Contents
Introduction
Several terrestrial biosphere Carbon Dioxide Removal (CDR) approaches rely on the capture and storage of carbon in living woody biomass, including both aboveground biomass (AGB) and belowground biomass (BGB). The quantification of BGB is often dependent upon AGB1, which is more directly observable. Thus, for these pathways, accurately and conservatively quantifying the gross storage of carbon in woody biomass is crucial for demonstrating net CO2 removal.
Aboveground biomass (AGB) encompasses all living vegetation above the soil surface, including stems, branches, foliage, and bark. Woody biomass refers to plants whose structure includes lignified stems, such as bamboo, shrubs, and trees. Belowground woody biomass (BGB) encompasses the subsurface woody biomass in root systems.
Field-based measurements underpin biomass estimation, typically identifying species and employing individual plant measurements of diameter at breast height (DBH), vegetation height, and wood density. These measurements feed into allometric equations, which are empirically derived relationships between these empirical parameters and biomass. These equations are species- or biome-specific, and are often developed through extensive field- and laboratory-based research.
Future Versions
This Module was developed based on the current state of the art, publicly available science regarding quantification of woody aboveground biomass and long-term monitoring of terrestrial ecosystems. This Module aims to be scientifically stringent and robust. We recognize that some requirements may exceed the status quo in the market and that there will be opportunities to improve the rigor of this Module.
Additionally, this Module will be reviewed when there is an update to published scientific literature, government policies, or legal requirements which would affect net CO2e removal quantification or the monitoring guidelines outlined in this Module, or at a minimum of every 2 years.
Applicability
This Module quantifies the total CO2 equivalent stored as aboveground woody biomass across the project area () at a given time point, t, through direct vegetation sampling and parameter estimation within survey plots and scientifically validated allometric equations. Where included as a pool, it also quantifies the total CO2 equivalent stored as belowground woody biomass across the project area () at a given time point, t, which is derived from the directly sampled aboveground biomass.
This Module is applicable to Projects where reliable field measurement data can be consistently collected, reported, and verified.
Throughout this Module, the use of “must” indicates a requirement, whereas “should” indicates a recommendation.
For the purposes of this Module, any allometric equations employed by the Project must have widespread acceptance in scientific literature or rigorous evidence supporting its applicability. Newly developed allometric equations must undergo validation against peer-reviewed standards and reference datasets.
Quantification of Biomass
This Module only quantifies living aboveground woody biomass and, where it is included as a pool, belowground woody biomass. Standing dead trees and deadwood are excluded from this Module.
Calculation of CO2eAGB
(tonnes) can be calculated by taking sufficient field plot measurements to obtain an estimate of the mean AGB density (in tonnes CO2e), which can then be multiplied by the project area to obtain a total AGB carbon pool:
(Equation 1)
Where:
- is average AGB density, in tonnes CO2e/hectare.
- is the total project area, in hectares.
Estimation of is based on direct measurements of tree parameters (e.g., diameter at breast height (DBH) in field plots), and the use of allometric equations to convert tree parameters to biomass.
As field plots may be of unequal area, average AGB density must be calculated as an area-weighted average to ensure the resultant is expressed in tonnes CO2e per hectare:
(Equation 2)
Where:
- is the AGB density (tonnes CO2e/hectare), in plot at time .
- is the area of plot , in hectares.
- is the number of plots.
Biomass density within each plot at a given time point is calculated by summing the biomass of all individual woody plants in that plot:
(Equation 3)
Where:
- is the aboveground biomass of the tree in plot , derived from an appropriate allometric equation, in tonnes CO2e.
- is the number of trees in plot .
For each tree within the plot, the aboveground biomass of each tree is determined via an allometric model (Section 4.3) which converts field measurements of tree size into a total aboveground biomass (tonnes). This value must be converted to a CO2e basis using the appropriate carbon fraction (), which describes the fraction of woody biomass that is carbon, and then applying the mass conversion for mass CO2 to mass C ().
