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Reforestation
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This Protocol (A 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.) provides the requirements and procedures for the calculation of net carbon dioxide equivalent (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.)) removal (The term used to represent the CO₂ taken out of the atmosphere as a result of a CDR process.) from the atmosphere via reforestation. Reforestation refers to activities (An activity or process or group of activities or processes that alter the condition of a Baseline and leads to Removals or Reductions.) that lead to an increase in forest cover on land that was previously covered by forest, restoring the native forest ecosystem1.
Earth’s forests store approximately 861 gigatonnes of carbon2. Forests can act as a source or sink of carbon, and are estimated to absorb a net 7.6 gigatonnes of CO2 per year3 by converting atmospheric CO2 into biomass through photosynthesis. Carbon is also steadily released from forest biomass through respiration and oxidation, or as a result of disturbances such as timber harvesting, fires, and deforestation.
Reforestation activities include planting tree seedlings, facilitating natural regeneration, and ongoing management of the forest to maximize and preserve the carbon removed from the atmosphere that is stored in tree biomass. Restoration of forested lands globally could represent an additional storage (Describes 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”.) of 200 gigatonnes of carbon at forest maturity4, making it a useful tool in reaching the projected IPCC Carbon Dioxide Removal (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.) (CDR) storage needs of the mid-century. In addition to carbon sequestration potential, reforestation has several co-benefits such as restoration of forest habitat, creation of wildlife corridors, and enhancement of biodiversity (The 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.) on previously degraded lands.
This Protocol accounts for the quantification of the gross amount of CO2 removed via growth and regeneration of forest vegetation, as well as all cradle-to-grave (Considering 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.) life-cycle 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).) emissions associated with the process. This Protocol is developed to adhere to the requirements of ISO (A worldwide federation (NGO) of national standards bodies from more than 160 countries, one from each member country.) 14064-2: 2019 – Greenhouse Gasses – Part 2: Specification with guidance at the Project (An activity or process or group of activities or processes that alter the condition of a Baseline and leads to Removals or Reductions.) level for quantification, monitoring, and reporting of greenhouse gas emission reductions (Lowering future GHG releases from a specific entity.) or removal enhancements.
The Protocol ensures:
Throughout this Protocol, the use of “must” indicates a requirement, whereas “should” indicates a recommendation.
This Protocol relies on and is intended to be compliant with the following standards and protocols:
Additional reference standards that inform the requirements and overall practices incorporated in this Protocol include:
Additional principles that were considered in the development of this Protocol and aligned with, where feasible, include:
Protocols and Methodologies that were assessed as part of a literature review during the development of this Protocol include:
This Protocol was developed based on the current state of the art, publicly available science regarding reforestation activities and long-term monitoring of forest carbon projects. This Protocol 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 Protocol. Key future improvements to the Protocol are outlined in Appendix E.
Additionally, this Protocol will be reviewed when there is an update to published scientific literature which would affect net CO₂e removal quantification or the monitoring guidelines outlined in this Protocol, or at a minimum of every 2 years.
This Protocol aims to guide Projects that restore inland forests to a state of ecological integrity (The 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.)5 in areas where they have historically existed and are resilient to future climate scenarios. Projects should emphasize protection and restoration of ecosystem function (The 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.), biodiversity, and social livelihoods. Projects should not resemble commercial forestry, and the fate of forests restored in accordance with this Protocol must not be clear-cutting for timber sale, even beyond the Monitoring Period.
Land cover data sources derived from remote sensing and used for land cover classifcationclassification in Section 4.1 should meet the following criteria:
Additionally, this Protocol applies to projects and associated operations that meet all of the following project conditions:
[Image: **Figure 1** Project timelines]
Figure 1 Summary of project periods. Colors represent actions owned by different stakeholders (Any person or entity who can potentially affect or be affected by Isometric or an individual Project activity.). Blue = Project Proponent. Green = VVB. Pink = Isometric.
A project starting in 2025 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) (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.) 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.
The Project must consider environmental and social impacts at all project locations. Appropriate measures must be implemented to identify and eliminate potential risks to terrestrial and aquatic ecosystems and biodiversity. Where risks cannot be eliminated, the Project Proponent must identify measures to monitor ecosystem health and mitigate adverse effects through a site-specific mitigation plan. Mitigation plans must be prepared by subject matter experts, in consultation with Isometric, the VVB, and relevant local authorities, if applicable. Refer to Section 3.7 of the Isometric Standard for further guidelines on environmental and social impacts.
Following the Isometric Standard, Credits issued under this Protocol are contingent on the implementation, transparent reporting, and independent Verification of comprehensive safeguards. These safeguards encompass a wide range of considerations, including environmental protection, social equity, community engagement, and respect for cultural values. The process mandates that safeguard plans be incorporated into all major project phases, with detailed reports made accessible to stakeholders. Adherence to and verification of environmental and social safeguards is a condition for all Crediting Projects.
An environmental and social risk assessment in adherence with Section 3.7 of the Isometric Standard must be completed to identify potential risks, followed by the development of tailored mitigation plans. These plans must encompass specific actions to avoid, minimize or rectify identified impacts. Effective implementation of these measures must also be accompanied by a robust monitoring plan to detect adverse effects and pause project activities if necessary, using the principles of adaptive management described below.
Environmental and social risk identification, assessment, avoidance, and mitigation planning will be unique to the technical, environmental, and social contexts of The Project. To accommodate this variation, the requirements outlined in this section serve as a minimum to which the Project Proponent and Isometric can add risks on a case by case basis, to be included in the PDD, if applicable.
Project Proponents must comply with all national and local laws, regulations and policies, and receive any necessary permits for project activities, if applicable. Where relevant, projects must comply with international conventions and standards governing human rights and uses of the environment.
Project Proponents must document activities that trigger environmental permitting requirements.
Adaptive management incorporates learnings and takeaways from project monitoring into project development11. Regular data collection and sharing is necessary to implement adaptive management. Results from data collection at the end of each Reporting Period must be shared with local stakeholders, as described in Section 6.5.1 of this Protocol, and be used to inform future iterations of project management and development.
Project Proponents are required to predict and plan for potential unintended outcomes of project activities and construct mitigation plans for such instances. Foreseeable risks identified during the preparation of the environmental and social risk assessment must be included in the PDD and the following must be detailed for each potential risk:
The Project should not hinder the ability of the community or local ecosystem to adapt to climate change as a result of the 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.) activity.
The High Conservation Values (HCV) Approach, developed by the HCV Network, identifies regionally specific facets of local communities and ecologies that must be considered during project developments resulting in land use change. The HCV Network has identified six values that may be at risk as a result of land use change projects. The values, along with corresponding requirements for Project Proponents to uphold them, are listed below:
For each value above, the Project Proponent must identify in the PDD if the value is present or absent in the project area. This list must be constructed in consultation with relevant stakeholder groups, as identified in Section 6.5.1 and carried out in accordance with Section 3.5 of the Isometric Standard . The Stakeholder Engagement Plan for HCV identification must also be included in the PDD.
If a value is absent from the project area, the Project Proponent must provide an explanation or justification such as survey results or recent publications. If a value is present in the project area, the Project Proponent must include a plan to monitor and protect it throughout the Project Commitment Period in the PDD. We encourage Project Proponents to review the Common Guidance for the Management and Monitoring of HCV in developing this plan. If protection is not feasible during the project activities and an HCV is damaged as a result of project activities, the Project Proponent must provide a restoration plan to return the area to its prior condition and quality.
If an HCV is threatened or damaged by forces or parties outside of the Project Proponent’s jurisdiction and not as a result of or response to project activities, the Project Proponent must report such instances to Isometric, but may not be responsible for enacting a restoration plan. Failure to properly identify, monitor, and protect an HCV may result in the cessation of Credits.
The Project Proponent must provide due diligence to ensure that the population density of rare, threatened, and endangered species in the project area does not decrease, nor are new species added to this list, as a result of project activities. If either of these adverse impacts do occur, the Project Proponent must work with Isometric and the VVB to identify sources and explanations for these impacts in order to rule out project activities as the primary cause.
It is recommended that Project Proponents strive to increase the population of rare, threatened, and endangered species. Endangered species are defined as species under threat of extinction from all or a significant amount of their natural habitat. Threatened species are defined as those that are at risk of becoming endangered. Rare species are defined as those uncommon and found in isolated geographical locations. Project Proponents must consult local authorities for further regulations on these or similar groups. If local regulations exist, the Project Proponent must state them in the PDD.
The Project Proponent must consult reputable (A source that would be widely considered trustworthy based on the process undertaken (e.g., peer review) or origin of the information (e.g., government body).) and current sources on rare, threatened, and endangered species to develop a list of these species, in the following order of priority:
The results of the rare, threatened, and endangered species list review must be included and referenced in the PDD.
For each rare, threatened, or endangered species identified, the Project Proponent must list the following in the PDD:
The Project Proponent must handle data and information related to rare, threatened, and endangered species with discretion for the protection of these species, especially regarding species and/or regions that have histories of poaching, over-harvesting, or other elevated threats to population density and livelihoods.
As stated in Section 4.1, reforestation projects must occur on degraded land to be eligible for crediting under this Protocol. Because of this applicability requirement and the nature of reforestation projects to plant and maintain species in the project area, reforestation projects are well placed to increase biodiversity in the region. To benchmark increased biodiversity, Project Proponents must include more than five species from two or more genera in their planting plan and should prioritize the planting of endemic, rare, threatened, and endangered native species. Species should be planted at ecologically appropriate richness and evenness15. There may be some regions that naturally support a limited number of species that fulfill ecosystem services and other functions or indicators of healthy ecosystems. Project Proponents in these regions may deviate from the minimum required species and genera included in planting plans, in consultation with Isometric. Such deviations must be accompanied by appropriate documentation, based in scientific literature and/or ongoing field studies, in the PDD.
The tree species used for reforestation must follow the principles outlined below.
The Project Proponent must list the species planted and/or maintained in the project area via project activities in the PDD. These species may include native, naturalized, or non-native range-expanding species. Project Proponents must not introduce species invasive (A species whose introduction, spread, and/or growth threatens biological diversity.) to the region or similar climates, geographies, or ecosystems of the project area16, 17. The definition of 'invasive species' in this Protocol is consistent with the Convention on Biological Diversity's definition of Invasive Alien Species, being a "species whose introduction and/or spread threaten([s)] biological diversity"18. Projects that plant invasive species will not be eligible for crediting under this Protocol. Additionally, Project Proponents must not introduce any species that harm rare, threatened, or endangered species as defined in Section 6.3.1 or adversely impact the integrity of rare, threatened, or endangered ecosystems and habitats (see Section 6.3). Project Proponents are highly encouraged to consult with Isometric, the VVB, and/or external subject matter experts to ensure that species included in the reforestation plan meet these requirements and the criteria described below.
For the purposes of this Protocol, native species are defined as:
Naturalized species are defined as:
Reforestation with native species should be the first course of action. If reforestation with only native and naturalized species is not feasible, non-native range-expanding species may be included in the reforestation planting plan. Any non-native species not considered range-expanding for the purposes of this Protocol must not be planted. Non-native range-expanding species are defined as:
In such instances, the majority of species planted must be native and/or naturalized, and the plurality must be native species. Additionally, the following due diligence must be taken when planting non-native range-expanding species for a project to be eligible for crediting. The Project Proponent must demonstrate:
Alternative burdens of proof may be sufficient, in consultation with Isometric.
The following due diligence must be conducted and included in the PDD if non-native range-expanding species are to be planted during project activities. The Project Proponent must demonstrate:
A robust seedling and germplasm pipeline is central to the ecological, socioeconomic, and cultural success of a reforestation project. A diverse, local, and sustainable pipeline ensures that project activities contribute to the restoration of ecosystem function and integrity, restore and protect biodiversity, safeguard community livelihoods, and uphold cultural values.
Project Proponents must procure and maintain their seedling and germplasm pipeline in alignment with the environmental and social safeguards outlined in Section 6 of this Protocol and Section 3.7 of the Isometric Standard.
The pipeline must be described in the PDD and the Project Proponent should:
In accordance with Section 3.5 of the Isometric Standard, Project Proponents must demonstrate active stakeholder engagement throughout project planning and operation, ensuring that all risk mitigation strategies contribute to sustainable project outcomes. Local stakeholders may contribute an in-depth understanding of the project area and operations, and provide invaluable insights and recommendations on potential risks, necessary safeguards and specific monitoring needs. Engaging local stakeholders in reforestation projects creates community buy-in, providing long term commitment and investment in the success of reforestation projects19, 11. Furthermore, lack of community support, stakeholder engagement, and perceived community benefits has been identified as a primary source of project failure in previous forestry projects20.
The Project Proponent must develop a Stakeholder Engagement Plan in accordance with the requirements outlined in Section 3.5 of the Isometric Standard. The plan and supporting documentation, including evidence of meetings or other forms of engagement, must be submitted in the PDD.
Prior to the commencement of project activities, Project Proponents are required to assess if Indigenous Peoples will be impacted by project activities, in consultation with Isometric. Impacts may include, but are not limited to:
Project Proponents must consult a reputable third party or subject matter expert to assess if Indigenous Peoples will be impacted by project activities. The results of this report must be included in the PDD. If the report identifies potential impacts to Indigenous Peoples, the Project Proponent must enact a Stakeholder Engagement Plan consistent with the principles of Free, Prior, and Informed Consent (FPIC) as outlined by the United Nations (UN) Declaration on the Rights of Indigenous Peoples21 in 2007 and expanded upon by the Food and Agriculture Organization of the United Nations in 201622.
