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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 Default Forest Carbon Tool (DFCT tool) enables users with limited site-specific data and knowledge of carbon accounting to produce first-order estimates of forest carbon stocks, forest carbon flux within an inventory period, and, if desired, potential changes in forest carbon stocks (flux) from a set of basic forest management scenarios for a user-defined area within the conterminous United States (CONUS). The methods that underlie the DFCT tool are largely based on the “Level 1” quantification approaches published in the USDA Entity Guidelines Chapter 5: Methods for Managed Forest Systems (Murray et al. 2024).
DFCT accomplishes this by matching basic user-supplied stand-level data inputs 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.
The resulting estimates empower users to produce general estimates of the potential impact of interventions for grant reporting or contribute to environmental assessments where site-specific data and analyses are not available.
Ac: Acres (land area measurement)
Bf: Board feet (wood volume measurement)
CO2e: Carbon dioxide equivalent
CFIT Custom Forest Inventory Tool
DFCT Default Forest Carbon Tool
FACT Forest Analytics for Carbon Tracking
FIA: Forest Inventory and Analysis (program of USDA Forest Service, National Forest Inventory)
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)
RMN: Rocky Mountain North (US Region)
RMS: Rocky Mountain South (US Region)
SC: South Central (US Region)
SE: Southeast (US Region)
Short tons: Imperial ton (2000 pounds)
The DFCT can generate two categories of results depending on the level of analysis the user wishes to perform. All analyses begin with completion of the required carbon inventory user inputs. Users may then optionally evaluate future carbon trajectories by selecting from a set of generalized forest management scenarios.
These user inputs form the basis for both the Carbon Inventory results and Forest Management Scenario projections, though certain Forest Management Scenarios require additional user inputs (detailed below under Section 3.3). For each stand the user wishes to produce results for, users must enter information summarized in Table 1.
[Table]
[Image - Map]
[Box - Key Input Definitions]
Once Carbon Inventory results are generated, the DFCT allows users to optionally explore how a limited set of broad forest management scenarios could affect stand carbon stocks and fluxes into the future. Additional user inputs beyond those that were already supplied at the stand-level for the Carbon Inventory are detailed in Table 2 for each forest management scenario included in the DFCT.
[Table]
During data processing, the DFCT 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 forest type group is reported in a region in which FIA has few or no records of that forest type group. In these cases, a carbon stock estimate are be computed based on a default (such as averages for the forest type group in other regions).
Exact warning message language TBD.
Graphical outputs
As stated, the DFCT produces two sets of outputs whereby once Carbon Inventory Outputs are rendered, they may opt to explore a set of generalized forest management scenarios. The sections below describe outputs for both the Carbon Inventory and Forest Management Scenario Projections.
After the DFCT processes data for the Carbon Inventory, several graphical outputs are rendered. These are displayed in the user interface and include estimates of total forest carbon stocks, total carbon change, and annualized carbon change. A bar chart is also presented that breaks down the carbon stocks by carbon pool across the 5-year carbon flux calculation period. Figures 3 and 4 below provides an example of the graphical outputs as displayed in the user interface.
[Figures will be labeled and additional detail will be added when programming is complete]
[Image]
[Image]
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]
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 the FACT platform’s Custom Forest Inventory Tool (CFIT) and the DFCT. Data were retrieved from the FIA database using the FIA EVALIDator tool (USDA 2026) through its application programming interface (API). Queries were conducted using the two most recent non-overlapping FIA evaluation groups available for each state or region to maximize temporal coverage while avoiding duplicate plot measurements across evaluation periods. Analyses were limited to FIA plots classified as unreserved forest land, representing forest land generally available for management and timber production activities.
EVALIDator outputs were extracted at the plot level, including grouping-variable attributes and the associated estimate of interest (e.g., aboveground live tree carbon) for each plot. For stand-age modeling, plot-level results were matched with recorded stand ages for individual FIA plots rather than the broader stand-age classes available directly through EVALIDator. The resulting datasets were then used to develop stand-level and tree-level models.
