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Methodologies
Technical specifications and calculation frameworks for evaluating avoided emissions through wood product substitution.
Technical specifications and calculation frameworks for evaluating avoided emissions through wood product substitution.
Forest Stand Carbon
Harvested Wood Product
The Custom Forest Inventory Tool (CFIT) enables users to translate traditional forest inventory data into a complete forest carbon inventory. Users upload their forest inventory data to the secure platform using the platform’s inventory templates and the CFIT uses those data to produce forest carbon stock and stock change estimates using standardized conversion procedures and USDA Forest Inventory and Analysis data.
While many corporate forest landowners have extensive forest inventory data, corporate forest inventories are usually focused on the “merchantable” (available for commercial use) portion of the forest. Other forest components (dead wood, soils, forest floor or litter layer) are not typically measured but are important elements of forest carbon estimation. The CFIT tool was designed, based on interviews with corporate forest inventory managers, to utilize the data commonly collected through corporate inventories to obtain estimates of all forest carbon stocks and stock changes across all forest carbon pools.
CFIT accomplishes this by matching user-supplied stand-level inventory data to “similar” forests measured by the USDA Forest Service’s Forest Inventory and Analysis (FIA) program. This ensures that carbon stock estimates are consistent for similar stands across a variety of ownerships and that users benefit from the scientifically reviewed carbon data and estimation methods used by FIA. Furthermore, to convert traditional tree inventories into carbon estimates, a consistent set of conversion factors are applied to convert tree volumes to weights, and weights to carbon stock estimates. This supports transparency, consistency, and comparability across corporate carbon inventory compilation efforts.
Throughout this document, reference will be made to codes, data, and equation coefficients stored in tables in the Excel workbook “CFIT_User_Documentation_Tables.xlsx”, which is an important part of this documentation.
Ac: Acres (land area measurement)
Bf: Board feet (wood volume measurement)
CO2e: Carbon dioxide equivalent
Cords: Cords (wood volume measurement)
Cubic feet, cf: Cubic feet (wood volume measurement)
CFIT Custom Forest Inventory Tool
DBH: Diameter at Breast Height; tree diameter measurement
DFCT Default Forest Carbon Tool
Dry tons: Wood weight measurement
FACT Forest Analytics for Carbon Tracking
FIA: Forest Inventory and Analysis (program of USDA Forest Service, National Forest Inventory)
FIPS: Federal Information Processing Standard (here, codes for identifying US counties)
Green tons: Wood weight measurement
MBF: Thousand board feet; wood volume measurement
Metric tonnes: Weight measurement
MT: Metric tonnes
NC: North Central (US Region)
NE: Northeast (US Region)
NLS: Northern Lake States (US Region)
PNWE: Pacific Northwest, East side (US Region)
PNWW: Pacific Northwest, West side (US Region)
PSW: Pacific Southwest (US Region)
Pulpwood: Smaller-diameter tree (or log) used primarily for paper manufacturing
RMN: Rocky Mountain North (US Region)
RMS: Rocky Mountain South (US Region)
Sapling: Individual of a tree species with DBH < 1 inch
Sawtimber: Larger diameter tree (or log) suitable for purchase by a sawmill
SC: South Central (US Region)
SE: Southeast (US Region)
Short tons: Imperial ton (2000 pounds)
The CFIT results are produced based on user-supplied inventory data, which must be submitted using the templates provided in the platform. These data serve as the basis for estimates of carbon stocks, as well as changes in those carbon stocks if more than one year of inventory data are provided.
Users have the option to choose one or both of the templates/inventory file types provided by the platform, depending on the level of detail contained in their existing forest inventory data, described in Table 1 below.
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If a user supplies CFIT with a single set of inventory data that represents a single point in time, the CFIT provides carbon stock estimates for that point in time. Users may also upload two sets of inventory data for the same set of stands reflecting two points in time, enabling the CFIT to estimate carbon stocks for each point in time and calculate the annual carbon stock change between them.
Because CFIT is based on data from the FIA program, FIA coding systems for forest types, tree species, etc. are applied in the CFIT. Users will find valuable additional information on FIA coding standards and data in the FIA Database User Manual (Burrill, et al. 2024).
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The CFIT requires that users enter an inventory date for each set of inventory data uploaded. Most forest inventories represent a specific point in time, reflecting when the entire ownership is inventoried, as may be done before a purchase or sale of a forest. However, it is also common for portions of a large ownership to be inventoried annually or periodically, and non-inventoried portions are “grown” or “projected” using forest growth models to update the inventory to a target point in time. The CFIT was not designed to apply growth models to project inventories over time, and rather assumes that the entire inventory supplied by a user represents a specific point in time.
Where more than one inventory set is supplied to estimate annual forest carbon stock changes, those dates must be at least one year apart. The CFIT estimates annual change by computing the time interval between inventory dates (in decimal years) and then divides carbon stock changes by the interval to obtain annual stock change. This is useful for both retrospective estimates (e.g., using two prior inventories to estimate stock change over a recent period) and prospective estimates (e.g., using a current inventory and an inventory projected with a harvest scheduling model to estimate future stock changes).
For the purposes of CFIT, the forest “stand” is a land area managed as a unit by the landowner In the US, stands are generally considered to be forest areas that are sufficiently homogeneous in terms of species composition, age class, and site quality that they are subject to the same silvicultural treatments. In managed forests of the US, stands are often spatially contiguous, but they do not need to be for the purposes of CFIT. For example, some forest landowners aggregate groups of similar stands into strata that may consist of numerous noncontiguous stands spread across a broader landscape (e.g., all hardwood-dominated streamside management zones in an administrative unit). For CFIT, a stratum can be treated the same as a stand (e.g., a single record in the stand description file).
Most owners of larger areas of forest land use a hierarchical system of administrative units. For example, a single ownership “parcel” or “tract” may contain numerous stands, then a “compartment” may contain multiple tracts, a “district” may contain numerous compartments, and a “region” may contain multiple districts. CFIT accommodates such hierarchical designations by allowing users to supply up to four administrative identifiers for each stand, but a stand cannot be in more than one unit of a given administrative level (e.g., it cannot be included within two tracts), and the stand “number” must be unique within the lowest (smallest) administrative level.
The unique identifier for a stand, therefore, is the combination of up to four administrative levels and a stand number; this is referred to as the “stand key”. Stand keys must be consistent between the stand description file and the stand detail file.
In the example shown in Table 2, stand 16B must be unique within the Wilson tract (there may be other stand 16Bs in other tracts), and if there is a record for this stand in the stand detail file, the key must exactly match the key in the stand description file.
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For reporting carbon stock changes between two points in time, it is critical that the estimates be computed for a land base that remains consistent between those points in time. Otherwise, land acquisitions could appear as carbon stock increases and dispositions would appear as carbon stock losses, obfuscating the actual carbon stock change on the landscape.
It is challenging to enforce that consistency at the stand level, because most large landowners report that stand boundaries may change over time due to silvicultural treatments or natural disturbances. Therefore, the consistency of the land base is enforced at the administrative unit level as defined by the user. Annual carbon stock change will only be calculated for administrative units whose area (in acres, as provided in the input files) is the same across each inventory data set supplied to the tool.
The CFIT (and the FACT Default Forest Carbon Tool [DFCT]) operate by matching a landowner’s forest stand characteristics with “similar” plots from the FIA database. For the purpose of the FACT platform, similar is defined as plots/stands of the same region, forest type or tree species group, stand origin, and age (see Glossary for definitions). The regions used in CFIT are subregions of the conterminous US (CONUS) used in the “Managed Forest Systems” chapter within the USDA Quantifying Greenhouse Gas Fluxes: Methods for Entity-Scale Inventory Technical Bulletin (Murray, et al. 2024) and the DFCT, displayed in Figure 1.
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Figure 1: Map of the regions used in CFIT
Geographic locations supplied to the CFIT are intentionally vague. This is both to protect confidentiality of user data and because specific locations are not necessary for matching with similar FIA data. Therefore, for each stand, a user must provide either a county code or an FIA survey unit (aggregates of counties defined in the FIA database documentation (Burrill, et al. 2024) and portrayed as light gray lines in the map above). See Annex 3 for information about these codes.
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The stand description file contains one record per stand, which includes a unique identifier (stand key) as a combination of up to four administrative units and a stand number, a geographic location, descriptive information about the stand including forest type, stand age, and stand origin, and the area of the stand in acres. A full description of the stand description file is provided in Annex 1.
The stand description file provides enough information for carbon stock estimates based on regional averages, similar to the way the DFCT works. It also provides critical information used in converting tree volume/weight estimates (such as forest type and region) into carbon stock estimates.