The Project Proponent is encouraged to prepare alternatives for the withdrawal or denial of consent to project activities by stakeholder groups.
If required, the stakeholder engagement process must be enacted early in the project development process, prior to the initiation of project activities. The stakeholder engagement schedule must be circulated prior to project initiation, and with enough notice to engage stakeholders in the planning processes. In some instances, Project Proponents that initiated project activities prior to engaging with Isometric and did not engage Indigenous Peoples stakeholders under the principles of FPIC may still be eligible for crediting under this Protocol, in consultation with Isometric, by demonstrating how stakeholder engagement will be incorporated into future project planning.
The following may serve as a burden(s)burdens of proof that the Stakeholder Input Process conforms with the principles of FPIC. The Project Proponent must indicate how these steps in the stakeholder engagement process were or will be carried out during the project lifetime. Multiple rounds of stakeholder engagement may take place during a project lifetime, as needed. The Project Proponent may identify other burdens of proof demonstrating that the principles of FPIC have been observed and submit them in the PDD in addition to, or instead of, those below, in consultation with Isometric.
The VVB may conduct random surveys or interviews with stakeholder groups, and/or witness some or all of the processes described above.
Project Proponents that do not identify Indigenous Peoples that will be affected by project activities are encouraged to consider if other relevant stakeholders rely on land or resources located within the project area, and engage them following the principles of FPIC described above. All stakeholder groups and local communities have valuable and unique perspectives on developments in the project area, which can contribute to project success.
The following information from the stakeholder engagement process must be made publicly available, with personal information anonymized or redacted to protect stakeholders, project personnel, and project outcomes. This may include:
The Project Proponent must identify and develop processes for the protection and promotion of community well-being in the PDD, as follows:
As previously mentioned, community buy-in is critical to the success of a reforestation project 19, 11, 20. Community buy-in may be established when stakeholders are properly informed about the benefits they can expect from the reforestation project. Equally important in maintaining buy-in is for the positive impacts resulting from the project to match the (perception of) potential benefits presented to community stakeholders at the project onset. A mismatch in benefits expected and benefits realized may similarly hinder project success.
While this Protocol will not prescribe requirements for community impacts, the Project Proponent is strongly encouraged to consider establishing the following programs and activities:
Positive impacts should be felt by all stakeholder groups identified in Section 6.5.21. Project Proponents should consider which groups may face the brunt of negative community impacts, and how positive community benefits may be shared equitably with these and other marginalized groups.
It is recommended that the Project Proponent provide support to the local communities and ecosystems to establish region specific mitigation strategies to adapt to changing climates.
The following topics are covered briefly in this Protocol due to their inclusion in the Isometric Standard, which governs all Isometric Protocols. See in-text references to the Isometric Standard for further guidance.
For each specific project to be evaluated under this Protocol, the Project Proponent must document project characteristics in a Project Design Document (PDD) as outlined in Section 3.2 of the Isometric Standard. The PDD will form the basis for project Validation and evaluation in accordance with this Protocol.
Projects must be validated and net CO2e removals verified by an independent third party, consistent with the requirements described in this Protocol, as well as in Section 4 of the Isometric Standard.
The Validation and Verification Body (VVB) must consider the following requisite components:
The threshold for Materiality (An acceptable difference between reported Removals/emissions or Reductions/emissions and what an auditor determines is the actual Removal/emissions or Reduction/emissions.), considering the totality of all omissions, errors and misstatements, is 5%, in accordance with Section 4.3 of the Isometric Standard.
Verifiers should also verify the documentation of uncertainty (A 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.) of the GHG Statement as required by Section 2.5.7 of the Isometric Standard. Qualitative Materiality issues may also be identified and documented, such as:
Project Validation and Verification must incorporate site visits to project facilities, namely in situ field plots, in accordance with the requirements of ISO 14064-3, 6.1.4.2. This is to include, at a minimum, site visits to the project site during Validation and initial Verification. Validators should, whenever possible, observe project operations to ensure full documentation of process inputs and outputs through visual observation (see Section 4 of the Isometric Standard).
Additional site visits may be required if there are substantial changes to field operations over the course of Validation, or if deemed necessary by Isometric or the VVB. Site visit plans are to be determined according to the VVB’s internal assessment, in consultation with Isometric.
Verifiers and Validators must comply with the requirements defined in Section 4 of the Isometric Standard. In addition, verification teams must maintain and demonstrate expertise associated with the specific technologies of reforestation and forest management, including both forest field measurements and Earth System remote sensing data processing and analysis.
CDR via reforestation is a result of a multi-step process (e.g., seed planting, forest maintenance, monitoring), with activities in each step potentially managed by a different operator, company, or owner. A single Project Proponent must be specified contractually as the sole owner of the Credits when there are multiple parties involved in the process, and to avoid Double Counting (Improperly allocating the same Removal or Reduction from a Project Proponent more than once to multiple Buyers.) of net CO₂e removals. Contracts must comply with all requirements defined in Section 3.1 of the Isometric Standard.
The Project Proponent must be able to demonstrate additionality through compliance with Section 2.5.3 of the Isometric Standard. The Baseline (A set of data describing pre-intervention or control conditions to be used as a reference scenario for comparison.) scenario and Counterfactual (An assessment of what would have happened in the absence of a particular intervention – i.e., assuming the Baseline scenario.) utilized to assess additionality must be project-specific and comply with Section 9.4 of this Protocol.
Government subsidies or civil contractual obligations for reforestation, such as organization bylaws, inhibit additionality and fall under the Regulatory criteria in Section 2.5.3 of the Isometric Standard. Environmental additionality (An evaluation of the likelihood that an intervention causes a climate benefit above and beyond what would have happened in a no-intervention Baseline scenario.) is assessed each Reporting Period using dynamic baselining as outlined in Section 9.4.
Additionality determinations should be reviewed and completed at every Verification at a minimum, or whenever project operating conditions change significantly, such as the following:
If a review indicates The Project has become non-additional, The Project will be ineligible for future Credits. Current or past Crediting Periods will not be affected.
The uncertainty in the overall estimate of the net CO2e removal as a result of The Project must be accounted for. The total net CO2e removed for a specific Reporting Period, [math: RP], [math: {CO}_{2}^{}e_{Removal, RP}^{}], must be conservatively (Purposefully 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.) determined in accordance with the requirements outlined in Section 2.5.7 of the Isometric Standard.
Projects must report a list of all key variables used in the net CO2e removal calculation and their uncertainties, as well as a description of the uncertainty analysis approach, including:
The uncertainty information should at least include the minimum and maximum values of a variable. More detailed uncertainty information should be provided if available, as outlined in Section 2.5.7 of the Isometric Standard.
In addition, a sensitivity analysis (An analysis of how much different components in a Model contribute to the overall Uncertainty.) that demonstrates the impact of each input parameter’s uncertainty on the final net CO2e uncertainty must be provided. Details of the sensitivity analysis method must be provided such that a third party can reproduce the results. Input variables may be omitted from an uncertainty analysis if they contribute to a < 1% change in the net CO2e removal. For all other parameters, information about uncertainty must be specified.
In accordance with the Isometric Standard, all evidence and data related to the underlying quantification of CO₂e removal and environmental and social safeguards monitoring will be available to the public through the Isometric platform. That includes:
The Project Proponent can request certain information to be restricted (only available to authorized Buyers (An entity that purchases Removals or Reductions, often with the purpose of Retiring Credits to make a Removal or Reduction claim.), the Registry (A database that holds information on Verified Removals and Reductions based on Protocols. Registries Issue Credits, and track their ownership and Retirement.), and VVB) where it is subject to confidentiality. This includes emission factors, specific data, and/or proprietary models from licensed databases. However, all other numerical data produced or used as part of the quantification of net CO2e removal will be made available.
The scope of this Protocol includes GHG sources (Any process or activity that releases a greenhouse gas, an aerosol, or a precursor of a greenhouse gas into the atmosphere.), sinks (Any process, activity, or mechanism that removes a greenhouse gas, a precursor to a greenhouse gas, or an aerosol from the atmosphere.) and reservoirs (A 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).) (SSRs) associated with a reforestation project. A cradle-to-grave GHG Statement must be prepared encompassing the GHG emissions relating to the activities outlined within the system boundary.
Any emissions from sub-processes or process changes that would not have taken place without The Project, and any activity that ultimately leads to the issuance of Credits, must be considered in the system boundary. This allows for accurate consideration of additional, incremental emissions induced by The Project.
The system boundary must include all SSRs controlled by, and related to, The Project, including but not limited to the SSRs in Table 1. If any GHG SSRs within Table 1 are deemed not appropriate to include in the system boundary, they may be excluded, provided that robust justification and appropriate evidence is included in the PDD. Materiality considerations for exclusions are set out in Section 8.1.1.1.
Table 1. Scope of activities and GHG SSRs to be included in the system boundary.
| Activity | GHG Source, sink or Reservoir | GHG | Scope | Timescale of emissions and accounting allocation |
|---|---|---|---|---|
| Project Establishment | Equipment and materials | All GHGs | Embodied emissions associated with equipment and materials manufacture related to project establishment (lifecycle modules A1-323). This must include product manufacture emissions for:
| Before project operations start - must be accounted for in the first Reporting Period or amortized in line with allocation rules (see Section 9.5.1) |
| Equipment and materials transport to site | All GHGs | Transport emissions associated with transporting materials, equipment and seedlings to the project site(s) (lifecycle module A423). | ||
| Planting and installation | All GHGs | Emissions related to construction and installation of the project site(s) (lifecycle module A523). This must include, as appropriate:
Emissions associated with soil disturbance are excluded as emissions are likely to be balanced by soil carbon accumulation over the project lifetime. Soil carbon is not included as part CO2 stored due to uncertainties. Projects should limit soil inversions during project establishment to < | ||
| Misc. | All GHGs | Any SSRs not captured by categories above (e.g., staff travel). | ||
| Operations | Fertilizer use (Direct) | N2O | Direct emissions (Emissions that are produced by a specific CDR process and are directly controllable.) related to the use of nitrogen-based fertilizers. | Over each Reporting Period - must be accounted for in the relevant Reporting Period (see Section 9.5.2). |
| Forest management | All GHGs | Emissions related to forest management activities (e.g., pruning, weeding, pest control, biomass burning and watering). This must include embodied emissions of equipment, as well as consumables such as water, fertilizers and pesticides. | ||
| Maintenance | All GHGs | Maintenance of the project area, including any repair or replacement of equipment, vehicles, buildings and infrastructure. | ||
Monitoring, Reporting, and Verification (MRV) (The multi-step process to monitor the Removals or Reductions and impacts of a Project, report the findings to an accredited third party, and have this third party Verify the report so that the results can be Certified.) | All GHGs | Emissions related to MRV activities (e.g., measurements, sampling, or commissioning LiDAR flights). | ||
| CO2 stored | CO2 | The gross amount of CO2 removed and durably stored in living aboveground woody biomass and belowground woody biomass (see Section 9.3). | ||
| Misc. | All GHGs | Any SSRs not captured by categories above (e.g., staff travel). | ||
End-of-Life | Ongoing Monitoring | All GHGs | Emissions relating to monitoring activities over the Project Commitment Period. | After Reporting Period - must be estimated and accounted for in the first Reporting Period or amortized in line with allocation rules (see Section 9.5.3) |
| Ongoing Forest management | All GHGs | Emissions relating to ongoing project management activities over the Project Commitment Period. | ||
| Misc. | All GHGs | Any SSRs not captured by categories above (e.g., ongoing staff travel). |
The Project Proponent must consider all GHGs associated with SSRs, in alignment with the United States Environmental Protection Agency’s definition of GHGs, which includes: carbon dioxide (CO2), methane (CH4), nitrous oxide (N2O) and fluorinated gasses such as hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF6) and nitrogen trifluoride (NF3). For CO2 stored, only CO2 will be included as part of the quantification and for Fertilizer use (Direct), only N2O shall be included as part of the quantification. For all other activities, all GHGs must be considered. For example, the release of CO2, CH4, and N2O is expected during diesel combustion.
All GHGs must be quantified and converted to CO2e in the GHG Statement using the 100-year Global Warming Potential (A measure of how much energy the emissions of 1 tonne of a GHG will absorb over a given period of time, relative to the emissions of 1 ton of CO₂.) (GWP) for the GHG of interest, based on the most recent volume of the IPCC Assessment Report (currently the Sixth Assessment Report24).
Miscellaneous GHG emissions are those that cannot be categorized by the GHG SSR categories provided in Table 1. The Project Proponent is responsible for identifying all sources of emissions directly or indirectly related to project activities and must report any outside of the SSR categories identified as miscellaneous emissions.
Emissions associated with The Project's impact on activities that fall outside of the system boundary of The Project must also be considered. This is covered under Leakage (The increase in GHG emissions outside the geographic or temporal boundary of a project that results from that project's activities.) in Section 8.3.
