Ohio Hills Fire and Fire Surrogate Study: vegetation, fuels, and fire behavior

Metadata:
Identification_Information:
Citation:
Citation_Information:
Originator: Hutchinson, Todd F.
Originator: Dickinson, Matthew B.
Publication_Date: 2024
Title:
Ohio Hills Fire and Fire Surrogate Study: vegetation, fuels, and fire behavior
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-2023-0059
Description:
Abstract:
This data publication contains summarized vegetation, fuels, and fire behavior data for the Ohio Hills site of the National Fire and Fire Surrogates Study. This study is in the Southern Unglaciated Allegheny Plateau Section in southeastern Ohio. Treatments at three study sites (blocks) were control (Cont, no active treatment), mechanical partial harvest (Mech), repeated prescribed fires (Fire), and the combination of mechanical partial harvest and repeated prescribed fires (Mech + Fire). For vegetation (overstory, midstory, large tree regeneration, groundlayer), data include pre-treatment values in 2000 as well as post-treatment values in 2017 (groundlayer) and 2021 (overstory, midstory, large tree regeneration). Post-treatment fuels data were collected in 2016. Fire behavior estimates in burn units were averaged across four prescribed fires in 2001, 2005, 2010, and 2016.
Purpose:
The objectives of the national study were to determine the effectiveness of fire and fire surrogate (i.e., mechanical thinning) treatments, alone and in combination, to create more open-structured, resilient, and sustainable conditions, and to reduce fire risk. At Ohio Hills, a primary objective was to reverse the process of mesophication which would be characterized by a suite of changes including reduced dominance of mesophytic trees beneath the canopy, an increase in the abundance of large oak-hickory advance regeneration, fuel beds more conducive to prescribed fire, and a more diverse and productive groundlayer flora. In addition, we sought to examine whether treatments reduced the risk of high-severity fire through fuel reduction.
Supplemental_Information:
For more information about this study and these data, see Hutchinson et al. (in press).
Time_Period_of_Content:
Time_Period_Information:
Range_of_Dates/Times:
Beginning_Date: 2000
Ending_Date: 2021
Currentness_Reference:
Ground condition
Status:
Progress: Complete
Maintenance_and_Update_Frequency: As needed
Spatial_Domain:
Description_of_Geographic_Extent:
We conducted this study in the Southern Unglaciated Allegheny Plateau Section in southeastern Ohio, USA, in three mature forest sites in two counties: REMA (Vinton County, 39.209444, -82.385278), Tar Hollow (Ross County, 39.329722, -82.769722), and Zaleski (Vinton County, 39.356111, -82.366389). Forest composition at all sites is representative of the oak-hickory forest type group.
Bounding_Coordinates:
West_Bounding_Coordinate: -82.77651
East_Bounding_Coordinate: -82.36135
North_Bounding_Coordinate: 39.35870
South_Bounding_Coordinate: 39.19543
Bounding_Altitudes:
Altitude_Minimum: 1000
Altitude_Maximum: 750
Altitude_Distance_Units: feet
Keywords:
Theme:
Theme_Keyword_Thesaurus: ISO 19115 Topic Category
Theme_Keyword: biota
Theme_Keyword: environment
Theme:
Theme_Keyword_Thesaurus: National Research & Development Taxonomy
Theme_Keyword: Ecology, Ecosystems, & Environment
Theme_Keyword: Plant ecology
Theme_Keyword: Fire
Theme_Keyword: Fire ecology
Theme_Keyword: Prescribed fire
Theme_Keyword: Natural Resource Management & Use
Theme_Keyword: Forest management
Theme_Keyword: Restoration
Theme:
Theme_Keyword_Thesaurus: None
Theme_Keyword: forest management
Theme_Keyword: fire behavior
Theme_Keyword: prescribed fire
Theme_Keyword: mesophication
Theme_Keyword: diversity
Theme_Keyword: regeneration
Theme_Keyword: topography
Theme_Keyword: Quercus
Theme_Keyword: fuels
Theme_Keyword: Joint Fire Science Program
Theme_Keyword: JFSP
Place:
Place_Keyword_Thesaurus: None
Place_Keyword: Ohio
Place_Keyword: Vinton Furnace State Forest
Place_Keyword: Zaleski State Forest
Place_Keyword: Tar Hollow State 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: 2023
Title:
Integrated Taxonomic Information System (ITIS)
Geospatial_Data_Presentation_Form: on-line database
Other_Citation_Details:
[December, 7, 2023]; CC0
Online_Linkage: https://www.itis.gov
Online_Linkage: https://doi.org/10.5066/F7KH0KBK
Classification_System_Modifications:
Due to the number of species in this data package, the taxonomic classification information is available separately in two different formats: taxonomy.html and taxonomy.xml.
Taxonomic_Procedures:
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:

