leakage rate derived from the supply-chain assessment in this Section; or
The leakage rate derived from the GTM implementation in Section 8.2.

If the supply-chain assessment yields a lower leakage deduction than the GTM for any Reporting Period, the GTM-derived deduction must be applied for that Reporting Period.

The minimum annual leakage deduction of 10% specified in Section 8.2 applies regardless of the method used.

8.3.1.4

Updates to Alternative Leakage Deduction

The supply-chain assessment must be updated and resubmitted at each Verification. Updated assessments must incorporate any material changes to substitute supply markets, trade flows, or carbon intensity data that have occurred since the prior assessment. Where region-specific data for substitute species become available that were not available at the prior assessment, these must be incorporated.

Isometric reserves the right to require the Project Proponent to revert to the GTM-derived leakage deduction if the supply-chain assessment is found to rely on incomplete, outdated, or insufficiently conservative data.

8.3.1.5

Activity-Shifting Requirements

Project Proponents applying an alternative leakage deduction must satisfy all attestation, documentation, and monitoring requirements for activity-shifting leakage in Section 8.1.2.

9.0

Quantification

Under this Module, the difference in storage between the project scenario and the counterfactual scenario are assessed cumulatively over the course of The Project. For a given Reporting Period, the incremental change is assessed by via the difference between the total additional carbon storage at the end of the current Reporting Period and the same value at the end of the prior Reporting Period. As such, change in the net difference between the project and counterfactual storage over a Reporting Period is calculated as a net storage term (CO₂e_{net, storage,RP}):

 $CO_2e_{net,storage,RP} = CO_2e_{stored,RP} - CO_2e_{counterfactual,RP} = (CO_2e_{stored,total} - CO_2e_{counterfactual,total}) - CO_2e_{net,storage,RP-1}$

(Equation 5)

Where:

$CO_2e_{stored,total}$ is the total CO₂ removed from the atmosphere and stored as carbon in living trees at the end of the current Reporting Period, in tonnes of CO₂e
$CO_2e_{counterfactual,total}$ is the total CO₂ removed from the atmosphere and stored as carbon in the counterfactual scenario at the end of the current Reporting Period, in tonnes of CO₂e
$CO_2e_{net,storage,RP-1}$ is the net storage term for the prior Reporting Period, in tonnes of CO₂e; If this is the first Reporting Period this term is set to 0

This net storage for the Reporting Period can then be used for the difference between $CO_2e_{stored,RP}$ and $CO_2e_{counterfactual,RP}$ for the calculation of net removals using Equation 1 in the IFM Protocol.

9.1

Calculation of CO|2|e|stored

Calculation of CO₂e_stored

Under this Module, the primary storage pool is aboveground woody biomass. In formerly logged areas, evidence indicates that the removal of carbon through the growth of new belowground biomass (BGB) does not exceed the degradation of pre-logged belowground biomass²⁸^,²⁹. This indicates that there is limited net removal of carbon through belowground biomass and, as a conservative measure, Projects must set CO₂e_BGB to 0.

With this, the stored carbon in the project area at time t can be described by the following equation:

 $CO_2e_{stored}(t)=CO_2e_{AGB}(t)$

(Equation 6)

Where:

$CO_2e_{stored}$ is the total CO₂ removed from the atmosphere and stored as carbon in living trees at time $t$ , in tonnes of CO₂e
$CO_2e_{AGB}$ is the total carbon stored in living aboveground woody biomass (AGB) at time $t$ , in tonnes of CO₂e

The total carbon stored in The Project up to the end of the current Reporting Period can be calculated as:

 $CO_2e_{stored,total} = CO_2e_{stored,t=RP} - CO_2e_{stored,t=0}$

(Equation 7)

Where:

$CO_2e_{stored,t=RP}$ and $CO_2e_{stored,t=0}$ are the total CO₂ removed from the atmosphere and stored as carbon in living trees at the end of the current Reporting Period and project initiation, respectively, in tonnes of CO₂e

9.2

Calculation of M|AGB

Calculation of M_AGB

Isometric encourages Project Proponents to quantify the total above-ground biomass, M_AGB, in the project area through one of the Capture & Conversion Modules listed in the IFM Protocol (see IFM Protocol Section 9.3.3).

If either LiDAR or Earth Observation methods are selected, benchmarking these methods with field plots must occur, at minimum, every ten years following the procedures within the corresponding Module. This benchmarking may use field data from national or sub-national forest inventory plots, as long as it can be demonstrated that these plots are representative of the project area in species composition and range of biomass density, and the data are otherwise adherent to the requirements for the benchmarking procedure.

Alternatively, subject to meeting all the requirements set forth in Section 9.2.1, Projects may elect to quantify M_AGB through an alternative growth-disturbance model. Projects electing to use a growth-disturbance model must obtain approval from Isometric at Validation based on a comprehensive evaluation of the methodology in accordance with the requirements in Sections 9.2.1.1 and 9.5.

9.2.1

Calculation of M|AGB| Through Growth-Disturbance Models

Calculation of M_AGB Through Growth-Disturbance Models

The total aboveground woody biomass at time t, M_AGB(t), can be derived via modeling of the change in biomass due to growth and disturbance (loss) since the most recent direct measurement of biomass within the project area (Figure 1). The model must be developed using national or sub-national forest inventory (NFI), or other publicly-available inventory (e.g., research, industry) plot data from the region, which may be derived from field plot measurements, LiDAR measurements, or some combination thereof. Hereafter these will be collectively referred to as NFI data for simplicity, but eligible datasets are broader as noted.

Figure 1. Visualization of growth-disturbance model for no-disturbance (left) and disturbance (right) scenarios. In the disturbance scenario, the biomass credited (green) is derived by imputing the loss from a disturbance event (grey) from the measured biomass.

To apply the model across the project area, the project area should be subdivided in a manner that corresponds to the NFI dataset which is being used for model development. For example, if rasterized NFI data are being used, the project area should be divided into pixels of equivalent or greater (up to 100%) size. If NFI field plots are being used, sampled field plots of equivalent size should be used within the project area as the basis for assessment.

Under this approach, The Project’s total aboveground woody biomass, M_AGB, at the current time point, t, can be calculated as:

 $M_{AGB,i}(t) = M_{AGB,i}(t_m) + \int_{t_m}^{t} G_i \, dt + \int_{t_m}^{t} D_i \, dt$

(Equation 8)

Where:

$M_{AGB,i}(t)$ is the total aboveground woody biomass at timepoint $t$ in project area sub-unit $i$ (e.g., pixel or plot), removed from the atmosphere and stored as carbon in living tree trees, in tonnes of C.
$M_{AGB,i}(t_m)$ is the carbon stock of sub-unit $i$ at year $t_m$ , where $t_m$ is the time of the most recent assessment of pixel-level carbon using field surveys or LiDAR (see Section 9.2.1.4)
$t$ is the current year
$G_i$ is the rate of carbon accumulation in sub-unit $i$ , derived from the modeling approach, in tonnes C yr^-1
$D_i$ is the rate of carbon loss associated with disturbance in sub-unit $i$ , derived from the modeling approach, in tonnes C yr^-1

To determine the project-level aboveground biomass, the mean across the project area sub-units should be used:

 $M_{AGB}(t) = \frac{\sum_{i=1}^{n} M_{AGB,i}(t)}{n}$

(Equation 9)

Where:

$M_{AGB}(t)$ is the project-level mean total aboveground woody biomass at timepoint $t$ in tonnes of C
$n$ is the total number of project area sub-units (e.g., pixels or plots) over which the model was applied.

To apply the growth-disturbance model described in Equation 8, Projects must meet all of the applicability requirements in Sections 9.2.1.2 and 9.2.1.3 for the respective model components.

9.2.1.1

Growth-Disturbance Model Approval

Project Proponents must demonstrate that the growth-disturbance model development and performance meets the following requirements:

Model performance must be assessed using out-of-sample data not involved in model training (e.g., using the model to predict biomass in NFI plots withheld from model development, and comparing modeled biomass to actual measured biomass in these plots).
The validation dataset must cover a range of biomass values that encompasses those within the project area, be from the same ecoregion, be at least 30% the size of the project area dataset, and include a disturbance magnitude.frequency which is relevant for the project area.
Based on assessment against the validation dataset, the model must achieve a minimum R² of 0.6.
The characterized model uncertainty impacts on overall Removal estimates must be propagated in accordance with the Isometric Standard (see Section 2.5.7).

9.2.1.2

Growth Model

Growth in the project area can be assessed through the development of models which estimate growth based on observed growth measured in NFI data for similar areas.

Project Proponents must meet all of the following requirements for the development and application of such growth model(s):

The model(s) must be developed using NFI plots with repeat measurements spanning at most 10 years;
Sub-area i must be matched to the three most similar NFI plots using k-nearest neighbors and compared to the average growth rate of these matched plots; and,
Current sub-area growth in i must be matched to a historical NFI or publicly available inventory plot, with plot re-measurement occurring over a period of time equal to or greater than the number of imputation years.

If using NFI data with spatially disjoint sub-plots, Project Proponents should aggregate these sub-plots according to the guidance and design of the NFI dataset.

Absolute change is then imputed on an annual basis for each sub-area plot based on the matches, and those annualized growth estimates are added to the latest direct measurement-derived estimate of the pixel (Equation 8).

9.2.1.3

Disturbance Model

Disturbance models may be used to estimate forest carbon loss stocks since the last field survey or LiDAR acquisition. Disturbance models both detect the occurrence of a loss within the project area, and estimate the carbon stock changes associated with the loss. The loss model is developed based on relevant observations of post-disturbance biomass change from NFI data or other publicly available datasets.

Project Proponents must meet all of the following requirements for model development and performance to use any disturbance model(s):

The model(s) must directly forecast absolute or relative decreases in carbon stock following a disturbance;
The model(s) must be parameterized with NFI data or repeat LiDAR acquisitions which capture a sufficiently large sample of disturbance events;
The model(s) must have a minimum recall of 0.85 for detecting disturbances within the harvested class; and
The model(s) must be able to detect partial harvests equivalent to ≤ 30% removal of carbon stocks.

Project Proponents are encouraged to leverage commercial high-resolution imagery, spaceborne multi-spectral imagery (e.g., Sentinel-2), and/or synthetic-aperture radar (SAR - e.g., ALOS or NISAR) in the development of their disturbance model(s).

In the event of a disturbance, the corresponding carbon stock must then be subtracted from the sub-unit biomass and sub-unit plot matches must be remapped for subsequent years (Equation 8).

9.2.1.4

Carbon Stock Acquisition

At the start of the Crediting Period, and at a minimum frequency of every 10 years thereafter throughout the Crediting Period, the Project Proponent will collect field-based or LiDAR-derived estimates of carbon stock across the project area to establish M_AGB,i(t_m). Further, if the modelled losses over the entire project area are greater than 60% of the modeled growth over the entire project area for a given Reporting Period, direct measurements must be made for that Reporting Period. Project Proponents must quantify this carbon stock through one of the following two approved Capture & Conversion Modules:

This Module details durability and monitoring requirements for area-based quantification of aboveground biomass.

This Module details durability and monitoring requirements for LiDAR based quantification of aboveground biomass.

9.3

Calculation of Baseline, CO|2|e|counterfactual

Calculation of Baseline, CO₂e_{counterfactual}

The following section outlines the workflow that Isometric will take for the calculation of CO₂e_{counterfactual,RP} via a dynamic baseline approach; the Project Proponent is not responsible for carrying out the steps in this section. Project Proponents may suggest areas that could constitute suitable control pixels or features for matching based on their expert knowledge of their unique system. However, the ultimate determination of control pixels will be done by Isometric following the procedure and criteria below.

9.3.1

Determination of Zone of Eligibility for Control Pixels

At Validation, the control plot zone must meet the following eligibility criteria:

Located in the same country and ecoregion as the project area;
Does not lie within protected areas, or within other carbon projects;
Be subject to commercial harvesting activities;
Be subject to the same relevant regulations, government incentives, and programs as the project area; and
Biomass, e.g., carbon stock values and productivity values must be within 10% of those of the project plots.

Where possible, other features should also be matched between the control plot zone and project area to the best extent possible following the matching procedure in Section 9.3.3. Examples, and potential data sources, are presented in Table 1.

Table 1. Potential variables and data sources for informing the matching procedure between project and control areas.

Category	Variable	Potential Datasets
Forest Structure	Carbon Proxy	LiDAR-derived biomass estimates; Forest inventory carbon models; Remote sensing carbon proxies (see Section 9.3.2)
	Stem Density	LiDAR point cloud analysis; Forest inventory plot data; Airborne laser scanning metrics
	Species composition	Forest type classification maps; Vegetation surveys; Hyperspectral imagery analysis
	Years since last disturbance/harvest	Forest management records; Disturbance history databases; Landsat time series analysis
	Historical harvest cycles	Forest management records; Disturbance history databases; Landsat time series analysis
Environmental	Elevation (≤30m resolution)	SRTM 30m DEM; ASTER Global DEM; National elevation datasets
	Slope (≤30m resolution)	DEM-derived slope calculations; USGS National Elevation Dataset; Terrain analysis products
	Bioclimatic variables (e.g., temperature, precipitation)	WorldClim data; Regional climate records
	Site Productivity	USGS SSURGO soil classification; Forest site index databases; Soil productivity indices
Socioeconomic	Land value estimates	Nolte, 2020³⁰; Property tax assessments; Real estate valuation models
	Distance to timber mills	Forest industry facility databases; Mill location registries; Economic facility datasets
	Distance from roads and/or navigable waterways	OpenStreetMap road networks; National transportation databases; Road density maps
	Distance from urban development	Urban boundary datasets; Land use/land cover maps; Census urbanized area files
	Geographic distance	Coordinate-based distance calculations; Spatial proximity analysis; GIS distance tools
	Parcel size	Cadastral boundary datasets; Property parcel databases; Land registry records
	State/Province Boundaries	World Administrative Boundaries

Initially, the zone for eligible control plots should be limited to the same state or province, or a 100 km band around the project area — whichever is smaller. However, if suitable matches (see Section 9.3.3) are not found in this zone, additional step-outs in 10 km increments may occur to find appropriate control plots, assuming they meet the criteria above. The final area determined for suitable control plots is hereafter referred to as the Donor Zone.