The stand detail file may contain zero to multiple records per stand. For stands where no tree volume data are collected by the user, there will be no records in this file and estimates will be based on stand description information alone. Where tree volume data have been collected, this file will contain volume by tree species group, product class, and (optionally) tree diameter class. A full description of the stand detail file is provided in Annex 2.
Prior to processing the user-supplied inventory data for carbon stock estimates, the CFIT scans all input data for errors. Errors that prevent further processing include invalid codes, missing required fields, or faulty linkages between stand keys in the stand description and stand detail files. Where errors are detected, the CFIT notifies the user of the types of errors and the locations (records) within the input files where the errors were detected and the user is prompted to correct those errors and upload the remediated file(s).
After the input files are determined to be free of errors, they are processed as described in the methodology described in Section 6 of this document. During that processing, the CFIT may need to adapt methodological procedures based on user-supplied data parameters, triggering the platform to produce a “warning” notification intended to support transparent user interpretation of results based on processing adjustments. Examples include when a parameter such as tree diameter or stand age is beyond the range for which sufficient FIA data are available, or when a forest type group is reported in a region in which FIA has few or no records of that forest type group. In these cases, carbon stock estimates are computed based on a default (such as averages for the forest type group in other regions).
Upon processing of the user’s inventory data, several graphical outputs are rendered. These are displayed in the user interface and include estimates of total forest carbon stocks by pool for each inventory date. If two dates of inventory are provided by the user, carbon stock changes by pool can also be presented. Additional summary statistics are displayed for the data provided, such as the total land area, the number of stands, and the inventory dates. Figures 2,3,and 4 below show the graphical outputs as displayed in the user interface.
[Figures will be labeled and additional detail will be added when programming is complete]
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Summary-level information is also provided to the user in reports/tables that can be generated and saved via the user interface. [To be determined: what are the options and the contents of these?]
In addition to summary results provided in the user interface and saved reports, users can download data files in the same framework (data structures) as the data they uploaded. Additional columns will be appended to the records uploaded by the user containing carbon stock estimates associated with the input records of the stand description file(s). For example, if the user uploaded two sets of inventory data for two dates, with stand description and stand detail files for each, the files available for the user to download after processing are depicted in Figure 5.
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The stand description results files will contain all the stand description input columns as well as columns for carbon stock per acre (MT CO2e/ac) for aboveground live tree carbon, belowground live tree carbon, sapling and understory carbon, dead wood carbon, litter carbon, and soil carbon, all for the corresponding point in time.
Because estimating carbon stock in live trees at the stand level requires aggregating products within species groups and diameter classes, the carbon stock results will not offer the same level of detail (stand/species group/product class/diameter class) as in the input files.
The stock change results file will contain annual carbon stock changes in the aboveground live tree pool (MT CO2e/yr) only for the administrative units that have consistent area between the two points in time. Output records will contain values for the (up to four) administrative levels, total acres in each unit, total carbon stocks by pool at each point in time, and the annual change in carbon stock for the aboveground live tree pool.
Extensive compilation and analysis of FIA data was conducted to build sets of equations and lookup tables that provide the carbon stock estimates used in CFIT and the DFCT. For some components of forest carbon inventory, where the estimates are dependent on stand age or tree diameter class, it was necessary to develop models (fitting equations to the data). Where modeling was not needed, such as carbon fractions or conversions of green weight to merchantable dry weight, lookup tables (e.g., average values for combinations of region and forest type) were developed or factors were obtained from scientific publications.
When modeling was needed, two general types of models were developed: (1) those that predict forest carbon stocks per acre at the stand level (such as soil carbon per acre, litter carbon per acre, etc.) from stand description data, and (2) those that are applied to groupings of trees (from stand detail data) to convert tree volumes or weights into tree carbon stock estimates.
The general process flow for developing the underlying data tables and models is depicted in Figure 6.
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The following sections describe the process used for (1) extracting estimates from the FIA database for specified groupings for FIA plots, (2) developing tables of estimates or factors in cases where modeling was not necessary, (3) fitting models for each grouping to derive trends of carbon stocks across stand ages for the stand-level estimates, (4) fitting models for each grouping to derive trends of carbon stocks across diameter classes for the tree-level estimates, and (5) the construction of lookup tables containing model coefficients or other values that are used in the CFIT.
Data were retrieved from the FIA database using the FIA EVALIDator tool (USDA 2026) through its application programming interface. In conducting the EVALIDator queries, data from the two most recent non-overlapping evaluation groups were used. For example, the most recent measurement published for Maine at the time of development was from 2024, and contained data from plots measured in 2020, 2021, 2022, 2023, and 2024. The next most recent evaluation group with no overlapping measurement years was the 2019 evaluation group, containing plot measurements from 2015, 2016, 2017, 2018, and 2019.
The population of interest was all FIA plots from unreserved forestland, defined by the FIA as forest land not withdrawn from management by statute or administrative designation, and therefore generally available for multiple uses, including timber production. EVALIDator queries allow for the selection of grouping variables (such that estimates are developed for each combination of grouping variables) and filters (to isolate plots with specific characteristics from the estimates). Data from EVALIDator were extracted at the plot level so that outputs included the values of each grouping variable and the desired estimate (e.g., aboveground live tree carbon) for each plot in the population.
For modeling by stand age, the plot-level EVALIDator results were matched with recorded stand ages for each plot (rather than the stand age classes available from EVALIDator).
From the datasets resulting from each EVALIDator query, the models for stand-level and tree-level estimates were developed. Annex 3 contains lists of the specific EVALIDator attributes used in the queries for each estimate of interest at the stand level, and Annex 4 contains details for the tree-level data.
In many cases, estimates do not vary consistently across stand age classes or tree diameter classes, and therefore modeling was not necessary for some stand-level and tree-level estimation processes. For example, FIA computes soil organic carbon (SOC) stocks using a model that estimates SOC based on climate, geophysical variables, and forest type (Domke, et al. 2017). Therefore, FIA-based estimates of SOC are not expected to vary across stand ages in a predictable manner, so averages of SOC density by region and forest type were developed for the purposes of the CFIT and DFCT (CFIT User Documentation Table 15). Another example at the tree level is the application of conversion factors to translate tree green weight to dry weight. These conversions depend only on species-specific factors contained in the FIA database. Therefore, average conversion factors by species group and region were developed using that source, which were further refined into weighted averages for the tree species in the tree species groups by region.
The lookup tables used by CFIT that did not require modeling are listed in Table 3, with references to the Table number in the CFIT User Documentation Tables containing the results.
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The estimates needed at the stand level included carbon densities (MT CO2e/ac) for all carbon pools, by stand age, for each grouping used in matching the forest conditions supplied by the user to comparable FIA plots. These groupings include the region (Figure 1), broad forest type groups, FIA forest type group, and stand origin (natural or artificial regeneration). For each combination of these groupings, a model was fit to estimate the carbon stock density (for each pool) as a function of stand age. With 11 regions, 32 forest type groups, and 2 stand origins, there are potentially 704 unique combinations of these groups. However, the ability to model all of these combinations was limited by available data. For example, there were no FIA data for Douglas-fir forest type group plots, either planted or natural, in the Southeast region.
For stand-level modeling of carbon density by age, the Hugershoff model (Prodan 1968) was used:
y = y0xbe-kx
where y is the carbon density, y0, b, and k are coefficients, and x is the stand age.
During model fitting, a multi-stage approach was used, corresponding to the grouping hierarchy (Figure 7). When a model could not be fit (with statistically significant parameter estimates at alpha = 0.1) for a specific combination of groupings (for example, Southeast region, bottomland hardwood, oak/gum/cypress forest type group, planted stand origin), then the lowest level grouping (stand origin) was dropped, and in a second stage, the model was fit to the remaining groupings (region, broad grouping, and forest type group). If a significant model did not result, then the lowest-level grouping (forest type group) was dropped and a third stage model was fit to just region and major forest type group (softwoods/hardwoods). Where this hierarchical approach continued to render no significant model results, then a model was fit to just region. The result of the modeling effort was a set of parameter estimates (y0, b, and k) for each combination of the grouping variables (documented in the CFIT User Documentation Tables file).
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The estimates needed at the tree level include several factors to convert user inputs to tree carbon estimates. The processing flow for stand detail data is depicted in Figure 8. User inputs (volumes/weights of inventoried trees in a stand, by tree species groups, product classes, and diameter classes) may be in a variety of units (cubic feet, cords, thousand board feet, tons). All inputs must be converted to green weight, which requires a variety of conversion factors.
Additional conversion factor ratios are needed to estimate total aboveground biomass from merchantable biomass, and carbon from dry weight (biomass), belowground carbon from aboveground carbon, etc. Many of these conversion factors are developed from models based on ratios of FIA data, others are based on factors reported in the literature, or factors that do not vary with age or diameter and therefore need no modeling.