Some studies25, 26 have identified reforestation projects to have high removal efficiency, with lower emissions on average when compared to removal capacity, than other CDR pathways (A collection of Removal or Reduction processes that have mechanisms in common.). These studies also indicate that emissions associated with reforestation projects still make up a material fraction of net CDR for these projects. Studies27 also highlight that other existing methodologies vastly underestimate emissions associated with reforestation projects, therefore leading to a risk of over-crediting.
At the time of Protocol development, a lack of suitable benchmark data exists to exclude categories of SSRs from GHG accounting requirements. When a suitable range of appropriate project data is available, this will be revisited. In the meantime, a Materiality threshold has been set at 1% of total removals. If emissions for an SSR are expected to be < 1% of total removals, they may be excluded from the GHG systems boundary. A sensitivity analysis must be used to demonstrate that excluded GHG SSRs are likely to contribute to < 1% of total project removals. The sensitivity analysis may be based on high level information and indicative values, but the decision making and logic followed must be appropriately and transparently evidenced. All exclusions must cumulatively make up < 1% of total removals. This threshold will be revised in light of new information or literature becoming available.
Ancillary activities (such as supplementary research and development activities and corporate administrative activities) that are associated with The Project, but are not directly or indirectly related to the issuance of Credits, can be excluded from the system boundary.
Reforestation may have additional impacts on GHG emissions beyond the scope of this Protocol. For example, positive leakage may occur where reforestation practices lead to positive ecological impacts outside of the project boundary (The defined temporal and geographical boundary of a Project.). These potential secondary climate effects are not considered in this Protocol.
The Baseline scenario for reforestation assumes that the activities associated with The Project do not take place and that any infrastructure associated with The Project is not built.
The Counterfactual is the CO2 stored that would have occurred due to natural regeneration over the Crediting Period in the absence of The Project. This Protocol uses a dynamic baseline approach to quantify the Counterfactual. This is detailed in Section 9.4.4.
Leakage emissions, [math: CO_2e_{Leakage}], occur when project activities lead to emissions that occur outside the system boundary of reforestation projects. They include increases in GHG emissions as a result of reforestation projects displacing emissions or causing a secondary effect that increases emissions elsewhere. Three key types of leakage can occur for reforestation projects:
Project activities that adversely alter the water table, harming ecological integrity within the project area and surrounding landscape and watershed, are not permitted under this Protocol. Furthermore, this Protocol limits reforestation to landscapes that were historically forests. Therefore, it is unlikely that surrounding landscapes sensitive to hydrological dynamics that were not present at the time the site was historically forested would have been established since deforestation. Assessing wider ecological leakage impacts is complex. For this version of the Protocol ecological leakage is assumed to be zero. This will be revisited in future updates to the Protocol.
Activity-shifting and market leakage are addressed in this Protocol. The overall process for addressing activity-shifting and market leakage is set out in the flowchart in Figure 2.
[Image: **Figure 2** Leakage assessment flow chart]
Figure 2 Flowchart of process for addressing activity-shifting and market leakage.
The flowchart is based on the following principles:
Implementation of the flowchart in Figure 2 requires an understanding of Pre-Project Productivity, [math: PPP], including pre-project information about Direct Actors and how the commodity was used. Direct Actors are defined as site owners, tenants or other users that engaged with the project site in a way that produced commodities before the project activities commenced.
The information required is set out below:
[math: PPP] is defined as the annual productivity of a commodity type at the project site in relevant units (e.g., tonnes/ yr). This should be an average of the three years prior to the project activities starting. For crops, this should be reflective of the last three complete annual crop cycles. For livestock, this should be reflective of the maximum cattle inventory over the last three years of production. For all other commodities, this should be reflective of production over the last three years of production.
The data hierarchy for obtaining information for [math: PPP] is set out below:
The hierarchy must be followed and data choices evidenced. For example, if land registry data is used, sufficient evidence of no available farm records will be required.
As part of determination of [math: PPP], the Project Proponent must confirm the following:
The following considerations and assumptions should be made when determining the type of commodity, [math: c]:
Productivity must be reflective of an average of the three years prior to the project activities starting.
The following considerations and assumptions should be made when determining productivity:
The Project Proponent must determine the previous use of the commodity and whether it was:
The Project Proponent must determine this using the following information:
If it is not possible to determine whether the commodity was for subsistence or commercial use, then the Project Proponent must assume it was subsistence.
If The Project determines that [math: PPP] is zero, this must be evidenced appropriately. This includes:
Evidence must be provided for three years preceding the Project Proponent’s purchase of the site for reforestation, or the project start date, whichever is earlier.
In addition, Isometric will undertake remote sensing analysis on project sites which claim that [math: PPP] is zero. Remote sensing mapping will be transparently displayed on the registry. Only where remote sensing analysis indicates there are no signs of agricultural production, pasture, or timber harvesting will The Project be eligible for claiming zero [math: PPP].
[math: CO_2e_{Leakage}] is part of the calculation of [math: CO_2e_{Emissions}], as set out in Equation 21 in Section 9.5.
[math: CO_2e_{Leakage}] is quantified with the following equation:
[math: CO_2e_{Leakage}\; =\; CO_2e_{Market\; Leakage}\; +\; CO_2e_{Activity-shifting\;Leakage\:Adjustment}\; +\; CO_2e_{Leakage\; Mitigation\; Emissions}]
(Equation 1)
Where:
[math: CO_2e_{Leakage}] is quantified for every Reporting Period, however the following should be noted:
The aim of leakage mitigation activities is to reduce the amount of leakage by increasing production of the commodity elsewhere. Leakage mitigation must take place in areas called Leakage Mitigation Sites (The site(s) where leakage mitigation activities take place.). These must be separate to the project site, but may be directly adjacent.
The following equation is used to calculate the effectiveness of leakage mitigation:
[math: uPPP_c = PPP_c - MAP_c]
(Equation 2)
Where:
When [math: PPP] is 0, The Project had zero productivity.
When [math: PPP] is > 0 and [math: uPPP] is 0, The Project has achieved full leakage mitigation and does not take a market leakage emissions deduction.
When [math: PPP] is > 0 and [math: uPPP] is > 0, The Project takes a market leakage emissions deduction.
Leakage mitigation requirements are different depending on whether mitigation is to address market leakage (see Section 8.3.3.2) or activity-shifting leakage (see Section 8.3.3.1). Activity-shifting leakage will also by nature address market leakage, however market leakage alone will not address activity-shifting leakage.
In addition to the leakage type specific requirements, all leakage mitigation activities must meet the following requirements:
For mitigation of activity-shifting leakage, the Project Proponent must have a full understanding of the information set out in Section 8.3.2.1: Determining Pre-Project Productivity. The mitigation must be informed by the Direct Actors and be undertaken in agreement with Direct Actors. Mitigation activities must lead to new productivity or productivity increases that directly benefit the Direct Actors. This likely means that the increase in production should be limited to the same commodity type, but this decision should be informed by the Direct Actors. This also likely means that the Leakage Mitigation Site should be in the same locality, but again this should be informed by the Direct Actors.
The Project Proponent should engage with Direct Actors associated with the site’s prior productivity to understand how the project activity impacted the previous users of the project site. Direct Actors include the previous site owners, tenants or other users that engaged with the project site in a way that produced commodities.
The Project Proponent must receive an affidavit from the identified Direct Actors confirming the following:
Full records of correspondence, including meeting notes, and signed agreements must be made available as part of the PDD.
If information from Direct Actors is unavailable, the Project Proponent will be unable to undertake activity-shifting leakage mitigation.
For mitigation of market leakage, the following must be true in addition to the requirements set out in Section 8.3.3:
The emissions impact of leakage mitigation activities, [math: CO_2e_{Leakage\;Mitigation\;Emissions}] must be considered. The same system boundaries set out in Table 1 must be considered, noting that it is likely only certain GHG SSRs will be included. At minimum, the following emissions sources must be considered:
Only activities that are additional as a result of the leakage mitigation activity should be considered as part of [math: CO_2e_{Leakage\;Mitigation\;Emissions}]. Activities that were already occurring and would continue to occur without the leakage mitigation activity may be omitted from the emissions accounting, if evidence that the activity was already occurring and would have continued to occur in the absence of the leakage mitigation activity is provided.
[math: CO_2e_{Market\;Leakage}] considers emissions associated with land conversion as a result of market leakage. It is noted that other emissions may result from market leakage, such as fertilizer use as part of intensification to produce an increase in commodity supply. These emissions sources have been excluded at this time given a lack of globally appropriate data availability. These emissions are also expected to be negligible compared to land conversion emissions.
If [math: PPP] includes multiple commodity types, [math: CO_2e_{Market\;Leakage}] must be quantified for each commodity type.
Market leakage emissions are quantified using the following equations:
[math: CO_2e_{Market\;Leakage} = \sum\limits_{c=1}^n CO_2e_{Market\;Leakage, c}]
(Equation 3)
Where:
and:
[math: CO_2e_{Market\;Leakage, c} = ha_{LC, c} \times EF_{Carbon\;Stock}]
(Equation 4)
Where:
Project Proponents are required to estimate the amount of new land brought into production, [math: ha_{LC}]. This estimate must be informed by:
The new land brought into production must be calculated separately for each commodity type being displaced as a result of The Project.
Land conversion for production is quantified using the following equation:
[math: ha_{LC, c} = \frac{aPPP_{c} \ \times \:IS_{c}\ \times \:NL_{c}}{Y_{NL, c}}]
(Equation 5)
Where:
Adjusted unmitigated Pre-Project Productivity, [math: aPPP], must be calculated using the following equation:
[math: aPPP_c = uPPP_c \times GR_c]
(Equation 6)
Where:
The annual growth rate in productivity of the commodity type and region must be assigned as part of Equation 6. This is a requirement to ensure that any likely future increases in productivity are accounted for as part of the assessment.
Growth rate must be calculated based on the following hierarchy:
Growth rate must be calculated using the following equation:
[math: GR_c = \frac{yield_{c,t}}{yield_{c,t-x}}-1]
(Equation 7)
Where:
Average growth rate is determined by taking the difference between yield in the most recent year of recorded data ([math: t]) and a historic year ([math: t-x]). Where possible [math: t-x] should represent 25 years prior to [math: t]. Where this is not possible, a minimum of 10 years prior to [math: t] is allowable.
If a recent negative shock leads to a negative growth estimate of yield growth, a value of zero should be used.
Increased Supply is the proportion of foregone productivity that will be replaced by increased supply elsewhere. This is underpinned by the premise that foregone production will not necessarily be replaced in totality by increased supply elsewhere as a result of elasticities of supply and demand. Global markets for commodities have been assumed for the purposes of the leakage assessment.
Estimates for [math: IS] are determined using the following equation:
[math: IS = \frac{ε_{s,c}}{ε_{s,c} +\ ε_{d,c}}]
(Equation 8)
Where:
Isometric has carried out a literature review of [math: ε_s] and [math: ε_d] values for certain regions. Values for [math: ε_s] and [math: ε_d] for these regions are provided in Appendix A. Where The Project falls into these regions, the default values provided must be used. This is because understanding which values to use from literature is challenging as academic papers are typically not written with this purpose or audience in mind. Isometric has completed this work for certain regions to lessen this complexity and provide consistency across projects.
The default values also serve as an example of appropriate values to select from the literature for other regions; however, it should be noted that the quality of research differs across regions. For all other regions, values for [math: ε_s] and [math: ε_d] must be sourced from literature. The procedure and requirements for sourcing default values for [math: ε_s] and [math: ε_d] are set out in Appendix A.
[math: NL] considers the percentage of increased supply that will result in new land brought into production for the commodity type. This is underpinned by the premise that not all increased supply will result in new lands being brought into production. Some increased supply may be made up of intensification of activities and increased yields on existing production lands.
Isometric have carried out a literature review of [math: NL] values for certain regions. Values for [math: NL] for these regions are provided in Appendix A. Where The Project falls into these regions, the default values provided must be used. The procedure and requirements for sourcing default values for [math: NL] are set out in Appendix A.
The default values also serve as an example of appropriate values to select, however it should be noted that the quality of research differs across regions.
[math: Y_{NL}] considers the yield on new land brought into production for commodity c. To determine yield on new land, follow the regional and national approach set out in the assessment of [math: Productivity] (Section 8.3.5.1.2).
[math: EF_{Carbon\;Stock}] must be derived from the IPCC average national aboveground biomass content of forests. Mean carbon stocks should be derived from aboveground biomass estimates in Table 3A.1.4 of the IPCC Good Practice Guidance for Land Use, Land Use Change and Forestry28. Carbon stocks should be determined using the same ratio of mass of CO2 to mass of C, and carbon fraction, [math: CF], as set out in Section 9.3.1. Belowground biomass stocks should be estimated using the same process as set out in Section 9.3.3.
Where activity-shifting mitigation is in place, activity-shifting leakage monitoring is not required. Where only market leakage mitigation is in place, activity-shifting leakage monitoring must be undertaken for The Project. This is because market leakage mitigation does not necessarily mitigate activity-shifting leakage and Direct Actors may still be implicated. Where only partial or no leakage mitigation is in place, activity-shifting leakage monitoring must be undertaken in addition to a full or partial market leakage emissions deduction.
