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 agroforestry. In the context of this Protocol, we draw on the definition of Terasaki Hart, et al., (2023)1 and define agroforestry as the intentional establishment or increase in woody cover integrated within agricultural landscapes, providing additional net carbon 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”.) against a counterfactual (An assessment of what would have happened in the absence of a particular intervention – i.e., assuming the Baseline scenario.)baseline (A set of data describing pre-intervention or control conditions to be used as a reference scenario for comparison.).
The carbon removal potential for agroforestry globally has been estimated to be as high as 0.31 Pg yr[math: ^{-1}], which is comparable to other nature-based climate solutions like reforestation2. In addition to climate mitigation, effective agroforestry practices can also provide other environmental and social benefits, including supporting local climate resilience, increasing food security, enhancing soil and water conservation, and generating supplemental income for local communities3, 4, 5. Despite potential benefits, implementation of agroforestry practices can often be limited by a lack of capital, as well as technical knowledge gaps6. As such, Carbon Finance (Resources provided to projects that are generating, or are expected to generate, greenhouse gas (GHG) Emission Reductions or Removals.) presents an opportunity for realizing the climate mitigation potential of agroforestry, as well as the co-benefits for local communities.
This Protocol applies to a variety of agroforestry practices, which may be implemented within existing agricultural systems or as new agroforestry systems on previously unproductive land. Following the definition above, Project (An activity or process or group of activities or processes that alter the condition of a Baseline and leads to Removals or Reductions.)activities (The steps of a Project Proponent’s Removal or Reduction process that result in carbon fluxes. The carbon flux associated with an activity is a component of the Project Proponent’s Protocol.) must involve the establishment or increase in woody cover within the new or existing agricultural system. Using common terminology for agroforestry practices, examples of such eligible activities include, but are not limited to:
This Protocol and the eligibility requirements are further designed to ensure that all project activities support the goal of climate mitigation and other co-benefits, while avoiding agroforestry practices that can be counterproductive towards these goals7.
This Protocol accounts for the quantification of the gross amount of CO2 removed via growth of woody vegetation in agroforestry systems, 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 (The term used to describe greenhouse gas emissions to the atmosphere as a result of Project activities.) 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 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:
This Protocol and all standardized approaches therein — including but not limited to the dynamic baseline (see Section 9.4) — are informed by the best available scientific knowledge and undergo external review by subject matter experts (Someone with extensive knowledge and/or skills in a particular domain as demonstrated by education, training, certifications, and/or experience carrying out closely related work.) and relevant stakeholders (Any person or entity who can potentially affect or be affected by Isometric or an individual Project activity.). All comments received during consultation are publicly addressed, with revisions incorporated as appropriate, to ensure the certified version of the Protocol will yield high quality Carbon Credits via rigorous, conservative (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.), and appropriate methodologies.
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 agroforestry activities and long-term monitoring of agroforestry 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 D.
Additionally, this Protocol will be reviewed when there is an update to published scientific literature, government policies, or legal requirements which would affect net CO2e removal quantification or the monitoring guidelines outlined in this Protocol, or at a minimum of every 2 years.
This Protocol aims to guide Projects that establish agroforestry systems which support sustainable production, ecosystem services, and local livelihoods while also being resilient to future climate scenarios. Projects must maintain or enhance 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.) in tandem with supporting agricultural activity. Agricultural production must be a primary component of The Project, demonstrated by either the majority of the land (>50%) within the project area or a minimum of 500 ha being dedicated to the production of at least one non-timber commodity. In this context, productive land is considered to be any land area which is used for the production of one or more non-timber commodities, including, but not limited to, areas planted with crops/commodity producing trees (non-commodity producing vegetation may be intermixed) or area used for grazing. This may be either through establishing new productive capacity, or via agricultural productivity that was in place prior to project initiation and will be continued for the duration of the Crediting Period (The period of time over which a Project Design Document is valid, and over which Removals or Reductions may be Verified, resulting in Issued Credits.). Commodities produced within the project area may be used for subsistence, or may be commercially sold. However, the fate of woody vegetation should not be clear-cutting for timber sale, even beyond the Project Commitment Period. Selective harvesting and production of timber commodities is permissible under this Protocol, but all harvesting plans must be approved by Isometric following consultation. Further, while production of timber commodities is allowable, other non-timber commodities must be the primary product(s) of the working landscape.
The geographic Project Boundary (The defined temporal and geographical boundary of a Project.) must encompass all geographic areas where the Project Proponent (The organization that develops and/or has overall legal ownership or control of a Removal or Reduction Project.) is conducting agroforestry activities for crediting purposes. This can consist of a collection of discrete planting areas, or a single continuous area. In the context of this Protocol, a discrete planting area is considered to be the largest contiguous land area which is subject to the same Project and management activities (e.g., a smallholder farm, land parcel) and can be no smaller than 0.2 ha. This Protocol applies across the temporal (see Section 5.0) and spatial scope of The Project. The Project Boundary must be set at the time of project initiation and cannot be modified beyond the addition of new areas to The Project once the crediting period begins. Any adjacent planting activities or land management by the Project Proponent must be disclosed with justification and evidence that they do not pose any risks to the agroforestry activities within the Project Boundary.
In order to support 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.), demonstrate additionality (An evaluation of the likelihood that an intervention—for example, a CDR Project—causes a climate benefit above and beyond what would have happened in a no-intervention Baseline scenario.), and ensure trust and transparency, it is incumbent upon Projects to adhere to the following requirements, which must be demonstrated in the Project Design Document (The document, written by a Project Proponent, which records key characteristics of a Project and which forms the basis for Project Validation and evaluation in accordance with the relevant Certified Protocol. (Also known as “PDD”).):
Land cover data sources derived from remote sensing and used for land cover classification 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:
Requirements. Projects must provide the following to evidence the length of the Project Commitment Period (see Section 11)
Land tenure and contractual obligation. To ensure the Project Proponent has proper authorization from the true property ownership, this Protocol explicitly prohibits lessees or concessionaires from enrolling land for Credits without the landowner's signatory consent, which must be provided in the PDD (The document that clearly outlines how a Project will generate rigorously quantifiable Additional high-quality Removals or Reductions.). The Project Proponent must have legal, documented land tenure for the duration of the Crediting Period and should have access to the project area throughout any Ongoing Monitoring Period for the purposes of meeting the Reversal reporting requirements under Section 10.5.2; or, if the Project Proponent is contracting on land owned by another party, the landowners must have legal, documented land tenure for the duration of the Crediting Period and the Project Proponent should have access to the land throughout any Ongoing Monitoring Period to perform all requirements set forth by this Protocol and Module (Independent components of Isometric Certified Protocols which are transferable between and applicable to different Protocols.)(s) the Project Proponent is crediting against. Additionally, Project Proponents are liable for the maintenance of the agroforestry system carbon stocks throughout the Project Commitment Period in accordance with the requirements of this Protocol and applicable Modules. If the Project Proponent is contracting on smallholder land, smallholders should be contractually obligated to maintain the agroforestry system carbon stocks in accordance with the requirements of this Protocol and applicable Modules.
Financial plan. Credit issuances (Certificates are issued to the Certificate Account of a Project Proponent with whom Isometric has a Validated Protocol after an Order for Verification and Certificate Issuance services from a Buyer and once a Verified Removal or Reduction has taken place.) will decrease over time, and continued financial payments are needed to incentivize maintenance of carbon stocks. To evidence the continued financial viability of The Project over the full Project Commitment Period, Project Proponents must provide a financial model and cash flow statement which demonstrates a clear payment structure for the duration of the Project Commitment Period. Methods to maintain continued financial incentives may include, but are not limited to:
If operational, legal, or regulatory constraints preclude the development of a financial model or negate its efficacy for supporting long-term maintenance, the Project Proponent must provide justification for the absence of a financially-based plan for long-term maintenance, as well as details of what alternative mechanisms will be in place to support maintenance of the Project carbon stocks over the full Project Commitment Period. Such mechanisms may include, but are not limited to, conservation easements, governmental protections, or land trusts.
The Durability of Credits is set to one half the length of the Project Commitment Period. As such, the Project Commitment Period must be set at the time of PDD submission. If the initial Crediting Period is less than the Project Commitment Period, the Crediting Period may be extended up to the duration of the Project Commitment Period. If the initial Crediting Period is not extended, the remainder of the Project Commitment Period must consist of an Ongoing Monitoring Period. For grouped projects, the Project Commitment Period must be the same duration for all areas, but Crediting Period and Ongoing Monitoring Period duration may vary across individual areas to reflect differences in land tenure.
If Projects elect to have an Ongoing Monitoring Period that is longer in duration than the initial Crediting Period, the Durability may be set to the length of the Ongoing Monitoring Period. Project Proponents must commit to this durability labeling and the length of the Ongoing Monitoring Period at the time of PDD submission. In this scenario, the Project Commitment Period may be extended at a later time if the Crediting Period is extended, but the Ongoing Monitoring Period must remain the same as the initial commitment at PDD submission.
Project A is a smallholder agroforestry project. It sets a Project Commitment Period of 40 years, with an initial Crediting Period of 20 years for all enrolled properties. At the end of the initial Crediting Period, most of the properties renew their enrollment for another 20 years and continue to accumulate Credits for the remainder of the Project Commitment Period. The remaining properties which did not renew their enrollment enter an Ongoing Monitoring Period to monitor for Reversals for the remaining 20 years of the Project Commitment Period. Monitoring for quantification is conducted by the Project Proponent through the Crediting Period for each enrolled property, and the reported activities are verified by a Validation and Verification Body (VVB) for each Reporting Period. For properties under an Ongoing Monitoring Period, Isometric conducts monitoring, and, if a Reversal is detected, the Project Proponent is required to complete reporting (see Section 10.5.2) All Credits from Project A have a durability of 20 years, equivalent to half of the 40 year Project Commitment Period.
Project B is an agroforestry project that commits to an initial Crediting Period of 30 years and an Ongoing Monitoring Period of 40 years at the time of PDD submission. The Project Proponent elects to use the Ongoing Monitoring Period as the basis for Durability, equating to 40 years for all Credits. Crediting activities proceed as in the prior example during the initial Crediting Period. At the end of the initial Crediting Period, the Project Proponent may extend the Crediting Period, but this is done via extension of the Project Commitment Period and the duration of the Ongoing Monitoring Period is maintained. The Ongoing Monitoring Period commences at the end of the Crediting 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. Project Proponents must conduct required procedures and assessments with relevant stakeholders to identify and subsequently mitigate social risks, while further meeting requirements within the Protocol designed to ensure projects support local livelihoods. 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 compliance 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 development12. 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, 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. While not all projects under this Protocol will necessarily result in land use change, these risks are still relevant to projects where there will be changes in land cover within existing agricultural use. As such, these requirements will apply to all projects, regardless of whether or not there is a change in land use. The values, along with corresponding requirements for Project Proponents to uphold them, are listed below:
Species Diversity: Rare, threatened, endangered, or endemic species, at populations significant to regional, national, or global levels.
Landscape-level ecosystems, ecosystem mosaics and intact native landscapes: Broad-scale regions of interacting ecosystems which contain species in their natural patterns or distributions at populations significant on regional, national, or global scales.
Ecosystems and habitats: Rare, threatened, or endangered ecosystems or habitats.
Ecosystem services: Fundamental ecosystem functions critical to ecological integrity and life, e.g., oxygen production, water filtration and protection of catchments, soil formation and erosion prevention, temperature regulation, nutrient cycling, habitat formation, provisioning of food and forage for fauna, etc.
Community needs: Commodities, resources, and community functions that are necessary for the livelihoods of local communities and Indigenous Peoples. This may include food, water, and infrastructure sources.
Cultural values: Sites, landscapes, and habitats of significant cultural, historical, religious, economic, or archaeological value to local communities, Indigenous Peoples, or other groups identified to engage in those locations.
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 within the project boundary 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 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.
While the aim of agroforestry systems is not necessarily to restore native ecosystems, agroforestry projects must not harm biodiversity and should aim to enhance biodiversity, when possible. At a minimum, Projects must not resemble large-scale commercial monoculture agriculture (see Section 4.0), but should incorporate more diverse planting, as is operationally practical. In addition to broadly enhancing ecosystem benefits, more diverse plantings can support greater resilience and productivity within the agroforestry system and greater carbon storage14, 15.