The groupings used for tree-level modeling are region, major species group (hardwood/softwood), FIA tree species group, and stand origin. Within each combination of groupings, a model was fit to estimate the factors needed as a function of tree diameter (DBH). In addition to the Hugershoff model used in stand-level modeling, tree aboveground to merchantable bole conversion factors were modeled using a modified version of the negative exponential decay function:
y = y0e-kx + c
where y is the factor of interest, y0, k, and c are coefficients, and x is the midpoint of the tree DBH class. During model fitting, the same multi-stage approach was used to fit models to fewer grouping levels as needed to obtain significant parameter estimates.
The factors developed using this modeling approach are listed in Table 4, with the model form used.
After all modeling was conducted, tables were prepared for each modeling step with all of the relevant grouping variables and the three modeling coefficients (y0, b, and k for Hugershoff models; y0, k, and c for negative exponential models). These tables of model coefficients, combined with the tables developed without modeling, represent the synthesized information that allows CFIT to perform all of the necessary calculations to develop carbon stock estimates from user inventory data at the stand and tree level. These tables are available in the CFIT User Documentation Tables file.
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This section describes the processing flow that CFIT uses to combine user-provided stand description and stand detail data with the pre-processed underlying data derived from FIA data. It begins with computing carbon stocks from the stand description data, then computes live tree carbon stocks from the stand detail data. It then adds carbon in un-inventoried trees (saplings) and understory to get totals for aboveground and belowground biomass. Finally, it combines all estimates for each point in time.
If two dates of inventory data are provided, it repeats the above steps for the second date, and finally computes carbon stock changes for geographically consistent administrative units.
For carbon pools not measured in conventional forest inventories (sapling and understory, dead wood, belowground carbon, soil carbon, etc.), the CFIT provides estimates based on descriptive information about the stand, obtained for each stand from the stand description file.
The user-supplied information on region, forest type group, stand origin, and stand age for each stand is used to select the appropriate model coefficients or values from lookup tables to calculate forest carbon densities (tons/ac), and then multiplied by stand area (acres) to get total carbon stock for each carbon pool.
Tables of model coefficients and lookup values for estimating forest carbon densities are contained in the CFIT_Lookup_Tables workbook. The tables contain values with more digits than are reported below (shortened here for convenience).
All carbon stock estimates will be in tons C (and tons C/acre) and are converted to metric tonnes of carbon dioxide equivalents (MT CO2e) at a later step.
The user-provided county FIPS codes or FIA survey unit codes are used to identify the region, based on what is documented in the County_Master table in the Valid Codes workbook or the the FIA_Unit table which documents FIA survey unit codes.
Where a user provides both a County FIPS code and an FIA Unit code, the County FIPS code takes precedence due to its greater spatial resolution.
Example: a record in the stand description file indicates the County_FIPS code is 22115. Looking this value up in the County_Master table of the Valid Codes workbook, we find this is Vernon county (parish) in Louisiana (22 is the state FIPS code for Louisiana, and 115 is the code for Vernon county, LA). This county belongs to FIA survey unit number 3 in Louisiana, or FIA_UNIT code 2203. The region code is SC (South Central).
Similarly, FIA_unit 2203 in the FIA_unit table in the Valid Codes workbook lists the corresponding region code is SC (South Central).
Table 11 in the CFIT User Documentation Tables provides the lookup values for model parameters for live aboveground carbon . Model parameters are grouped by region, forest type code, and stand origin code. The CIFT matches the user-provided region with those listed in the REG_11 column, the forest type code in the FORTYPGRPCD column and the stand origin in the STAND_ORIGIN column to retrieve the lookup table values for the three parameters needed: y0 (from the Estimate.y0 column), b (from the Estimate.b column), and k (from the Estimate.k column). Live aboveground carbon density (lagcd) can then be computed using the following equation (i.e., Hugershoff model)
lagcd = y0 * ab * exp(-k * a)
where lagcd is the live aboveground carbon density in tons per acre,
y0 is the parameter retrieved from the lookup table,
a is the stand age from the stand description file,
b is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
k is the parameter retrieved from the lookup table.
Finally, to get total live aboveground tree carbon in the stand, the per-acre lagcd value is multiplied by the stand area from the stand description file.
lagc = lagcd * Stand_area
Example: a record in the stand description file indicates that stand number 28 is in the SC region, forest type 600, Natural stand origin, age 62 years old, and contains 58.69 acres.
In the lookup table, we find the corresponding record contains the following parameters:
y0 = 1.41424
b = 0.79210
k = 0.003188
The live aboveground carbon density (carbon per acre) is then:
lagcd = (1.41424) * (62^0.79210) * (exp(-0.003188 * 62))
lagcd = 30.510 tC/ac
The total live aboveground carbon in the stand is then:
lagc = 30.510 * 58.69 = 1,790.605 tC
Table 12 in the CFIT User Documentation Tables provides the lookup values for model parameters for live below carbon. Model parameters are grouped by region, forest type code, and stand origin code. The CIFT matches the user-provided region with those listed in the REG_11 column, the forest type code in the FORTYPGRPCD column and the stand origin in the STAND_ORIGIN column to retrieve the lookup table values for the three parameters needed: y0 (from the Estimate.y0 column), b (from the Estimate.b column), and k (from the Estimate.k column). Live belowground carbon density (lbgcd) can then be computed using the following from the equation (i.e., Hugershoff model)
lbgcd = y0 * ab * exp(-k * a)
where lbgcd is the live belowground carbon density in tons per acre,
y0 is the parameter retrieved from the lookup table,
a is the stand age from the stand description file,
b is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
k is the parameter retrieved from the lookup table.
Finally, to get total live belowground tree carbon in the stand, multiply the per-acre value by the stand area from the stand description file.
lbgc = lbgcd * Stand_area
Example: a record in the stand description file indicates that stand number 28 is in the SC region, forest type 600, Natural stand origin, age 62 years old, and contains 58.69 acres.
In the lookup table, we find the corresponding record contains the following parameters:
y0 = 4.82948
b = 0
k = 0
The live belowground carbon density (carbon per acre) is then:
lbgcd = (4.82948) * (62^0) * (exp(-0 * 62))
lbgcd = 4.8295 tC/ac
The total live belowground carbon in the stand is then:
lbgc = 4.8295 * 58.69 = 283.442 tC
Table 13 in the CFIT User Documentation Tables provides the lookup values for model parameters for deadwood carbon density. Model parameters are grouped by region, forest type code, and stand origin code. The CIFT matches the user-provided region with those listed in the REG_11 column, the forest type code in the FORTYPGRPCD column and the stand origin in the STAND_ORIGIN column to retrieve the lookup table values for the three parameters needed: y0 (from the Estimate.y0 column), b (from the Estimate.b column), and k (from the Estimate.k column). Dead wood carbon density (dwcd) can then be computed using the following from the equation (i.e., Hugershoff model)
dwcd = y0 * ab * exp(-k * a)
where dwcd is the dead wood carbon density in tons per acre,
y0 is the parameter retrieved from the lookup table,
a is the stand age from the stand description file,
b is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
k is the parameter retrieved from the lookup table.
Finally, to get total dead wood carbon in the stand, the per-acre value is multipled by the stand area from the stand description file.
dwc = dwcd * Stand_area
Example: a record in the stand description file indicates that stand number 28 is in the SC region, forest type 600, Natural stand origin, age 62 years old, and contains 58.69 acres.
In the lookup table, we find the corresponding record contains the following parameters:
y0 = 0.52973
b = 0.52053
k = -0.002966
The dead wood carbon density (carbon per acre) is then:
dwcd = (0.52973) * (62^0.52053) * (exp(0.002966 * 62))
dwcd = 5.457 tC/ac
The total dead wood carbon in the stand is then:
dwc = 5.457 * 58.69 = 320.243 tC
Table 14 in the CFIT User Documentation Tables provides the lookup values for model parameters for litter carbon. Model parameters are grouped by region, forest type code, and stand origin code. The CIFT matches the user-provided region with those listed in the REG_11 column, the forest type code in the FORTYPGRPCD column and the stand origin in the STAND_ORIGIN column to retrieve the lookup table values for the three parameters needed: y0 (from the Estimate.y0 column), b (from the Estimate.b column), and k (from the Estimate.k column). Litter carbon density (litcd) can then be computed using the following from the equation (i.e., Hugershoff model)
litcd = y0 * ab * exp(-k * a)
where litcd is the litter carbon density in tons per acre,
y0 is the parameter retrieved from the lookup table,
a is the stand age from the stand description file,
b is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
k is the parameter retrieved from the lookup table.
