Future projections of U.S. forest succession classes on federal lands

Metadata:
Identification_Information:
Citation:
Citation_Information:
Originator: Walker, David M.
Originator: Costanza, Jennifer K.
Originator: Potter, Kevin M.
Originator: Koch, Frank H.
Originator: Gray, Andrew N.
Originator: Coulston, John W.
Publication_Date: 2025
Title:
Future projections of U.S. forest succession classes on federal lands
Geospatial_Data_Presentation_Form: tabular digital data
Publication_Information:
Publication_Place: Fort Collins, CO
Publisher: Forest Service Research Data Archive
Online_Linkage: https://doi.org/10.2737/RDS-2025-0039
Description:
Abstract:
Changing climate conditions, wildfires, and tree harvesting could affect the amount of mature and old-growth forests in the United States. We used a stochastic modeling system to project future areal extents of mature and old-growth forests on National Forest System (NFS) and Bureau of Land Management (BLM) land across the conterminous United States, and to assess threats to these forests under a variety of socioeconomic and climate futures. The data included in this package contain estimates and projections, from 2020 to 2070, of forest area and volume by forest successional class (old growth, mature, and younger) for 20 futures, which are combinations of four socioeconomic scenarios and five global climate models. Estimates of area, tree volume, fire mortality, and harvest removals are provided for each Resources Planning Act (RPA) region. Additionally, estimates of current and future area of mature and old-growth by Forest Inventory and Analysis (FIA) forest type group are included. For each of the 20 futures in the regional and forest type group summaries, 100 future realizations from the stochastic modeling system are included, allowing for the quantification of uncertainty. Finally, data on initial sampling errors by forest successional class and forest type group are included. It is important to note that estimates by forest type group only include the twelve largest forest type groups (by area in 2020).
Purpose:
These data were developed to assess the effects of changing climate and socioeconomic factors on the projected amount of mature and old-growth forests on federal forests in the United States.
Supplemental_Information:
For more information about this study and these data, see Costanza et al. (accepted, 2025).

These data were published on 08/04/2025. On 08/13/2025, the R code included in this package was updated to correct some of the legends and other updates related to the figures generated.
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2020
Ending_Date: 2070
Currentness_Reference:
Ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: As needed
Spatial_Domain:
Description_of_Geographic_Extent:
Data cover the conterminous United States.
Bounding_Coordinates:
West_Bounding_Coordinate: -127.84295
East_Bounding_Coordinate: -65.41667
North_Bounding_Coordinate: 51.51897
South_Bounding_Coordinate: 23.24503
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: biota
Theme_Keyword: climatologyMeteorologyAtmosphere
Theme_Keyword: economy
Theme_Keyword: environment
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Climate change
Theme_Keyword: Ecology, Ecosystems, & Environment
Theme_Keyword: Environment and People
Theme_Keyword: Fire
Theme_Keyword: Forest & Plant Health
Theme_Keyword: Inventory, Monitoring, & Analysis
Theme_Keyword: Natural Resource Management & Use
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: mature forest
Theme_Keyword: old-growth forest
Theme_Keyword: Resources Planning Act Assessment
Theme_Keyword: RPA Assessment
Theme_Keyword: Forest Inventory and Analysis
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: conterminous United States
Access_Constraints: None
Use_Constraints:
These data were collected using funding from the U.S. Government and can be used without additional permissions or fees. If you use these data in a publication, presentation, or other research product please use the following citation:

Walker, David M.; Costanza, Jennifer K.; Potter, Kevin M.; Koch, Frank H.; Gray, Andrew N.; Coulston, John W. 2025. Future projections of U.S. forest succession classes on federal lands. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2727/RDS-2025-0039
Point_of_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: David M. Walker
Contact_Organization: USDA Forest Service, Southern Research Station through Oak Ridge Institute for Science and Education
Contact_Position: Research
Contact_Address:
Address_Type: mailing and physical
Address: 1650 Research Center Drive
City: Blacksburg
State_or_Province: VA
Postal_Code: 24061
Country: USA
Contact_Voice_Telephone: 540-232-8727
Contact_Electronic_Mail_Address: david.walker@usda.gov
Contact Instructions: This contact information was current as of original publication date. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Data_Set_Credit:
Funding for this project is provided by the USDA Forest Service, Southern Research Station; the USDA Forest Service, Pacific Northwest Research Station; and the USDA Forest Service, Resources Planning Act (RPA) Assessment (joint-venture agreement through ORISE: 21IA11330180032).