Recognizing that small-scale working landscapes may face operational limitations that preclude proper management of a high number of species, the minimum number of species for inclusion in the planting plan is applied at the level of discrete planting areas within The Project (see Section 4.0), and is dependent on the size of the discrete planting area. If a Project is composed of a single continuous area, these thresholds apply to the total project area. The minimum number of species are as follows:
To further illustrate with an example, a Project which consists of a single continuous area of 200 ha must have a minimum of 5 species planted throughout the project area. In another example, a Project consisting of a collection of smallholder farms, each ranging from 5 to 30 ha in size, can be considered. For this Project, all smallholder farms less than 25 ha in size may be planted must have a minimum of 3 species, whereas all the remaining smallholder farms between 25 and 30 ha in size must have a minimum of 4 species.
These minimums are inclusive of both woody and non-woody vegetation (e.g., crops), and include both any new species planted, as well as any pre-existing species which will be maintained as part of project activities. Potential exceptions can be made in consultation with Isometric for a lower number of species if the Project Proponent can provide evidence to demonstrate that a lower number of species is both operationally necessary and not a threat to local biodiversity.
The species used for agroforestry must follow the principles outlined below.
The Project Proponent must list all vegetation species (both woody and non-woody) planted and/or maintained in the project area via project activities in the PDD. For vegetation not supporting commodity production, selected species must be native, naturalized, or non-native range-expanding species (see definitions below). For commodity producing vegetation or vegetation which provides services that directly supports commodity production (e.g., nitrogen fixation), non-native species may be used. All planted species must meet the following requirements:
Project Proponents are highly encouraged to consult with external subject matter experts to ensure that species included in the agroforestry 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:
Non-native range-expanding species are defined as:
The use of any genetically-modified species must be disclosed within the PDD. Genetically-modified species are defined as:
If genetically-modified species are included in the agroforestry planting plan, Project Proponents must submit a justification explaining their use. This should cover why alternative non-genetically-modified species are not used and how biodiversity is safeguarded from the use of genetically-modified species.
A robust seedling and germplasm pipeline is central to the ecological, socioeconomic, and cultural success of an agroforestry project. A diverse, local, and sustainable pipeline ensures that project activities maintain ecosystem function and integrity, 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 agroforestry projects creates community buy-in, providing long-term commitment and investment in the success of forestry-based projects 19, 12. 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 must assess if Indigenous Peoples will be impacted by project activities. Impacts may include, but are not limited to:
This assessment must incorporate analysis of reputable, independent data conducted by a subject matter expert or be conducted by a reputable third party subject matter expert. The results of this assessment must be included in the PDD. If the assessment 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 Peoples20 in 2007 and expanded upon by the Food and Agriculture Organization of the United Nations in 201621. If there are no identified potential impacts on Indigenous Peoples, the Project Proponents are still encouraged to complete a Stakeholder Engagement Plan consistent with FPIC principles. FPIC principles include:
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 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:
Additional requirements apply to any projects which operate via partnerships with smallholder landowners. We note that there is no standard definition of the term smallholder, and the land area of these farms can be variable across the globe22. In the context of this Protocol, smallholder landowners are considered to be individuals who hold rights to the land and play a primary role in management activities occurring within the land. Projects which operate via a collection of separate land agreements which are held directly with such landowners will be considered to be operating via a smallholder arrangement and subject to the following requirements. Project Proponents must follow the same stakeholder engagement plan and principles of FPIC described in Section 6.5.1 for all enrolled landowners.
It is vital that enrolled landowners understand the contracts they are entering into as part of The Project. As part of this stakeholder engagement and FPIC process, Project Proponents must disclose the following to enrolled landowner(s) and ensure that these landowner(s) understand:
In regards to revenue sharing agreements, Project Proponent must disburse a minimum of 20% of the revenues generated from Credits issued under The Project to enrolled landowners over the lifetime of The Project.
Eligible forms of revenue sharing include:
All of these must be provided to landowners at an individual level and any non-monetary, in-kind components must involve a transfer of ownership to the landowner. If any of these are contingent upon the landowner meeting particular requirements (e.g., maintenance of system), those requirements must be clearly communicated to landowners at the time of the initial agreement and disclosed in the PDD. At PDD submission, Project Proponents must provide details of the systems which will be used for benefit distribution and the documentation which will be produced for tracking distribution (e.g., digital payment records, other documentation in absence of formal financial systems). These systems must also include a mechanism for landowners to report any grievances or disputes related to revenue sharing and for the tracking of the response and resolution of these issues.
Project Proponents must provide an anticipated timeline of how revenue sharing will be distributed over the duration of The Project in the PDD. At every verification, Project Proponents must provide evidence demonstrating progress on the revenue sharing plans, including proof of payments and benefit distribution, and report any grievances raised by landowners via the reporting system and subsequent responses and resolution by the Project Proponents. Projects which fail to provide sufficient evidence and/or reporting may be required to undergo an audit by an independent certified financial auditor. If at any verification the cumulative revenue sharing has fallen >20% below the level at which it was projected to be at for that time in the initial plan at PDD submission, the Project Proponent must submit an updated revenue sharing plan and timeline to demonstrate how The Project will meet the revenue sharing required by this Protocol and their agreements with landowners. This revised plan will be used as the benchmark for subsequent verifications.
Revenue sharing percentages should be made public, including percent revenue or Credits divided among each party (e.g., Project Proponent, enrolled landowner(s), insurance provider(s), and other documented parties listed in the PDD).
Project Proponents must also disclose within the PDD what training and/or assistance will be provided to enrolled landowners to support proper management of the agroforestry system. These plans should be informed by engagement with the enrolled landowners, and address any needs or risks that are identified through this process.
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 an agroforestry project. Community buy-in may be established when stakeholders are properly informed about the benefits they can expect from the agroforestry 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 6.5.1. 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 Project must not harm the quantity or quality of local water resources. While implementation of agroforestry practices can support water conservation in existing agricultural areas, increasing tree cover also introduces new water demands into the landscape. Even in ecosystems that previously held forest cover, significantly increasing tree cover can alter the hydrological balance in ways that can be detrimental to surrounding communities if there are pre-existing strains on water resources. Project Proponents must assess whether The Project is occurring in an area that already has existing risks to its water supply as a result of the combination of water supply and demand. Within this Protocol, we define these areas of elevated water risk to be basins which have been categorized as “High” or “Extremely High” Baseline Annual Physical Risk for Water Quantity by the [Aqueduct Water Risk Atlas](https://www.wri.org/applications/aqueduct/water-risk-atlas/ ?advanced=false&basemap=hydro&indicator=w_awr_def_tot_cat&lat=-14.445396942837744&lng=-142.85354599620152&mapMode=view&month=1&opacity=0.5&ponderation=DEF&predefined=false&projection=absolute&scenario=optimistic&scope=baseline&timeScale=annual&year=baseline&zoom=2)23.
If The Project is occurring in an area with existing elevated water risk per the above criteria, the Project Proponent must assess whether reforestation in the project area is projected to have a negative impact on water supply. The Project Proponent must identify if the project area lies in areas at risk of >1% decrease in water availability due to reforestation as described by Hoek van Diejke et al. (2022)24. While agroforestry systems will not necessarily result in the same increase in tree cover density as reforestation, the scenario of reforestation results in a conservative estimate of the hydrological impact of increasing tree cover density. In regards to these analyses and for the purposes of this Protocol, The Project presents a risk to water supplies if it is projected to decrease annual water yield by more than 1% in the Hoek van Diejke et al. dataset, inclusive of any evaporative recycling effects.
If The Project is occurring in an area with both elevated water risk and where reforestation (as a proxy (A measurement which correlates with but is not a direct measurement of the variable of interest.) for agroforestry) is anticipated to decrease local water yields per the above definitions, Project Proponents must provide details in the PDD of how their project implementation and management plans are designed to limit hydrological impacts and include provisions for monitoring any adverse effects on local water resources. These plans could include, but are not limited to:
Project Proponents should not use synthetic herbicides or fertilizers for agroforestry system management during the Crediting Period. Any use of synthetic herbicides or fertilizers must be reported to Isometric and adhere to best management practices (BMPs) as well as all local, state/provincial, and national laws and regulations regarding their use. Any planned use for project establishment at project initiation or project operations must be reported in the PDD.
Projects should not use synthetic pesticides except for the control of non-native pests and/or invasive insect outbreaks. Any such use of synthetic pesticides must be targeted and limited in scope towards the targeted pest(s) or insect(s), and be thoroughly justified and reported immediately to Isometric. Further, any such use must adhere to BMPs as well as all local, state/provincial, and national laws and regulations regarding their use. Any planned use for project establishment at project initiation must be reported in the PDD. Additionally, Project Proponents must adhere to the Forest Stewardship Council’s Pesticides Policy.
The emissions associated with any use of synthetic herbicides, fertilizers, and pesticides must be accounted for in line with the emissions accounting requirements of Section 9.5.
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:
As part of this evaluation, the VVB must also review the characterization and quantification of all individual uncertainty sources within the listed components that contribute to the calculation of net CO2e removal.
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 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 during the first Validation or Verification of a Project, to the project site(s). Validators should, whenever possible, observe project operation to ensure full documentation of process inputs and outputs through visual observation and validation of instrumentation, measurements, and required data quality measures.
A site visit must occur at least once during each Project Validation. Additional site visits may be required if there are substantial changes to field operations over the course of a Project's Validation period, 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 agroforestry and management of agricultural systems, including both field measurements and Earth System remote sensing data processing and analysis. Verification teams must also demonstrate competence in assessing stakeholder engagement processes.
CDR via agroforestry is a result of a multi-step process (e.g., seed planting, system maintenance, monitoring), with activities in each step potentially managed by a different operator, company, or owner. Further, agroforestry projects can also often involve a coalition of smallholder landowners. 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 Materiality 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 scenario and Counterfactual utilized to assess additionality must be project-specific and comply with Section 9.4.
Projects must not occur in regions where significant agroforestry activities are driven by market demand, local and/or national incentives, or agricultural policies that would lead to similar agroforestry practices without Carbon Finance.
Government subsidies or civil contractual obligations for agroforestry, such as organization bylaws, inhibit additionality and fall under the Regulatory criteria in Section 2.5.3 of the Isometric Standard. Additionality is assessed each Reporting Period using dynamic baselining (A method for establishing and regularly updating the reference carbon stock levels in a reforestation project area, based on ongoing analysis of comparable non-project plots, to account for natural fluctuations and improve the accuracy of carbon credit calculations over the project lifetime.) as outlined in Section 9.4.
All projects must demonstrate the necessity of Carbon Finance for project viability following Section 2.5.3 of the Isometric Standard. If any revenue will be produced from commodity production within the project area or sources other than Removals, additional requirements for demonstrating financial additionality (An evaluation of the likelihood that an intervention that causes a climate benefit above and beyond what would have happened in a no-intervention Baseline scenario was the result of revenues from carbon finance.) are described in Section 2.5.3.2 of the Isometric Standard.
Financial Additionality must be reconsidered at Crediting Period renewal, in accordance with the requirements in this section. Projects must select one of the following options to meet ongoing Financial Additionality:
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.
Where a Project’s existing Financial Additionality demonstration was conducted over a defined investment horizon, the existing Financial Additionality determination remains valid up to the end of that investment horizon, provided The Project can demonstrate that key economic and operational assumptions used in the original demonstration remain materially unchanged. Projects which continue under an existing Financial Additionality determination in this way may only do so until the end of the investment horizon considered in the original determination, and must reassess Financial Additionality at the first verification event following the end of the existing investment horizon period.
Reassessment of Financial Additionality is required if any of the following conditions apply:
Where reassessment is required in accordance with the above requirements, the Project Proponent must demonstrate that continued Carbon Finance remains necessary to continue project crediting activities, by conducting a full Financial Additionality assessment against the updated Project and baseline scenarios.
The following steps must be taken to demonstrate that without Carbon Finance the project activity is not Common Practice, in accordance with the requirements defined in Section 2.5.3.1 of the Isometric Standard.
a) Survey-based approach:
b) Data from existing literature: Statistics on agroforestry activities derived from data collected within five years of the project start date may be used for this demonstration, provided they are relevant to the project area, do not distinguish between activities incentivized by and not incentivized by Carbon Finance (thus are conservative), and are publicly available as:
In accordance with Section 2.5.3.1 of the Isometric Standard, the proposed Project activity is considered to demonstrate Common Practice additionality where the market penetration rate is below or equal to 20%.