If after, including geographic expansion of the boundary up, the Donor Zone is less than ten times the size of the project area, the donor pool may be further expanded by using the Time for Space Substitution procedure described in Section 9.3.1.1.

9.3.1.1

Time for Space Substitution

In some scenarios, constraining the zone for eligible control pixels based on the criteria above may severely limit the size of the Donor Zone. Although further control pixels can be selected by expanding the potential Donor Zone area in 10-kilometer increments, doing so may only marginally increase the area of the Donor Zone or improve the performance benchmark accuracy.

Environmental criteria such as bioclimatic variables, productivity, and biogeography used for control pixel matching tend to exhibit spatial autocorrelation — especially in areas of high topographic relief. Therefore, control pixels selected even short distances from the project area can have fundamentally different ecological conditions that can lead to biased control pixel selection and forest carbon stocks and/or proxies. Land use history can similarly constrain the Donor Zone. To ensure accurate matching, the Donor Zone should account for legacy effects—such as prior management regimes, levels of degradation, and priority effects—that influence long-term carbon storage capacity. However, controlling for land use history does further limit eligible Donor Zone pixels due to the asynchronous timing of land-use changes across the landscape. In any given year, areas with similar land use may vary in the time elapsed since active management (e.g., harvesting, cultivation, grazing, or disturbance), potentially biasing control pixel selection and forest carbon stocks and/or proxies.

One consequence of a small Donor Zone is small control pixel sample sizes, which can reduce performance benchmark accuracy through sampling bias. If the eligible Donor Zone after masking for the initial set of variables (see Section 9.3.1) is less than five times the size of the project area, Isometric may temporally expand the pool of potential control pixels using a time-for-space substitution (TFSS) sampling strategy. TFSS relaxes the requirement to match the Donor Zone and project area from identical calendar years, thereby expanding the n-dimensional area available for valid control pixel selection. Instead of aligning control pixel and project forest carbon stocks and/or proxies by the same calendar year, TFSS compares changes in forest carbon stocks and/or proxies relative to the time elapsed since pre-project conditions, enabling more robust estimates of additionality.

In this approach, historical data for control pixels can be matched to current data for the Project. The same criteria as listed above must apply across the time points (i.e., current regulations which apply to the Project must have also been applicable at the historical time point for the control pixel). If TFSS is required based on the initial Donor Zone size, Isometric will include the justification for the approach as well as the specific methodological approach and data included in the TFSS in its documentation of the baseline procedure.

When the TFSS is used, the temporal range considered for eligible control pixels will be expanded in 5-year increments, up to 15 years maximum. In addition to the features and criteria above, eligibility for the use of time substituted control pixels also includes:

Historical data must be collected using the same methodology and be of equivalent quality and resolution as current data, ensuring consistent data fidelity across all years included;
Datasets must be temporally harmonized to ensure that observed trends reflect actual changes in vegetation dynamics rather than inconsistencies in data sources or collection methods;
Climate conditions must be similar between historical and current time windows; and,
There must be no meaningful differences in the occurrence of disturbance events.
- Sampling must avoid years with atypical socioeconomic or ecological conditions (e.g., government-mandated harvesting or severe droughts) within the TFSS temporal window that could introduce biased sampling or artificially inflate estimates of additionality by suppressing control pixel growth.

When temporal substitution is used for control pixels, their eligibility will be re-evaluated at each Reporting Period according to the guidance set out in Section 9.3.4.

9.3.2

Generation of Forest Carbon Map

Once the boundaries of the Donor Zone are determined, Isometric will generate high-resolution (≤30 m) pixel maps representing forest carbon stocks or a suitable proxy for forest carbon stocks. These layers must cover the entire project area and Donor Zone at the same resolution for at least five historical time points relative to the start of The Project. Each historical time point must be separated by at least 1 year.

Isometric will select a suitable proxy that meets the following criteria:

The proxy must be correlated with AGB throughout the Crediting Period.
If the proxy saturates in the project area or Donor Zone during the Crediting Period and becomes insensitive to further carbon gain (e.g., as is the case for many simple optical indices), it will be excluded³¹. Proxies such as canopy height from models which use datasets from multiple types of earth observation (particularly 2D satellite imagery, LiDAR and SAR) are preferred³².
The proxy map product should exclude cloud occlusion, saturation, and other contamination. This may lead to seasonal composite images.
The proxy should be insensitive to seasonal variability, which may be addressed through taking an annual average to remove the seasonal cycle.
The proxy should be stable, so that in the absence of carbon change, the proxy value stays the same.

9.3.3

Matching of Project and Control Pixels

Project and control plot pixels will be matched by Isometric at Validation, and these matches will be retained and tracked over the Crediting Period. In this procedure a representative random sample of project pixels are matched to control plot pixels based on a mix of current and historical time series of environmental, socioeconomic, management, and forest structure data — including the selected forest carbon proxy, C_proxy, of each pixel — using k-nearest neighbors without replacement, or an alternative justified algorithm.

This matching will use, at a minimum, five historical time points of C_proxy capturing at least the five years prior to project initiation. Isometric shall use, where possible and relevant, additional datasets from Table 1 for matching. Other than the historical time series of C_proxy, all dynamic remotely sensed variables must be captured within the past 18 months. Each selected project pixel must be matched to a minimum of 5 different control pixels, and the mean of each dataset over the group of control pixels is used — with the mean forest carbon proxy over the group of control pixels derived from the map product created using the procedure described in Section 9.3.2.

9.3.4

Evaluation of Dynamic Baseline Deduction

To evaluate the carbon stored in the counterfactual scenario, the change in the stocking index in the project pixels is compared to the change in the control pixels. Specifically, linear regressions are fit through both the project and control pixels proxy values, and the relative ratio is then used to calculate the counterfactual storage:

 $CO_2e_{Counterfactual,Total} = CO_2e_{Stored,total} \left( \frac{Control_{proxy,slope}}{Project_{proxy,slope}} \right)$

(Equation 10)

Where:

$CO_2e_{Counterfactual,Total}$ is the total counterfactual CO₂ removed from the atmosphere and stored in the absence of project activities over the course of The Project up to the end of the current Reporting Period, in tonnes of CO₂e
$Control_{proxy,slope}$ and $Project_{proxy,slope}$ are the slopes for the linear regressions fit through the proxy values for the control and slope pixels, respectively

To meet the additionality condition, the change in proxy value in the project area represented by the slope of the project pixels, must be statistically greater ( $p$ < 0.05, inclusive of uncertainty) than that of the matched control pixels. If the slope of the proxy change in the control pixels is negative such that the resulting product of Equation 10 is negative, the counterfactual carbon storage, $CO_2e_{counterfactual}$ , will be assumed to be 0 in order to ensure the accounting of carbon storage is limited to removals above the harvest counterfactual.

At each Verification, the control pixels are reviewed to determine continued eligibility around similar regulatory regimes within control plots as outlined in Section 9.3.1. In the event that control pixel matches are no longer suitable, replacements will be selected for the impacted project pixels. For example, a change in regulations around IFM projects which leads to variance in the legality of such projects between control and project pixels would lead to rematching of control and project pixels.

The counterfactual will be calculated using Equation 10 for each Reporting Period, unless:

Within a single Reporting Period, the mean proxy value of the controls decreases by 20% or more, which is indicative of harvest having occurred in the counterfactual; or
The slope of the control regression is $\leq$ 20% of the slope of the project regression for the prior five year period (excluding years prior to project initiation), which is indicative of harvesting keeping biomass levels far below what is being observed in the no-harvest project scenario.

If either of the above conditions is met in a given Reporting Period, the counterfactual is then calculated as the temporal mean for that Reporting Period and all remaining Reporting Periods in the Crediting Period:

 $C_{counterfactual,total} = C_{stored,total} \left( \frac{Control_{proxy,mean}}{Project_{proxy,RP}} \right) x \, f_{HWP}$

(Equation 11)

Where:

$Control_{proxy,mean}$ is the temporal mean of the control proxy
$Project_{proxy,RP}$ is the mean proxy value of the project pixels at the end of the current Reporting Period
$f_{HWP}$ is the counterfactual harvested wood storage factor

The counterfactual harvested wood storage factor reflects the relative ratio of the long-term mean of harvested wood carbon relative to the long-term mean of standing carbon in counterfactual. This term is calculated based on information about historical harvesting activities and wood products within the project area:

 $f_{HWP} = 1 + \frac{\sum_{i=1}^{n} \frac{f_i}{\lambda_i}}{T(\gamma - \beta)}$

(Equation 12)

Where:

$f_i$ is the fraction of pre-harvest biomass in pool i of n total pools for the fate of the harvested biomass [-]
$\lambda_i$ is the decay rate for pool i, in years^-1
$T$ is the harvest cycle length, in years
$\gamma$ is the harvest intensity [-]
$\beta$ is the normalized regrowth symmetry [-]

Further details on the calculation and required evidence for these terms are provided in Section 9.3.4.1 and the full derivation is in Appendix E. The calculation of $f_{HWP}$ must be included in the uncertainty assessment for the calculation of removals. As such, uncertainty information for the parameters must be reported, or evidence that the value is a conservative estimate provided. Project Proponents must provide their assessment and corresponding evidence for the calculation of $f_{HWP}$ at Validation.

9.3.4.1

Parameters for Counterfactual Wood Products Assessment

The fraction of biomass in different pools post-harvest ( $f_i$ ) is assessed by considering how the initial pre-harvest standing AGB volume gets divided into harvest residues, mill residues, and wood products.

First, a biomass expansion factor (BEF) is used to determine how the standing pre-harvest total AGB volume (K) is partitioned into between merchantable volume of biomass (MV) which goes to the mill and harvest residues (R_H):

 $K = MV + R_H = \frac{1}{BEF}K + (1 - \frac{1}{BEF})K$

(Equation 13)

Where available, species-specific biomass expansion factors should be used. If none is available, then default IPCC values for the region and system may be used³³.

The merchantable volume is then further partitioned as part of the milling process into the commercial volume (CV) of wood products and waste residues produced in the milling process. This partitioning is described by the efficiency of the processing of harvested wood products (W_HWP). The efficiency of the processing of harvested wood products is well documented, and the value of W_HWP must be assigned to each harvested wood product, HWP, according to the sawmill location, with the values derived from Winjum, et. al. 1998³⁴. For developed countries, this value is 0.19; for developing countries, this value is 0.24.

 $MV = CV + R_H = (1-W_{HWP})MV + W_{HWP}MV$

(Equation 14)

Note that the above expression represents a single type of wood product and associated wastes, but the merchantable volume may be partitioned into multiple milling processes and wood products as applicable.

The above equations can then be combined and normalized by $K$ to express the fractional pools:

 $1 = f_{RH} + f_{RM} + f_{CV} = (1 - \frac{1}{BEF}) + \frac{W_{HWP}}{BEF} + \frac{1- W_{HWP}}{BEF}$

(Equation 15)

Where:

$f_{RH}$ is the harvest residue fraction, equivalent to the first term on the right-hand side of the equation
$f_{RM}$ is the milling residue fraction, equivalent to the middle term on the right-hand side of the equation
$f_{CV}$ is the commercial volume fraction that goes into wood products, equivalent to the final term on the right-hand side of the equation

The decay rate ( $\lambda_i$ ) is derived from the half-life of the pool:

 $\lambda_i= \frac{ln(2)}{t_{1/2,i}}$

(Equation 16)

Where:

$t_{1/2,i}$ is the half life of pool i, in years

The half-life values applied for harvested wood products must be specific to the product type, end use, and regional practices associated with The Project and harvested wood product. Residue pools (e.g., harvest residues and milling residues) will be subject to an assessment of decay kinetics to account for biogenic carbon that would remain durably stored in the counterfactual. Half-life values must be selected from independently published sources, in the following order of preference:

Peer-reviewed, region- and product-specific studies that characterize the service life of wood products in the geographic context of The Project (e.g., Skog, 2008³⁵);
National greenhouse gas inventories or government reports that provide country-specific half-life values for major wood product categories;
IPCC 2019 Refinement to the 2006 Guidelines for National Greenhouse Gas Inventories default half-life values, categorized by product type³³;
As a last resort, if none of the above sources are applicable, conservative assumptions must be used that reflect the longest reasonable service life for the respective product category, with justification provided based on material characteristics and market practices.

The harvest cycle length ( $T$ ) should be derived from historical harvest data from the site. Evidence could include records from the harvesting operations or remote sensing data.