The carbon fraction, , must be chosen from the following hierarchy:
- A regional and species-specific factor that is justified based on scientific literature (e.g., Doraisami et al., 20222). This is the preferred approach to have the most accurate estimate and avoid overestimation;
- If the above is not available, then a genus-specific or national average factor that is justified based on scientific literature can be used;
- As a last resort, if it is proven that the above two factors are not available, then a default factor of 47%, which is a mean across species, can be used3,4.
If the project area is stratified, the total biomass is calculated as the area-weighted sum over all the strata:
(Equation 4)
Where:
- is the area of strata of total strata, in hectares
- is the mean AGB density in strata , in tonnes per ha
- is the total project area, in hectares
Calculation of MBGB
The total carbon stored in belowground woody biomass at time () is determined by multiplying the measured aboveground biomass for each individual by an appropriate root-to-shoot ratio (), a dimensionless parameter which describes the ratio of belowground biomass to aboveground biomass:
(Equation 5)
Where:
- is the carbon stored in belowground biomass in tree at time , in tonnes CO2e
- is the dimensionless root-to-shoot ratio
Appropriate root-to-shoot ratios should be selected by regional and species-specific factors that are justified based on scientific literature (e.g., USFS's Component Ratio Method or similar national-level species-specific ratios). This is the preferred approach to have the most accurate estimate and avoid overestimation. If sufficient evidence is provided to demonstrate that no suitable project-specific factor can be obtained, matching to the ecological zone and continent of the project area, based on the IPCC 2019 Table 4.43, 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 Database5.
The uncertainty in selected factors must be reported from the same source dataset. For example, the IPCC 2019 Chapter on Forest Land3 provides an uncertainty in the root-to-shoot ratio.
With the calculated BGB values for each measured individual tree, the same procedure for scaling from individual measurements to project-level estimates is used for BGB as described for AGB in Section 4.1.
Allometric Equation Requirements
Allometric equations must be specific to the forest type and ecoregion in which the Project is located.
For each allometric model, the applicable size range over which it may be applied must be reported (e.g., DBH > 5 cm) reflecting the size range over which the model was developed and validated.
Project Proponents should use independently published allometric equations, from the following sources, in order of preference:
- Local peer-reviewed equations;
- National forest inventories;
- Chave, et al. (2014)6 for project areas in the Tropics;
- IPCC generalized equations.
Projects may deviate from this hierarchy with justification in scenarios where models from lower tiers offer better quality or fit to the project scenario (e.g., larger sample sizes, applicable size range, etc.).
Where wood density is required as part of the allometric model for calculation of AGB, Project Proponents must use wood density values from the following hierarchy:
- Species -specific values sourced from scientific literature or databases (e.g., Global Wood Density Database)
- Genus or Family specific values
- Ecosystem mean values
Use of New Allometric Models
Any proposed allometric equations used must have clear documentation of their development, validation, and applicability to the project area. Additionally, Project Proponents must demonstrate that the proposed equations meet the following requirements:
- Provide documentation of robust validation through peer-reviewed publication or an equally-rigorous scientific review.
- Include validation datasets (must be withheld from calibration) and clearly report metrics such as relative root mean square error (RMSE), relative bias, and the residual standard error and distribution. These must be reported both overall and by diameter class.
- Provide comparative analysis with established equations to demonstrate equal or improved accuracy.
- Justify suitability explicitly for the Project's specific biome and species composition.
In order to use a newly developed allometric model, the Project Proponent must demonstrate that a suitable model does not exist in the scientific literature. To demonstrate this, Project Proponents must supply a list of search terms of relevant project characteristics to be captured in the allometric model (e.g., species, setting, size class) and a list of scientific databases which were used to search for suitable allometric models in the literature. If any potential models exist, a newly developed model can only be used where the new allometric model produces more conservative estimates of biomass or where it can be justified that the new model is of demonstrably better quality (e.g., developed using larger sample sizes, lower uncertainty, etc.).
Uncertainty
Models and measurements of woody biomass inherently include uncertainty from the assumptions and various sources of data which are used in the calculation of biomass.
While it is not expected that all uncertainties are exhaustively quantified, Project Proponents must evaluate, report, and conservatively account for identifiable and significant sources following the approved approaches outlined in the Isometric Standard.