Finally, to get total litter carbon in the stand, the per-acre value is multipled by the stand area from the stand description file.
litc = litcd * Stand_area
Example: a record in the stand description file indicates that stand number 28 is in the SC region, forest type 600, Natural stand origin, age 62 years old, and contains 58.69 acres.
In the lookup table, we find the corresponding record contains the following parameters:
y0 = 1.39763
b = 0.10016
k = -0.001079
The litter carbon density (carbon per acre) is then:
litcd = (1.39763) * (62^0.10016) * (exp(0.001079 * 62))
litcd = 2.259 tC/ac
The total litter carbon in the stand is then:
litc = 2.259 *58.69 = 132.599 tC
Table 15 in the CFIT User Documentation Tables provides the lookup values for soil organic carbon. Because soil organic carbon density is not dependent on stand age or stand origin, this lookup table leads directly to the SOC density (tC/ac) without the need for modeling using the modeling parameters applied for the other forest carbon pools.
The CIFT matches the user-provided region with those listed in the REG_11 column and the forest type code in the FORTYPGRPCD column to retrieve the soil organic carbon density (socd) estimate directly from the table (SOC columns).
Finally, to get total soil carbon in the stand, the per-acre value is multiplied by the stand area from the stand description file.
soc =socd * Stand_area
Example: a record in the stand description file indicates that stand number 28 is in the SC region, forest type 600, Natural stand origin, age 62 years old, and contains 58.69 acres.
In the lookup table, we find the corresponding record contains the following estimate:
SOC = 42.28193
The soil organic carbon density (carbon per acre) is then:
socd = 42.28193 tC/ac
The total soil organic carbon in the stand is then:
soc = 42.28193 * 58.69 = 2,481.526 tC
In some cases, there are no records in the lookup tables for certain combinations of region, forest type group, and stand origin. This happens most commonly when a given type of forest is rare in a geographic region, or when a type of forest rarely is planted and only occurs as natural stands. In these cases, there were insufficient data in FIA to derive an estimate.
In these cases, when an attempt to find a matching record in a lookup or coefficient table fails:
Furthermore, while users may enter stand ages greater than 100 years, the FACT platform applies a maximum modeled age of 100 years for carbon estimation purposes. As a result, stands older than 100 years are assigned the same estimated carbon density as a 100-year-old stand.
In all cases when such exceptions occur, warnings are reported to the user that reference the record number, stand description file, and where insufficient data were detected to render results based on user inputs and what, if any, deviations were made in the modeling process.
(Exact warning messages will be updated once interface design is complete)
In the stand detail file, there is a record for each combination of stand key, tree species group, tree product class, and tree diameter class. This is necessary because it is possible to have different measurement units (cubic feet, board feet, green tons, etc.) for different products (pulpwood, sawtimber, etc.), and each needs to be converted to common units (initially, green tons).
Commercial forest inventories generally report “merchantable volume”, which is the volume in the portion of the tree for which local markets exist. This usually consists of the main stem, from ground line or a specified stump height to a limiting diameter of the stem near the top of the tree (for example, a 3” top stem diameter). Merchantable volumes exclude wood in tree tops (the portion of the tree above the threshold stem diameter), branches, and trees in the forest below a threshold diameter at breast height (DBH; usually 5”). However, reporting of carbon in live trees should include those non-merchantable portions of trees and trees too small to be merchantable. The CFIT therefore applies a factor based on FIA data to make an appropriate adjustment (depending on the region, tree species, etc.).
All trees also store carbon in their root systems, so belowground live tree carbon is estimated based on published ratios that estimate belowground live tree carbon from the amount of carbon in the tree aboveground. Computing belowground live tree carbon is done for each record after aboveground live tree carbon is computed.
Finally, the tree inventory data provided by users will not include two components that are part of the aboveground and belowground live carbon pools: saplings (trees between 1” diameter and 5” diameter), and understory (vegetation less than 1” diameter). These will be estimated similarly to the forest carbon pools from stand description data (region, forest type, and age).
The general flow of the processing steps for data provided via the stand detail template is depicted in Figure 8. The broad processing steps (referenced in Table 5) are:
All carbon stock estimates will be in tons C (and tons C/acre) and converted to metric tonnes (MT) CO2e at a later step.
Table 16 in the CFIT User Documentation Tables provides the lookup table values to convert MBF International ¼” to green tons . A factor (mbfint_fact) is calculated that converts thousand board feet (MBF International ¼” log rule) to green tons based on the user-provided region, species group code, and stand origin code. The CFIT locates the corresponding record in the model parameter lookup table (matching the region in the REG_11 column, the species group code in the SPGRPCD column and the stand origin in the STAND_ORIGIN column) to retrieve the three parameters needed: y0 (from the Estimate.y0 column), b (from the Estimate.b column), and k (from the Estimate.k column). The conversion factor (mbfint_fact) is computed using the following equation:
mbfint_fact = y0 * db * exp(-k * d)
where mbfint_fact is the board feet International to green tons conversion factor,
y0 is the parameter retrieved from the lookup table,
d is the diameter class value from the stand detail file (column 8),
b is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
k is the parameter retrieved from the lookup table.
Then, to get green tons for the stand/species/product class/diameter combination, the conversion factor is multiplied by the volume_ac (column 9) in the stand detail file.
grnwt_ac = volume_ac * mbfint_fact
Example: a record in the stand detail file indicates that stand number 13 is in the RMN region, and is a natural stand. For this stand, there is a record for species group 24 (other western softwoods), product class 101 (softwood sawtimber), and average tree diameter of 12.626”, containing 2.957 MBF International ¼” per acre. In the LU6_mbfint lookup table, we find the corresponding record contains the following parameters:
y0 = 0.90129
b = 0.80424
k = 0.04385
The conversion factor is then:
mbfint_fact = (0.90129) * (12.626^0.80424) * (exp(-0.04385* 12.626))
mbfint_fact = 3.982 green tons/MBF Int
The green tons per acre in this stand/species/product/diameter class is then:
grnwt_ac = 2.957 * 3.982 = 11.775 green tons/ac
Table 17 in the CFIT User Documentation Tables provides the lookup table values that convert cubic feet inside bark to green tons. A factor (cf_fact) is calculated that converts cubic feet to green tons using the user-provided region, species group code, and stand origin code. The CFIT locates the corresponding record in the model parameter lookup table (matching the region in the REG_11 column, the species group code in the SPGRPCD column and the stand origin in the STAND_ORIGIN column) to retrieve the three parameters needed: y0 (from the Estimate.y0 column), b (from the Estimate.b column), and k (from the Estimate.k column). Then the conversion factor (cf_fact) is computed from the equation:
cf_fact = y0 * db * exp(-k * d)
where cf_fact is the cubic feet to green tons conversion factor,
y0 is the parameter retrieved from the lookup table,
d is the diameter class value from the stand detail file (column 8),
b is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
k is the parameter retrieved from the lookup table.
Then, to get green tons for the stand/species/product class/diameter combination, the conversion factor is multiplied by the volume_ac (column 9) in the stand detail file.
grnwt_ac = volume_ac * cf_fact
Example: a record in the stand detail file indicates that stand number 25 is in the RMN region, and it is a natural stand. For this stand, there is a record for species group 12 (true fir), product class 102 (softwood pulpwood), and average tree diameter of 5.89”, containing 161.426 cubic feet per acre. In the LU7_cuft lookup table, we find the corresponding record contains the following parameters:
y0 = 0.02329
b = -0.16819
k = -0.02779
The conversion factor is then:
cf_fact = (0.023298) * (5.89^-0.16819) * (exp(0.02779* 5.89))
cf_fact = 0.02036 green tons/cubic foot
The green tons per acre in this stand/species/product/diameter class is then:
grnwt_ac = 161.426 * 0.02036 = 3.286 green tons/ac
Table 18 in the CFIT User Documentation Tables provides the lookup table values that convert cords to green tons. The CFIT retrieves a factor (cord_fact) that converts cords to green tons using the user-provided region and species group code. The CFIT locates the corresponding record in the lookup table (matching the region in the REG_11 column, the species group code in the SPGRPCD column) to retrieve the factor (cord_fact) from the FACTOR column.