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: CO_2e_{Removal,RP}], must be conservatively 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 individual 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 each individual 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. Variables may be omitted from the sensitivity analysis if they are already being included in the uncertainty analysis. 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, and VVB) where it is subject to confidentiality. This includes emission factors, specific data, and/or proprietary models from licensed databases. Restrictions can also be requested when working with smallholder landowners when it is necessary for protecting landowner privacy. 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 (Sources, Sinks and Reservoirs)) associated with an agroforestry project.
A cradle-to-grave GHG Statement must be prepared encompassing the GHG emissions relating to the activities outlined within the system boundary.
GHG emissions and removals associated with The Project may be direct emissions (Emissions that are produced by a specific CDR process and are directly controllable.) from a process, or indirect emissions from combustion of fuels, electricity generation, or other sources. Emissions must include all GHG SSRs within the system boundary, from the construction or manufacturing of each physical site and associated equipment, closure and disposal of each site and associated equipment, and operation of each process, including embodied emissions (Life cycle GHG emissions associated with production of materials, transportation, and construction or other processes for goods or buildings.) of equipment and consumables used in The Project. The Project Proponent is responsible for identifying all sources of emissions directly or indirectly related to project activities.
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 relevant GHG SSRs controlled, related and affected by The Project, including but not limited to the SSRs set out 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 provided in the PDD.
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 A1-325). 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 A425). | ||
| Planting and installation | All GHGs | Emissions related to construction and installation of the project site(s) (Lifecycle Module A525). 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. Projects should limit soil inversions during project establishment to < 25 cm (See Section 4.3). | ||
| Misc. | All GHGs | Any SSRs not captured by categories above (e.g., staff travel). | ||
| Operations | Fertilizer use (Direct) | N2O | Direct emissions 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). |
| Agroforestry management | All GHGs | Emissions related to agroforestry management activities (e.g., pruning, weeding, pest control, biomass burning and watering, harvesting). 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. | ||
| Additional activities to maintain productivity | All GHGs | Additional GHG emissions resulting from increased resource use required to sustain baseline productivity levels. See Section 8.1.1.1 | ||
| Monitoring, Reporting, and Verification (MRV) | 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). |
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 in Section 8.3.
Agroforestry project activities may be integrated into existing operations, such as planting trees between crops. Activities that were already occurring, and would continue to occur in the absence of The Project, may be omitted from the system boundary of the GHG accounting if evidence of this is provided.
Project Proponents must assess and include any emissions associated with additional resources needed to maintain productivity at pre-project levels. For example, in alley cropping crops and trees may compete for soil nutrients, leading to crops requiring more fertilizer to maintain the same level of productivity. GHG emissions associated with the use of additional fertilizer must be assessed and included in the GHG statement.
In line with the GHG Accounting Module v1.0, The Project 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 (N20) and fluorinated gasses such as hydrofluorocarbons (HFCs), perfluorocarbons (PFCs), sulfur hexafluoride (SF6) and nitrogen trifluoride (NF3). For CO2 stored, only CO2 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 consumption;
The Baseline scenario for agroforestry assumes that the activities associated with The Project do not take place, and that any pre-existing cropland-based and livestock-based activities where The Project is located keep occurring.
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 agroforestry projects. They include increases in GHG emissions as a result of agroforestry projects displacing emissions or causing a secondary effect that increases emissions elsewhere. Three key types of leakage can occur for agroforestry 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. Section 6.6 requires assessment of whether The Project presents a risk to water resources, and requires mitigation and management plans be put in place if risks are present, making adverse hydrological impacts unlikely. 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. This Protocol introduces a framework specifically for agroforestry systems, which can generate agricultural and silvicultural commodities alongside carbon removals. This in-project production can serve as a direct countermeasure to leakage by replacing or exceeding the productivity that was displaced by the roject's establishment.
The overall process for addressing activity-shifting and market leakage is set out in the flowchart in Figure 1.
[Image: **Figure 1** Leakage assessment flow chart]
Figure 1. Flowchart of process for addressing activity-shifting and market leakage.
The flowchart is based on the following principles:
Implementation of the flowchart in Figure 1 requires an understanding of Net-Project Productivity, [math: NPP], 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.
For agroforestry projects, the Net Project Productivity ([math: NPP]) must be calculated for each commodity type. [math: NPP] compares the productivity displaced by The Project with the new productivity generated by the agroforestry system itself.
The Net Project Productivity is calculated for each commodity type, c, as follows:
[math: NPP_c=max ( PPP_c-PSP_c , 0)]
(Equation 1)
Where:
For the purposes of leakage accounting, [math: PSP] includes:
For the purposes of leakage accounting, [math: PSP] excludes:
Netting [math: PPP] with [math: PSP] is permitted only if all the following conditions are met:
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) prior to The Project. 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 displaced commodity and whether it was:
The Project Proponent must determine this using the following information:
If it is not possible to determine whether the displaced 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 agroforestry practices, or the project start date, whichever is earlier.
In addition, Isometric will undertake remote sensing analysis on project sites which claim that 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].
Agroforestry projects can generate agricultural or silvicultural commodities. This production within the project boundary is defined as Project-Scenario Productivity ([math: PSP]). [math: PSP] can serve as a countermeasure to leakage through on-site mitigation actions. Therefore, the quantification of PSP is fundamental as it is used to mitigate the leakage risk calculated from displaced pre-project activities.
The Project Proponent must quantify the [math: PSP] for each commodity type produced within the project system. [math: PSP] projected average annual production expected from eligible commodities within the agroforestry system. This must be presented in appropriate units (e.g. tonnes / yr).
Only commodities and production that meet the Leakage eligibility criteria outlined in Section 8.3.2 may be included in [math: PSP] for leakage accounting. Yields from Project trees themselves (e.g., nuts, fruit, timber) must not be included in [math: PSP] for leakage accounting.
The data for determining [math: PSP] should be farm records, including physical production records and accounts for crops, livestock, poultry and timber, and financial logs including income and expense records and receipts. Farm records may include traditional activity log data, or data from technology like smart tractors and GPS tags on cattle.
When claiming prospective [math: PSP], the Project Proponent must provide a transparent and justifiable estimate in the PDD. This estimate must be specific to the commodities, practices, and timeline of the Project. The estimation must include:
To safeguard against over-crediting, any project that uses prospective PSP estimates to calculate leakage must perform a mandatory ex-post reconciliation upon system maturity. This process compares the estimated productivity with the realized productivity once the system has matured. The following procedure must be followed:
All assumptions, models, and data sources used to quantify [math: PSP] must be transparently documented and justified in the PDD.
Where [math: PSP] is significantly lower than projected [math: PSP], and the shortfall is primarily due to exogenous natural causes beyond the reasonable control of The Project (such as extreme weather events, drought, flooding, hail, or region-wide pest or disease outbreaks), [math: PSP] performance may be evaluated in a broader regional context.
In such circumstances, Project Proponents must provide evidence demonstrating that:
Evidence may include, but is not limited to:
Where Isometric determines that the [math: PSP] shortfall is predominantly attributable to exogenous natural causes, Isometric may adjust the evaluation of realized [math: PSP] for the purposes of leakage reconciliation, including by applying a counterfactual estimate of [math: PSP] that reflects regional yield impacts.
[math: CO_2e_{Leakage}] is part of the calculation of [math: CO_2e_{Emissions}], as set out 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 2)
Where:
[math: CO_2e_{Leakage}] is quantified for every Reporting Period, however the following should be noted:
This section only applies for commodity types [math: NPP_c] is greater than zero (Section 8.3.2). Where [math: NPP_c] is zero or negative, The Project has achieved full leakage mitigation through its own productivity ([math: PSP]) and does not require a Leakage Mitigation Site (The site(s) where leakage mitigation activities take place.) or a market leakage emissions deduction.
Where [math: NPP_c] is greater than zero, the Project Proponent may implement external leakage mitigation activities to cover the remaining deficit by establishing a Leakage Mitigation Site (off-site). If used, standard yield intensification requirements apply to the off-site area, as set out in Sections 8.3.3.1 and 8.3.3.2.
Leakage mitigation must take place in areas called Leakage Mitigation Sites. These must be separate to the project site, but may be directly adjacent. Leakage mitigation activities should be equal to or greater than the expected displacement of production. The effectiveness of any additional, external leakage mitigation is then calculated using:
[math: uNPP_c = NPP_c - MAP_c]
(Equation 3)
Where:
When [math: NPP_c] is 0 or negative, The Project has achieved full leakage mitigation through its own productivity and does not require external mitigation or market leakage emissions deductions.
When [math: NPP_c] is > 0 and [math: uNPP_c] is 0, The Project has achieved full external leakage mitigation and does not take a market leakage emissions deduction.
When [math: NPP_c] is [math: >] 0 and [math: uNPP_c] is [math: >] 0, The Project takes a market leakage emissions deduction based on the remaining deficit.
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:
Activity-shifting leakage mitigation is mandatory where:
For commodities with [math: NPP_c] ≤ 0, no activity-shifting leakage mitigation is required as the agroforestry system provides equal or greater productivity than what was displaced.
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. 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 and fully compensate for the remaining productivity deficit. 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}] are only calculated for commodity types where the Net Project Productivity ([math: NPP]) is greater than zero. For commodities where [math: NPP] ≤ 0, no market leakage emissions are calculated as the agroforestry system fully mitigates leakage risk through its own productivity.
For commodities with [math: NPP] > 0, market leakage emissions consider 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 where [math: NPP] > 0.
Market leakage emissions are quantified using the following equations:
[math: CO_2e_{Market \ Leakage}=\sum_{c=1}^{n} CO_2e_{Market \ Leakage,c}]
(Equation 4)
Where:
and:
[math: CO_2e_{Market \ Leakage,c} = ha_{LC,c} \times EF_{Carbon\ Stock}]
(Equation 5)
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{auNPP_c \times \ IS_c \times \: NL_c}{Y_{NL,c}}]
(Equation 6)
Where:
Adjusted unmitigated Net Project Productivity, [math: auNPP], represents the remaining productivity deficit after accounting for agroforestry system productivity and any external mitigation, adjusted for growth trends in commodity productivity. This value reflects the net shortfall that may trigger market responses leading to land conversion elsewhere.
[math: auNPP], must be calculated using the following equation:
[math: auNPP_c =uNPP_c(1+GR_c)]
(Equation 7)
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/x}-1]
(Equation 8)
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 ([math: IS]) 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 IS are determined using the following equation:
[math: IS = \frac{\epsilon_{s,c}}{\epsilon_{s,c}+|\epsilon_{d,c}|}]
(Equation 9)
Where:
Isometric has carried out a literature review of [math: \epsilon_{s}] and [math: \epsilon_{d}] values for certain regions. Values for [math: \epsilon_{s}] and [math: \epsilon_{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: \epsilon_{s}] and [math: \epsilon_{d}] must be sourced from literature. The procedure and requirements for sourcing default values for [math: \epsilon_{s}] and [math: \epsilon_{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 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,c}] considers the yield on new land brought into production for commodity [math: c]. To determine yield on new land, follow the regional and national approach set out in the assessment of Productivity (Section 8.3.4.1.2).
[math: EF_{Carbon \ Stock}] must be derived from the IPCC average national aboveground biomass content of the land cover for the relevant ecosystem. 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 Forestry26.
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.
Activity-shifting leakage monitoring is required only for commodity types where:
For commodities where [math: NPP] ≤ 0, no activity-shifting leakage monitoring is required as the agroforestry system provides equal or greater productivity than what was displaced, eliminating the risk of activity-shifting leakage.
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 ecosystem conversion rate of the Leakage Monitoring Zone with the average rate in the region. Whenever the conversion 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 ecosystem conversion observed are unrelated to The Project and not as a result of actions relating to the Direct Actors, then no further action is required. Acceptable evidence includes documentation from government authorities or other local records that show the observed deforestation was unrelated to The Project and the Direct Actors. This can be further supplemented with remote sensing observations and notarized statements. Both Isometric and the VVB must independently review the evidence and determine whether the Direct Actors were responsible. If either Isometric or the VVB determine the evidence is insufficient, then the above-average area of ecosystem conversion must be considered as part of the leakage calculation.
