Data from "Wildfire severity and postfire salvage harvest effects on long-term forest regeneration"

Metadata:

Identification_Information:
Citation:
Citation_Information:
Originator: Povak, Nicholas A.
Originator: Churchill, Derek J.
Originator: Cansler, C. Alina
Originator: Hessburg, Paul F.
Originator: Kane, Van R.
Originator: Kane, Jonathan T.
Originator: Lutz, James A.
Originator: Larson, Andrew J.
Publication_Date: 2021
Title:
Data from "Wildfire severity and postfire salvage harvest effects on long-term forest regeneration"
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-2020-0079
Description:
Abstract:
This data publication contains data from a study that evaluated long-term (15-30 year) post-fire regeneration patterns across eastern Washington. These data include both: 1) field-based measurements on seedling and sapling (< 4-meter[m]) height regeneration, overstory tree (> 4-m height), and understory vegetation, and 2) remotely sensed fire severity (Monitoring Trends in Burn Severity; Eidenshink et al. 2007), 30-year climate normals and post-fire weather (climateWNA; Wang et al. 2016), and topography data (National Elevation Dataset, http://ned.usgs.gov/). The study area was located within the Okanogan-Wenatchee and Colville National Forests. A total of 248 sample sites were visited in summer 2017 and represented a gradient of dry, moist, and cold-dry mixed-conifer forest types. Sites were selected within salvage logged and untreated areas and were selected exclusively in moderate and high severity fire patches. Field sampling occurred within a fixed 16-m radius circular plot within which four subplots (which varied in size depending on initial assessment of regeneration densities) were established at cardinal directions, where tree regeneration was tallied by species and height class.
Purpose:
These data were collected for ecological research purposes.
Supplemental_Information:
For more information about this study, the data, and collection methods see Povak et al. (2020).
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 20170701
Ending_Date: 20171111
Currentness_Reference:
Ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: None planned
Spatial_Domain:
Description_of_Geographic_Extent:
The study area is located on state and federal lands within the boundaries of National Forests in eastern Washington State, USA, including the northern half of the Okanogan-Wenatchee NF (ONF) and the western half of the Colville NF (CNF), and including National Park Service, and Washington State Department of Fish and Wildlife, and Department of Natural Resources lands.
Bounding_Coordinates:
West_Bounding_Coordinate: -121.20000
East_Bounding_Coordinate: -117.00000
North_Bounding_Coordinate: 49.00000
South_Bounding_Coordinate: 47.45000
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: environment
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Fire
Theme_Keyword: Fire effects on environment
Theme_Keyword: Ecology, Ecosystems, & Environment
Theme_Keyword: Landscape ecology
Theme_Keyword: Natural Resource Management & Use
Theme_Keyword: Forest management
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: climatic tolerance
Theme_Keyword: Douglas-fir
Theme_Keyword: dry forest
Theme_Keyword: high severity
Theme_Keyword: lodgepole pine
Theme_Keyword: ponderosa pine
Theme_Keyword: regeneration
Theme_Keyword: resilience
Theme_Keyword: salvage harvest
Theme_Keyword: seed dispersal
Theme_Keyword: western larch
Theme_Keyword: wildfire
Theme_Keyword: Joint Fire Science Program
Theme_Keyword: JFSP
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Washington
Place_Keyword: Eastern Cascades section (M242C)
Place_Keyword: Highlands section (M333A)
Place_Keyword: Okanogan-Wenatchee National Forest
Place_Keyword: Colville National Forest
Taxonomy:
Keywords/Taxon:
Taxonomic_Keyword_Thesaurus:
None
Taxonomic_Keywords: multiple species
Taxonomic_Keywords: plants
Taxonomic_System:
Classification_System/Authority:
Classification_System_Citation:
Citation_Information:
Originator: ITIS
Publication_Date: 2021
Title:
Integrated Taxonomic Information System
Geospatial_Data_Presentation_Form: database
Other_Citation_Details:
Retrieved [March, 8, 2021]
Online_Linkage: https://www.itis.gov
Taxonomic_Procedures:
Taxonomic_Classification:
Taxon_Rank_Name: Kingdom
Taxon_Rank_Value: Plantae
Applicable_Common_Name: plantes
Applicable_Common_Name: Planta
Applicable_Common_Name: Vegetal
Applicable_Common_Name: plants
Taxonomic_Classification:
Taxon_Rank_Name: Subkingdom
Taxon_Rank_Value: Viridiplantae
Applicable_Common_Name: green plants
Taxonomic_Classification:
Taxon_Rank_Name: Infrakingdom
Taxon_Rank_Value: Streptophyta
Applicable_Common_Name: land plants
Taxonomic_Classification:
Taxon_Rank_Name: Superdivision
Taxon_Rank_Value: Embryophyta
Taxonomic_Classification:
Taxon_Rank_Name: Division
Taxon_Rank_Value: Tracheophyta
Applicable_Common_Name: vascular plants
Applicable_Common_Name: tracheophytes
Taxonomic_Classification:
Taxon_Rank_Name: Subdivision
Taxon_Rank_Value: Spermatophytina
Applicable_Common_Name: spermatophytes
Applicable_Common_Name: seed plants
Applicable_Common_Name: phanérogames
Taxonomic_Classification:
Taxon_Rank_Name: Class
Taxon_Rank_Value: Magnoliopsida
Taxonomic_Classification:
Taxon_Rank_Name: Superorder
Taxon_Rank_Value: Rosanae