Then, to get green tons for the stand/species/product class/diameter combination, the conversion factor is multiplied by the volume_ac (column 9) in the stand detail file.
grnwt_ac = volume_ac * cord_fact
Example: a record in the stand detail file indicates that stand number 47 is in the RMN region. For this stand, there is a record for species group 24 (other western softwoods), product class 102 (softwood pulpwood), and average tree diameter of 7.1255”, containing 0.95346 cords per acre. In the LU8_cords lookup table, we find the corresponding record contains the following factor:
cord_fact = 2.25 green tons/cord
The green tons per acre in this stand/species/product/diameter class is then:
grnwt_ac = 0.95346 * 2.25 = 2.145 green tons/ac
Table 19 in the CFIT User Documentation Tables provides the lookup table values that convert MBF Doyle to MBF International ¼”. First, the broad species group (Broad_Group column) is retrieved from the Species_group tab in the Valid_Codes file by matching the species group code provided by the user with the Code column. Using the diameter or diameter class provided by the user, and the broad species group, the CFIT finds the corresponding record in the lookup table (matching the diameter class in the ClassMidpt column or between the Class_min and Class_max in Table 19). The factor (doyle_fact) is then retrieved from the FACTOR column.
Then, to get MBF International for the stand/species/product class/diameter combination, the conversion factor is multiplied by the volume_ac (column 9) in the stand detail file.
mbfint_ac = volume_ac * doyle_fact
Next, the procedure documented in Section 6.2.1.1 is applied to convert the MBF International (mbfint_ac) value to green tons.
Example: a record in the stand detail file indicates that stand number 25 is in the RMN region. For this stand, there is a record for species group 18 (Engelmann and other spruces; Softwood broad group), product class 101 (softwood sawtimber), and average tree diameter of 14.93”, containing 5.911 MBF Doyle per acre. In the lookup table, we find the corresponding record contains the following factor:
doyle_fact = 1.6689 MBF International/MBF Doyle
(14” class midpoint, softwood Broad_Group)
The MBF International per acre in this stand/species/product/diameter class is then:
mbfint_ac = 5.911 * 1.6689 = 9.865 MBF International/ac
Using the procedure in 6.2.1.1, we compute the MBF International to green tons conversion factor as:
mbfint_fact = 3.4116 green tons/MBF International per ac
And the green tons is then:
grnwt_ac = 3.4116 * 9.865 = 33.655 green tons per acre
Table 20 in the CFIT User Documentation Tables provides the lookup table to convert MBF Scribner to MBF International ¼”. First, the broad species group (Broad_Group column) is retrieved from the Species_group tab in the Valid_Codes file (matching the species group code provided by the user with the Code column). Using the diameter or diameter class provided by the user, and the broad species group, the corresponding record is selected in the lookup table (matching the diameter class in the ClassMidpt column or between the Class_min and Class_max in Table 20). The factor (scrib_fact) is then retrieved from the FACTOR column.
Then, to get MBF International for the stand/species/product class/diameter combination, the conversion factor is multiplied by the volume_ac (column 9) in the stand detail file.
mbfint_ac = volume_ac * scrib_fact
Next, the procedure documented in Section 6.2.1.1 is applied to convert the MBF International (mbfint_ac) value to green tons.
Example: a record in the stand detail file indicates that stand number 25 is in the RMN region. For this stand, there is a record for species group 18 (Engelmann and other spruces; Softwood broad group), product class 101 (softwood sawtimber), and average tree diameter of 14.93”, containing 5.911 MBF Scribner per acre. In the lookup table, we find the corresponding record contains the following factor:
scrib_fact = 1.1659 MBF International/MBF Scribner
(14” class midpoint, softwood Broad_Group)
The MBF International per acre in this stand/species/product/diameter class is then:
mbfint_ac = 5.911 * 1.1659 = 6.892 MBF International/ac
Using the procedure in 3.1.1, we compute the MBF International to green tons conversion factor as:
mbfint_fact = 3.4116 green tons/MBF International per ac
And the green tons is then:
grnwt_ac = 3.4116 * 6.892 = 23.513 green tons per acre
Table 21 in the CFIT User Documentation Tables provides the lookup table values to convert cubic feet outside bark to cubic feet inside bark. A factor (bark_fact) is calculated that converts cubic feet inside bark to cubic feet outside bark using the user-provided region, species group code, and stand origin code. The CFIT locates the corresponding record in the model parameter lookup table (matching the region in the REG_11 column, the species group code in the SPGRPCD column and the stand origin in the STAND_ORIGIN column) to retrieve the three parameters needed: y0 (from the Estimate.y0 column), b (from the Estimate.b column), and k (from the Estimate.k column). The conversion factor (bark_fact) is then computed from the following equation:
bark_fact = y0 * db * exp(-k * d)
where bark_fact is the cubic feet outside bark to inside bark conversion factor,
y0 is the parameter retrieved from the lookup table,
d is the diameter class value from the stand detail file (column 8),
b is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
k is the parameter retrieved from the lookup table.
Then, to get cubic feet inside bark for the stand/species/product class/diameter combination, the conversion factor is multiplied by the volume_ac (column 9) in the stand detail file.
cuftib_ac = volume_ac * bark_fact
Next, the procedure documented in section in 6.2.1.2 is applied to convert the cubic feet inside bark (cuftib_ac) value to green tons.
grnwt_ac = cuftib_ac * cf_fact
Example: a record in the stand detail file indicates that stand number 6 is in the SE region, and it is a planted stand. For this stand, there is a record for species group 2 (loblolly and shortleaf pines), product class 102 (softwood pulpwood), and average tree diameter of 6.17”, containing 158.312 cubic feet (outside bark) per acre. In the lookup table, we find the corresponding record contains the following parameters:
y0 = 0.56330
b = 0.207102
k = 0.0102802
The conversion factor is then:
bark_fact = (0.56330) * (6.17^0.207103) * (exp(-0.0102802*6.17))
bark_fact = 0.77066 cf_ib/cf_ob
The cubic feet inside bark per acre in this stand/species/product/diameter class is then:
cuft_ib_ac = 158.312 * 0.77066 = 122.005 cuft_ib/ac
Using the procedure in 3.1.2, we compute the cubic feet inside bark to green tons conversion factor as:
cf_fact = 0.03141 green tons/cubic feet inside bark per ac
And the green tons per acre is then:
grnwt_ac = 122.005 * 0.03141 = 3.8322 green tons per acre
Table 22 in the CFIT User Documentation Tables contains the lookup table values toconvert merchantable green weight to merchantable dry weight. The CFIT retrieves a factor (grn2dry_fact) that converts the green weight to dry weight using FIA averages for the user-selected region and species group. The CFIT finds the corresponding record in the lookup table for the region and species group code to retrieve the FACTOR (grn2dry_fact) from the table.
Then, to get dry tons for the stand/species/product class/diameter combination, the conversion factor is multiplied by the green weight (which was either provided by the user or computed in the steps above).
merch_drywt = merch_grnwt * grn2dry_fact
Example: a record in the stand detail file indicates that stand number 37 is in the SC region. For this stand, there is a record for species group 2 (Loblolly and shortleaf pines; Softwood broad group), product class 102 (softwood pulpwood), and average tree diameter of 9.77”, containing 4.089 green tons per acre. In the lookup table, we find the corresponding record contains the following factor:
grn2dry_fact = 0.55101 dry tons/green ton
The merchantable dry tons per acre in this stand/species/product/diameter class is then:
merch_drywt = 4.089 * 0.55101 = 2.253 merchantable dry tons/ac
Table 23 in the CFIT User Documentation Tables is referenced to adjust dry weight to a user-specified top diameter to dry weight to the FIA-standard 4” top diameter.
FIA data uses a 4” top diameter for computing merchantable volumes and weights. However, many companies use variable top diameters for different products, and the smallest top diameter (usually for pulpwood) may be 2” or 3”. In the step following this one, merchantable dry weight of trees is converted to total aboveground biomass (dry weight) of trees, which should include the top portion of the stem above the 4” top, as well as branches. Without adjusting for user-specified top diameters, there is a potential to overestimate the tree carbon. For example, the volume to a 2” top will be higher than the volume to a 4” top. If an adjustment factor based on the 4” top to volumes to a 2” top is applied, the biomass and carbon in the tree would be overestimated. Therefore, we apply a factor to convert the biomass up to a user-specified top diameter to the corresponding biomass to a 4” top diameter.
Table 23 in the CFIT User Documentation Tables contains the lookup table values to convert the merchantable dry weight to a user-specified top diameter (merch_drywt) to merchantable dry weight to a 4” top (drywt_4inch). The CFIT retrieves the model coefficients based on the user-provided region and species group code. The CFIT locates the corresponding record in the model parameter lookup table (matching the region in the REG_11 column and the species group code in the SPGRPCD) to retrieve the two parameters needed: α (from the Estimate.a column) and β (from the Estimate.b column). The conversion factor (top_adj) is computed using the following equation:
[Formula]
where:
top_adj is the factor used to compute the corresponding dry weight to a 4” top,
D is the minimum of 42” or the diameter class value from the stand detail file (column 8),
Dt is the top diameter (merchantability specification) retrieved from the stand detail file (column 11),
α is a parameter retrieved from the lookup table (Estimate.a),
β is a parameter retrieved from the lookup table (Estimate.b).