Author Information:

David M. Walker
USDA Forest Service, Southern Research Station through Oak Ridge Institute for Science and Education

Jennifer K. Costanza
USDA Forest Service, Southern Research Station
https://orcid.org/0000-0002-3747-538X

Kevin M. Potter
USDA Forest Service, Southern Research Station
https://orcid.org/0000-0002-7330-5345

Frank H. Koch
USDA Forest Service, Southern Research Station
https://orcid.org/0000-0002-3750-4507

Andrew N. Gray
USDA Forest Service, Pacific Northwest Research Station

John W. Coulston
USDA Forest Service, Southern Research Station
https://orcid.org/0009-0008-6619-0325
Cross_Reference:
Citation_Information:
Originator: Costanza, Jennifer K.
Originator: Walker, David M.
Originator: Potter, Kevin M.
Originator: Koch, Frank H.
Originator: Gray, Andrew N.
Originator: Coulston, John W.
Publication_Date: 2025
Title:
Old growth forest area projected to increase on United States federal lands under alternative future scenario
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Earth's Future
Other_Citation_Details:
[accepted]
Analytical_Tool:
Analytical_Tool_Description:
R is a free software environment for statistical computing and graphics.
Tool_Access_Information:
Online_Linkage: https://www.r-project.org/
Tool_Access_Instructions:
See website
Tool_Citation:
Citation_Information:
Originator: R Core Team
Publication_Date: 2025
Title:
R: A Language and Environment for Statistical Computing
Geospatial_Data_Presentation_Form: software
Publication_Information:
Publication_Place: Vienna, Austria
Online_Linkage: https://www.R-project.org/
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
The modeling system relied on data from the Forest Inventory and Analysis (FIA) program. FIA conducts a known-probability sample of all lands across the United States in which each plot represents approximately 2428 hectares (ha) (Bechtold and Patterson 2005). Additionally, FIA uses post-stratification to reduce the variance of estimates, where the population is divided into relatively homogenous strata using remotely sensed imagery.


Bechtold, William A.; Patterson, Paul L. [Editors]. 2005. The enhanced forest inventory and analysis program - national sampling design and estimation procedures. Gen. Tech. Rep. SRS-80. Asheville, NC: U.S. Department of Agriculture, Forest Service, Southern Research Station. 85 p. https://doi.org/10.2737/SRS-GTR-80
Logical_Consistency_Report:
Data were checked to ensure there were no missing values and that estimates were logical (i.e., no negative estimates of area or volume). There are no known errors in the data. Consistency was verified as part of the data compilation and analysis.
Completeness_Report:
These data represent all forest area managed by the USDA Forest Service, National Forest System (NFS) and the Bureau of Land Management (BLM) circa 2020. The projection system assumes that the areal extent of NFS and BLM forest is constant through time in the projection.
Lineage:
Methodology:
Methodology_Type: Field
Methodology_Description:
FOREST ATTRIBUTES