Activity-shifting leakage monitoring requires satellite imagery of a buffer or boundary zone along the project perimeter, called the Leakage Monitoring Zone (A transitional or boundary zone along the Project’s perimeter that is monitored for activity-shifting leakage.). The Leakage Monitoring Zone will form a consistent buffer zone along the perimeter of the project site. The distance between the exterior perimeters of the project site and Leakage Monitoring Zone (i.e., the buffer width) will be determined by the smaller of the following:
The Leakage Monitoring Zone sizing is based on the likelihood that most of the displacements from the project area will not go beyond a five-kilometer radius, as well as to reflect the relative impact of variations in project size.
Isometric will undertake monitoring of the Leakage Monitoring Zone. The satellite imagery will be monitored at every Verification and will account for seasonal differences in vegetation cover. The satellite imagery will compare the deforestation rate of the Leakage Monitoring Zone with the average deforestation rate in the region. Whenever the deforestation rate in the Leakage Monitoring Zone is higher than the average for the region, the Project Proponent must provide additional information. The additional information must include:
If the Project Proponent is able to provide justification that the above-average rates of deforestation observed are unrelated to The Project and not as a result of actions relating to the Direct Actors, then no further action is required. If the Project Proponent is unable to provide sufficient justification, then the above-average area of deforestation must be considered as part of the leakage calculation.
Consider two forest conservation projects with different areas:
Example 1: Small Project
The small reforestation project has a project area of 1 km2. Using the first approach, a 5 km buffer width would create a Leakage Monitoring Zone of 120 km2 (calculated as an 11 km x 11 km total area minus the 1 km2 project area). Using the second approach, the Leakage Monitoring Zone would only need to be 5 km2 (five times the project area). In this case, the second approach would be used as it results in the smaller Leakage Monitoring Zone.
Example 2: Large Project
The large reforestation project has a project area of 100 km2. Using the first approach, a 5 km buffer width would create a Leakage Monitoring Zone of 300 km2 (calculated as a 20 km x 20 km total area minus the 100 km2 project area). Using the second approach, the Leakage Monitoring Zone would need to be 500 km2 (five times the Project Area). In this case, the first approach would be used as it results in the smaller Leakage Monitoring Zone.
The amount of above-average deforestation that should be attributed to The Project as activity-shifting leakage is determined by the total amount of possible activity-shifting leakage. The difference between market leakage and identified activity-shifting leakage is included in the calculation of [math: CO_2e_{Leakage}] in Equation 9. [math: CO_2e_{Activity-shifting\;Leakage\:Adjustment}] is calculated with the following equation:
[math: CO_2e_{Activity-shifting\;Leakage\:Adjustment} = max\;(ha_{ASL} \times EF_{Carbon\;Stock}-CO_2e_{Market\:Leakage}\:, 0)]
(Equation 9)
Where:
The amount of above-average deforestation that should be attributed to The Project as activity-shifting leakage, [math: ha_{ASL}], is determined by the total amount of possible activity-shifting leakage. This is represented in the following equation:
[math: ha_{ASL} = min\:(\frac{ha_{Monitored\:LC}}{ha_{Max \:LC}},1) \times ha_{Max\;LC}]
(Equation 10)
Where:
[math: ha_{Max\:LC}] is calculated using the following calculation:
[math: ha_{Max\:LC} = \frac{aPPP}{Y_{NL}}]
(Equation 11)
Where:
The Reporting Period for reforestation projects represents an interval of time over which removals are calculated and reported for Verification. The minimum duration of a Reporting Period is one year and the maximum duration of a Reporting Period is five years (see Section 5.3).
Total net CO2e removal is calculated for each Reporting Period and is written hereafter as [math: CO_2e_{Removal, RP}]. The net CO2e removal quantification must be conservatively determined, giving high confidence that at a minimum, the credited amount of CO2e was removed and stored.
GHG emission calculations must include all emissions related to the project activities that occur within the Reporting Period (see Table 1). This includes:
In line with the Isometric Standard, this Protocol requires that Removal Credits are issued ex-post (Issuance of Credits after removal or reduction took place. This is the manner in which Isometric Delivers Credits.). Credits may be issued once CO2 has been removed from the atmosphere and is stored in living trees.
Net CO2e removal for a reforestation project for each Reporting Period (RP), is calculated with the following equation:
[math: CO_2e_{Removal, RP} = CO_2e_{Stored, RP} - CO_2e_{Counterfactual, RP} - CO_2e_{Emissions, RP}]
(Equation 12)
Where:
The total amount of CO2 stored from a reforestation project is calculated as
[math: CO_2e_{Stored,RP}=CO_2e_{AGB, RP}+CO_2e_{BGB, RP}]
(Equation 13)
Where:
The carbon pools within the scope of this Protocol are aboveground and belowground woody biomass (see Table 1), since they can be quantified with the highest level of accuracy and are able to be effectively monitored over time. Soil, deadwood, and litter carbon pools are excluded from the calculation of [math: CO_2e_{Stored, RP}] due to large uncertainties in quantification approaches and/or relatively small contributions to the total forest carbon pool. For the remainder of the Protocol, the use of AGB and BGB refers to only the living aboveground and belowground woody biomass, respectively, unless otherwise noted. Details of how to calculate [math: CO_2e_{AGB, RP}] and [math: CO_2e_{BGB, RP}] are described below.
The total carbon stored in aboveground biomass over a Reporting Period is calculated by taking the difference between the start and end of the Reporting Period:
[math: CO_2e_{AGB, RP} = CO_2e_{AGB}(t_2) - CO_2e_{AGB}(t_1)]
(Equation 14)
Where:
Reporting Periods are consecutive, so that [math: t_2] then becomes the start of the next RP.
The aboveground biomass carbon stock at a point in time, [math: t], is further calculated as:
[math: CO_2e_{AGB}(t) = \frac{44}{12} \times CF \times M_{AGB}(t)]
(Equation 15)
Where:
The carbon fraction, [math: CF], must be chosen from the following hierarchy:
This Protocol currently supports the following three options for quantifying the total AGB over the project area at a point in time, [math: M_{AGB}(t)]:
Requirements for each approach is described in the sections below. Project Proponents must describe in the PDD which option is used, and adhere to the requirements of that approach. Note that Options 2 and 3 still require field plots as the source of truth for benchmarking the maps. This list of acceptable approaches may be expanded upon in future versions of the Protocol.
Project Proponents who wish to use an alternative approach must provide sufficient evidence to demonstrate that it meets or exceeds the accuracy of the workflows presented in this Protocol. Alternative approaches must be agreed upon ahead of time with Isometric and undergo an independent scientific review.
[math: M_{AGB}] can be calculated by taking sufficient field plot measurements to obtain an estimate of the mean AGB density, which can then be multiplied by the project area to obtain a total AGB:
[math: M_{AGB}(t) = \bar{m}_{AGB}(t) \times A ]
(Equation 16)
Where:
Estimation of [math: \bar{m}_{AGB}(t)] is based on direct measurements of tree parameters (e.g., diameter at breast height (DBH) in field plots), and the use of allometric equations to convert tree parameters to biomass.
Allometric equations must be specific to the forest type and ecoregion in which The Project is located. Fixed size thresholds must be imposed on independent variables (e.g., DBH > 10 cm).
Project Proponents must use independently published allometric equations, from the following sources, in order of preference:
Field measurements must follow a prescribed field manual, such as the USFS field guide, the Climate Action Reserve’s field guide, or similar manuals produced for national forest inventories. Field measurements should occur during the leaf-off season when possible, to encourage alignment with potential LiDAR sampling (see Appendix B).
Field sampling must be conducted within a number of representative plots spanning the project area. Project Proponents should consider the following when establishing field plots and inventories:
Project Proponents must report the following information in the PDD for this option:
For each Verification, Project Proponents must submit a description of the measurements collected and report the full field inventory data.
Another approach for estimating [math: M_{AGB}] is Area Based Modeling with airborne laser scanning (ALS) measurements, where LiDAR or stereo photogrammetry data is collected from the air using drones, helicopters, or airplanes. In this approach, a machine learning model is trained on ALS measurements as well as plot measurements in similar regions that are representative of the project area. The model is trained to predict AGB for every pixel on a map. Once a regional model is trained, the model can be applied to "wall-to-wall" ALS measurements taken over the entire project area to generate a map of AGB at a point in time.
Project Proponents taking this approach should follow established best practices, such as White et al., 2013: A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach (Version 2.0)33. See Appendix C for more details on this approach, including requirements for training data, ALS data acquisition, data processing, and statistical modeling.
Project Proponents must conduct field sampling to quantify aboveground biomass density (biomass over area) in field plots. The biomass density derived from field sampling must be reported as a benchmark against biomass density estimated from the regional AGB map over the same region. This benchmarking must be done at least once every 5 years during the Crediting Period.
Field plots for the purpose of validating an external map should adhere to the following requirements:
Project Proponents must report the following information in the PDD, to ensure transparency and with enough detail to allow for repeatability:
The following information must be reported for Verification:
This final option for quantifying [math: M_{AGB}] is to use independent third-party global AGB maps, which are typically generated from a combination of satellite remotely sensed data, ground data, and models. Third-party forest biomass data products must be assessed at a validation stage of 2 or higher under the CEOS validation hierarchy. Isometric will, in due time, publish acceptable third-party AGB resources based on region and forest type, updating the resource list as new products and vendors become available and are reviewed by Isometric.
The third party global AGB map must be benchmarked against field plot measurements, at least once every 5 years during the Crediting Period. Field plots for the purpose of validating an external map should adhere to the following requirements:
If the equivalence test is not passed, then the global map cannot be used directly for quantifying [math: M_{AGB}] directly. In this case, the global map can be corrected and remapped with field plots to adjust for any local errors. This should be done using a simple linear regression relating field measurements to estimated carbon stock, which requires a sufficient number of field plots to obtain a model with reasonable accuracy (such as an R2 ≥ 0.85). This corrective mapping should ideally either be done across many forest ages at once (i.e., a chrono-sequence), or should be remapped periodically.
Reporting requirements for global third-party AGB maps include:
The total carbon stored in belowground biomass over a Reporting Period is calculated as:
[math: CO_2e_{BGB, RP} = RS \times CO_2e_{AGB, RP}]
(Equation 17)
Where:
Appropriate root-to-shoot ratios should be selected by regional and species-specific factors that are justified based on scientific literature (e.g., USFS's Component Ratio Method or similar national-level species-specific ratios). This is the preferred approach to have the most accurate estimate and avoid overestimation. If sufficient evidence is provided to demonstrate that no suitable project-specific factor can be obtained, matching to the ecological zone and continent of the project area, based on the IPCC 2019 Table 4.430, must be used.
The uncertainty in selected [math: RS] factors must be reported from the same source dataset. For example, the IPCC 2019 Chapter on Forest Land30 provides an uncertainty in the root-to-shoot ratio.
This Protocol uses a dynamic baseline approach to quantify the counterfactual impact on forest carbon stocks if the project activity had not occurred. As a default, dynamic baselines will be independently determined and transparently reported by Isometric at each Verification to determine any deduction in Credit issuance based on the Baseline scenario. The following section outlines the workflow that Isometric will take–the Project Proponent is not responsible for carrying out the steps in this section. However, Project Proponents who wish to own the selection of control plots must follow a similar approach and provide a transparent and reproducible plan that is agreed upon ahead of time with Isometric.
Additionally, Isometric will make a pre-project estimation of the Baseline scenario at project initiation using historical data as described below.
The control plot zone must meet the following eligibility criteria:
If possible, other features should also be matched between the control plot zone and project area, such as:
Initially, the zone for eligible control plots should be limited to a 100 km band around the project area. However, if suitable matches (see Section 9.4.3 for matching step) 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.
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:
Project pixels are matched to control plot pixels based on the historical time series of the selected forest carbon proxy, [math: C_{proxy}], of each pixel, using k-nearest neighbors with replacement (or an alternative justified algorithm). Each project pixel must be matched to a minimum of 10 different control pixels, and the mean forest carbon proxy over the group of control pixels is used. Multiple project pixels may be matched to the same control pixels.
The baseline correction is calculated using the equation below. The difference between forest carbon stock change is assessed per project-control pixel set. Then, the differences are summed across The Project to determine the cumulative baseline.
[math: CO_2e_{Counterfactual,RP}=\sum_{i=1}^n[CO_2e_{Stored,RP, i}\times(\frac{\Delta\ C_{proxy,control,i}}{\Delta\ C_{proxy,project,i}})]]
(Equation 18)
Where:
The [math: \Delta] represents the change over a Reporting Period, e.g.,
[math: \Delta C_{proxy} = C_{proxy}(t_2) - C_{proxy}(t_1)],
(Equation 19)
where [math: t_1] and [math: t_2] are the start and end of the Reporting Period, respectively.
At each Verification, the control pixels are reviewed to determine continued eligibility within control plots as outlined in Section 9.4.1. In the event that control pixel matches are no longer suitable, replacements will be selected for the impacted project pixels. Example scenarios that should lead to control pixels being reviewed and reselected include:
A performance benchmark for the project area, [math: PB_{RP}] can be calculated by:
[math: PB_{RP} = \frac{CO_2e_{Removed,\ RP}}{CO_2e_{Counterfactual,\ RP}}]
(Equation 20)
The performance benchmark must be [math: PB_{RP} > 1] to meet the environmental additionality requirement.