Using the merch_drywt computed in step 6.2.2, multiply by the top_adj factor to obtain merchantable dry weight to a 4” top diameter:
drywt_4inch = merch_drywt * top_adj
Example: a record in the stand detail file indicates that stand number 37 is in the SC region, and it is a planted stand. For this stand, there is a record for species group 2 (loblolly and shortleaf pines), product class 102 (softwood pulpwood), and average tree diameter of 0.77” containing 2.253 merchantable dry weight (to a 2” top) per acre. In the LU13_topadj lookup table, we find the corresponding record contains the following parameters:
α = 2.996
β = 0.735
The conversion factor is then:
Top_adj = 1-49.772.9961-29.772.9960.735
Top_adj = 0.95496
The merchantable dry weight to a 4” top for this stand/species/diameter combination is then:
drywt_4inch = 2.253 * 0.95496 = 2.1515 tons/ac
Table 24 in the CFIT User Documentation Tables contains the lookup table values to convert the merchantable dry weight to a 4” top (drywt_4inch) to total tree aboveground biomass. The CFIT retrieves the model coefficients based on the user-provided region, species group code, and stand origin code. The CFIT locates the corresponding record in the model parameter lookup table (matching the region in the REG_11 column, the species group code in the SPGRPCD column and the stand origin in the STAND_ORIGIN column) to retrieve the three parameters needed: y0 (from the Estimate.y0 column), k (from the Estimate.k column), and c (from the Estimate.c column). The conversion factor (merch2agb_fact) is computed using the following equation (note this equation is different from previous ones):
merch2agb_fact = y0 * exp(-k * d) + c
where merch2stem_fact is the merchantable to total stem biomass factor,
y0 is the parameter retrieved from the lookup table,
d is the diameter class value from the stand detail file (column 8),
k is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
c is the parameter retrieved from the lookup table.
Then, to get total tree aboveground biomass (treeagb_ac) for the stand/species/product class/diameter combination, the conversion factor is multiplied by the dry weight to a 4” top computed in step 6.2.3:
treeagb_ac = drywt_4inch * merch2agb_fact
Example: a record in the stand detail file indicates that stand number 42 is in the PNWW region, and it is a planted stand. For this stand, there is a record for species group 10 (Douglas-fir), product class 101 (softwood sawtimber), and average tree diameter of 12.25”, containing 56.3 green tons per acre. In step 3.2 we computed the corresponding merchantable dry weight was 39.328 tons per acre (to a 4” top diameter). In the lookup table, we find the corresponding record contains the following parameters:
y0 = 5.09132
k = 0.35144
c = 1.15752
The conversion factor is then:
merch2agb_fact = (5.09132) * (exp(-0.35144*12.25)) + 1.15752
merch2agb_fact = 1.22625 tons total aboveground biomass/merchantable ton
The total aboveground biomass per acre in this stand/species/product/diameter class is then:
treeagb_ac = 39.328 * 1.22625 = 48.226 tons/ac
Table 25 in the CFIT User Documentation Tables provides the lookup table values to convert total tree aboveground biomass to total aboveground live tree carbon,. The CFIT retrieves a factor (agb2agc_fact) based on the user-provided region and species group that converts the tree biomass to carbon reflecting FIA averages.
Then, to get aboveground tree carbon for the stand/species/product class/diameter combination, the conversion factor is multiplied by the total stem biomass per acre (totstem_ac, which was computed in step 6.2.4).
treeagc_ac= treeagb_ac * agb2agc_fact
Example: a record in the stand detail file indicates that stand number 37 is in the SC region. For this stand, there is a record for species group 2 (Loblolly and shortleaf pines; Softwood broad group), product class 102 (softwood pulpwood), and average tree diameter of 9.77”, containing 4.089 green tons per acre. We computed the merch_drywt to be 2.253 tons/ac (in step 3.2), then following steps 3.3 and 3.4 found the total stem biomass to be 2.464 tons/ac.
In the lookup table, we find the corresponding record contains the following factor:
agb2agc_fact = 0.477 tons C/ton biomass
The tree aboveground carbon per acre in this stand/species/product/diameter class is then:
treeagc_ac = 2.464 * 0.477 =1.175 tons C/ac
Users may wish to know what portion of aboveground carbon is stored in the merchantable portions of their stands. Based on the aboveground live tree carbon already computed, the conversion factor used previously in Step 6.2.4 (merch2agb_fact) can be applied to compute the desired proportion.
merchc_ac = treeagc_ac / merch2agb_fact
Example: in Step 6.2.4, we used stand number 42 in the PNWW region, species group 10 (Douglas-fir), product class 101 (softwood sawtimber), and average tree diameter of 12.25”, containing 39.328 dry tons per acre to a 4” top diameter, and a total tree aboveground biomass of 48.226 tons/ac. When converted to carbon (agb2agc_fact = 0.516), this becomes 24.885 tC/acre.
For this stand, we found the merch2agb_fact:
merch2agb_fact = 1.22625 tons total stem/merchantable ton
So dividing by this factor results in the carbon in the merchantable portion of the trees:
merchc_ac = 24.885 / 1.22625 = 20.293 tons C/acre in merchantable portion
Belowground tree carbon is estimated following the FIA approach that applies equations published in Jenkins, et al. (2003). This approach uses parameters based on broad species group (softwood hardwood) and tree diameters to compute the ratio of belowground carbon to aboveground carbon. The equation to obtain the ratio is:
ratio = exp[B0 + B1/(d*2.54)]
where ratio is the belowground C divided by the aboveground C,
B0 and B1 are parameters from Table 5 below,
d is the diameter class value (in inches) from the stand detail file (column 8),
2.54 cm/inch is the factor to convert diameters in inches to diameters in cm,
exp is the exponentiation function (e to the power).
[Table]
To get the belowground tree carbon per acre, the following formula is applied:
treebgc_ac = treeagc_ac * ratio
Example: a record in the stand detail file indicates that stand number 37 is in the SC region. For this stand, there is a record for species group 2 (Loblolly and shortleaf pines; Softwood broad group), product class 102 (softwood pulpwood), and average tree diameter of 9.77”, containing 4.089 green tons per acre. We computed the treeagc_ac to be 1.175 tons/ac (in step 3.5).
We compute the ratio as:
ratio = exp[-1.5619 * 0.6614/(9.77*2.54)] = 0.2154
The belowground carbon per acre in this stand/species/product/diameter class is then:
treebgc_ac = 1.175 *0.2154 =0.253 tons C/ac
Based on the user-supplied data from the stand detail file, the following estimates have been computed in Steps 6.2.1-6.2.7:
grnwt_ac: the merchantable green weight (short tons) of trees per acre,
merch_drywt: the merchantable dry weight (short tons) of trees per acre,
drywt_4inch: the merchantable dry weight to a 4” top (short tons/ac),
totstem_ac: the total stem dry weight (short tons/ac),
merchc_ac: the carbon in the merchantable portion of trees,
treeagc_ac: the carbon in aboveground live trees per acre (short tons/ac),
treebgc_ac: the carbon in belowground live trees per acre (short tons/ac).
Stand-level totals can now be calculated across all species, products, and diameters (treeagc_ac and treebgc_ac) which are described as:
Sum (merchc_ac
treeagc_ac
treebgc_ac by stand key
)
The stand totals (merchc_ac, treeagc_ac, and treebgc_ac) are then multiplied by the stand acres to get totals for all stands:
Merchc = merchc_ac * Stand_area
treeagc = treeagc_ac * Stand_area
treebgc = treebgc_ac * Stand_area
In some cases, there are no records in the lookup tables for certain combinations of region, species group, and stand origin. This happens most commonly when a given type of forest is rare in a geographic region, or when a type of forest rarely is planted and only occurs as natural stands. Processing exceptions are also applied where users enter a zero for diameter, diameter estimates exceed 42 inches DBH, or estimates of the age of the stand exceed 100 years. In these cases, default values are applied as follows:
In all cases when such exceptions occur, warnings are reported to the user that reference the record number, stand description file, and where insufficient data were detected to render results based on user inputs and what, if any, deviations were made in the modeling process.