Stand-level estimates were developed for carbon density (MTCO2e acre⁻¹) across all modeled carbon pools as a function of stand age. Models were stratified according to the grouping variables used to match user-supplied forest conditions to comparable FIA plots, including FIA region, broad forest type group, FIA forest type group, and stand origin (natural or artificial regeneration). In theory, the combination of 11 FIA regions, 32 FIA forest type groups, and two stand-origin classes yields up to 704 unique model combinations; however, model development was constrained by data availability, and some combinations were not represented in the FIA dataset. For each valid grouping combination, carbon density by stand age was modeled using the Hugershoff growth function (Prodan 1968), expressed as:
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.
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 the DFCT and CFIT to perform all of the necessary calculations to develop carbon stock estimates from user inventory data at the stand level. These tables are available in the CFIT User Documentation Tables file.
For more detailed information, see the Custom Forest Inventory Tool User Methodology.
FIA-based lookup tables and statistical models were developed to estimate forest carbon stocks and harvest-related metrics across a range of forest conditions in CONUS. Building on the framework described for developing modeling coefficients that described relationships between stand-age and carbon density to stand age for across forest carbon pools, additional analyses were conducted to support the DFCT to support modeling of harvest-oriented forest management scenarios where users do not possess stand-level forest inventory or merchantable volume data.
Domain-specific growing stock volume-carbon (GSVC) ratios were developed expressing the relationship between growing-stock volume and live aboveground carbon. Growing-stock volume was defined according to FIA standards as net merchantable bole volume of live growing-stock trees (TREECLCD = 2) at least 5 inches d.b.h. on unreserved forest land. Ratios were developed using weighted FIA estimates and stratified according to region, forest type group, stand origin, and stand-age class, subject to data availability and statistical reasonableness constraints. Where sample sizes were insufficient to support fully stratified estimates, a hierarchical aggregation approach was applied consistent with existing platform procedures to derive more generalized fallback estimates. These resulting GSVC lookup tables support estimation of merchantable growing-stock volume from modeled live aboveground carbon estimates within the DFCT, thereby improving consistency between modeled forest carbon stocks and downstream harvested wood product calculations.
The GSVC ratios are provided in the accompanying “Growing Stock Volume-to-Carbon Ratios” Excel document.
To offer estimates of potential emissions from fire scenarios (naturally occurring and prescribed), a lookup table containing emission factors by region, forest type group, and fire-severity class has been prepared and is included in Annex 2 of this document.
The emission factors applied in the DFCT are the same as those developed for quantifying immediate emissions from fire in forests under the “Level 1” approach documented within the 2024 Entity Guidelines (Murray et al. 2024). Users are directed to Section 5.2.3, Wildfire and Prescribed Fire, of that report for additional information regarding the derivation of the underlying emission factors.
The original emission factors were reported in units of megagrams per hectare (Mg ha⁻¹). For consistency with the DFCT and other estimates reported throughout this methodology, emission factors were converted to metric tons per acre (MT ac⁻¹) using the standard hectare-to-acre conversion factor (1 ha = 2.471 acres).
The DFCT produces carbon estimates in metric tons of carbon dioxide equivalent (MTCO2e) for the current inventory year as well as an estimated annual flux over the preceding 5 years. Positive flux numbers indicate a CO2 emission, whereas negative numbers represent a removal of CO2 from the atmosphere.
Based on user inputs for region (r), forest type (t), stand origin (p), and current stand age (a), MTCO2e per acre estimates are sourced by referencing the appropriate growth models (see section 4.1). This data retrieval renders estimates carbon stocks across all carbon pools.
To generate estimates of carbon stocks in the stand at both , they must be extrapolated to match the user-defined stand area by multiplying the stand-level carbon by the user-supplied area, as described in the following equation:
Equation DFCT-1: Total Inventory C stocks
[Formula]
These scenarios offer a first-order estimate of projected forest carbon stocks at 5-year timesteps, up to 50 years into the future, for the user-selected combination of U.S. region, forest type, age class, stand origin, and rotation length (where applicable).
This projection offers an estimate of the carbon stocks and fluxes (from the forest stand up to 50 years into the future, quantified and reported as total flux in living and dead carbon pools (MT CO2e) over that period. This projection essentially follows the same steps as documented in section 5.1 section of this document but repeats the calculation at 5-year timesteps across the 50-year projection.