Hutchinson, Todd F.; Dickinson, Matthew B. 2024. Ohio Hills Fire and Fire Surrogate Study: vegetation, fuels, and fire behavior. Fort Collins, CO: Forest Service Research Data Archive. https://doi.org/10.2737/RDS-2023-0059
Point_of_Contact:
Contact_Information:
Contact_Organization_Primary:
Contact_Organization: USDA Forest Service, Northern Research Station
Contact_Person: Todd F. Hutchinson
Contact_Position: Research Ecologist
Contact_Address:
Address_Type: mailing and physical
Address: Forestry Sciences Laboratory, 359 Main Road
City: Delaware
State_or_Province: OH
Postal_Code: 43015
Country: USA
Contact_Voice_Telephone: 740-368-0064
Contact_Electronic_Mail_Address: todd.hutchinson@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 provided by Joint Fire Science Program (JFSP Grant 99-S-1 and JFSP Project 15-1-07-20): https://www.firescience.gov. Support also provided by USDA Forest Service, Northern Research Station.


Author Information:

Todd F. Hutchinson
USDA Forest Service, Northern Research Station
https://orcid.org/0000-0002-5872-8657

Matthew B. Dickinson
USDA Forest Service, Northern Research Station
https://orcid.org/0000-0003-3635-1219
Cross_Reference:
Citation_Information:
Originator: Hutchinson, Todd F.
Originator: Adams, Bryce T.
Originator: Dickinson, Matthew B.
Originator: Heckle, Maryjane
Originator: Royo, Alejandro A.
Originator: Thomas-Van Gundy, Melissa
Publication_Date: unknown
Title:
Sustaining eastern oak forests: synergistic effects of fire and topography on vegetation and fuels
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Ecological Applications
Other_Citation_Details:
[In press]
Cross_Reference:
Citation_Information:
Originator: Hutchinson, Todd F.
Originator: Dickinson, Matthew B.
Originator: Rebbeck, Joanne
Publication_Date: 2021
Title:
Feedbacks between fuels, fire behavior, and vegetation: fire severity alters successional pathways during oak forest restoration
Geospatial_Data_Presentation_Form: document
Series_Information:
Series_Name: JFSP Final Report
Issue_Identification: JFSP PROJECT ID: 15-1-07-20
Other_Citation_Details:
(also available in data publication download: \Supplements\15-1-07-20_JFSP_final_report.pdf)
Online_Linkage: https://www.firescience.gov/projects/15-1-07-20/project/15-1-07-20_final_report.pdf
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Data_Quality_Information:
Attribute_Accuracy:
Attribute_Accuracy_Report:
To the best of our knowledge, the values are true and accurate. The gridpoints, permanent plots, subplots, and individual trees (≥10 centimeters [cm] diameter at breast height [DBH]) were well-monumented and visited periodically throughout the study. All field data were collected by well-trained field staff with excellent tree and plant identification skills, as well as being trained in measuring fuels. For the diverse groundlayer flora, when species ID was not possible, taxa were recorded to the genus level or as a morphotype. For ocular estimates of percent cover, 1% and 5% disks were used to improve accuracy of estimates into cover class categories. The field measurements of DBH and height for trees used standard equipment and to the best of our knowledge are accurate. When data entry was complete, we checked for potential errors by sorting on maximum and minimum values. For values that were outliers, the original data sheets were checked to confirm these values had been recorded in the field and in some cases the field plots were revisited to confirm the entered values.

There are cases where the consumed variables in the fuels data file are negative and there are a variety of sources of this error. First, there is a lot of variability in fuels and pre- and post-fire measurements are offset for duff and litter depths to avoid measurement at a previously disturbed location. The offset, where fuel consumption is minimal, can result in apparent increases in fuel loads after fire. Similarly, for downed woody fuels, transect tapes may be inadvertently shifted by small amounts, affecting the results. Large additions of downed woody fuels are likely standing material that was weakened by the fire and fell across transects to be counted in the post-fire inventory. In addition, there is observer error when different people are doing measurements pre- and post-fire. The large quantity of negative values indicates that the sample at each gridpoint was not really adequate. The results at the unit scale are better, having smoothed out the error.
Logical_Consistency_Report:
The data are logically consistent. The consistency was verified as part of the quality assurance that occurred during data analysis.
Completeness_Report:
A blank cell is used in the OHIO_HILLS_FFS_Fuels_Data_2016.csv file to denote data that were not applicable; data on fuels consumed do not apply to sites that were not burned.
Lineage:
Methodology:
Methodology_Type: Field
Methodolgy_Identifier:
Methodolgy_Keyword_Thesaurus:
None
Methodology_Keyword: field-based sampling of vegetation
Methodology_Keyword: fuels
Methodology_Keyword: fire behavior at plots and gridpoints
Methodology_Description:
STUDY SITES

The Ohio Hills installation of the Fire and Fire Surrogate (FFS) study was established in 2000. Three study sites were identified: REMA (located in Vinton Furnace State Forest, Vinton County), Zaleski State Forest (Vinton County), and Tar Hollow State Forest (Ross County). The sites are located within the Southern Unglaciated Allegheny Plateau Section. Topography is dissected, featuring narrow ridges and ravines with steep side slopes. The Tar Hollow site had on average greater soil moisture (Integrated Moisture Index, see Iverson et al. 1997), as well as higher soil fertility (greater total Nitrogen, N-cycling rates, and Calcium [Ca] concentration; Boerner et al. 2007). Detailed site descriptions can be found in Boerner et al. (2007) and Hutchinson et al. (2008).