(Exact warning messages will be updated once interface design is complete)
Tables 26 (for aboveground sapling carbon density) and 27 (for belowground sapling carbon density) in the CFIT User Documentation Tables provide the lookup tables for sapling carbon. The CFIT matches the user-provided region, forest type code, and stand origin code to locate the corresponding record in the model parameter lookup table (matching the region in the REG_11 column, the forest type code in the FORTYPGRPCD column and the stand origin in the STAND_ORIGIN column) and retrieve the three parameters needed: y0 (from the Estimate.y0 column), b (from the Estimate.b column), and k (from the Estimate.k column). Sapling carbon density (sap_ag_cd and sap_bg_cd, for aboveground and belowground) is then computed using the following equation:
sap_xx_cd = y0 * ab * exp(-k * a)
where sap_xx_cd is the sapling carbon density in tons per acre for xx= ag or bg,
y0 is the parameter retrieved from the lookup table,
a is the stand age from the stand description file,
b is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
k is the parameter retrieved from the lookup table, with parameters retrieved from Table 26 for aboveground and Table 27 for belowground.
Finally, to get total aboveground and belowground sapling carbon in the stand, the per-acre value is multiplied by the stand area from the stand description file.
sap_ag = sap_ag_cd * Stand_area
Sap_bg = sap_bg_cd * Stand_area
Example: a record in the stand description file indicates that stand number 28 is in the SC region, forest type 600, Natural stand origin, age 62 years old, and contains 58.69 acres.
In the aboveground lookup table, we find the corresponding record contains the following parameters:
y0 = 1.01458
b = 0.72218
k = 0.03501
The sapling aboveground carbon density (carbon tons per acre) is then:
Sap_ag_cd =(1.01458) * (62^0.72218) * (exp(-0.03501 * 62))
Sap_ag_cd = 2.28 tC/ac
The total sapling aboveground carbon in the stand is then:
Sap_ag =2.28 * 58.69 = 133.82 tC
Similarly, the parameters retrieved from the belowground lookup table are:
y0 = 0.18773
b = 0.66060
k = 0.03110
The sapling belowground carbon density (carbon tons per acre) is then:
sap_bg_cd = (0.18773) * (62^0.66060) * (exp(-0.03110 * 62))
sap_bg_cd = 0.42 tC/ac
The total sapling belowground carbon in the stand is then:
sap_bg =0.42 * 58.69 = 24.47 tC
Table 28 (for aboveground understory carbon density) and 29 (for belowground understory carbon density) in the CFIT User Documentation Tables provide the lookup tables for understory carbon. The CFIT matches the user-provided region, forest type code, and stand origin code to locate the corresponding record in the model parameter lookup table (matching the region in the REG_11 column, the forest type code in the FORTYPGRPCD column and the stand origin in the STAND_ORIGIN column) to retrieve the three parameters needed: y0 (from the Estimate.y0 column), b (from the Estimate.b column), and k (from the Estimate.k column). Understory carbon density (und_ag_cd and und_bg_cd, for aboveground and belowground) is then estimated using the following equation:
Und_xx_cd = y0 * ab * exp(-k * a)
where und_xx_cd is the understory carbon density in tons per acre for xx= ag or bg,
y0 is the parameter retrieved from the lookup table,
a is the stand age from the stand description file,
b is the parameter retrieved from the lookup table,
exp is the exponentiation function (e to the power),
k is the parameter retrieved from the lookup table, with parameters retrieved from Table 28 for aboveground and Table 29 for belowground.
Finally, to get total aboveground and belowground understory carbon in the stand, the per-acre value is multipled by the stand area from the stand description file.
und_ag = und_ag_cd * Stand_area
und_bg = und_bg_cd * Stand_area
Example: a record in the stand description file indicates that stand number 28 is in the SC region, forest type 600, Natural stand origin, age 62 years old, and contains 58.69 acres.
In the aboveground lookup table, we find the corresponding record contains the following parameters:
y0 = 0.8648
b = -0.13245
k = -0.0037
The understory aboveground carbon density (carbon tons per acre) is then:
Und_ag_cd = (0.8648) * (62^-0.13245) * (exp(0.0037 * 62))
Und_ag_cd =0.63 tC/ac
The total understory aboveground carbon in the stand is then:
Und_ag = 0.63 * 58.69 = 36.96 tC
Similarly, the parameters retrieved from the belowground lookup table are:
y0 = 0.09609
b = -0.13245
k = -0.0037
The understory belowground carbon density (carbon tons per acre) is then:
und_bg_cd = (0.09609) * (62^-0.13245) * (exp(0.0037 * 62))
und_bg_cd = 0.07 tC/ac
The total sapling belowground carbon in the stand is then:
und_bg = 0.07 * 58.69 = 4.11 tC
Live aboveground and belowground carbon is comprised of three components each: tree carbon based on inventory measurements, sapling carbon based on FIA modeled data, and understory carbon based on FIA modeled data. These three components are summed to get total live aboveground and belowground carbon:
lagc_detail = treeagc + sapagc + undagc
lbgc_detail = treebgc + sapbgc + undbgc
In the list below, the “detail” in the variable name indicates this estimate comes from stand detail (rather than stand description) data. While lagc and lbgc were computed based on the stand description data (in steps 6.1.2 and 6.1.3), the more reliable estimates from the stand detail data will be utilized for any stand for which stand detail data were provided.
The primary estimates for each stand will be:
lagc_detail (or lagc from step 6.1.2 for stands without detail data),
lbgc_detail (or lbgc from step 6.1.3 for stands without detail data),
merchc (for stands with detail data),
nonmerchc (for stands with detail data; nonmerchc = lagc_detail – merchc),
dwc: dead wood carbon (from step 6.1.4),
litc: litter carbon (from step 6.1.5),
soc: soil organic carbon (tfrom step 6.1.6).
These estimates rendered in short tons C. Therefore, as a final step, they need to be converted to metric tonnes (MT) CO2e based on the following two steps
1) Multiply the carbon in short tons by 0.9071847 metric tonnes per short ton
2)Multiply the result by 3.666667 tonnes CO2e per tonne C to obtain MT CO2e.
The CFIT can compute carbon stock change estimates if a user uploads complete inventory datasets for two points in time at least a year apart.
Using those files, the CFIT completes an error-check for each inventory dataset separately
The error checking evaluates consistency between datasets in describing the administrative aggregates and their reported area (acres) at both inventory dates. The CFIT does this by summarizing and comparing the total stand areas for all administrative units for the two inventories. Where there are discrepancies detected in area estimates for administrative aggregates, the CFIT produces a warning message that describes the nature of the error that prevents stock change computation.
[Table]
Then stock change computation can proceed for those administrative units whose area did not change between inventories.
The stock change computation is performed using all carbon pools except for soil organic carbon. Soil carbon stocks are assumed to be static across inventory years due to the higher level of uncertainty and protracted timelines associated with soil carbon changes. Therefore the equations for estimating carbon stock change is as follows:
Stock1 = lagc1 + lbgc1 + dwc1 + lit1
Stock2 = lagc2 + lbgc2 + dwc2 + lit2
Tot_chng = Stock2 – Stock1
Ann_chng = Tot_chng / years_between
Where c_pooln is the carbon in a pool at inventory date n, summed to the designated administrative unit,
Stockn is the total forest carbon stock (excluding soil carbon) at inventory date n for the designated administrative unit,
Tot_chng is the overall stock change between inventories,
years_between is the time (in decimal years) between the two inventories, and
Ann_chng is the average annual forest carbon stock change (in MT CO2e/year) for the administrative unit between the inventories.
Example:
The entries in red in the table below show where the administrative unit area changed between inventories, preventing calculation of stock change for those areas.
For the other units, the stocks at time 1 and time 2 are shown. If the Inventory time 1 was July 1, 2023 and the inventory time 2 was December 31, 2024, then the years_between would be 1.5.
Total changes are:
South District B: 3,967,248 – 3,819,361 = 147,888 MT CO2e
South District C: 2,336,668 – 2,207,097 = 129,571 MT CO2e
PNW District A: 960,924 – 1,033,095 = -72,171 MT CO2e
Annual changes are:
South District B: 147,888 MT CO2e / 1.5 yrs = 98,592 MT CO2e/yr
South District C: 129,571 MT CO2e / 1.5 yrs = 86,380 MT CO2e/yr
PNW District A: -72,171 MT CO2e / 1.5 yrs = -48,114 MT CO2e/yr
[Table]
This file type contains location identification information for each stand in the inventory (administrative levels and units used by the company and location identifiers). The location identifiers are intentionally general to protect confidential information and are used for lookup purposes to find data for geographically similar stands. The stand key, or unique identifier, consists of a combination of the administrative units and stand number.
There should be one record per stand in the user’s inventory.
[Table]
1 See CFIT User Documentation Table 1 for valid code listings by state.
2 See CFIT User Documentation Table 2 for valid FIA survey unit codes.
3 See CFIT User Documentation Table 3 for valid forest type group codes.
4 Valid codes are 0 for naturally regenerated stands, and 1 for artificially regenerated (e.g., planted) stands (see CFIT User Documentation Table 4).