Consider two agroforestry projects with different areas:
Example 1: Small Project
The small agroforestry project has a project area of 1 km[math: ^2]. Using the first approach, a 5 km buffer width would create a Leakage Monitoring Zone of 120 km[math: ^2] (calculated as an 11 km x 11 km total area minus the 1 km[math: ^2] project area). Using the second approach, the Leakage Monitoring Zone would only need to be 5 km[math: ^2] (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 agroforestry project has a project area of 100 km[math: ^2]. Using the first approach, a 5 km buffer width would create a Leakage Monitoring Zone of 300 km[math: ^2] (calculated as a 20 km x 20 km total area minus the 100 km[math: ^2] project area). Using the second approach, the Leakage Monitoring Zone would need to be 500 km[math: ^2] (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 ecosystem conversion 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}*EF_{Carbon \ Stock} - CO_2e_{Market\ Leakage},0)]
(Equation 10)
Where:
The amount of above-average ecosystem conversion 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 11)
Where:
[math: ha_{Max,LC}] is calculated using the following calculation:
[math: ha_{Max,LC} = \frac{auNPPP}{Y_{NL,c}}]
(Equation 12)
Where:
Note that [math: auNPP] represents the total remaining productivity deficit across all commodity types with positive [math: NPP] values, after accounting for both the agroforestry system's own productivity and any external mitigation activities. This ensures that activity-shifting leakage monitoring is appropriately scaled to the actual remaining risk rather than the theoretical maximum based on gross displaced productivity.
The Reporting Period for agroforestry 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:
For projects which establish agroforestry practices within existing productive land, emissions associated with continuation of pre-project productivity are excluded (see Section 9.6).
In line with the Isometric Standard, this Protocol requires that Removal Credits are issued ex-post. Credits may be issued once CO2 has been removed from the atmosphere and is stored in living trees.
Net CO2e removal for an agroforestry project for each Reporting Period ([math: RP]), is calculated with the following equation:
[math: CO_2e_{Removal,\ RP} = CO_2e_{Stored,\ RP} - CO_2e_{Counterfactual,\ RP} - CO_2e_{Emissions,\ RP} + CO_2e_{HWP,\ RP}]
(Equation 13)
Where:
The total amount of CO2 stored from an agroforestry project is calculated as:
[math: CO_2e_{Stored,RP} = CO_2e_{AGB,RP} + CO_2e_{BGB,RP}]
(Equation 14)
Where:
The carbon pools within the scope of this Protocol are aboveground and belowground woody biomass (see Section 8.1), 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}]. 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 for 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 15)
Where:
Reporting Periods are consecutive, so that [math: t_2] then becomes the start of the next [math: 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 16)
Where:
The carbon fraction, [math: CF], must be chosen from the following hierarchy:
This Protocol currently supports the following two Capture and Conversion Modules for quantifying the total AGB over the project area at a point in time, [math: M_{AGB}(t)]:
Uses field-based measurements of vegetation species and size taken within sample plots along with allometric equations to quantify biomass.
Uses aerial LiDAR data collected over the project area and trained models to quantify biomass.
Requirements for each approach are described in the corresponding Modules. Project Proponents must describe in the PDD which option is used, and adhere to the requirements of that approach. Note that the LiDAR approach still requires field plots as the source of truth for benchmarking the maps. For field sampling in any discrete planting areas less than 0.5 ha in area, it is recommended to use a census approach that measures the entire discrete planting area rather than subdividing the planting area into smaller plots.
In addition to the requirements within the Modules, biomass quantification for agroforestry practices must also use allometric equations that are specific to agroforestry settings, when available, as growth patterns can be distinct from forest ecosystems29. Allometric equations should also reflect any management practices which affect the allometry of the woody biomass (e.g., pruning, grafting), when possible. Lack of availability of relevant allometric equations must be evidenced. Acceptable evidence must show a list of search terms used within a research database (e.g., Web of Science, Google Scholar) that encapsulate the region, management practices, and species relevant to The Project. Allometric equations must also clearly exclude any non-woody components of plant biomass (e.g., fruit, nuts) when these are distinguishable in the equations.
This list of acceptable approaches may be expanded upon in future versions of the Protocol.
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 and, when available, use ratios that are specific to agricultural settings29. 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 4.426, must be used. In this case, sufficient evidence documenting the unsuccessful search for project specific factors must also be supplied. Acceptable evidence must show (1) a list of search terms used within a research database (e.g., Web of Science, Google Scholar) that encapsulate the region and species relevant to The Project, and (2) the relevant species are not included in the list of species for which root-to-shoot ratio data are available on the TRY Plant Trait Database30.
This Protocol uses a dynamic baseline approach to quantify the counterfactual impact on carbon stocks if the project activity had not occurred. In this approach, the counterfactual is determined by observing changes in carbon stocks for a collection of areas outside of the project area (control pixels) that are representative of the project area except for the project activity. Through this approach of using observations of matched controls, dynamic baselines are able to reflect changes in market trends, policies, environmental changes, etc., that can affect counterfactual carbon storage and which would be difficult to capture in static approaches. As such, the use of real-time remote sensing and robust matching procedures in the dynamic baseline procedure leads to the most plausible baseline scenario that can be clearly quantified and compared to the project activities. Further, in the dynamic baseline approach, the pixel matching procedure matches pixels within the project area to multiple pixels in the control area. Through this procedure, an ensemble of samples is generated which captures multiple baseline scenarios. This ensemble approach inherently generates probabilistic uncertainty through the variation in control pixels. This uncertainty is then included in carbon calculations (see Section 9.4.5). Because of this, the use of dynamic baseline approaches that leverage remote sensing to compare project activities to matched controls has been noted as a rigorous and conservative approach in the scientific literature31, 32, 33, 34, 35. 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. Credit issuance will only occur for carbon removal that is determined to be additional via the following procedure, inclusive of uncertainty. The following section outlines the standardized workflow that Isometric will take; the Project Proponent is not responsible for carrying out the steps in this section. Project Proponents may suggest areas that could constitute suitable control pixels or features for matching based on their expert knowledge of their unique system. However, the ultimate determination of control pixels will be done by Isometric following the procedure and criteria below. Although dynamic baseline approaches are reliant on the suitability of the matched areas to act as controls, the standardized approach includes provisions for using several criteria for the matching, matching to multiple pixels, assessing match quality, expanding the number of potential matches, and regularly reassessing control pixel suitability to minimize the associated uncertainty.
Additionally, Isometric will make a pre-project estimation of the Baseline scenario at project validation using historical data as described in Section 9.4.6.
The zone from which control pixels will be selected, termed the Donor Zone, must meet the following eligibility criteria:
If possible, other features should also be matched between the Donor Zone and project area, such as:
Initially, the potential area for the Donor Zone should be limited to a band of up to 100 km around the project area. However, if suitable matches (see Section 9.4.3 for matching step) are not found in the initial zone, additional step-outs in 10 km increments may occur to find appropriate control pixels, assuming they meet the criteria above. For projects consisting of multiple discrete planting areas spread across a region, multiple planting areas can share an initial single Donor Zone which encapsulates the planting areas. Depending on the geographic spread of the planting areas, multiple Donor Zones may be defined.
In some scenarios, constraining the zone for eligible control pixels based on the criteria above may severely limit the size of the Donor Zone. Although further control pixels can be selected by expanding the potential Donor Zone area in 10-kilometer increments, doing so may only marginally increase the area of the Donor Zone or improve the performance benchmark accuracy.
Environmental criteria such as bioclimatic variables, productivity, and biogeography used for control pixel matching tend to exhibit spatial autocorrelation — especially in areas of high topographic relief. Therefore, control pixels selected even short distances from the project area can have fundamentally different ecological conditions that can lead to biased control pixel selection and carbon stocks and/or proxies. Land use history can similarly constrain the Donor Zone. To ensure accurate matching, the Donor Zone should account for legacy effects—such as prior management regimes, levels of degradation, and priority effects—that influence long-term carbon storage capacity. However, controlling for land use history does further limit eligible Donor Zone pixels due to the asynchronous timing of land-use changes across the landscape. In any given year, areas with similar land use may vary in the time elapsed since active management (e.g., harvesting, cultivation, grazing, or disturbance), potentially biasing control pixel selection and carbon stocks and/or proxies.
One consequence of a small Donor Zone is small control pixel sample sizes, which can reduce performance benchmark accuracy through sampling bias. In this situation, Isometric may temporally expand the pool of potential control pixels using a time-for-space substitution (TFSS) sampling strategy. TFSS relaxes the requirement to match the Donor Zone and project area from identical calendar years, thereby expanding the n-dimensional area available for valid control pixel selection. Instead of aligning control pixel and project carbon stocks and/or proxies by the same calendar year, TFSS compares changes in carbon stocks and/or proxies relative to the time elapsed since pre-project conditions, enabling more robust estimates of additionality.
In this approach, historical data for control pixels can be matched to current data for The Project. The same criteria as listed above must apply across the time points (i.e., current regulations which apply to The Project must have also been applicable at the historical time point for the control pixel). This approach will only be used when there is demonstrated necessity for its application to yield a sufficiently sized Donor Zone. If TFSS is implemented, Isometric will include the justification for the approach as well as the specific methodological approach and data included in the TFSS in its documentation of the baseline procedure.
When the TFSS is used, the temporal range considered for eligible control pixels will be expanded in 5-year increments, up to 15 years maximum. In addition to the features and criteria above, eligibility for the use of time substituted control pixels also includes:
When temporal substitution is used for control pixels, their eligibility will be re-evaluated at each Reporting Period according to the guidance set out in Section 9.4.4.
Once the boundaries of the Donor Zone are determined, Isometric will generate high-resolution (≤30 m) pixel maps representing woody biomass carbon stocks or a suitable proxy for woody biomass 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:
A representative random sample of project pixels are matched to control plot pixels based on the historical time series of the selected carbon proxy, [math: C_{proxy}], of each pixel and any other relevant features, using k-nearest neighbors (or an alternative justified algorithm). This matching will use, at a minimum, five historical time points capturing at least the five years prior to project initiation. Each sampled project pixel must be matched to a minimum of 10 different control pixels, and the mean carbon proxy over the group of control pixels is calculated from the map product created using the procedure described in Section 9.4.2.
For each selected Project pixel, the change in carbon stock over the Reporting Period is calculated both for the project pixel and for the collection of corresponding control pixels (taking the mean across the group) using the values from the carbon proxy map:
[math: \Delta C_{proxy} = C_{proxy}(t_2) - C_{proxy}(t_1)]
(Equation 18)
Where:
The carbon removal of the counterfactual scenario is found by scaling the quantified carbon removal in the project area by the ratio of the mean differences of the proxy change between the project and control pixels:
[math: CO_2e_{Counterfactual,RP} = CO_2e_{Stored,RP} \times \frac{\mu_{\Delta C_{proxy,project}} - \mu_{\Delta C_{proxy,difference}}}{\mu_{\Delta C_{proxy,project}}}]
(Equation 19)
Where:
To meet the additionality condition, the change in proxy value in the project area ([math: \Delta C_{proxy, project}]) must be statistically greater (p < 0.05) than the mean change in proxy value for the matched control pixels ([math: \Delta C_{proxy, control}]). If the mean proxy change in the control pixels is negative such that the resulting product of Equation 19 is negative, the counterfactual carbon storage ([math: CO_2e_{counterfactual,RP}]) will be assumed to be 0 in order to ensure the accounting of carbon storage is limited to removals.
The counterfactual carbon storage is then used to calculate a performance benchmark for the project area, [math: PB_{RP}]:
[math: PB_{RP} = \frac{CO_2e_{Stored,\ RP}}{CO_2e_{Counterfactual,\ RP}}]
(Equation 20)
If the additionality requirement is met, the performance benchmark will be greater than 1, with larger magnitudes indicating a greater difference between storage in the project and control areas.
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. All details related to evaluation and replacement of control pixels will be included as part of the reporting on the calculation of the baseline. The baseline assessment at Project initiation (t=0) must be done after site preparation but before planting, including capturing any pre-existing biomass that will remain in the Project area. If the site preparation includes any removal of woody biomass (e.g., invasives), this must be captured in the GHG emissions from project establishment as described in Section 8.1.