EXPERIMENTAL DESIGN AND TREATMENTS

The design was a randomized complete block, where each 80 - 100 hectare (ha) study site (i.e., replicate block) was divided into four 20 - 25 ha treatment units. Treatments were mechanical partial harvest (Mech), prescribed fire (Fire), their combination (Mech + Fire), and an untreated control (Cont). Treatments were initiated in the winter of 2000-2001. First, a commercial partial harvest was conducted on all Mech and Mech + Fire units, reducing basal area by an average of 30% (herbicide was not applied to cut stumps). Cutting was focused on trees in midstory and lower canopy strata 15 - 35 cm DBH but larger overstory trees were removed to meet residual basal area targets when necessary. Smaller trees and saplings were not cut. Following mechanical treatments, a total of four (March - April) fires were applied to the Fire and Mech + Fire units over the course of the study. The first fires were in 2001 and were generally low to moderate intensity (flame lengths less than 1 meter [m]). The second fires in 2005, conducted under drier conditions, ranged from low to high-intensity, and significant overstory mortality occurred in patches up to 5 ha in size on some dry south-facing slopes. The third (2010) and fourth (2016) fires also had some areas of high-intensity fire that led to additional mortality (see Table S1 in Hutchinson et al. [in press] for fire weather and fuel moisture conditions in 2016). Most fires were hand-ignited but several also used helicopters for interior ignition. In general, most of the landscape was burned with strip headfires. However, the size of the strips varied considerably, from approximately 10 m near fire lines to approximately 100 m on some interior hillslopes. This wide range of sizes, in addition to variable fire weather and fuel moisture conditions, caused variable fire intensities, including patches of high-severity fire on some upper south-facing slopes.


DATA COLLECTION - VEGETATION

We collected pre-treatment vegetation data in 2000 (hereafter year 0), and post-treatment data collection occurred periodically until year 21, but Hutchinson et al. (in press) only compares year 0 to the final post-treatment measurement. A 50-m sampling grid was distributed throughout each unit to facilitate data collection. Using the grid, a total of 10 0.1-ha (50 x 20 m) plots (n = 120 overall) were established within each unit. Plots were distributed to capture a range of moisture conditions, estimated by the Integrated Moisture Index (IMI). In year 0, we tagged and measured DBH for all live and standing dead trees ≥10 cm DBH within each 0.1-ha plot, and we monitored mortal status and DBH during each subsequent sample. Ten 10 x 10-m subplots were nested within each plot, and stems ≥1.4 m height to 9.9 cm DBH were counted by species in three of the subplots; for multi-stemmed clumps of resprouts, each stem >1.4 m tall was counted. Stems 50 - 139.9 cm tall were tallied in 20 1-m² microplots; here, multi-stemmed clumps were counted as a single stem (rootstock). In year 21, sampling of stems 50 - 139.9 cm height was expanded to include four additional 2-m radius (12.6 m²) microplots due to many plots (primarily controls) have zero stems for one or more species group. Ground-layer vegetation, the cover of vascular plants (woody and herbaceous) by species, was recorded in 12 of the microplots; here the final measurement was in year 17. Foliar cover from the ground to 1 m height was estimated by species in the following cover (%) classes: less than 1, 1, 2 - 5, 6 - 10 , 11 - 25 , 26 - 50 , 51 - 75 , and 76 - 100. Some taxa were recorded to the genus or family level.


DATA COLLECTION - FUELS

Fuels data were collected in year 16 and from 36 grid points in each unit (total n = 432). We sampled pre- and post-fire duff, litter, and 1 - 1000-hour (hr) woody fuels along modified Brown’s lines and coarse woody material (CWM) within belt transects, following Graham and McCarthy’s (2006) methods. At each gridpoint, two 20 m Brown’s lines were anchored 2 m from the gridpoint, and a single belt transect (80 m2; 20 x 4 m) was centered on one of the lines. The pre- and post-fire samples on fire units were collected February - March and April - May, respectively (CWM was not measured post-fire), while non-fire units were sampled in May - June. Duff and litter depth measurements were recorded at 5, 10, and 15 m along each line. We defined duff as the humic layer (Oa - organic matter of unidentifiable origin) and litter as the combined unconsolidated (Oi) and fermentation (Oe) layers, though some studies define the duff as including the Oe layer (e.g., Arthur et al. 2017). Finally, for coarse woody debris (CWD), the species, diameter at the large end (>15 cm), diameter at the small end (>7.6 cm), length (length >1.0 m), and decay class I-V were recorded for each log or section of log that fell within the transect (i.e., diameters and length were of the portion of the log within the transect).