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Fagales
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Betulaceae
Applicable_Common_Name: alder
Applicable_Common_Name: birch
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Alnus
Applicable_Common_Name: alder
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Alnus rhombifolia
Applicable_Common_Name: rhombie leaf alder
Applicable_Common_Name: white alder
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Alnus rubra
Applicable_Common_Name: red alder
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Betula
Applicable_Common_Name: birch
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Sapindales
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Sapindaceae
Applicable_Common_Name: soapberries
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Acer
Applicable_Common_Name: maples
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Acer macrophyllum
Applicable_Common_Name: bigleaf maple
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Malpighiales
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Salicaceae
Applicable_Common_Name: willows
Applicable_Common_Name: saules
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Populus
Applicable_Common_Name: cottonwood
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Populus tremuloides
Applicable_Common_Name: quaking aspen
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Populus nigra
Applicable_Common_Name: black cottonwood
Applicable_Common_Name: black poplar
Applicable_Common_Name: Lombardy's poplar
Taxonomic_Classification:
Taxon_Rank_Name: Class
Taxon_Rank_Value: Pinopsida
Applicable_Common_Name: conifers
Taxonomic_Classification:
Taxon_Rank_Name: Subclass
Taxon_Rank_Value: Pinidae
Taxonomic_Classification:
Taxon_Rank_Name: Order
Taxon_Rank_Value: Pinales
Applicable_Common_Name: pines
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Pinaceae
Applicable_Common_Name: pines
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Abies
Applicable_Common_Name: fir
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Abies amabilis
Applicable_Common_Name: red fir
Applicable_Common_Name: white fir
Applicable_Common_Name: cascade fir
Applicable_Common_Name: lovely fir
Applicable_Common_Name: Pacific silver fir
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Abies grandis
Applicable_Common_Name: white fir
Applicable_Common_Name: silver fir
Applicable_Common_Name: giant fir
Applicable_Common_Name: lowland white fir
Applicable_Common_Name: yellow fir
Applicable_Common_Name: grand fir
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Picea
Applicable_Common_Name: spruce
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Picea engelmannii
Applicable_Common_Name: Engelmann spruce
Applicable_Common_Name: Columbian spruce
Applicable_Common_Name: mountain spruce
Applicable_Common_Name: silver spruce
Applicable_Common_Name: white spruce
Applicable_Common_Name: Engelmann's spruce
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Pinus
Applicable_Common_Name: pine
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Pinus contorta
Applicable_Common_Name: lodgepole pine
Applicable_Common_Name: scrub pine
Applicable_Common_Name: shore pine
Applicable_Common_Name: tamarack pine
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Pinus monticola
Applicable_Common_Name: western white pine
Applicable_Common_Name: Idaho white pine
Applicable_Common_Name: mountain white pine
Applicable_Common_Name: silver pine
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Pinus ponderosa
Applicable_Common_Name: ponderosa pine
Applicable_Common_Name: bull pine
Applicable_Common_Name: western yellow pine
Applicable_Common_Name: blackjack pine
Applicable_Common_Name: pinabete
Applicable_Common_Name: rock pine
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Larix
Applicable_Common_Name: larch
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Larix occidentalis
Applicable_Common_Name: hackmatack
Applicable_Common_Name: Montana larch
Applicable_Common_Name: mountain larch
Applicable_Common_Name: western tamarack
Applicable_Common_Name: western larch
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Pseudotsuga
Applicable_Common_Name: Douglas-fir
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Pseudotsuga menziesii
Applicable_Common_Name: red fir
Applicable_Common_Name: Douglas spruce
Applicable_Common_Name: Oregon pine
Applicable_Common_Name: Douglas-fir
Taxonomic_Classification:
Taxon_Rank_Name: Family
Taxon_Rank_Value: Cupressaceae
Applicable_Common_Name: cypress
Applicable_Common_Name: redwood
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Thuja
Applicable_Common_Name: arborvitae
Applicable_Common_Name: cèdre
Applicable_Common_Name: thuya
Applicable_Common_Name: red cedar
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Thuja plicata
Applicable_Common_Name: western red cedar
Applicable_Common_Name: western redcedar
Taxonomic_Classification:
Taxon_Rank_Name: Genus
Taxon_Rank_Value: Juniperus
Applicable_Common_Name: juniper
Applicable_Common_Name: cedar
Applicable_Common_Name: cedro
Applicable_Common_Name: redcedar
Applicable_Common_Name: sabino
Taxonomic_Classification:
Taxon_Rank_Name: Species
Taxon_Rank_Value: Juniperus occidentalis
Applicable_Common_Name: western juniper
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:

Povak, Nicholas A.; Churchill, Derek J.; Cansler, C. Alina; Hessburg, Paul F.; Kane, Van R.; Kane, Jonathan T.; Lutz, James A.; Larson, Andrew J. 2021. Data from "Wildfire severity and postfire salvage harvest effects on long-term forest regeneration". Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2020-0079
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Pacific Northwest Research Station
Contact_Person: Nicholas A. Povak
Contact_Position: Post-doc Research Forester
Contact_Address:
Address_Type: mailing and physical
Address: 400 North 34th Street, Suite 201
City: Seattle
State_or_Province: WA
Postal_Code: 98103
Country: USA
Contact_Voice_Telephone: 608-347-7629
Contact_Electronic_Mail_Address: nicholas.povak@usda.gov
Data_Set_Credit:
Funding for this project provided by Joint Fire Science Program (JFSP # 16-1-05-24): https://www.firescience.gov. Some funds for salary were also provided by USDA Forest Service, Pacific Southwest Research Station and USDA Forest Service, Pacific Northwest Research Station.


Author Information:

Povak, Nicholas A.
USDA Forest Service, Pacific Southwest Research Station
https://orcid.org/0000-0003-1220-7095

Churchill, Derek J.
Washington State Department of Natural Resources

Cansler, C. Alina
University of Washington, School of Environmental and Forest Sciences

Hessburg, Paul F.
USDA Forest Service, Pacific Northwest Research Station
https://orcid.org/0000-0002-0330-7230

Kane, Van R.
University of Washington
https://orcid.org/0000-0002-0792-4850

Kane, Jonathan T.
University of Washington

Lutz, James A.
Utah State University
https://orcid.org/0000-0002-2560-0710

Larson, Andrew J.
University of Montana
https://orcid.org/0000-0003-4926-7569
Cross_Reference:
Citation_Information:
Originator: Povak, Nicholas A.
Originator: Churchill, Derek J.
Originator: Cansler, C. Alina
Originator: Hessburg, Paul F.
Originator: Kane, Van R.
Originator: Kane, Jonathan T.
Originator: Lutz, James A.
Originator: Larson, Andrew J.
Publication_Date: 2020
Title:
Wildfire severity and postfire salvage harvest effects on long‐term forest regeneration
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Ecosphere
Issue_Identification: 11(8): p.e03199
Online_Linkage: https://doi.org/10.1002/ecs2.3199
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
Data entry was error checked using double entry on subset of data. Summary tables and visualizations in R were used to check for accuracy and completeness.

