United States

Department of 

Agriculture

Forest Service

Northern 

Research Station

General Technical

Report NRS-P-46

Proceedings of the 3rd 

Fire in Eastern Oak 

Forests Conference
Visit our homepage at: http://www.nrs.fs.fed.us/

Published by: For additional copies:

U.S. FOREST SERVICE U.S. Forest Service 

11 CAMPUS BLVD SUITE 200 Publications Distribution

NEWTOWN SQUARE PA 19073-3294 359 Main Road

Delaware, OH 43015-8640

June 2009 Fax: (740)368-0152

The findings and conclusions of each article in this publication are those of the individual 

author(s) and do not necessarily represent the views of the U.S. Department of Agriculture 

or the Forest Service. All articles were received in digital format and were edited for uniform 

type and style. Each author is responsible for the accuracy and content of his or her paper.

The use of trade, firm, or corporation names in this publication is for the information and 

convenience of the reader. Such use does not constitute an official endorsement or approval 

by the U.S. Department of Agriculture or the Forest Service of any product or service to the 

exclusion of others that may be suitable. 

Abstract

Contains 10 full-length papers and 12 abstracts of posters that were presented at the 3rd Fire 

in Eastern Oak Forests conference, held in Carbondale, IL, May 20-22, 2008. The conference 

was attended by over 200 people from a variety of groups, including federal and state agencies, 

nongovernmental organizations, universities, and private citizens.

Review Process

Each paper was peer-reviewed by two reviewers. The authors worked with the editor to revise 

their manuscripts, based on the reviewers’ comments. Revised manuscripts were submitted to 

the Northern Research Station for technical editing and publishing. The authors are responsible 

for the accuracy and content of the papers. Reviews were provided by Mary Arthur, Patrick 

Brose, Timothy Carter, Joseph Charney, Steve Croy, Larry Hedrick, Bill Jackson, R. Andrew 

King, Dave Minney, Paul Nelson, David Peterson, Kevin Robertson, Tom Schuler, Stephen 

Shifley, Marty Spetich, and John Waldron.

Acknowledgments

The steering committee thanks Southern Illinois University SIU for hosting the conference. 

Planning and logistical support were provided by the SIU Department of Continuing Education 

(DCE). Jackie Welch, DCE conference coordinator, was extremely helpful; her efforts led 

to a successful conference. We thank the following sponsors for their support: U.S. Forest 

Service, Northeastern Area State and Private Forestry; U.S. Forest Service, Southern Region; 

Illinois Forestry Council, Illinois Society of American Foresters, Southern Illinois University, 

Ohio Division of Forestry, Professional Association of Conservation Resource Managers, 

Southeastern Illinois Regional Planning and Development Commission, U.S. Forest Service, 

Northern Research Station; and U.S. Forest Service, Shawnee National Forest. The Joint Fire 

Sciences Program provided funding for the publication of this proceedings.

Cover Photos

Top: Mixed-oak forest after several prescribed fires; Photo by Robert Long, U.S Forest Service.

Middle: Prescribed fire in mixed-oak forest; Photo by Mike Broecker, used with permission.

Bottom: White oak (Quercus alba) seedling; Photo by Todd Hutchinson, U.S. Forest Service
Proceedings of the 3rd 

Fire in Eastern Oak Forests Conference

May 20-22, 2008

Southern Illinois University, Carbondale, Illinois

Edited by

Todd F. Hutchinson

U.S. Forest Service, Northern Research Station

Steering Committee

Charles Ruffner (Co-chair), Southern Illinois University, Department of Forestry

Todd Hutchinson, (Co-chair), U.S. Forest Service, Northern Research Station

Michael Bowden, Ohio Division of Forestry

Scott Crist, U.S. Forest Service, Shawnee National Forest

Matthew Dickinson, U.S. Forest Service, Northern Research Station

John Groninger, Southern Illinois University, Department of Forestry

Alan Zentz, U.S. Forest Service, Northeastern Area State and Private Forestry

Sponsors

U.S. Forest Service, Northeastern Area State and Private Forestry

U.S. Forest Service, Southern Region

Joint Fire Sciences Program

Illinois Forestry Council

Illinois Society of American Foresters

Southern Illinois University

U.S. Forest Service, Northern Research Station

Shawnee National Forest

Ohio Department of Natural Resources, Division of Forestry

Professional Association of Conservation Resource Managers

Southeastern Illinois Regional Planning and Development Commission
Contents

fire effects on vegetation and wildlife

A Review Of Fire And Oak Regeneration And Overstory Recruitment.....................................2

Daniel C. Dey and Zhaofei Fan

Effects of Overstory Stand Density and Fire on Ground Layer Vegetation in Oak

Woodland and Savanna Habitats...............................................................................................21

John B. Taft

Fire and Fire Surrogate Study: Annotated Highlights from Oak-Dominated Sites ...............40

Daniel A. Yaussy and Thomas A. Waldrop

Fire and the Endangered Indiana Bat........................................................................................51

Matthew B. Dickinson, Michael J. Lacki, and Daniel R. Cox

modeling tools to support fire management and planning

Performance of Fire Behavior Fuel Models Developed for the Rothermel Surface Fire

Spread Model...............................................................................................................................78

Robert Ziel, and W. Matt Jolly

Smoke Modeling in Support of Management of Forest Landscapes in the Eastern

United States................................................................................................................................88

Gary L. Achtemeier

Modeling Fire and Other Disturbance Processes Using Landis...........................................107

Stephen R. Shifley, Jian Yang, and Hong He

fire and forest management

Building a State Prescribed Fire Program: Experiences and Lessons Learned in Ohio.... 118

Michael Bowden

Landscape-Scale Fire Restoration on The Big Piney Ranger District in the Ozark

Highlands of Arkansas..............................................................................................................126

John Andre, McRee Anderson, Douglas Zollner, Marie Melnechuk, and Theo Witsell

Restoring Oak Ecosystems on National Forest System Lands in the Eastern Region: 

an Adaptive Management Approach .......................................................................................133

Gregory Nowacki, Michael Ablutz , Dan Yaussy, Thomas Schuler, and Dan Dey
poster abstracts

Response of Upland Oak and Co-occurring Competitor Seedlings Following Single

and Repeated Prescribed Fires................................................................................................142

Heather D. Alexander, Mary Arthur, David Loftis, and Stephanie Green

First-Year Results of a Prescribed Burn in a High-Elevation Red Oak Stand .....................143

Peter Bates and Dean Simon

Modeling the Protection Afforded by Burrows, Cavities, and Roosts During 

Wildland Surface Fires..............................................................................................................144

Anthony Bova and Matthew Dickinson

Prescribed Fire Research in Pennsylvania.............................................................................145

Patrick Brose

Red Maple (Acer Rubrum) Response to Prescribed Burning on The William B. 

Bankhead National Forest, Alabama .......................................................................................147

Stacy L. Clark and Callie J. Schweitzer

Surface Fire Effects on Conifer and Hardwood Crowns—Applications of an

Integral Plume Model ................................................................................................................148

Matthew Dickinson, Anthony Bova, Kathleen Kavanagh, Antoine Randolph, and Lawrence Band

Fire History and the Establishment of Oaks And Maples in Second-Growth Forests........149

Todd Hutchinson, Robert Long, Robert Ford, and Elaine Kennedy Sutherland

Fire History and Age Structure Analysis in The Sherburne National Wildlife Refuge, 

Minnesota: Establishing Reference Conditions in a Remnant Oak Savanna Woodland ...150

 Kurt F. Kipfmueller and Tim Hepola

Oak Regeneration Across a Heterogeneous Landscape in Ohio: Some Limited 

Success After Thinning, Two Fires, and Seven Years ...........................................................151

Louis Iverson, Todd Hutchinson, Anantha Prasad, and Matthew Peters

Prescribed Fire and Oak Seedling Development in an Appalachian Forest........................152

Jacob Royse, Mary Arthur, and David Loftis

Predicting Fire Scars in Ozark Timber Species Following Prescribed Burning..................153

Aaron P. Stevenson, Richard P. Guyette, Rose-Marie Muzika

Airborne Fire Monitoring—Extraction of Active Fire Fronts from Time-Sequence 

Imaging of The Arch Rock Fire in Southeast Ohio.................................................................154

Loredana Suciu, Anthony S. Bova, Matthew B. Dickinson, Jim Dyer, Robert Kremens, and Valerie L. Young
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 1

fire effects on

vegetation and wildlife
2 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

A REVIEW OF FIRE AND OAK REGENERATION

AND OVERSTORY RECRUITMENT

Daniel C. Dey1 and Zhaofei Fan2

1

Research Forester, U.S. Forest Service, Northern Research Station, Columbia, MO 2

Assistant Professor, Department of Forestry, College of Forest Resources, Mississippi State University

DCD is corresponding author; to contact, call (573) 875-5341 or email at ddey@fs.fed.us

Abstract.—Fire has played a prominent role in the history of oak in eastern North America, and it is useful 

today for promoting oak regeneration where competition with other woody vegetation is a problem and for 

managing savannas and woodlands. We spent the last century extinguishing wildfire from forests for good 

reason, but now we must spend some time relearning how to use fire as a tool for sustaining oak-dominated 

ecosystems. The use of fire to favor oak in forested settings where timber production is a goal is very different 

from its role in managing savannas and woodlands. Fire as a tool originated in wildlife management and 

then found application in savanna and woodland restoration. In the past 30 years, there has been increased 

emphasis on fire in silviculture research and forest management. This paper discusses the use of fire in the 

context of oak ecology and silviculture with emphasis on promoting oak regeneration and dominance. 

Highlights include: (1) fire interactions with acorns and oak seedlings, and advance reproduction; (2) fireinduced changes in stand structure and understory and implications for oak regeneration; (3) fire as part of 

the regeneration prescription; and (4) the role of fire in the process of oak recruitment into the overstory.

The future looks bright

for those unafraid to light,

but who know how to use fire

to get what they desire.

 Dey 2008

we are learning how to use fire to manage oak systems 

that occur over such a large and varied landscape. This 

paper reviews some of what we know about fire and oak 

ecology and silviculture. We discuss how fire may be 

used to favor oak regeneration and recruitment in forests, 

woodlands, and savannas. We review key fire effects on 

oak regeneration from acorn germination to seedling 

establishment and development. Fire in combination 

with thinning and regeneration harvesting is discussed 

in relation to managing stand structure with the goal of 

sustaining oak beginning with the regeneration process. 

Following regeneration, oak trees must be successful in 

competing through stand development to achieve the 

goal of sustaining oak in the mature overstory, a process 

we refer to as “recruitment.” Together, regeneration and 

recruitment of oak are essential to sustain oak forests, 

woodlands, and savannas.

INTRODUCTION

The history of fire in eastern North America has been 

brought to public attention (Pyne 1982, Williams 1989, 

Guyette et al. 2002), and fire’s importance in promoting 

the distribution and dominance of oak species is now 

widely recognized (Abrams 1992). The lack of fire in 

modern times is listed as one of the major contributors 

to the successional replacement of oak by mesophytic 

hardwood species. These competitors are favored by 

increasing forest density and disturbances that create 

small forest openings the size of single to small groups of 

canopy trees (Nowacki and Abrams 2008).

In the East, fire is beginning to be used to (1) favor 

oak regeneration in an attempt to sustain oak forests; 

and (2) restore oak woodlands and savannas. Through 

research and operational use of fire in eastern forests, 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 3

ACORN GERMINATION AND

SEEDLING ESTABLISHMENT

Acorn germination in species of the white oak group 

(Quercus section Quercus) begins in the fall when 

the radicle emerges before the seed goes into winter 

dormancy. White oak germination is completed in the 

spring with development of the epicotyl. In contrast, red 

oak group species (Quercus section Lobatae) have embryo 

dormancy and require a period of cold stratification 

before germination in the spring. Regardless of species, 

acorns must maintain high seed moisture content to 

remain viable. The white oak group species require 

moisture content in excess of 40 percent to maintain 

seed viability (Korstian 1927). Red oak group species 

can tolerate greater seed drying and viability is good 

above 25-percent moisture content. In either case, seed 

desiccation during the winter is a major cause of seed loss 

in many ecosystems (Korstian 1927).

Acorns fall to the ground in autumn just before or during 

leaf drop. The covering of leaves helps maintain seed 

moisture content. In more northern climates, permanent 

winter snowpack creates an excellent environment for 

seed storage and stratification. At the ground-snow 

interface, temperatures and humidity are just right for 

acorns. Contact with, or burial in, mineral soil provides 

further protection against seed drying, and buried acorns 

may be less available to seed predators. Some small 

mammals and birds are key agents of acorn dispersal and 

burial, but along with insects and other wildlife species, 

they also consume much of the annual acorn crop in the 

process. Hence, seedling establishment is greatest in years 

of good to bumper acorn crops, when seed predators are 

overwhelmed with a bountiful seed supply. 

Deep litter (> 2 inches) can be a physical barrier to 

epicotyl emergence from acorns located beneath the 

litter layer. Furthermore, radicles emerging from acorns 

lying on or mixed in thick litter over duff layers may 

be unable to penetrate into mineral soil before they dry 

out and die. Fire that reduces litter and duff layers to 

less than 2 inches thick before the autumn acorn and 

leaf drop favors the establishment of oak seedlings. The 

benefit of a fire removing litter and duff layers lasts for 

several years because it takes that long for these layers to 

reaccumulate. In undisturbed, mature oak-hickory forests 

of the Missouri Ozarks, Stambaugh and others (2006) 

estimated that it takes 4 years following a fire for the 

majority (75 percent) of the litter layer to reaccumulate 

to preburn levels. 

Late autumn and early winter fires that burn after seed 

drop and leaf fall tend to remove the beneficial covering 

offered by the current year’s leaves, thus promoting seed 

desiccation over the winter. In addition, the heat from 

a fire after acorn drop directly kills a high proportion 

of the seed crop. Auchmoody and Smith (1993) 

reported that a cool fall prescribed fire in northwestern 

Pennsylvania killed 40 to 49 percent of the acorns in 

the litter, and the combination of fire and acorn weevils 

lowered germination rates by 20 percent compared to 

unburned acorns. Dey (unpublished data) found that a 

spring surface fire in an Ontario northern red oak-maple 

stand reduced acorn germination capacity from 85 to 16 

percent. Acorns buried in mineral soil are better able to 

survive surface fires because (1) they are insulated from 

the heat of surface fires by soil, which is generally a poor 

heat conductor when soil moisture is at field capacity 

or less; (2) low intensity fires, common in the East, are 

less likely to heat the soil to lethal temperatures; and (3) 

dormant-season fires occur when ambient temperatures 

and seed physiological activity are low. 

Iverson and Hutchinson (2002) and Iverson and others 

(2004) measured soil temperatures during spring surface 

fires in Ohio oak forests and found that the greatest 

maximum temperature observed at one location was 82 

°F at 0.4 inches deep in the soil even though maximum 

air temperatures 4 inches above the ground ranged from 

325 to 600 °F. On average, they found that surface soil 

temperatures during fires reached only 45 to 51 °F, 

depending on fire frequency. These soil temperatures 

were insufficient to cause death to living organisms and 

plant tissue in the soil, including buried acorns and 

tree roots. If a good crop of acorns is on the ground, it 

is best to delay burning until seedlings are established 

and have grown large enough to respond by sprouting 

vigorously after burning. This process may take 3 years 

or more, depending on overstory density (i.e., degree 

of shading) and site quality (Brose 2008). Mechanical 
4 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

scarification may be an alternative to fire for breaking 

up deep litter layers and burying acorns. Both Rathfon 

and others (2008) and Lhotka and Zaczek (2003) found 

that mechanical scarification increased the density of oak 

seedlings that established after seed fall.

SEEDLING DEVELOPMENT

Fire damage to a tree’s cambium, leading to death of the 

shoot or the entire individual, is related to temperature 

and duration of the tree’s exposure to fire’s heat. In 

general, plant tissue dies when it is exposed to ≥ 140 °F 

for 60 seconds (Hare 1965). Longer exposure to lower 

temperatures can also be lethal. Average maximum 

temperatures at or near the ground (i.e., within 10 

inches) during spring (dormant-season) prescribed fires 

in hardwood forests have been recorded from 183 °F 

to 698 °F in the Missouri Ozarks (Dey and Hartman 

2005), Ohio (Iverson et al. 2004, Rebbeck et al. 2004, 

Hutchinson et al. 2005, Phillips et al. 2007) and the 

southern Appalachian Mountains (Elliott and Vose 2005, 

Phillips et al. 2007). Clearly, dormant-season burns are 

capable of causing death or topkill in hardwood and pine 

seedlings.

In trees of any species, bark thickness is a major 

determinant of fire resistance (Hengst and Dawson 

1994). A tree’s fire resistance increases exponentially as 

bark thickness increases, and stem diameter has been 

shown to be significantly correlated to tree survival after 

fire (Loomis 1973, Regelbrugge and Smith 1994, Dey 

and Hartman 2005). Oak seedlings that are less than 

3 years old suffer high mortality (>70 percent) after a 

single low intensity dormant-season fire (Johnson 1974, 

Dey and Parker 1996) in part because of thin bark 

and low root carbohydrate reserves. Further, because 

germination in oak is hypogeal, location of the acorn 

at time of germination, i.e., in the litter or buried in 

soil, determines to a large extent its ability to survive a 

surface fire (Brose and Van Lear 2004). The multitude of 

dormant buds located near the root collar, which give oak 

its great ability to sprout after death of the shoot, are at 

much higher risk of mortality when the acorn germinates 

in the litter than when it germinates an inch or two in 

the soil. Soil protects seedling roots and other tissues 

from lethal temperatures during dormant-season fires in 

Midwestern hardwood forests (Iverson and Hutchinson 

2002, Boerner 2006).

Prescribed fires typical of those conducted in eastern 

North America may cause the death or, more commonly, 

shoot dieback of hardwood stems that are less than 5 

inches in diameter (Reich et al. 1990, Waldrop et al. 

1992, Barnes and Van Lear 1998, Brose and Van Lear 

1998). A single fire is sufficient to kill the shoot in young, 

small-diameter hardwoods (Dey and Hartman 2005). 

Most hardwood species, however, respond to this damage 

by sprouting from surviving root systems, especially 

larger advance reproduction in the seedling and sapling 

size classes (Fig. 1). Only new and recent germinants 

are significantly more subject to complete mortality 

following low intensity fires regardless of species. 

Seedlings growing slowly in the dense shade of mature 

forest (typical on high quality, mesic sites) are vulnerable 

to fire mortality for a much longer duration than those 

growing rapidly in more open environments, where they 

reach fire-resistant sizes sooner. Factors other than tree 

size also play an important role in determining whether 

mortality occurs; for instance, fire intensity, seasonality, 

and frequency; and plant physiological activity (Whelan 

1995, Debano et al. 1998, Dey 2002).

A tree’s ability to sprout after the death or removal of 

the shoot increases exponentially with increasing stem 

diameter up to a threshold diameter, which varies by 

species (Fig. 1) (Dey 1991). As tree size increases beyond 

the threshold diameter, sprouting capacity declines 

(Fig. 2) (Dey et al. 1996a). Declines in sprouting capacity 

in larger and older trees are probably a function of (1) 

increased mechanical resistance to bud emergence as bark 

thickness increases; and (2) physiological senescence in 

mature and over-mature trees.

For similarly sized trees, mortality after a single fire varies 

by species, and oak and hickory species are more likely 

to survive than many of their common competitors, such 

as sugar maple (Acer saccharum Marsh.), red maple (Acer 

rubrum L.), black birch (Betula lenta L.), and yellowpoplar (Liriodendron tulipifera L.) (Kruger and Reich 

1997, Brose and Van Lear 1998). Dey (2002) and Brose 

and others (2006) classified common eastern species 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 5

2 

Figure 1.—The probability of advance reproduction’s being alive one growing season 

after a spring (March-April) prescribed burn on The Nature Conservancy’s Chilton 

Creek, MO, property (from Dey and Hartman 2005). Most stems were topkilled by 

the fire but produced multiple sprouts.

Initial stump diameter (inches)

0 10 20 30 40

Probability

0.0

0.2

0.4

0.6

0.8

1.0

White oak

Black oak

Scarlet oak

Post oak

Blackjack oak

1 

Figure 2.—Estimated probability of 

having a live stump sprout 5 years after 

clearcutting, based on initial stump 

diameter for common oak species in the 

Missouri Ozarks (from Dey et al. 1996).
6 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

[1 

2 

3

Figure 3.—Probability of advance reproduction’s being alive either 4 years after 

one burn, 2 years after three burns, or 1 year after four annual burns in mature 

fully stocked Missouri Ozark forests (averaging 78 ft2

/ac basal area and 69 percent 

stocking) subjected to multiple spring prescribed fires (from Dey and Hartman 2005). 

Basal diameter of advance reproduction ranged from 0.1 to 6 inches for seedlings 

and saplings (up to 50 feet tall) before any burning.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 7

by their ability to survive as adults or persist through 

basal stem and root sprouting in a disturbance regime 

of frequent fires (Table 1). Differences in mortality 

among species are more significant in the small seedling 

size classes and are related to ability to regenerate after 

frequent fire damage. Species differ in morphological and 

physiological adaptations that protect them from high 

temperatures during fires, or allow them to regenerate 

after suffering damage. The type and location of their 

reproductive structures (dormant buds) and seeds 

(chemical and thermal seed dormancy and longevity 

in the forest floor seedbank) determines whether they 

individually or as a species will survive and persist after 

fire. Capacity to produce biomass and allocation of 

carbon within the plant make some species’ strategies 

more competitive than others in a regime of frequent fire. 

Oaks are survivalists in a world of fire.

One fire seldom causes long-term shifts in species 

composition (McGee 1979, Wendell and Smith 1986, 

Van Lear 1991, Van Lear and Waldrop 1991). Only 

after repeated fires (i.e., annual to every 5 years), 

whether applied before or after regeneration harvesting, 

do tree species begin dropping out of mature forest 

understories, or young stands. Oak reproduction is 

better adapted than many of its woody competitors 

because it has numerous dormant buds near the root 

collar, which is often located buried in the soil, protected 

from most surface fires. In addition, oak seedlings 

preferentially allocate carbon to the root system, even 

at the expense of shoot growth (Kolb and Steiner 1990, 

Walters et al. 1993). With sufficient light, oak advance 

reproduction is able to build a large root system with 

high carbohydrate reserves that supports rapid shoot 

growth following disturbances causing shoot dieback. 

This survival strategy is advantageous in environments 

that are subjected to drought, herbivores that feed on 

hardwoods, or fire that destroys the shoot. Where large 

oak advance reproduction accumulate through natural 

disturbances in “intrinsic oak accumulator systems,” i.e., 

Table 1.—Classification of relative ability to survive intact or persist through vegetative reproduction in a disturbance 

regime of frequent fires for common eastern tree species (from Dey [2002] and Brose et al. [2005]). (* species that are 

fire-sensitive when young but have greater ability to survive when mature; ** species that are fire-sensitive as older, 

larger individuals, but are prolific stump or root sprouters).