DATA COLLECTION - FIRE BEHAVIOR

Fire behavior (consumption, reaction intensity) was estimated for Fire and Mech + Fire units across all four prescribed fires over the 20-year study period. To estimate fire behavior, five stainless-steel thermocouple probes (TCPs; Onset Computer Corp., Bourne Massachusetts) were placed 20 cm above the mineral soil in each 0.1-ha plot, one on each plot corner and one at plot center. The TCPs were connected to HOBO® type K thermocouple loggers (Onset Computer Corp., Bourne Massachusetts), which recorded temperature at 1 second intervals; see Bova and Dickinson (2008) for more details. Fuel consumption (megagrams [Mg] per ha) is estimated from the time-integral temperatures and a calibration constant. Residence time was estimated from the cumulative time over which the TCPs absolute rate of temperature change was >2°Celsius (°C) per second. Reaction intensity (kilowatts/m²) is estimated from the ratio of consumption (kilograms/m²) and residence time and describes an aerial rate of fuel consumption within the flaming front. Fireline intensity was estimated but not analyzed because of error associated with the initial heating rate of the TCPs.


For more details, see Hutchinson et al (in press).
Methodology_Citation:
Citation_Information:
Originator: Arthur, Mary A.
Originator: Blankenship, Beth A.
Originator: Schörgendorfer, Angela
Originator: Alexander, Heather D.
Publication_Date: 2017
Title:
Alterations to the fuel bed after single and repeated prescribed fires in an Appalachian hardwood forest
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Forest Ecology and Management
Issue_Identification: 403: 126-136
Online_Linkage: https://doi.org/10.1016/j.foreco.2017.08.011
Methodology_Citation:
Citation_Information:
Originator: Boerner, Ralph E.J.
Originator: Brinkman, Jennifer A.
Originator: Yaussy, Daniel A.
Publication_Date: 2007
Title:
Ecosystem restoration treatments affect soil physical and chemical properties in Appalachian mixed oak forests
Geospatial_Data_Presentation_Form: conference proceedings
Other_Citation_Details:
pages 107-115
Online_Linkage: https://www.fs.usda.gov/research/treesearch/27769
Larger_Work_Citation:
Citation_Information:
Originator: Buckley, David S. (ed.)
Originator: Clatterbuck, Wayne K. (ed.)
Publication_Date: 2007
Title:
Proceedings, 15th central hardwood forest conference
Geospatial_Data_Presentation_Form: conference proceedings
Series_Information:
Series_Name: General Technical Report
Issue_Identification: SRS 101
Publication_Information:
Publication_Place: Asheville, NC
Publisher: U.S. Department of Agriculture, Forest Service, Southern Research Station
Other_Citation_Details:
770 p.
Online_Linkage: https://www.fs.usda.gov/research/treesearch/27398
Methodology_Citation:
Citation_Information:
Originator: Bova, Anthony S.
Originator: Dickinson, Matthew B.
Publication_Date: 2008
Title:
Beyond “fire temperatures”: calibrating thermocouple probes and modeling their response to surface fires in hardwood fuels
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Canadian Journal of Forest Research
Issue_Identification: 38: 1008-1020
Online_Linkage: https://doi.org/10.1139/X07-204
Online_Linkage: https://www.fs.usda.gov/research/treesearch/15917
Methodology_Citation:
Citation_Information:
Originator: Hutchinson, Todd F.
Originator: Long, Robert P.
Originator: Ford, Robert D.
Originator: Sutherland, Elaine K.
Publication_Date: 2008
Title:
Fire history and the establishment of oaks and maples in second-growth forests
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Canadian Journal of Forest Research
Issue_Identification: 38: 1184-1198
Online_Linkage: https://doi.org/10.1139/X07-216
Online_Linkage: https://www.fs.usda.gov/research/treesearch/19027
Methodology_Citation:
Citation_Information:
Originator: Graham, John B.
Originator: McCarthy, Brian C.
Publication_Date: 2006
Title:
Forest floor fuel dynamics in mixed-oak forests of south-eastern Ohio
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: International Journal of Wildland Fire
Issue_Identification: 15: 479-488
Online_Linkage: https://doi.org/10.1071/WF05108
Methodology_Citation:
Citation_Information:
Originator: Iverson, Louis R.
Originator: Dale, Martin E.
Originator: cott, Charles T.
Originator: rasad Anantha
Publication_Date: 1997
Title:
A GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (USA)
Geospatial_Data_Presentation_Form: journal article
Series_Information:
Series_Name: Landscape Ecology
Issue_Identification: 12(5): 331-348
Online_Linkage: https://doi.org/10.1023/A:1007989813501
Online_Linkage: https://www.fs.usda.gov/research/treesearch/21908
Process_Step:
Process_Description:
DATA PREPARATION

A total of 13 vegetation variables were prepared for analysis. In this study we focus on approximately 20-year vegetation change, as the difference between pre-treatment (year 0) and the most recent post-treatment measurement (i.e., years 17 or 21). For each plot, we calculated tree basal area (m²/ha) and stand-density (number per ha) for stems ≥10 cm DBH. We assigned species to three groups, oak-hickory, mesophytes, and other species. We also calculated the density of midstory mesophytes (10 - 25 cm DBH). Species in the mesophyte group are considered the main competitors of the target oak-hickory species. Next, we calculated densities of saplings (3 - 9.9 cm DBH) and large regeneration (50 cm in height - 2.9 cm DBH) for each species group using the subplot and microplot measurements. For the ground-layer vegetation, we calculated the mean cover (%) using cover class midpoints and richness m-2 of herbaceous and woody species per plot.