If the planting plan of The Project does not allow for adequate temporal separation of site preparation and planting to allow for baseline establishment (e.g., site preparation and planting done simultaneously), Project Proponents must provide justification for the necessity of their timeline and approach for project establishment. In this scenario, Isometric will assess the initial baseline prior to any site preparation. Project Proponents must still report all GHG emissions associated with project establishment as above, including explicitly reporting all removals of woody biomass for site preparation. Isometric will review the reported data and, if appropriate, remove the cleared woody biomass component from the GHG emission analysis if this carbon pool is already accounted for in the baseline set before removals occurred as part of site preparation.
In scenarios where there is removal of woody biomass as part of site preparation, the performance baseline may be less than one in the early period of The Project, and therefore ineligible for crediting, until growth of the planted area results in greater biomass than what was removed as part of project establishment. However, this would not be considered a reversal as long as i) the Project Proponent has provided documentation that biomass was removed as part of site preparation and ii) there is not a continued decrease in biomass once site preparation is complete.
Isometric will account for uncertainty in the dynamic baseline to obtain a conservative estimate of [math: CO_2e_{counterfactual,RP}]. This will be done via a placebo approach, in which a representative random subsample of the control pixels are further matched to other placebo pixels in the donor zone following the same matching procedure as is used for the project-control matches38. These placebo pixels represent areas which are similar to the control pixels and where no interventions are being made. In theory, the biomass in the placebo and control pixels should evolve in a similar manner. As such, any difference observed between the control and placebo pixel's biomass evolution is indicative of uncertainty in the underlying datasets and matching procedure.
At each Reporting Period, the distribution of differences between the sampled control pixels and matched placebos will be used to quantify the uncertainty in the dynamic baseline and used in the propagation of overall uncertainty in removals (see Section 7.5).
At validation, Isometric will use the historical data across the control pixels used in the matching procedure (Section 9.4.3) to produce an ex-ante projection of counterfactual biomass. This baseline will be used to evaluate additionality. To be considered additional, the carbon removal in the project area must be statistically significantly greater than this ex-ante baseline. The dynamic baselining procedure described in the preceding subsections of Section 9.4 will be used for all ex-post issuance of Credits.
To compute the baseline, Isometric will use historical data points over the matched control pixels to calculate the slope of the linear regression representing the expected change in carbon storage over time for the counterfactual scenario. This slope will be assumed to be constant and used to create projections of future counterfactual carbon storage to which the ex-ante carbon curve can be assessed against.
The total GHG emissions associated with a Reporting Period, [math: RP], can be calculated as:
[math: CO_2e_{Emissions,RP} = CO_2e_{Establishment,RP} + CO_2e_{Operations,RP} + CO_2e_{EndOfLife,RP} + CO_2e_{Leakage,RP}]
(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 soil preparation. 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 to the moment before the first removal activity takes place. GHG emissions associated with project establishment may be amortized over the anticipated project lifetime, or per output of product. Requirements for amortization (The term used to describe allocation of Project emissions to multiple Removals or Reductions.) are outlined in Section 7 of the GHG Accounting Module.
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 agroforestry projects, the Reporting Period covers a set period of time (e.g., one year), during which woody biomass accumulates. [math: CO_2e_{Operations,RP}] emissions must be attributed to the Reporting Period in which they occur. This includes any emissions associated with management of the agroforestry system or harvesting/processing of commodities for which production was established by The Project. The emissions from these activities must be calculated as explained in Section 9.5. 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_{EndOfLife,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_{EndOfLife,RP}] must be estimated upfront and allocated in the same way as set out for calculation of [math: CO_2e_{Establishment,RP}].
Given the uncertain nature of [math: CO_2e_{EndOfLife,RP}] emissions, assumptions must be revisited at each Reporting Period and any necessary adjustments made. Furthermore, if there are unexpected [math: CO_2e_{EndOfLife,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 and is not repeated here.
GHG emissions accounting must be undertaken in alignment with the GHG Accounting Module v1.0, which ensures a consistently rigorous standard in how GHG emissions are quantified and reported between different CDR Projects and approaches. This includes:
See the GHG Accounting Module for detailed requirements
The Energy Use Accounting Module 1.3 provides requirements 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.
Energy emissions are those related to electricity or fuel usage. They may include, but are not limited to:
The GHG Accounting Module v1.0 provides requirements on how transportation and energy-related emissions must be calculated for The Project so that they can be subtracted in the net CO2e removal calculation.
Embodied emissions are those related to the life cycle impact of equipment and consumables. They may include, but are not limited to:
Transportation emissions are those related to transportation of products and equipment. They may include, but are not limited to:
Any models used to fulfill requirements 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 agroforestry 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 determined relative to the length of the Project Commitment Period as outlined in Section 5.4. The minimum duration of the Project Commitment Period is 40 years, and therefore minimum durability of Credits issued under this Protocol, is 20 years.
The durability must not exceed any of the following:
Reversal risks which may threaten the durability of agroforestry system carbon and project-level risk assessment and mitigation requirements are discussed in Section 10.2 and Section 10.3, respectively.
A forestry-wide Buffer Pool managed by Isometric is used to insure Credits against Reversals. Throughout any 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 and 10.5).
Project Proponents must design The Project in a manner that is aligned with long-term durability and sustainability. Well-designed projects should mitigate risk of timber harvest or Reversal after The Project ends (see Section 5.5). Support for long-term durability may consist of evidence of the following, and ideally a combination of factors:
Reversals are defined as reductions in living woody 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 living woody 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 Agroforestry Risk Assessment in Appendix E and provide supporting evidence, where required. The Agroforestry Risk Assessment is independently evaluated by a third-party VVB. The Agroforestry Risk Assessment is used to determine the risk profile of The Project, including risks to Credit delivery 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 Agroforestry 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 agroforestry 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 vegetation age and translate this into a highly accurate Buffer Pool contribution. As a result, we apply either a flat contribution requirement on The Project or a model to translate the Agroforestry 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 forestry-wide Buffer Pool managed by Isometric. Pooling of a diversified portfolio of forestry projects across geographic regions, project types, spatial scales and temporal scales can reduce the exposure to systemic risks stemming from forestry projects constrained to a geographic area or ecological type40, 41, 31. The forestry-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, 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:
If the Project Proponent is unable to access the project area to complete a full reversal report to demonstrate otherwise, the affected project area will be considered to have experienced a full avoidable reversal for the purpose of the buffer pool compensation process.
Quantification of Reversals are calculated by determining the relative change in a proxy aboveground biomass parameter such as tree 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 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:
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 2.
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 the Leakage Monitoring Zone.
[Image: **Figure 2** Monitoring locations]
Figure 2. Schematic of the various monitoring locations referred to throughout this Protocol.
The entire project area in Figure 2 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. Isometric will handle all aspects of the dynamic baseline assessment. Project Proponents are responsible for monitoring conducted within the project area that is required for the selected AGB quantification method (see Section 9.3.2).
After the Crediting Period, ongoing monitoring of the agroforestry system biomass (e.g., tree cover or vegetation indices), when required, 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 woody vegetation growth in similar land areas outside the project area to determine the additional carbon storage of an agroforestry 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 carbon between the project and Counterfactual scenario for each Reporting Period. Isometric is responsible for the selection of control pixels and the calculation of the dynamic baseline (see Section 9.4).
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 ecosystem conversion near the project area. Annual monitoring of land cover characteristics over time is used to calculate conversion rates over time. See Section 8.3.5 for more details on how leakage monitoring is used.
Isometric will be responsible for conducting the monitoring.
Airborne laser scanning measurements are only applicable for projects that wish to use LiDAR to estimate AGB (details described in corresponding Module). ALS data collection should occur throughout the Crediting Period, at the end of each Reporting Period.
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, or are used for benchmarking LiDAR-derived AGB maps. Details of the application of these methodologies for AGB quantification are described in the corresponding Modules (see Section 9.3.2). For projects selecting the quantification approach 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 LiDAR approaches, field measurements must be taken at a minimum of every 5 years for benchmarking purposes. 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 woody biomass tend to overestimate in young plantings. 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 vegetation biomass may be highly uncertain during the initial years after tree planting due to high rates of tree mortality and biases during early growth stages. 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 Area-Based AGB Quantification (see Module for details). 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 Area-Based AGB Quantification (see Module for details). 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 aboveground biomass | Required when LiDAR quantification Module selected, otherwise not applicable | Project Proponent |
| At the start and end of each Reporting Period, e.g., once a year in the same season | Control pixels & project area | Vegetation carbon proxy (e.g, canopy height, biomass saturation index) | Satellite data or third-party mapped product | To quantify relative change in agroforestry system carbon sequestration between control pixels and Project area (Equation 19) | 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 ecosystem conversion | Satellite | To identify any activity-shifting leakage that should be taken into account for the net carbon removal calculation (Equation 10) | 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 tree cover loss | Satellite | To identify Reversals and appropriately remediate through the Buffer Pool | Required | Isometric or a third party |
We would like to thank all the individuals and organizations who provided valuable feedback as part of the consultation process of this Protocol.
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.
[math: 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)42 |
| Global | Coffee | -0.305 | 0.285 | 0.48 | Akiyama and Varangis (1990)43 |
| Global | Cocoa | -0.075 | 0.075 | 0.50 | Askari and Cummings (1977)44, Behrman (1965)45 |
| South America | Livestock | -0.40 | 0.4 | 0.5 | Fragoso et al. (2011) 45 |
| North America | Livestock | -0.40 | 1.6 | 0.80 | Mintert et al. (2009)46, Jeong (2019)47 |
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. [math: NL] values proposed aim to capture the net effect of a one unit removal of crop area on forestland conversion. These [math: NL] values will be smaller in magnitude than [math: 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 [math: NL] values are more speculative than the [math: 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 changes48.
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)49 |
| US | cropland | 0.28 | Lark et al (2022)50 |
| Mexico | cropland | N/A | Can use Brazil value |
| Panama | cropland | N/A | Can use Brazil value |
| Brazil | livestock | 0.83 | Bowman (2012)51 |
| US | livestock | 0.20 | Wu (2000)52 |
| 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”53 |
| Global | other specialty crops | N/A | See: global coffee value |
When assessing the net climate impact (NCI) within the project area using the data from Hasler et al. (2024)9, the threshold for determining whether an area is net climate negative should use the biome-specific uncertainty values shown in Table B1 which are derived from Table S2 of the study. The uncertainty value for a given biome is taken from the range of values yielded from different parameterizations used in the study. Areas will be considered to be net climate negative, and therefore ineligible for planting, when their NCI Density value plus biome specific uncertainty is less than zero. For example, for temperate broadleaf and mixed forests, any areas with NCI densities less than -31 Mg CO2e ha[math: ^{-1}] will be considered net climate negative.
Table B1. Net Climate Impact (NCI) Density [Mg [math: CO_{2}e] ha[math: ^{-1}]] Biome-Specific Uncertainty.
| Biome | Mean NCI Density | Min NCI Density | Max NCI Density | Uncertainty (+/-) |
|---|---|---|---|---|
| Tundra | -110 | -190 | -41 | 74.5 |
| Boreal Forests/Taiga | 42 | 0 | 85 | 42.5 |
| Temperate Grasslands, Savannas & Shrublands | -98 | -138 | -56 | 41 |
| Mediterranean Forests, Woodlands & Scrub | -92 | -135 | -65 | 35 |
| Temperate Conifer Forests | 156 | 110 | 196 | 43 |
| Temperate Broadleaf & Mixed Forests | 182 | 147 | 209 | 31 |
| Tropical & Subtropical Grasslands, Savannas, & Shrublands | 39 | -15 | 70 | 42.5 |
| Tropical & Subtropical Coniferous Forests | 250 | 235 | 260 | 12.5 |
| Tropical & Subtropical Dry Broadleaf Forests | 203 | 179 | 216 | 18.5 |
| Tropical & Subtropical Moist Broadleaf Forests | 598 | 588 | 605 | 8.5 |
| Mangroves | 527 | 519 | 532 | 6.5 |
| Flooded Grasslands & Savannas | 91 | 65 | 108 | 21.5 |
| Montane Grasslands and Shrublands | -233 | -315 | -188 | 63.5 |
| Deserts & Xeric Shrublands | -205 | -250 | -171 | 39.5 |
| Globally | 120 | 80 | 150 | 35 |
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 States54 and the coefficients are given in the supplementary materials.