Projection timesteps are indexed as:
i = 0,…,10
Where:
i = Indexes the current inventory year and subsequent 5-year projection timesteps across the 50-year projection period.
Stand age at each timestep is calculated as:
aᵢ = a₀ + 5i
Where:
aᵢ = Stand age at timestep i
a0 = User-defined stand age in the current inventory year
Total carbon flux across the 50-year projection is calculated as the difference between carbon stocks at the start year of the projection and those at the end of the projection, as described in the equation below:
[Formula]
The average annual C flux across the 50-year projection is calculated as described in the equation below:
[Formula]
[Table]
This projection estimates the carbon stocks and sequestration up to a user-specified planned harvest time and then re-grows the forest post-harvest. Projected forest carbon fluxes are combined with estimates carbon storage and emissions from harvest to offer total forest biogenic (AFOLU sector) carbon stock change (flux) (MTCO2e).
The current modeling framework assumes stand-replacing harvest conditions (i.e., clearcut) for purposes of post-harvest carbon accounting. This simplifying assumption was incorporated to support generalized scenario modeling while avoiding the additional complexity and uncertainty associated with modeling residual stand structure and carbon dynamics under partial harvest systems.
Under this framework, biomass estimated to become delivered forest products is routed to the harvested wood product (HWP) Tool, while remaining non-soil biomass is assigned to a post-harvest logging residue pool. This may include tops and limbs, non-merchantable material, unutilized biomass, harvest losses, and other organic material remaining onsite following harvest activity.
Carbon associated with logging residues is modeled over time using literature-informed decay assumptions, including decay rates adopted from the Forest and Agricultural Sector Optimization Model with Greenhouse Gases (FASOM-GHG; Beach et al. 2010), to represent gradual decomposition and associated emissions following harvest. For purposes of generalized scenario modeling, a common decay framework is applied across post-harvest residue pools despite likely differences in decay dynamics among biomass components.
Because post-harvest residue dynamics vary substantially based on harvest practices, utilization rates, site conditions, slash treatment, disturbance, and decomposition environment, modeled residue trajectories should be interpreted as generalized representations rather than stand-specific forecasts of post-harvest carbon behavior.
The calculation procedures for this step are the same as described in section 6.2.2 Basic Projection of this document, except the projection end time (i.e., the value for “x” in Equation DFCT-3) is modified to reflect the user-specified harvest year.
Once the harvest occurs, the carbon stocks and flux associated with post-harvest regrowth are estimated. The methodological procedures for projecting post-harvest regrowth through the rest of the total 50-year projection are the DFCT-3, except:
Biogenic carbon stock change estimates include the growth or decay of living organisms and fall within the IPCC agriculture, forestry, and other land use (AFOLU) sector. They do not include emissions from other sectors such as energy or waste (e.g., emissions from equipment usage and transportation).
In the DFCT, two options are available for estimating the carbon flux associated with harvested wood products under the Basic Projection with Harvest forest management scenario, based on whether or not a user knows the amount of wood harvested:
Where harvest volumes/mass are known: the DFCT tool will use those data to draw from methods already integrated into the Harvested Wood Product Carbon tools. Estimates of wood volumes harvested will be entered into the DFCT user interface and sent to the Harvested Wood Carbon tool, with results returned for:
Where harvest volumes/mass are not known: This option applies FIA-derived default estimates of growing-stock volume to estimate the portion of the live tree carbon pool represented by merchantable growing-stock trees and therefore potentially available for harvest.
The following steps capture how the amount of harvest is calculated (CCF) using Option 2, which are then ported into the Harvested Wood Carbon Tool for deriving a final estimate of carbon stored in harvested wood products over a 100-year post-harvest timeline in MT CO2e. Figure 4 provides a methodological decision tree that illustrates the steps that send the estimated CCF removed at harvest to the Harvested Wood Carbon Tool.