A total of 10 fuels variables were prepared for analysis. Litter loadings were calculated from calibration equations developed from depth and loading samples collected at the control units. Using data from all control units, the least-squares regression equation was used where loading (kg/m²) = 0.1162*depth (cm). For duff, the regression for loading was from Dickinson et al. (2016). Brown’s (1974) equation was used to calculate woody loadings by time-lag class. Transect slope and particle tilt angles (a), piece diameters (d2), and specific gravities (s) from Riccardi (2005) were used in Brown’s equation. For 1000-hr and larger woody fuels (>76 millimeter [mm] diameter), specific gravities were assigned to rotten (0.48 grams [g]/m³) and sound (0.63 g/cm³) particles based on Riccardi’s (2005) measurements. For CWD, wood volume (m³/ha) was estimated from Smalian’s formula (Wenger 1984). Specific gravity (g/cm³) values for each species and decay class were taken from Hoadley (1990) and from Adams and Owens (2001) and used to calculate CWD loading (Mg/ha) from wood volume (Van Wagner 1968). Total fuel, woody fuel (sum 1 - 1000-hr), and litter-to-10-hr fuel (sum litter - 10-hr) were also calculated and considered for analysis. CWD loading (Mg/ha) was estimated from the product of log volume per unit area and wood specific gravity. Following Brown (1974), specific gravity is a weighted average for each decay class based on proportions of each species in the 2016 sample and values from Adams and Owens (2001). For fire behavior, the average (across the four fires in years 1, 5, 10, and 16) consumption (W, Mg/ha) and reaction intensity (Qi, kW/m²) was estimated through TCP responses over the four prescribed fires (Bova and Dickinson 2008).

The GIS-derived Integrated Moisture Index (IMI; Iverson et al. 1997) was used to capture varying topography and soils influences on vegetation, fuels, and fire behavior. The IMI model was a 7.5-m raster with cell values scaled from 0 (generally representing dry, poor site quality) to 100 (moist, high site quality) and IMI values were extracted for each plot and gridpoint for use in the statistical analyses. The IMI can be applied in similar landscapes with dissected topography and relatively uniform bedrock geology (Peters et al. 2013).


Adams, M.B.; Owens, D.R. 2001. Specific gravity of coarse woody debris for some central Appalachian hardwood forest species. Res. Pap. NE-716. Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northeastern Research Station. 4 p. https://doi.org/10.2737/NE-RP-716

Bova, Anthony S.; Dickinson, Matthew B. 2008. Beyond “fire temperatures”: calibrating thermocouple probes and modeling their response to surface fires in hardwood fuels. Canadian Journal of Forest Research 38(5): 1008-1020. https://doi.org/10.1139/X07-204 and https://www.fs.usda.gov/research/treesearch/15917

Brown, James K. 1974. Handbook for inventorying downed woody material. Gen. Tech. Rep. INT-16. Ogden, UT: U.S. Department of Agriculture, Forest Service, Intermountain Forest and Range Experiment Station. 24 p. https://www.fs.usda.gov/research/treesearch/28647

Dickinson, M. B., T. F. Hutchinson, M. Dietenberger, F. Matt, and M. P. Peters. 2016. Litter species composition and topographic effects on fuels and modeled fire behavior in an oak-hickory forest in the eastern USA. PloS One 11:e0159997.

Dickinson, Matthew B.; Hutchinson, Todd F.; Dietenberger, Mark; Matt, Frederick; Peters, Matthew P.; Yang, Jian. 2016. Litter species composition and topographic effects on fuels and modeled fire behavior in an Oak-Hickory Forest in the Eastern USA. PLOS ONE. 11(8). 30 pp. https://doi.org/10.1371/journal.pone.0159997 and https://www.fs.usda.gov/research/treesearch/52394

Hoadley, R. Bruce. 1990. Identifying wood: accurate results with simple tools. Taunton Press.

Iverson, Louis R.; Dale, Martin E.; Scott, Charles T.; Prasad Anantha. 1997. A GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (USA). Landscape Ecology. 12(5): 331-348. https://doi.org/10.1023/A:1007989813501 and https://www.fs.usda.gov/research/treesearch/21908

Peters, Matthew P.; Iverson, Louis R.; Matthews, Stephen N.; Prasad, Anantha M. 2013. Wildfire hazard mapping: exploring site conditions in eastern US wildland–urban interfaces. International Journal of Wildland Fire. 22(5): 567-578. https://doi.org/10.1071/wf12177

Riccardi, Cynthia L. 2005. The effect of prescribed fire on fuel loads, seed germination, and acorn weevils (coleoptera: Curculionidae) in mixed-oak forests of central Appalachia. PhD dissertation. Ohio University, Athens, OH.