Furthermore, Allometric is an R package that curates allometric equations and facilitates their usage.
Approved Resources and Third-Party Datasets
Albedo
Baseline
Buffer Pool Contribution
Emergency Response
Insurance
Leakage
Quantification Methods
Stakeholder Engagement
Uncertainty
The Agroforestry Risk Assessment is used to assess the overall delivery and storage risk associated with the agroforestry activities 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 with corresponding evidence supplied and must then 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 Agroforestry Risk Assessment.
For projects with discrete planting areas, the risk assessment must include all geographic areas relevant to The Project. For risk indicators that are geographically explicit (e.g., disturbance risks), the score may be calculated via an area-weighted average and rounded up to the nearest whole number.
If Project Proponents choose to forgo a flat 20% Buffer Pool contribution (see Section 10.4.1), the Agroforestry 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.
After each new Agroforestry Risk Assessment evaluation, Isometric will update the required percentage of newly issued Credits that must be contributed to the Buffer Pool by The Project. We encourage Project Proponents to continuously monitor, mitigate, and reduce risks.
Table E1. Agroforestry Risk Assessment, with the score to be filled out for each question.
| RISK CATEGORY | RISK INDICATOR | EVIDENCE | SCORING GUIDELINES | SCORE |
|---|---|---|---|---|
| Project Proponent Capacity Risk | Does the Project Proponent maintain staff with domain expertise relevant for agroforestry carbon projects? (e.g., sustainable agriculture, agroecology, 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 all portions of the project area? | 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 agroforestry, 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, other 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 agroforestry projects in the same region, local or national reports on environmental crimes or violations |
| ||
| Does the Project Proponent have documentation to demonstrate that the Project Proponents will have access to the project area for the full Project Commitment Period for the purpose of meeting the Reversal reporting requirements? | Land access and/or tenure documentation | If no, +2. | ||
| Financial Viability Risk | Has The Project secured funding to cover all activities required before carbon/commodity 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 vegetation 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 full Project Commitment Period to maintain agroforestry system 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 witihn the past 50 years 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 The Project have a detailed benefit-sharing plan that includes: clear distribution mechanisms, transparent criteria for beneficiary selection, a grievance resolution process, monitoring and reporting procedures? | Project financial plan |
| ||
| 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 | Mean daily Global Fire Weather Index over the prior two years |
| |
| Pest and disease outbreak risk | Regional third-party maps, if available. |
| ||
| Extreme weather (temperature - heat and cold) | IPCC AR659 | From 0 to 2, see Appendix F | ||
| Extreme weather (hydrologic - flood and drought) | IPCC AR659 | From 0 to 2, see Appendix F | ||
| 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 |
| ||
| Ability of land to support woody cover | Land cover classification, historical documentation/imagery, ecoregion classification, scientific studies, projections of suitability under future climate (e.g., Bastin et al., 201960), and/or traditional ecological knowledge | If no evidence of past woody vegetation cover nor suitability of future climate for woody vegetation cover, +2 | ||
| Flood plain hazards | Project area overlap with identified floodplain based on Nardi et al., 201961 or regional/local equivalent |
|
The following section outlines how Isometric calculates the indicator scores for climate-related extreme weather disturbance risks to carbon permanence within a project’s region (Figure F1). Project Proponents should use Table F1 to lookup the Isometric-calculated values for their project's region and include those scores in their Agroforestry Risk Assessment (see Appendix E).
Extreme weather risks are assessed via two indicators: a temperature indicator (extreme heat and/or cold) and a hydrologic indicator (flooding and/or drought). Each indicator includes both historical data (1961-2015) and projected future extreme events. Historical data indicate the likelihood of extreme events based on past climate patterns, e.g., projects in regions with extended dry periods are expected to experience increased water stress as part of their typical climate. Climate model projections describe how changing climate conditions, relative to historical patterns, might present an increased risk of disturbances. Areas where there is a larger shift towards extreme conditions under future climate relative to their historical baseline have a greater disturbance risk (e.g., drier conditions relative to historical averages increases risk for drought-driven mortality).
To calculate the scores in Table F1, Isometric uses values from the Intergovernmental Panel on Climate Change AR6 report59. The temperature indicator is calculated using data describing the annual number of frost days ([math: FD], minimum temperature below 0°C) and annual number of days with a maximum temperature above 40°C ([math: TX_{40}]) to capture extreme cold and extreme heat risks, respectively. The hydrologic indicator is calculated using data describing the maximum 5-day precipitation ([math: RX_{5Day}]) and annual maximum number of consecutive dry days ([math: CDD]) to capture risks of flooding and drought, respectively. All values come from the CMIP6 climate models. Future projections use the SSP2-4.5 medium term (2041-2060) scenario and are assessed as the change in value relative to a historical baseline (1961-1990).
For each indicator subcomponent, the region’s terrestrial median value is compared with the global terrestrial distribution of the same variable (Table F2). To convert the regional value into a subscore, regional values below the global 75th percentile are considered Low Risk, regional values equal to or greater than the global 75th percentile but below the 90th percentile are Medium Risk, and any regional values equal to or greater than the global 90th percentile are High Risk. Low Risks are given a subscore of 0, Medium Risks are 0.25, and High Risks are 0.5. The overall score for each of the indicators is calculated by summing the corresponding subscores, as described below:
[math: Indicator_{Temperature} = Historical_{TX_{40}} + Future_{TX_{40}} + Historical_{FD}]
[math: Indicator_{Hydrological} = Historical_{CDD} + Future_{CDD} + Historical_{RX_{5Day}} + Future_{RX_{5Day}}]
Projected change in the number of frost days is not included as a subcomponent since it is projected that they will decline under future climate across the globe, representing a low risk of future extreme cold events.
Figure F1. Map and lookup table for IPCC regional codes
Table F1. Regional Lookup Table of Disturbance Risk
| Region | Indicator | Variable | Time | Value | Risk | Score | Total |
|---|---|---|---|---|---|---|---|
| NW North America (NWN) | Temperature | Frost Days | Historical | 224.2 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0 | Low | 0 | ||||
| Hydrological | CDD | Historical | 23.5 | Low | 0 | 0.5 | |
| Change (Days) | -1.4 | Low | 0 | ||||
| 5-Day Precip | Historical | 54.4 | Low | 0 | |||
| Change (%) | 11.9 | High | 0.5 | ||||
| NE North America (NEN) | Temperature | Frost Days | Historical | 242.9 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0 | Low | 0 | ||||
| Hydrological | CDD | Historical | 25.1 | Low | 0 | 0.5 | |
| Change (Days) | -2.7 | Low | 0 | ||||
| 5-Day Precip | Historical | 50.6 | Low | 0 | |||
| Change (%) | 11.8 | High | 0.5 | ||||
| Western North America (WNA) | Temperature | Frost Days | Historical | 128.4 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0.9 | Low | 0 | |||
| Change (Days) | 2 | Low | 0 | ||||
| Hydrological | CDD | Historical | 40.6 | Low | 0 | 0 | |
| Change (Days) | -0.2 | Low | 0 | ||||
| 5-Day Precip | Historical | 67.3 | Low | 0 | |||
| Change (%) | 5.5 | Low | 0 | ||||
| Central North America (CNA) | Temperature | Frost Days | Historical | 104.9 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 4.7 | Low | 0 | |||
| Change (Days) | 8.9 | Low | 0 | ||||
| Hydrological | CDD | Historical | 23.7 | Low | 0 | 0.25 | |
| Change (Days) | -0.4 | Low | 0 | ||||
| 5-Day Precip | Historical | 84.3 | Medium | 0.25 | |||
| Change (%) | 6.7 | Low | 0 | ||||
| Eastern North America (ENA) | Temperature | Frost Days | Historical | 116 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0.1 | Low | 0 | |||
| Change (Days) | 0.6 | Low | 0 | ||||
| Hydrological | CDD | Historical | 15.5 | Low | 0 | 0.75 | |
| Change (Days) | -0.3 | Low | 0 | ||||
| 5-Day Precip | Historical | 89.4 | High | 0.5 | |||
| Change (%) | 9 | Medium | 0.25 | ||||
| Northern Central America (NCA) | Temperature | Frost Days | Historical | 15.9 | Low | 0 | 0 |
| Days > 40°C | Historical | 4.7 | Low | 0 | |||
| Change (Days) | 8.7 | Low | 0 | ||||
| Hydrological | CDD | Historical | 51.6 | Low | 0 | 0.5 | |
| Change (Days) | -0.2 | Low | 0 | ||||
| 5-Day Precip | Historical | 92.9 | High | 0.5 | |||
| Change (%) | 6 | Low | 0 | ||||
| Southern Central America (SCA) | Temperature | Frost Days | Historical | 0.1 | Low | 0 | 0 |
| Days > 40°C | Historical | 0.5 | Low | 0 | |||
| Change (Days) | 1.7 | Low | 0 | ||||
| Hydrological | CDD | Historical | 39.7 | Low | 0 | 0.5 | |
| Change (Days) | -1.6 | Low | 0 | ||||
| 5-Day Precip | Historical | 134.3 | High | 0.5 | |||
| Change (%) | 4.3 | Low | 0 | ||||
| Caribbean (CAR) | Temperature | Frost Days | Historical | 0 | Low | 0 | 0 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0 | Low | 0 | ||||
| Hydrological | CDD | Historical | 24.3 | Low | 0 | 0.5 | |
| Change (Days) | 0.1 | Low | 0 | ||||
| 5-Day Precip | Historical | 99.9 | High | 0.5 | |||
| Change (%) | 0.8 | Low | 0 | ||||
| NW South America (NWS) | Temperature | Frost Days | Historical | 0.6 | Low | 0 | 0 |
| Days > 40°C | Historical | 0.1 | Low | 0 | |||
| Change (Days) | 0.8 | Low | 0 | ||||
| Hydrological | CDD | Historical | 28.6 | Low | 0 | 0.5 | |
| Change (Days) | -0.2 | Low | 0 | ||||
| 5-Day Precip | Historical | 133 | High | 0.5 | |||
| Change (%) | 7.5 | Low | 0 | ||||
| Northern South America (NSA) | Temperature | Frost Days | Historical | 0 | Low | 0 | 0 |
| Days > 40°C | Historical | 0.5 | Low | 0 | |||
| Change (Days) | 9.4 | Low | 0 | ||||
| Hydrological | CDD | Historical | 46.7 | Low | 0 | 1 | |
| Change (Days) | 9.7 | High | 0.5 | ||||
| 5-Day Precip | Historical | 111.6 | High | 0.5 | |||
| Change (%) | 5.5 | Low | 0 | ||||
| NE South America (NES) | Temperature | Frost Days | Historical | 0 | Low | 0 | 0 |
| Days > 40°C | Historical | 0.3 | Low | 0 | |||
| Change (Days) | 4.4 | Low | 0 | ||||
| Hydrological | CDD | Historical | 95 | High | 0.5 | 1.5 | |
| Change (Days) | 6.3 | High | 0.5 | ||||
| 5-Day Precip | Historical | 144.3 | High | 0.5 | |||