Very sensitive Sensitive Intermediate Resistant Very resistant

Balsam fir American holly American beech ** Aspen *, ** Bear oak

Eastern redcedar American Basswood Cherrybark oak Black locust ** Blackjack oak *

Hemlock * American beech ** Blackgum Black oak Bluejack oak

Northern white cedar Aspen *, ** Blackjack oak * Bur oak Dwarf chinkapin oak

Red pine * Black cherry Nuttall oak Chestnut oak Longleaf pine

Virginia pine Black walnut Overcup oak Chinkapin oak Post oak

White pine * Cottonwood * Pin oak Cottonwood * Slash pine

White spruce Elm Pin cherry Hickory Turkey oak

Yellow-poplar * Flowering dogwood Red maple ** Northern pin oak

Ironwood Scarlet oak Northern red oak

Laurel oak Southern red oak Red pine *

Magnolia Swamp chestnut oak Sassafras **

Red maple ** Swamp white oak Shortleaf pine

Sassafras ** Southern red oak White oak

Silver maple Swamp chestnut oak White pine *

Striped maple Swamp white oak Yellow-poplar *

Sugar maple

Sweet birch

Sweetgum

Sycamore

Water oak

White ash

Willow oak
8 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

xeric oak forest (Johnson et al. 2002), they often occur 

in sufficient numbers to sustain oak dominance. In these 

forests, frequent fire often benefits oak preferentially by 

improving its competitive status in the regeneration layer 

(Brose et al. 2006) in part because oak seedlings are large 

enough to recover from intermittent fire and benefit from 

the temporary reduction in competition. In “recalcitrant 

oak accumulator systems,” i.e., mesic and hydric forests, 

oak advance reproduction is unable to persist in the 

understory and has low capacity to replace the oak in 

the parent stand. In these forests, small oak seedlings are 

periodically numerous following a good acorn crop, but 

shear numbers of small oak reproduction are not enough 

to ensure success in oak regeneration. Young and small 

oak advance reproduction have low competitive capacity 

to regenerate and sustain oak, and they are vulnerable to 

mortality following intense or frequent fires. 

Although frequent fires and high intensity fires may 

reduce the density of oak seedlings and saplings, oak’s 

relative competiveness is often enhanced by burning 

because fire’s effect on other species is more severe (Brose 

et al. 2006). The Santee Fire Study in South Carolina 

(Waldrop et al. 1992) nicely illustrates the tenacity of 

oaks as they outlasted their competitors after 43 years of 

frequent burning in summer or winter. In Coastal Plain 

loblolly pine (Pinus taeda L.) forests, it took up to 20 

years of annual summer burning to practically eliminate 

hardwood advance reproduction in the 0- to 1-inch 

diameter at breast height (d.b.h.) class, and oaks were 

one of the last species groups to drop out. All woody 

vegetation less than 4.5 feet tall had been eliminated 

after 43 years of annual summer burning in these forests, 

but density of woody species was still high (e.g., 8,000 

to 15,000 stems per acre for all species) under periodic 

or biennial summer or winter burning, and annual 

winter burning. Allowing 2 to 7 years between fires 

permitted the hardwood sprouts to continue building 

root biomass and increase in vigor, especially for the oak 

species growing under a mixed pine-hardwood overstory. 

Even with annual winter burning, oak sprouts had an 

entire growing season to recover from shoot dieback and 

replenish the supply of root carbohydrates before the 

next burn. Waldrop and others (1992) predicted that 

all fire treatments except the annual summer burning 

would sustain a hardwood midstory that would develop 

quickly upon cessation of burning, and oak would be a 

dominant species. Many other studies throughout eastern 

North America report on oak’s persistence and improved 

competitiveness after long-term frequent burning (e.g., 

Dey and Hartman 2005).

In recalcitrant oak accumulator systems (Johnson et al. 

2002), light levels in the understory are so low (e.g., 1 

percent of full sunlight) that oak advance reproduction 

occurring after a good acorn crop remains small in size, 

and cohort survival over a 10-year period is typically low, 

e.g., less than 10 percent (Beck 1970, Loftis 1988, Crow 

1992, Parker and Dey 2008). Burning forests with small 

oak advance reproduction often causes high mortality 

in oak seedlings and accelerates succession to shadetolerant species. Shade-tolerant advance reproduction 

is able to grow to larger sizes in the understory than 

oak. This ability improves the likelihood that shadetolerant reproduction will either survive intact or sprout 

in the shade after a single fire, or infrequent fires. Oak 

sprouts from surviving root stocks are unable to meet 

their respiration needs in such low-light environments. 

Oak species are intolerant to intermediate in shade 

tolerance, and require 30 to 50 percent of full sunlight 

for good growth (Phares 1971, Teskey and Shrestha 

1985, McGraw et al. 1990, Ashton and Berlyn 1994, 

Gottschalk 1994, Brose 2008). Therefore, burning 

in mature, fully stocked stands on high quality 

sites is usually of little benefit to small oak advance 

reproduction.

FIRE AND STAND STRUCTURE

Removal of the midstory canopy in mature forests is one 

way to increase light to small oak advance reproduction. 

Prescribed burns typical of those conducted in eastern 

North America are capable of reducing the density 

of midstory trees (1- to 6-inch d.b.h.) in mature 

forests (e.g., Waldrop et al. 1992). Midstory density 

is reduced by fires that kill or topkill trees in that size 

class. However, density in the smaller size classes often 

increases dramatically after a fire because many of the 

hardwood saplings that are topkilled by the fire sprout. 

Height growth of these hardwood sprouts is slow in the 

understory of closed-canopy forests because of relatively 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 9

low light levels. Four years after a single spring burn in a 

mature Ozark forest Dey and Hartman (2005) observed 

that height growth of flowering dogwood (Cornus florida

L.) and white oak (Quercus alba L.) sprouts was slow, and 

75 percent or more of the sprouts, some from saplings 

that were initially as tall as 20 feet or more, were still 

in the 3-foot height class. Frequent fires over 4 years 

kept practically all advance reproduction of any species 

in the smallest height class (1 foot). Thus, one spring 

fire was effective in reducing the midstory hardwood 

strata. No doubt understory light levels were increased to 

somewhere between 10 and 20 percent of full sunlight as 

has been reported in a number of studies (Lorimer et al. 

1994, Miller et al. 2004, Motsinger 2006).

Under the intact closed canopy of the overstory (trees ≥ 

4.5 inches d.b.h.), suppression of sprout height growth 

persists for a number of years, thereby negating the need 

for annual burning if the objective is to keep understory 

woody structure low. In mature Missouri Ozark forests, 

annual or frequent burning (mean fire return interval = 

3.6 years) for 10 years did not improve light conditions 

beyond what was gained from one fire primarily because 

of its lack of effect on overstory density, i.e., dormantseason fires caused little mortality of overstory trees. 

However, these frequent spring fires caused 50-percent 

reductions in the density of midstory trees (i.e., ≥ 1.5 

inches to < 4.5 inches d.b.h.) and 75 percent or more in 

understory trees (i.e., ≥ 3 feet tall and < 1.5 inches d.b.h.) 

(Figs. 4 and 5). Finally, the effect of surface fires on the 

midstory varied by oak species. Density reductions in 

midstory white oak species (40 percent) were half that 

observed in red oak species (80 percent) after 10 years of 

burning. In contrast, overstory density was unaffected, 

or even increased, over the 10 years of frequent burning 

when spring fires were of low intensity. Moderate to 

high intensity fires are needed to cause reductions in 

overstory density through tree mortality. These types of 

fires may be more appropriate in managing savannas and 

woodlands across larger landscapes (e.g., thousands of 

acres), but in forests a more direct and controlled way of 

managing overstory density and composition is through 

timber harvesting and stand thinning.

Annual Burns

-100

-80

-60

-40

-20

0

20

40

Stem density percent change

Understory Burns every 3.6 years

-100

-80

-60

-40

-20

0

20

Stem density percent change

Midstory

Overstory

Shortleaf 

pine 

Red 

oak 

White Hickory 

oak All 

4

1 

Figure 4.—Percent change in density of trees in 

the understory (3 feet tall and up to 1.5 inches 

d.b.h.), midstory (1.5 to < 4.5 inches d.b.h.), and 

overstory (≥ 4.5 inches d.b.h.) after 10 years of 

annual spring burns and frequent fires (every 

3.6 years on average) in mature oak-hickory 

forests of the Missouri Ozarks.
10 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

FIRE AND REGENERATION

METHODS

Silvicultural prescriptions for regenerating oak should 

consider combining fire with regeneration methods 

such as clearcut, shelterwood, seedtree, or group and 

single-tree selection for managing forest structure to 

provide a desirable environment for oak reproduction 

development. Single fires are largely indiscriminant in the 

species they affect in the smaller size classes. Fire’s ability 

to reduce stand density is stochastic, giving managers less 

control over species composition, stand structure, and 

stem distribution within the stand. Prescribed fires are 

often set in the winter or early spring because (1) burning 

windows are more common considering weather and fine 

fuel condition; (2) personnel are less likely to be needed 

to fight wildfires; and (3) fires are safer to conduct. 

Dormant-season burning limits the killing power of 

fire, which may be a plus or minus depending on the 

outcome managers desire. Fire alone is limited in how 

big a tree it is able to kill or set back, generally having 

less effect as tree diameter increases above 5 inches d.b.h.. 

Fuel loading must be increased or burning done in 

seasons with high burning indices to increase fire’s ability 

to kill larger trees for reduction of stand density. For 

these reasons, other methods such as timber harvesting, 

and thinning by chemical or mechanical practices, 

are in many cases better suited than fire for managing 

the density of larger trees (i.e., > 5 inches d.b.h.) and 

composition of the mature forest overstory.

Light is a major limiting factor in oak regeneration 

(Abrams 1992, Lorimer 1993, Johnson et al. 2002). 

Managers control light available to reproduction 

by managing the various strata of forest vegetation. 

Reduction of the midstory, whether by mechanical 

cutting, herbicide application, or prescribed burning, 

may increase light levels to 10 to 20 percent of full 

sunlight, which is an improvement over the extremely 

low light levels (e.g., <5 percent of full sunlight) in 

mature forests, especially on productive, mesic sites 

(Lorimer et al. 1994, Barnes and Van Lear 1998, Miller 

et al. 2004, Motsinger 2006). Survival and growth of 

oak advance reproduction is improved by this increase 

in light, but oak reproduction requires 30 to 50 percent 

of full sunlight to achieve maximum photosynthesis 

and growth rates (Gottschalk 1987, Hanson et al. 1987, 

Gottschalk 1994).

Combining fire with one of the regeneration methods 

is a good way to provide enough light to maximize 

oak reproduction growth while controlling competing 

vegetation. Single-tree selection harvesting does not 

increase understory light much above that in uncut 

forests and is not often recommended for regenerating 

oak on mesic sites, or most other places outside of 

the xeric forests of the Missouri Ozarks (Johnson et 

al. 2002). A further complication is that fire may scar 

young trees, which remain for decades to grow to 

maturity before being harvested. Decay resulting from 

such scarring takes decades to progress in trees and may 

 [

A B

1 

Dey Page 1 4/16/2009 

Figure 5.—Low intensity surface fires can alter forest structure in the understory of mature 

eastern hardwood forests by killing smaller advance reproduction and causing shoot 

dieback in larger seedlings and saplings. Shown in the photographs is a mature Missouri 

Ozark forest (A) before prescribed burning and (B) after 10 years of frequent burns 

averaging one fire every 3 years. 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 11

cause significant loss of sound volume and declines in 

tree grade and log quality. Group selection openings of 

sufficient size (e.g., opening diameter equal to one to two 

times the height of the dominant trees in adjacent stands) 

can be used to regenerate oak, but it is hard to apply 

fire to control competing vegetation within the group 

openings because the groups are isolated and scattered 

throughout the stand. Additionally, group selection is 

often done in combination with single-tree selection 

harvesting between the group openings.

Fire with clearcutting or shelterwood harvesting 

probably has the greatest promise for regenerating oaks. 

Clearcutting to regenerate oak in mixed hardwood forests 

is most successful when there is adequate regeneration 

potential from oak advance reproduction and stump 

sprouts to give some certainty that oak stocking desired 

at stand maturity will be met. Models for assessing oak 

regeneration potential based on success probabilities for 

advance reproduction and stump sprouts are available for 

some species and regions in eastern North America: 

•	 Loftis (1990a) presented models for estimating 

performance of northern red oak advance 

reproduction in southern Appalachian clearcuts

•	 Loftis (1989), and Schweitzer and others (2004) 

are developing a regional regeneration model 

for the southern Appalachian Mountains and 

Cumberland Plateau

•	 Dey and others (1996b) developed ACORn for 

predicting stand size structure and composition 

for natural regeneration in upland oak-hickory 

forests in the Missouri Ozarks managed by evenaged methods

•	 Brose and others (2008) developed SILVAH 

for regenerating oak forests in the mid-Atlantic 

Region

Many other reports have been published on oak stump 

sprouting probabilities (Wendell 1975, Johnson 1977, 

McGee 1978, Lynch and Bassett 1987, Dey et al. 

1996a, Weigel and Peng 2002, Weigel et al. 2006, Dey 

et al. 2008) and success probabilities for oak planted in 

shelterwoods and clearcuts (Johnson 1984, Spetich et al. 

2002).

When oak advance reproduction is absent, a three-stage 

shelterwood is a good approach for regenerating and 

sustaining oak advance reproduction.

1) Fire can be used any number of times before a 

good acorn crop to begin reducing the density of 

competing species in the mid- and understory.

2) A light harvesting is done to release the crowns 

of potential seed-bearing oak trees and to 

remove the seed producers of competing species, 

especially species like yellow-poplar.

3) An establishment cutting may be done during 

a good acorn crop year to increase understory 

light levels and take the opportunity to manage 

competing vegetation, but fire should not be 

used after acorn drop.

4) Once seedlings establish, fire should be withheld 

until they are large enough to have good 

sprouting capacity after burning.

If adequate numbers of small oak advance reproduction 

are already present in the stand, then

1) The initial harvest of a two-stage shelterwood 

can be used to promote oak seedling growth 

by increasing the amount of light (Brose et al. 

1999a, b).

2) Post-harvest burning may be considered 3 to 

5 years later to give oak time to increase in size 

(e.g., 0.5 to 1.0 inches basal diameter).

3) Monitoring for free-to-grow oak will indicate 

whether a second burn is needed to control 

competing woody vegetation. The intent is to get 

the oak advance reproduction as big as possible 

before burning.

If fire is undesirable because mortality of small oak would 

occur, but competing vegetation needs to be reduced, 

then

1) Mechanical or herbicide control of the midstory 

and unmerchantable trees can be done in 

conjunction with shelterwood harvesting. 

Herbicide application must be done carefully to 

avoid killing the oak.
12 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

2) Higher shelterwood densities are recommended 

on high quality sites to help retard shadeintolerant competing vegetation (Loftis 1990b, 

Schlesinger et al. 1993). Yellow-poplar can 

overwhelm oak reproduction in clearcuts and 

low density shelterwoods on productive sites. 

3) Brose and others (1999b) recommend that oak 

seedlings be 0.5 to 1.0 inch in basal diameter 

before burning is considered. Burning may occur 

at the time of the final shelterwood removal or 3 to 

5 years afterwards. Oak does benefit from increased 

light after removing the shelterwood for a number 

of years, until crown canopy competition begins 

limiting light availability to oak.

There is much flexibility in designing a shelterwood 

prescription that promotes oak by meeting its resource 

needs while limiting development of competing 

vegetation. Success requires monitoring and adaptive 

management. A key ingredient of the regeneration 

prescription is the management of stand structure to 

provide adequate light to developing oak reproduction. 

Although not all oak species are the same in silvical 

requirements for good growth, most oak reproduction 

develops more quickly under a shelterwood when light 

is between 30 and 50 percent of full sunlight. Managers 

usually underestimate how much of stand stocking 

must be removed to increase light appreciably in forest 

understories. Based on a number of studies in widely 

divergent eastern forest types, 30 to 50 percent of full 

sunlight requires reducing stand stocking by more than 

40 percent, basal area by more than 50 percent, or crown 

cover by more than 30 percent by harvesting from below 

and removal of any midstory layer if present (Godman 

and Tubbs 1973, Sander 1979, Leak and Tubbs 1983, 

Schlesinger et al. 1993, Schweitzer 2004, Gardiner and 

Yeiser 2006, Parker and Dey 2008). 

Once an adequate density of large oak advance 

reproduction has developed, final shelterwood removal 

maximizes oak growth and probabilities of dominance 

throughout stand development. Retaining overstory trees 

at some point affects tree growth and eventually species 

composition of the regeneration. Miller and others 

(2006) found that clearcutting with reserves, leaving 

about 23 ft2

/ac in Appalachian mixed hardwood forests, 

caused 30- to 40-percent reductions in basal area of 

reproduction compared to similar stands that had been 

clearcut. They reported that reserve trees suppressed 

reproduction growth and shifted composition toward 

more shade-tolerant species. Larsen and others (1997) 

found that harvesting treatments that left overstory 

densities greater than 61 ft2

/ac, or 70 percent crown 

cover reduced oak seedling growth and survival in 

the Missouri Ozark forests. In the same region, Dey 

and others (2008) reported that single-tree selection 

harvesting that left 62 ft2

/ac, or 58 percent crown cover 

on average significantly reduced the growth of oak 

stump sprouts compared to those growing in clearcuts. 

Green (2008) observed decreasing densities of large oak 

reproduction as overstory basal area increased following 

regeneration harvesting including clearcutting and 

single-tree selection. Overstory basal areas above 50 ft2

/

ac caused substantial reductions in numbers of large oak 

reproduction. Furthermore, significant reductions in oak 

reproduction height growth occurred under only 20 ft2

/

ac compared to oaks growing in clearcuts. 

Kabrick and others (2008) reported that single-tree 

selection harvesting in the Missouri Ozarks significantly 

suppressed the density of oak reproduction (sized ≥ 

3.3 feet tall and up to 1.5 inches d.b.h.) compared to 

clearcutting. Moreover, black oak (Quercus velutina

Lam.) and scarlet oak (Quercus coccinea Muenchh.) 

regeneration were prominent only in clearcuts. Arthur 

and others (1998) also noted that openings much larger 

than multiple tree canopy gaps in oak-pine forests in 

the Cumberland Plateau were needed for black and 

scarlet oak regeneration to be successful. They reported 

that two dormant-season surface fires separated by 2 

years and a spring wildfire in mature, ridgetop oak-pine 

forests resulted in mortality of 16 and 20 percent in the 

overstory (i.e., trees > 4.0 inches d.b.h.), respectively, 

causing single-tree and multiple-tree gaps in the canopy. 

These small to mid-sized gaps were insufficient alone for 

regeneration of the shade-intolerant oak species.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 13

RECRUITMENT INTO THE 

OVERSTORY

Regeneration by even-aged methods can be managed to 

favor oak using prescribed burning to modify competitive 

relations. Fire can easily topkill stems below 5 inches 

d.b.h., and repeated fire favors oak species over their 

competitors. Young stands can be kept in a perpetual 

state of stand initiation with frequent fire. Eventually, 

however, fire must be withheld for forest development 

to proceed if the goal is a mature forest. Once stands 

reach crown closure, it is probably preferable to manage 

oaks and competing species by mechanical or chemical 

stand thinning rather than prescribed fire. To promote 

recruitment of oak into the overstory, oaks should be 

initially free to grow, unencumbered by overly dense 

residual overstories. Fire-free periods are needed to allow 

for oak trees to grow beyond the sapling size class and 

develop enough diameter, bark thickness, and height to 

increase the probability that they can avoid shoot dieback 

if a fire should occur again. 

In Missouri, the average diameter growth for codominant 

white oak saplings (1 to 3 inches d.b.h.) is 1.5 inches in 

10 years (Shifley and Smith 1982). Therefore, a 33-

year fire-free period is needed to allow such a white oak 

to grow to 5 inches d.b.h. and have a better chance of 

surviving a fire intact. Shifley and Smith (1982) found 

that average growth rates for red oak species were similar. 

An important point to note is that half of the trees in 

their analyses grew at rates greater than the average, 

assuming a normal distribution in oak diameter growth, 

and the upper 5 percent of oak trees had significantly 

greater diameter growth, which would lessen the time 

needed to develop thicker bark and greater fire resistance. 

It then becomes a matter of having sufficient numbers of 

large, fire-resistant oak to meet management goals for oak 

stocking at maturity.

The fire-free period may not need to be so long for oak 

stump sprouts, which exhibit an accelerated growth rate 

for some time after initial sprouting. Dey and others 

(2008) reported that oak stump sprouts in Missouri 

Ozark clearcuts grew to an average of 3.1 inches for 

scarlet oak, 2.3 inches for black oak, and 2.2 inches for 

white oak in 10 years. If the objective is to use fire to 

regenerate oak-dominated forests, then once the oaks 

are free to grow, burning does not have to be considered 

again until the period when the forest manager needs 

to create advance oak reproduction for the next 

rotation, which could be two to three decades before 

the final regeneration harvest. In woodland or savanna 

management, periodic recruitment of oak is necessary 

to sustain the desired overstory density. Because trees 

of white oak species may live to be 250 to 400 years 

old, and 80 to 200 years old for red oak species, oak 

recruitment need only occur occasionally in savannas and 

woodlands. However, when it is needed, there must be a 

sufficient fire-free period.

Newly regenerated hardwood stands in eastern North 

America have thousands of trees per acre, but stand 

density rapidly declines with time, especially after 

crown closure (Miller et al. 2007). The oaks that express 

dominance early have the best, or only, chance of 

surviving to have a place of prominence in the upper 

canopy crown classes at maturity (Ward and Stephens 

1994). Competition is severe on high quality sites, 

and oaks have little chance of maintaining dominance 

without some type of management intervention (Hilt 

1985), such as crop-tree thinning applied when the stand 

reaches crown closure (Miller et al. 2007).

FINAL THOUGHTS

Efforts to use fire to sustain oak-dominated forests, and 

to restore oak woodlands and savannas, have increased 

over the past 20 years, especially in the Great PlainsEastern Forest ecotone. Historically, fire promoted the 

invasion of prairies into eastern forests as far as Ohio, 

creating the Prairie Peninsula Region (Transeau 1935). 

During this time, Native Americans had a great effect 

on the distribution of forest and prairie in the East 

through their use of fire. An eyewitness account by Black 

Hawk, a Sauk warrior in the early 1800s, testifies to 

this influence. In 1832, Black Hawk led his people in a 

fight to secure their homeland in northern Illinois and 

southern Wisconsin from settlement by frontiersmen and 

their families. Defeated in battle, Black Hawk and a small 

group of chiefs and leaders were transported east to meet 

with President Andrew Jackson. They were taken on a 

tour through Philadelphia, Baltimore, and New York 
14 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

City to impress upon them the strength of the United 

States and the futility of further fight with the invading 

European settlers. In New York the Indian delegation 

viewed a fireworks display, of which Black Hawk noted 

in his autobiography originally published in 1833:

The chiefs [U.S. military and political leaders]

were particular in showing us every thing that 

they thought would be pleasing or gratifying to 

us. We went with them to Castle-Garden to 

see the fireworks, which was quite an agreeable 

entertainment–but...less magnificent than the sight 

of one of our large prairies would be when on fire.

Fire was not merely an entertainment spectacle for the 

Indians; they used it to manage their lands to provide for 

the needs of the people. The Sauk and neighboring tribes 

used fire to cultivate large (e.g., 800-acre) crop fields of 

corn and other vegetables and manage native prairies as 

pastures for their horses and wild game (Black Hawk 

1833).

In modern times in the East, fire is still largely an 

anthropogenic phenomenon, but we suppress fires before 

they burn much land, and this action has greatly altered 

the fire regimes promulgated by the Native Americans. 

The ill effects of fire on forests from a timber perspective 

and the shadow of Smokey Bear still have a strong 

influence on the use of fire in forest management. Today, 

our understanding is improving in how fire:

1) acts on plants through biological processes, 

2) modifies a species’ regeneration and development 

through ecological processes, 

3) changes the competitive relations among species, 

and 

4) affects long-term site productivity and ecosystem 

integrity by modifying physical properties and 

biological components of the site.