The harvest intensity ( $\gamma$ ) describes how much of the standing biomass in the forest is subject to harvest during harvesting:

 $\gamma = \frac{B}{K}$

(Equation 17)

Where:

$B$ is the standing total pre-harvest biomass in the forest
$K$ is the biomass that is harvested, inclusive of all residue pools for the harvested wood, in the same units as $B$

In scenarios of clear-cutting, $\gamma$ is equal to its minimum value of one. Where there is selection harvesting, $\gamma$ is greater than one. This should be estimated based on historical practice within the project site and can be evidenced by documentation from the harvesting operations or remote sensing. Where suitable evidence is not available, clear-cutting must be assumed as a conservative estimate of $\gamma$ .

The normalized regrowth symmetry ( $\beta$ ) describes non-linearity in the regrowth dynamics of the standing forest post-harvest (harvest occurs at t=0):

 $\beta = 1 - \int_{0}^{T} \frac{B(t) - B_{min}}{K} \, dt$

(Equation 18)

Where:

$B(t)$ is the standing biomass at time $t$ , in the same units as $K$
$B_{min}$ is the standing biomass post-harvest (excluding residues)

The integral term in this equation is equivalent to the temporal mean value of standing biomass over the course of a harvest cycle normalized to the harvest volume. Values of $\beta$ range from 0 to 1. A value of 0.5 represents perfectly linear regrowth in the forest. Values less than 0.5 indicate more rapid regrowth rates in early years that then decrease in latter years. Values greater than 0.5 indicate slower growth in initial years with acceleration of the growth rate in latter years.

The value of $\beta$ should be estimated from growth models which are ecologically suitable for the represented species or from historical remote sensing data of regrowth within the project area.

9.3.5

Evaluation of Dynamic Baseline Uncertainty

Isometric will account for uncertainty in the dynamic baseline to ensure a conservative estimate of CO₂e_{counterfactual,Total} in Equation 5. This will include an evaluation of at least the following sources of uncertainty:

Uncertainty in the forest carbon proxy maps, due to the uncertainty in data and models used to generate the proxy map;
Uncertainty in how well the forest carbon proxy represents relative changes in carbon stock between the control and project pixels;
Variation in the ensemble of control pixel values matched to each project pixel, representing the uncertainty across the ensemble of baseline scenarios therein; and
Uncertainty in the control pixels matched and if they adequately represent the likely Counterfactual scenario.

9.3.6

Counterfactual Determination in Settings With Limited Donor Zone

Situations may arise where The Project operates within an ecologically unique ecosystem, employs uncommon management techniques, or is located in a region where comparable concession-level spatial data are unavailable — thereby limiting the donor pool of spatial or temporal matches for dynamic baselining.

Under such conditions, Projects may derive the counterfactual scenario using a modeled dynamic baseline, constructed from The Project’s own historical harvesting record, supply-side operational capacity, and demand-side market conditions — subject to the constraints and dynamic evaluation requirements specified below. The modeled baseline must be conservative, evidence-based, and subject to upward-only (decreased harvest, increased counterfactual biomass) adjustment over time.

9.3.6.1

Applicability

A project may apply this section only where Isometric has determined, at Validation, that the eligible Donor Zone after masking for required variables and applying the time for space substitution (see Section 9.3.1.1) is still less than five times the project area.

The determination that a limited donor zone exists must be documented by Isometric and reported in the Validation Report. Once a Project applies a modeled dynamic baseline, it must continue to use the modeled baseline approach for the remainder of the Crediting Period unless Isometric determines that a sufficient donor pool has become available, in which case The Project must transition to the standard approach on a forward-moving basis.

9.3.6.2

Construction of the Modeled Baseline

Project Proponents must derive modeled baseline harvest scenarios from the following inputs, which will be approved for use at Validation:

Historical harvest rate. The baseline annual harvest area (in hectares per year) must be set equal to the historical average over a period no shorter than one-half of the rotation length and no shorter than 10 years, using the most recent pre-project data available. Years affected by exceptional circumstances (e.g., pandemic-related shutdowns, force majeure) may be excluded provided the exclusion is justified and documented. The Project must not select the historical period in a manner that inflates the baseline; where multiple defensible averaging periods exist, the most conservative value shall be used.
Accessibility and Operability of Harvest. The baseline must be evaluated against the baseline conditions set forth in Section 4.1.2 of this Module and Section 4.1.1 of the IFM Protocol, where the initial baseline is set on the project area and carbon stock which are subject to immediate harvest demand.
Supply-side operational capacity. The Project must document the concession’s harvesting capacity under normal operating conditions, including available equipment, workforce, and infrastructure. The baseline harvest area must not exceed demonstrated operational capacity.
Demand-side market conditions. The Project must document the regional market demand for the relevant timber products, including identified buyers and their historical purchasing volumes. The baseline harvest area must not exceed the volume supportable by demonstrated market demand.
- Projects must evaluate the demand in accordance with the principles outlined in Section 4.1.2.5.
Regulatory and concession constraints. The baseline must incorporate all applicable legal and regulatory constraints on harvesting, including concession license terms, allowable annual cut provisions, and any restrictions arising from forest management plans or regulatory authorities.
Carbon recovery curve. The Project must specify the carbon recovery curve used to translate the baseline harvest schedule into carbon stock changes over time. The curve must be derived from field data within the project area or from ecologically suitable growth models for the represented species and ecosystem. Uncertainty in the recovery curve must be quantified and reported.
- All models used in the development of the carbon recovery curve must meet the requirements set forth in Section 9.5.

The modeled baseline harvest area shall be set to the long-term average of the historical harvest rate, demonstrated supply-side capacity, demonstrated demand-side market absorption, and the regulatory allowable harvest. This ensures the baseline is conservative across all relevant dimensions.

9.3.6.3

Modeled Baseline Output and Counterfactual Calculation

The model must predict the standing aboveground counterfactual biomass as a function of time (CO₂e_{counterfactual,AGB}). This should be done at a minimum of annual resolution.

The modeled output must then be used in the equivalent calculations to Equations 10 and 11 to yield the counterfactual deduction. From project initiation up until any harvest is predicted by the model, the counterfactual will be calculated as:

 $CO_2e_{Counterfactual,Total} = CO_2e_{Counterfactual,AGB,t=RP}$

(Equation 19)

Where:

$CO_2e_{Counterfactual,AGB,t=RP}$ is the standing total counterfactual AGB at the end of the current Reporting Period in tonnes of CO₂e

Once any harvest occurs within the counterfactual, the counterfactual is calculated as:

 $CO_2e_{Counterfactual,Total} = f_{HWP} \frac{\int_{0}^{RP} CO_2e_{Counterfactual,AGB}(t) \, dt}{RP}$

(Equation 20)

Where:

$RP$ is the total project length at the end of the current Reporting Period, in years

Note that this equation is equivalent to Equation 11, and $f_{HWP}$ should be calculated following the parameters and procedure in Section 9.3.4.1.

9.3.6.4

Dynamic Evaluation of the Modeled Baseline

At each Reporting Period, the modeled baseline assumptions must be tested against observed conditions using the Modeled Baseline Evaluation Framework (Table 2). When any category undergoes a material change in the conditions which underpin the modeled baseline, The Project must adjust the baseline harvest area and associated carbon stock projections accordingly.

Where this evaluation identifies a material change, the project must:

Identify the specific baseline parameter(s) affected and quantify the impact on the baseline harvest area.
Recalculate the counterfactual carbon stock projections using the adjusted harvest area for the current Reporting Period and all subsequent Reporting Periods.
Report the adjustment, its justification, and its quantitative impact in the Monitoring Report for the current Reporting Period.

Adjustments are applied on a forward-moving basis from the start of the Reporting Period in which the change is identified. Adjustments cannot be applied retroactively to previously verified Reporting Periods. All adjustments are subject to approval by Isometric and the VVB.

Table 2. Modeled Baseline Evaluation Framework

Category	Test	Required Evidence	Recourse (if test fails)
Regulatory & Concession Status	Are the legal and regulatory conditions under which the concession operates unchanged such that the baseline harvest is still legally permissible?This includes concession license terms, allowable annual cut quotas, harvest moratoria, land tenure changes, and environmental regulations.	Review of current concession license, relevant legislation, and regulatory instruments.Documentation of any new restrictions, quota reductions, or moratoria affecting the project area.	Reduce the baseline harvest area to reflect the new legally allowable maximum.If logging is fully prohibited, the baseline harvest area is set to zero and no further Credits may be issued under this section.Recalculate counterfactual carbon stocks for the current and all subsequent Reporting Periods.
Accessibility & Operability	Are all areas assumed harvestable in the baseline still physically accessible and operable?This includes road and track condition, bridge or infrastructure collapse, natural disaster impacts, and terrain changes. Infrastructure deterioration attributable to project activities (e.g., road disuse following cessation of logging) must be considered.	Assessment following guidance set forth in Section 4.1.2.Identification of specific areas with reduced or eliminated access, with estimated area (ha) affected.	Reduce the baseline harvest area in proportion to the area no longer accessible or operable.Recalculate counterfactual carbon stocks for the current and all subsequent Reporting Periods.
Supply-Side Operational Capacity	Does the concession’s operational capacity still support the baseline harvest area?This includes equipment availability, workforce levels, and extraction infrastructure. Capacity reductions attributable to project activities (e.g., equipment sold or workforce reassigned following cessation of logging) must be considered.	Documentation of current equipment fleet status, workforce availability, and operational infrastructure relative to baseline assumptions.Evidence may include attestations from concession management, equipment inventories, or independent operational assessments.	Reduce the baseline harvest area to reflect the current demonstrated operational capacity.Recalculate counterfactual carbon stocks for the current and all subsequent Reporting Periods.
Demand-Side Market Conditions	Could regional and accessible markets absorb the timber output assumed in the baseline?This includes closures of mills, ports, or processing facilities; reductions in buyer purchasing volumes; and shifts in market demand for the relevant timber products.Demand is evaluated over a rolling period of at least one-half of the rotation length, with a minimum of 10 years. Consistent reductions in demand of more than 5% annually over this period constitute a material change.	Regional timber trade data, buyer records, or national export statistics for the relevant product class.Where The Project uses the Global Timber Model (Section 8.2), updated GTM outputs for the relevant product and region may be used.	Reduce the baseline harvest area to reflect the current demonstrated market absorption capacity.Recalculate counterfactual carbon stocks for the current and all subsequent Reporting Periods.
Carbon Recovery Curve Assumptions	Do the carbon recovery curve parameters (regrowth rate, maximum carbon stock, regrowth symmetry) remain valid based on the best available evidence?This includes new field data, updated allometric equations, or revised growth models for the project ecosystem.	Review of any new field measurements, published literature, or growth model updates applicable to the project area’s species and ecosystem.Where new evidence indicates the recovery curve overestimates carbon accumulation, the curve must be revised downward.	Revise the carbon recovery curve to reflect the most conservative interpretation of available evidence.Recalculate counterfactual carbon stocks for the current and all subsequent Reporting Periods using the revised curve.

9.3.6.5

Reporting

Each Monitoring Report must include a detailed summary of the modeled baseline evaluation applied for the Reporting Period, covering all categories in Table 2 and their results. Any baseline parameters identified as requiring adjustment and the reasoning for such a determination must be clearly reported. All adjustments must be fully described, including their quantitative impact on the counterfactual carbon stock projections and the volume of Credits requested for the current Reporting Period.

The following must be reported at each Reporting Period:

The result of each evaluation category in Table 2, including a clear statement of whether the test was passed or failed.
For any failed test: the specific evidence relied upon, the magnitude of the adjustment to the baseline harvest area, and the recalculated counterfactual carbon stock projections.
A comparison of the current modeled baseline harvest area with the originally validated baseline, identifying all cumulative adjustments made since Validation.

9.3.6.6

Verification

Verification of the modeled baseline evaluation must assess:

The completeness and accuracy of the evidence supporting each evaluation category.
The appropriateness and conservativeness of any adjustments to the baseline harvest area or carbon recovery curve.
The correct recalculation of counterfactual carbon stock projections and their impact on credited emission reductions and removals.

Where the verifier identifies evidence of a material change in baseline conditions that The Project has not accounted for, the verifier must require The Project to apply the appropriate adjustment before Credits may be issued for the Reporting Period.

9.3.6.7

Uncertainty Assessment of the Modeled Baseline

Uncertainty in the counterfactual must be characterized and propagated following to obtain a conservative estimate of C_{counterfactual}. This includes assessment of all relevant sources of uncertainty described in Section 9.3.5. Additionally, Projects using this approach must characterize and account for uncertainty in all the parameters informing the model. For parameters where uncertainty is not easily quantified, evidence must be provided to demonstrate that the value used is conservative. For all other parameters, the quantified uncertainty must be propagated through the modeled output and reported as part of the modeling procedures and results.

9.4

Calculation of CO|2|e|emissions,RP

Calculation of CO₂e_emissions,RP

CO₂e_emissions,RP is the total GHG emissions associated with a given Reporting Period, RP.

Equations and emissions calculation requirements for CO₂e_emissions,RP are set out in the relevant Protocol and are not repeated in this Module.

As part of CO₂e_emissions,RP, CO₂e_Leakage,RP must be quantified for the Reporting Period. CO₂e_Leakage,RP is quantified following the approach described in Section 8.2.