Isometric will account for uncertainty in the dynamic baseline to obtain a conservative estimate of [math: CO_{2}e_{Counterfactual,\ RP}] in Equation 18. This will include an evaluation of at least the following sources of uncertainty:
[math: CO_2e_{Emissions, RP}] is the total GHG emissions associated with a Reporting Period, RP. This can be calculated as:
[math: CO_2e_{Emissions} = CO_2e_{Establishment} + CO_2e_{Operations} + CO_2e_{End-Of-Life} + CO_2e_{Leakage}]
(Equation 21)
Where:
The following sections set out specific quantification requirements for each term in Equation 21.
GHG emissions associated with project establishment should include all historic emissions incurred as a result of project establishment, including but not limited to the SSRs set out in Table 1, such as biomass burning for site preparation, temporary structures, and fertilizer and/or herbicide application. An inventory of pre-project vegetation is required to quantify vegetation removed during planting and site preparation.
Project establishment emissions occur from the point of project inception through to the start of the first Reporting Period, which is typically immediately following planting. GHG emissions associated with project establishment may be allocated in one of the following ways, with the allocation method selected and justified by the Project Proponent:
The anticipated lifetime of The Project should be based on the Crediting Period. Allocation of project establishment emissions to removals must be reviewed at each Reporting Period and any adjustments made. If the Project Proponent is not able to comply with the allocation schedule described in the PDD (e.g., due to changes in delivered volume or anticipated project lifetime), the Project Proponent should notify Isometric as early as possible in order to adjust the allocation schedule for future removals. If that is not possible, the Reversal process will be triggered in accordance with Section 5.6 of the Isometric Standard, to account for any remaining emissions.
GHG emissions associated with [math: CO_2e_{Operations,\ RP}] should include all emissions associated with operational activities, including but not limited to the SSRs set out in Table 1.
For reforestation projects, the Reporting Period covers a set period of time (e.g., one year), during which the forest was growing and increasing its woody biomass. [math: CO_2e_{Operations,\ RP}] emissions must be attributed to the Reporting Period in which they occur. Allocation outside of the current Reporting Period may be permitted in certain instances, on a case by case basis in agreement with Isometric.
[math: CO_2e_{End-of-Life,\ RP}] includes all emissions associated with activities that are anticipated to occur after the Crediting Period until the end of the Project Commitment Period. This includes activities related to ongoing monitoring for Reversals.
[math: CO_2e_{End-of-Life,\ RP}] must be estimated upfront and allocated in the same way as set out for calculation of [math: CO_2e_{Establishment}].
Given the uncertain nature of [math: CO_2e_{End-of-Life,\ RP}] emissions, assumptions must be revisited at each Reporting Period and any necessary adjustments made. Furthermore, if there are unexpected [math: CO_2e_{End-of-Life, RP}] emissions that occur after The Project has ended, then the Reversal process described in Section 5.6 of the Isometric Standard will be triggered to compensate for any emissions not accounted for.
[math: CO_2e_{Leakage, RP}] includes emissions associated with a project's impact on activities that fall outside of the system boundary of The Project. It includes increases in GHG emissions as a result of The Project displacing emissions or causing a secondary effect that increases emissions elsewhere.
The [math: CO_2e_{Leakage,\ RP}] calculation approach is set out in full in Section 8.3.2.4 and is not repeated here.
Project Proponents must use the most representative, accurate and plausible data that is available at the time of assessment in the GHG Statement. Activity data used to inform GHG accounting may be:
Project Proponents must strive to use primary data in GHG accounting, but secondary data may be used where primary data is not available or not practical. Unavailability of primary data should be suitably justified.
An example is emissions related to plant nurseries. The Project Proponent should strive to obtain activity data such as electricity use and consumable use at plant nurseries where seedlings are sourced. If such data is not available, it is acceptable to use an industry average emission factor for tree seedling production. Suitable emission factor sources are described in relevant modules (Independent components of Isometric Certified Protocols which are transferable between and applicable to different Protocols.), as set out below.
This section sets out specific requirements relating to quantification of energy use as part of the GHG Statement. Emissions associated with energy usage result from the consumption of electricity or fuel.
Examples of activities that may require electricity or fuel usage may include, but are not limited to:
The Energy Use Accounting Module 1.2 provides guidancerequirements on how energy-related emissions must be calculated for The Project so that they can be subtracted in the net CO2e removal calculation. It sets out the calculation approach to be followed for intensive facilities and non-intensive facilities and acceptable emission factors.
Refer to Energy Use Accounting Module for the calculation guidelinesrequirements.
This section sets out specific requirements relating to quantification of transportation emissions as part of the GHG Statement.
Emissions associated with transportation include transportation of products and equipment as part of project activities. Examples may include, but are not limited to:
The Transportation Emissions Accounting Module 1.01 provides guidancerequirements on how transportation-related emissions must be calculated for The Project so that they can be subtracted in the net CO2e removal calculation. It sets out the calculation approach to be followed and acceptable emission factors.
Refer to Transportation Emissions Accounting Module for the calculation guidelinesrequirements.
This section sets out specific requirements relating to quantification of embodied emissions as part of the GHG Statement. Embodied emissions are those related to energy use or other emissions during the manufacture of equipment and materials used in a process.
Examples of project-specific materials and equipment that must be considered as part of the embodied emission calculation include but are not limited to:
The Embodied Emissions Accounting Module 1.0 sets out the calculation approach to be followed including allocation of embodied emissions, life cycle stages to be considered, data sources and emission factors.
Refer to Embodied Emissions Accounting Module for the calculation guidelinesrequirements.
Any models used under this Protocol must be well-validated and skillful for the purpose that they were used for. Proof of model validation can be achieved through either:
The storage reservoir of the CO2 removed through reforestation is live aboveground and belowground 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, risks of Reversals and requirements for storage of removed atmospheric CO2 as live woody biomass.
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 Protocol, is 40 years.
The duration of the Ongoing Monitoring Period must not exceed any of the following:
Reversal risks which may threaten the durability of forest carbon and project-level risk assessment and mitigation requirements are discussed in Section 10.2 and Section 10.3, respectively.
A reforestation-wide Buffer Pool managed by Isometric is used to insure Credits against Reversals. Throughout the Ongoing Monitoring Period, Isometric will monitor for Reversals to ensure Credits achieve their stated durability. Upon detection and quantification of carbon losses, Credits issued to the Buffer Pool will be canceled in equal proportion to the loss (see Sections 10.4: Buffer Pool and 10.5: Ongoing Monitoring for Reversals).
A long-term durability plan to continue maintenance of forest carbon beyond the Project Commitment Period is needed to mitigate risk of timber harvest or Reversal after The Project ends (see Section 5.5: Post-Project Commitment Period). The long term durability plan may consist of evidence of the following, and ideally a combination of factors:
Reversals are defined as reductions in forest biomass that may result in emissions of CO2 to the atmosphere. Reversal risk is quantified by assessing the likelihood of a disturbance event occurring over a period of time and estimating the severity of the disturbance in terms of biomass loss. Disturbance events may be natural or anthropogenic, such as fire, drought/heat, insect and disease, deforestation, and timber harvesting. A disturbance event which results in a reduction in forest biomass is considered a loss event. The duration of disturbance events may be over multiple years (e.g., drought) or for a very limited duration (e.g., windstorm).
The likelihood and severity of disturbances are influenced by external and project-related factors.
External factors:
Project-related factors:
Furthermore, the risk profile of The Project may change over the Project Commitment Period due to:
Projects must complete Isometric’s Reforestation Risk Assessment in Appendix F, which is independently evaluated by a third-party VVB. The Reforestation Risk Assessment is used to determine the risk profile of The Project, including risks to Credit delivery (The outcome of a Project Proponent providing Credits to fulfill Buyers' purchases.) and storage. Aspects of The Project which have higher risk exposure must be accompanied by an appropriate risk mitigation plan. To safeguard against high risk projects, The Project must score below the indicated thresholds to be eligible for crediting under this Protocol. The Reforestation Risk Assessment must be updated each Reporting Period by the Project Proponent and increased risk scores will result in additional mitigation activities.
Mandatory Safeguards
The following safeguards are required for all reforestation projects and must be in place at the start of The Project and maintained throughout the Project Commitment Period. The Project Proponent must:
As outlined in Section 5.6 of the Isometric Standard, the Buffer Pool is a mechanism used to insure against risks of Reversals that may be observable and attributable to The Project through monitoring.
Currently, there is insufficient published scientific evidence to quantitatively account for climate change, management activities, or forest age and translate this into a highly accurate Buffer Pool contribution39. As a result, we apply either a flat contribution requirement on The Project or a model to translate the Reforestation Risk Assessment into a Buffer Pool contribution. As actuarial data improve and more research is published, the Protocol requirements will be updated accordingly.
To be eligible under this Protocol, The Project must either:
The Buffer Pool contribution will be held in a reforestation-wide Buffer Pool managed by Isometric. Pooling of a diversified portfolio of reforestation projects across geographic regions, spatial scales and temporal scales can reduce the exposure to systemic risks stemming from reforestation projects constrained to a geographic area or ecological type40, 41, 42. The reforestation-wide Buffer Pool composition will be transparently reported on the Isometric Registry.
The Buffer Pool Compensation Process is governed by the Isometric Standard. The following procedures apply upon detection and quantification of a loss event.
For more details on Reversals, refer to Sections 2.5.9 and 5.6 of the Isometric Standard.
Isometric will independently conduct continuous monitoring for Reversals for the full length of the Project Commitment Period. Monitoring will consist of:
Upon detection of a Reversal, Project Proponents must thoroughly investigate, initiate adaptive management to minimize losses (for open systems, biogeochemical and/or physical interactions which occur during the removal process that decrease the CO₂ removal .), and implement mitigation actions to reduce future risks of Reversal.
Loss events representing a reduction of carbon stored in live woody biomass greater than 1% of the cumulative tonnes of CO2e removed by The Project (based on total number of Credits issued) must be reported, investigated, and compensated for.
Upon detection of a loss event by Isometric or other third party, the following procedures will commence:
Quantification of Reversals are calculated by determining the relative change in a proxy aboveground biomass parameter such as forest area cover or vegetation indices. Since only carbon stored in live woody biomass is considered in the quantification of carbon removal, this Protocol conservatively assumes that all carbon stored in live woody biomass is immediately released to the atmosphere upon mortality as a result of a disturbance event. Belowground biomass is conservatively assumed to be lost proportionally to aboveground biomass.
The method for quantifying Reversals is subject to the following limitations, and will be updated with developing science:
Projects which experience a Reversal on the scale of 20% of the cumulative tonnes of CO2e removed by The Project (based on total number of Credits issued) must conduct field sampling to quantify the remaining stocks of forest carbon stored in live woody biomass.
All pre-deployment requirements must be described in the PDD, as outlined in Section 7.1. The requirements are as follows:
Description of the project site, including:
Description of project timeline, including:
Description of planned reforestation activities, including:
Documentation of any pre-Validation activities, including:
Description of leakage assessment and leakage mitigation plan, including:
Description of monitoring activities, including:
Risk of Reversal plan, including:
This Protocol requires a combination of in situ and remotely-sensed monitoring for the following purposes:
This section summarizes the Monitoring requirements that are discussed throughout this Protocol.
Project monitoring responsibilities are split between the Project Proponent and Isometric as follows:
Isometric owns:
Project Proponent owns and provides in monitoring reports:
This Protocol refers to monitoring at multiple different locations, which are illustrated in an example in Figure 3.
Maps of monitoring locations that the Project Proponent is responsible for (i.e., everything inside the project area) must be described and submitted with the PDD. Isometric will transparently disclose locations of control pixels and Leakage Monitoring Zone.
[Image: **Figure 3** Monitoring locations]
Figure 3. Schematic of the various monitoring locations referred to throughout this Protocol.
The entire project area in Figure 1 must be monitored for the duration of the Project Commitment Period (see Section 5.1).
During the Crediting Period, monitored parameters from an AGB proxy map (e.g., canopy height) in the project area is used in conjunction with control pixels to establish a dynamic baseline for determining the additionality of carbon storage in the project area. It is highly recommended that Isometric or another independent third party be responsible for project area monitoring for establishing relative change compared to control pixels (see Section 12.4). Project Proponents may carry this monitoring out themselves provided that a transparent and reproducible monitoring plan is agreed upon ahead of time with Isometric.
After the Crediting Period, ongoing monitoring of forest biomass (e.g., forest cover or saturation index) must continue annually until the end of the Project Commitment Period for detection of Reversals (see Section 10.5). Isometric will ensure independent ongoing monitoring for Reversals until the end of the Project Commitment Period.
Control pixels are used to assess natural regeneration in similar land areas outside the project area to determine the additional carbon storage of a reforestation project beyond the counterfactual scenario. Control pixels are selected by matching each project area pixel to a number of pixels outside the project area that historically behaved similarly (see Section 9.4.3).
An AGB proxy map (e.g., canopy height) is used to determine the relative difference in forest carbon between The Project and Counterfactual scenario for each Reporting Period (see Section 9.4). It is highly recommended that Isometric or another independent third party be responsible for selection and monitoring of control pixels. Project Proponents may carry this monitoring out themselves provided that a transparent and reproducible monitoring plan is agreed upon ahead of time with Isometric.