We are quickly moving away from the simple approach 

of “return frequent fire to the system and all will be 

well.” We are moving toward a more realistic and 

holistic management system approach by combining 

prescribed fire with other silvicultural practices to manage 

forest regeneration and succession within an ecological 

classification system to achieve well defined objectives 

desired by society. As in the past, the ecosystem goods 

and services we desire today guide the role of fire in forest 

plans and silvicultural prescriptions. Through research, 

monitoring, and adaptive management, we are exploring 

new ways to use fire judiciously in managing oak forests 

for a multitude of benefits including timber production.

LITERATURE CITED

Abrams, M.D. 1992. Fire and the development of oak 

forests. BioScience. 42: 346-351.

Arthur, M.A.; Paratley, R.D.; Blankenship, B.A. 1998. 

Single and repeated fires affect survival and 

regeneration of woody and herbaceous species in 

an oak-pine forest. Journal of the Torrey Botanical 

Society. 125(3): 225-236.

Ashton, P.S.; Berlyn, G.P. 1994. A comparison of 

leaf physiology and anatomy of Quercus (section 

Erythrobalanus-Fagaceae) species in different light 

environments. American Journal of Botany. 81: 589-

597.

Auchmoody, L.R.; Smith, H.C. 1993. Survival of 

acorns after fall burning. Res. Pap. NE-678. Radnor, 

PA: U.S. Department of Agriculture, Forest Service, 

Northeastern Forest Experiment Station. 5 p.

Barnes, T.A.; Van Lear, D.H. 1998. Prescribed 

fire effects on advanced regeneration in mixed 

hardwood stands. Southern Journal of Applied 

Forestry. 22: 138-142.

Beck, D.E. 1970. Effect of competition on survival and 

height growth of red oak seedlings. Res. Pap. SE-56. 

Asheville, NC: U.S. Department of Agriculture, Forest 

Service, Southeastern Forest Experiment Station. 7 p.

Black Hawk. 1833. Life of Ma-Ka-Tai-Me-She-KiaKiak or Black Hawk. In: Jackson, D., ed. 1990. Black 

Hawk an autobiography. Chicago, IL: University of 

Illinois Press. 177 p.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 15

Boerner, R.E.J. 2006. Soil, fire, water, and wind: 

how the elements conspire in the forest context.

In: Dickinson, M.B., ed. Fire in eastern oak forests: 

delivering science to land managers, proceedings of 

a conference; 2005 November 15-17; Columbus, 

OH. Gen. Tech. Rep. NRS-P-1. Newtown Square, 

PA: U.S. Department of Agriculture, Forest Service, 

Northern Research Station: 104-122.

Brose, P.H. 2008. Root development of acornorigin oak seedlings in shelterwood stands on the 

Appalachian Plateau of northern Pennsylvania: 

4-year results. Forest Ecology and Management. 255: 

3374-3381.

Brose, P.H.; Van Lear, D.H. 1998. Responses of 

hardwood advance regeneration to seasonal 

prescribed fires in oak-dominated shelterwood 

stands. Canadian Journal of Forest Research. 28: 331-

339.

Brose, P.H.; Van Lear, D.H. 2004. Survival of 

hardwood advance regeneration during prescribed 

fires: the importance of root development and root 

collar location. In: Spetich, M.A., ed. Proceedings, 

upland oak ecology symposium: history, current 

conditions, and sustainability; 2002 October 7-10; 

Fayetteville, AR. Gen. Tech. Rep. SRS-73. Asheville, 

NC: U.S. Department of Agriculture, Forest Service, 

Southern Research Station: 123-127.

Brose, P.H.; Schuler, T.M.; Ward, J.S. 2006. Responses 

of oak and other hardwood regeneration to 

prescribed fire: what we know as of 2005. In: 

Dickinson, M.B., ed. Proceedings, fire in eastern oak 

forests: delivering science to land managers; 2005 

November 15-17; Columbus, OH. Gen. Tech. Rep. 

NRS-P-1. Newtown Square, PA: U.S. Department 

of Agriculture, Forest Service, Northern Research 

Station: 123-135.

Brose, P.; Van Lear, D.; Cooper, R. 1999a. Using 

shelterwood harvests and prescribed fire to 

regenerate oak stands on productive upland sites.

Forest Ecology and Management. 113: 125-141.

Brose, P.H.; Van Lear, D.H.; Keyser, P.D. 1999b. 

A shelterwood-burn technique for regenerating 

productive upland oak sites in the Piedmont 

Region. Southern Journal of Applied Forestry. 23(3): 

158-163.

Brose, P.H.; Gottschalk, K.W.; Horsley, S.B.; Knopp, 

P.D.; Kochenderfer, J.N.; McGuinness, B.J.; Miller, 

G.W.; Ristau, T.E.; Stoleson, S.H.; Stout, S.L. 2008. 

Prescribing regeneration treatments for mixed oak 

forests in the Mid-Atlantic Region. Gen. Tech. Rep. 

NRS-33. Newtown Square, PA: U.S. Department 

of Agriculture, Forest Service, Northern Research 

Station. 100 p.

Crow, T.R. 1992. Population dynamics and growth 

patterns for a cohort of northern red oak (Quercus 

rubra) seedlings. Oecologia. 91: 192-200.

DeBano, L.F.; Neary, D.G.; Ffolliott, P.F. 1998. Fire’s 

effects on ecosystems. New York, NY: John Wiley 

and Sons. 333 p.

Dey, D.C. 1991. A comprehensive Ozark regenerator. 

Columbia, MO: University of Missouri. 283 p. Ph.D. 

dissertation.

Dey, D.C. 2002. The ecological basis for oak 

silviculture in eastern North America. Chapter 

5. In: McShea, W.J.; Healy, W.M.,eds. Oak forest 

ecosystems ecology and management for wildlife. 

Baltimore, MD: The Johns Hopkins University Press: 

60-79.

Dey, D.C.; Hartman, G. 2005. Returning fire to Ozark 

Highland forest ecosystems: effects on advance 

regeneration. Forest Ecology and Management. 217: 

37-53.

Dey, D.C.; Parker, W.C. 1996. Regeneration of red 

oak (Quercus rubra L.) using shelterwood systems: 

ecophysiology, silviculture and management 

recommendations. For. Res. Info. Pap. No. 126. 

Sault Ste. Marie, ON: Ontario Ministry of Natural 

Resources, Ontario Forest Research Institute. 59 p.
16 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Dey, D.C.; Jensen, R.G.; Wallendorf, M.J. 2008. Singletree harvesting reduces survival and growth of oak 

stump sprouts in the Missouri Ozark Highlands.

In: Jacobs, D.F.; Michler, C.H., eds. Proceedings, 

16th central hardwood forest conference; 2008 April 

8-9; West Lafayette, IN. Gen. Tech. Rep. NRS-P-24. 

Newtown Square, PA: U.S. Forest Service, Northern 

Research Station: 26-37.

Dey, D.C.; Johnson, P.S.; Garrett, H.E. 1996a. 

Modeling the regeneration of oak stands in the 

Missouri Ozark Highlands. Canadian Journal of 

Forest Research. 26(4): 573-583.

Dey, D.C.; Ter-Mikaelian, M.; Johnson, P.S.; 

Shifley, S.R. 1996b. Users guide to ACORn: a 

comprehensive Ozark regeneration simulator. Gen. 

Tech. Rep. NC-180. St. Paul, MN: U.S. Department 

of Agriculture, Forest Service, North Central Forest 

Experiment Station. 35 p.

Elliott, K.J.; Vose, J.M. 2005. Effects of understory 

prescribed burning on shortleaf pine (Pinus 

echinata Mill.)/mixed-hardwood forests. Journal of 

the Torrey Botanical Society. 132(2): 236-251.

Gardiner, E.S.; Yeiser, J.L. 2006. Underplanting 

cherrybark oak (Quercus pagoda Raf.) seedlings on 

a bottomland site in the southern United States.

New Forests. 32: 105-119.

Godman, R.M.; Tubbs, C.H. 1973. Establishing 

even-age northern hardwood regeneration by the 

shelterwood method—a preliminary guide. Res. 

Pap. NC-99. St. Paul, MN: U.S. Department of 

Agriculture, Forest Service, North Central Forest 

Experiment Station. 9 p.

Gottschalk, K.W. 1987. Effects of shading on growth 

and development of northern red oak, black oak, 

black cherry, and red maple seedlings. II. Biomass 

partitioning and prediction. In: Hay, R.L.; Woods, 

F.W.; DeSelm, H., eds. Proceedings, 6th central 

hardwood forest conference; 1987 February 24-

26; Knoxville, TN. Knoxville, TN: University of 

Tennessee: 99-110.

Gottschalk, K.W. 1994. Shade, leaf growth and crown 

development of Quercus rubra, Quercus velutina, 

Prunus serotina, and Acer rubrum seedlings. Tree 

Physiology. 14: 735-749.

Green, J. 2008. Overstory density and its effect on 

regeneration abundance, understory height growth, 

and overstory canopy expansion in the Missouri 

Ozark Highlands. Columbia, MO: University of 

Missouri. MS thesis.

Guyette, R.P.; Muzika, R.M.; Dey, D.C. 2002. 

Dynamics of an anthropogenic fire regime.

Ecosystems. 5: 472-486.

Hanson, P.J.; Isebrands, J.G.; Dickson, R.E. 1987. 

Carbon budgets of Quercus rubra L. seedlings 

at selected stages of growth: influence of light.

In: Hay, R.L.; Woods, F.W.; DeSelm, H., eds. 

Proceedings, 6th central hardwood forest conference. 

Knoxville, TN: University of Tennessee: 269-276.

Hare, R.C. 1965. The contribution of bark to fire 

resistance of southern trees. Journal of Forestry. 63: 

248-251.

Hengst, G.E.; Dawson, J.O. 1994. Bark properties 

and fire resistance of selected tree species from 

the central hardwood region of North America.

Canadian Journal of Forest Research. 24: 688-696.

Hilt, D.E. 1985. Species composition of young central 

hardwood stands that develop after clearcutting. In: 

Proceedings, 5th central hardwood forest conference. 

Champaign-Urbana, IL: University of Illinois: 11-14.

Hutchinson, T.F; Sutherland, E.K.; Yaussy, D.A. 2005. 

Effects of repeated prescribed fires on the structure, 

composition, and regeneration of mixed-oak forests 

in Ohio. Forest Ecology and Management. 218: 210-

228.

Iverson, L.R.; Hutchinson, T.F. 2002. Soil temperature 

and moisture fluctuations during and after 

prescribed fire in mixed-oak forests, USA. Natural 

Areas Journal. 22: 296-304.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 17

Iverson, L.R.; Yaussy, D.A.; Rebbeck, J.; Hutchinson, 

T.F.; Long, R.P.; Prasad, A.M. 2004. A comparison 

of thermocouples and temperature paints to 

monitor spatial and temporal characteristics of 

landscape-scale prescribed fires. International 

Journal of Wildland Fire. 13: 311-322.

Johnson, P.S. 1974. Survival and growth of northern 

red oak seedlings following a prescribed burn.

Res. Note NC-177. St. Paul, MN: U.S. Department 

of Agriculture, Forest Service, North Central Forest 

Experiment Station. 3 p.

Johnson, P.S. 1977. Predicting oak stump sprouting 

and sprout development in the Missouri Ozarks.

Res. Pap. NC-149. St. Paul, MN: U.S. Department 

of Agriculture, Forest Service, North Central Forest 

Experiment Station. 11 p.

Johnson, P.S. 1984. Responses of planted northern red 

oak to three overstory treatments. Canadian Journal 

of Forest Research. 14: 536-542.

Johnson, P.S.; Shifley, S.R.; Rogers, R. 2002. The 

ecology and silviculture of oaks. New York, NY: 

CABI Publishing. 503 p.

Kabrick, J.M.; Zenner, E.K.; Dey, D.C.; Gwaze, D.; 

Jensen, R.G. 2008. Using ecological land types 

to examine landscape-scale oak regeneration 

dynamics. Forest Ecology and Management. 255: 

3051-3062.

Kolb, T.E.; Steiner, K.C. 1990. Growth and biomass 

partitioning of northern red oak and yellowpoplar seedlings: effects of shading and grass root 

competition. Forest Science. 36: 34-44.

Korstian, C.F. 1927. Factors controlling germination 

and early survival in oaks. School of Forestry 

Bulletin 19. New Haven, CT: Yale University. 122 p.

Kruger, E.L.; Reich, P.B. 1997. Responses of hardwood 

regeneration to fire in mesic forest openings. I. 

Post-fire community dynamics. Canadian Journal of 

Forest Research 27: 1822-1831.

Larsen, D.R.; Metzger, M.A.; Johnson, P.S. 1997. Oak 

regeneration and overstory density in the Missouri 

Ozarks. Canadian Journal of Forest Research. 27: 

869-875.

Leak, W.B.; Tubbs, C.H. 1983. Percent crown cover 

tables for applying the shelterwood system in 

New England. Res. Note NE-313. Radnor, PA: 

U.S. Department of Agriculture, Forest Service, 

Northeastern Forest Experiment Station. 4 p.

Lhotka, J.M.; Zaczek, J.J. 2003. Effects of scarification 

disturbance on the seedling and midstory layer in a 

successional mixed-oak forest. Northern Journal of 

Applied Forestry. 20(2): 85-91.

Loftis, D.L. 1988. Regenerating oaks on high quality 

sites, an update. In: Smith, H.C.; Perkey, A.W.; 

Kidd, Jr., W.E., eds. Proceedings, Guidelines for 

regenerating Appalachian hardwood stands. SAF 

Publication 88-03. Washington, DC: Society of 

American Foresters: 199-209.

Loftis, D.L. 1989. Species composition of regeneration 

after clearcutting southern Appalachian hardwoods.

In: Miller, J.H., comp. Proceedings, 5th biennial 

southern silvicultural research conference; 1988 

November 1-3; Memphis, TN. Gen. Tech. Rep. 

SO-74. New Orleans, LA: U.S. Department 

of Agriculture, Forest Service, Southern Forest 

Experiment Station: 253-257.

Loftis, D.L. 1990a. Predicting post-harvest 

performance of advance red oak reproduction in 

the southern Appalachians. Forest Science. 36(4): 

908-916.

Loftis, D.L. 1990b. A shelterwood method for 

regenerating red oak in the southern Appalachians.

Forest Science. 36(4): 917-929.

Loomis, R.M. 1973. Estimating fire-caused mortality 

and injury in oak-hickory forests. Res. Pap. NC-94. 

St. Paul, MN: U.S. Department of Agriculture, Forest 

Service, North Central Forest Experiment Station. 6 p.
18 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Lorimer, C.G. 1993. Causes of the oak regeneration 

problem. In: Loftis, D.L.; McGee, C.E., eds. 

Proceedings, oak regeneration: serious problems, 

practical recommendations. Gen. Tech. Rep. SE-84. 

Asheville, NC: U.S. Department of Agriculture, Forest 

Service, Southeastern Forest Experiment Station: 14-

39.

Lorimer, C.G.; Chapman, J.W.; Lambert, W.D. 1994. 

Tall understorey vegetation as a factor in the poor 

development of oak seedlings beneath mature 

stands. Journal of Ecology. 82: 227-237.

Lynch, A.M.; Bassett, J.R. 1987. Oak stump sprouting 

on dry sites in northern Lower Michigan. Northern 

Journal of Applied Forestry. 4: 142-145.

McGee, D.E. 1978. Size and age of tree affect white 

oak stump sprouting. Res. Note SO-239. New 

Orleans, LA: U.S. Department of Agriculture, Forest 

Service, Southern Forest Experiment Station. 2 p.

McGee, C.E. 1979. Fire and other factors related to 

oak regeneration. In: Holt, H.A.; Fisher, B.C., eds. 

Proceedings, 1979 J.S. Wright forestry conference. 

West Lafayette, IN: Purdue University: 75-81.

McGraw, J.B.; Gottschalk, K.W.; Vavrek, M.C.; 

Chester, A.L. 1990. Interactive effects of resource 

availabilities and defoliation on photosynthesis, 

growth and mortality of red oak seedlings. Tree 

Physiology. 7: 247-254.

Miller, G.W.; Kochenderfer, J.N.; Fekedulegn, D.B. 

2006. Influence of individual reserve tress on 

nearby reproduction in two-aged Appalachian 

hardwood stands. Forest Ecology and Management. 

224: 241-251.

Miller, G.W.; Kochenderfer, J.N.; Gottschalk, K.W. 

2004. Effect of pre-harvest shade control and 

fencing on northern red oak seedling development 

in the central Appalachians. In: Spetich, M.A., ed. 

Proceedings, upland oak ecology symposium: history, 

current conditions, and sustainability; 2002 October 

7-10; Fayetteville, AR. Gen. Tech. Rep. SRS-73. 

Asheville, NC: U.S. Department of Agriculture, Forest 

Service, Southern Research Station: 182-189.

Miller, G.W.; Stringer, J.W.; Mercker, D.C. 2007. 

Technical guide to crop tree release in hardwood 

forests. Professional Hardwood Notes University 

of Tennessee Extension PB1774. Knoxville, TN: 

University of Tennessee. 23 p.

Motsinger, J. 2006. Response of natural and artificial 

pin oak reproduction to mid- and understory 

removal in a bottomland forest. Columbia, MO: 

University of Missouri. 79 p. M.S. thesis.

Nowacki, G.J.; Abrams, M.D. 2008. The demise of 

fire and “mesophication” of forests in the eastern 

United States. BioScience. 58(2): 123-138.

Parker, W.C.; Dey, D.C. 2008. Influence of overstory 

density on ecophysiology of red oak (Quercus 

rubra) and sugar maple (Acer saccharum) seedlings 

in central Ontario shelterwoods. Tree Physiology. 

28: 797-804.

Phares, R.E. 1971. Growth of red oak (Quercus rubra

L.) seedlings in relation to light and nutrients.

Ecology. 52: 669-672.

Phillips, R.; Hutchinson, T.; Brudnak, L.; Waldrop, 

T. 2007. Fire and fire surrogate treatments in 

mixed-oak forests: effects on herbaceous layer 

vegetation. In: Butler, B.W.; Cook, W., comps. The 

fire environment—innovations, management, and 

policy; conference proceedings; 26-30 March 2007; 

Destin, FL. RMRS-P-46CD. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station: 475-485.

Pyne, S.J. 1982. Fire in America: a cultural history of 

wildland and rural fire. Princeton, NJ: Princeton 

University Press. 654 p.

Rathfon, R.A.; Lichti, N.I.; Swihart, R.K. 2008. Disking 

and mid- and understory removal following an 

above-average acorn crop in three mature oak forests 

in southern Indiana. In: Jacobs, Douglass F.; Michler, 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 19

Charles H., eds. 2008. Proceedings, 16th central 

hardwood forest conference; 2008 April 8-9; West 

Lafayette, IN. Gen. Tech. Rep. NRS-P-24. Newtown 

Square, PA: U.S. Department of Agriculture, Forest 

Service, Northern Research Station: 59-69.

Rebbeck, J.; Long, R.; Yaussy, D. 2004. Survival 

of hardwood seedlings and saplings following 

overstory thinning and prescribed fires in mixedoak forests of southern Ohio. In: Spetich, M.A., 

ed. Upland oak ecology symposium: history, current 

conditions, and sustainability; 2002 October 7-10; 

Fayetteville, AR. Gen. Tech. Rep. SRS-73. Asheville, 

NC: U.S. Department of Agriculture, Forest Service, 

Southern Research Station: 275-284.

Regelbrugge, J.C.; Smith, D.W. 1994. Postfire tree 

mortality in relation to wildfire severity in mixed 

oak forests in the Blue Ridge of Virginia. Northern 

Journal of Applied Forestry. 11: 90-97.

Reich, P.B.; Abrams, M.D.; Ellsworth, D.S.; Kruger, 

E.L.; Tabone, T.J. 1990. Fire affects ecophysiology 

and community dynamics of central Wisconsin oak 

forest regeneration. Ecology. 71: 2179-2190.

Sander, I.L. 1979. Regenerating oaks with the 

shelterwood system. In: Proceedings, J.S. Wright 

forestry conference. West Lafayette, IN: Purdue 

University: 54-60.

Schlesinger, R.C.; Sander, I.L.; Davidson, K.R. 

1993. Oak regeneration potential increased by 

shelterwood treatments. Northern Journal of Applied 

Forestry. 10: 149-153.

Schweitzer, C.J. 2004. First-year response of an upland 

hardwood forest to five levels of overstory tree 

retention. In: Proceedings, 12th biennial southern 

silvicultural research conference; 2003 February 24-

28; Biloxi, MS. Gen. Tech. Rep. SRS-71. Asheville, 

NC: U.S. Department of Agriculture, Forest Service, 

Southern Research Station: 287-291.

Schweitzer, C.J.; Loftis, D.L.; Wang, Y.; Janzen, G.C. 

2004. Regeneration potential of selected forested 

stands on the Cumberland Plateau of north 

Alabama. In: Spetich, M.A., ed. Proceedings, Upland 

oak ecology symposium: history, current conditions, 

and sustainability; 2002 October 7-10; Fayetteville, 

AR. Gen. Tech. Rep. SRS-73. Asheville, N.C.: U.S. 

Department of Agriculture, Forest Service, Southern 

Research Station: 269-274.

Shifley, S.R.; Smith, W.B. 1982. Diameter growth, 

survival, and volume estimates for Missouri Trees.

Res. Note NC-292. St. Paul, MN: U.S. Department 

of Agriculture, Forest Service, North Central Forest 

Experiment Station. 7 p.

Spetich, M.A.; Dey, D.C.; Johnson, P.S.; Graney, D.L. 

2002. Competitive capacity of Quercus rubra L. 

planted in Arkansas Boston Mountains. Forest 

Science. 48(3): 504-517.

Stambaugh, M.C.; Guyette, R.C.; Grabner, K.W.; 

Kolaks, J. 2006. Understanding Ozark forest litter 

variability through a synthesis of accumulation 

rates and fire events. In: Andrews, P.L.; Butler, B.W., 

comps. 2006. Fuels management-how to measure 

success: conference proceedings. 28-30 March 2006; 

Portland, OR. Proceedings RMRS-P-41. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station: 321-332.

Teskey, R.O.; Shrestha, R.C. 1985. A relationship 

between carbon dioxide, photosynthetic efficiency 

and shade tolerance. Physiologia Plantarum. 63: 126-

132.

Transeau, E.N. 1935. The prairie peninsula. Ecology. 

16(3): 423-437.

Van Lear, D.H. 1991. Fire and oak regeneration in the 

southern Appalachians. In: Nodvin, S.C.; Waldrop, 

T.A., eds. Gen. Tech. Rep. SE-69. Asheville, N.C.: 

U.S. Department of Agriculture, Forest Service, 

Southern Forest Experiment Station: 15-21.

Van Lear, D.H.; Waldrop, T.A. 1991. Prescribed 

burning for regeneration. In: Duryea, M.L.; 

Dougherty, P.M., eds. Chapter 12 forest regeneration 
20 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

manual. Netherlands: Kluwer Academic Publishers: 

235-250.

Waldrop, T.A.; White, D.L.; Jones, S.M. 1992. Fire 

regimes for pine-grassland communities in the 

southeastern United States. Forest Ecology and 

Management . 47: 195-210.

Walters, M.B.; Kruger, E.L.; Reich, P.B. 1993. 

Relative growth rate in relation to physiological 

and morphological traits for northern hardwood 

tree seedlings: species, light environment and 

ontogenetic considerations. Oecologia. 96: 219-231.

Ward, J.S.; Stephens, G.R. 1994. Crown class transition 

rates of maturing northern red oak (Quercus rubra

L.). Forest Science. 40(2): 221-237.