| Change (%) | 5.7 | Low | 0 | ||||
| South America-Monsoon (SAM) | Temperature | Frost Days | Historical | 7.5 | Low | 0 | 0.25 |
| Days > 40°C | Historical | 2.2 | Low | 0 | |||
| Change (Days) | 11.5 | Medium | 0.25 | ||||
| Hydrological | CDD | Historical | 64.8 | Medium | 0.25 | 1.25 | |
| Change (Days) | 13.7 | High | 0.5 | ||||
| 5-Day Precip | Historical | 133.7 | High | 0.5 | |||
| Change (%) | 6 | Low | 0 | ||||
| SW South America (SWS) | Temperature | Frost Days | Historical | 35.8 | Low | 0 | 0 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0 | Low | 0 | ||||
| Hydrological | CDD | Historical | 65.9 | Medium | 0.25 | 0.5 | |
| Change (Days) | -4.2 | Low | 0 | ||||
| 5-Day Precip | Historical | 83 | Medium | 0.25 | |||
| Change (%) | -0.9 | Low | 0 | ||||
| SE South America (SES) | Temperature | Frost Days | Historical | 16.6 | Low | 0 | 0 |
| Days > 40°C | Historical | 2.8 | Low | 0 | |||
| Change (Days) | 5.5 | Low | 0 | ||||
| Hydrological | CDD | Historical | 36.3 | Low | 0 | 0.75 | |
| Change (Days) | 0.4 | Medium | 0.25 | ||||
| 5-Day Precip | Historical | 105.1 | High | 0.5 | |||
| Change (%) | 8.4 | Low | 0 | ||||
| Southern South America (SSA) | Temperature | Frost Days | Historical | 75.4 | Low | 0 | 0 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0.1 | Low | 0 | ||||
| Hydrological | CDD | Historical | 20.5 | Low | 0 | 0.5 | |
| Change (Days) | 1.6 | High | 0.5 | ||||
| 5-Day Precip | Historical | 57.5 | Low | 0 | |||
| Change (%) | 3.4 | Low | 0 | ||||
| Northern Europe (NEU) | Temperature | Frost Days | Historical | 150.3 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0 | Low | 0 | ||||
| Hydrological | CDD | Historical | 18.5 | Low | 0 | 0.25 | |
| Change (Days) | 0 | Low | 0 | ||||
| 5-Day Precip | Historical | 52.8 | Low | 0 | |||
| Change (%) | 10 | Medium | 0.25 | ||||
| Western & Central Europe (WCE) | Temperature | Frost Days | Historical | 109.7 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0.1 | Low | 0 | |||
| Change (Days) | 0.7 | Low | 0 | ||||
| Hydrological | CDD | Historical | 22.8 | Low | 0 | 0.5 | |
| Change (Days) | 1.3 | High | 0.5 | ||||
| 5-Day Precip | Historical | 55 | Low | 0 | |||
| Change (%) | 8.5 | Low | 0 | ||||
| Eastern Europe (EEU) | Temperature | Frost Days | Historical | 171.4 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 1 | Low | 0 | |||
| Change (Days) | 2.7 | Low | 0 | ||||
| Hydrological | CDD | Historical | 27.6 | Low | 0 | 0.5 | |
| Change (Days) | 1.1 | Medium | 0.25 | ||||
| 5-Day Precip | Historical | 42.9 | Low | 0 | |||
| Change (%) | 10 | Medium | 0.25 | ||||
| Mediterranean (MED) | Temperature | Frost Days | Historical | 27.6 | Low | 0 | 0.25 |
| Days > 40°C | Historical | 6 | Low | 0 | |||
| Change (Days) | 11.8 | Medium | 0.25 | ||||
| Hydrological | CDD | Historical | 75 | High | 0.5 | 1 | |
| Change (Days) | 6.7 | High | 0.5 | ||||
| 5-Day Precip | Historical | 49.5 | Low | 0 | |||
| Change (%) | 3.9 | Low | 0 | ||||
| Western Africa (WAF) | Temperature | Frost Days | Historical | 0 | Low | 0 | 1 |
| Days > 40°C | Historical | 24 | High | 0.5 | |||
| Change (Days) | 26.4 | High | 0.5 | ||||
| Hydrological | CDD | Historical | 83.5 | High | 0.5 | 1.25 | |
| Change (Days) | -0.4 | Low | 0 | ||||
| 5-Day Precip | Historical | 85.2 | Medium | 0.25 | |||
| Change (%) | 19.6 | High | 0.5 | ||||
| Central Africa (CAF) | Temperature | Frost Days | Historical | 0 | Low | 0 | 0.25 |
| Days > 40°C | Historical | 11.1 | Medium | 0.25 | |||
| Change (Days) | 9.2 | Low | 0 | ||||
| Hydrological | CDD | Historical | 61.8 | Low | 0 | 0.75 | |
| Change (Days) | -0.1 | Low | 0 | ||||
| 5-Day Precip | Historical | 84.4 | Medium | 0.25 | |||
| Change (%) | 14.9 | High | 0.5 | ||||
| North Eastern Africa (NEAF) | Temperature | Frost Days | Historical | 0 | Low | 0 | 1 |
| Days > 40°C | Historical | 16.1 | High | 0.5 | |||
| Change (Days) | 15.4 | High | 0.5 | ||||
| Hydrological | CDD | Historical | 80.4 | High | 0.5 | 1 | |
| Change (Days) | -2.1 | Low | 0 | ||||
| 5-Day Precip | Historical | 64.6 | Low | 0 | |||
| Change (%) | 15.4 | High | 0.5 | ||||
| South Eastern Africa (SEAF) | Temperature | Frost Days | Historical | 0 | Low | 0 | 0 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0.3 | Low | 0 | ||||
| Hydrological | CDD | Historical | 78.5 | High | 0.5 | 1.5 | |
| Change (Days) | 0.4 | Medium | 0.25 | ||||
| 5-Day Precip | Historical | 91.9 | High | 0.5 | |||
| Change (%) | 9.7 | Medium | 0.25 | ||||
| West Southern Africa (WSAF) | Temperature | Frost Days | Historical | 1.2 | Low | 0 | 0 |
| Days > 40°C | Historical | 0.1 | Low | 0 | |||
| Change (Days) | 3 | Low | 0 | ||||
| Hydrological | CDD | Historical | 108.7 | High | 0.5 | 1.5 | |
| Change (Days) | 10.5 | High | 0.5 | ||||
| 5-Day Precip | Historical | 87.6 | High | 0.5 | |||
| Change (%) | 2 | Low | 0 | ||||
| East Southern Africa (ESAF) | Temperature | Frost Days | Historical | 2.7 | Low | 0 | 0 |
| Days > 40°C | Historical | 0.7 | Low | 0 | |||
| Change (Days) | 2.8 | Low | 0 | ||||
| Hydrological | CDD | Historical | 68.7 | Medium | 0.25 | 1.25 | |
| Change (Days) | 4.3 | High | 0.5 | ||||
| 5-Day Precip | Historical | 127.5 | High | 0.5 | |||
| Change (%) | 6 | Low | 0 | ||||
| Madagascar (MDG) | Temperature | Frost Days | Historical | 0 | Low | 0 | 0 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0.2 | Low | 0 | ||||
| Hydrological | CDD | Historical | 46.7 | Low | 0 | 0.5 | |
| Change (Days) | -1.2 | Low | 0 | ||||
| 5-Day Precip | Historical | 175.7 | High | 0.5 | |||
| Change (%) | 5.8 | Low | 0 | ||||
| Russian-Arctic (RAR) | Temperature | Frost Days | Historical | 271.3 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0 | Low | 0 | ||||
| Hydrological | CDD | Historical | 31.5 | Low | 0 | 0.5 | |
| Change (Days) | -4.3 | Low | 0 | ||||
| 5-Day Precip | Historical | 39.7 | Low | 0 | |||
| Change (%) | 16.7 | High | 0.5 | ||||
| West Siberia (WSB) | Temperature | Frost Days | Historical | 203.1 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0.7 | Low | 0 | |||
| Change (Days) | 2 | Low | 0 | ||||
| Hydrological | CDD | Historical | 31.4 | Low | 0 | 0.25 | |
| Change (Days) | -0.4 | Low | 0 | ||||
| 5-Day Precip | Historical | 37.5 | Low | 0 | |||
| Change (%) | 10.8 | Medium | 0.25 | ||||
| East Siberia (ESB) | Temperature | Frost Days | Historical | 233.9 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0.1 | Low | 0 | ||||
| Hydrological | CDD | Historical | 34.1 | Low | 0 | 0.25 | |
| Change (Days) | -3.7 | Low | 0 | ||||
| 5-Day Precip | Historical | 54.5 | Low | 0 | |||
| Change (%) | 11.5 | Medium | 0.25 | ||||
| Russian-Far-East (RFE) | Temperature | Frost Days | Historical | 238.1 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0 | Low | 0 | ||||
| Hydrological | CDD | Historical | 28.8 | Low | 0 | 0.5 | |
| Change (Days) | -3.2 | Low | 0 | ||||
| 5-Day Precip | Historical | 65.1 | Low | 0 | |||
| Change (%) | 14.4 | High | 0.5 | ||||
| West Central Asia (WCA) | Temperature | Frost Days | Historical | 95.8 | High | 0.5 | 1.5 |
| Days > 40°C | Historical | 22 | High | 0.5 | |||
| Change (Days) | 17.5 | High | 0.5 | ||||
| Hydrological | CDD | Historical | 113.6 | High | 0.5 | 0.75 | |
| Change (Days) | -0.3 | Low | 0 | ||||
| 5-Day Precip | Historical | 42.5 | Low | 0 | |||
| Change (%) | 10 | Medium | 0.25 | ||||
| East Central Asia (ECA) | Temperature | Frost Days | Historical | 195.6 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 0.5 | Low | 0 | |||
| Change (Days) | 2.5 | Low | 0 | ||||
| Hydrological | CDD | Historical | 75.1 | High | 0.5 | 1 | |
| Change (Days) | -6.2 | Low | 0 | ||||
| 5-Day Precip | Historical | 30.5 | Low | 0 | |||
| Change (%) | 12.9 | High | 0.5 | ||||
| Tibetan-Plateau (TIB) | Temperature | Frost Days | Historical | 258.6 | High | 0.5 | 0.5 |
| Days > 40°C | Historical | 1.6 | Low | 0 | |||
| Change (Days) | 0.4 | Low | 0 | ||||
| Hydrological | CDD | Historical | 42.3 | Low | 0 | 0.75 | |
| Change (Days) | -2.6 | Low | 0 | ||||
| 5-Day Precip | Historical | 80.9 | Medium | 0.25 | |||
| Change (%) | 11.6 | High | 0.5 | ||||
| East Asia (EAS) | Temperature | Frost Days | Historical | 91.7 | Medium | 0.25 | 0.25 |
| Days > 40°C | Historical | 0.3 | Low | 0 | |||
| Change (Days) | 0.7 | Low | 0 | ||||
| Hydrological | CDD | Historical | 29.1 | Low | 0 | 0.75 | |
| Change (Days) | 0.1 | Low | 0 | ||||
| 5-Day Precip | Historical | 132 | High | 0.5 | |||
| Change (%) | 9.6 | Medium | 0.25 | ||||
| South Asia (SAS) | Temperature | Frost Days | Historical | 7.9 | Low | 0 | 1 |
| Days > 40°C | Historical | 33.1 | High | 0.5 | |||
| Change (Days) | 14.5 | High | 0.5 | ||||
| Hydrological | CDD | Historical | 93.9 | High | 0.5 | 1.5 | |
| Change (Days) | -3.3 | Low | 0 | ||||
| 5-Day Precip | Historical | 132.2 | High | 0.5 | |||
| Change (%) | 12 | High | 0.5 | ||||
| Southeast Asia (SEA) | Temperature | Frost Days | Historical | 0 | Low | 0 | 0 |
| Days > 40°C | Historical | 0.3 | Low | 0 | |||
| Change (Days) | 1.1 | Low | 0 | ||||
| Hydrological | CDD | Historical | 26.8 | Low | 0 | 0.75 | |
| Change (Days) | 0.8 | Medium | 0.25 | ||||
| 5-Day Precip | Historical | 168.4 | High | 0.5 | |||
| Change (%) | 7.3 | Low | 0 | ||||
| Northern Australia (NAU) | Temperature | Frost Days | Historical | 0 | Low | 0 | 0.75 |
| Days > 40°C | Historical | 11.8 | Medium | 0.25 | |||
| Change (Days) | 20.4 | High | 0.5 | ||||
| Hydrological | CDD | Historical | 95.7 | High | 0.5 | 1.25 | |
| Change (Days) | 0.7 | Medium | 0.25 | ||||
| 5-Day Precip | Historical | 163.7 | High | 0.5 | |||
| Change (%) | 7.7 | Low | 0 | ||||
| Central Australia (CAU) | Temperature | Frost Days | Historical | 0.1 | Low | 0 | 1 |
| Days > 40°C | Historical | 27.8 | High | 0.5 | |||
| Change (Days) | 75.8 | High | 0.5 | ||||
| Hydrological | CDD | Historical | 27.3 | Low | 0 | 1 | |
| Change (Days) | 3.5 | High | 0.5 | ||||
| 5-Day Precip | Historical | 86.5 | High | 0.5 | |||
| Change (%) | 4.7 | Low | 0 | ||||
| Eastern Australia (AU) | Temperature | Frost Days | Historical | 1.4 | Low | 0 | 0 |
| Days > 40°C | Historical | 2.7 | Low | 0 | |||
| Change (Days) | 4.2 | Low | 0 | ||||
| Hydrological | CDD | Historical | 35.8 | Low | 0 | 0.5 | |
| Change (Days) | -0.5 | Low | 0 | ||||
| 5-Day Precip | Historical | 120.6 | High | 0.5 | |||
| Change (%) | 5.6 | Low | 0 | ||||
| Southern Australia (SAU) | Temperature | Frost Days | Historical | 1.3 | Low | 0 | 0 |
| Days > 40°C | Historical | 7.1 | Low | 0 | |||
| Change (Days) | 6.9 | Low | 0 | ||||
| Hydrological | CDD | Historical | 40.2 | Low | 0 | 0.5 | |
| Change (Days) | 2 | High | 0.5 | ||||
| 5-Day Precip | Historical | 60.3 | Low | 0 | |||
| Change (%) | 2.8 | Low | 0 | ||||
| New Zealand (NZ) | Temperature | Frost Days | Historical | 5.9 | Low | 0 | 0 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0 | Low | 0 | ||||
| Hydrological | CDD | Historical | 13.8 | Low | 0 | 0.75 | |
| Change (Days) | 0.5 | Medium | 0.25 | ||||
| 5-Day Precip | Historical | 92.3 | High | 0.5 | |||
| Change (%) | 5.6 | Low | 0 | ||||
| South Pacific Ocean (SPO) | Temperature | Frost Days | Historical | 0 | Low | 0 | 0 |
| Days > 40°C | Historical | 0 | Low | 0 | |||
| Change (Days) | 0 | Low | 0 | ||||
| Hydrological | CDD | Historical | 19.4 | Low | 0 | 0.5 | |
| Change (Days) | -0.5 | Low | 0 | ||||
| 5-Day Precip | Historical | 183.3 | High | 0.5 | |||
| Change (%) | 3.8 | Low | 0 |
Table F2. Global Benchmark Values for Extreme Weather Risks.