Estimates of forest attributes are measured by the Forest Inventory and Analysis (FIA) program as part of their National Forest Inventory (NFI). Either direct measurements or variables collected in the field are the basis for estimating forest area, wood volume, harvest removals, and tree mortality. Field data collection and compilation were conducted using standard FIA protocols (USDA Forest Service 2024, Burrill et al. 2024). Mature and old-growth forest classification of FIA plots were assigned using the methodology of Pelz et al. (2023) and Woodall et al. (2023). Data were obtained from the FIA DataMart.
Methodology_Citation:
Citation_Information:
Originator: Burrill, Elizabeth A.
Originator: DiTommaso, Andrea M.
Originator: Turner, Jeffery A.
Originator: Pugh, Scott A.
Originator: Christensen, Glenn
Originator: Kralicek, Karin M.
Originator: Perry, Carol J.
Originator: Lepine, Lucie C.
Originator: Walker, David M.
Originator: Conkling, Barbara L.
Publication_Date: 2024
Title:
The Forest Inventory and Analysis Database (FIADB) User Guide
Edition: version 9.3
Geospatial_Data_Presentation_Form: document
Series_Information:
Series_Name: FIADB User Guides
Issue_Identification: database description (version 9.3), nationwide forest inventory (NFI)
Publication_Information:
Publisher: U.S. Department of Agriculture, Forest Service
Other_Citation_Details:
1026 p.
Online_Linkage: https://research.fs.usda.gov/understory/forest-inventory-and-analysis-database-user-guide -nfi
Methodology_Citation:
Citation_Information:
Originator: USDA Forest Service
Publication_Date: 2024
Title:
Forest Inventory and Analysis National Core Field Guide for the Nationwide Forest Inventory
Edition: version 9.4
Geospatial_Data_Presentation_Form: document
Publication_Information:
Publisher: U.S. Department of Agriculture, Forest Service
Other_Citation_Details:
550 p.
Online_Linkage: https://research.fs.usda.gov/sites/default/files/2024-09/wo-v9-4_sep2024_fg_nfi_natl.pdf
Methodology_Citation:
Citation_Information:
Originator: Pelz, K. A.
Originator: Hayward, G.
Originator: Gray, A. N.
Originator: Berryman, E. M.
Originator: Woodall, C. W.
Originator: Nathanson, A.
Originator: Morgan, N. A.
Publication_Date: 2023
Title:
Quantifying old-growth forest of United States Forest Service public lands
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Forest Ecology and Management
Issue_Identification: 549: 121437
Online_Linkage: https://doi.org/10.1016/j.foreco.2023.121437
Online_Linkage: https://research.fs.usda.gov/treesearch/66801
Methodology_Citation:
Citation_Information:
Originator: Woodall, C. W.
Originator: Kamoske, A. G.
Originator: Hayward, G. D.
Originator: Schuler, T. M.
Originator: Hiemstra, C. A.
Originator: Palmer, M.
Originator: Gray, A. N.
Publication_Date: 2023
Title:
Classifying mature federal forests in the United States: The forest inventory growth stage system
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Forest Ecology and Management
Issue_Identification: 546: 121361
Online_Linkage: https://doi.org/10.1016/j.foreco.2023.121361
Online_Linkage: https://research.fs.usda.gov/treesearch/66576
Source_Information:
Source_Citation:
Citation_Information:
Originator: USDA Forest Service
Publication_Date: 2024
Title:
Forest Inventory and Analysis database (FIA DataMart)
Geospatial_Data_Presentation_Form: database
Publication_Information:
Publisher: USDA Forest Service, Northern Research Station
Other_Citation_Details:
(last updated 18 October, 2024)
Online_Linkage: https://doi.org/10.2737/RDS-2001-FIADB
Online_Linkage: https://apps.fs.usda.gov/fia/datamart/datamart.html
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2020
Ending_Date: 2020
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
FIA DataMart
Source_Contribution:
Forest area, wood volume, harvest removals, and tree mortality
Process_Step:
Process_Description:
PROJECTIONS

The initial inventory plots were projected forward in time using the Forest Dynamics Model (FDM). The 2020 inventory plots were based on the most recent set of FIA inventory plots that were available circa 2020. The FDM is a stochastic modeling system developed for the 2020 Resources Planning Act Assessment that incorporates projections of forest conditions and areas for the conterminous United States for 2020-2070. Full documentation of the FDM can be found elsewhere (Coulston et al. 2023), but the following is a brief summary. The FDM projects FIA plot conditions, including mature or old-growth classification, into the future using an imputation approach (Coulston et al. 2023, USDA Forest Service 2023), allowing for consistent projections that are based on the observed relationships among FIA variables at the plot level through the projection period. The FDM is informed by exogenous variables including climate, timber prices, global timber demand, human population, and income, as well as by a set of submodels governing harvest choices, harvest volume, fire, growth, aging, regeneration, and forest type transitions over time (USDA Forest Service 2023).

The modeling system used four scenarios of socioeconomic growth and warming from the Intergovernmental Panel on Climate Change (IPCC) Shared Socioeconomic Pathways and Representative Concentration Pathways: lower warming/moderate U.S. growth (LM), high warming/low U.S. growth (HL), high warming/moderate U.S. growth (HM), and high warming/high U.S. growth (HH) (O’Dea et al. 2023). Each was coupled with five climate models representing the envelope of projected future temperature and precipitation across the United States. We additionally quantified projected trends in mature and old-growth tree mortality due to wildfire, as well as expected tree harvest rates (Joyce and Coulson 2020).

The current and future inventories were summarized by RPA region, forest successional class (old growth, mature, and younger), and forest type group. The forest successional classes were assigned based on methodologies presented in Pelz et al. (2023) and Woodall et al. (2023). Forest-type groups are categories used to represent communities made up of similar tree and plant species. The forest type of each FIA plot are assigned by FIA based on relative species stocking levels.


For additional details, see Costanza et al. (accepted, 2025).


Costanza, Jennifer K.; Walker, David M.; Potter, Kevin M.; Koch, Frank H.; Gray, Andrew N.; Coulston, John W. [accepted, 2025]. Old growth forest area projected to increase on United States federal lands under alternative future scenario. Earth's Future.