Weigel, D.R.; Peng, C-Y.J. 2002. Predicting stump 

sprouting and competitive success of five oak 

species in southern Indiana. Canadian Journal of 

Forest Research. 32: 703-712.

Weigel, D.R.; Dey, D.C.; Peng, C-Y.J. 2006. Stump 

sprout dominance probabilities of five oak 

species in southern Indiana 15 years after clearcut 

harvesting. Proceedings, 13th biennial southern 

silvicultural research conference; 2005 February 

28-March 4; Memphis, TN. Gen. Tech. Rep. SRS-92. 

Asheville, NC: U.S. Department of Agriculture, Forest 

Service, Southern Research Station: 551-558.

Wendell, G.W. 1975. Stump sprout growth and 

quality of several Appalachian hardwood species 

after clearcutting. Res. Pap. NE-329. Upper Darby, 

PA: U.S. Department of Agriculture, Forest Service, 

Northeastern Forest Experiment Station. 9 p.

Wendell, G.W.; Smith, H.C. 1986. Effects of a 

prescribed burn in a central Appalachian oakhickory stand. Res. Pap. NE-594. Broomall, PA: 

U.S. Department of Agriculture, Forest Service, 

Northeastern Forest Experiment Station. 8 p.

Whelan, R.J. 1995. The ecology of fire. Cambridge, 

UK: Cambridge University Press. 346 p.

Williams, M. 1989. Americans and their forests: a 

historical geography. Cambridge, UK: Cambridge 

University Press. 599 p.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 21

EFFECTS OF OVERSTORY STAND DENSITY AND FIRE ON GROUND LAYER

VEGETATION IN OAK WOODLAND AND SAVANNA HABITATS

John B. Taft1

1 Plant Ecologist,Illinois Natural History Survey, Champaign, IL

JBH is corresponding author; to contact, call (217) 244-5046 or email at taft@inhs.uiuc.edu

Abstract.—Vegetation changes underway in oak woodland and savanna communities in the eastern and 

midwestern United States, primarily a result of reduced fire frequency or fire absence, include increased tree 

density and shading and loss of species diversity in the ground layer. However, some habitats, particularly 

on dry-mesic to xeric sites, retain considerable restoration potential, and insights are needed for directing 

management efforts, such as with prescribed fire, where they can be most effective. This paper examines 

overstory and ground layer interactions in flatwoods, barrens, and dry-mesic woodland habitats, together with 

fire effects, and highlights structural characteristics relevant to ecological condition and restoration potential.

In nested vegetation sample plots throughout Illinois, patterns of ground layer diversity were strongly related 

to levels of tree density at several study sites. At these sites, with increasing tree density, or “thicketization,” 

the diversity of ground layer species and plant functional groups declines. Where this pattern was lacking 

suggests two possibilities: tree density has yet to become a limiting factor for ground layer species and 

functional group diversity, or, more typically, tree density has progressed to the point where remaining 

ground layer species are sparsely distributed, shade-tolerant, and relatively indifferent to levels of tree 

density. The pattern of ground layer species attrition with increasing thicketization is interpreted as a 

signal for productive restoration opportunities compared to the latter, low diversity condition. Efforts 

to restore these former communities with reintroduction of fire have shown promise. Use of fire on 

sites even with extensive thicketization seems to improve overstory structure and ground layer diversity; 

however, in these cases, the soil seed bank may be limited following prolonged periods of stand closure.

Interactions between overstory and ground layer vegetation also were examined for ordered 

patterns of plant functional group losses (community disassembly) with increasing tree density. 

Documenting ordered patterns along the structural gradient of tree density provides additional 

insights regarding ecological condition and restoration potential of sites or habitats. Functional 

groups that appear most sensitive to thicketization and are the first to decline with extended fire 

absence are herbaceous vines (relatively scarce), perennial grasses, sedges, and perennial forbs. While 

opportunities remain to restore aspects of oak woodland and savanna habitats, the attrition pattern 

suggests a limited time frame for the full restoration of ground layer diversity, even in dry to xeric sites.

INTRODUCTION

Oak-dominated savanna, barrens, and woodland habitats 

occur throughout North America but have undergone 

extensive habitat loss and degradation, particularly as a 

result of declining fire frequency and fire absence, and 

are considered imperiled ecosystems (Anderson et al. 

1999, Abrams 2005). Restoring these communities has 

become a priority for conservation agencies and habitat 

managers. The prairie-forest transition zone (Anderson 

1983), a region centered on Illinois and overlapping with 

the leading edge of the “prairie peninsula” (Transeau 

1935), provides opportunities for testing the restoration 

potential of oak woodland and savanna-like habitats. 

While about 55 percent of the landcover of Illinois 

was prairie in the early 1800s (Szafoni et al. 2002), the 

remaining lands primarily were forest, woodland, and 

savanna. These vegetation types formed a heterogeneous 

mosaic; wooded habitats were most prevalent in dissected 

terrain and prairie predominated where slopes were less 

than 4 percent (Anderson 1991). Fires that contributed 

to the maintenance of prairie also maintained the 

structural and compositional characteristics of savanna 

and woodland habitats (Nuzzo 1986, Taft 1997, 

Anderson and Bowles 1999). This fire history, while 
22 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

seemingly in the distant past, is within the life-span of 

some long-lived trees still standing (e.g., bur [Quercus 

macrocarpa], white [Q. alba], and post oaks [Q. stellata]). 

The open-grown form of many of these veteran trees 

serves as a reminder of the more open structure of 

woodlands and savannas in the pre-settlement period. 

In some cases, burning of woodlands was a practice 

that continued into the early 20th century, when it was 

strongly discouraged and disparaged as a “savage custom” 

(Miller 1920). However, once fire frequency declined, 

many of these stands quickly underwent closure, or 

“thicketization” (Archer et al. 2004, Breshears 2006), 

resulting in conversion of prairies and savannas to 

woodlands and then forests.

Some savanna and woodland habitats in the prairie-forest 

transition zone on seasonally dry sites such as flatwoods 

and barrens demonstrate a degree of resistance to change 

during long fire-free intervals. The great majority of 

floristic diversity in these habitats is in the ground layer 

(Taft 1997); consequently, they provide an opportunity 

to examine the patterns of influence of overstory 

structure on ground layer composition and diversity 

for evidence of interactions that may be absent in less 

ecologically stressful habitats, where extended periods 

of fire absence have resulted in prolonged ground layer 

shading (e.g., Hutchinson et al. 2005).

Interactions between overstory and ground layer 

vegetation in forests and woodlands can be reciprocal, 

with overstory influencing ground layer and ground 

layer influencing successful regeneration among tree 

species (Gilliam and Roberts 2003). Using flatwoods, 

barrens, and dry-mesic woodlands as examples, this 

paper will focus on how overstory structure in woodland 

and savanna-like habitats is related to and possibly 

affects patterns of ground-layer species diversity and 

composition. Maintaining a species pool at a given 

habitat can be influenced by both regional and local 

processes and involves a balance of processes at each 

scale (Huston 1999). Local factors that tend to decrease 

diversity include competition (Huston 1994), such as 

from woody overstory species in savanna-like habitats 

(Peterson and Reich 2008), an effect that could be 

ameliorated by regional interactions promoting species 

exchanges among habitats (Ricklefs and Schluter 1993). 

However, habitat fragmentation would tend to limit 

species exchanges while ecological islands such as dry to 

xeric habitats also would limit the types of species that 

could become established. Consequently, it is expected 

in the highly fragmented prairie-forest transition zone 

(e.g., Schwartz 1997) that with thicketization, especially 

in dry to xeric sites, the interaction between woodland/

savanna overstory and ground layer vegetation would 

be manifested as a pattern of species loss, or attrition, in 

the ground layer. Ground layer species in forest habitats 

also can be very diverse (Gilliam 2007); however, forest 

species generally adapted to mesic conditions could not 

be expected to compensate for attrition of species in 

closed dry savanna and woodland habitats, particularly in 

fragmented landscapes.

Under the framework in the current study, situations 

where tree density and ground-layer species diversity 

are found to be inversely related would provide a signal, 

perhaps a finite opportunity, of restoration potential 

and an indicator where management with prescribed fire 

could be focused. A significant regression of tree density 

on ground layer diversity (P < 0.05) will be referred to 

as fitting the post-fire species attrition hypothesis. This 

hypothesis is based on the concept of plant functional 

groups, which are assemblages of species with a shared 

set of attributes that may include morphological and 

physiological characteristics, ecological roles, resource 

use, and response to disturbance (Symstad 2002). 

Diversity in functional groups has been shown to be 

closely linked with ecosystem functioning and stability, 

and can serve as an indicator of community integrity 

(Hooper and Vitousek 1997, Tilman et al. 1997, Mason 

et al. 2003). Monitoring the density of plant functional 

groups shows promise as a rapid assessment technique 

in prairies for evaluating habitat integrity, as it is highly 

correlated with species richness and estimates of floristic 

integrity (Sivicek 2007). It is expected that the diversity 

of plant functional groups would decline with stand 

closure. This pattern will be referred to as the post-fire 

functional group attrition hypothesis.

Where such a pattern is lacking would suggest one of 

two null hypotheses: 1) relatively stable condition where 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 23

tree density has yet to limit ground layer diversity; or, 

more typically 2) the progression of thicketization to the 

point where remaining ground layer species are shadetolerant and indifferent to levels of tree density. The 

differences in these alternative null states can be readily 

distinguished by evidence of thicketization and the extent 

of herbaceous species in the ground layer vegetation. Sites 

fitting the second null model would be densely shaded 

stands with few herbaceous species, a predominance of 

woody species, and substantial bare ground. Although 

quite rare, null condition 1 would be optimal in 

open-woodland and savanna habitats; the negative 

attrition profile would indicate greater opportunities for 

restoration compared with null condition 2. The attrition 

pattern would suggest an existing heterogeneous stand 

structure with gaps containing more and different ground 

layer species (e.g., Leach and Givnish 1999, Peterson 

and Reich 2008) compared with areas with greater 

tree density. Consequently, with the attrition pattern, 

the species pool retains shade-intolerant taxa that are 

responding, albeit negatively, to stand thicketization. 

Attempting restoration at closed stands where these 

species are absent would rely on diversity found offsite (limited by habitat fragmentation and ecological 

condition) or among the selected species residing in 

the soil seed bank that could be stimulated with fire 

treatments.

METHODS AND DATA SOURCES

Vegetation Sampling

Data for the following habitat descriptions and analyses 

were collected employing similar vegetation sample 

methods involving stratified-random distribution of 

nested sample units with 0.05-ha circular plots for trees 

(≥ 6 cm diameter at breast height [d.b.h.]), 0.005-ha 

subplots for shrubs and saplings (> 50 cm tall), and 12 

to 25 ground-layer sample quadrats (primarily 1/4-m2

; 

one study [Taft 2005] with 1⁄2-m2

 quadrats) on a transect 

within each tree plot. The data come from several sources 

(Table 1). Habitat characterization for flatwoods is based 

on a quantitative survey of vegetation and soils at 50 

plots (0.05-ha) sampled among six sites on the Illinoian 

till plain (Taft et al. 1995). All six sites are recognized 

by the Illinois Natural Areas Inventory ([INAI], White 

1978) as high quality habitats. Data from an additional 

site, Mt. Vernon Flatwoods ([MVF], Taft 2005), also 

are used. Data for barrens were recorded from a pair of 

sites in southern Illinois monitored since 1989 as part 

of a fire effects study (Taft 2003) and include more 

recent unpublished data. The INAI recognized the fire 

treatment site, Gibbons Creek Barrens (GCB), as a 

high quality barrens remnant. The fire-free reference 

site, Forest Service Barrens (FSB), was similar in many 

ways to the fire treatment site (Taft and Solecki 2002). 

Table 1.—Summary of habitat type, sites name, sample intensity (0.05-ha circular tree plots), 

and fire history for sites examined in this study. Most data are baseline, preburn data. INAI = 

Illinois Naural Areas Inventory sites.

Community Site Baseline fire

Typea name Plot # treatments Citations

Flatwoods (INAI) Reckers Woods 8 none Taft et al. 1995

Flatwoods (INAI) Chip-O-Will Woods 8 none Taft et al. 1995

Flatwoods (INAI) Posen Woods 8 none Taft et al. 1995

Flatwoods (INAI) Wms Creek Woods 8 none Taft et al. 1995

Flatwoods (INAI) Jackson Slough 8 none Taft et al. 1995

Flatwoods (INAI) Lake Sara Flatwoods 10 20 yrs, annual Taft et al. 1995

Flatwoods Mt. Vernon 23 none (preburn) Taft 2005

Dry Barrens (INAI) Gibbons Creek 15 none (preburn) Taft and Solecki

2002

Dry Barrens (INAI) Forest Service 8 none Taft and Solecki

2002

Woodlandb Beaver Dam SP 12 1-3 burns Taft 2006

Woodlandb Beaver Dam SP 15 none Taft 2006

a Community classification follows White and Madany (1978)

b Community classification follows White and Madany (1978), with revisions.
24 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Data from dry-mesic woodland habitat were collected 

from six management units at Beaver Dam State Park 

(BDSP) in central Illinois, including three units with and 

three without recent burns as part of a fire management 

program (Taft 2006).

Habitat Descriptions

Dominant species and summary parameters for canopy, 

shrub/sapling, and ground layer strata are shown in 

Appendix 1, combining data from flatwoods (Taft et al. 

1995), barrens (Taft and Solecki 2002), and woodland 

habitats (Taft 2006). Dominance is based on importance 

values calculated as the sum of two relative values (IV 

200): basal area and density for trees, frequency and 

density for saplings and shrubs, and percent cover and 

frequency for ground layer species, including woody 

plants to 50 cm tall. The top-ranking 10, 15, and 50 

species from canopy, shrub/sapling, and ground layer 

strata, respectively, are shown. Many species in the 

woody strata are present across habitats. By contrast, 

as an indication of dissimilarity among habitats in 

the ground layer stratum, only two species (Virginia 

creeper [Parthenocissus quinquefolia] and poison ivy 

[Toxicodendron radicans]) were found in all three 

habitats. Botanical nomenclature follows Mohlenbrock 

(1986) and community classification follows that 

developed for the Illinois Natural Areas Inventory 

(modified from White and Madany 1978). Eleven plant 

functional groups were recognized for the ground layer 

species in these habitats: ferns, annual/biennial forbs, 

herbaceous vines, legumes, perennial forbs, C3 perennial 

grasses (cool season), C4 perennial grasses (warm season), 

perennial sedges, shrubs, trees (seedlings to 50 cm), and 

woody vines.

Flatwoods - The flatwoods included in this study also 

are termed “southern flatwoods” (White 1978) or “post 

oak flatwoods” due to the predominance of post oak, a 

species accounting for about 57 percent of the IV. Oak 

and hickory species combined account for 93 percent 

of the IV in the canopy, but were relatively scarce in 

the shrub/sapling stratum. The shrub/sapling layer had 

just over 4,000 stems/ha (Appendix 1), an indication of 

thicketization.

Flatwoods are level woodlands (≤ ~2-percent slope) with 

claypan soils. Claypans (argillic horizons) are subsurface 

soil horizons characterized by a sharp increase in clay 

content compared to overlying soil horizons. Claypans 

can result in a perched water table in the spring; however, 

with evapo-transpiration during summer months, the 

surface soil horizons typically become very dry. These 

woodlands formerly were widespread on the Illinoian till 

plain (Telford 1926, Braun 1936, Aldridge and Homoya 

1984) but have been reduced by extensive logging and 

land-use changes (Taft et al. 1995).

Flatwoods remnants can be instructive for examining 

overstory-ground layer interactions because variance 

in overstory structure and composition ordinarily 

attributable to degree of slope and aspect is reduced to 

variation in edaphic characteristics, such as soil nutrient 

content, depth to claypan, and soil available water 

holding capacity (AWC). For example, total density of 

woody stems is positively related to depth to claypan 

and particularly to soil AWC (Taft et al. 1995). Sites 

with more mesic soil conditions will be the fastest to 

undergo vegetation changes with fire absence and perhaps 

the most challenging to restore. Accordingly, stability 

in overstory structure and composition varies widely 

among flatwoods remnants with some demonstrating 

both structural and compositional instability, the typical 

condition for many oak woodlands (Abrams 1992, 

Moser et al. 2005). In contrast, some stands demonstrate 

compositional and structural stability with apparently 

sustainable levels of post oak regeneration. Differences 

can be traced to variance in soil parent materials. 

Unstable sites with poor oak recruitment and prolific 

regeneration of invading tree species tend to be found 

on relatively deeper soils with greater AWC. These tend 

to be soil types developed in loess deposits with a siltyloam texture. Structurally stable sites have been found 

on lacustrine deposits with considerable sand content 

in the surface soil horizons (about 40-50 percent) and, 

consequently, lower AWC (Taft et al. 1995).

At MVF (not included in Appendix 1), an old secondgrowth flatwoods, white oak was co-dominant with 

post oak. Tree density was 465/ha ( 6 cm d.b.h.), basal 

area was 24.7 m2

/ha, and sapling/shrub density was 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 25

just over 7,000 stems/ha (Taft 2005), demonstrating 

considerable thicketization. Ground layer vegetation was 

very sparse and dominated by woody seedlings and vines; 

Virginia creeper, poison ivy, sassafras, riverbank grape 

(Vitis riparia), Mayapple (Podophyllum peltatum), and 

black oak accounted for more than half of the species 

occurrences. No grasses and only a single occurrence of 

one sedge was found in baseline samples.

Barrens - Barrens is a term applied to a wide range of 

physiographic and environmental conditions to describe 

distinctly different types of vegetation (e.g., Hutchison 

1994, Bowles and McBride 1994). As the term is used 

in forested regions of the Midwest, barrens typically 

refer to a savanna-like community characterized by 

local assemblages of a prairie flora (White and Madany 

1978). Today, barrens remnants occur primarily in 

dissected terrain on south- and southwest-facing aspects 

with shallow soils over bedrock (Heikens and Robertson 

1995). During extended periods of fire absence, barrens 

tend to convert to closed woodland.

Baseline data from a pair of dry barrens in southern 

Illinois examined for a long-term fire effects study 

indicate that post oak was the dominant tree species, 

accounting for about 55 percent of the IV for trees (Taft 

and Solecki 2002). These sites, GCB (the fire treatment 

site) and FSB (a fire-free reference site), occur on shallow 

soils developed in loess and residuum over sandstone. 

Oak and hickory species combined accounted for 77 

percent of the IV for trees. The size class distribution 

pattern for trees indicated compositional stability because 

post oak likely will continue to be dominant; however, 

prolific regeneration of post oak forming a strong 

reverse-J-shaped curve indicates a structurally unstable 

site and portends stand closure. Stem density for saplings 

and shrubs was just over 5,000 stems/ha, indicating 

thicketization was well underway (Appendix 1, pg. 38).

Dry-Mesic Woodland - Woodland habitat at BDSP, 

Macoupin County, IL, occurs primarily on rolling, 

dissected glacial moraines. Soils are developed in glacial 

till deposits and generally have a silty-loam texture 

(Tegeler 2004). Fire management units at Beaver Dam 

State Park included woodlands with one to three recent 

burns as well as unburned units. Oak and hickory 

species accounted for 49 percent of the total IV. Oak 

species were dominant in terms of basal area, but the 

high density of slippery elm (Ulmus rubra) and hackberry 

(Celtis occidentalis) made them prominent species as 

well. Overstory regeneration generally was a pattern of 

instability with little successful oak recruitment. Total 

shrub/sapling stem density was just over 14,000/ha, 

indicating advanced thicketization. Previously burned 

units had slightly lower tree density but slightly higher 

tree basal area compared to unburned units, much lower 

stem density in the shrub/sapling stratum, and higher 

ground-layer species density and diversity.

Perennial forbs are the most species-rich functional group 

in the ground layer of flatwoods, barrens, and woodland 

habitats in this study. However, the profiles of plant 

functional group importance in these habitats show a shift 

from woody vine dominance and near-equal secondary 

dominance of forbs, sedges, and grasses in flatwoods, to 

graminoid (grass and sedge) dominance in barrens and 

forb dominance in woodlands (Fig. 1).

DATA ANALYSIS

Data from canopy cover estimates made with a spherical 

densiometer and overstory structure were recorded in 

both flatwoods and barrens habitats. Correlations between 

canopy cover and total density of trees were positive, 

particularly in flatwoods (r = 0.57). However, tree density 

explained more of the variance in ground layer vegetation 

than did canopy cover (r = -0.67 vs. r = -0.44). Tree basal 

area was unrelated to ground layer diversity patterns in 

flatwoods, barrens, and woodland datasets. Consequently, 

tree density is used to examine the interactions between 

overstory and ground layer vegetation.

Interactions between overstory tree density and ground 

layer species and functional groups were examined with 

regression analysis; mean comparisons of tree density 

classes and ground layer parameters were done with 

ANOVA and Tukey post-hoc tests (SPSS ver. 10, 

Chicago, IL). Tree density classes of high, medium, 

and low levels were created for each habitat to examine 

trends among ground-layer functional groups. Tree 

density classes were formed by dividing the range of tree 

densities into equal thirds; in each case, mean differences 
26 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

in tree density classes were significant overall and with all 

pairwise Tukey post-hoc comparisons. Species density in 

the ground layer stratum is the average number of species 

per quadrat (generally, 1⁄4 m2

). Species diversity is the 

Shannon-Wiener Index (H'). Functional group richness 

is calculated as the total number of plant functional 

groups in ground layer quadrat samples nested within 

tree plots.

RESULTS

Overstory-Ground Layer Interactions

Regression analysis of the interaction between tree 

density and ground layer diversity for all sample data 

combined from flatwoods, barrens, and woodland 

habitats showed no pattern. However, interactions were 

found between overstory and ground layer strata when 

individual community types were examined separately.

flatwoods

0

5

10

15

20

25

30

Fern

A/B-Forb

H-Vine

Legumes

P-Forb

P-Grass C3

P-Grass C4

P-Sedge

Shrub

Tree

W-Vine

relative abundance (Iv)

0

10

20

30

40

50

60

70

80

Species #

Barrens

0

5

10

15

20

25

30

35

Fern

A/B-Forb

H-Vine

Legumes

P-Forb

P-Grass C3P-Grass C4

P-Sedge

Shrub

Tree

W-Vine

relative abundance (Cover)

0

5

10

15

20

25

30

35

Species #

woodland

0

5

10

15

20

25

30

35

40

45

50

Fern

A/B-Forb

H-Vine

Legumes

P-Forb

P-Grass C3

P-Grass C4

P-Sedge

Shrub

Tree

W-Vine

relative abundance (Cover)

0

10

20

30

40

50

60

Species #

Fig. 1

Figure 1.—Relative abundance (bars [left 

y axis]) and species richness (line and 

point data [right y axis]) of plant functional 

groups from vegetation sample data in 

flatwoods, barrens, and woodland habitats 

in Illiniois. A/B = annual/biennial, H = 

herbaceous, P = perennial, W = woody. 

Quadrat numbers for each community type 

were: flatwoods - 1,080, barrens - 276, 

and woodlands - 312.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 27

Flatwoods

Survey of Six INAI Sites on the Illinoian Till Plain - 

Ground layer species diversity was inversely related 

to tree density (Fig. 2) on all plots from the six sites 

examined together and on four of the six sites examined 

separately. The two exceptional sites fit the null attrition 

model 2; these latter sites had the greatest mean soil 

AWC among flatwoods study sites. The overall pattern 

due to regression of tree density on ground-layer diversity 

(Fig. 2) fits the species attrition hypothesis ( r = -0.57, 

F = 23.1, df = 48, P < 0.0001) and is made particularly 

strong by including Lake Sara Flatwoods (LSF), a site 

with an extensive fire history (20 years of nearly annual 

fire). Without the burned unit, the pattern is weaker but 

still significant ( r = -0.37, F = 6.1, df = 38, P = 0.017). 