Specifics on accuracy of each measurement are provided, where known, in the variable descriptions provided.
Completeness_Report:
"Unknown", "NA", and blank cells are used to denote missing data. See the Notes column for each data set for additional information. Unknown for Planted, PCT, and salvage would indicate that it was not possible to determine if that type of management was conducted in the field. The rows where most of the information is blank cells are those plots that were abandoned. Most of those say that the plot was moved or abandoned in the notes. Blank UTM coordinates suggest missing UTM data and NAs in the time_off field were just not recorded. Other NAs indicate the attributes were not recorded in the field (e.g., missing data). Often NAs are labelled with "Missing Data" in the Notes field.
Lineage:
Methodology:
Methodology_Type:
Methodology_Description:
STUDY AREA AND DESIGN

Our sample sites focused on three classes of mixed-conifer forest—dry, moist, and cold-dry, which were derived from U.S. Forest Service potential vegetation maps and classifications. These types were chosen because they occupy a range of climatic conditions that vary in the evaporative demand placed on tree establishment and growth, represent the majority of forest land-scapes, are regularly influenced by wildfires, and are the focus of postfire management.

Our experimental design included three main factors: (1) fire severity (moderate or high), (2) postfire salvage logging (without post-harvest planting) or no postfire management, and (3) potential vegetation type (PVT, dry mixed-coni-fer, moist mixed-conifer, or cold-dry forest. Potential sample sites were retained if they satisfied six criteria: They were (1) within a fire perimeter that occurred prior to 2007, (2) >30 m inside a fire severity patch of moderate or higher severity, (3) within a dry mixed, moist mixed, or cold-dry conifer type, (4) within an area of recent LiDAR acquisition, (5) within 3 kilometers (km) of a road, and (6) suitable for sampling after evaluation with aerial photography.

In the data files, Plot_IDs identify the main plot or the sample site. Subplots were located within each main plot where tree regeneration and non-tree regeneration were sampled.


DATA COLLECTION

A total of 248 sample sites were visited in summer 2017 and represented a gradient of dry, moist, and cold-dry mixed-conifer forest types. Sites were selected within salvage logged and untreated areas and were selected exclusively in moderate and high severity fire patches. Field sampling occurred within a fixed 16-m radius circular plot within which four subplots were established at cardinal directions, where tree regeneration (stems < 4-m height) was tallied by species and height class (< 1-m, 1 to 2-m, 2 to 4-m heights). Subplots varied in size from 16 x 0.5-m (0.0008 ha; n = 36), 16 x 2-m (0.0032 ha; n = 120) to the full 16-m circle (0.08 ha; n = 92), depending on initial assessment of regeneration densities.

Plot identification numbers follow a pattern beginning with a series of randomly generated numbers and a three-letter acronym where 1) the first letter represents forest type: D) dry mixed-conifer, M) moist mixed-conifer, and C) cold forest, 2) the second letter represents fire severity: M) moderate, H) high severity, and 3) the third letter represents management: N) no management, S) salvage harvested with no planting.

Seed Source Info: Distance to seed trees were measured in the field from plot center to the base of each tree. A seed tree is defined here as a species of mature seed-bearing tree that would have been alive and reproductive after fire. Similarly, distance to patch edge was measured, where patch edge was determined in the field where the moderate or high severity patch ended and unburned or low-severity burned patches started.