For projects without sufficient activity-shifting leakage mitigation, the Leakage Monitoring Zone must be monitored using satellite imagery for the duration of the Crediting Period to detect deforestation near the project area. Annual monitoring of forest cover over time is used to calculate deforestation rates over time. See Section 8.3.6 for more details on how leakage monitoring is used.
It is highly recommended that Isometric or another independent third party be responsible for monitoring of the Leakage Monitoring Zone. Project Proponents may carry this monitoring out themselves provided that a transparent and reproducible monitoring plan is agreed upon ahead of time with Isometric, and will be checked annually by Isometric.
Airborne laser scanning measurements are only applicable for projects that wish to use regional LiDAR models to estimate AGB (Option 2 described in Section 9.3.2.2). ALS data collection should occur throughout the Crediting Period, at the end of each Reporting Period. Measurements should be taken in the same season (e.g., leaf-off) to reduce uncertainty and biases.
Wall-to-wall laser scanning measurements are highly recommended. Laser scanning of representative subplots throughout the project area is also permissible with rigorous statistical analysis to constrain the uncertainty associated with subplot selection and upscaling. See Section 9.3.2.2 and Appendix C for more information on laser scanning requirements.
In situ field measurements are required for all projects throughout the Crediting Period. Field plots may be used as the primary method for calculating aboveground biomass (Option 1 in Section 9.3.2.1), or are used for benchmarking regional or global AGB maps (Option 2 in Section 9.3.2.2, or Option 3 in Section 9.3.2.3). For projects using Option 1, where AGB is derived directly from field measurements, then in situ field plots must be sampled at the beginning and end of each Reporting Period. Otherwise for Options 2 and 3, field measurements must be taken at a minimum of every 5 years for benchmarking AGB models.
See Appendix B for general guidance on field plot surveys, and Sections 9.3.2.1 - 9.3.2.3 for specific field plot requirements for each quantification approach. At minimum, species identification and DBH must be measured for all trees with DBH > 10 cm within the in situ field plot.
During the first few years after planting seedlings, there may not be many trees with DBH > 10 cm. However, it is still important to monitor field plots during this time as young forests are particularly vulnerable to disease, ecological hazards, and may experience high rates of mortality. In addition, techniques to quantify forest biomass tend to overestimate in young forests. Between project initiation and first Verification (see Section 5), it is recommended to monitor for early tree mortality every 6 months to better constrain early stage growth as well as inform any mortality mitigation activities (e.g., replanting trees).
Table 2 Summary of the required and recommended monitoring parameters.
| Frequency | Location | Parameter | Methods | Justification | Recommended or Required | Responsible party |
|---|---|---|---|---|---|---|
From initial planting to first Verification, recommended every 6 months | In-situ field plots | Tree mortality | Mortality survey, or high resolution drone imagery | Estimations of forest biomass may be highly uncertain during the initial years after tree planting due to high rates of tree mortality and biases in young forests. Surveys for early tree mortality can better constrain early stage biomass growth, and enable mortality mitigation activities | Recommended | Project Proponent |
At the start and end of each Reporting Period for Option 1 in Section 9.3.2.1. Otherwise, at least every 5 years. | In situ field plots | DBH for all trees larger than 10 cm diameter | Tape measure | Fundamental measurement estimating AGB using allometric equations | Required | Project Proponent |
At the start and end of each Reporting Period for Option 1 in Section 9.3.2.1. Otherwise, at least every 5 years. | In situ field plots | Tree species | Ecologist identification | Necessary for selecting species-specific allometric equations and parameters | Required | Project Proponent |
At the start and end of each Reporting Period, e.g., once a year in the same season | Laser scanning plots | 3D Point clouds and derived metrics (e.g., canopy height) | Laser scanning instruments mounted on aerial | To derive estimates of forest aboveground biomass | Required for Option 2 (Section 9.3.2.2), otherwise not applicable | Project Proponent |
At the start and end of each Reporting Period, e.g., once a year in the same season | Project area | AGB Map | Satellite data or third-party mapped product | To derive estimates of forest aboveground biomass | Required for Option 3 (Section 9.3.2.3), otherwise not applicable | Isometric or a third party |
| At the start and end of each Reporting Period, e.g., once a year in the same season | Control pixels & project area | Forest carbon proxy (e.g, canopy height, biomass saturation index) | Satellite data or third-party mapped product | To quantify relative change in forest carbon sequestration between control pixels and project area (Equation 18) | Required | Isometric or a third party |
| At the start and end of each Reporting Period, e.g., once a year in the same season | Leakage buffer zone | Indicators of deforestation | Satellite | To identify any activity-shifting leakage that should be taken into account for the net carbon removal calculation (Equation 9) | Required | Isometric or a third party |
From the end of the Crediting Period to the end of the Project Commitment Period, annually | Project area | Indicators of deforestation | Satellite | To identify Reversals and appropriately remediate through the Buffer Pool | Required | Isometric or a third party |
Isometric has carried out a literature review of [math: ε_s] and [math: ε_d] values to inform [math: IS], as well as values for [math: NL] for certain regions. Where The Project falls into these regions, the default values provided must be used. This is because understanding which values to use from literature is challenging as academic papers are typically not written with this purpose or audience in mind. Isometric has completed this work for certain regions to lessen this complexity and provide consistency across projects.
These default values also serve as an example of appropriate values to select, however it should be noted that the quality of research differs across regions.
The following sections set out the procedure to be followed to obtain [math: IS] and [math: NL] values and set out the default values to be used for the regions studied.
The regions considered in the literature review were:
These regions were selected following a review of projected project demand. Isometric will update this analysis with additional regions iteratively based on demand. Values for other regions will be reviewed by Isometric on a case by case basis.
IS represents the amount of production that is diverted to other locations. The IS value does not provide any information on where or in what manner that production is produced.
Procedure for determining [math: IS] values:
Where possible:
Table A1.[math: IS] default values.
| Geography | Crop | εdc | εsc | IS | Key citation |
|---|---|---|---|---|---|
| Global | Calories (rice, wheat, corn, soy) | -0.05 | 0.12 | 0.70 | Roberts and Schlenker (2013)43 |
| Global | Coffee | -0.305 | 0.285 | 0.48 | Akiyama and Varangis (1990)44 |
| Global | Cocoa | -0.075 | 0.075 | 0.50 | Askari and Cummings (1977)45, Behrman (1965)46 |
| South America | Livestock | -0.40 | 0.4 | 0.5 | Fragoso et al. (2011) 47 |
| North America | Livestock | -0.40 | 1.6 | 0.80 | Mintert et al. (2009)48, Jeong (2019)49 |
Procedure for determining [math: NL] values:
In an ideal world, there would be estimates of the specific types of land use that were converted and their locations. However, this data is not available. Instead, the Project Proponent should focus on the most important elements of potential land use change from a carbon emissions perspective. NL values proposed aim to capture the net effect of a one unit removal of crop area on forestland conversion. These NL values will be smaller in magnitude than NL values that incorporate the possibility of conversion of grazing land or the conversion of lower-value crops to higher-value crops. Focusing on forests is more tractable and likely provides a large share of the relevant land use change emissions, since forest conversion is relatively permanent in a way that livestock to cropland conversion is not. In general, the NL values are more speculative than the IS values and often rely on assumptions about the yield-price elasticity that have not been empirically confirmed.
There are possible methodologies for obtaining [math: NL] values, which are set out here. Method B is in most cases the preferred approach. This is because the necessary conditions to implement Method A (limited trade/ disconnected markets and demand driven quantity increase) are rarely met in practice. Method A should only be used in special cases and justified appropriately. Both methods are set out below:
[math: NL = \frac{{Gross\: new\: production\:}_x}{{Gross\: new\: production\:}_x +\ {\Delta \ Average\: yield \:}_x\: + \ Total\: land \:area}]
(Equation A1)
Where:
[math: x] is variable under the assumption that changes to supply are predominantly channeled through price changes50.
By dividing the numerator and denominator, the above equation can be reformulated as:
[math: NL = \frac{{\Delta \ Area\:}_x}{{\Delta \ Area\:}_x +\ {\Delta \ Yield \:}_x\:}]
(Equation A2)
Where:
The following default values have been gathered using Method B.
Table A2.[math: NL] default values.
| Geography | Crop | NL | Key citation |
|---|---|---|---|
| Brazil | cropland | 0.61 | Pendrill et al (2019)51 |
| US | cropland | 0.28 | Lark et al (2022)52 |
| Mexico | cropland | N/A | Can use Brazil value |
| Panama | cropland | N/A | Can use Brazil value |
| Brazil | livestock | 0.83 | Bowman (2012)53 |
| US | livestock | 0.20 | Wu (2000)54 |
| Mexico | livestock | N/A | Can use Brazil value |
| Panama | livestock | N/A | Can use Brazil value |
| Global | Coffee | 0.60 | Report: “60% of land suitable for coffee is forested”55 |
| Global | Other specialty crops | N/A | See: global coffee value |
Field plot surveys can be used as a primary approach for quantifying AGB, used for training regional area-based LiDAR models, or benchmarking and calibrating various AGB models. This Appendix summarizes some general guidance for field plot surveys, but specific requirements will depend on the intended usage of the field data. See Section 9.3.2 of the Protocol for specific requirements for particular usages.
Project Proponents should follow best practices guidelines. Recommended resources for guidance on field plot surveys include:
Field plots should be designed with the following considerations in mind:
Tree species should be recorded and the following should be measured:
The timing and frequency of field measurements depends on the usage of the measurements.
The following section outlines guidance for Airborne Laser Scanning (ALS) measurements, specifically for the purpose of training regional area-based models to estimate forest carbon from LiDAR measurements. ALS data can also be used to develop other types of models for forest carbon, such as through Individual Tree Crown modeling. Individual Tree Crown modeling is not in scope for this current Protocol version, but guidelines may be included in future iterations.
Project Proponents should follow established best practices in White et al., 2013: A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach (Version 2.0)33.
Training regional area-based ALS models requires a large amount of overlapping LiDAR and field measurements from the region in which the model will be applied. It is important that the training data have a sufficient number of plots that are representative of the project area. Furthermore, the training data should encompass a variety of forest stand ages, so that the model can perform well for young and mature forests.
Specific recommendations for plot selection:
Project Proponents are referred to White et al., 201333 for guidance on data acquisition parameters. Specific best practices recommendations include:
Data processing techniques must be sufficiently documented to permit replication, including quality control, filtering, and statistical analysis. The recommended quality control process differs between instruments. A typical LiDAR processing workflow consists of the following steps:
White et al. 201333 outlines best practices for LiDAR acquisition, planning, and development.
It should be emphasized that this is different from conventional, moderate resolution remote sensing workflows where the plots are typically treated as a point and are spatially intersected with the rasterized feature layers. This approach yields poor performance with LiDAR data.
LiDAR-based AGB maps have been developed with a variety of statistical models, including:
It is recommended to use the simplest possible statistical model that yields high-performance on the modeling dataset.
Models used to estimate AGB should:
Non-parametric models commonly exhibit a phenomena called “regression-to-the-mean”. Machine learning models work by optimizing a loss function with the goal of obtaining the lowest possible error rate. Often, the lowest possible error will be obtained by over-estimating areas with low AGB densities and under-estimating areas with large AGB densities. This can be observed in the one-to-one regression plots of many papers (e.g., see Figure 3, Panel 1 in Pflugmacher et al., 2014)64.
When a model exhibits regression to the mean, it is not appropriate to simply sum the pixel values within a given area as the systematic error of the model has not been accounted for. This is a considerable problem for regrowth modeling. Non-parametric models that use satellite imagery will almost always dramatically over-estimate low-biomass densities. Similarly, there is good evidence that the “green-up” of stands to pre-disturbance levels in moderate resolution vegetation indices will predate the actual structural regeneration of the stand by many years65.
Model-assisted estimation is a framework that allows ancillary information to be incorporated into the estimation procedure. This can allow for more precise estimates of AGB density. The typical setup for a model-assisted estimation procedure is as follows:
Details for model assisted estimation, and an associated R package, can be found in McConville et al., 2020 66.
Finally, it is worth nothing that there are many geostatistical considerations that come into play when developing statistical models. Spatial autocorrelation can violate the assumption of independence. This is why clustered plot designs are less efficient than other sampling schemes; the clustered plots are effectively pseudo-replicates. Under a design-based model-assisted framework, this is not a concern. However, it is a concern if the pixels in a map are being summed as all pixels within the same forest patch are pseudo replicates. Therefore, the sampling size is falsely inflated, given an optimistic estimate of the variance of the estimated mean.
It is recommended to make use of root-to-shoot ratios that are developed in tandem with the allometry used. Allometric equations and root-to-shoot ratios should be selected based on the following hierarchy:
For example in the United States, the National Scale Volume Biomass (NSVB) equations can be used, and these equations come with root allometry. The framework is explained in A national-scale tree volume, biomass, and carbon modeling system for the United States67 and the coefficients are given in the supplementary materials.
Furthermore, Allometric is an R package that curates allometric equations and facilitates their usage.