Van Wagner, C.E. 1968. The line intersect method in forest fuel sampling. Forest Science. 14(1): 20-26.

Wenger, K.F. 1984. Forestry handbook. John Wiley & Sons.
Process_Date: 2023
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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
Sample unit = Sample unit
Area or distance sampled = Area of sample area or length of transect


DATA FILES (5)

1. \Data\OHIO_HILLS_FFS_Behavior_Data.csv: CSV file containing plot-level fuel consumption and reaction intensity data averaged across multiple years (2001, 2005, 2010, 2016).

Columns include:

PLOT = Field plot name

SITE = Study site: R=REMA, T=Tar Hollow, Z=Zaleski

TRT = Treatment: C=Control, M=Mechanical, F=Fire, MF=Mechanical + fire

GP = Gridpoint number

PLOT IMI = Integrated Moisture Index of plot (See Iverson et al. 1997) (index values, precision 0.01)

W_kgm2 = Mean Consumption (years 2001, 2005, 2010, 2016 averaged), calculated (see methods) from 5 thermocouple probes per plot (F and MF treatments only) (kilograms per square meter [kg/m²], precision 0.0001). Estimated from the time-integral temperatures and a calibration constant.

Qi_KJm2 = Mean Reaction Intensity (years 2001, 2005, 2010, 2016 averaged), calculated (see methods) from 5 thermocouple probes per plot (F and MF treatments only) (kilojoules per square meter [KJ/m²], precision 0.0001). Estimated from the cumulative time over which the thermocouple probe’s absolute rate of temperature change was >2°Celsius (°C) per second.


2. \Data\OHIO_HILLS_FFS_Fuels_Data_2016.csv: CSV file containing post-treatment presence and consumption of fuels data collected in 2016.

Columns include:

SITE = Study site: R=REMA, T=Tar Hollow, Z=Zaleski

TRT = Treatment: C=Control, M=Mechanical, F=Fire, MF=Mechanical + fire

GP = Gridpoint number

IMI = Integrated Moisture Index (See Iverson et al. 1997) (index values, precision 0.01)

YEAR = Calendar year = 2016

LITTER = Mean litter (L + F layers) mass (megagrams per hectare [Mg/ha], precision 0.001); estimated from three depth measurements taken along three modified 20 meter Brown’s transect lines per gridpoint (see methods)

DUFF = Mean duff (H layer; humic layer of unidentifiable origin) mass (Mg/ha, precision 0.001); estimated from three depth measurements taken along three modified 20 meter Brown’s transect lines per gridpoint (see methods)

W1HR = Estimated mean 1 hour (hr) time lag woody (0-6 millimeter [mm] diameter) mass (Mg/ha, precision 0.001) from counts sampled along 2 meters of 3 modified 20 meter Brown’s transect lines per gridpoint (see methods)

W10HR = Estimated mean 10 hr time lag woody (6-25 mm diameter) mass (Mg/ha, precision 0.001) from counts along 2 meters of 3 modified 20 meter Brown’s transect lines per gridpoint (see methods)

W100HR = Estimated mean 100 hr time lag woody (25-75 mm diameter) mass (Mg/ha, precision 0.001) from counts along 4 meters of 3 modified 20 meter Brown’s transect lines per gridpoint (see methods)

W1000HR_R = Mean 1000 hr time lag rotten woody (>7.65 centimeter [cm] diameter) mass (Mg/ha, precision 0.001); estimated from counts along the entire length of 3 modified 20 meter Brown’s transect lines per gridpoint (see methods)

W1000HR_S = Mean 1000 hr time lag sound woody (>7.65 cm diameter) mass (Mg/ha, precision 0.001); estimated from counts along the entire length of 3 modified 20 meter Brown’s transect lines per gridpoint (see methods)

CWM = Estimated coarse woody material (>1 meter length, large end diameter >15 cm, small end diameter >7.6 cm) from large end and small end diameters and length (Mg/ha, precision 0.001) in one 80 m² belt transect per gridpoint. (NOTE: There is one outlier left in these data that was not included in the analysis. See the NOTES column for more details.)

FuelTo10HR = Sum of estimated mean mass for litter, duff, 1-hr timelag woody, and 10-hr timelag woody fuels (Mg/ha, precision 0.001); collected along 3 20-meter long modified Brown’s transects per gridpoint.

TotalFuel = Sum of estimated mean mass for litter, duff, 1-hr timelag woody, 10-hr timelag woody, 100-hr timelag woody, and 1000-hr timelag woodfuels (Mg/ha, precision 0.001); collected along 3 20-meter long modified Brown’s transects per gridpoint.