MODEL DATA

Model data (Model_Data.csv) include data that were collected in the field (e.g., regeneration, seed tree, overstory data) and that were remotely sensed (e.g., climate, post-fire weather, topography data). Columns C-N represent regeneration densities measured in the field for all species (C), for individual species (D-M), and for non-conifer species (N). Live and dead tree overstory density (TPH; trees per hectare [ha]), basal area (BA; m² ha-1), and quadratic mean diameter (cm) data were also collected in the field and represented in columns S-AS. These data are recorded for all trees and for individual species. The distance to nearest seed tree (in meters) were also measured in the field from the plot center to the nearest mature tree of each dominant conifer species and are represented in columns AT-BF. Plot center locations were also measured in the field and represented in both latitude and longitude (BG, BH), and in albers projection (BI, BJ). Distance to road (d2r, column BL) was measured using a GIS for each plot. Fuel model was also assessed in the field (column BM), the number of fires (BN) and fire severity (rdnbr) class (BO) was assessed using MTBS burn severity data (Eidenshink et al. 2007). Severity class 2 is moderate severity, and class 3 is high severity. AET.x (BQ) and DEF (BR) are actual evapotranspiration and climatic water deficit calculate by Derek Churchill and Sean Jeronimo (unpublished, available upon request). Topography variables were derived in GIS (BS-BW). Time since last fire (tslf; BX) was assessed in GIS using MTBS data. USDA Forest Service membership was assessed in GIS using the Administrative Forest Boundaries data set from the USDA Forest Service National Datasets (https://data.fs.usda.gov/geodata/edw/datasets.php). Climate data: MAT (mean annual temperature; column CA), MAP (mean annual precipitation; CB), Reference Evapotranspiration (Eref, CC), climatic moisture deficit (CMD, CD), and actual evapotranspiration (AET.y, CE) were all derived from climateWNA (Wang et al. 2016). Percentile weather conditions MATp (CF), MAPp (CG), Eref (CH), CMDp (CI), AETp (CJ) were similarly derived from climateWNA and represent percentile post-fire weather conditions (1-3 years post-fire) based on a 50-year time series of weather data 1965-2016. Understory vegetation were also measured in the field and include percent shrub cover (shrb_pcov, CN), average shrub height (meters, shrb_avht, CO), maximum shrub height (meters, shrb_mxht, CP), percent grass cover (grs_pcov, CQ), average grass height (meters, grs_avht, CR), maximum grass height (meters, grs_mxht, CS).


For complete details see Povak et al. (2020).
Methodology_Citation:
Citation_Information:
Originator: Povak, Nicholas A.
Originator: Churchill, Derek J.
Originator: Cansler, C. Alina
Originator: Hessburg, Paul F.
Originator: Kane, Van R.
Originator: Kane, Jonathan T.
Originator: Lutz, James A.
Originator: Larson, Andrew J.
Publication_Date: 2020
Title:
Wildfire severity and postfire salvage harvest effects on long-term forest regeneration
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Ecosphere
Issue_Identification: 11(8): p.e03199
Online_Linkage: https://doi.org/10.1002/ecs2.3199
Source_Information:
Source_Citation:
Citation_Information:
Originator: Eidenshink, Jeff
Originator: Schwind, Brian
Originator: Brewer, Ken
Originator: Zhu, Zhi-Liang
Originator: Quayle, Brad
Originator: Howard, Stephen
Publication_Date: 2007
Title:
A project for monitoring trends in burn severity
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Fire ecology
Issue_Identification: 3(1): 3-21
Online_Linkage: https://doi.org/10.4996/fireecology.0301003
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 1984
Ending_Date: 2015
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
Eidenshink et al. (2007)
Source_Contribution:
Remotely sensed fire severity data come from the 30-meter resolution Monitoring Trends in Burn Severity (MTBS; mtbs.gov) database. Fires that were > 404 hectares and that burned between 1984 and 2015 were considered for sampling.

Number of fires (BN) and fire severity (rdnbr) class (BO) was assessed using MTBS burn severity data (Eidenshink et al. 2007) as well as time since last fire (tslf; BX) was assessed in GIS using MTBS data.
Source_Information:
Source_Citation:
Citation_Information:
Originator: Wang, Tongli
Originator: Hamann, Andreas
Originator: Spittlehouse, Dave
Originator: Carroll, Carlos
Publication_Date: 2016
Title:
Locally downscaled and spatially customizable climate data for historical and future periods for North America
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: PLOS ONE
Issue_Identification: 11: e0156720
Online_Linkage: https://doi.org/10.1371/journal.pone.0156720
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2017
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
Wang et al. (2016)
Source_Contribution:
30-year climate normals and post-fire weather data were obtained using the desktop application climateWNA (Wang et al. 2016): http://www.climatewna.com/.

Specifically, MAT (mean annual temperature; column CA), MAP (mean annual precipitation; CB), Reference Evapotranspiration (Eref, CC), climatic moisture deficit (CMD, CD), and actual evapotranspiration (AET.y, CE) were all derived from climateWNA.
Source_Information:
Source_Citation:
Citation_Information:
Originator: U.S. Geological Survey, National Geospatial Program
Publication_Date: Unknown
Title:
National Elevation Dataset
Geospatial_Data_Presentation_Form: raster digital data
Online_Linkage: http://ned.usgs.gov/
Type_of_Source_Media: Online
Source_Time_Period_of_Content:
Time_Period_Information:
Single_Date/Time:
Calendar_Date: 2017
Source_Currentness_Reference:
Publication Date
Source_Citation_Abbreviation:
NED
Source_Contribution:
We obtained a 1/3 arc-second (~10 m) digital elevation model (DEM) from the National Elevation Dataset (http://ned.usgs.gov/), and re-projected the elevation data to 30-m resolution using bilinear interpolation.
Process_Step:
Process_Description:
For information regarding data obtained from other sources, see the methodology section.