[Image]
Lookup tables for deriving the growing stock volume estimates are provided within the accompanying “Growing Stock Volume-to-Carbon Ratios” Excel document. The tab “stdageclass5yr_main” provides GSVC ratio to modeled live aboveground carbon estimates, grouped by 5-year stand-age class intervals. This ratio represents the relationship between merchantable growing-stock volume and live aboveground carbon and is expressed as cubic feet per short ton C (ft³ short ton C⁻¹). Specifically, the numerator reflects net merchantable bole wood volume of growing-stock trees (≥5 inches d.b.h. “FIA class 2” trees) on forest land, measured in cubic feet, while the denominator reflects FIA forest carbon pool 1 (live aboveground carbon) expressed in short tons C per acre.
Because the GSVC ratio is defined relative to the FIA live aboveground carbon pool, live aboveground carbon estimates are first calculated separately using the applicable model coefficients (see Custom Forest Inventory Tool documentation). The resulting live aboveground carbon estimates (Mg C acre⁻¹) are then converted to short tons C acre⁻¹ to align with the denominator units of the GSVC ratio (ft³ short ton C⁻¹). The converted carbon estimates are then multiplied by the GSVC ratio to estimate growing stock volume in cubic feet acre⁻¹ and subsequently divided by 100 to convert estimates to hundred cubic feet per acre (CCF acre⁻¹), as expressed in the formula below:
[Formula]
If no matching record is found in the “stdageclass5yr_main” table, alternate values from the “GSVC stdageclass5yr_exceptions” table are used as a fallback. These fallback values represent generalized GSVC estimates aggregated across forest types, stand origins, and age classes. In contrast to the primary lookup table, the exception table does not stratify GSVC estimates by region and instead provides region-agnostic average values.
Based on the user data entry, users will either select “hardwood”, “softwood”, or “unknown” as their wood type. Where users know the wood type (i.e., “hardwood” or “softwood” are selected), there is no need to partition into wood types and this step can be skipped because only the CCF for that selected wood type will be estimated. The value WTf in the Equation DFCT-6 below is therefore “1”.
Where users do not know the wood type (i.e., “unknown” is selected), refer to Smith et al. Table 4 (Table 5 in Annex 1, column highlighted in blue) to select the appropriate fraction of GSV that is softwood that matches the user-selected region and forest type group. The remaining fraction (i.e., 1 minus softwood fraction) is assumed to be hardwood.
Based on the user data entry, users will either select “sawlogs”, “pulpwood”, “fuelwood”, or “unknown” as their log type.
Where users know the log type (i.e., “sawlogs”, “pulpwood”, or “fuelwood” are selected), there is no need to partition into log types and this step can be skipped because only the CCF for that selected log type will be estimated. The value LTf in the Equation DFCT-6 below is therefore “1”.
Where users do not know the log type, refer to Smith et al. Table 4 (Table 5 in Annex, column highlighted in blue, columns highlighted in orange) to select the appropriate fraction of wood that is sawtimber size for the hardwood and softwood categories that matches the user-selected region and forest type group.
Referring to Smith et al. Table 5 (Table 6 in Annex 1, green column), apply the appropriate fraction to determine the amount of growing stock volume that is removed as roundwood for the selected wood and log types based on the user-selected region and forest type group.
Referring to Smith et al. Table 5 (Table 6 in Annex 1, yellow column), determine the amount of Growing Stock Volume that is removed as roundwood for each of the wood and log types identified/ selected.
The final calculations for the pulpwood and sawlogs log types are the same (DFCT-6) and differ from the final calculations for fuelwood (DFCT-7 and DFCT-8). The final estimate of wood volume to send to the Harvested Wood Product Calculator is calculated by applying Eq. DFCT-9 which is the sum of the relevant results from DFCT-6, DFCT-7, and/or DFCT-8 Table 3 below provides a guide for which equations to apply based on the user data entry wood type and log type options:
[Table]
[Formula]
Where users do not know their wood type and/or log type (i.e., they select “unknown” for these categories) the above formula must be applied for both wood types (softwood/hardwood) categories and/or for each log type.