9.5

Model Validation Requirements

Any models used under this Protocol which contribute to the quantification of net CDR must be well-validated and skillful for the purpose that they were used for. Proof of model validation can be achieved through either:

A track record of use in science, industry, or government applications, which is demonstrated through multiple peer-reviewed papers, or proof of usage in a number of previous applications. Furthermore, the model must be relevant to the project area and tree species (e.g., covers similar ecoregions); or
Newly developed models without a track record of usage must be validated against reputable data sources, which include quality-controlled in situ measurements and public datasets adhering to FAIR (Findable, Accessible, Interoperable and Reusable) principles³⁶). Sufficient model validation data must be provided with the PDD.
Any models developed or used for the purpose of AGB quantification using the methodology described in Section 9.2.1 must also be evaluated and approved by Isometric as part of the required comprehensive assessment of the approach prior to use.

10.0

Storage and Durability of CO|2|e Removals

Storage and Durability of CO₂e Removals

The storage reservoir or the CO₂ removed through the IFM interventions in this Module is live aboveground woody biomass. The durability of a CDR process refers to the length of time for which CO₂ is removed from the Earth’s atmosphere and cannot contribute to further climate change. This Section details the durability and reversal monitoring requirements for storage of removed atmospheric CO₂ as aboveground woody biomass under this Module.

10.1

Durability

The durability of a Credit is equal to the length of the Ongoing Monitoring Period as outlined in Section 5.4. The minimum duration of the Ongoing Monitoring Period, and therefore minimum durability of Credits issued under this Module, is 40 years.

The duration of the Ongoing Monitoring Period must not exceed any of the following:

Protected status of land. If the protected status implemented at the end of the Crediting Period (see Section 4.3) has any associated duration, the Ongoing Monitoring Period must not exceed this time period.
Forest maintenance activities. Project Proponents must continue forest management and risk mitigation practices to maintain forest carbon stocks throughout the Ongoing Monitoring Period.

10.2

Ongoing Monitoring Period for Reversals

For the duration of the Ongoing Monitoring Period, Isometric will conduct monitoring for Reversals in the project area following the procedures described in IFM Protocol Section 10.5. Project Proponents will be responsible for reporting and quantification in response to any detected Reversals for the duration of the Ongoing Monitoring Period.

11.0

Definitions and Acronyms

Above Ground Biomass (AGB)The total mass of living woody biomass existing above the soil surface in a specified area.
AdditionalityAn evaluation of the likelihood that an intervention—for example, a CDR Project—causes a climate benefit above and beyond what would have happened in a no-intervention Baseline scenario.
BaselineA set of data describing pre-intervention or control conditions to be used as a reference scenario for comparison.
Below Ground Biomass (BGB)The total mass of living woody biomass existing below the soil surface in a specified area.
BeneficiaryThe organization benefiting from the Removal or Reduction claim afforded by a Certificate. This may be the current holder of the Certificate at the time of Retirement, or an organization specified by the Certificate account holder during the Retirement procedure.
BiodiversityThe diversity of life across taxonomic and spatial scales. Biodiversity can be measured within species (i.e. genetic diversity and variations in allele frequencies across populations), between species (i.e. the total number and abundance of species within and across defined regions), within ecosystems (i.e. the variation in functional diversity, such as guilds, life-history traits, and food-webs), and between ecosystems (variation in the services of abiotic and biotic communities across large, landscape-level scales) that support ecoregions and biomes.
Buffer PoolA common and recognized insurance mechanism among Registries allowing Certificates to be set aside (in this case by Isometric) to compensate for Reversals which may occur in the future.
Carbon Dioxide Equivalent Emissions (CO₂e)The amount of CO₂ emissions that would cause the same integrated radiative forcing or temperature change, over a given time horizon, as an emitted amount of GHG or a mixture of GHGs. One common metric of CO₂e is the 100-year Global Warming Potential.
Carbon Dioxide Removal (CDR)Activities that remove carbon dioxide (CO₂) from the atmosphere and store it in products or geological, terrestrial, and oceanic Reservoirs. CDR includes the enhancement of biological or geochemical sinks and direct air capture (DAC) and storage, but excludes natural CO₂ uptake not directly caused by human intervention.
ConservativePurposefully erring on the side of caution under conditions of Uncertainty by choosing input parameter values that will result in a lower net CO₂ Removal or GHG Reduction than if using the median input values. This is done to increase the likelihood that a given Removal or Reduction calculation is an underestimation rather than an overestimation.
CounterfactualAn assessment of what would have happened in the absence of a particular intervention – i.e., assuming the Baseline scenario.
Cradle-to-GraveConsidering impacts at each stage of a product's life cycle, from the time natural resources are extracted from the ground and processed through each subsequent stage of manufacturing, transportation, product use, and ultimately, disposal.
Crediting PeriodThe period of time over which a Project Design Document is valid, and over which Removals, Reductions or Environmental Attributes may be Verified, resulting in Issued Certificates.
DurabilityThe amount of time carbon removed from the atmosphere by an intervention – for example, a CDR project – is expected to reside in a given Reservoir, taking into account both physical risks and socioeconomic constructs (such as contracts) to protect the Reservoir in question.
Dynamic BaseliningA method for establishing and regularly updating the reference carbon stock levels in a reforestation project area, based on ongoing analysis of comparable non-project plots, to account for natural fluctuations and improve the accuracy of carbon Certificate calculations over the project lifetime.
Ecological IntegrityThe ability of an ecosystem to support and maintain ecological processes and a diverse community of organisms. It is measured as the degree to which a diverse community of native organisms is maintained, and is used as a proxy for ecological resilience, intended as the capacity of an ecosystem to adapt in the face of stressors, while maintaining the functions of interest.
Ecosystem FunctionThe natural processes and interactions that occur within an ecosystem, including the flow of energy and materials through biotic and abiotic components, encompassing activities like nutrient cycling, primary production, and habitat provision, which collectively maintain the balance and stability of the ecosystem.
EmissionsThe term used to describe greenhouse gas emissions to the atmosphere as a result of Project activities.
Greenhouse Gas (GHG)Those gaseous constituents of the atmosphere, both natural and anthropogenic (human-caused), that absorb and emit radiation at specific wavelengths within the spectrum of terrestrial radiation emitted by the Earth’s surface, by the atmosphere itself, and by clouds. This property causes the greenhouse effect, whereby heat is trapped in Earth’s atmosphere (CDR Primer, 2022).
International Standards Organization (ISO)A worldwide federation (NGO) of national standards bodies from more than 160 countries, one from each member country.
Issuance (of a Certificate)Certificates are issued to the Certificate Account of a Project Proponent with whom Isometric has a Validated Protocol after an Order for Verification and Certificate Issuance services from a Buyer and once a Verified Removal or Reduction has taken place.
LeakageThe increase in GHG emissions outside the geographic or temporal boundary of a project that results from that project's activities.
Light Detection and Ranging (LiDAR)LiDAR is a remote sensing technology that uses laser pulses to create highly accurate three-dimensional maps of forest structure, enabling measurements of tree height, canopy density, and biomass.
ModuleIndependent components of Isometric Certified Protocols which are transferable between and applicable to different Protocols.
Non-Governmental Organization (NGO)A nonprofit, usually with a societal, scientific, or political purpose; by definition an NGO is not associated with a governmental entity.
PathwayA collection of Removal or Reduction processes that have mechanisms in common.
ProjectAn activity or process or group of activities or processes that alter the condition of a Baseline and leads to Removals or Reductions.
Project Design Document (PDD)The document that clearly outlines how a Project will generate rigorously quantifiable Additional high-quality Removals or Reductions.
Project ProponentThe organization that develops and/or has overall legal ownership or control of a Removal or Reduction Project.
Project boundaryThe defined temporal and geographical boundary of a Project.
ProtocolA document that describes how to quantitatively assess the net amount of CO₂ removed by a process. To Isometric, a Protocol is specific to a Project Proponent's process and comprised of Modules representing the Carbon Fluxes involved in the CDR process. A Protocol measures the full carbon impact of a process against the Baseline of it not occurring.
Remote SensingThe use of satellite, aircraft and terrestrial deployed sensors to detect and measure characteristics of the Earth's surface, as well as the spectral, spatial and temporal analysis of this data to estimate biomass and biomass change.
RemovalThe term used to represent the CO₂ taken out of the atmosphere as a result of a CDR process.
ReservoirA location where carbon is stored. This can be via physical barriers (such as geological formations) or through partitioning based on chemical or biological processes (such as mineralization or photosynthesis).
Sensitivity AnalysisAn analysis of how much different components in a Model contribute to the overall Uncertainty.
StakeholderAny person or entity who can potentially affect or be affected by Isometric or an individual Project activity.
StorageDescribes the addition of carbon dioxide removed from the atmosphere to a reservoir, which serves as its ultimate destination. This is also referred to as “sequestration”.
Synthetic Aperture Radar (SAR)A remote sensing technology which uses radio waves to create images of the earth’s surface.
UncertaintyA lack of knowledge of the exact amount of CO₂ removed by a particular process, Uncertainty may be quantified using probability distributions, confidence intervals, or variance estimates.
ValidationA systematic and independent process for evaluating the reasonableness of the assumptions, limitations and methods that support a Project and assessing whether the Project conforms to the criteria set forth in the Isometric Standard and the Protocol by which the Project is governed. Validation must be completed by an Isometric approved third-party (VVB).
Validation and Verification Bodies (VVBs)Third-party auditing organizations that are experts in their sector and used to determine if a project conforms to the rules, regulations, and standards set out by a governing body. A VVB must be approved by Isometric prior to conducting validation and verification.
VerificationA process for evaluating and confirming the net Removals and Reductions for a Project, using data and information collected from the Project and assessing conformity with the criteria set forth in the Isometric Standard and the Protocol by which it is governed. Verification must be completed by an Isometric approved third-party (VVB).

12.0

Appendix A: Risk Assessment

The Risk Assessment is used to assess the overall delivery and storage risk associated with improved forest management through transition to protected status and may inform the Buffer Pool contribution during Credit delivery (see IFM Protocol Section 10.4). The assessment must first be filled in by the Project Proponent and must be validated by a VVB. During project Validation, discrepancies between the Project Proponent’s self reported score and VVB may result in monitoring or risk mitigation activities, or project ineligibility. Eligible projects must have an initial risk score ≤ 16 and initial risk category scores at or below the following thresholds:

Project Proponent Capacity Risk ≤ 7
Financial Viability Risk ≤ 7
Social Governance Risk ≤ 9
Disturbance Risk ≤ 14

All risk categories shall have a minimum score of 0, regardless of the outcome of the Risk Assessment.

If Project Proponents choose to forgo a flat 20% Buffer Pool contribution, this Risk Assessment will inform Buffer Pool contributions for The Project according to the process outlined in Appendix C for each Reporting Period and in accordance with the requirements in the IFM Protocol (see Section 10.4.1).

After each new Risk Assessment evaluation, Isometric will update the required percentage of newly issued Credits that must be contributed to the Buffer Pool by The Project. Isometric encourages Project Proponents to continuously monitor, mitigate, and reduce risks.

Table A1. Risk Assessment for Improved Forest Management projects involving transition to protected status of previously logged lands, with the score to be filled out for each question.