Coulston, John W.; Domke, Grant M.; Walker, David M.; Brooks, Evan B.; O'Dea, Claire B. 2023. Near-term investments in forest management support long-term carbon sequestration capacity in forests of the United States. Pnas Nexus. 2(11): pgad345. https://doi.org/10.1093/pnasnexus/pgad345

Joyce, Linda A.; Coulson, David. 2020. Climate Scenarios and Projections: A Technical Document Supporting the USDA Forest Service 2020 RPA Assessment. General Technical Report. RMRS-GTR-413. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. https://doi.org/10.2737/RMRS-GTR-413

O'Dea, Claire B.; Langner, Linda L.; Joyce, Linda A.; Prestemon, Jeffrey P.; Wear, David N. 2023. Future Scenarios. Chapter 3. https://doi.org/10.2737/WO-GTR-102-Chap3. In: U.S. Department of Agriculture, Forest Service. 2023. Future of America’s Forest and Rangelands: Forest Service 2020 Resources Planning Act Assessment. General Technical Report. WO-102. Washington, DC: U.S. Department of Agriculture, Forest Service. 348 p. https://doi.org/10.2737/WO-GTR-102

U.S. Department of Agriculture, Forest Service. 2023. Future of America’s Forest and Rangelands: Forest Service 2020 Resources Planning Act Assessment. General Technical Report. WO-102. Washington, DC: U.S. Department of Agriculture, Forest Service. 348 p. https://doi.org/10.2737/WO-GTR-102
Source_Used_Citation_Abbreviation:
FIA DataMart
Process_Date: Unknown
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Entity_and_Attribute_Information:
Overview_Description:
Entity_and_Attribute_Overview:
Below you will find a list and description of the files included in this data publication.

VARIABLE DESCRIPTION FILE (1)

1. \Data\_variable_descriptions.csv: Comma-separated values (CSV) file containing a list and description of variables found in all data files. (A description of these variables is also provided in the metadata below.)

Columns include:

Filename = name of data file
Variable = name of variable
Units = units (if applicable)
Precision = precision (if applicable)
Description = description of variable



DATA FILES (3)

1. \Data\mog_data_forest_type_group.csv: CSV file containing estimates of current (2020) and future (2030-2070) areas of mature and old growth (mog). Data are provided by Forest Inventory and Analysis (FIA) forest type group (12 classes), forest successional class (mature, old growth, younger), and 20 different climate scenarios/models.

Variables include:

scenario = Intergovernmental Panel on Climate Change (IPCC) Shared Socioeconomic Pathways and Representative Concentration Pathway scenario, where:
HH = High warming/high growth
HL = High warming/low growth
HM = High warming/moderate growth
LM = Lower warming/moderate growth)

gcm = Global climate model, values include:
Dry (IPSL-CM5A-MR)
Hot (HadGEM2-ES365)
Least Warm (MRI-CGCM3)
Middle (NorESM1-M)
Wet (CNRM-CM5)

year = Year (2020, 2030, 2040, 2050, 2060, 2070)

mog.class = Mature and old-growth forest class (mature, old growth, younger)

forest.type.group = Forest Inventory and Analysis (FIA) forest-type group, values include:
Aspen / birch
California mixed conifer
Douglas-fir
Fir / spruce / mtn. hemlock
Hemlock / Sitka spruce
Lodgepole pine
Longleaf / slash pine
Oak / hickory
Pinyon / juniper
Ponderosa pine
Spruce / fir
Western larch

rep = Replication number (1-100)

area = Area of the estimates, in hectares


2. \Data\mog_data_initial_sampling_error.csv: CSV file containing initial sampling error. Data are provided by forest successional class and forest type group.

Variables include:

mog.class = Mature and old-growth forest class (mature, old growth, younger)

forest.type.group = Forest Inventory and Analysis (FIA) forest-type group, values include:
Aspen / birch
California mixed conifer
Douglas-fir
Fir / spruce / mtn. hemlock
Hemlock / Sitka spruce
Lodgepole pine
Longleaf / slash pine
Oak / hickory
Pinyon / juniper
Ponderosa pine
Spruce / fir
Western larch

area_estimate = Area of the estimates, in hectares

se_of_estimate_pct = Percent sampling error of the estimate

se_of_estimate = Sampling error of the estimate, in hectares

var_of_estimate = Variance of the estimate, in hectares

total_plots = Total number of plots in the sample

non_zero_plots = Number of plots where the attribute of interest was observed

tot_pop_ac = Area represented by all plots (total_plots) in the sample, in hectares


3. \Data\mog_data_region.csv: CSV file containing regional estimates of area, tree volume, fire mortality, and harvest removals. Regional data are provided by forest successional class, decade (2020-2070), and 20 different climate scenarios/models.