[Formula]
REFER TO SEPARATE PROCEDURES BEING DOCUMENTED BY SIG TO CONVERT VOLUME TO CARBON (OR CARBON DIOXIDE)
Output: HWPtot (MTCO2e)
To estimate carbon in harvest residues which reflects the biomass left on site (i.e., coarse root biomass, stumps, branches, leaves), it is necessary to estimate the amount of harvest residue first and then apply harvest residue/coarse woody debris decay rates to determine the emissions from the harvest residues over time.
Step 8.a Estimate harvest residues
Harvest residues are estimated by first estimating the harvest residue immediately post-harvest and then applying a decay factor. This is because harvest residues do not decay as a fixed amount each year and decomposition occurs at a rate that is proportional to the amount of material remaining.
The initial post-harvest residue is estimated by subtracting the wood volume removed from harvest in MTCO2e (Step 7 above) from the original carbon stocks at the harvested site (not including soil carbon stocks), as described in Equation DFCT-10. While residues generated by harvest would typically be treated as additions to the deadwood and litter pools, for accounting completeness and transparency, they are tracked as a separate post-harvest decay pool in the DFCT.
[Formula]
After the harvest year, the onsite residue pool decays each year by the annual decay rate (DR), provided in Table 4 below.
The remaining residue carbon stocks at 5-year points is estimated by compounding the annual decay rate over the number of years since harvest.
[Formula]
[Table]
Step 8.b Estimate emissions from harvest residues
Emissions during each 5-year timestep are equal to the decrease in the remaining residue stock over that timestep and calculated applying equation DFCT-12 described below.
[Formula]
[Table]
This projection estimates the carbon benefit from deferring harvest in even-aged stands, including estimates of carbon flux from harvest, to estimate total biogenic carbon stock flux (MT CO2eq). The results reflect the difference between projected carbon stocks under the business-as-usual (BAU) planned harvest date and the extended rotation harvest date. The analysis only allows for the option from the HWP calculation where default values on growing stock volumes are applied to estimate postharvest carbon flux (i.e., it does not allow users to enter custom data on harvest volumes).
This allows for side-by-side analysis of harvest scenario results.
Business-as-usual (BAU) planned harvest date
[Table]
Extended rotation planned harvest date
[Table]
Two afforestation options are offered: (1) natural; and (2) planted. Results show the projected total amount of carbon sequestered over 50 years.
The methodological procedures for this scenario are the same as those included under Section 6.2.1 from the “Basic projection” scenario described above, except:
Deforestation
[Table]
Avoided Deforestation
[Table]
Under this scenario, greenhouse gas emissions are quantified for three fire-severity classes. Estimates reflect immediate emissions from combustion of forest biomass, including carbon dioxide (CO₂), methane (CH₄), and nitrous oxide (N₂O). The estimates do not include longer-term post-fire carbon fluxes, such as changes in forest regeneration, decomposition, or subsequent carbon accumulation following the fire event. Users are directed to refer to section 5.2.3 Wildfire and Prescribed Fire within the 2024 Entity Guidelines (Murray et al. 2024) for more information on how these emission factors were devised.
The per-acre emissions magnitude for carbon dioxide (CO2), nitrous oxide (N2O), and methane (CH4) by fire severity scenario (high, moderate, low) have been pre-calculated and converted into metric tonnes of carbon dioxide equivalents (MT CO2e) for each forest type group and region. This scenario projection only uses forest type and region user data entries to estimate immediate emissions from the combustion of forest biomass, so no future projection is included. Therefore, the calculation procedures for this scenario are relatively straightforward, as described in equation DFCT-14 below.
The low-severity fire scenario may be interpreted as a general proxy for prescribed burning.
[Formula]
[Table]
Table 5 Crosswalk with Smith et al. (2006) Table 4 —Factors to calculate carbon in growing stock volume: softwood fraction, sawtimber-size fraction, and specific gravity by region and forest type group
[Table]
Table 6 Crosswalk with Smith et al. (2006) Table 5. — Regional factors to estimate carbon in industrial roundwood logs, bark on logs, and fuelwood
Table 7 Fire Emission Factor Lookup Table
[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.
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.
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 (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.
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 DFCT define regions as the standard, Resources Planning Act regions (see Figure 1)
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.
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 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).
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.