LITTER_Consumed = Mean of preburn-postburn for the litter layer (L-unconsolidated and F-fermentation layers combined); F and MF treatments only (Mg/ha, precision 0.001)

DUFF_Consumed = Mean of preburn-postburn for the duff layer (Humic layer of unidentifiable origin); F and MF treatments only (Mg/ha, precision 0.001)

W1HR_Consumed = Mean of preburn-postburn for 1-hr time lag woody fuels 0-6 mm diameter; F and MF treatments only (Mg/ha, precision 0.001)

W10HR_Consumed = Mean of preburn-postburn for 10-hr time lag woody fuels 6-25 mm diameter; F and MF treatments only (Mg/ha, precision 0.001)

W100HR_Consumed = Mean of preburn-postburn for 100-hr time lag woody fuels 25-75 mm diameter; F and MF treatments only (Mg/ha, precision 0.001)

W1000HR_S_Consumed = Mean of preburn-postburn for 1000-hr time lag sound woody fuels >7.65 cm diameter; F and MF treatments only (Mg/ha, precision 0.001)

W1000HR_R_Consumed = Mean of preburn-postburn for 1000-hr time lag rotten woody fuels >7.65 cm diameter; F and MF treatments only (Mg/ha, precision 0.001)

TotalConsumed = Mean of preburn-postburn (F and MF treatments only), total fuels litter, duff, 1 hr, 10 hr, 100 hr and 1000 hr (Mg/ha, precision 0.001)

ConsumedTo10HR = Mean of preburn-postburn (F and MF treatments only), for litter, duff, 1 hr and 10-hr (Mg/ha, precision 0.001)

NOTES = There is one large CWM measurement left in the data, that was removed from the analysis. This field provided information regarding this value.


3. \Data\OHIO_HILLS_FFS_Groundlayer_Species_Freq_Cov.csv: CSV file containing the frequency and cover of vascular plant taxa by plot both pre-treatment (2000) and post-treatment (2017).

Columns include:

PLOT = Field plot name

SITE = Study site: R=REMA, T=Tar Hollow, Z=Zaleski

TRT = Treatment: C=Control, M=Mechanical, F=Fire, MF=Mechanical + fire

YEAR = Calendar year = 2000 (pre-treatment), 2017 (post-treatment)

Genus_species = Genus and species or morphotype (some taxa to Genus only)

CODE = Species code in USDA Plants database (or added if not in database - morphotypes and unknowns)

PLANTS_DB = Is species in USDA PLANTS Database (USDA, NRCS 2023): Y=yes in USDA Plants database; N=not in USDA Plants database (morphotypes and unknowns)

LF1 = Life form 1: H=herbaceous, W=woody

LF2 = Life form 2: FB=forb, FN=fern, GR=graminoid, SH=shrub, TR=tree, WV=woody vine

FREQ = Frequency of occurrence (count, precision 1)

COVER = Mean percent cover, from cover class midpoints (percent, precision 0.01)


4. \Data\OHIO_HILLS_FFS_Tree_Species_List.csv: CSV file containing a list of tree species in this study and their species group.

Columns include:

PLANTS_SYMBOL = USDA PLANTS Database (USDA, NRCS 2023) symbol

PLANTS_GENUS_SPECIES = Genus and species or morphotype (some taxa to Genus only)

GROUP = Species group: Oak-hickory, Mesophyte, Other


5. \Data\OHIO_HILLS_FFS_Vegetation_Data.csv: CSV file containing vegetation cover and density by species group and forest stratum, both pre-treatment (2000) and post-treatment (2017 or 2021).

Columns include:

PLOT = Field plot name

SITE = Study site: R=REMA, T=Tar Hollow, Z=Zaleski

TRT = Treatment: C=Control, M=Mechanical, F=Fire, MF=Mechanical + fire

IMI = Integrated Moisture Index (See Iverson et al. 1997) (index values, precision 0.01)

BA_00 = Basal area of living trees >=10 cm diameter at breast height (DBH), year 2000 (m²/ha, precision 0.1)

BA_21 = Basal area of living trees >=10 cm DBH, year 2021 (m²/ha, precision 0.1)

BA_CHNG = Basal area change, year 2000 to year 2021 (m²/ha, precision 0.1)

TPH_00 = Density of living trees >=10 cm DBH per ha, year 2000 (trees per ha, precision 1)

TPH_21 = Density of living trees >=10 cm DBH per ha, year 2021 (trees per ha, precision 1)

TPH_CHNG = Living tree density per ha change, year 2000 to year 2021 (trees per ha, precision 1)

MIDMES_00 = Density of midstory mesophyte trees 10 to 25 cm DBH per ha, year 2000 (trees per ha, precision 1)

MIDMES_21 = Number of midstory mesophyte trees 10 to 25 cm DBH per ha, year 2021 (trees per ha, precision 1)

MIDMES_CHNG = Midstory mesophyte density per ha change, year 2000 to year 2021 (trees per ha, precision 1)

SAPMES_00 = Mean density of mesophyte saplings (3.0 to 9.9 cm DBH) per ha, year 2000 (stems per ha, precision 1)

SAPMES_21 = Mean density of mesophyte saplings (3.0 to 9.9 cm DBH) per ha, year 2021 (stems per ha, precision 1)

SAPMES_CHNG = Mean mesophyte sapling density per ha change, year 2000 to year 2021 (stems per ha, precision 1)