Mean comparisons of ground layer diversity (H') by tree 

density classes (low, medium, and high) were significantly 

different (Fig. 3), with the greatest diversity in the low 

tree density class. All pairwise comparisons also were 

different. (The difference between low and medium tree 

density was marginally significant [P = 0.055]).

Functional group richness also was inversely related to 

tree density (Fig. 4), but this pattern was true primarily 

at the community level. Only one individual site, Posen 

Woods, showed this pattern. Overall differences in 

functional group richness among tree-density classes were 

significant (Fig. 5). Functional groups proportionately 

more common in low- and medium-density portions of 

stands include nitrogen-fixing species (legumes), annual/

biennial species, perennial forbs, perennial sedges, and 

perennial grasses. Woody functional groups (vines, 

shrubs, tree seedlings) were predominant in the high treedensity sites (Fig. 6).

Fig 2

INAI Flatwoods

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 5 10 15 20 25 30 35 40

Tree Density (0.05-ha)

Grd Layer Diversity (H')

Recker Woods

C-O-W Woods

Posen Woods

Wms Creek Flatwoods

Jackson Slough Flatwoods

Lake Sara Flatwoods

r = -0.57, F = 23.1, df = 48, P < 0.0001

Fig 3

Flatwoods

0

0.5

1

1.5

2

2.5

3

3.5

Low Medium High

Tree Density Classes

Ground Layer Diversity (H')

A* B C

Figure 2.—Interaction between overstory 

tree density and ground layer diversity 

fitting the species attrition hypothesis for six 

flatwoods recognized by the Illinois Natural 

Areas Inventory (INAI). Ground layer 

diversity is the average Shannon-Wiener 

Index (H') from 12 (Lake Sara) to 25 

quadrats for each tree plot. Tree density is 

based on stems ≥ 6 cm d.b.h.

Figure 3.—Mean comparison of ground 

layer diversity (Shannon-Wiener Index 

[H') among tree density classes for six 

flatwoods recognized by the Illinois Natural 

Areas Inventory. The overall differences are 

significant (ANOVA: F = 11.6, df = 2, P < 

0.0001); different letters indicate significant 

pairwise comparisons with Tukey post-hoc 

test (*difference between low and medium 

tree density is marginally significant [P = 

0.055]). Error bars are SE.
28 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Figure 4.—Interaction between 

overstory tree density and ground 

layer functional group richness for 

six flatwoods recognized by the 

Illinois Natural Areas Inventory. 

The pattern fits the functional group 

attrition hypothesis. Functional group 

richness is the total count among 

sample quadrats for each tree plot (n 

= 12 for Lake Sara and n = 25 for all 

other sites). Tree density is based on 

stems ≥ 6 cm d.b.h.

Figure 5.—Comparison of average 

ground-layer functional group 

richness among tree density classes 

in flatwoods. Differences from mean 

comparisons are significant (ANOVA: 

F = 5.8, df = 2, P < 0.006). Different 

letters indicate significant differences 

in pairwise comparisons with Tukey 

post-hoc test. Error bars are SE. 

Figure 6.—Distribution of groundlayer functional groups proportionate 

to tree density classes in flatwoods. 

Tree density classes had significantly 

different means. N2 = nitrogen 

fixers, A/B = annual/biennial, H = 

herbaceous, P = perennial, Hemi/par. 

= Hemiparasites, W = woody.

Fig 4

Flatwoods

0

2

4

6

8

10

12

0 5 10 15 20 25 30 35 40

Tree Density (0.05-ha)

Ground Layer Functional 

Group Richness

Recker Woods

COW Flatwoods

Posen Woods

Wms Creek Flatwoods

Jackson Slough Woods

Lake Sara Flatwoods r = -0.42, df = 48, F = 10.1, p = 0.003

Fig 5

Flatwoods

0

2

4

6

8

10

Low Medium High

Tree Density Classes

Ground Layer Functional 

Group Richness

A AB B

Fig 6

Flatwoods

0%

20%

40%

60%

80%

100%

N2 fixers

A/B-Forb

P-Forb

P-Sedge

P-Grass

Shrub

H-Vine

P-Forb mono

Tree

Hemi/par

W-Vine

Fern

Relative Importance

Low Tree Density

Medium Tree Density

High Tree Density
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 29

Mt. Vernon Flatwoods - Sample data from MVF are in 

contrast with most of the flatwoods dataset described 

above. At MVF there was no correlation between stand 

density and ground layer diversity. Fifteen of the 20 

most frequent taxa in the ground layer were woody 

species. These conditions suggest null attrition model 2. 

A fire management study was conducted to determine 

restoration potential of this site (Taft 2005; see below).

Barrens

Gibbons Creek and Forest Service Barrens - Ground-layer 

species diversity trends lower with increasing tree density 

(Fig. 7). The pattern due to regression fits the species 

attrition hypothesis when baseline, preburn data from 

both sites are combined. Density of post oak alone, by far 

the dominant tree, explains even more of the variance in 

ground layer diversity (F = 25.8, P < 0.001). Differences 

in mean ground layer diversity among tree-density classes 

were significant with the greatest diversity in the low tree 

density class; however, there were no differences between 

low and medium tree-density classes (Fig. 8).

Functional group richness also trends lower with 

increased tree density (Fig. 9). Differences in 

functional group richness among tree-density classes 

were significant with the greatest richness in the low 

tree density class, though there were no differences 

between low and medium tree-density classes (Fig. 10). 

Functional groups proportionately more common in low 

density portions of stands are herbaceous vines, ferns, 

cool and warm season grasses, perennial forbs, and sedges 

(Fig. 11).

Fig 7

Dry Barrens

0.0

0.5

1.0

1.5

2.0

2.5

3.0

3.5

4.0

0 10 20 30 40 50 60 70 80

Tree Density (0.05-ha)

Ground Layer Diversity (H')

Gibbons Creek Barrens

Forest Service Barrens r = -0.51, df = 21, F = 7.3, P = 0.01

Fig 8

Barrens

0

0.5

1

1.5

2

2.5

3

3.5

Low Medium High

Tree Density Classes

Ground Layer Diversity (H')

A A B

Figure 7.—Interaction between 

overstory tree density and ground 

layer diversity fitting the species 

attrition hypothesis from 23 plots 

sampled at Gibbons Creek and 

Forest Service barrens. Ground 

layer diversity is the average 

Shannon-Wiener Index (H') for each 

tree plot. Tree density includes 

stems ≥ 6 cm d.b.h.

Figure 8.—Mean comparison of 

ground layer diversity (ShannonWiener Index [H']) among tree 

density classes in barrens sample 

data. The overall differences are 

significant (ANOVA: F = 5.4, df = 2, 

P = 0.01); different letters indicate 

significant pairwise comparisons 

with Tukey post-hoc test. Error bars 

are SE.
30 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Figure 9.—Interaction between 

overstory tree density and groundlayer functional group richness 

in baseline (preburn) barrens 

sample data. The pattern fits 

the functional group attrition 

hypothesis. Functional group 

richness is the total count among 

sample quadrats for each tree plot 

(n = 12). Tree density is based on 

stems ≥ 6 cm d.b.h.

Figure 10.—Comparison of 

average ground-layer functional 

group richness among tree density 

classes in barrens. Differences from 

mean comparisons are significant 

(ANOVA: F = 6.2, df = 2, P = 

0.008). Different letters indicate 

significant differences in pairwise 

comparisons with Tukey post-hoc 

test. Error bars are SE. 

Figure 11.—Distribution of 

ground layer functional groups 

proportionate to tree density 

classes in barrens. Tree density 

classes had significantly different 

means. H = herbaceous, P = 

perennial, C3 (cool season), C4 

(warm season), A/B = annual/

biennial, W = woody, N2 = 

nitrogen fixers.

Fig 9

Barrens

0

2

4

6

8

10

12

20 30 40 50 60 70 80

Tree Density (0.05-ha)

Ground Layer Functional 

Group Richness

Gibbons Creek Barrens

Forest Service Barrens r = -54, df = 21, F = 8.8, P = 0.007

Fig 10

 Barrens

0

2

4

6

8

10

12

Low Medium High

Tree Density Classes

Ground Layer Functinoal 

Group Richness

A A B

Barrens

0%

10%

20%

30%

40%

50%

60%

70%

80%

90%

100%

H-Vine

Fern

P-Grass C3

P-Grass C4

P-Forb

P-Sedge

W-Vine

A/B Forb

P-Forb N2

Tree

Shrub

Relative Importance

Low Tree Density

Medium Tree Density

High Tree Density

Fig. 11
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 31

Dry-Mesic Woodland

Beaver Dam State Park - Among all sampled 

management units at BDSP, there is no correlation 

between tree density and ground-cover species density 

or diversity of ground-layer functional groups, 

suggesting null attrition model 2 with the extensive 

thicketization. Previously burned units show a weak 

pattern consistent with the species attrition hypothesis; 

however, the pattern due to regression is nonsignificant. 

Functional group richness also did not show a pattern of 

attrition with greater tree density. However, functional 

groups with affinity for low tree-density zones include 

herbaceous vines, perennial grasses, perennial sedges, 

perennial forbs, and woody vines (Fig. 12).

Fire Effects on Interactions 

Among Strata

Flatwoods - Lake Sara Flatwoods, a site with an extensive 

fire history, strengthened the species attrition pattern 

found among sample units with relatively high species 

diversity and low tree density. Ground-layer species 

density was over four times the mean species density 

for all other sites. LSF and MVF occur on the same 

soil series, Wynoose silt loam, but differ greatly in 

ground layer cover, composition, and diversity (Fig. 13). 

Following three burns at MVF, species density increased 

three-fold and tree density declined 26 percent; however, 

there was a 270-percent increase in density of stems in 

the shrub/sapling stratum (Taft 2005). Following three 

burns, there remained no discernable species attrition 

Fig. 13

Figure 12.—Distribution of 

ground-layer functional groups 

proportionate to tree density 

classes in woodlands. Tree density 

classes had significantly different 

means. H = herbaceous, A/B = 

annual/biennial, P = perennial, W = 

woody, N = native, X = nonnative.

Woodland

0%

20%

40%

60%

80%

100%

H-Vine

P-Grass

P-Sedge

P-Forb

W-Vine

Tree

A/B Forbs

N Shrub

Fern

X Shrub

Relative Importance

Low Tree Density

Medium Tree Density

High Tree Density

Fig. 12

Figure 13.—Lake Sara Flatwoods (left) in Effingham County, IL, following a 20‐year period of annual burns. Photo taken 

in July 1990. Note the absence of fire scars. Contrast with Mt. Vernon Flatwoods (right) in Jefferson County, IL, on the 

same soil series (Wynoose) but lacking recent fire. While tree densities (stems ≥ 6 cm d.b.h.) differ greatly (284 vs. 465 

stems/ha), basal area is more similar (20.2 vs. 24.7 m2

/ha).
32 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

pattern. The increase in ground layer diversity resulted 

primarily from species stored in the soil seed bank. 

Eight sedge species that were absent in baseline samples 

emerged following the burns, but perennial grasses 

dominant at other flatwoods remnants remained very 

sparse or absent.

Barrens - Following four burns over a 17-year period at 

GCB, ground layer species density more than doubled 

(Fig. 14), tree density declined 29 percent, shrub/

sapling density declined 35 percent, and the pattern 

of ground-layer species attrition was strengthened 

compared to the baseline sample (r = -0.70 compared to 

r = -0.51), but only when the fire-free reference plots are 

included. Data from the fire treatment unit following 

four burns approximates null attrition model 1 with 

extensive percent cover of a rich herbaceous ground 

layer. The pattern of functional group attrition also 

was strengthened compared to the baseline sample data 

(r = -0.68 compared to r = -0.54), and made particularly 

strong when data from fire treatment and fire-free 

reference units are combined.

Not only do spatial patterns of tree density and ground 

layer diversity support the species attrition hypothesis, 

but long-term trends data from FSB, the fire-free 

reference site, also show gradual species losses over time 

(Fig. 14). Trends for mean functional group richness 

show a diverging pattern from nearly equal values in 

the baseline samples (1989) to widely and significantly 

divergent means in 2006 following 17+ years of fire 

absence at FSB and four burns at GCB (Fig. 15). 

Fig 14

Barrens Ground-Cover 

2

4

6

8

10

12

1989 1990 1991 1993 1994 1995 2006

Species Density/0.25-m-sq

Gibbons Creek Barrens

Forest Service Barrens

Barrens

0

2

4

6

8

10

12

1989 1995 2006

Years

Mean Ground Layer Functional 

Group Richness

Gibbons Creek Barrens

Forest Service Barrens

*

Fig. 15

Figure 14.—Comparison of trends 

in ground-layer species density 

between a barrens remnant managed 

with prescribed fire (Gibbons Creek 

Barrens) and a fire-free reference 

unit (Forest Service Barrens) in Pope 

County, IL. Arrows indicate times of 

burns. Error bars are SE.

Figure 15.—Comparison of changes 

in mean functional group richness in 

fire treatment and fire‐free reference 

units in dry barrens habitats. Two 

fire treatments occurred before 1995 

and two after. * indicates significant 

difference (t-test: t = 7.4, df = 21, P < 

0.0001). Error bars are SE.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 33

Predominantly declining functional groups at FSB 

include perennial grasses (C3 and C4 species combined 

for a 35-percent reduction in cover), sedges, woody vines, 

and perennial forbs. All functional groups declined in 

percent cover at FSB except for tree seedlings.

Dry-Mesic Woodland - Fire treatments at BDSP resulted 

in a significant decrease of tree density (5.6 percent) 

and a significant increase in ground-layer species density 

(17 percent). In fire-free reference units, there were a 

slight increase in tree density and a significant decline 

in ground-layer species richness compared to baseline 

samples 2 years earlier. As a result of these changes, 

an overall pattern consistent with the species attrition 

hypothesis developed; however, the pattern due to 

regression is relatively weak and non-significant (P = 

0.14). Data from fire treatment units alone, which 

showed a weak but nonsignificant attrition pattern with 

the baseline data, show a significant inverse pattern in 

the relationship between tree density and ground-layer 

species density after an additional fire treatment ( r = 

-0.57, F = 5.7, df = 12, P = 0.03).

DISCUSSION

A chief limiting factor for ground-layer species richness 

and cover in savanna habitats is light availability (Bray 

1958, 1960, Leach and Givnish 1999, Peterson et al. 

2007). However, available light is spatially and temporally 

heterogeneous and accurate assessment requires specialized 

equipment and considerations of several abiotic and biotic 

variables measured over time (Neufeld and Young 2003). 

In this study, tree density was tested as a factor for rapid 

and cost-effective assessment of the influence of overstory 

stand structure on ground-layer species diversity in 

savanna and woodland habitats. Tests were conducted at 

different ecological scales: across multiple habitats, within 

habitats, and within individual sites and management 

units. Patterns of overstory-to-ground layer interactions 

were obscured in this study when multiple habitat types, 

including sites with widely ranging ecological conditions, 

were examined collectively. Based on these datasets, the 

most appropriate ecological scale for examining patterns 

of overstory and ground layer interactions relevant to 

the species and functional group attrition hypotheses is 

within habitats and sites.

Results summarized here explore overstory-ground 

layer interactions as an indicator of ecological condition 

and restoration potential. The post-fire species attrition 

hypothesis and functional group attrition hypothesis 

predict that with increasing thicketization (overstory 

density) during extended periods of fire absence, 

ground-layer species diversity and the richness of plant 

functional groups will decline until a stasis is reached and 

remaining species are relatively indifferent to shade levels 

(null attrition model 2). Alternatively, with increasing 

fire, reduced tree density, and increased ground layer 

diversity (e.g., Taft 2003, Bowles et al. 2007, Peterson 

et al. 2007), the relations between tree density and 

ground-layer diversity may strengthen. Eventually, a 

temporary stasis might be reached where shade levels are 

not limiting to ground layer vegetation (null attrition 

model 1).

These results suggest a sequence of three developmental 

stages with fire absence in savanna and open woodland 

habitats relevant to ecological condition and restoration 

potential: 1) null attrition model 1, where tree density 

has yet to alter ground layer patterns of diversity; 2) 

post-fire species attrition where patterns of tree density 

are inversely related to ground layer diversity; and 3) null 

attrition model 2, where tree density (thicketization) 

has progressed to the stage where primarily only 

shade-tolerant ground layer species remain (e.g, MVF, 

unburned portions of BDSP). While there is potential 

for restoration of some aspects of habitats resembling null 

attrition model 2, full restoration may not be possible 

without species augmentation at some sites due to seed 

bank attrition (Bond 1984). In contrast, sites fitting null 

model 1 and the post-fire species attrition model merit 

consideration as management priority sites.

The pace of thicketization with fire absence can be 

attributed to edaphic resource availability (Taft et al. 

1995, Peterson et al. 2007). Among the flatwoods 

examined here, sites fitting null attrition model 2 had the 

greatest AWC. Likewise, savanna habitats on deep, rich 

soils are particularly imperiled because they have fewer 

resource limitations (e.g., available moisture) compared 

to dry-to-xeric sites and readily convert to forests with 

extended fire absence (Nuzzo 1986, Anderson and 

Bowles 1999).
34 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Applications of prescribed fire in oak savannas and 

woodlands in the prairie-forest transition zone, 

particularly repeated burns, consistently result in 

reduced tree density and increased ground layer species 

richness and diversity (White 1983, Taft 2003, Bowles 

et al. 2007). Consequently, development of the species 

attrition pattern where formerly absent (i.e., null model 

2) would indicate successful treatment. The loss of the 

attrition pattern with fire management where it once 

occurred potentially would suggest the development of 

null attrition model 1.

In addition to the spatial pattern of decline among 

ground layer species with stand thicketization, long-term 

trends data at a fire-free reference barrens community 

(FSB) suggest that species loss can be a gradual and 

ongoing process. Perennial grasses and sedges showed 

the greatest decline with long-term fire absence at FSB. 

Similar patterns during long fire-free intervals can be 

expected in savanna and woodland habitats throughout 

the prairie-forest transition zone. Functional groups most 

affiliated with lower tree density in flatwoods, barrens, 

and woodland habitats in descending average rank order 

are: herbaceous vines, cool-season perennial grasses, 

perennial forbs, warm-season perennial grasses, perennial 

sedges, and nitrogen-fixing species. (In barrens, these 

species are most strongly affiliated with intermediate treedensity zones.) Herbaceous vines (e.g., crested bindweed 

[Polygonum cristatum], wild yam [Dioscorea villosa], 

small passion flower [Passiflora lutea], and carrion flower 

[Smilax lasioneuron]) were relatively scarce in all datasets 

(absent in Appendix 1, pg. 38).

Based on data summarized here, ordered disassembly 

(Zavaleta and Hulvey 2004) of savanna/woodland 

ground layer with thicketization begins with declines 

among perennial grasses, sedges, perennial forbs 

including herbaceous vines, and nitrogen-fixing species. 

A degree of spatial heterogeneity in stand structure 

contributes to overall site diversity because plant 

functional groups are partitioned into differentially 

shaded zones, for example with warm-season grasses in 

the most open sites and forbs most abundant in semishaded zones (Leach and Givnish 1999, Peterson et al. 

2007). Similar results are found in the present study with 

lower diversity most pronounced in the high tree-density 

zones. Such trends can help guide interpretation of site 

conditions and the degree of needed restoration for 

recovery of ground layer diversity.

The soil seed bank is an important refuge for ground 

layer diversity (Taft 2003), particularly where there is 

extensive habitat fragmentation. However, the abundance 

of viable seeds likely declines over time. Bond (1984) 

and Bond and van Wilgen (1996) described a post-fire 

seed attrition hypothesis that predicts seed availability 

following fire would decline in the seed bank depending 

on the time frame for action by seed predators, decay, 

and disease. The restoration of sedges at MVF but not 

grasses or legumes (Taft 2005) and the recovery of C3 

grasses but not C4 grasses at GCB (Taft 2003) suggest 

some species and functional groups may not persist in the 

seed bank for extended periods.

The question has been raised as to whether it is too 

late to restore oak communities in the eastern United 

States using prescribed fire except on the driest sites 

(Abrams 2005). While there remain opportunities for 

restoring woodland and savanna-like habitats in the 

prairie-forest transition zone, particularly remnants on 

dry to xeric sites, spatial and long-term trends in these 

communities suggest at least structural and in some cases 

compositional instability in the overstory. In addition, 

ground layer diversity continually declines during long 

periods of fire absence. In a highly fragmented landscape 

such as the Midwest, where species immigration 

opportunities are limited, the time frame for restoring the 

full compliment of species and plant functional groups 

in ground layer vegetation of oak woodland and savannalike habitats appears to be limited.

ACKNOWLEDGMENT

The support of grants from the Illinois Department of 

Natural Resources for a portion of this work is greatly 

appreciated.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 35

LITERATURE CITED

Abrams, M.D. 1992. Fire and the development of oak 

forests. BioScience. 42(5): 346-353.

Abrams, M.D. 2005. Prescribing fire in eastern oak 

forests: is time running out? Northern Journal of 

Applied Forestry. 22(3): 190-196.

Aldrich, J.R.; Homoya, M.A. 1984. Natural barrens and 

post oak flatwoods in Posey and Spencer counties, 

Indiana. Proceedings of the Indiana Academy of 

Science. 93: 291-301.

Anderson, R.C. 1983. The eastern prairie-forest 

transition—an overview. In: Brewer, R., ed. 

Proceedings, 8th North American prairie conference. 

Kalamazoo, MI: Western Michigan University: 86-92.

Anderson, R.C. 1991. Presettlement forests of Illinois.

In: Burger, G.V.; Ebinger, J.; Wilhelm, O.S., eds. 

Proceedings of the oak woods management workshop. 

Charleston, IL: Eastern Illinois University: 9-19.

Anderson, R.C.; Bowles, M.L. 1999. Deep-soil 

savannas and barrens of the midwestern United 

States. In: Anderson, R.C.; Fralish, J.S.; Baskin, 

J.M., eds. Savannas, barrens, and rock outcrop plant 

communities of North America. New York, NY: 

Cambridge University Press: 155-170.

Anderson, R.C.;, Fralish, J.S.; Baskin, J.M. 1999. 

Introduction. In: Anderson, R.C.; Fralish, J.S.; 

Baskin, J.M., eds. Savannas, barrens, and rock outcrop 

plant communities of North America. New York, NY: 

Cambridge University Press: 1-4.

Archer, S.; Boutton, T.W.; McMurtry, C.R. 2004. 

Carbon and nitrogen accumulation in a savanna 

landscape: field and modeling perspectives. In: 

Shiyomi, M.; Kawahata, H.; Koizumi, H.; Tsuda, A.; 

Awaya, Y., eds. Global environmental change in the 

ocean and on land. Tokyo: Terrapub: 359-373.

Bond, W.J. 1984. Fire survival of Cape Proteaceae 

- influence of fire season and seed predators.

Vegetatio. 56: 65-74.

Bond, W.J.; van Wilgen, B.W. 1996. Fire and plants.

London: Chapman and Hall.

Bowles, M.L.; McBride., J.L. 1994. Presettlement 

barrens in the glaciated prairie region of Illinois. In: 

Fralish, J.S.; Anderson, R.C.; Ebinger, J.E.; Szafoni, 

R., eds. Proceedings, North American conference 

on barrens and savannas. Normal, IL: Illinois State 

University: 75-86.