Variables include:

scenario = Intergovernmental Panel on Climate Change (IPCC) Shared Socioeconomic Pathways and Representative Concentration Pathway scenario, where:
HH = High warming/high growth
HL = High warming/low growth
HM = High warming/moderate growth
LM = Lower warming/moderate growth)

gcm = Global climate model, values include:
Dry (IPSL-CM5A-MR)
Hot (HadGEM2-ES365)
Least Warm (MRI-CGCM3)
Middle (NorESM1-M)
Wet (CNRM-CM5)

year = Year (2020, 2030, 2040, 2050, 2060, 2070)

mog.class = Mature and old-growth forest class (mature, old growth, younger)

region = Resources Planning Act (RPA) region (North, Pacific Coast, Rocky Mountain, South)

rep = Replication number (1-100)

area = Area of the estimates, in hectares

live_vol = Net merchantable bole wood volume of live trees (timber species at least 5 inches diameter at breast height (dbh)), in cubic meters

fire_vol = Annual net merchantable bole wood volume of trees (timber species at least 5 inches dbh) killed by fire, in cubic meters per year

removal = Average annual harvest removals of merchantable bole wood volume of growing-stock trees (at least 5 inches dbh), in cubic meters per year



SUPPLEMENTAL FILES (1)

1. \Supplements\summarize_MOG_FDM.R: Text file containing R code that summarizes output from the Forest Dynamics Model (FDM) model and generates figures for Constanza et al. (2025).
Entity_and_Attribute_Detail_Citation:
Costanza, Jennifer K.; Walker, David M.; Potter, Kevin M.; Koch, Frank H.; Gray, Andrew N.; Coulston, John W. [accepted, 2025]. Old growth forest area projected to increase on United States federal lands under alternative future scenario. Earth's Future.
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Distribution_Information:
Distributor:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Research and Development
Contact_Position: Research Data Archivist
Contact_Address:
Address_Type: mailing and physical
Address: 240 West Prospect Road
City: Fort Collins
State_or_Province: CO
Postal_Code: 80526
Country: USA
Contact_Voice_Telephone: see Contact Instructions
Contact Instructions: This contact information was current as of August 2025. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Resource_Description: RDS-2025-0039
Distribution_Liability:
Metadata documents have been reviewed for accuracy and completeness. Unless otherwise stated, all data and related materials are considered to satisfy the quality standards relative to the purpose for which the data were collected. However, neither the author, the Archive, nor any part of the federal government can assure the reliability or suitability of these data for a particular purpose. The act of distribution shall not constitute any such warranty, and no responsibility is assumed for a user's application of these data or related materials.

The metadata, data, or related materials may be updated without notification. If a user believes errors are present in the metadata, data or related materials, please use the information in (1) Identification Information: Point of Contact, (2) Metadata Reference: Metadata Contact, or (3) Distribution Information: Distributor to notify the author or the Archive of the issues.
Standard_Order_Process:
Digital_Form:
Digital_Transfer_Information:
Format_Name: CSV
Format_Version_Number: see Format Specification
Format_Specification:
Comma-separated values file
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2025-0039
Digital_Form:
Digital_Transfer_Information:
Format_Name: R
Format_Version_Number: see Format Specification
Format_Specification:
Text file containing R code
Digital_Transfer_Option:
Online_Option:
Computer_Contact_Information:
Network_Address:
Network_Resource_Name: https://doi.org/10.2737/RDS-2025-0039
Fees: None
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Metadata_Reference_Information:
Metadata_Date: 20250813
Metadata_Contact:
Contact_Information:
Contact_Person_Primary:
Contact_Person: David M. Walker
Contact_Organization: USDA Forest Service, Southern Research Station through Oak Ridge Institute for Science and Education
Contact_Position: Research
Contact_Address:
Address_Type: mailing and physical
Address: 1650 Research Center Drive
City: Blacksburg
State_or_Province: VA
Postal_Code: 24061
Country: USA
Contact_Voice_Telephone: 540-232-8727
Contact_Electronic_Mail_Address: david.walker@usda.gov
Contact Instructions: This contact information was current as of original publication date. For current information see Contact Us page on: https://doi.org/10.2737/RDS.
Metadata_Standard_Name: FGDC Biological Data Profile of the Content Standard for Digital Geospatial Metadata
Metadata_Standard_Version: FGDC-STD-001.1-1999
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