Potential sources of uncertainty to consider include, but are not limited to:
- Errors in field measurements (e.g., DBH measurement errors, height estimation bias)
- Variability in measured plant traits (e.g., wood density variability)
- Plot sampling design (e.g., plot representativeness)
- Uncertainty associated with allometric equations used
Field Measurements & Plot Design
Field measurements must follow a prescribed field manual and best practices guidelines.
Recommended resources for guidance on field plot surveys include:
- USFS Measurement guidelines for forest sequestration7;
- Climate Action Reserve’s inventory manual8; and
- RAINFOR protocol, which has guidance on establishing plots, tree measurements, and data recording9.
Field sampling must be conducted within a number of representative plots spanning the project area. At minimum, there must be at least three plots within each strata to enable variance calculations. The plot size and design must be sufficient to capture heterogeneity and reduce edge effects, and based on best practices for the setting and forest characteristics. The area of plots established on sloped terrain must be corrected to ensure the true (horizontal) ground area is used in subsequent calculations. Field plots must be determined a priori, and any changes in field plots during the Crediting Period must be disclosed and justified. Robust field sampling design can be expected to decrease the uncertainty of the resulting biomass estimates.
Projects must describe the process used for determining the spatial distribution of plots and justification for how it ensures representative and statistically robust sampling. It is recommended that projects use either a randomized or systematic approach to help ensure plot distribution is unbiased (e.g., favoring locations next to roads). It is recommended that plots are placed, at minimum, 200 m apart from one another. Designs which use more clustered plot locations must be justified. Project Proponents must also develop and document a pre-specified procedure for handling inaccessible or unsafe plot locations.
For project areas where there is heterogeneity in forest cover or conditions, projects must use a stratified design for their measurements. For stratification, Project Proponents must provide details on their procedure and report:
- Factors used for stratification and the corresponding data sources
- The boundaries (as a GIS file) and areas of each stratum
- Plot allocation across strata
- Plans for how strata will be reviewed and revised over time
Factors used for stratification should be selected to reflect relevant variables for the project setting and intervention. This may include, but is not limited to, differences in forest/vegetation type, stand age/structure, productivity, physical environmental variables, management/intervention differences, system type, and planting density.
Projects which do not stratify must provide justification and evidence that the project area is homogeneous.
It is expected that the field sampling design will be tailored to the project area and conditions. Project areas with more heterogeneity in biomass are likely to need a higher number of field plots and/or larger field plots than project areas with more homogeneous biomass. As such, the below are recommended best practices to help decrease the uncertainty of biomass estimates, but are not strict requirements:
-
Fixed-radius permanent sample plots are recommended
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Plot size and shape should be chosen to suit the forest type, stem density, and terain
-
Where permanent plots are used, plot centers or other landmarks should be monumented and a reference azimuth recorded to enable remeasurement over time
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Projects may use a nested field plot design, with clear documentation submitted for the design and resulting calculations
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Projects should establish enough plots to achieve good precision in the mean AGB estimate, with a recommended target being +/- 10% at 90% confidence. The number of plots should be determined using this target along with the observed or estimated variance of biomass within the project area, with further consideration of plot size and project area heterogeneity.
Data Collection
Within each plot, the species of individual trees must be recorded. Projects must provide details on the procedure used for species identification. Stems which cannot be confidently identified must be recorded as such, and the most conservative allometric model and parameter values must be applied for calculation of the biomass.
The following data must be collected, with the sub-bullets indicating recommended additional data collection:
-
Tree diameter at 1.3 m above the ground (DBH) must be recorded for all trees in the field plot with a diameter greater than 10 cm. Where allometric models use metrics other than DBH (e.g., crown area or basal stem diameter), these variables must be collected in lieu of a standard DBH for the corresponding species and the procedures for this must be clearly defined within the field protocol.
- Recommended: DBH should be recorded for trees with a diameter greater than 5 cm.
- Recommended: During the initial years following planting, there may not be many trees with DBH > 5 or 10 cm. However, field plot surveys should still monitor for any potential disease, ecological hazards, and/or mortality as these risks can be higher in young trees.