Additionality
Approved Resources and Third-Party Datasets
Albedo
Baseline
Buffer Pool Contribution
Insurance
Quantification with LiDAR
Leakage
Leakage Mitigation
Restoration Plan
Stakeholder Engagement
Uncertainty
Project Deviations
Emergency Response
The Reforestation Risk Assessment is used to assess the overall delivery and storage risk associated with reforestation and may inform the Buffer Pool contribution during Credit delivery (see 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 ≤ 20 and initial risk category scores at or below the following thresholds:
All risk categories shall have a minimum score of 0, regardless of the outcome of the Reforestation Risk Assessment.
If Project Proponents choose to forgo a flat 20% Buffer Pool contribution (see Section 10.4.1), the Reforestation Risk Assessment will inform Buffer Pool contributions for The Project according to the process outlined in Appendix G for each Reporting Period and in accordance with the requirements in Section 10.3.
Table F1. Reforestation Risk Assessment, 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 ecosystem restoration, 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 |
| ||
| Financial Viability Risk | Has The Project secured funding to cover all activities required before carbon revenue accrues? | Project financial plan |
| |
| What is the projected time to reach financial breakeven? | Project financial plan |
| ||
| 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 demonstrate sufficient cash flow throughout the Ongoing Monitoring Period to maintain forest carbon stocks? | Project financial plan | If continued financial incentive is low compared to likely opportunity cost of harvest, +2. | ||
| Does the project financial plan rely on future increases in market price for Carbon credits? | Project financial plan | If yes, +1. | ||
| 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 double-counting of project Credits and NDC contributions? | National registries | If no, +1. | ||
| Does | ||||
| Project financial plan |
| |||
| 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. | ||
| Does the Project Proponent have a presence in negative press content? | Online search | If yes, +1. | ||
| Have projects on Indigenous or Community Lands been identified? | Cross reference project documentation with Global Forest Watch | If no, fail. | ||
| Are baseline activities primarily subsistence-driven? | Land use documentation, Socioeconomic surveys |
| ||
| (a) Are there anticipated or demonstrated net positive community impacts? | Community impact assessment, project financial plan, socio-economic surveys | If no, +2. | ||
| (b) What is the net present value (NPV) of alternative land use compared to project NPV? | NPV analysis comparing alternative uses to project activities over Crediting Period, price forecasts, discount rate justification |
| ||
| Are opportunity cost risk mitigations in place? | Legal agreements protecting carbon stocks, Non-profit status documentation, grant/funding agreements |
| ||
| Disturbance Risk | Fire risk | Global Fire Weather Index |
| |
| Pest and disease outbreak risk | Regional third-party maps, if available. |
| ||
| Extreme weather (temperature - heat and cold) | IPCC AR6 24 |
| ||
| Extreme weather (hydrologic - flood and drought) | IPCC AR6 24 |
| ||
| Coastal risks (sea level rise, storm surge, tropical cyclones, salinity intrusion) | Regional third-party maps, if available. |
| ||
| Geologic risks (earthquakes, tsunami, volcanoes) | NOAA NCEI Natural Hazards viewer | If historical hazards in area, +1. | ||
| Illegal timber risk | Country IDAT risk score |
| ||
| 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 |
|
By default, projects are subject to a flat 20% Buffer Pool contribution as outlined in Section 10.4.1. Project Proponents may opt to calculate a project-specific Buffer Pool contribution based on the outputs of their Reforestation Risk Assessment for each Reporting Period.
The following steps are used to convert the outputs of the Reforestation Risk Assessment into a Buffer Pool contribution:
Table G1. Risk score to Buffer Pool contribution conversion for each risk category.
| Risk Category | Cumulative Risk Score | Buffer Pool Contribution |
|---|---|---|
| Project Proponent Capacity Risk | 0 | 2.5% |
| 1 | 3.3% | |
| 2 | 4.1% | |
| 3 | 5.5% | |
| 4 | 7.0% | |
| 5 | 8.4% | |
| 6 | 9.2% | |
| 7 | 10.0% | |
| Financial Viability Risk | 0 | 2.5% |
| 1 | 3.2% | |
| 2 | 3.9% | |
| 3 | 4.9% | |
| 4 | 6.2% | |
| 5 | 7.6% | |
| 6 | 8.6% | |
| 7 | 9.3% | |
| 8 | 10.0% | |
| Social Governance Risk | 0 | 2.5% |
| 1 | 3.1% | |
| 2 | 3.5% | |
| 3 | 4.0% | |
| 4 | 4.8% | |
| 5 | 5.7% | |
| 6 | 6.8% | |
| 7 | 7.7% | |
| 8 | 8.5% | |
| 9 | 9.0% | |
| 10 | 9.4% | |
| 11 | 10.0% | |
| Disturbance Risk | 0 | 2.5% |
| 1 | 3.1% | |
| 2 | 3.4% | |
| 3 | 3.9% | |
| 4 | 4.5% | |
| 5 | 5.3% | |
| 6 | 6.2% | |
| 7 | 7.2% | |
| 8 | 8.0% | |
| 9 | 8.6% | |
| 10 | 9.1% | |
| 11 | 9.4% | |
| 12 | 10.0% |
The Buffer Pool contribution for each risk category is determined using a sigmoid function described by Equation G1. The Buffer Pool contribution for each risk category ranges from 2.5% to 10%.
[math: BP_{risk} = \frac{L}{1 + e^{-k(x - x_0)}} + 2.5]
(Equation G1)
Where:
The sigmoid function, Equation G1, applied to each risk category can also be visualized in Figure G1.
[Image: **Figure G1** Buffer Pool contribution based on risk score for each risk category.]
Figure G1. Buffer Pool contribution based on risk score for each risk category.
The Project has completed the Reforestation Risk Assessment and obtained the following risk scores in a Reporting Period:
Mapping these risk scores to Table G1, the total Buffer Pool contribution for The Project is:
4.1% + 6.2% + 4.0% + 3.9% = 18.2%
Isometric would like to thank following contributors to this Protocol:
Isometric would like to thank following reviewers of this Protocol:
van Diemen, R., Matthews, J. B. R., Möller, V., Fuglestvedt, J. S., Masson-Delmotte, V., Méndez, C., Reisinger, A., & Semenov, S. (Eds.). (2022). Annex I: Glossary. In P. R. Shukla, J. Skea, R. Slade, A. Al Khourdajie, R. van Diemen, D. McCollum, M. Pathak, S. Some, P. Vyas, R. Fradera, M. Belkacemi, A. Hasija, G. Lisboa, S. Luz, & J. Malley (Eds.), Climate Change 2022: Mitigation of Climate Change. Contribution of Working Group III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change. Cambridge University Press. https://doi.org/10.1017/9781009157926.020↩
Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., ... & Hayes, D. (2011). A large and persistent carbon sink in the world’s forests. Science, 333(6045), 988-993. https://doi.org/10.1126/science.1201609↩
Harris, N. L., Gibbs, D. A., Baccini, A., Birdsey, R. A., De Bruin, S., Farina, M., ... & Tyukavina, A. (2021). Global maps of twenty-first century forest carbon fluxes. Nature Climate Change, 11(3), 234-240. https://doi.org/10.1038/s41558-020-00976-6↩
Bastin, J. F., Finegold, Y., Garcia, C., Mollicone, D., Rezende, M., Routh, D., ... & Crowther, T. W. (2019). The global tree restoration potential. Science, 365(6448), 76-79. https://doi.org/10.1126/science.aax0848↩
Tierney, G. L., Faber-Langendoen, D., Mitchell, B. R., Shriver, W. G., & Gibbs, J. P. (2009). Monitoring and evaluating the ecological integrity of forest ecosystems. Frontiers in Ecology and the Environment, 7(6), 308-316. https://doi.org/10.1890/070176↩
FAO (2000). On Definitions of Forest and Forest Change. Forest Resources Assessment Programme, Working Paper 33, Rome. ↩
Hasler, N., Williams, C. A., Denney, V. C., Ellis, P. W., Shrestha, S., Terasaki Hart, D. E., ... & Cook-Patton, S. C. (2024). Accounting for albedo change to identify climate-positive tree cover restoration. Nature Communications, 15(1), 2275. https://doi.org/10.1038/s41467-024-46577-1↩
Dinerstein, E., Olson, D., Joshi, A., Vynne, C., Burgess, N. D., Wikramanayake, E., ... & Saleem, M. (2017). An ecoregion-based approach to protecting half the terrestrial realm. BioScience, 67(6), 534-545. https://doi.org/10.1093/biosci/bix014↩↩2
Besnard, S., Koirala, S., Santoro, M., Weber, U., Nelson, J., Gütter, J., ... & Carvalhais, N. (2021). Mapping global forest age from forest inventories, biomass and climate data. Earth System Science Data Discussions, 2021, 1-22. https://doi.org/10.5194/essd-13-4881-2021↩
Searle, E. B., & Chen, H. Y. (2017). Tree size thresholds produce biased estimates of forest biomass dynamics. Forest Ecology and Management, 400, 468-474. https://doi.org/10.1016/j.foreco.2017.06.042↩
Di Sacco, A., Hardwick, K. A., Blakesley, D., Brancalion, P. H., Breman, E., Cecilio Rebola, L., ... & Antonelli, A. (2021). Ten golden rules for reforestation to optimize carbon sequestration, biodiversity recovery and livelihood benefits. Global Change Biology, 27(7), 1328-1348. https://doi.org/10.1111/gcb.15498↩↩2↩3
Ewers, R. M., Orme, C. D. L., Pearse, W. D., Zulkifli, N., Yvon-Durocher, G., Yusah, K. M., ... & Banks-Leite, C. (2024). Thresholds for adding degraded tropical forest to the conservation estate. Nature, 631(8022), 808-813. https://doi.org/10.1038/s41586-024-07657-w↩
Lindenmayer, D. B., & Luck, G. (2005). Synthesis: thresholds in conservation and management. Biological Conservation, 124(3), 351-354. https://doi.org/10.1016/j.biocon.2005.01.041↩
IUCN. 2024. The IUCN Red List of Threatened Species. Version 2024-1. https://www.iucnredlist.org. Accessed on [16 Oct. 2024]. ↩
Zhang, Y., Chen, H. Y., & Reich, P. B. (2012). Forest productivity increases with evenness, species richness and trait variation: a global meta‐analysis. Journal of ecology, 100(3), 742-749. https://doi.org/10.1111/j.1365-2745.2011.01944.x↩
Pagad, S., Bisset, S., Genovesi, P., Groom, Q., Hirsch, T., Jetz, W., ... & McGeoch, M. A. (2022). Country compendium of the global register of introduced and invasive species. Scientific Data, 9(1), 391. https://doi.org/10.1038/s41597-022-01514-z↩
van Kleunen, M., Pyšek, P., Dawson, W., Essl, F., Kreft, H., Pergl, J., ... & Winter, M. (2019). The global naturalized alien Flora (Glo NAF) database. ↩
Convention on Biological Diversity. (2002). Decision VI/23: Biodiversity and climate change. Retrieved from https://www.cbd.int/decision/cop/default.shtml?id=7197↩
Gann, G. D., McDonald, T., Walder, B., Aronson, J., Nelson, C. R., Jonson, J., ... & Dixon, K. (2019). International principles and standards for the practice of ecological restoration. Restoration ecology, 27(S1), S1-S46. https://doi.org/10.1111/rec.13035↩↩2
Höhl, M., Ahimbisibwe, V., Stanturf, J. A., Elsasser, P., Kleine, M., & Bolte, A. (2020). Forest landscape restoration—what generates failure and success?. Forests, 11(9), 938. https://doi.org/10.3390/f11090938↩↩2
United Nations General Assembly. (2007). United Nations declaration on the rights of indigenous peoples (A/RES/61/295). Retrieved from https://www.un.org/development/desa/indigenouspeoples/wp-content/uploads/sites/19/2018/11/UNDRIP_E_web.pdf↩
United Nations. (2016). Free, prior, and informed consent: An indigenous peoples’ right and a good practice for local communities. Retrieved from https://www.un.org/development/desa/indigenouspeoples/publications/2016/10/free-prior-and-informed-consent-an-indigenous-peoples-right-and-a-good-practice-for-local-communities-fao/↩
Life cycle modules as described in BS EN 15978:2011 Sustainability of construction works — Assessment of environmental performance of buildings — Calculation method. https://knowledge.bsigroup.com/products/sustainability-of-construction-works-assessment-of-environmental-performance-of-buildings-calculation-method?version=standard↩↩2↩3
IPCC, 2023: Climate Change 2023: Synthesis Report. Contribution of Working Groups I, II and III to the Sixth Assessment Report of the Intergovernmental Panel on Climate Change [Core Writing Team, H. Lee and J. Romero (eds.)]. IPCC, Geneva, Switzerland, pp. 35-115. https://doi.org/10.59327/IPCC/AR6-9789291691647↩↩2↩3