Bowles, M.L., Jacobs, K.A., Mengler, J. 2007. Longterm changes in an oak forest’s woody understory 

and ground layer with repeated burning. Journal of 

the Torrey Botanical Society. 134(2): 223-237.

Braun, E.L. 1936. Forests of the Illinois till plain of 

southwestern Ohio. Ecological Monographs. 6: 89-

149.

Breshears, D.D. 2006. The grassland-forest continuum: 

trends in ecosystem properties for woody plant 

mosaics? Frontiers in Ecology and the Environment. 

4: 96-104.

Bray, J.R. 1958. The distribution of savanna species 

in relation to light intensity. Canadian Journal of 

Botany. 36: 671-681.

Bray, J.R. 1960. The composition of savanna 

vegetation in Wisconsin. Ecology. 41: 721-732.

Gilliam, F.S. 2007. The ecological significance of the 

herbaceous layer in temperate forest ecosystems.

BioScience. 57(10): 845-858.

Gilliam, F.S.; Roberts, M.R. 2003. Interactions 

between the herbaceous layer and overstory canopy 

of eastern forests: a mechanism for linkage. In: 

Gilliam, F.S.; Roberts, M.R., eds. The herbaceous 

layer in forests of eastern North America. New York, 

NY: Oxford University Press: 198-223.

Heikens, A.L.; Robertson, P.A. 1995. Classification of 

barrens and other natural xeric forest openings in 

southern Illinois. Bulletin of the Torrey Botanical 

Club. 122: 203-214.
36 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Hooper, D.U.; Vitousek, P.M. 1997. The effects of 

plant composition and diversity on ecosystem 

processes. Science. 277: 1302-1305.

Huston, M.A. 1994. Biological diversity: the 

coexistence of species on changing landscapes.

Cambridge, UK: Cambridge University Press.

Huston, M.A. 1999. Local processes and regional 

patterns: appropriate scales for understanding 

variation in the diversity of plants and animals.

Oikos. 86: 393-401.

Hutchinson, T.F.; Berner, R.E.J.; Sutherland, S.; 

Sutherland, E.K.; Ortt, M.; Iverson, L.R. 2005. 

Prescribed fire effects on the herbaceous layer 

of mixed oak forests. Canadian Journal of Forest 

Research. 35: 877-890.

Hutchison, M.D. 1994. The barrens of the Midwest: an 

historical perspective. Castanea. 59: 195-203.

Leach, M.K.; Givnish, T.J. 1999. Gradients in the 

composition, structure, and diversity of remnant 

oak savannas in southern Wisconsin. Ecological 

Monographs. 69(3): 353-374.

Mason, N.W.H.; MacGillivray, K.; Steel, J.B.; Wilson, 

J.B. 2003. An index of functional diversity. Journal 

of Vegetation Science. 14: 571-578.

Miller, R.B. 1920. Fire prevention in Illinois forests.

Forestry Circular No. 2. Urbana, IL: Division of the 

Natural History Survey. Department of Registration 

and Education.

Mohlenbrock, R.H. 1986. Guide to the vascular flora 

of Illinois. Revised and enlarged edition. Carbondale, 

IL: Southern Illinois University Press.

Moser, W.K.; Hansen, M.; McWilliams, W.; Sheffield, 

R. 2005. Oak composition and structure in the 

eastern United States. In: Dickinson, M.B., ed. 

Fire in eastern oak forests: delivering science to land 

managers; 2005 November 15-17; Columbus, OH. 

Gen. Tech. Rep. NRS-P-1. Newtown Square, PA: 

U.S. Department of Agriculture, Forest Service, 

Northern Research Station: 49-61.

Neufeld, H.S.; Young, D.R. 2003. Ecophysiology of the 

herbaceous layer in temperate deciduous forests.

In: Gilliam, F.S.; Roberts, M.R., eds. The herbaceous 

layer in forests of eastern North America. New York, 

NY: Oxford University Press: 38-90.

Nuzzo, V.A. 1986. Extent and status of Midwest oak 

savanna: presettlement and 1985. Natural Areas 

Journal. 6: 6-36.

Peterson, D.W.; Reich, P.B.; Wrage, K.J. 2007. Plant 

functional group responses to fire frequency and 

tree canopy cover gradients in oak savannas and 

woodlands. Journal of Vegetation Science. 18: 3-12.

Peterson, D.W.; Reich, P.B. 2008. Fire frequency 

and tree canopy structure influence plant species 

diversity in a forest-grassland ecotone. Plant 

Ecology. 194: 5-16.

Ricklefs, R.E.; Schluter, D. 1993. Species diversity: 

regional and historical influences. In: Ricklefs, 

R.E.;chluter, D., eds. Species diversity in ecological 

communities. Chicago, IL: University of Chicago 

Press: 350-363.

Schwartz, M.W., ed. 1997. Conservation in highly 

fragmented landscapes. New York, NY: Chapman 

and Hall Press.

Sivicek. V.A. 2007. Prairie functional composition: 

development of a rapid assessment method for 

measuring vegetation integrity. Champaign, IL: 

University of Illinois. 73 p. M.S. thesis.

Symstad, A.J. 2002. An overview of ecological 

plant classification systems: linking functional 

response and functional effect groups. In: Ambasht, 

R.S.; Ambasht, N.K., eds. Modern trends in applied 

terrestrial ecology. Dordrecht, the Netherlands: 

Kluwer Academic Publishers: 13-50.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 37

Szafoni, D.L; Greer, D.; Cordle, L. 2002. Land cover of 

Illinois in the early 1800s. Location: Illinois Natural 

History Survey. Digital vector data.

Taft, J.B. 1997. Savannas and open woodlands.

In: Schwartz, M.W., ed. Conservation in highly 

fragmented landscapes. New York, NY: Chapman and 

Hall Press: 24-54.

Taft, J.B. 2003. Fire effects on community structure, 

composition, and diversity in a dry sandstone 

barrens. Journal of the Torrey Botanical Society. 130: 

170-192.

Taft, J.B. 2005. Fire effects on structure, composition, 

and diversity in a flatwoods remnant in southcentral Illinois. Castanea. 70: 298-313.

Taft, J.B. 2006. Fire effects on vegetation structure, 

composition, and species richness in oak woodland 

habitats at Beaver Dam State Park and Chip-OWill woods. Illinois Nat. History Surv. Tech. Rep. 

2006(3). Champaign, IL: Illinois Natural History 

Survey. 169 p. Available at www.ideals.uiuc.edu/

handle/2142/10477 (Accessed 8 May 2009).

Taft, J.B.; Schwartz, M.W.; Phillippe, L.R. 1995. 

Vegetation ecology of flatwoods on the Illinoian till 

plain. Journal of Vegetation Science. 6: 647-666.

Taft, J.B.; Solecki, M.K. 2002. Vegetation composition, 

structure, and diversity patterns of two dry 

sandstone barrens in southern Illinois. Castanea. 67: 

343-368.

Tegeler, R.A. 2004. Soil Survey of Macoupin 

County, Illinois. Champaign, IL: U.S. Department 

of Agriculture, Natural Resources Conservation 

Service in cooperation with the Illinois Agricultural 

Experiment Station.

Telford, C.J. 1926. Third report on a forest survey of 

Illinois. Illinois Natural History Survey Bulletin. 16: 

1-102.

Transeau, E.N. 1935. The prairie peninsula. Ecology. 

16: 423-437.

Tilman, D.; Knops, J.M.H.; Wedin, D.A.; Reich, P.B.; 

Ritchie, M.E.; Siemann, E. 1997. The influence of 

functional diversity and composition on ecosystem 

processes. Science. 277: 1300-1302.

White, A.S. 1983. The effects of thirteen years 

of annual prescribed burning on a Quercus 

ellipsoidalis community in Minnesota. Ecology. 64: 

1081-1085.

White, J. 1978. Illinois natural areas inventory 

technical report. Vol. 1. Survey methods and results. 

Urbana, IL: Illinois Natural Areas Inventory.

White, J.; Madany, M.H. 1978. Classification of 

natural communities in Illinois. In: White, J., 

ed. Illinois Natural Areas technical report, volume 

1. Survey methods and results. Urbana, IL: Illinois 

Natural Areas Inventory: 301-405.

Zavaleta, E.; Hulvey, K.B. 2004. Realistic species losses 

disproportionately reduce grassland resistance to 

biological invaders. Science. 306: 1175-1177.
38 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Appendix 1

Dominant species examined for this study from flatwoods, barrens, and woodland habitats in 

Illinois. The dominant species are the top ranking 10, 15, and 50 species from canopy, shrub/

sapling, and ground cover strata, respectively, from combined lists for all three habitats. 

Summary values for each stratum and habitat are shown. IV 200 is sum of two relative values 

(e.g., basal area and density for trees). FG = Functional Group, af = annual forb, pf = perennial 

forb, pg C3 = perennial grass (cool season), pg C4 = perennial grass (warm season), ps = 

perennial sedge. * = nonnative species.

FLATWOODS BARRENS WOODLAND

CANOPY STRATUM

- Top 10 ranking species IV 200 IV 200 IV 200

Quercus stellata 114.8 109.9 13.5

Ulmus rubra 3.0 - 41.3

Ulmus alata - 35.5 -

Quercus velutina 14.9 0.3 20.0

Carya ovata 10.9 4.4 16.5

Quercus alba 5.9 0.6 23.2

Quercus marilandica 17.3 6.9 -

Celtis occidentalis - - 24.2

Carya texana 2.5 15.1 -

Carya glabra 0.6 14.6 -

% of IV 85.0 93.7 69.4

Summary Data

Tree Density/ha 464.0 975.0 796.0

Basal Area (m2

/ha) 23.1 18.1 25.8

SHRUB/SAPLING STRATUM 

-Top 15 ranking species IV 200 IV 200 IV 200

Ulmus alata - 44.7 -

Ulmus rubra 7.0 - 30.4

Rubus alleghiensis/pen. 29.6 - 0.5

Sassafras albidum 20.4 - 8.1

Quercus stellata 7.8 17.8 -

Carya ovata 13.3 7.2 3.7

Prunus serotina 15.5 4.6 3.8

Fraxinus americana 2.9 10.3 9.9

Rosa multiflora* 2.0 - 20.4

Quercus velutina 11.1 10.6 0.3

Celtis occidentalis 2.5 - 19.5

Carya texana 7.1 13.6 -

Symphoricarpos orbiculatus - 13.7 7.0

Lonicera maackii* - - 16.9

Quercus marilandica 9.5 5.2 -

% of IV 64.3 63.8 60.2

Summary Data

Shrub/Sapling Density/ha 4,004 5,323 14,196

GROUND LAYER SPECIES

- Top 50 species, combined 

habitats

IV 200 IV 200 IV 200 FG

Acalypha gracilens 2.19 3.52 - af

Impatiens capensis - - 4.13 af

Pilea pumila - - 2.52 af

continued
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 39

Asplenium platyneuron - 3.21 - fern

Helianthus divaricatus 18.39 15.12 - pf

Sanicula odorata - - 22.98 pf

Eupatorium rugosum - - 8.49 pf

Circaea lutetiana - - 6.59 pf

Helianthus strumosus - - 5.17 pf

Polygonum virginicum - - 3.63 pf

Galium pilosum - 3.50 - pf

Antennaria plantaginifolia - 3.41 - pf

Geum canadense - - 3.37 pf

Parthenium integrifolium 3.10 - - pf

Viola sororia - - 3.08 pf

Phryma leptostachya - - 2.68 pf

Euphorbia corollata - 2.40 - pf

Solidago ulmifolia - - 2.25 pf

Smilacina racemosa - - 2.14 pf

Danthonia spicata 1.51 34.01 - pg C3

Dichanthelium laxiflorum - 16.39 - pg C3

Cinna arundinacea 9.83 - - pg C3

Agrostis scabra 7.86 - - pg C3

Dichanthelium acuminatum 7.84 - - pg C3

Dichanthelium boscii - 4.74 - pg C3

Dichanthelium linearifolium - 3.57 - pg C3

Festuca obtusa - - 2.66 pg C3

Bromus pubescens - - 2.06 pg C3

Schizachyrium scoparium - 21.19 - pg C4

Sorghastrum nutans - 3.26 - pg C4

Andropogon gerardii - 2.65 - pg C4

Carex artitecta - 12.71 - ps

Carex pensylvanica 9.69 - - ps

Eleocharis verrucosa 6.76 - - ps

Carex festucacea 6.26 - - ps

Carex hirsutella 4.99 - - ps

Carex blanda - - 2.36 ps

Carex radiata - - 1.92 ps

Rubus allegheniensis 13.59 - - shrub

Rubus flagellaris 7.53 - - shrub

Rosa carolina - 2.63 - shrub

Ulmus rubra - - 11.10 tree

Quercus stellata 3.65 1.82 - tree

Sassafras albidum 4.45 - - tree

Celtis occidentalis - - 3.33 tree

Cercis canadensis - - 1.99 tree

Parthenocissus quinquefolia 30.60 12.57 24.54 w vine

Toxicodendron radicans 5.04 1.55 2.17 w vine

Vitis riparia - - 2.86 w vine

Smilax hispida - - 2.14 w vine

% of IV 71.64 74.13 61.12

Summary Data

Species Density (1/4-m2 quadrat) 2.79 4.65 6.51

Species Diversity (H') 2.33 2.67 2.02

Appendix 1 continued

FLATWOODS BARRENS WOODLAND
40 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

FIRE AND FIRE SURROGATE STUDY: 

ANNOTATED HIGHLIGHTS FROM OAK-DOMINATED SITES

Daniel A. Yaussy1 and Thomas A. Waldrop2

1

Supervisory Research Forester, U.S. Forest Service, Northern Research Station, Delaware, OH 2

Team Leader, U.S. Forest Service, Southern Research Station, Clemson, SC 

DAY is corresponding author; to contact, call (740) 368-0101 or email at dyaussy@fs.fed.us

Abstract.—The National Fire and Fire Surrogate (FFS) study was implemented to investigate 

the ecological impacts of prescribed fire and mechanical operations to mimic fire in restoring the 

structure and function of forests typically maintained by frequent, low-intensity fires. Two of the 

12 sites were located in oak-dominated forests, one in Ohio and another in North Carolina. This 

paper summarizes results from these two sites that have been published in peer-reviewed literature, 

covering fire history, fuels and fire behavior, entomology, soils and belowground processes, wildlife, 

and vegetation. We concluded that the FFS treatments did little harm to this ecosystem, benefit many 

ecosystem components, and promote oak and hickory regeneration. These effects could be transient, 

however, and need to be studied over the long term to determine sustainability of the ecosystem.

INTRODUCTION

The National Fire and Fire Surrogate (FFS) Study was 

established in 2000 to compare ecological and economic 

impacts of prescribed fire and mechanical fuel-reduction 

treatments in forest types that developed under low 

intensity, high frequency fire regimes (Youngblood et al. 

2005). These treatments were chosen to restore ecosystem 

structure and resiliency to forests that have experienced 

fire suppression for several decades. Twelve independent 

study sites across the United States (seven in the West 

and five in the East; Fig. 1) received identical treatment 

(prescribed fire and mechanical fuel reduction treatments) 

and measurement protocols. Core variables collected 

at each of the 12 sites encompassed several ecosystem 

components: vegetation composition and structure, fuel 

loading and fire behavior, soils and forest floor physical 

and chemical properties, wildlife, entomology, pathology, 

and utilization and economics. Five western sites are 

dominated by ponderosa pine (Pinus ponderosa) and two 

are classified as mixed coniferous forests. Eastern sites 

consist of hardwood-dominated forests in the Central 

Appalachian Plateau in Ohio and Southern Appalachian 

Mountains of North Carolina, a pine-hardwood forest 

in the Piedmont of South Carolina, a forest dominated 

by longleaf pine (P. palustris) in Alabama, and a site 

dominated by slash pine (P. elliottii) in Florida.

Two FFS sites—the Southern Appalachian Mountain 

and Central Appalachian Plateau sites—are located in 

oak-dominated forests. Scientific information generated 

by these two sites has been disseminated to more than 

10,000 people during field trips. More than 50 scientific 

articles have been published in peer-reviewed journals or 

U.S. Forest Service publications. Downloadable versions 

of many of these publications are available through 

the www.treesearch.fs.fed.us Website. A listing of most 

FFS study articles may be found at the frames.nbii.gov 

website (click on the FFS link, then publications). In this 

paper we present an annotated reference list of some of 

the research highlights from these two oak-dominated 

sites to provide the readers with a sense of the breadth 

of the work conducted. Land managers may wish to 

use this publication as a starting point to find articles 

concerning the effects of fire and mechanical treatments 

on oak-dominated ecosystem components. In some 

cases, results reported in earlier articles (such as Rebbeck 

et al. 2004, Albrecht and McCarthy 2006, Long et al. 

2006, and Phillips et al. 2007) have been included or 

superseded by articles annotated here. Specifically, we 

will show that mechanical and prescribed fire treatments 

can restore a more open structure to oak-dominated 

forests of the Appalachians without causing harm to the 

ecosystem.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 41

SITE LOCATIONS

The Central Appalachian and Southern Appalachian 

study sites each consist of three replicate blocks, with 

four fuel reduction treatments applied to a randomly 

chosen treatment unit within each block. The Central 

Appalachian FFS site is located on the unglaciated 

Allegheny Plateau of southern Ohio. The climate of the 

region is cool temperate with a mean annual precipitation 

of 40.3 in and a mean annual temperature of 52.3 

o

F (Sutherland et al. 2003). The forests of the region 

developed between 1850 and 1900, after the cessation of 

cutting for the charcoal and iron industries (Sutherland 

et al. 2003). The current canopy composition differs 

little from that recorded in the original land surveys 

of the early 1800s. The most abundant species in the 

current canopy were white oak (Quercus alba), chestnut 

oak (Q. prinus), hickories (Carya spp.), and black oak 

(Q. velutina); however, the midstory and understory are 

now dominated by species that have become common 

in this community only in the last few decades (e.g., 

sugar maple [Acer saccharum], red maple [A. rubrum], 

and yellow-poplar [Liriodendron tulipifera]) (Yaussy et al. 

2003). The Central Appalachian FFS site is composed 

of three experimental blocks, with one each in the 

Figure 1.—Name and location of 12 Fire and Fire Surrogate (FFS) sites, showing nearest federal lands (western sites only), 

fire return interval (FRI), and elevational range (meters). Black shaded areas are federal lands adjacent to the western sites; 

lighter shading indicates ‘representative land base,’ or the area to which FFS results can be most directly applied for each site. 

Representative land bases are derived from EPA Type III Ecoregions: www.epa.gov/wed/pages/ecoregions/level_iii.htm. This 

paper deals specifically with the Central Appalachian Plateau and Southern Appalachian Mountain sites located in Ohio and 

North Carolina.

Southern Sierra Nevada

Sequoia-King Canyon

National Park/

Sequoia National Forest

Sierran Mixed Conifer

FRI: ~27 yrs (7-56 yrs)

1900-2150 m

Central Sierra Nevada

Eldorado/Stanislaus/Taos

National Forests

Sierran Mixed Conifer

FRI: ~5 yrs (4-28 yrs)

1100-1410 m

Blue Mountains

Wallowa-Whitman/Malheur

National Forests

Ponderosa Pine/Douglas-Fir

FRI: ~10 yrs (3-22 yrs)

1000-1500 m

Southern Cascades

Klamath National Forest

Ponderosa Pine/Red Fir

FRI: ~8 yrs (5-20 yrs)

1480-1780 m

Southwestern Plateau

Coconino/Kaibab

National Forests

Ponderosa Pine

FRI: ~5 yrs (2-10 yrs)

2100-2300 m

Northeastern Cascades

Onanogan-Wenatchee 

National Forest

Ponderosa Pine/Douglas-Fir/Grand 

Fir

FRI: ~15 yrs (10-20 yrs)

600-1300 m

Northern Rocky 

Mountains

Lolo National Forest

Ponderosa Pine/Douglas-fir

FRI: ~15 yrs (2-25yrs)

900-1400 m

Florida Coastal Plain

Pine Flatwoods

FRI: ~1.5 yrs (1-2 yrs)

< 100 m

Central Appalachian

Plateau

Oak Hickory 

FRI: ~10 yrs (3-15 yrs)

200-300 m

Southern 

Appalachian

Mountains

Appalachian Hardwood

FRI: ~10 yrs

300-900 m

Southeastern Piedmont

Piedmont Pine

FRI: ~15 yrs (1-30 yrs)

Gulf Coastal 200 - 300 m

Plain

Longleaf Pine

FRI: ~3 yrs (2-5 yrs)

< 100 m
42 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Raccoon Ecological Management Area (REMA), Zaleski 

State Forest (ZAL), and Tar Hollow State Forest (TAR). 

Funding for the initial implementation on this site of the 

FFS study was through a grant from the USDA-USDI 

Joint Fire Sciences Program.

The Southern Appalachian FFS site is located in the 

Green River Game Land in the Blue Ridge Physiographic 

Province, Polk County, NC. The climate of the region 

is warm continental, with a mean annual precipitation 

of 64.5 in and a mean annual temperature of 63.7 o

F 

(Keenan 1998). The forests of the study area were 80 

to 120 years old, and no indication of past agriculture 

or recent fire was present, though the historical firereturn interval prior to 1940 was approximately 10 

years (Harmon 1982). The most abundant species in 

the canopy were northern red oak (Q. rubra), chestnut 

oak, white oak, black oak, pignut hickory (C. glabra), 

mockernut hickory (C. tomentosa), and shortleaf 

pine (P. echinata). A relatively dense evergreen shrub 

assemblage was present in the understory of most of 

the study site, with mountain laurel (Kalmia latifolia) 

and rhododendron (Rhododendron maximum) the most 

common species. A grant from the National Fire Plan 

funds this site of the FFS study.

TREATMENTS AND

EXPERIMENTAL DESIGN

Each of the three replicate blocks in each site is composed 

of four treatment units. At the Central Appalachian site, 

individual treatment units were 47 to 64 ac whereas in 

the Southern Appalachian site they were approximately 

35 ac in size. A 164-ft x 164-ft grid was established in 

each treatment unit, and 10 sample plots of 0.25 ac were 

established randomly within each treatment unit. 

Treatments were randomly allocated among treatment 

units at each site. Treatments consisted of prescribed fire 

(B), a mechanical treatment (M), the combination of 

prescribed fire and mechanical treatments (MB), and an 

untreated control (C). In the Central Appalachian site, 

the M treatment involved a shelterwood harvest. This 

commercial operation reduced basal area from 125 to 88 

ft2

/ac. At the Southern Appalachian site, the M treatment 

was designed to create a vertical fuel break. Chainsaw 

crews removed all stems >6.0 ft tall and < 4.0 in d.b.h., 

as well as all mountain laurel and rhododendron stems, 

regardless of size. All detritus generated by the mechanical 

treatments was left on site in both areas.

M treatments were accomplished between September 

2000 and April 2001 in Ohio and between December 

2001 and February 2002 at the Southern Appalachian 

site. The prescribed fires were applied during MarchApril 2001 and 2005 in the Central Appalachian and 

March 2003 and 2006 at the Southern Appalachian 

site. The fires were applied on both the M and MB 

experimental units. These dormant-season fires consumed 

unconsolidated leaf litter and fine woody fuels while 

leaving most of the coarse woody fuels only charred. 

At the Southern Appalachian site, the fire prescription 

was also designed to kill ericaceous shrubs. Details of 

fire behavior are given by Iverson and others (2004a, b; 

2008) for the Central Appalachian and Tomcho (2004) 

and Waldrop and others (2008) for the fires at the 

Southern Appalachian site.