-
G-EBVH-0GPS coordinates of a plot reference point sufficient to enable relocation must be recorded using mapping-grade receivers or higher (capable of achieving < 3 m accuracy, e.g., 500 measurements at a rate of 1 point per second).
- Recommended: Multiple location measurements should be taken at each point of interest.
-
Tree height must be collected for individuals where it is required for the allometric model. If it is not required for the allometric model then measurement of height is optional.
- Recommended: Tree height should be recorded for a subset of trees (e.g., selected using a basal-area factor prism), even if not required for the allometric model.
Reporting
Project Proponents must report the following information in the Project Design Document (PDD):
Field measurements:
- Field manual that was followed for sampling
- Description of field plots, and how they were designed, allocated, and selected
- Stratum definitions and areas
- GPS coordinates, shape, size, and orientation of field plots
- G-20Q6-0Description of measurement approaches and instruments used (e.g., diameter tape or calipers for DBH, clinometer or hypsometer for tree height)
Allometric equations used and their sources:
- Allometric equations used and their sources
- Any other input parameters used (e.g., wood density) and their sources)
- Assessment of major sources of uncertainty (e.g., measurement errors, equation parameterization):
- Quantify uncertainty for key identified sources through the approved approaches outlined in the Isometric Standard.
- Report conservative AGB estimates
For each Verification, Project Proponents must submit a description of the measurements collected and report the full tree-level field inventory data. This includes, at minimum, the plot ID, species, and DBH for each measured individual. Any changes in methods between verifications (e.g., changes in allometric models) must be reported and justified.
Acknowledgements
Isometric would like to thank Renoster, for their extensive feedback during this Module's development.
Definitions
- Carbon Dioxide Equivalent Emissions (CO₂e)The amount of CO₂ emissions that would cause the same integrated radiative forcing or temperature change, over a given time horizon, as an emitted amount of GHG or a mixture of GHGs. One common metric of CO₂e is the 100-year Global Warming Potential.
- ModuleIndependent components of Isometric Certified Protocols which are transferable between and applicable to different Protocols.
Relevant Works
Footnotes
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Pan, Y., Birdsey, R. A., Fang, J., Houghton, R., Kauppi, P. E., Kurz, W. A., ... & Hayes, D. (2011). A large and persistent carbon sink in the world’s forests. Science, 333(6045), 988-993. https://doi.org/10.1126/science.1201609 ↩
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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 ↩
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Aalde, Harald. vol. 4, Institute for Global Environmental Strategies (IGES), 2006. IPCC Guidelines for National Greenhouse Gas Inventories: Agriculture, Forestry and Other Land Use. https://www.osti.gov/etdeweb/biblio/20880391 ↩ ↩2 ↩3
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McGroddy, M. E., Daufresne, T., & Hedin, L. O. (2004). Scaling of C: N: P stoichiometry in forests worldwide: Implications of terrestrial redfield‐type ratios. Ecology, 85(9), 2390-2401. https://doi.org/10.1890/03-0351 ↩
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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. ↩
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Chave, J., Réjou‐Méchain, M., Búrquez, A., Chidumayo, E., Colgan, M. S., Delitti, W. B., ... & Vieilledent, G. (2014). Improved allometric models to estimate the aboveground biomass of tropical trees. Global change biology, 20(10), 3177-3190. https://doi.org/10.1111/gcb.12629 ↩
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Pearson, T. R. (2007). Measurement guidelines for the sequestration of forest carbon (Vol. 18). US Department of Agriculture, Forest Service, Northern Research Station. https://doi.org/10.2737/NRS-GTR-18 ↩
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Climate Action Reserve (2018). Standardized Inventory Methodology Version 1.0. https://www.climateactionreserve.org/wp-content/uploads/2018/06/Standardized-Inventory-Methodology_v1.0.pdf ↩
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Phillips, O., Baker, T., Feldpausch, T., & Brienen, R., (2001). RAINFOR Field Manual for Plot Establishment and Remeasurement. https://forestplots.net/upload/ManualsEnglish/RAINFOR_field_manual_EN.pdf ↩
Contributors