5 Due to lack of FIA data for older stands, any stand age over 100 will be treated as a 100 year-old stand when retrieving carbon stock estimates from FIA data (i.e., carbon stocks estimated based on forest type and age will have the values for 100-year-old stands).
This file type contains volumetric inventory data summarized by tree species groups, product classes (e.g., sawtimber, veneer, pulpwood, etc.), and (optionally) tree diameter classes within a stand. Because inventories may use different units for different product classes (e.g., board feet for sawtimber and cords for pulpwood), there may need to be multiple product records per species in a stand. Furthermore, many inventories provide details by diameter classes, which provides more accurate estimates of tree volume, biomass, and carbon. Thus, there can be multiple records per stand for different combinations of species group, product, and diameter class.
[Table]
5 See CFIT User Documentation Table 5 for valid species group codes.
6 See CFIT User Documentation Table 6 for valid product class codes.
7 For compatibility with FIA, we use two-inch diameter classes with even-numbered midpoints. For example, the 8” diameter class (represented by the number 8) is for trees 7.0” to 8.9” in DBH. Floating-point numbers for average diameters are also acceptable. If no diameter class or average diameter is recorded for a combination combination of species group and product, enter a zero.
8 See CFIT User Documentation Table 7 for valid volume unit codes.
9 See CFIT User Documentation Table 8 for top diameter values.
Data retrieval using the EVALIDator tool requires specification of the attributes of interest. For example, to get soil organic carbon stock per acre on unreserved forestland, an EVALIDator query might use the following attributes in a ratio query:
Numerator: Carbon in organic soil, in short tons, on forest land (ATTR #52)
Denominator: Area of forest land, in acres (ATTR #2)
Filter string to exclude reserved forestland: “and COND.RESERVCD=0”
The stand-level estimates were derived from data retrieved from EVALIDator using the following attribute specifications. All EVALIDator outputs reflect plot measurements from land designated as “unreserved forest land” and produced data at the FIA plot level.
[Table]
Data retrieval using the EVALIDator tool requires specification of the attributes of interest. For example, to the average ratio of inside-bark volume to outside-bark volume for trees, an EVALIDator query might use the following attributes in a ratio query:
Numerator: Sound bole bark volume of live trees (timber species at least 5 inches d.b.h.), in cubic feet, on forest land (ATTR #11012)
Denominator: Sound bole wood volume of live trees (timber species at least 5 inches d.b.h.), in cubic feet, on forest land (ATTR #574174)
Filter string to exclude reserved forestland: “and COND.RESERVCD=0”
The tree-level estimates were derived from data retrieved from EVALIDator using the following attribute specifications. EVALIDator outputs reflect plot measurements from land designated as “unreserved forest land”, and produced data at the FIA plot level. The numbers in “Estimate of Interest” column refer to the step numbers in Figure 8.
[Table]
Aboveground live tree carbon pool: Carbon stored in the aboveground portion of living trees, including stems, branches, and foliage, typically expressed per unit area. Estimates are derived from tree measurements using established allometric relationships and conversion models applied within the USDA Forest Service.
Administrative unit: A user-defined analysis boundary based on political, jurisdictional, or corporate divisions (e.g., states, counties, district) used to group FIA plots.
Belowground live tree carbon pool: Carbon stored in the living root biomass of trees, including coarse and fine roots, typically expressed per unit area. Estimates are derived from tree measurements using established allometric relationships and conversion models applied within the USDA Forest Service. Landscape Tool
Biomass: The mass of organic material in trees, typically expressed as oven-dry or green weight, including stems, bark, and branches. Biomass may refer to live or dead components and can be converted to carbon using standard conversion factors.
Carbon density: Carbon stock per unit area, typically expressed as mass per area (e.g., MT C per acre), representing the concentration of carbon within a defined land base
Carbon Flux: The rate of transfer of greenhouse gases between a defined system and the atmosphere over a specified time interval, typically expressed as mass per unit time (e.g., tCO₂e·yr⁻¹). Positive values indicate emissions to the atmosphere, while negative values indicate removals (sequestration).
Note: Net flux is equal in magnitude and opposite in sign to carbon stock change within the system, although sign conventions differ between stock-based and flux-based reporting frameworks.
Carbon Stock Change: The net change in the mass of carbon within a defined carbon pool over a specified period, typically expressed as mass per unit time (e.g., Mt CO2·yr⁻¹). It reflects the balance between carbon gains (e.g., growth, inputs) and losses (e.g., harvest, decomposition, disturbance). A positive value indicates a net increase in stored carbon, while a negative value indicates a net decrease.
Dead wood carbon pool: Carbon stored in non-living woody biomass, including both standing and downed material, typically comprising standing dead trees (snags), down dead wood, and associated coarse woody debris within a defined area.
Forest type group: A classification used by FIA program that aggregates individual forest types into broader categories based on dominant tree species and ecological similarity, enabling consistent summarization and reporting of forest attributes across regions. In the conterminous United States (CONUS), FIA defines 28 forest type groups (USDA Forest Service, FIA; see Forest Type Group metadata: https://data.fs.usda.gov/geodata/rastergateway/forest_type
Litter carbon pool: Carbon stored in non-living organic material on the forest floor, including leaves, needles, twigs, bark fragments, and other fine debris that have not yet decomposed into soil organic matter, typically expressed per unit area.
Merchantability specification: A set of criteria defining which portion of a tree is considered usable or “merchantable” for wood products, based on attributes such as minimum diameter, top diameter, stem form, and usable length, used to determine merchantable volume within the USDA Forest Service.
Merchantable volume: The volume of wood within a tree that meets specified merchantability criteria, typically referring to the usable portion of the stem between a defined minimum diameter and a specified top diameter, expressed in cubic units.
Product class: A categorical classification of harvested wood based on its intended use and physical characteristics, such as sawtimber, pulpwood, or other wood products, used to differentiate how timber is processed and valued within the USDA Forest Service.
Region: A spatial unit defined by administrative or analytical boundaries that groups multiple geographic areas for the purpose of summarizing and comparing forest attributes. Within the FACT Platform regions may be defined in multiple ways to enhance analytical flexibility, but the CFIT and DFIT define regions as the standard, Resources Planning Act regions (see Figure 1).
Sapling: A live tree of small diameter, typically defined as having a diameter at breast height (dbh) between 1.0 and 4.9 inches (2.5–12.7 cm), within the USDA Forest Service classification system.
Soil carbon pool: The carbon stored in soil organic matter within a defined depth (commonly up to 1 meter), including decomposed organic material and fine roots, but excluding coarse root biomass accounted for in belowground biomass pools, typically expressed per unit area.
Species group (SPGRPCD): A classification used by the Forest Inventory and Analysis program that aggregates individual tree species into broader groups based on taxonomic and ecological similarity for consistent summarization and analysis of forest attributes.
Stand: A community of trees that can be distinguished from adjacent communities due to similarities and uniformity in tree and site characteristics, such as age-class distribution, species composition, spatial arrangement, structure, etc.
Stand age: A stand descriptor that indicates the average age of the live dominant and codominant trees in the predominant stand-size class of a condition.
Stand age/stand age class: A stand descriptor that indicates the average age of the live dominant and codominant trees in the predominant stand-size class of a condition.
Stand key: A unique identifier used to distinguish and track a specific forest stand or condition within a dataset, enabling linkage of plot-level observations and attributes across measurements.
Stand origin: A classification used by the Forest Inventory and Analysis program that indicates the regeneration origin of a forest stand, distinguishing between stands established through natural regeneration and those established through artificial means (e.g., planting or seeding).
Stratum: A relatively homogeneous subset of a population, defined by selected attributes, within which sampling and estimation are conducted to reduce variance and improve the precision of statistical estimates.
Survey unit: A sub-state geographic division used by the USDA Forest Service to organize and report forest inventory data, typically grouping counties with similar forest characteristics for sampling and estimation purposes.
Tree Diameter Class: An FIA-based classification that groups trees into discrete DBH classes (typically 1-inch increments or aggregated bins) for consistent analysis of forest structure and size distribution.
Tops: The portion of a tree above the defined merchantable limit (e.g., minimum top diameter), consisting of smaller stem sections and branches that are not considered merchantable under specified utilization standards but contribute to total tree biomass and carbon.
Understory carbon pool: Carbon stored in non-tree vegetation beneath the forest canopy, including woody shrubs and tree seedlings or saplings below 1 inch (2.5 cm) dbh, as well as herbaceous plants, typically expressed per unit area.
Unreserved forest land: Forest land not withdrawn from management by statute or administrative designation, and therefore generally available for multiple uses, including timber production. Landscape Tool, CFIT