Risk Category	Risk Indicator	Evidence	Scoring Guidelines
Project Proponent Capacity Risk	Does the Project Proponent maintain staff with domain expertise relevant for forest carbon projects? (e.g., forest ecology, forest measurement, carbon accounting)	Project's team structure	If no, describe how gaps in relevant expertise will be filled, +1.
	Does the Project Proponent maintain a staff presence in the local vicinity (within one day of travel) of the project site?	Project's team structure	If no, +2.
	Was the Project Proponent established more than 12 months ago?	Project Proponent declaration	If no, +1.
	Does the Project Proponent have prior experience in improved forest management, carbon projects or planting?	Review of Project Proponent provided evidence and independent research	If yes, -1.
	Has the Project Proponent abandoned or failed previous projects?	Review of projects on other registries	If yes, +3.
	What proportion of the project area requires active enforcement against external threats (e.g., illegal logging, agricultural encroachment, unauthorized grazing) to protect carbon stocks?	Peer-reviewed publications, local or national government databases, NGO reports and assessments, site security assessment, satellite data, data on enforcement from other reforestation projects in the same region, local or national reports on environmental crimes or violations	If > 50% of project area, +2. If 25 to 50% of project area, +1. If no active enforcement required, -1.
	Has the Project obtained non-delivery risk insurance	Project Proponent declaration	If yes, -1.
Financial Viability Risk	Has the Project secured funding to cover all activities required before carbon revenue accrues?	Project financial plan	If > 90%, -2. If > 80%, -1. If < 50%, +1. If < 30%, +2. If < 10%, fail.
	What is the projected time to reach financial breakeven?	Project financial plan	If > 20 years, fail. If 15 to 20 years, +3. If 10 to 15 years, +2. If 5 to 10 years, +1.
	Is the budget reasonable given the proposed project activities and ex-ante estimates for forest growth? Budget should at minimum include: personnel, equipment and supplies, infrastructure, travel and certification fees.	Project financial plan	If no, +2.
	Does the project financial plan rely on future increases in market price for Carbon Credits?	Project financial plan	If yes, +1.
	Has The Project obtained non-delivery risk insurance	Project Proponent declaration	If yes, -2.
Social Governance Risk	Are there currently or have there been disputes over land ownership over the last 20 years?	Jurisdictional history	If yes, + 2.
	Does the government have a history of revoking legal agreements regarding land ownership, access, and usage?	Jurisdictional history	If yes, + 2.
	Does the project host country score below the 40th percentile on 3+ of the Worldwide Governance Indicators over the last 10 years?	Worldwide Governance Indicators	If yes, +2.
	Does the government have an NDC in place that addresses corresponding adjustments/prevents of project Credits and NDC contributions?	National registries	If no, +1.
	Does The Project have a detailed benefit-sharing plan that includes: clear distribution mechanisms, transparent criteria for beneficiary selection, a grievance resolution process, monitoring and reporting procedures?	Project financial plan	If no, +2. If missing elements, +1. If legally binding with all elements, -1. If audited by 3rd party with all elements, -1
	Does the Project Proponent have a presence on human rights, environmental or labor infraction lists?	National registries	If yes, fail.
	Does the Project Proponent have ongoing legal disputes?	National registries	If yes, +1.
	Have projects on Indigenous or Community Lands been identified?	Cross reference project documentation with Global Forest Watch	If no, fail.
	Has the Project Proponent developed and/or procured a forest management plan for enrolled landowners	Project Design Document and/or Project Proponent Declaration	If no, +1.
	Are opportunity cost risk mitigations in place?	Legal agreements protecting carbon stocks, Non-profit status documentation, grant/funding agreements	Legally protected for Crediting Period, -1. Legally protected for ≥ 100 years, -2. Non-profit status or secured additional funding, -1.
Disturbance Risk	Fire risk	Mean daily Global Fire Weather Index over the prior two years	If > 10, +1. If > 30, +2. If > 50, +3. If > 75, fail.
	Pest and disease outbreak risk	Regional third-party maps, if available.	If high, +2. If medium, +1. If low, 0.
	Extreme weather (temperature - heat and cold)	IPCC AR6³⁷ - See Appendix B for scoring	If high, +2. If medium, +1. If low, 0.
	Extreme weather (hydrologic - flood and drought)	IPCC AR6³⁷ - See Appendix B for scoring	If high, +2. If medium, +1. If low, 0.
	Windfall risk	Regional third-party maps, if available.	If high, +2. If medium, +1. If low, 0.
	Icestorm risk	Regional third-party maps, if available.	If high, +2. If medium, +1. If low, 0.
	Coastal risks (sea level rise, storm surge, tropical cyclones, salinity intrusion)	Regional third-party maps, if available.	If high, +2. If medium, +1. If low, 0.
	Geologic risks (earthquakes, tsunami, volcanoes)	NOAA NCEI Natural Hazards viewer	If historical hazards in area, +1.
	Illegal timber risk	Country IDAT risk score	If high, +2. If medium, +1. If low, 0.
	Surrounding anthropogenic activities pose environmental risk (e.g., toxic pollution, industrial farming, new developments etc.)	Satellite imagery, site visit	If yes, +1.
	Ecological Resilience	Project Design Document	If > 80% of trees heat/drought tolerant, -1.

13.0

Appendix B: Calculating Extreme Weather Risk Scores

The following section outlines how Isometric calculates the indicator scores for climate-related extreme weather disturbance risks to carbon permanence within a project’s region (Figure B1). Project Proponents should use Table B1 to lookup the Isometric-calculated values for their project's region and include those scores in their Risk Assessment (see Appendix A).

Extreme weather risks are assessed via two indicators: a temperature indicator (extreme heat and/or cold) and a hydrologic indicator (flooding and/or drought). Each indicator includes both historical data (1961-2015) and projected future extreme events. Historical data indicate the likelihood of extreme events based on past climate patterns, e.g., projects in regions with extended dry periods are expected to experience increased water stress as part of their typical climate. Climate model projections describe how changing climate conditions, relative to historical patterns, might present an increased risk of disturbances. Areas where there is a larger shift towards extreme conditions under future climate relative to their historical baseline have a greater disturbance risk (e.g., drier conditions relative to historical averages increases risk for drought-driven mortality).

To calculate the scores in Table B1, Isometric uses values from the Intergovernmental Panel on Climate Change AR6 report³⁷. The temperature indicator, IndicatorTemperature, is calculated using data describing the annual number of frost days (FD, minimum temperature below 0°C) and annual number of days with a maximum temperature above 40°C (TX40) to capture extreme cold and extreme heat risks, respectively. The hydrologic indicator, IndicatorHydrological, is calculated using data describing the maximum 5-day precipitation (RX5Day) and annual maximum number of consecutive dry days (CDD) to capture risks of flooding and drought, respectively. All values come from the CMIP6 climate models. Future projections use the SSP2-4.5 medium term (2041-2060) scenario and are assessed as the change in value relative to a historical baseline (1961-1990).

For each indicator subcomponent, the region’s terrestrial median value is compared with the global terrestrial distribution of the same variable (Table B2). To convert the regional value into a subscore, regional values below the global 75th percentile are considered Low Risk, regional values equal to or greater than the global 75th percentile but below the 90th percentile are Medium Risk, and any regional values equal to or greater than the global 90th percentile are High Risk. Low Risks are given a subscore of 0, Medium Risks are 0.25, and High Risks are 0.5. The overall score for each of the indicators is calculated by summing the corresponding subscores, as described below:

Projected change in the number of frost days is not included as a subcomponent since it is projected that they will decline under future climate across the globe, representing a low risk of future extreme cold events.