SEQUENTIAL ANNOTATIONS FOR

SELECTED REFERENCES

Fuels and Fire Behavior

Iverson, L.R.; Yaussy, D.A.; Rebbeck, J.; Hutchinson, 

T.F.; Long, R.P.; Prasad, A.M. 2004a. A comparison of 

thermocouples and temperature paints to monitor 

spatial and temporal characteristics of landscape-scale 

prescribed fires. International Journal of Wildland 

Fire. 13: 1-12.

A method to monitor fire behavior using rigid 

steel thermocouple probes is described and 

compared to the use of temperature-sensitive 

paints at the Ohio site. Different paints melt to 

indicate the maximum temperature recorded. 

The thermocouple probes can be programmed 

to record temperature at set intervals, such as 

every 2 seconds, to indicate not only maximum 

temperature, but the duration of increased 

temperature. Readings from the two methods 

corresponded closely with each other. Deployed 

on a 55-yd x 55-yd grid, these sensors each 

give readings that may be used to calculate fire 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 43

behavior metrics such as rate of spread and Byram’s 

fireline intensity. An illustration of prescribed fire 

movement through the ZAL burn treatments is 

included.

Graham, J.B.; McCarthy, B.C. 2006. Forest floor fuel 

dynamics in mixed-oak forests of south-eastern Ohio.

International Journal of Wildland Fire. 15: 479-488.

The authors examined fuel dynamics following 

the fire and thinning treatments at the Central 

Appalachian site to determine how these 

treatments influence the future fuel composition 

and structure in eastern mixed-oak forests. They 

found that the M treatment to create shelterwoods, 

increased 100-hr, 1000-hr sound, and coarse 

woody debris, and decreased 1-hr fuels 3 years 

after treatment, whether the units were burned or 

not. The M treatment without burning increased 

litter during this time. The B treatment increased 

1000-hr sound fuels and decreased 1000-hr rotten 

fuels. The MB treatments decreased 10-hr fuels 

and the duff layer. Unlike western FFS study sites 

where fuels accumulate over time, fuel inputs were 

balanced by rapid decomposition at this site.

Phillips, R.J.; Waldrop, T.A.; Simon, D.M. 2006. 

Assessment of the FARSITE model for predicting fire 

behavior in the Southern Appalachian Mountains.

Proceedings of the 13th biennial Southern Silvicultural 

Research Conference. Gen. Tech. Rep. SRS-92. 

Asheville, NC: U.S. Department of Agriculture, Forest 

Service, Southern Research Station: 521-525.

The authors wished to evaluate FARSITE by 

comparing fire behavior from simulations to that 

from a prescribed burn and to test the effects of 

different fuel treatments on fire behavior in the 

Southern Appalachian Mountains. Fire behavior 

was monitored using thermocouple probes 

deployed on a 55-yd x 55-yd grid. Fire behavior 

simulations produced by FARSITE were not 

adequate for use in the Southern Appalachian 

region using standard fire behavior fuel models 

(FBFM) with or without calibrations. The FBFM 

used in this version of FARSITE did not account 

for the high fuel moistures of the heavier fuels. The 

irregular fire shape caused by a linear drip torch fire 

front (as opposed to point-source ignition) resulted 

in higher rates of spread than those predicted by 

FARSITE. The flammability of the ericaceous 

shrubs was not adequately modeled in the FBFM. 

FARSITE 4.1.0 (which was not available at 

the time of this evaluation) incorporates many 

improvements that may make the software more 

robust for this region.

Hutchinson, T.F.; Long, R.P.; Ford, R.D.; Sutherland, 

E.K. 2008. Fire history and the establishment of oaks 

and maples in second-growth forests. Canadian Journal 

of Forest Research. 38: 1184-1198.

To better understand how past fires were related to 

tree establishment, dendrochronological analysis 

was conducted on trees which were harvested 

to create the shelterwood stand structure on the 

Central Appalachian site. The authors found 

mean fire intervals (average number of years 

between fires) varied between 9.1 and 11.3 yrs 

on the six mechanical treatment units between 

1870 and 1933. The oaks that were harvested 

originated between 1845 and 1900. Virtually no 

oaks established after 1925, close to the start of 

the fire suppression policies in Ohio. Harvested 

maples established after fire suppression. This 

finding supports the hypothesis that frequent, lowintensity surface fire was the ecosystem process that 

created the oak-dominated forests of today.

Soils and Belowground Processes

Iverson, L.R.; Prasad, A.M.; Hutchinson, T.F.; Rebbeck, 

J.; Yaussy, D.A. 2004b. Fire and thinning in an Ohio 

oak forest: grid-based analyses of fire behavior, 

environmental conditions, and tree regeneration 

across a topographic moisture gradient. In: Spetich, 

M.A., ed. Upland oak ecology symposium: history, 

current conditions, and sustainability. Gen. Tech. Rep. 

SRS-73. Asheville, NC: U.S. Department of Agriculture, 

Forest Service, Southern Research Station: 190-197.

The authors present a preliminary analysis of 

how fire behavior, seasonal soil temperature and 
44 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

moisture, canopy light penetration, and oak and 

hickory seedling and sapling populations vary 

among moisture classes and before and after the 

first season of treatments. Thermocouple probes 

were deployed on a 55-yd x 55-yd grid 1 in below 

the soil within the C and MB treatments located 

on the ZAL State Forest. These probes indicated 

higher soil temperatures on the MB treatments at 

all slopes and aspects than on the C treatment. This 

trend was evident from April through September. 

The vegetation analysis presented in this paper is 

included and updated in Iverson et al. 2008 (see 

below), and will not be commented on here.

Boerner, R.E.J.; Brinkman, J.A.; Yaussy, D.A. 2007. 

Ecosystem restoration treatments affect soil physical 

and chemical properties in Appalachian mixed oak 

forests. In: Buckley, D.S.; Clatterbuck, W.K., eds. 

Proceedings, 15th central hardwood forest conference. 

e-Gen. Tech. Rep. SRS-101. Asheville, NC: U.S. 

Department of Agriculture, Forest Service, Southern 

Research Station: 107-115 [CD-ROM].

This paper assesses the effects of the treatments 

at the Central Appalachian site on soil physical 

and chemical properties measured immediately 

post-treatment and 3 years post-treatment (prior 

to the second prescribed fire) and evaluates the 

impact that any effects might have on decisions 

to implement one or more of these management 

approaches more broadly. Mineral soil exposure 

was still significantly higher in the treated 

areas than in the C at the time of the second 

measurement. Soil pH increased after burning 

and persisted at higher levels for at least 3 years. 

Phosphorus availability decreased and remained 

lower in the B and MB areas through the 

second measurement. The Ca:Al ratio increased 

immediately after burning, but the effect was 

greatly reduced by the second measurement. There 

was no significant effect on Ca, K, or Al availability 

or soil compaction.

Boerner, R.E.J.; Coates, T.A.; Yaussy, D.A.; Waldrop, 

T.A. 2008. Assessing ecosystem restoration alternatives 

in eastern deciduous forests: the view from 

belowground. Restoration Ecology. 16:3, 425-434.

The article investigates whether any or all of the 

treatments would move these ecosystems toward 

the N-limited ecosystems that preceded fire 

suppression and heavy atmospheric N deposition. 

The authors found that treatment effects differed 

somewhat between the Southern and Central 

Appalachian sites. At the North Carolina site, 

all manipulative treatments initially resulted in 

reduced soil organic carbon content, C:N ratio, 

and overall microbial activity; however, only 

the reduced microbial activity persisted into the 

fourth growing season. At the Ohio site, the 

M treatment was the only manipulation that 

resulted in a significant change in these properties, 

with an initial increase in organic carbon and a 

decreased C:N ratio. Four years post-treatment, 

all treatments at this site were similar to the C. 

Using evidence from soil properties, the researchers 

concluded that mechanical treatments and a single 

prescribed fire did not result in progress toward 

ecosystems present prior to fire suppression.

Coates, T.A.; Boerner, R.E.J.; Waldrop, T.A.; Yaussy, 

D.A. 2008. Soil nitrogen transformations under 

alternative management strategies in Appalachian 

forests. Soil Science Society of America Journal. 72(2): 

558-565.

The authors wished to gain insight into the 

consequences of the management strategies 

represented by the FFS treatments to nitrogen 

availability. Treatment effects on available total 

inorganic nitrogen, nitrogen mineralization, and 

nitrification were measured at both the Central and 

Southern Appalachian sites, once pre- and twice 

post-treatment (prior to the second prescribed fire 

at each site). Changes in nitrogen transformations 

were modest and transient. Transformation rates 

were 2 to 10 times higher in Ohio than in North 

Carolina, which may be due to the inhibitory 

effects of the litter produced by the ericaceous 

shrubs present at the Southern Appalachian site.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 45

Insects

Campbell, J.W.; Hanula, J.L.; Waldrop, T.A. 2007. 

Effects of prescribed fire and fire surrogates on floral 

visiting insects of the Blue Ridge province in North 

Carolina. Biological Conservation. 134: 393-404.

This study was conducted to determine how 

various groups of pollinating insects vary in 

abundance and species richness in response to 

treatments at the Southern Appalachian site. 

The number of pollinators captured during 

two summers was highly correlated to change 

in basal area. Reduction of basal area by any 

of the treatments increased light to the forest 

floor, stimulating herbaceous plant growth and 

flowering. Insect pollinators, mostly bees, were 

captured in significantly higher numbers in MB 

sites than in other treatment areas.

Campbell, J.W.; Hanula, J.L.; Waldrop, T.A. 2007. 

Observations of Speyeria diana (Diana fritillary) 

utilizing forested areas in North Carolina that have 

been mechanically thinned and burned. Southeastern 

Naturalist. 6(1): 179-182.

The authors suggest that forest management 

practices that include fire with other disturbances 

may enhance food resources for the Diana 

fritillary. The Diana fritillary is considered a 

species of concern by the U.S. Fish and Wildlife 

Service. This lepidoptera is thought to be 

indicative of undisturbed communities. During 

the data collection for the pollinator study above, 

several males of this species were observed in two 

consecutive years on flowering sourwood trees 

(Oxydendrum arboretum) in the MB treatment 

areas only. Further study of the habitat preferences 

of this butterfly is needed.

Lombardo, J.A.; McCarthy, B.C. 2008. Forest 

management and curculionid weevil diversity in 

mixed oak forests of southeastern Ohio. Natural Areas 

Journal. 28(4): 363-369.

The purpose of this study was to determine 

whether stand level treatments affect the diversity 

and abundance of adult weevils at the Central 

Appalachian site. Weevils were collected from 

acorns following the second prescribed fire 

conducted 4 years after the first treatment. The 

authors found no discernable treatment effects 

on the number of weevils, but the manipulative 

treatments increased weevil species diversity over 

the C treatment.

Wildlife

Greenberg, C.H.; Tomcho, A.L.; Lanham, J.D.; 

Waldrop, T.A.; Tomcho, J.; Phillips, R.J.; Simon, 

D. 2007. Short-term effects of fire and other fuel 

reduction treatments on breeding birds in a Southern 

Appalachian upland hardwood forest. The Journal of 

Wildlife Management. 71(6): 1906-1916.

The FFS study afforded the authors the 

opportunity to examine whether and how the 

treatments would affect bird communities or 

individual species. Breeding bird surveys were 

conducted annually for 5 years on the Southern 

Appalachian site starting 1 year pretreatment. Four 

years after treatment, species richness and density 

increased on the MB treatment, while only species 

richness increased on the B treatment. The decline 

in the density of three species was associated with 

decreased leaf litter and shrubs. Shrub cover was 

reduced on all manipulative treatments compared 

to the C treatment. Leaf litter depth was similar on 

the C and B, lowest on the MB, and highest on the 

M treatments.

Greenberg, C.H.; Miller, S.; Waldrop, T.A. 2007. 

Short-term response of shrews to prescribed fire and 

mechanical fuel reduction in a Southern Appalachian 

upland hardwood forest. Forest Ecology and 

Management. 243: 231-236.

This study examined the FFS treatment effects on 

communities of shrews, an important component 

of the food web in southern Appalachian oak 

ecosystems. Shrew populations were followed the 

first and second years after prescribed fire at the 

Southern Appalachian site. During this period, 

the abundance of shrews was not significantly 
46 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

different in the treatments than in the C; however, 

the MB treatment had significantly fewer shrews 

than the M treatment. Shrew abundance decreased 

significantly between the first collection and 

the second, which was not associated with any 

treatment effects. There was no difference in 

macroarthropods between treatments. Leaf litter 

depth differed, with the highest depths occurring 

on the M treatment and the thinnest leaf litter on 

the MB replications. These results imply that the 

difference in shrew abundance was due not to food 

source but to habitat structure.

Greenberg, C.H.; Otis, D.L.; Waldrop, T.A. 2006. 

Response of white-footed mice (Peromyscus leucopus) 

to fire and fire surrogate fuel reduction treatments in a 

southern Appalachian hardwood forest. Forest Ecology 

and Management. 234: 355-362.

Mice are known to be important herbivores, 

predators, and prey in oak ecosystems. The 

authors examined the effects of the FFS treatments 

on habitat structure and white-footed mouse 

populations. Seventy-nine percent of the rodents 

caught at the North Carolina site were whitefooted mice. The number captured increased each 

year from pre-treatment to 2 years post-treatment 

on all treatments. The abundance of mice was 

no different on the M treatment than on the C 

for any year. The abundance increased on the B 

and MB treatments the first year after fire, but 

was significant only on the MB due to the high 

variability of collections.

Greenberg, C.H.; Waldrop, T.A. 2008. Short-term 

response of reptiles and amphibians to prescribed 

fire and mechanical fuel reduction in a southern 

Appalachian upland hardwood forest. Forest Ecology 

and Management. 255: 2883-2893.

Reptile populations appear to be more affected 

by practices which open the canopy than by 

prescribed fire. This study compares the effects of 

these two treatments, plus the combination of the 

two on reptile and amphibian populations. A total 

of 1,308 amphibians (13 species) and 335 reptiles 

(10 species) were captured over 4 years starting 1 

year pretreatment at the Southern Appalachian 

site. Few significant effects were observed for 

families or species for the manipulative treatments. 

All significant effects were increases in numbers 

captured or in species richness; no significant 

negative effects were observed.

Vegetation

Huang, J.; Boerner, R.E.J. 2008. Shifts in plant 

morphological traits and seed production of 

Desmodium nudiflorum following prescribed fire 

alone or in combination with forest canopy thinning.

Botany. 86: 376-384.

The researchers investigated the effects of the 

FFS treatments on Desmodium nudiflorum, a 

common perennial found across moisture and 

nutrient gradients of the Central Appalachian 

site. This long-lived perennial was chosen to 

represent understory herbaceous plants across the 

landscape. Plots were sampled during the summer 

on the C, B, and MB treatments at the REMA 

and ZAL replications four growing seasons after 

initial treatments and one growing season after the 

second prescribed fire (2004, 2005). Total plant 

biomass, seed mass, and seed production were 

significantly higher under either manipulative 

treatment. Specific leaf area (leaf area/leaf mass) 

was significantly lower under the manipulative 

treatments. This study found the B and MB 

treatments improve fitness for this species.

McCament, C.L.; McCarthy, B.C. 2005. Two-year 

response of American chestnut (Castanea dentata) 

seedlings to shelterwood harvesting and fire in a 

mixed-oak forest ecosystem. Canadian Journal of Forest 

Research. 35: 740-749.

Hybrid American chestnut seeds resistant to blight 

are soon to be released for outplanting to restore 

the species on the landscape. To quantify the 

forest structure most likely to produce successful 

plantings, 100 pure American chestnut seeds were 

planted in each of the replications and treatments 

of the Central Appalachian site prior to the second 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 47

growing season after initial treatments were 

installed. Eleven seedling variables were measured 

for two growing seasons including leaf, stem, 

root, fine root, and total biomass; leaf area; stem 

height; basal diameter; and root length. All of these 

variables were significantly and positively affected 

by each of the manipulative treatments, with 

the exception of root length in the B treatment. 

The authors conclude the proper environment to 

reintroduce hybrid American chestnut into the 

Appalachian forest would include open stands, 

possibly with a prescribed fire regime.

Joesting, H.M.; McCarthy, B.C.; Brown, K.J. 2007. 

The photosynthetic response of American chestnut 

seedlings to differing light conditions. Canadian 

Journal of Forest Research. 37: 1714-1742.

Using a subsample of the American chestnut 

seedlings in the paper cited above, the authors 

investigated the photosynthetic capabilities of 

leaves in the C and M treatments of the ZAL 

and REMA replications of the Ohio site. The 

leaves of seedlings growing in the M treatment 

assimilated CO2

 at higher rates than leaves from 

seedlings in the C treatment at all but the lowest 

light levels. There was no significant difference in 

the amount of N in the leaves between treatments 

and the amount of N was not correlated to any 

photosynthetic variables or canopy openness. The 

authors recommend forests with higher light levels 

than found in undisturbed forests for successful 

reintroduction of hybrid American chestnut.

Schelling, L.R.; McCarthy, B.C. 2007. Seed banks of 

mixed oak forest: effects of forest management on 

species composition and spatial pattern. Natural Areas 

Journal. 27: 320-331.

Soil samples were collected 3 years following 

initial treatment implementation on the ZAL and 

REMA replications of the Central Appalachian 

site to investigate the effects of the FFS treatments 

on the soil seed bank. Species composition of the 

seed bank contained in these samples did not differ 

significantly between treatments. As other studies 

have found, the composition of the seed bank 

was significantly different from the aboveground 

composition on all treatments, implying that many 

species present aboveground do not rely on banked 

seeds for regeneration success.

Chiang, J.-M.; McEwan, R.W.; Yaussy, D.A.; 

Brown, K.J. 2008. The effects of prescribed fire and 

silvicultural thinning on the aboveground carbon 

stocks and net primary production in an oak-hickory 

ecosystem in southern Ohio. Forest Ecology and 

Management. 255: 1584-1594.

With the concern over the carbon sequestration 

potential of forests, the authors examined the 

potential effects of the silvicultural treatments on 

carbon stocks. Annual net primary production 

(ANPP) was calculated for the treatments of 

the Ohio site for the first 4 years of the study. 

ANPP significantly decreased in the M and MB 

treatments the first year following harvesting 

due to the reduction in basal area. However, the 

decrease in ANPP did not persist into the second 

through fourth years, implying an equivalent 

amount of biomass was being produced with fewer 

trees than on the C and B treatments. Prescribed 

fire had no persistent effect on ANPP.

Lombardo, J.A.; McCarthy, B.C. 2008. Silvicultural 

treatment effects on oak seed production and 

predation by acorn weevils in southeastern Ohio.

Forest Ecology and Management. 255: 2566-2576.

To quantify the effects of the FFS treatments 

on mast production, acorns were collected from 

72 chestnut oak and 72 black oak trees evenly 

distributed within the treatments of the ZAL and 

REMA replications of the Central Appalachian 

site for the five growing seasons following initial 

treatment implementation. Black oak acorn 

production did not vary among the treatments 

and was greater and more consistent than the 

masting levels of the chestnut oak. After the second 

prescribed fire, the chestnut oaks in the M and 

MB treatments produced significantly more and 
48 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

smaller acorns than the chestnut oaks in the C and 

B treatments.

Yaussy, D.A.; Waldrop, T.A. In press. Delayed mortality 

of eastern hardwoods: a function of fire behavior, 

site, or pathology? In: Stanturf, J.A., ed. Proceedings, 

14th biennial southern silvicultural research conference. 

Asheville, NC: U.S. Department of Agriculture, Forest 

Service, Southern Research Station.

Overstory mortality was modeled using survival 

analysis for both Appalachian sites to investigate 

the effects of the FFS treatments on stand structure 

and composition. Mortality increased on the B 

and MB treatments the first growing season after 

prescribed fire and this increase persisted until the 

next fire. Mortality on the B and MB treatments 

increased even more after the second prescribed 

fire. The analysis indicated that maximum 

thermocouple temperature, preburn crown vigor, 

bark thickness, and duration of heating were the 

variables that explained most of the differences 

in mortality among treatments. Intense or slowmoving fires increase mortality of overstory trees, 

especially those of low vigor and thin bark, and the 

mortality may occur several years after burning.

Iverson, L.R.; Hutchinson, T.F.; Prasad, A.M.; Peters, 

M.P. 2008. Thinning, fire, and oak regeneration across 

a heterogeneous landscape in the eastern U.S.: 7-year 

results. Forest Ecology and Management. 255: 3035-

3050.

The authors wished to evaluate the longer-term 

effects of the FFS treatments on canopy openness 

and tree regeneration. Data were collected at the 

grid points of the C and MB treatments at the 

REMA and ZAL replications of the Ohio site, 

pretreatment, and during the first, fourth, and 

sixth growing season after treatment initiation. 

Abundance of small trees (<4 in d.b.h.) is reported 

for five size classes and several species across a 

moisture gradient. Oak-hickory regeneration > 

20 in tall, was less than 130 stems/ac on the MB 

grid points prior to treatment initiation. Two 

growing seasons after the second prescribed fire, 

oaks and hickories in these size classes averaged 

more than 930 stems/ac at dry gridpoints, and 

more than 685 stems/ac at intermediate gridpoints. 

There was little change at the mesic grid points. 

Each grid point was assigned an oak-hickory 

competition class based on density of seedlings, 

density of saplings, and competition. Maps are 

used to demonstrate the increase in oak-hickory 

competitiveness across the landscape as the result 

of moisture gradient and change in canopy 

openness.

Waldrop, T.A.; Yaussy, D.A.; Phillips, R.; Hutchinson, 

T.F.; Brudnak, L.; Boerner, R.E.J. 2008. Fuel reduction 

treatments affect stand structure of hardwood forests 

in Western North Carolina and Southern Ohio, USA.

Forest Ecology and Management. 255: 3117-3129.

To synthesize several years of data collection, 

summaries of the effects of the FFS treatments 

on vegetation over time are reported for both the 

Central and Southern Appalachian sites for up to 5 

years after initial study installation. Data following 

the second prescribed fire at the Ohio site were 

not available for this analysis. No attempt is made 

to compare the effects of treatments between the 

sites. The vegetation variables reported include 

basal area, mortality, density of regeneration and 

saplings (by species), shrub cover (by species), and 

ground layer cover (by plant type). Differences 

among treatments within sites can be explained 

by increased light availability (reduction in basal 

area), time since prescribed fire, and intensity of 

prescribed fire. Both sites indicate an increase in 

oak saplings on the MB treatment after the first 

prescribed fire.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 49

CONCLUSIONS

The FFS study was designed as a long-term investigation 

of the ecosystem consequences of the reintroduction 

of a fire regime or its mechanical surrogate. So far, 

the results from these two sites have shown that the 

treatments do little harm to the insects, wildlife, and 

belowground processes and may provide some benefits to 

many ecosystem components such as plant biodiversity. 

Significant large oak regeneration has developed at both 

sites with the MB treatment after two prescribed fires. 

Although more than 50 peer-reviewed articles have 

been published concerning the Southern and Central 

Appalachian sites of the FFS study, the results are 

preliminary. The treatments have changed the structure 

and composition of the forest, from the soils to the 

canopy. How long will these changes persist and what 

effects will a periodic burning regime have on the 

ecosystem? Currently, both sites are in a maintenance 

mode, where periodic prescribed fires are implemented 

every 3 to 5 years and rudimentary vegetation data 

are collected. Detailed fuel, wildlife, insect, and soils 

information will no longer be collected unless funding 

is obtained. The long-term effects of these restoration 

treatments on the ecosystem components for which the 

study was designed will be forfeited.