SAPOAH_00 = Mean density of oak-hickory saplings (3.0 to 9.9 cm DBH) per ha, year 2000 (stems per ha, precision 1)

SAPOAH_21 = Mean density of oak-hickory saplings (3.0 to 9.9 cm DBH) per ha, year 2021 (stems per ha, precision 1)

SAPOAH_CHNG = Mean oak-hickory sapling density per ha change, year 2000 to year 2021 (stems per ha, precision 1)

SAPOTH_00 = Mean density of other species saplings (3.0 to 9.9 cm DBH) per ha, year 2000 (stems per ha, precision 1)

SAPOTH_21 = Mean density of other species saplings (3.0 to 9.9 cm DBH) per ha, year 2021 (stems per ha, precision 1)

SAPOTH_CHNG = Mean other species sapling density per ha change, year 2000 to year 2021 (stems per ha, precision 1)

LMES_00 = Mean density of mesophyte large regeneration stems (50 cm height to 2.9 cm DBH) per ha, year 2000 (stems per ha, precision 1)

LMES_21 = Mean density of mesophyte large regeneration stems (50 cm height to 2.9 cm DBH) per ha, year 2021 (stems per ha, precision 1)

LMES_CHNG = Mean mesophyte large regeneration density per ha change, year 2000 to 2021 (stems per ha, precision 1)

LOAH_00 = Mean density of oak-hickory large regeneration stems (50 cm height to 2.9 cm DBH) per ha, year 2000 (stems per ha, precision 1)

LOAH_21 = Mean density of oak-hickory large regeneration stems (50 cm height to 2.9 cm DBH) per ha, year 2021 (stems per ha, precision 1)

LOAH_CHNG = Mean oak-hickory large regeneration density per ha change, year 2000 to 2021 (stems per ha, precision 1)

LOTH_00 = Mean density of other species large regeneration stems (50 cm height to 2.9 cm DBH) per ha, year 2000 (stems per ha, precision 1)

LOTH_21 = Mean density of other species large regeneration stems (50 cm height to 2.9 cm DBH) per ha, year 2021 (stems per ha, precision 1)

LOTH_CHNG = Mean other species large regeneration density per ha change, year 2000 to 2021 (stems per ha, precision 1)

HRICH_00 = Mean number of herbaceous taxa per m², year 2000 (taxa per m², precision 0.1)

HRICH_17 = Mean number of herbaceous taxa per m², year 2017 (taxa per m², precision 0.1)

HRICH_CHNG = Mean change in number of herbaceous taxa per m², year 2000 to 2017 (taxa per m², precision 0.1)

WRICH_00 = Mean number of woody taxa per m², year 2000 (taxa per m², precision 0.1)

WRICH_17 = Mean number of woody taxa per m², year 2017 (taxa per m², precision 0.1)

WRICH_CHNG = Mean change in number of woody taxa per m², year 2000 to 2017 (taxa per m², precision 0.1)

HCOV_00 = Mean percent cover of herbaceous plants, year 2000 (percent cover, precision 0.01)

HCOV_17 = Mean percent cover of herbaceous plants, year 2017 (percent cover, precision 0.01)

HCOV_CHNG = Mean change in percent cover of herbaceous plants year 2000 to 2017 (percent cover, precision 0.01)

WCOV_00 = Mean percent cover of woody plants, year 2000 (percent cover, precision 0.01)

WCOV_17 = Mean percent cover of woody plants, year 2017 (percent cover, precision 0.01)

WCOV_CHNG = Mean change in percent cover of woody plants year 2000 to 2017 (percent cover, precision 0.01)



SUPPLEMENTAL FILES (3)

1. \Supplements\15-1-07-20_JFSP_final_report.pdf: Portable Document Format file containing the 2021 JFSP Final Report "Feedbacks between fuels, fire behavior, and vegetation: fire severity alters successional pathways during oak forest restoration" for JFSP PROJECT ID: 15-1-07-20.

2. \Data\taxonomy.html: HTML file containing complete taxonomic classification information for all species measured in this data package, both understory and overstory, obtained from https://www.itis.gov.

3. \Data\taxonomy.xml: XML file containing complete taxonomic classification information for all species measured in this data package, both understory and overstory, obtained from https://www.itis.gov.
Entity_and_Attribute_Detail_Citation:
Hutchinson, Todd F.; Adams, Bryce T.; Dickinson, Matthew B.; Heckel, Maryjane; Royo, Alejandro A.; Thomas-Van Gundy, Melissa. [In press]. Sustaining eastern oak forests: synergistic effects of fire and topography on vegetation and fuels. Ecological Applications.

Iverson, Louis R.; Dale, Martin E.; Scott, Charles T.; Prasad Anantha. 1997. A GIS-derived integrated moisture index to predict forest composition and productivity of Ohio forests (USA). Landscape Ecology. 12(5): 331-348. https://doi.org/10.1023/A:1007989813501 and https://www.fs.usda.gov/research/treesearch/21908

USDA, NRCS. 2023. The PLANTS Database (http://plants.usda.gov, 12/06/2023). National Plant Data Team, Greensboro, NC USA.
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