Figure B1. Map and lookup table for IPCC regional codes

Table B1. Regional Lookup Table of Disturbance Risk

Region	Indicator	Variable	Time	Value	Risk	Score	Total
NW North America (NWN)	Temperature	Frost Days	Historical	224.2	High	0.5	0.5
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0	Low	0
	Hydrological	CDD	Historical	23.5	Low	0	0.5
		CDD	Change (Days)	-1.4	Low	0
		5-Day Precip	Historical	54.4	Low	0
		5-Day Precip	Change (%)	11.9	High	0.5
NE North America (NEN)	Temperature	Frost Days	Historical	242.9	High	0.5	0.5
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0	Low	0
	Hydrological	CDD	Historical	25.1	Low	0	0.5
		CDD	Change (Days)	-2.7	Low	0
		5-Day Precip	Historical	50.6	Low	0
		5-Day Precip	Change (%)	11.8	High	0.5
Western North America (WNA)	Temperature	Frost Days	Historical	128.4	High	0.5	0.5
		Days > 40°C	Historical	0.9	Low	0
		Days > 40°C	Change (Days)	2	Low	0
	Hydrological	CDD	Historical	40.6	Low	0	0
		CDD	Change (Days)	-0.2	Low	0
		5-Day Precip	Historical	67.3	Low	0
		5-Day Precip	Change (%)	5.5	Low	0
Central North America (CNA)	Temperature	Frost Days	Historical	104.9	High	0.5	0.5
		Days > 40°C	Historical	4.7	Low	0
		Days > 40°C	Change (Days)	8.9	Low	0
	Hydrological	CDD	Historical	23.7	Low	0	0.25
		CDD	Change (Days)	-0.4	Low	0
		5-Day Precip	Historical	84.3	Medium	0.25
		5-Day Precip	Change (%)	6.7	Low	0
Eastern North America (ENA)	Temperature	Frost Days	Historical	116	High	0.5	0.5
		Days > 40°C	Historical	0.1	Low	0
		Days > 40°C	Change (Days)	0.6	Low	0
	Hydrological	CDD	Historical	15.5	Low	0	0.75
		CDD	Change (Days)	-0.3	Low	0
		5-Day Precip	Historical	89.4	High	0.5
		5-Day Precip	Change (%)	9	Medium	0.25
Northern Central America (NCA)	Temperature	Frost Days	Historical	15.9	Low	0	0
		Days > 40°C	Historical	4.7	Low	0
		Days > 40°C	Change (Days)	8.7	Low	0
	Hydrological	CDD	Historical	51.6	Low	0	0.5
		CDD	Change (Days)	-0.2	Low	0
		5-Day Precip	Historical	92.9	High	0.5
		5-Day Precip	Change (%)	6	Low	0
Southern Central America (SCA)	Temperature	Frost Days	Historical	0.1	Low	0	0
		Days > 40°C	Historical	0.5	Low	0
		Days > 40°C	Change (Days)	1.7	Low	0
	Hydrological	CDD	Historical	39.7	Low	0	0.5
		CDD	Change (Days)	-1.6	Low	0
		5-Day Precip	Historical	134.3	High	0.5
		5-Day Precip	Change (%)	4.3	Low	0
Caribbean (CAR)	Temperature	Frost Days	Historical	0	Low	0	0
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0	Low	0
	Hydrological	CDD	Historical	24.3	Low	0	0.5
		CDD	Change (Days)	0.1	Low	0
		5-Day Precip	Historical	99.9	High	0.5
		5-Day Precip	Change (%)	0.8	Low	0
NW South America (NWS)	Temperature	Frost Days	Historical	0.6	Low	0	0
		Days > 40°C	Historical	0.1	Low	0
		Days > 40°C	Change (Days)	0.8	Low	0
	Hydrological	CDD	Historical	28.6	Low	0	0.5
		CDD	Change (Days)	-0.2	Low	0
		5-Day Precip	Historical	133	High	0.5
		5-Day Precip	Change (%)	7.5	Low	0
Northern South America (NSA)	Temperature	Frost Days	Historical	0	Low	0	0
		Days > 40°C	Historical	0.5	Low	0
		Days > 40°C	Change (Days)	9.4	Low	0
	Hydrological	CDD	Historical	46.7	Low	0	1
		CDD	Change (Days)	9.7	High	0.5
		5-Day Precip	Historical	111.6	High	0.5
		5-Day Precip	Change (%)	5.5	Low	0
NE South America (NES)	Temperature	Frost Days	Historical	0	Low	0	0
		Days > 40°C	Historical	0.3	Low	0
		Days > 40°C	Change (Days)	4.4	Low	0
	Hydrological	CDD	Historical	95	High	0.5	1.5
		CDD	Change (Days)	6.3	High	0.5
		5-Day Precip	Historical	144.3	High	0.5
		5-Day Precip	Change (%)	5.7	Low	0
South America-Monsoon (SAM)	Temperature	Frost Days	Historical	7.5	Low	0	0.25
		Days > 40°C	Historical	2.2	Low	0
		Days > 40°C	Change (Days)	11.5	Medium	0.25
	Hydrological	CDD	Historical	64.8	Medium	0.25	1.25
		CDD	Change (Days)	13.7	High	0.5
		5-Day Precip	Historical	133.7	High	0.5
		5-Day Precip	Change (%)	6	Low	0
SW South America (SWS)	Temperature	Frost Days	Historical	35.8	Low	0	0
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0	Low	0
	Hydrological	CDD	Historical	65.9	Medium	0.25	0.5
		CDD	Change (Days)	-4.2	Low	0
		5-Day Precip	Historical	83	Medium	0.25
		5-Day Precip	Change (%)	-0.9	Low	0
SE South America (SES)	Temperature	Frost Days	Historical	16.6	Low	0	0
		Days > 40°C	Historical	2.8	Low	0
		Days > 40°C	Change (Days)	5.5	Low	0
	Hydrological	CDD	Historical	36.3	Low	0	0.75
		CDD	Change (Days)	0.4	Medium	0.25
		5-Day Precip	Historical	105.1	High	0.5
		5-Day Precip	Change (%)	8.4	Low	0
Southern South America (SSA)	Temperature	Frost Days	Historical	75.4	Low	0	0
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0.1	Low	0
	Hydrological	CDD	Historical	20.5	Low	0	0.5
		CDD	Change (Days)	1.6	High	0.5
		5-Day Precip	Historical	57.5	Low	0
		5-Day Precip	Change (%)	3.4	Low	0
Northern Europe (NEU)	Temperature	Frost Days	Historical	150.3	High	0.5	0.5
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0	Low	0
	Hydrological	CDD	Historical	18.5	Low	0	0.25
		CDD	Change (Days)	0	Low	0
		5-Day Precip	Historical	52.8	Low	0
		5-Day Precip	Change (%)	10	Medium	0.25
Western & Central Europe (WCE)	Temperature	Frost Days	Historical	109.7	High	0.5	0.5
		Days > 40°C	Historical	0.1	Low	0
		Days > 40°C	Change (Days)	0.7	Low	0
	Hydrological	CDD	Historical	22.8	Low	0	0.5
		CDD	Change (Days)	1.3	High	0.5
		5-Day Precip	Historical	55	Low	0
		5-Day Precip	Change (%)	8.5	Low	0
Eastern Europe (EEU)	Temperature	Frost Days	Historical	171.4	High	0.5	0.5
		Days > 40°C	Historical	1	Low	0
		Days > 40°C	Change (Days)	2.7	Low	0
	Hydrological	CDD	Historical	27.6	Low	0	0.5
		CDD	Change (Days)	1.1	Medium	0.25
		5-Day Precip	Historical	42.9	Low	0
		5-Day Precip	Change (%)	10	Medium	0.25
Mediterranean (MED)	Temperature	Frost Days	Historical	27.6	Low	0	0.25
		Days > 40°C	Historical	6	Low	0
		Days > 40°C	Change (Days)	11.8	Medium	0.25
	Hydrological	CDD	Historical	75	High	0.5	1
		CDD	Change (Days)	6.7	High	0.5
		5-Day Precip	Historical	49.5	Low	0
		5-Day Precip	Change (%)	3.9	Low	0
Western Africa (WAF)	Temperature	Frost Days	Historical	0	Low	0	1
		Days > 40°C	Historical	24	High	0.5
		Days > 40°C	Change (Days)	26.4	High	0.5
	Hydrological	CDD	Historical	83.5	High	0.5	1.25
		CDD	Change (Days)	-0.4	Low	0
		5-Day Precip	Historical	85.2	Medium	0.25
		5-Day Precip	Change (%)	19.6	High	0.5
Central Africa (CAF)	Temperature	Frost Days	Historical	0	Low	0	0.25
		Days > 40°C	Historical	11.1	Medium	0.25
		Days > 40°C	Change (Days)	9.2	Low	0
	Hydrological	CDD	Historical	61.8	Low	0	0.75
		CDD	Change (Days)	-0.1	Low	0
		5-Day Precip	Historical	84.4	Medium	0.25
		5-Day Precip	Change (%)	14.9	High	0.5
North Eastern Africa (NEAF)	Temperature	Frost Days	Historical	0	Low	0	1
		Days > 40°C	Historical	16.1	High	0.5
		Days > 40°C	Change (Days)	15.4	High	0.5
	Hydrological	CDD	Historical	80.4	High	0.5	1
		CDD	Change (Days)	-2.1	Low	0
		5-Day Precip	Historical	64.6	Low	0
		5-Day Precip	Change (%)	15.4	High	0.5
South Eastern Africa (SEAF)	Temperature	Frost Days	Historical	0	Low	0	0
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0.3	Low	0
	Hydrological	CDD	Historical	78.5	High	0.5	1.5
		CDD	Change (Days)	0.4	Medium	0.25
		5-Day Precip	Historical	91.9	High	0.5
		5-Day Precip	Change (%)	9.7	Medium	0.25
West Southern Africa (WSAF)	Temperature	Frost Days	Historical	1.2	Low	0	0
		Days > 40°C	Historical	0.1	Low	0
		Days > 40°C	Change (Days)	3	Low	0
	Hydrological	CDD	Historical	108.7	High	0.5	1.5
		CDD	Change (Days)	10.5	High	0.5
		5-Day Precip	Historical	87.6	High	0.5
		5-Day Precip	Change (%)	2	Low	0
East Southern Africa (ESAF)	Temperature	Frost Days	Historical	2.7	Low	0	0
		Days > 40°C	Historical	0.7	Low	0
		Days > 40°C	Change (Days)	2.8	Low	0
	Hydrological	CDD	Historical	68.7	Medium	0.25	1.25
		CDD	Change (Days)	4.3	High	0.5
		5-Day Precip	Historical	127.5	High	0.5
		5-Day Precip	Change (%)	6	Low	0
Madagascar (MDG)	Temperature	Frost Days	Historical	0	Low	0	0
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0.2	Low	0
	Hydrological	CDD	Historical	46.7	Low	0	0.5
		CDD	Change (Days)	-1.2	Low	0
		5-Day Precip	Historical	175.7	High	0.5
		5-Day Precip	Change (%)	5.8	Low	0
Russian-Arctic (RAR)	Temperature	Frost Days	Historical	271.3	High	0.5	0.5
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0	Low	0
	Hydrological	CDD	Historical	31.5	Low	0	0.5
		CDD	Change (Days)	-4.3	Low	0
		5-Day Precip	Historical	39.7	Low	0
		5-Day Precip	Change (%)	16.7	High	0.5
West Siberia (WSB)	Temperature	Frost Days	Historical	203.1	High	0.5	0.5
		Days > 40°C	Historical	0.7	Low	0
		Days > 40°C	Change (Days)	2	Low	0
	Hydrological	CDD	Historical	31.4	Low	0	0.25
		CDD	Change (Days)	-0.4	Low	0
		5-Day Precip	Historical	37.5	Low	0
		5-Day Precip	Change (%)	10.8	Medium	0.25
East Siberia (ESB)	Temperature	Frost Days	Historical	233.9	High	0.5	0.5
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0.1	Low	0
	Hydrological	CDD	Historical	34.1	Low	0	0.25
		CDD	Change (Days)	-3.7	Low	0
		5-Day Precip	Historical	54.5	Low	0
		5-Day Precip	Change (%)	11.5	Medium	0.25
Russian-Far-East (RFE)	Temperature	Frost Days	Historical	238.1	High	0.5	0.5
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0	Low	0
	Hydrological	CDD	Historical	28.8	Low	0	0.5
		CDD	Change (Days)	-3.2	Low	0
		5-Day Precip	Historical	65.1	Low	0
		5-Day Precip	Change (%)	14.4	High	0.5
West Central Asia (WCA)	Temperature	Frost Days	Historical	95.8	High	0.5	1.5
		Days > 40°C	Historical	22	High	0.5
		Days > 40°C	Change (Days)	17.5	High	0.5
	Hydrological	CDD	Historical	113.6	High	0.5	0.75
		CDD	Change (Days)	-0.3	Low	0
		5-Day Precip	Historical	42.5	Low	0
		5-Day Precip	Change (%)	10	Medium	0.25
East Central Asia (ECA)	Temperature	Frost Days	Historical	195.6	High	0.5	0.5
		Days > 40°C	Historical	0.5	Low	0
		Days > 40°C	Change (Days)	2.5	Low	0
	Hydrological	CDD	Historical	75.1	High	0.5	1
		CDD	Change (Days)	-6.2	Low	0
		5-Day Precip	Historical	30.5	Low	0
		5-Day Precip	Change (%)	12.9	High	0.5
Tibetan-Plateau (TIB)	Temperature	Frost Days	Historical	258.6	High	0.5	0.5
		Days > 40°C	Historical	1.6	Low	0
		Days > 40°C	Change (Days)	0.4	Low	0
	Hydrological	CDD	Historical	42.3	Low	0	0.75
		CDD	Change (Days)	-2.6	Low	0
		5-Day Precip	Historical	80.9	Medium	0.25
		5-Day Precip	Change (%)	11.6	High	0.5
East Asia (EAS)	Temperature	Frost Days	Historical	91.7	Medium	0.25	0.25
		Days > 40°C	Historical	0.3	Low	0
		Days > 40°C	Change (Days)	0.7	Low	0
	Hydrological	CDD	Historical	29.1	Low	0	0.75
		CDD	Change (Days)	0.1	Low	0
		5-Day Precip	Historical	132	High	0.5
		5-Day Precip	Change (%)	9.6	Medium	0.25
South Asia (SAS)	Temperature	Frost Days	Historical	7.9	Low	0	1
		Days > 40°C	Historical	33.1	High	0.5
		Days > 40°C	Change (Days)	14.5	High	0.5
	Hydrological	CDD	Historical	93.9	High	0.5	1.5
		CDD	Change (Days)	-3.3	Low	0
		5-Day Precip	Historical	132.2	High	0.5
		5-Day Precip	Change (%)	12	High	0.5
Southeast Asia (SEA)	Temperature	Frost Days	Historical	0	Low	0	0
		Days > 40°C	Historical	0.3	Low	0
		Days > 40°C	Change (Days)	1.1	Low	0
	Hydrological	CDD	Historical	26.8	Low	0	0.75
		CDD	Change (Days)	0.8	Medium	0.25
		5-Day Precip	Historical	168.4	High	0.5
		5-Day Precip	Change (%)	7.3	Low	0
Northern Australia (NAU)	Temperature	Frost Days	Historical	0	Low	0	0.75
		Days > 40°C	Historical	11.8	Medium	0.25
		Days > 40°C	Change (Days)	20.4	High	0.5
	Hydrological	CDD	Historical	95.7	High	0.5	1.25
		CDD	Change (Days)	0.7	Medium	0.25
		5-Day Precip	Historical	163.7	High	0.5
		5-Day Precip	Change (%)	7.7	Low	0
Central Australia (CAU)	Temperature	Frost Days	Historical	0.1	Low	0	1
		Days > 40°C	Historical	27.8	High	0.5
		Days > 40°C	Change (Days)	75.8	High	0.5
	Hydrological	CDD	Historical	27.3	Low	0	1
		CDD	Change (Days)	3.5	High	0.5
		5-Day Precip	Historical	86.5	High	0.5
		5-Day Precip	Change (%)	4.7	Low	0
Eastern Australia (AU)	Temperature	Frost Days	Historical	1.4	Low	0	0
		Days > 40°C	Historical	2.7	Low	0
		Days > 40°C	Change (Days)	4.2	Low	0
	Hydrological	CDD	Historical	35.8	Low	0	0.5
		CDD	Change (Days)	-0.5	Low	0
		5-Day Precip	Historical	120.6	High	0.5
		5-Day Precip	Change (%)	5.6	Low	0
Southern Australia (SAU)	Temperature	Frost Days	Historical	1.3	Low	0	0
		Days > 40°C	Historical	7.1	Low	0
		Days > 40°C	Change (Days)	6.9	Low	0
	Hydrological	CDD	Historical	40.2	Low	0	0.5
		CDD	Change (Days)	2	High	0.5
		5-Day Precip	Historical	60.3	Low	0
		5-Day Precip	Change (%)	2.8	Low	0
New Zealand (NZ)	Temperature	Frost Days	Historical	5.9	Low	0	0
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0	Low	0
	Hydrological	CDD	Historical	13.8	Low	0	0.75
		CDD	Change (Days)	0.5	Medium	0.25
		5-Day Precip	Historical	92.3	High	0.5
		5-Day Precip	Change (%)	5.6	Low	0
South Pacific Ocean (SPO)	Temperature	Frost Days	Historical	0	Low	0	0
		Days > 40°C	Historical	0	Low	0
		Days > 40°C	Change (Days)	0	Low	0
	Hydrological	CDD	Historical	19.4	Low	0	0.5
		CDD	Change (Days)	-0.5	Low	0
		5-Day Precip	Historical	183.3	High	0.5
		5-Day Precip	Change (%)	3.8	Low	0

Table B2. Global Benchmark Values for Extreme Weather Risks.

Time Frame	Variable	Median	75th%	90th%
Historical	Frost Days	89.8	94.1	97.5
	Days Max Temp > 40°C	9.9	15.1	21.9
	Consecutive Dry Days	63.7	71	76.2
	Maximum 5-day Precipitation (mm)	79.5	86	90.4
Projected Future	Frost Days	-	-	-
	Days Max Temp > 40°C	9.9	11.8	14.6
	Consecutive Dry Days	0.3	1.1	1.8
	Maximum 5-day Precipitation (%)	8.9	11.5	14.1

14.0

Appendix C: Buffer Pool Contributions

By default, Projects are subject to a flat 20% Buffer Pool contribution as outlined in the IFM Protocol (see Section 10.4.1) of the Improved Forest Management Protocol. Project Proponents may opt to calculate a project-specific Buffer Pool contribution based on the outputs of their Risk Assessment (Appendix A) for each Reporting Period.

As required in Section 4.3, an additional 5% must be added to the buffer pool contribution for every Verification (regardless of the contribution calculation selected from the above) where documentation is not in place to evidence the protection status of the project area at the end of the Crediting Period.

The following steps are used to convert the outputs of the Risk Assessment into a Buffer Pool contribution:

Sum the total score for each risk category in Table A1.
Map the risk score for each risk category into a Buffer Pool contribution using Table C1.
Sum the Buffer Pool contribution for each risk category to obtain the total Buffer Pool contribution.

Table C1. Risk score to Buffer Pool contribution conversion for each risk category.

Risk Category	Cumulative Risk Score	Buffer Pool Contribution
Project Proponent Capacity Risk	0	2.0
	1	2.2
	2	2.7
	3	4.0
	4	6.0
	5	7.3
	6	7.8
	7	8.0
Financial Viability Risk	0	2.0
	1	2.2
	2	2.7
	3	4.0
	4	6.0
	5	7.3
	6	7.8
	7	8.0
Social Governance Risk	0	2.0
	1	2.2
	2	2.5
	3	3.1
	4	4.3
	5	5.7
	6	6.9
	7	7.5
	8	7.8
	9	8.0
Disturbance Risk	0	2.0
	1	2.1
	2	2.3
	3	2.5
	4	2.8
	5	3.4
	6	4.1
	7	5.0
	8	5.9
	9	6.6
	10	7.2
	11	7.5
	12	7.7
	13	7.9
	14	8.0

The Buffer Pool contribution for each risk category is determined using a sigmoid function described by Equation C1. The Buffer Pool contribution for each risk category ranges from 2% to 8%.

 $BP_{risk}=\frac{L}{1+e^{-k(x-x_0)}}+2$

(Equation C1)

Where:

$BP_{risk}$ is the Buffer Pool contribution for a given risk category.
$L=6$ is the range of Buffer Pool contributions within each risk category (2% to 8%).
$k = \frac{10}{cutoff -1}$ is the steepness parameter of the sigmoid curve and determines how quickly the function transitions between its minimum and maximum values.
$x_0 = \frac{cutoff}{2}$ is the midpoint of the sigmoid curve.
$x$ is the risk score for a given risk category.
$cutoff$ is the value at which the Project fails the Risk Assessment, noted in Appendix A.

The sigmoid function, Equation C1, applied to each risk category can also be visualized in Figure C1.

Figure C1. Buffer Pool contribution based on risk score for each risk category.

14.1

Project-Specific Buffer Pool Contribution Example

The Project has completed the Risk Assessment and obtained the following risk scores in a Reporting Period:

Project Proponent Capacity Risk = 2
Financial Viability Risk = 4
Social Governance Risk = 3
Disturbance Risk = 3

Mapping these risk scores to Table C1, the total Buffer Pool contribution for the Project is:

2.7% + 6.0% + 3.1% + 2.5% = 14.3%

If The Project did not have evidence of protected status commencing at the end of the Crediting Period, the total would be 19.3%.