Field data was summarized using abundance statistics at the plot scale.

For regeneration (i.e., all stems < 4 m height) the density of regenerating stems was calculated for each subplot based on the count of stems in a subplot and the area of the subplot, which was determined in the field and documented in the Seed_Sap column of the Plot_Data.csv (S = 16 x 0.5-m (0.0008 ha), M = 16 x 2-m (0.0032 ha) to the L = full 16-m circle (0.08 ha; n = 92)).

See Povak et al. (2020) for more information.
Process_Date: 201805
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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 (8) included in this data publication.

All data files are provided as comma-separated values files.

1. \Data\Variable_Descriptions.csv: List and description of each of the variables found in the data files included in this package.
Columns in this file include:
Worksheet = name of worksheet
Variable = name of variable
Description = description of variable
Units or Code Descriptions = units for variable, or if variable is categorical codes are defined

2. \Data\Heights.csv: Overstory tree heights measured in the full 16-meter (m) main plot. Heights were measured on a subsample of 3-9 trees depending on the number of species present. File includes Height, total crown ratio (TCR), and compacted crown ratio (CCR).

3. \Data\Model_Data.csv: Plot-level summaries used to summarize plot- and treatment-level regeneration summaries, and regression modeling. Includes data summarized to the main-plot level from Plot_Data.csv, Seed_Sap.csv, Seed_Source.csv, Overstory.csv, and Non_Tree.csv.

4. \Data\Non_Tree.csv: Non-tree vegetation sampling. Categories are tall shrubs (TS, > 2 m); shrubs (S, 0.5 m - 2 m tall); sub-shrubs (< 0.5 m tall) and forbs/herbs combined (SS); pinegrass (Calamagrostis rubescens) only (PG); and all graminoids including pinegrass (GR). Data include percent cover, average height and maximum height.

5. \Data\Overstory.csv: Overstory tree data collected within the 16-m main plot. Data were collected for live and dead trees > 4 m tall and include species, diameter, and tree status. Snag decay classes (Maser et al. 1979) include D1 (Snag decay class 1), D2 (Snag decay class 2-3), and D3 (Snag decay class 4-5).

6. \Data\Plot_Data.csv: Plot information such as whether it was measured or abandoned, whether there was evidence of planting, pre-commercial thinning, and/or salvage. It also denotes the size of the seedling/sapling subplots, the GPS coordinates and fuel model. (Note: this file contains data for the 248 plots in this study and the additional plots denoted as abandoned.)

7. \Data\Seed_Sap.csv: Seedling and sapling (< 4 m height) field data collected from each regeneration subplot.

8. \Data\Seed_Source.csv: Data representing the distance from plot center to individual mature seed trees. Seed trees are those that are > 10 inches DBH, or > 25 feet tall, or a tree that has visible reproductive structures (cones, seeds, flowers, etc.) seed, flowers. Also recorded was the edge of the stand-replacing burn patch, defined as a group of ≥ 10 live, reproductively mature trees.
Entity_and_Attribute_Detail_Citation:
Maser, C. M.; Anderson, R. G.; Cormack Jr., K.; Williams, J. T.; Martin, R. E. 1979. Dead and down woody material. pp 78-95. In: Thomas, Jack Ward [Technical Editor] 1979. Wildlife Habitats in Managed Forests the Blue Mountains of Oregon and Washington. Agriculture Handbook No. 553. U.S. Department of Agriculture, Forest Service. 512 p. https://www.fs.usda.gov/treesearch/pubs/6630

Scott, Joe H.; Burgan, Robert E. 2005. Standard fire behavior fuel models: a comprehensive set for use with Rothermel's surface fire spread model. Gen. Tech. Rep. RMRS-GTR-153. Fort Collins, CO: U.S. Department of Agriculture, Forest Service, Rocky Mountain Research Station. 72 p. https://doi.org/10.2737/RMRS-GTR-153
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