United States Energy Association (2022) Life Cycle Assessment of Carbon Dioxide Removal Methods Summary Report. Available at: https://usea.org/sites/default/files/USEA_CDR_LCA_SummaryReport_Final.pdf↩
Cooper, J., Dubey, L., & Hawkes, A. (2022). Life cycle assessment of negative emission technologies for effectiveness in carbon sequestration. Procedia CIRP, 105, 357-361. https://doi.org/10.1016/j.procir.2022.02.059↩
Lefebvre et al. (2021) Assessing the carbon capture potential of a reforestation project. Available at: https://www.nature.com/articles/s41598-021-99395-6↩
IPCC (2003) Good Practice Guidance for Land Use, Land-Use Change and Forestry. Available at: https://www.ipcc.ch/site/assets/uploads/2018/03/GPG_LULUCF_FULLEN.pdf↩
Doraisami, M., Kish, R., Paroshy, N. J., Domke, G. M., Thomas, S. C., & Martin, A. R. (2022). A global database of woody tissue carbon concentrations. Scientific Data, 9(1), 284. https://doi.org/10.1038/s41597-022-01396-1↩
Aalde, Harald. vol. 4, Nstitute for Global Environmental Strategies (IGES), 2006. IPCC Guidelines for National Greenhouse Gas Inventories: Agriculture, Forestry and Other Land Use. https://www.osti.gov/etdeweb/biblio/20880391↩↩2↩3
McGroddy, M. E., Daufresne, T., & Hedin, L. O. (2004). Scaling of C: N: P stoichiometry in forests worldwide: Implications of terrestrial redfield‐type ratios. Ecology, 85(9), 2390-2401. https://doi.org/10.1890/03-0351↩
Chave, J., Réjou‐Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M. S., Delitti, W. B., ... & Vieilledent, G. (2014). Improved allometric models to estimate the aboveground biomass of tropical trees. Global change biology, 20(10), 3177-3190. https://doi.org/10.1111/gcb.12629↩
White, J. (2013). A best practices guide for generating forest inventory attributes from airborne laser scanning data using an area-based approach (INFORMATION REPORT FI-X-010). Natural Resources Canada. https://ostr-backend-prod.azurewebsites.net/server/api/core/bitstreams/3eac62d1-8765-48cb-a48e-a777eb8ae015/content↩↩2↩3↩4↩5↩6↩7
Chave, J., Condit, R., Lao, S., Caspersen, J. P., Foster, R. B., & Hubbell, S. P. (2003). Spatial and temporal variation of biomass in a tropical forest: results from a large census plot in Panama. Journal of ecology, 91(2), 240-252. https://doi.org/10.1046/j.1365-2745.2003.00757.x↩↩2
Ploton, P., Mortier, F., Réjou-Méchain, M., Barbier, N., Picard, N., Rossi, V., ... & Pélissier, R. (2020). Spatial validation reveals poor predictive performance of large-scale ecological mapping models. Nature communications, 11(1), 4540. https://doi.org/10.1038/s41467-020-18321-y↩
Gao, S., Zhong, R., Yan, K., Ma, X., Chen, X., Pu, J., ... & Myneni, R. B. (2023). Evaluating the saturation effect of vegetation indices in forests using 3D radiative transfer simulations and satellite observations. Remote Sensing of Environment, 295, 113665. https://doi.org/10.1016/j.rse.2023.113665↩
An initial evaluation of carbon proxies for dynamic reforestation baselines. Pachama. Retrieved October 16, 2024, from https://pachama.com/blog/dynamic-reforestation-baselines/↩
Wilkinson, M. D., Dumontier, M., Aalbersberg, I. J., Appleton, G., Axton, M., Baak, A., ... & Mons, B. (2016). The FAIR Guiding Principles for scientific data management and stewardship. Scientific data, 3(1), 1-9. https://doi.org/10.1038/sdata.2016.18↩
Zolkos, S. G., Goetz, S. J., & Dubayah, R. (2013). A meta-analysis of terrestrial aboveground biomass estimation using lidar remote sensing. Remote sensing of environment, 128, 289-298. https://doi.org/10.1016/j.rse.2012.10.017↩↩2
Schwartzman, S., Lubowski, R. N., Pacala, S. W., Keohane, N. O., Kerr, S., Oppenheimer, M., & Hamburg, S. P. (2021). Environmental integrity of emissions reductions depends on scale and systemic changes, not sector of origin. Environ. Res. Lett, 16(9), 091001. https://doi.org/10.1088/1748-9326/ac18e8↩
Galik, C. S., Murray, B. C., Mitchell, S., & Cottle, P. (2016). Alternative approaches for addressing non-permanence in carbon projects: an application to afforestation and reforestation under the Clean Development Mechanism. Mitigation and adaptation strategies for global change, 21, 101-118. https://doi.org/10.1007/s11027-014-9573-4↩
Haya, B. K., Evans, S., Brown, L., Bukoski, J., Butsic, V., Cabiyo, B., ... & Sanchez, D. L. (2023). Comprehensive review of carbon quantification by improved forest management offset protocols. Frontiers in Forests and Global Change, 6, 958879. https://doi.org/10.3389/ffgc.2023.958879↩
Roberts, M. J., & Schlenker, W. (2013). Identifying supply and demand elasticities of agricultural commodities: Implications for the US ethanol mandate. American Economic Review, 103(6), 2265-2295. https://doi.org/10.1257/aer.103.6.2265↩
Akiyama, T., & Varangis, P. N. (1990). The impact of the International Coffee Agreement on producing countries. The World Bank Economic Review, 4(2), 157-173. https://doi.org/10.1093/wber/4.2.157↩
Askari, H., & Cummings, J. T. (1977). Estimating Agricultural Supply Response with the Nerlove Model: A Survey. International Economic Review, 18(2), 257. https://doi.org/10.2307/2525749↩
Jere Richard Behrman, 1965. "Cocoa: A Study of Demand Elasticities in the Five Leading Consuming Countries, 1950–1961," American Journal of Agricultural Economics, Agricultural and Applied Economics Association, 47(2), 410-417. https://ideas.repec.org/a/oup/ajagec/v47y1965i2p410-417..html↩
Fragoso, R. M. D. S., Marques, C., Lucas, M. R., Martins, M. D. B., & Jorge, R. (2011). The economic effects of common agricultural policy on Mediterranean montado/dehesa ecosystem. Journal of Policy Modeling, 33(2), 311-327. https://doi.org/10.1016/j.jpolmod.2010.12.007. ↩
Mintert, J. R., Tonsor, G. T., & Schroeder, T. C. (2009). US beef demand drivers and enhancement opportunities: a research summary. https://beef.unl.edu/beefreports/symp-2009-14-xxi.shtml↩
Jeong, S. (2019). The change in price elasticities in the US beef cattle industry and the impact of futures prices in estimating the price elasticities. Proceedings of the NCCC-134 Conference on Applied Commodity Price Analysis, Forecasting, and Market Risk Management. Minneapolis, MN. http://www.farmdoc.illinois.edu/nccc134↩
UN-REDD: Defintion of market leakage [Accessed October 2024]. Available at: https://www.un-redd.org/glossary/market-leakage#:~:text=Definition,actors%20to%20shift%20their%20activities↩
Pendrill, F., Persson, U. M., Godar, J., & Kastner, T. (2019). Deforestation displaced: trade in forest-risk commodities and the prospects for a global forest transition. Environmental Research Letters, 14(5), 055003. https://doi.org/10.1088/1748-9326/ab0d41↩
Lark, T. J., Hendricks, N. P., Smith, A., Pates, N., Spawn-Lee, S. A., Bougie, M., Booth, E. G., Kucharik, C. J., & Gibbs, H. K. (2022). Environmental outcomes of the US Renewable Fuel Standard. Proceedings of the National Academy of Sciences, 119(9). https://doi.org/10.1073/pnas.2101084119↩
Bowman, M. S., Soares-Filho, B. S., Merry, F. D., Nepstad, D. C., Rodrigues, H., & Almeida, O. T. (2012). Persistence of cattle ranching in the Brazilian Amazon: A spatial analysis of the rationale for beef production. Land use policy, 29(3), 558-568. https://doi.org/10.1016/j.landusepol.2011.09.009. ↩
Wu, Z., Satter, L., & Sojo, R. (2000). Milk production, reproductive performance, and fecal excretion of phosphorus by dairy cows fed three amounts of phosphorus. Journal of Dairy Science, 83(5), 1028–1041. https://doi.org/10.3168/jds.s0022-0302(00)74967-8↩
Coffee Barometer. In Coffee Barometer (pp. 1–36). https://hivos.org/assets/2018/06/Coffee-Barometer-2018.pdf↩
Pearson, T. R. (2007). Measurement guidelines for the sequestration of forest carbon (Vol. 18). US Department of Agriculture, Forest Service, Northern Research Station. https://doi.org/10.2737/NRS-GTR-18↩
Climate Action Reserve (2018). Standardized Inventory Methodlogy Version 1.0. https://www.climateactionreserve.org/wp-content/uploads/2018/06/Standardized-Inventory-Methodology_v1.0.pdf↩↩2
Phillips, O., Baker, T., Feldpausch, T., & Brienen, R., (2001). RAINFOR Field Manual for Plot Establisment and Remeasurement. https://forestplots.net/upload/ManualsEnglish/RAINFOR_field_manual_EN.pdf↩
Goodbody, T. R., Coops, N. C., Queinnec, M., White, J. C., Tompalski, P., Hudak, A. T., ... & Woods, M. E. (2023). sgsR: a structurally guided sampling toolbox for LiDAR-based forest inventories. Forestry, 96(4), 411-424. https://doi.org/10.1093/forestry/cpac055↩
Queinnec, M., Coops, N. C., White, J. C., McCartney, G., & Sinclair, I. (2022). Developing a forest inventory approach using airborne single photon lidar data: from ground plot selection to forest attribute prediction. Forestry: An International Journal of Forest Research, 95(3), 347-362. https://doi.org/10.1093/forestry/cpab051↩
Ayrey, E., Hayes, D. J., Kilbride, J. B., Fraver, S., Kershaw, J. A., Cook, B. D., & Weiskittel, A. R. (2021). Synthesizing disparate LiDAR and satellite datasets through deep learning to generate wall-to-wall regional inventories for the complex, mixed-species forests of the eastern United States. Remote Sensing, 13(24), 5113. https://doi.org/10.3390/rs13245113↩
Meyer, H., & Pebesma, E. (2021). Predicting into unknown space? Estimating the area of applicability of spatial prediction models. Methods in Ecology and Evolution, 12(9), 1620-1633. https://doi.org/10.1111/2041-210X.13650↩
Johnson, L. K., Mahoney, M. J., Bevilacqua, E., Stehman, S. V., Domke, G. M., & Beier, C. M. (2022). Fine-resolution landscape-scale biomass mapping using a spatiotemporal patchwork of LiDAR coverages. International Journal of Applied Earth Observation and Geoinformation, 114, 103059. https://doi.org/10.1016/j.jag.2022.103059↩
Pflugmacher, D., Cohen, W. B., Kennedy, R. E., & Yang, Z. (2014). Using Landsat-derived disturbance and recovery history and lidar to map forest biomass dynamics. Remote Sensing of Environment, 151, 124-137. https://doi.org/10.1016/j.rse.2013.05.033↩
Pickell, P. D., Hermosilla, T., Frazier, R. J., Coops, N. C., & Wulder, M. A. (2016). Forest recovery trends derived from Landsat time series for North American boreal forests. International Journal of Remote Sensing, 37(1), 138-149. https://doi.org/10.1080/2150704X.2015.1126375↩
McConville, K.S., Moisen, G. G., & Frescino, T. S. (2020). A Tutorial on Model-Assisted Estimation with Application to Forest Inventory. Forests. 11(2), 244. https://doi.org/10.3390/f11020244↩
Westfall, J. A., Coulston, J. W., Gray, A. N., Shaw, J. D., Radtke, P. J., Walker, D. M., Weiskittel, A. R., MacFarlane, D. W., Affleck, D. L., Zhao, D., Temesgen, H., Poudel, K. P., Frank, J. M., Prisley, S. P., Wang, Y., Meador, A. J. S., Auty, D., & Domke, G. M. (2023). A national-scale tree volume, biomass, and carbon modeling system for the United States. https://doi.org/10.2737/wo-gtr-104↩
Masiliūnas, D., Tsendbazar, N. E., Herold, M., Lesiv, M., Buchhorn, M., & Verbesselt, J. (2021). Global land characterisation using land cover fractions at 100 m resolution. Remote Sensing of Environment, 259, 112409. https://doi.org/10.1016/j.rse.2021.112409. ↩
Captain, N., Xu, P., Herold, M., Lesiv, M., Duerauer, M., Ruben Van De Kerchove, VITO, & Olivier Arino. (2022). Product Validation report. https://worldcover2021.esa.int/data/docs/WorldCover_PVR_V2.0.pdf↩
Brown, C. F., Brumby, S. P., Guzder-Williams, B., Birch, T., Hyde, S. B., Mazzariello, J., Czerwinski, W., Pasquarella, V. J., Haertel, R., Ilyushchenko, S., Schwehr, K., Weisse, M., Stolle, F., Hanson, C., Guinan, O., Moore, R., & Tait, A. M. (2022). Dynamic World, Near real-time global 10 m land use land cover mapping. Scientific Data, 9(1). https://doi.org/10.1038/s41597-022-01307-4↩
Venter, Z. S., Barton, D. N., Chakraborty, T., Simensen, T., & Singh, G. (2022). Global 10 m land use land cover datasets: A comparison of dynamic world, world cover and esri land cover. Remote Sensing, 14(16), 4101. https://doi.org/10.3390/rs14164101↩