15.0

Appendix D: Implementation of the Global Timber Model

This appendix provides detailed information on how Isometric implements the Global Timber Model (GTM) for leakage assessment in this Module, including technical requirements, scalar values, and forest type-regional classifications used in the modeling process.

15.1

Model Implementation Overview

Isometric implements the Global Timber Model (GTM) to quantify leakage deductions for each Reporting Period based on global runs of leakage rates for forest-type regions, annualized and weighted by The Project's basal area (see Section 8.2). Currently, Isometric uses a 2025 version of the GTM published by Dr. Adam Daigneault at the University of Maine, Dr. Brent Sohngen at Ohio State University, and collaborators from The Nature Conservancy.

15.2

GTM Scalar Values and Parameters

Isometric currently applies the scalar values and parameters found below in Table D1 in its GTM implementation.

Table D1. Summary Table of Key Scalars in GTM for Protocol Leakage Assessment

Scalar	Value	Same as used in Daigneault et al 2025	Explanation
Annual discount rate	5.00%	Yes	Commonly assumed to represent the average expected rate of return in the global forest sector
Global carbon project implementation rate	4.00%	No	A conservative accounting of forest area unavailable for commercial harvest due to carbon projects; see detailed explanation below
Elasticity of management intensity to timber price	Variable	Yes	Set for each region
Elasticity of timber demand to timber price	-1.0	Yes	Substitutions occur over decade-long timesteps in GTM, and in aggregate are more likely than single substitutions in single years. See Sohngen 2024 for additional explanation.
Elasticity of land area in forest to timber price	0.3	Yes	Based on Lubowski et al. 2006³⁸, Sohngen et al. 2019²⁶

15.2.1

Global Carbon Project Implementation Rate Detail

To date, the GTM uses a global implementation rate representing the proportion of all forest land globally available for harvest that is enrolled in forest carbon projects. Isometric determines harvest eligibility by accessibility, i.e., all accessible forests are eligible. However, Isometric has excluded forest area reported in the FAO Forest Resources Assessment as "protected".

At publication of this Module, the total global area of land enrolled in forest carbon projects is 77.599 Mha, based on an analysis of all forest-based carbon projects recorded by Renoster as of June 3, 2024. This represents approximately 8% of the total available forest area, which is 982.5 Mha as of the publication of this Module.

Research by Haya et al. (2023)²⁴^,²³, Stapp et al. (2023)³⁹, and others suggests that the majority of forest carbon projects greatly overestimate emission reductions and that enrollment in carbon projects has historically been unlikely to result in near-term reductions in harvesting or deforestation. Thus, Isometric applies a conservative estimate that the actual amount of carbon project land on which all harvest is prevented is 50% of the calculated implementation rate of 8%. Thus, Isometric applies a global carbon project implementation rate of 4% (Table D1).

15.3

Forest Type-Region Classifications

Isometric will match the species present in the project area to a GTM forest type and region (Tables D2, D3). The forest types are based on the 2010 United Nations Food and Agriculture Organization (UN FAO) Global Ecological Zones (GEZs), with enhanced resolution for United States forest types based on USFS FIA Regional Groupings. If species or genus are not explicitly listed in the GTM forest types, consult authoritative sources including local foresters and Wood Database to determine similar commercial use and ecological characteristics for matching.

Table D2. Forest type and region classification table for the United States

Forest Type	Region	Forest Type Description	Region Description
Pine	Southeast	Pine species grown naturally or commercially, including loblolly pine (Pinus taeda), slash pine (P. elliottii), longleaf pine (P. palustris), and shortleaf pine (P. echinata)	Virginia, North Carolina, South Carolina, Georgia, Florida, Alabama, Mississippi, Louisiana
EHW		Eastern non-oak hardwood species grown naturally or commercially, including sweetgum (Liquidambar styraciflua), yellow-poplar (Liriodendron tulipifera), and red maple (Acer rubrum)
Oak		Oak species (Quercus spp.) including white oak (Q. alba), northern red oak (Q. rubra), southern red oak (Q. falcata), and post oak (Q. stellata)
Pine	South-Central	Pine species including shortleaf pine (Pinus echinata), loblolly pine (P. taeda), and pitch pine (P. rigida)	Kentucky, Tennessee, Arkansas, Oklahoma
EHW		Eastern non-oak hardwood species including tulip tree (Liriodendron tulipifera), sweetgum (Liquidambar styraciflua), and black walnut (Juglans nigra)
Oak		Oak species including white oak (Quercus alba), black oak (Q. velutina), and chestnut oak (Q. prinus)
SF	Northeast	Spruce-fir forest types including red spruce (Picea rubens), balsam fir (Abies balsamea), and eastern hemlock (Tsuga canadensis)	Maine, New Hampshire, Vermont, Massachusetts, Rhode Island, Connecticut, New York, Pennsylvania
Pine		Northern pine species including eastern white pine (Pinus strobus), red pine (P. resinosa), and jack pine (P. banksiana)
EHW		Eastern hardwood species including sugar maple (Acer saccharum), American beech (Fagus grandifolia), and yellow birch (Betula alleghaniensis)
Oak		Oak species including northern red oak (Quercus rubra), white oak (Q. alba), and chestnut oak (Q. prinus)
SF	North-Central	Spruce-fir complexes including white spruce (Picea glauca), balsam fir (Abies balsamea), and northern white-cedar (Thuja occidentalis)	Minnesota, Wisconsin, Michigan, Iowa, Missouri, Illinois, Indiana, Ohio
Pine		Northern pine species including red pine (Pinus resinosa), jack pine (P. banksiana), and eastern white pine (P. strobus)
EHW		Hardwood species including sugar maple (Acer saccharum), American basswood (Tilia americana), and northern red oak (Quercus rubra)
Oak		Oak species including bur oak (Quercus macrocarpa), white oak (Q. alba), and northern red oak (Q. rubra)
DF	West	Douglas-fir (Pseudotsuga menziesii) and associated coniferous species including western hemlock (Tsuga heterophylla) and grand fir (Abies grandis)	California, Oregon, Washington
Pine		Western pine species including ponderosa pine (Pinus ponderosa), sugar pine (P. lambertiana), and lodgepole pine (P. contorta)
HW		Western hardwood species including red alder (Alnus rubra), bigleaf maple (Acer macrophyllum), and Oregon white oak (Quercus garryana)
SW		Softwood species other than Douglas-fir and pine, including western redcedar (Thuja plicata), western hemlock (Tsuga heterophylla), and true fir species (Abies spp.)
HW	Southwest	Southwestern hardwood species including Fremont cottonwood (Populus fremontii), Arizona sycamore (Platanus wrightii), and Gambel oak (Quercus gambelii)	Texas, New Mexico, Arizona
DF	Southwest	Douglas-fir (Pseudotsuga menziesii) adapted to southwestern growing conditions	Texas, New Mexico, Arizona
Pine	Mountain	Mountain pine species including ponderosa pine (Pinus ponderosa), lodgepole pine (P. contorta), and limber pine (P. flexilis)	Montana, Wyoming, Colorado, Idaho, Nevada, Utah
HW	Mountain	Mountain hardwood species including quaking aspen (Populus tremuloides), Rocky Mountain maple (Acer glabrum), and paper birch (Betula papyrifera)	Montana, Wyoming, Colorado, Idaho, Nevada, Utah

Table D3. Forest type and region classification table for Countries and regions excluding the United States.

Forest Type	Region	Forest Type Description	Region Description
Plantation	China	Fast-growing plantation species including eucalyptus (Eucalyptus spp.), poplar (Populus spp.), and Chinese fir (Cunninghamia lanceolata) under intensive management	All administrative regions with forest plantation development
Natural	China	Natural forest ecosystems including mixed temperate forests, boreal forests, and subtropical forests with native species composition
S. Plt.	Brazil	Short-rotation plantation forestry focused on eucalyptus (Eucalyptus spp.) and pine (Pinus spp.) for industrial wood production	All states with plantation forestry operations
Trop. Evergreen		Tropical evergreen rainforest including Amazon rainforest with diverse hardwood species	Primarily Amazon Basin states
Trop. Mixed		Tropical mixed forests including Atlantic Forest remnants and Cerrado formations	Atlantic coast regions and central Cerrado
Atlantic/MW HW	Canada	Atlantic and Maritime hardwood forests including sugar maple (Acer saccharum), yellow birch (Betula alleghaniensis), and American beech (Fagus grandifolia)	Atlantic Maritime provinces
Atlantic/MW SW		Atlantic and Maritime softwood forests dominated by red spruce (Picea rubens), balsam fir (Abies balsamea), and eastern hemlock (Tsuga canadensis)
Atlantic/MW Mx		Atlantic and Maritime mixed forests combining hardwood and softwood species
Boreal/Hudson HW		Boreal hardwood forests including paper birch (Betula papyrifera), trembling aspen (Populus tremuloides), and balsam poplar (P. balsamifera)	Hudson Bay lowlands region
Boreal/Hudson SW		Boreal softwood forests including black spruce (Picea mariana), white spruce (P. glauca), and jack pine (Pinus banksiana)
Boreal/Hudson MX		Boreal mixed forests combining deciduous and coniferous species in the Hudson Bay region
Taiga HW		Northern taiga hardwood species including paper birch (Betula papyrifera) and trembling aspen (Populus tremuloides)	Northern territories and provinces
Taiga SW		Taiga softwood forests dominated by black spruce (Picea mariana) and tamarack (Larix laricina)
Taiga Mx		Taiga mixed forests combining hardwood and softwood species in extreme northern climates
Boreal West HW		Western boreal hardwood forests including trembling aspen (Populus tremuloides), balsam poplar (P. balsamifera), and paper birch (Betula papyrifera)	Western boreal regions
Boreal West SW		Western boreal softwood forests including white spruce (Picea glauca), black spruce (P. mariana), and lodgepole pine (Pinus contorta)
Boreal West MX		Western boreal mixed forests representing transitions between hardwood and softwood stands
Boreal Montane HW		Montane boreal hardwood forests including trembling aspen (Populus tremuloides) and paper birch (Betula papyrifera)	Rocky Mountain and cordilleran regions
Boreal Montane SW		Montane boreal softwood forests including subalpine fir (Abies lasiocarpa), Engelmann spruce (Picea engelmannii), and lodgepole pine (Pinus contorta)
Boreal Montane Mx		Mixed montane boreal forests combining elevation-adapted hardwood and softwood species
Pacific HW		Pacific coast hardwood forests including red alder (Alnus rubra) and bigleaf maple (Acer macrophyllum)	British Columbia coastal regions
Pacific SW		Pacific coast softwood forests dominated by western hemlock (Tsuga heterophylla), western redcedar (Thuja plicata), and Douglas-fir (Pseudotsuga menziesii)
Pacific Mx		Pacific coast mixed forests combining coastal hardwood and softwood species
Conifer	Russia	Russian coniferous forests including Siberian pine (Pinus sibirica), Siberian spruce (Picea obovata), and Siberian fir (Abies sibirica)	Siberian and Far East regions
Temp HW		Temperate hardwood forests including birch (Betula spp.), aspen (Populus spp.), and oak species (Quercus spp.)	European Russia and southern regions
Bor HW		Boreal hardwood forests dominated by birch (Betula spp.) and aspen (Populus spp.)	Northern boreal zone
HW		General hardwood forest classification for mixed deciduous species	Various regions with hardwood forest presence
Nord. Plt.	European Union	Nordic plantation forestry including Norway spruce (Picea abies), Scots pine (Pinus sylvestris), and managed species	Scandinavia and northern European countries
Ce.S. Plt.		Central European softwood plantations including Norway spruce (Picea abies) and silver fir (Abies alba)	Germany, Austria, Czech Republic, and surrounding regions
Ce.H.Plt.		Central European hardwood plantations including European beech (Fagus sylvatica) and oak species (Quercus spp.)	Germany, Austria, Czech Republic, and surrounding regions
So.S.Plt.		Southern European softwood plantations including maritime pine (Pinus pinaster) and stone pine (P. pinea)	Mediterranean countries
So.H.Plt.		Southern European hardwood plantations including cork oak (Quercus suber), holm oak (Q. ilex), and eucalyptus (Eucalyptus spp.)	Mediterranean countries
E. SW		Eastern European softwood forests including Norway spruce (Picea abies) and Scots pine (Pinus sylvestris)	Eastern European member states
E. HW		Eastern European hardwood forests including European beech (Fagus sylvatica), oak species (Quercus spp.), and hornbeam (Carpinus betulus)	Eastern European member states
Temp HW	Europe (Non-EU)	Temperate hardwood forests in non-EU European countries including beech (Fagus spp.) and oak (Quercus spp.)	Non-EU European countries including Switzerland, Norway, and Balkans
Temp SW		Temperate softwood forests including Norway spruce (Picea abies) and Scots pine (Pinus sylvestris)
Temperate Mixed		Mixed temperate forests combining hardwood and softwood species
LR PLT	South Asia	Large-rotation plantation forestry including teak (Tectona grandis) and sal (Shorea robusta)	India, Pakistan, Bangladesh, and surrounding countries
Tropical	South Asia	Tropical forests including monsoon forests, dry deciduous forests, and wet evergreen forests	India, Pakistan, Bangladesh, and surrounding countries
S PLT	Central America	Small-scale plantation forestry including coffee shade trees and mahogany (Swietenia spp.)	Mexico, Guatemala, Belize, Honduras, El Salvador, Nicaragua, Costa Rica, Panama
TMP EVER		Temperate evergreen forests including cloud forests and pine-oak forests
TMP MX		Temperate mixed forests combining coniferous and deciduous species
TMP DC		Temperate deciduous forests including oak forests and mixed deciduous formations
S PLT	Rest of South America	Short-rotation plantation forestry including eucalyptus (Eucalyptus spp.) and pine (Pinus spp.)	Countries other than Brazil
TR EVER		Tropical evergreen rainforests including Amazon basin forests
TR MIX		Tropical mixed forests including seasonal dry forests and forest-savanna mosaics
TEMP MX		Temperate mixed forests including Valdivian rainforest and Andean mixed forests
S PLT	Sub-Saharan Africa	Short-rotation plantation forestry including eucalyptus (Eucalyptus spp.) and wattle (Acacia spp.)	African countries south of the Sahara Desert
TR EV		Tropical evergreen forests including Congo Basin rainforests and East African montane forests
TR MIX		Tropical mixed forests including miombo woodlands and moist forests
Dipt	Southeast Asia	Dipterocarp forests dominated by Dipterocarpaceae family species characteristic of Southeast Asian rainforests	Indonesia, Malaysia, Thailand, Philippines, Vietnam, and surrounding countries
Trop. Dry		Tropical dry forests including monsoon forests and deciduous forests
Trop. Moist		Tropical moist forests including lowland rainforests and wet evergreen formations
S. Plt.		Short-rotation plantation forestry including oil palm (Elaeis guineensis), rubber (Hevea brasiliensis), and timber species
Temp	Oceania	Temperate forests including sclerophyll forests and wet temperate rainforests	Australia, New Zealand, and Pacific Islands
Trop. Dry		Tropical dry forests and woodlands adapted to seasonal rainfall
Trop. Moist		Tropical moist forests including wet tropical rainforests
S. Plt.		Short-rotation plantation forestry including eucalyptus (Eucalyptus spp.) and pine (Pinus spp.)
Temperate	Japan	Temperate forests including deciduous broad-leaved forests and mixed forests	All prefectures
S PLT	Japan	Short-rotation plantation forestry including Japanese cedar (Cryptomeria japonica) and other managed species	All prefectures
TR EVER	Africa and Middle East	Tropical evergreen forests in limited areas with suitable tropical climate	Limited tropical forest areas
TR MIX	Africa and Middle East	Tropical mixed forests and woodlands including dry forests and savanna-forest transitions	Various countries in Africa and Middle East