| Time Frame | Variable | Median | 75th % | 90th % |
|---|---|---|---|---|
| Historical | Frost Days | 89.8 | 94.1 | 97.5 |
| Days Max Temp > 40°C | 9.9 | 15.1 | 21.9 | |
| Consecutive Dry Days | 63.7 | 71 | 76.2 | |
| Maximum 5-day Precipitation (mm) | 79.5 | 86 | 90.4 | |
| Projected Future | Frost Days | - | - | - |
| Days Max Temp > 40°C | 9.9 | 11.8 | 14.6 | |
| Consecutive Dry Days | 0.3 | 1.1 | 1.8 | |
| Maximum 5-day Precipitation (%) | 8.9 | 11.5 | 14.1 |
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 Agroforestry Risk Assessment for each Reporting Period.
The following steps are used to convert the outputs of the Agroforestry 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 | 2.6% | |
| 2 | 3.1% | |
| 3 | 4.8% | |
| 4 | 7.7% | |
| 5 | 9.4% | |
| 6 | 9.9% | |
| 7 | 10.0% | |
| Financial Viability Risk | 0 | 2.5% |
| 1 | 2.6% | |
| 2 | 2.9% | |
| 3 | 3.9% | |
| 4 | 6.3% | |
| 5 | 8.6% | |
| 6 | 9.6% | |
| 7 | 9.9% | |
| 8 | 10.0% | |
| Social Governance Risk | 0 | 2.5% |
| 1 | 2.6% | |
| 2 | 2.7% | |
| 3 | 3.1% | |
| 4 | 3.9% | |
| 5 | 5.3% | |
| 6 | 7.2% | |
| 7 | 8.6% | |
| 8 | 9.4% | |
| 9 | 9.8% | |
| 10 | 9.9% | |
| 11 | 10.0% | |
| Disturbance Risk | 0 | 2.5% |
| 0.25 | 2.5% | |
| 0.5 | 2.6% | |
| 0.75 | 2.6% | |
| 1 | 2.6% | |
| 1.25 | 2.6% | |
| 1.5 | 2.6% | |
| 1.75 | 2.6% | |
| 2 | 2.7% | |
| 2.25 | 2.7% | |
| 2.5 | 2.8% | |
| 2.75 | 2.8% | |
| 3 | 2.9% | |
| 3.25 | 3.0% | |
| 3.5 | 3.1% | |
| 3.75 | 3.2% | |
| 4 | 3.3% | |
| 4.25 | 3.5% | |
| 4.5 | 3.7% | |
| 4.75 | 3.9% | |
| 5 | 4.2% | |
| 5.25 | 4.5% | |
| 5.5 | 4.8% | |
| 5.75 | 5.1% | |
| 6 | 5.5% | |
| 6.25 | 5.9% | |
| 6.5 | 6.3% | |
| 6.75 | 6.6% | |
| 7 | 7.0% | |
| 7.25 | 7.4% | |
| 7.5 | 7.7% | |
| 7.75 | 8.0% | |
| 8 | 8.3% | |
| 8.25 | 8.6% | |
| 8.5 | 8.8% | |
| 8.75 | 9.0% | |
| 9 | 9.2% | |
| 9.25 | 9.3% | |
| 9.5 | 9.4% | |
| 9.75 | 9.5% | |
| 10 | 9.6% | |
| 10.25 | 9.7% | |
| 10.5 | 9.7% | |
| 10.75 | 9.8% | |
| 11 | 9.8% | |
| 11.25 | 9.9% | |
| 11.5 | 9.9% | |
| 11.75 | 9.9% | |
| 12 | 9.9% | |
| 12.25 | 9.9% | |
| 12.5 | 9.9% | |
| 12.75 | 10.0% | |
| 13 | 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 Project has completed the Agroforestry 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% + 2.9% = 17.2%
Terasaki Hart, D. E., Yeo, S., Almaraz, M., Beillouin, D., Cardinael, R., Garcia, E., ... & Cook-Patton, S. C. (2023). Priority science can accelerate agroforestry as a natural climate solution. Nature Climate Change, 13(11), 1179-1190. ↩
Roe, S. et al. Land‐based measures to mitigate climate change: potential and feasibility by country. Glob. Change Biol. 27, 6025–6058 (2021). ↩
Lasco, R. D., Delfino, R. J. P., Catacutan, D. C., Simelton, E. S., & Wilson, D. M. (2014). Climate risk adaptation by smallholder farmers: the roles of trees and agroforestry. Current Opinion in Environmental Sustainability, 6, 83-88. ↩
Ickowitz, A., McMullin, S., Rosenstock, T., Dawson, I., Rowland, D., Powell, B., ... & Nasi, R. (2022). Transforming food systems with trees and forests. The Lancet Planetary Health, 6(7), e632-e639. ↩
Rosenstock, T. S., Dawson, I. K., Aynekulu, E., Chomba, S., Degrande, A., Fornace, K., ... & Steward, P. (2019). A planetary health perspective on agroforestry in Sub-Saharan Africa. One Earth, 1(3), 330-344. ↩
Tranchina, M., Reubens, B., Frey, M., Mele, M., & Mantino, A. (2024). What challenges impede the adoption of agroforestry practices? A global perspective through a systematic literature review. Agroforestry Systems, 98(6), 1817-1837. ↩
Ollinaho, O. I., & Kröger, M. (2021). Agroforestry transitions: The good, the bad and the ugly. Journal of Rural Studies, 82, 210–221. https://doi.org/10.1016/j.jrurstud.2021.01.016↩
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. ↩↩2
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. ↩↩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. ↩
Searle, E. B., & Chen, H. Y. (2017). Tree size thresholds produce biased estimates of forest biomass dynamics. Forest Ecology and Management, 400, 468-474. ↩
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. ↩↩2
IUCN. 2024. The IUCN Red List of Threatened Species. Version 2024-1. https://www.iucnredlist.org. Accessed on [16 Oct. 2024]. ↩
Jinger, D., Kumar, R., Kakade, V., Dinesh, D., Singh, G., Pande, V. C., ... & Singhal, V. (2022). Agroforestry for controlling soil erosion and enhancing system productivity in ravine lands of Western India under climate change scenario. Environmental Monitoring and Assessment, 194(4), 267. ↩
Pappo, E., Cook-Patton, S., Beillouin, D., Cardinael, R., Cesario, F., Culbertson, K., ... & Bennett, R. (2025). Carbon payment strategies in coffee agroforests shape climate and biodiversity outcomes. Communications Earth & Environment, 6(1), 661. ↩
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. ↩
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. W. (2019). International principles and standards for the practice of ecological restoration. Restoration Ecology. 27 (S1): S1-S46., 27(S1), S1-S46. ↩
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↩↩2
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/↩
Cohn, A. S., Newton, P., Gil, J. D., Kuhl, L., Samberg, L., Ricciardi, V., Manly, J.R., & Northrop, S. (2017). Smallholder agriculture and climate change. Annual Review of Environment and Resources, 42(1), 347-375. ↩
Kuzma, S., Bierkens, M. F., Lakshman, S., Luo, T., Saccoccia, L., Sutanudjaja, E. H., & Van Beek, R. (2023). Aqueduct 4.0: Updated decision-relevant global water risk indicators. ↩
Hoek van Dijke, A. J., Herold, M., Mallick, K., Benedict, I., Machwitz, M., Schlerf, M., ... & Teuling, A. J. (2022). Shifts in regional water availability due to global tree restoration. Nature Geoscience, 15(5), 363-368. ↩
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
Aalde, Harald. vol. 4, Institute for Global Environmental Strategies (IGES), 2006. IPCC Guidelines for National Greenhouse Gas Inventories: Agriculture, Forestry and Other Land Use. ↩↩2↩3
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↩
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. ↩
Cardinael, R., Cadisch, G., Dupraz, C., Lojka, B., & Oelbermann, M. (2025). Guidelines for improved quantification and reporting of carbon stocks and additional carbon storage in agroforestry systems. Agroforestry Systems, 99(4), 82. ↩↩2
Kattge, J., Bönisch, G., Díaz, S., Lavorel, S., Prentice, I. C., Leadley, P., ... & Cuntz, M. (2020). TRY plant trait database–enhanced coverage and open access. Global change biology, 26(1), 119-188. ↩
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. ↩↩2
Sanders‐DeMott, R., Hutyra, L. R., Hurteau, M. D., Keeton, W. S., Fallon, K. S., Anderegg, W. R. L., ... & Walker, W. S. (2025). Ground‐Truth: Can Forest Carbon Protocols Ensure High‐Quality Credits?. Earth's Future, 13(5), e2024EF005414. ↩
Coffield, S. R., Vo, C. D., Wang, J. A., Badgley, G., Goulden, M. L., Cullenward, D., ... & Randerson, J. T. (2022). Using remote sensing to quantify the additional climate benefits of California forest carbon offset projects. Global Change Biology, 28(22), 6789-6806. ↩
Andam, K. S., Ferraro, P. J., Pfaff, A., Sanchez-Azofeifa, G. A., & Robalino, J. A. (2008). Measuring the effectiveness of protected area networks in reducing deforestation. Proceedings of the national academy of sciences, 105(42), 16089-16094. ↩
Ferraro, P. J., & Hanauer, M. M. (2014). Quantifying causal mechanisms to determine how protected areas affect poverty through changes in ecosystem services and infrastructure. Proceedings of the national academy of sciences, 111(11), 4332-4337. ↩
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/↩
Terra, T. N., Immitzer, M., Hemes, K. S., Fronza, J. G., Pierre, J., Della Justina, D. D., & Atzberger, C. (2023). Monitoring agroforestry projects over time by remote sensing: dynamic baselines for the quantification of additionality. ↩
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. ↩
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. ↩
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(1), 101-118. ↩
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↩↩2
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↩
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↩
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
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. ↩
Nardi, F., Annis, A., Di Baldassarre, G., Vivoni, E. R., & Grimaldi, S. (2019). GFPLAIN250m, a global high-resolution dataset of Earth’s floodplains. Scientific data, 6(1), 1-6. ↩