16.0

Appendix E: Derivation of Counterfactual Wood Pool Factor

16.1

Appendix E.1: Deriving Long Term Mean of Harvested Pools

For a total standing AGB mass of $K$ at the pre-harvest, we can consider how it is broken up into $n$ pools (e.g., harvest residue, milling residue, product 1, product 2, etc.). As such, the remaining amount at any given time point of a single harvest can be described as the sum of what is remaining in all the individual pools:

 $H_s(t) = \sum_{i=1}^{n} H_{s,i}(t)$

(Equation E1)

Where:

$H_{s,i}(t)$ is the remaining carbon in product i at time t from a single harvest event

$H_{s,i}(t)$ can be described by:

 $H_{s,i}(t) = f_i K e^{-\lambda_i t}$

(Equation E2)

Where:

$f_i$ is fraction of harvest to product/pool $i$
$\lambda_i$ is the decay rate of product $i$ , in years^-1

The decay rate is defined exponentially as:

 $\lambda_i = \frac{\ln 2}{t_{1/2, i}}$

(Equation E3)

Where:

$t_{1/2, i}$ is the half life of product $i$ , in years

For longer-lived pools, we also need to consider potential remaining biomass from prior harvests; e.g.

 $H_i(t) = f_i K e^{-\lambda_i t} + f_i K e^{-\lambda_i(t+T)} + f_i K e^{-\lambda_i(t+2T)} + \dots = f_i K e^{-\lambda_i t} \sum_{n=0}^{\infty} e^{-\lambda_i n T}$

(Equation E4)

Where:

$T$ is the harvest cycle length, in years

The summation term is a geometric series and thus the equation can be simplified as:

 $H_i(t) = f_i K e^{-\lambda_i t} \left( \frac{1}{1 - e^{-\lambda_i T}} \right) = \frac{f_i K e^{-\lambda_i t}}{1 - e^{-\lambda_i T}}$

(Equation E5)

To find the temporal mean over a single rotation cycle, we can integrate and divide by the length, $T$ :

 $\bar{H}_i = \frac{1}{T} \int_{0}^{T} H_i(t) dt$

(Equation E6)

Substituting in the expression for $H_i(t)$ :

 $\bar{H}_i = \frac{f_i K}{T(1 - e^{-\lambda_i T})} \int_{0}^{T} e^{-\lambda_i t} dt$

(Equation E7)

Integrating:

 $\bar{H}_i = \frac{f_i K}{T(1 - e^{-\lambda_i T})} \cdot \left( \frac{1}{\lambda_i} (1 - e^{-\lambda_i T}) \right)$

(Equation E8)

And simplifying yields:

 $\bar{H}_i = \frac{f_i K}{T \lambda_i}$

(Equation E9)

For multiple pools, the total harvest product mean would then be the sum of all the individual pools for harvested wood:

 $\bar{H} = \sum_{i=1}^{n} \frac{f_i K}{T \lambda_i} = \frac{K}{T} \left( \frac{f_1}{\lambda_1} + \frac{f_2}{\lambda_2} + \dots \right)$

(Equation E10)

16.2

Appendix E.2: Deriving Long Term Mean of Standing Counterfactual in Equivalent Terms

From here we want to define the mean standing stock $\bar{B}$ in the counterfactual, which will be measured as part of the dynamic baseline, in terms of the same variables so that we can express $\bar{H}$ relative to $\bar{B}$

We can define the harvest amount ( $K$ ), inclusive of all residues, in terms of the standing biomass as:

 $K = B_{\max} - B_{\min}$

(Equation E11)

Where:

$B_{\max}$ & $B_{\min}$ are pre- and post- harvest standing biomass, respectively

The mean forest biomass is then:

 $\bar{B} = \frac{1}{T} \int_{0}^{T} B(t) dt$

(Equation E12)

After a harvest, we can define $B(t)$ as:

 $B(t) = \underbrace{B_{\min}}_{\text{starting point}} + \underbrace{B(t) - B_{\min}}_{\text{regrowth}}$

(Equation E13)

Where:

$t$ is the time since last harvest, in years

We can normalize the regrowth portion of the equation to be relative to the harvest amount ( $K$ ):

 $g(t) = \frac{B(t) - B_{\min}}{K}$

(Equation E14)

Where:

$g(t)$ is the fractional regrowth of the harvest amount at time $t$ ; This value ranges from 0 to 1
- For example, when $t=T$ , $g(t) = (B_{max}-B_{min})/k = 1$

We can rearrange Equation E14 to be:

 $B(t) = B_{\min} + K g(t)$

(Equation E15)

Substituting this back into the integral mean expression for $\bar{B}$ (Equation E12) we get:

 $\bar{B} = \frac{1}{T} \int_{0}^{T} (B_{\min} + K g(t)) dt$

(Equation E16)

Integrating yields:

 $\bar{B}= \frac{1}{T} \int_{0}^{T} B_{\min} dt + \frac{1}{T} \int_{0}^{T} K g(t) dt = B_{\min} + \underbrace{\frac{K}{T}\int_{0}^{T} g(t) dt}_{\substack{\text{Time averaged} \text{normalized regrowth, } \bar{g}}}$

(Equation E17)

The final integral term over $T$ is equivalent to the time average normalized regrowth ( $\bar{g}$ ), such that:

 $\bar{B} = B_{\min} + K \bar{g}$

(Equation E18)

We can then substitute $B_{\min} = B_{\max} - K$ (from Equation B11) to get:

 $\bar{B} = B_{\max} - K + K \bar{g} = B_{\max} - K(1 - \bar{g})$

(Equation E19)

We can then define $\gamma = B_{\max}/K$ which describes the harvest intensity and rewrite the Equation E19 as:

 $\bar{B} = \gamma K - K(1 - \bar{g})$

(Equation E20)

We can now define $\beta = 1-\bar{g}$ , which describes the temporal asymmetry in regrowth.

For symmetric regrowth, $\beta$ is approximately 0.5 since $\bar{B}$ will be exactly between $B_{min}$ and $B_{max}$
For fast then slow regrowth, $\beta$ approaches 0 since $\bar{B}$ will be closer to $B_{max}$
For slow then fast regrowth, $\beta$ approaches 1 since $\bar{B}$ will be closer to $B_{min}$

We can substitute in this term for $\beta$ into the derivation of $\bar{B}$ :

 $\bar{B} = \gamma K - \beta K = K(\gamma - \beta)$

(Equation E21)

16.3

Appendix E.3: Combining Derivations to Express Harvested Pools Relative to Standing Pool Mean

We can then define the ratio of the full counterfactual (standing + harvested pools) relative to the standing mean only by combining Equations E10 and E21:

 $\frac{\bar{B} + \bar{H}}{\bar{B}} = \frac{K(\gamma - \beta) + \frac{K}{T} \sum_{i=1}^{n} \frac{f_i}{\lambda_i}}{K(\gamma - \beta)} = 1 + \frac{\frac{K}{T} \sum_{i=1}^{n} \frac{f_i}{\lambda_i}}{K(\gamma - \beta)}= 1 + \frac{\frac{1}{T} \sum_{i=1}^{n} \frac{f_i}{\lambda_i}}{(\gamma - \beta)}$

(Equation E22)

This term is equal to $f_{HWP}$ , and acts as a correction factor that can be used as a multiplier of the time averaged standing counterfactual stock which comes from the dynamic baseline ( $C_{DB,counterfactual}$ ) to yield the full counterfactual (C_{counterfactual}) which includes both the standing stock and the harvested pools:

 $C_{\text{counterfactual}} = \left( 1 + \frac{\frac{1}{T} \sum_{i=1}^{n} \frac{f_i}{\lambda_i}}{(\gamma - \beta)} \right) C_{DB,\text{counterfactual}}$

(Equation E23)

For example, if $f_{HWP}$ was equal to 1.2, this means that adding in the harvested pools raises the standing-only baseline by 20%. As such, we implement this method by measuring $C_{DB,counterfactual}$ from the dynamic baseline, and then calculating the project-specific $f_{HWP}$ to add in the harvested pools.

17.0

Relevant Works

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Contributors

Jeannie Wilkening, Ph.D.

Ryan Huang, Ph.D.

Christopher Kilner, Ph.D.

Chris Pollard

Michael Shell

Isometric

Contents

Introduction

Sources and Reference Standards and Methodologies

Future Versions

Applicability

Viability of the Project and Determination of the Project Area

Land Enrollment and Determination of the Project Area

Integrity of Enrolled Land

Ecological and Operational Feasibility of Harvest

Soil Drainage Limits

Operability Exception

Proximity to Water Bodies

Geographical Constraints

Proximity to Dwellings and Other Structures

Merchantibility to Markets

Economic Viability Analysis

Market Capacity Assessment

Harvest Consistency

Intent to Protect

Other Requirements

Project Timelines

Project Commitment Period

Crediting Period

Reporting Period

Ongoing Monitoring Period

Example Project Timeline

Environmental and Social Safeguarding

Forest Management Activities

Stand Improvement Activities

Pre-Existing Forest Management Plan

Safeguarding of Communities

Stakeholder Engagement

Community Impacts and Well-Being

Relation to Isometric Standard

Additionality

Intent of Harvest

System Boundary, Project Baseline and Leakage

Leakage

Scientific Justification for a Unified Modeling Framework

Prohibition on Shifting Activities

Global Timber Model Implementation

Regional Leakage Rate Calculation

Project Leakage Calculation

Alternative Leakage Deduction

Alternative Supply-Chain Leakage Assessment

Conservative Leakage Assumptions

Data Requirements

Application Eligibility

Updates to Alternative Leakage Deduction

Activity-Shifting Requirements

Quantification

Calculation of CO2estored

Calculation of MAGB

Calculation of MAGB Through Growth-Disturbance Models

Growth-Disturbance Model Approval

Growth Model

Disturbance Model

Carbon Stock Acquisition

Calculation of Baseline, CO2ecounterfactual

Determination of Zone of Eligibility for Control Pixels

Time for Space Substitution

Generation of Forest Carbon Map

Matching of Project and Control Pixels

Evaluation of Dynamic Baseline Deduction

Parameters for Counterfactual Wood Products Assessment

Evaluation of Dynamic Baseline Uncertainty

Counterfactual Determination in Settings With Limited Donor Zone

Applicability

Construction of the Modeled Baseline

Modeled Baseline Output and Counterfactual Calculation

Dynamic Evaluation of the Modeled Baseline

Reporting

Verification

Uncertainty Assessment of the Modeled Baseline

Calculation of CO2eemissions,RP

Model Validation Requirements

Storage and Durability of CO2e Removals

Durability

Ongoing Monitoring Period for Reversals

Definitions and Acronyms

Calculation of CO₂e_stored

Calculation of M_AGB

Calculation of M_AGB Through Growth-Disturbance Models

Calculation of Baseline, CO₂e_{counterfactual}

Calculation of CO₂e_emissions,RP

Storage and Durability of CO₂e Removals