ACKNOWLEDGMENTS

This is Contribution Number 194 of the National Fire 

and Fire Surrogate Project, funded by the U.S. Joint Fire 

Science Program and the U.S. Forest Service through 

the National Fire Plan. The authors are the site managers 

for the Central and Southern Appalachian sites and 

are indebted to the land managers, scientists, students, 

field workers, and professional assistants who made 

this research possible. We also would like to recognize 

the other members of the Science and Management 

Integration Committee of the National FFS study 

for their support and cooperation throughout this 

continuing process.

OTHER LITERATURE CITED

Albrecht, M.A.; McCarthy, B.C. 2006. Effects of 

prescribed fire and thinning on tree recruitment 

patterns in central hardwood forests. Forest Ecology 

and Management. 226: 88-103.

Harmon, M.E. 1982. Fire history of the westernmost 

portion of the Great Smoky Mountains National 

Park. Bulletin of the Torrey Botanical Club. 109: 

74-79.

Keenan, S.C. 1998. Soil survey of Polk County, NC.

Washington, DC: United States Department of 

Agriculture, Natural Resources Conservation Service. 

218 p.

Long, R.P.; Apsley, D.K.; Rebbeck, J. 2006. Oak and 

maple stump sprout dynamics in response to 

thinning and burning treatments in southern Ohio.

In: Dickinson, M.B., ed. Fire in eastern oak forests: 

delivering science to land managers, proceedings of 

a conference; 2005 November 15-17; Columbus, 

OH. Gen. Tech. Rep. NRS-P-1. Newtown Square, 

PA: U.S. Department of Agriculture, Forest Service, 

Northern Research Station: 283.

Phillips, R; Hutchinson, T.F; Brudnak, L.; Waldrop, 

T.A. 2007. Fire and fire surrogate treatments in 

mixed-oak forests: Effects on herbaceous layer 

vegetation. In: Butler, B.W.; Cook, W., comps. The 

fire environment—innovations, management, and 

policy; conference proceedings; 2007 March 26-30; 

Destin, FL. RMRS-P-46CD. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station: 475-485. CD-ROM

Rebbeck, J.; Long, R.P.; Yaussy, D.A. 2004. Survival 

of hardwood seedlings and saplings following 

overstory thinning and prescribed fires in mixedoak forests of southern Ohio. In: Spetich, M.A., 
50 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

ed. Upland oak ecology symposium: history, current 

conditions, and sustainability. Gen. Tech. Rep. SRS73. Asheville, NC: U.S. Department of Agriculture, 

Forest Service, Southern Research Station: 275-284.

Sutherland, E.K., Hutchinson, T.F.; Yaussy, D.A. 

2003. Introduction, study area description, 

and experimental design. In: Sutherland, E.K; 

Hutchinson, T.F., eds. Characteristics of mixedoak forest ecosystems in southern Ohio prior to 

the reintroduction of fire. Gen. Tech. Rep. NE299. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northeastern Research 

Station: 1-16.

Tomcho, A.L. 2004. Effects of prescribed fire and 

understory removal on bird communities in a 

southern Appalachian forest. Clemson, SC: Clemson 

University. 72 p. M.S. thesis.

Yaussy, D.A., Hutchinson, T.F.; Sutherland, E.K. 2003. 

Structure, composition, and condition of overstory 

trees. In: Sutherland, E.K.; Hutchinson, T.F., eds. 

Characteristics of mixed-oak forest ecosystems in 

southern Ohio prior to the reintroduction of fire. 

Gen. Tech. Rep. NE-299. Newtown Square, PA: 

U.S. Department of Agriculture, Forest Service, 

Northeastern Research Station: 99-112.

Youngblood, A.; Metlen, K.L.; Knapp, E.E.; Outcalt, 

K.W.; Stephens, S.L.; Waldrop, T.A.; Yaussy, 

D.A. 2005. Implementation of the Fire and 

Fire Surrogate Study-a national research effort 

to evaluate the consequences of fuel reduction 

treatments. In: Peterson, C.E.; Maguire, D.A., eds. 

Balancing ecosystem values: Innovative experiments 

for sustainable forestry. Gen. Tech. Rep. PNWGTR-635. Portland, OR: U.S. Department of 

Agriculture, Forest Service, Pacific Northwest Research 

Station: 315-321.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 51

Fire and the endangered Indiana BAT

Matthew B. Dickinson1, Michael J. Lacki2, and Daniel R. Cox2

1 Ecologist, U.S. Forest Service, Northern Research Station, Delaware, OH 2 Professor (ML), Adjunct Assistant Professor (DC), Department of Forestry, University of Kentucky, Lexington, KY 

MBD is corresponding author: to contact, call (740) 368-0093 or email at mbdickinson@fs.fed.us

Abstract.—Fire and Indiana bats (Myotis sodalis) have coexisted for millennia in the central hardwoods 

region, yet past declines in populations of this endangered species, and the imperative of fire use in 

oak silviculture and ecosystem conservation, call for an analysis of both the risks and opportunities 

associated with using fires on landscapes in which the bat occurs. In this paper, we explore the potential 

direct effects of prescribed fire and associated smoke on Indiana bats. We identify the immediate 

effects on bats, such as exposure to smoke and displacement, when individuals are in tree roosts 

(under exfoliating bark or in crevices) and hibernacula (caves and mines). Radio-tracked northern 

long-eared bats (Myotis septentrionalis), an Indiana bat surrogate, flushed shortly after prescribed fire 

ignition in the Daniel Boone National Forest (Kentucky) on a warm spring day, confirming previously 

reported observations. We also consider the longer-term effects on bats of the habitat changes caused 

by fire use. Finally, we review National Forest Plans and ask how the available science supports their 

standards and guidelines. Efforts to manage Indiana bats are based on limited monitoring of the effects 

of habitat manipulations and a body of research that is deficient in key areas, providing a poor basis 

on which to either practice adaptive management or counter restrictions on growing-season burning.

INTRODUCTION

The Indiana bat (Myotis sodalis) is a rather small (6 

to 9 g), aerially feeding (insectivorous), tree-roosting, 

and migratory bat with a summer distribution that 

encompasses much of the Midwest, and portions of New 

England and the south-central states (Harvey et al. 1999, 

U.S. Fish and Wildlife Service [USFWS] 2007a). Tree 

roosting occurs under exfoliating bark and in crevices 

in dead trees (snags) and live trees. First reproduction 

for healthy females occurs in their first year and females 

can give birth to a single pup each year for 14 to 15 

years (Humphrey et al. 1977, Humphrey et al. 1977). 

Pregnant females and females with young aggregate in 

maternity colonies of tens to hundreds of individuals. 

The bat’s distribution is believed to be associated with the 

prevalence of limestone caves in the eastern United States 

(Menzel et al. 2001). Today, hibernacula include both 

caves and mines.

The species was listed as endangered on March 11, 1967, 

after winter populations declined significantly at the 

majority of known hibernacula (USFWS 2007a). Early 

recovery efforts focused on protection and rehabilitation 

of hibernacula, yet declines in populations of the species 

continued with an estimated 350,000 individuals 

remaining as of the 1997 census. Through the period 

of declines, losses in southerly hibernacula have been 

partially offset by increases in northerly hibernacula 

(Clawson 2002). Trends since 2001 have been upward, 

and 2007 population estimates reached approximately 

468,000 (USFWS 2008). On the negative side, mortality 

of Indiana bats associated with white-nose syndrome in 

the Northeast over the winter of 2007-2008 has been 

confirmed (USFWS 2009c).

Indiana bat foraging and roosting habitat includes 

forested areas outside of hibernacula used during the 

period of transition out of hibernation (staging), areas 

used during the warmer months of the year (summer 

habitat), and, again, areas outside of hibernacula 

used during the breeding period before hibernation 

(swarming). Indiana bats either stay close to hibernacula 

during the summer or migrate, with a maximum known 

migration distance of 520 km (Gardner and Cook 2002). 

Males and females have different roosting requirements 

during the summer; female Indiana bats form maternity 
52 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

colonies that use collections of snags and live roosts 

(Humphrey et al. 1977, Kurta et al. 1993, Callahan et al. 

1997, Britzke et al. 2003, 2006). During the swarming 

period, bats breed and must gain weight rapidly to 

prepare for hibernation (USFWS 2007a).

Implementing the widely advocated prescription for 

controlled burns to restore and maintain oak ecosystems 

(see papers in Dickinson 2006, Yaussy et al. 2008), the 

U.S. Forest Service (USFS) is carrying out prescribed 

fire treatments on oak forests, including those that occur 

within the distributional limits of the Indiana bat (e.g., 

Alexander et al. 2006, Lyons et al. 2006). For example, 

on the Daniel Boone National Forest, plans call for 

burning upwards of 22,700 ha/year within the next 

decade (Mann 2006). Use of growing-season burning 

as a silvicultural and ecological restoration tool in 

mixed-oak forests has been proposed and causes concern 

about increased risks to bats from the direct effects of 

smoke, yet holds promise for improving bat habitat. 

Growing-season burning is an emerging issue for which 

scientific information is needed on attendant risks and 

opportunities for bats.

Widespread use of fire might have both direct (shortterm) and indirect effects on bats. Direct effects include 

displacement, injury, and mortality. During fires, 

roosting bats may be exposed to heat from flames and 

the smoke plume. In addition, elevated concentrations of 

the products of combustion (e.g., carbon monoxide and 

irritants) occur over burn units and through the canopy. 

Exposure depends not only on fire behavior but also on 

roost characteristics, bat behavior, whether the bats are 

in torpor (a diurnal hibernation-like state, marked by a 

temporary decline in body temperature and metabolic 

rate), and bat gender and age. Risks from heat and gases 

probably would be greatest for nonreproductive bats in 

torpor, particularly if they are roosting near the ground 

or on dry landscape positions where smoke exposures are 

likely to be greatest. Reproductive female bats also use 

torpor though they appear to do so during conditions 

that would often not be conducive to burning. Arousal 

of bats from exposure to smoke in hibernacula is a 

concern relative to dormant-season burning. Bats arouse 

from hibernation periodically as a normal course of 

affairs, possibly because of the need to rehydrate, but 

each arousal is energetically equivalent to many days of 

hibernation (e.g., approximately 60 days for little brown 

bats [M. lucifugus] in the laboratory), and extra arousals 

from smoke exposure or other causes are a serious 

concern (Thomas et al. 1990, USFWS 2007a). 

Indirect effects of fire on bats arise from fire-induced 

habitat change. Fire use is generally advocated as a way 

of improving bat habitat, through snag production, 

creation of more open stands preferred for foraging, and 

increased insect abundance and diversity (e.g., USDA 

FS 2003, USFWS 2007a). Fire, alone or in combination 

with thinning, may affect bat roost availability. Fires both 

create and destroy snags, with unknown long-term effects 

in eastern hardwood forests. Fires would be expected to 

reduce insect prey abundances in the short run, but their 

long-term effects on prey abundances are unknown.

Krusac and Mighton (2002) estimate that 5.5 million 

ha of lands managed by the USFS occur within the 

distributional limits of the Indiana bat, though not 

all forests contain summer habitat. The discovery in 

1994 of a reproductive female bat on the Daniel Boone 

National Forest galvanized search and discovery of more 

reproductive females on other forests and, by way of the 

Endangered Species Act (1973), formal consultation 

between Forests and the USFWS. Since 1994, most 

National Forests within the range have revised their 

forest plans, including standards and guidelines intended 

to maintain and improve bat habitat and reduce risk to 

bats from management activities such as fire. State and 

private lands, which, combined, represent the majority 

of forest area in the East, presumably offer important 

habitat for bats, but little information is available on 

their importance for Indiana bats. Coordination efforts 

between state and private land managers and the USFWS 

have just begun.

Identifying the factors that have caused both the 

historical declines in Indiana bat populations, as well 

as recent increases, is central to recovery efforts (e.g., 

Caughley and Gunn 1995, USFWS 2007a). Authors 

have identified hydric habitats in the Midwest as core 

habitat supporting more robust maternity colonies than 

those that occur in upland forests, yet these habitats 

are severely diminished by conversion to agriculture 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 53

and other land uses (e.g., Carter 2005). Research in the 

forested Appalachians has shown that foraging bats use 

riparian habitats more heavily than they use such upland 

sites as undisturbed stands and stands impacted by an 

array of forestry practices (Owen et al. 2004, Ford et al. 

2005). Toxic effects of agricultural and other pesticides 

have potential, but unproven, negative consequences for 

bats (USFWS 2007a). The hibernation phase continues 

to be of concern because of bats’ exacting microclimatic 

requirements; changes in hibernation patterns, perhaps 

owing to climate change; responses to ongoing cave 

disturbance; and, most recently, succumbing to whitenose syndrome during hibernation. Research and 

monitoring should continue to focus on the effects of 

bottomland hardwood habitat loss, pesticide toxicology, 

and hibernation problems on Indiana bat populations in 

order to identify the most effective management actions.

While hydric and riparian habitats are crucial to Indiana 

bats’ life cycle, upland habitats are also used by Indiana 

bats for roosting and foraging during swarming, staging, 

and maternity periods. Furthermore, upland habitats are 

connected ecologically and hydrologically with riparian 

and hydric habitats. Because of the bat’s endangered 

status, considerable efforts, including forest burning, are 

being made on Federal lands to maintain and improve 

summer habitat for Indiana bats, yet it is not possible to 

say whether these efforts are leading to gains in Indiana 

bat populations and, if so, why. Given low rates of 

upland burning relative to historical levels, it is worth 

considering whether fire suppression has a role in bat 

population declines and whether seasonal restrictions 

on burning are counterproductive. In this paper, as the 

data permit, we focus on the direct and indirect effects 

of fire on Indiana bats in upland mixed-oak habitats. 

We first report results of a field study on behavior of an 

Indiana bat surrogate species during and in the days after 

a prescribed fire and the results of a literature survey of 

Indiana bat roost characteristics and roosting behavior. 

Then, we discuss potential short-term effects of upland 

fires on bats and the longer-term effects of fire on bat 

habitat (see also Carter et al. 2002). Finally, we examine 

National Forest Plan standards and guidelines with 

relevance to fire management and adaptive management 

of Indiana bats.

OBSERVATIONS ON NORTHERN

LONG-EARED BAT RESPONSE 

TO FIRES

The objectives of the following study were to document 

short-term behavioral response of tree-roosting bats to a 

prescribed fire. Longer-term responses will be reported 

in a forthcoming paper. Because no Indiana bats were 

captured as a part of this study, we chose the northern 

long-eared bat (M. septentrionalis) as a surrogate for the 

Indiana bat. The Indiana bat and the northern long-eared 

bat overlap in distribution, are similar in body mass and 

wing morphology, and form maternity colonies in live 

trees and snags during summer months (Foster and Kurta 

1999, Carter and Feldhamer 2005, Lacki et al. 2008).

Methods

Study Area and Burn Unit

The Bear Waller unit is located in Red River Gorge 

Geological Area, Daniel Boone National Forest, 

Kentucky (37° 51’N, 83° 39’W). The terrain of the 

region is characterized by dissected valleys, steep ridges, 

cliffs, and rocky outcrops, with elevations ranging from 

200-365 m (McGrain 1983). The forest community is 

typical of the Cumberland Plateau physiographic region 

in eastern Kentucky. Forest composition is primarily 

mixed mesophytic species,including several oaks (Quercus 

spp.), American beech (Fagus grandifolia), cucumber 

magnolia (Magnolia acuminata), maples (Acer spp.), 

tulip tree (Liriodendron tulipifera), white ash (Fraxinus 

americana), eastern hemlock (Tsuga canadensis), and 

several pine species (Jones 2005). The climate is moderate 

with average temperatures ranging from 16.6 °C to 

22.9 °C from May to August and an average annual 

precipitation of 101 cm.

The burn unit encompassed approximately 185 ha of 

uneven terrain and supported second-growth forest at the 

time of the burn event. A prominent ridgeline traverses 

the unit, where a storm blow-down occurred in the 

recent past. Thus, much of the ridgeline was overgrown 

with thick stands of greenbrier (Smilax rotundifolia) and 

red maple (A. rubrum) prior to burning. Two wildlife 

ponds are located in the immediate area, one of which is 

situated directly within the burn unit and is surrounded 

by a closed canopy of upland hardwoods. This pond 
54 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

served as the focal point for capturing bats. The burn unit 

was selected in collaboration with U.S. Forest Service 

personnel to meet both research and management needs. 

The burn unit had no history of management with 

prescribed fire; however, reports exist of “numerous fires 

having burned” within the original Cumberland purchase 

unit prior to 1930 (Collins 1975). An 8-ha wildland fire 

was documented near the center of the burn unit on Oct. 

30, 1994.

The experimental burn occurred on April 30, 2007 

and was conducted by Daniel Boone National Forest, 

Cumberland Ranger District staff. The ignition pattern 

consisted of igniting ridgelines with a drip torch and 

allowing the fire to back down slopes. Flame heights 

ranged from 0.2 to 2 m, but were typically <1 m. 

At the time of burn, new seasonal vegetative growth 

was abundant in the under- and overstory. Scattered 

smoldering and mid- and lower-slope flaming on the 

day after the burn produced low-level smoke exposures 

on ridges (see below); thus, the burn can be considered 

an early growing-season burn. Scattered snags and 

downed woody debris were found smoldering on the 

unit as late as May 9, 2007. For smoke monitoring, 

carbon monoxide sensors (Sixth Sense, Inc. Eco-Sense 2e 

electrochemical sensors with a custom electronics signal 

conditioning board) were placed at 2.4 and 6.1 m above 

ground on towers at three ridge locations within the burn 

unit.

Bat Capture and Tracking

We captured bats from April 22 to April 29, 2007 

using nylon mist nets (Avinet Inc., Dryden, NY) of 

varying widths. Nets were placed over the wildlife 

pond at the interior of the burn unit. We recorded 

gender, reproductive condition, body mass, and forearm 

length of each captured bat. Our netting effort in the 

surrounding area in summer 2006, along with 2007, 

resulted in no Indiana bat captures, so we chose to use 

the northern long-eared bat as a surrogate.

We fitted five adult northern long-eared bats (four 

females and one male) with 0.36 to 0.42 g transmitters 

(LB-2N, Holohil Systems Ltd., Carp, ONT) between the 

shoulder blades using Skinbon® adhesive cement (Smith 

and Nephew United, Largo, FL). We held bats with 

transmitters for 20 to 30 min to allow the adhesive to 

form a secure bond between transmitters and the dorsal 

surface of bats. Before release, we observed bats to ensure 

normal behavior and, thus, the safety of the animals, 

and to verify that transmitters were working properly. 

Transmitter load was 5.8 to 8 percent of the bats’ body 

mass.

We tracked radiotagged bats to roost trees each day 

with TRX-1000S receivers and three-element yagi 

antennas (Wildlife Materials Inc., Murphysboro, IL). 

Tracking continued until a transmitter battery failed 

or the transmitter was shed by the bat. Transmitters 

lasted for approximately 8 to 10 days and we report 

behavior up to 7 days post-burn in this paper. We 

determined coordinates for each roost tree using a 

geographic positioning system (GPS). For each roost tree 

we recorded species, whether the tree was alive or dead, 

height of the tree (m), and diameter of the tree (cm). 

When possible, we measured height of the roost (m), 

noted whether the roost was beneath a plate of bark or 

inside a crevice or cavity, and counted the number of bats 

exiting the roost on the night it was first discovered. 

On the day of the prescribed burn, we located roost 

trees of each radiotagged bat prior to ignition at 1620 

EST. Afterwards, two crew members were outfitted with 

receivers and stationed near roost trees known to be 

occupied by two of the radiotagged bats. A USFS Safety 

Officer monitored fire and smoke conditions near the 

telemetry crew to ensure a safety zone and an exit route. 

For safety reasons, the telemetry crew was required to 

work close to each other; thus, behavior of only two bats 

was monitored during the burn. Monitoring consisted 

of recording time of emergence, when bats were roosting 

or in flight, flight patterns, time spent in flight, and any 

other observations deemed pertinent. We monitored 

behavior of these bats until 1930 EST, at which time 

the general roosting positions of all five radiotagged bats 

was determined. On the day of the burn, we could not 

identify the specific roost trees of all bats prior to their 

exiting for nightly foraging because of time constraints 

and inaccessibility to habitats due to fire; however, by 

determining general roosting areas after the burn, we 

were able to confirm whether individual bats relocated 

during the fire.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 55

Home Range and Habitat Use

We used triangulation to determine location of 

radiotagged bats during nightly foraging. Triangulation 

began after bats left their respective roosts and continued 

until at least midnight each night. Two to three crew 

members were stationed at high elevation locations 

and recorded their position with a GPS. Simultaneous 

azimuths were taken and estimated foraging locations 

were derived by means of triangulation (White and 

Garrott 1990). We recorded azimuths at 3 to 5 min 

intervals and communicated via hand-held radios. We 

tracked individual bats in alternating 30-min time 

periods. Foraging data were collected on nights before 

and after the burn. We did not collect foraging data on 

the first night after ignition as a safety precaution.

We entered telemetry station locations and azimuths 

into the Locate 3.19 program to determine bat locations 

(Nams 2006). In all cases, two azimuths were used to 

determine a bat location. Studies with other animal 

species have shown that use of >2 azimuths does 

not necessarily increase accuracy or precision when 

radiotracking (Nams and Boutin 1991). We limited 

home range calculations to bats with ≥ 30 locations, 

although 50 locations are considered to be optimal 

(Seaman et al. 1999). We used ArcGIS version 9.2 

(ESRI, Redlands, CA) to calculate 95-percent home 

ranges using Hawth’s Tools extension version 3.27 

(Beyer 2004). We generated pre- and post-burn estimates 

of home range size for bats where data were sufficient. 

We evaluated use of the burn unit by bats while foraging 

relative to timing of the burn. We compared percentage 

of radiolocations on the burn unit to those off the burn 

unit before and after the burn and across radiotagged bats 

using a chi square test of homogeneity (Daniel 1974).

Results

Response of Northern Long-Eared Bats to Fire

Northern long-eared bats demonstrated an average home 

range of 59.6 ± 1.84 (SE) ha, with a male B7 possessing 

the smallest home range (Table 1). One female B10 was 

not recorded after the night of tagging and release. We 

had sufficient data to derive home range estimates for 

two bats pre- and post-burn. Female B5 demonstrated 

a home range of 41.4 ha pre-burn, which increased to 

74.7 ha following the burn. In turn, male B7 possessed a 

home range of 60.9 ha before the burn, which declined 

to 46.1 ha post-burn.

Use of foraging habitat was significantly different among 

bats (χ2

 = 157, df = 9, p < 0.005). Female B5 and male 

B7 spent the majority of time foraging over the burn 

unit, both pre- and post-burn (Table 1). Female B9, not 

tagged until just before the burn, foraged exclusively over 

the burn unit following the burn. Only female B11, the 

lone pregnant female that we tracked, foraged more often 

off the burn unit than over the burn unit after the burn 

was completed.

Northern long-eared bats were tracked to nine roost 

trees of four species, the majority of which were oaks 

(Table 2). Of these, 77.8 percent were live trees with 

Table 1.—Sex, reproductive class, body mass, and spatial data for northern long-eared bats radiotracked on and 

adjacent to the April 30, 2007, Bear Waller burn on the Daniel Boone National Forest, KY

Pre-burn Post-burn

Sex/

ID no.

Female

reproductive

class

Body

mass

(g)

Home range

size

(haa

)

% locations (# locations) % locations (# locations)

on unit off unit on unit off unit 

Female (B5) nonreproductive 5.25 64.9 100 (32) 0 (0) 75 (30) 25 (10)

Female (B9) nonreproductive 5.25 59.1 no datab no data 100 (24) 0 (0)

Female (B10) nonreproductive 6.0 -

c no data no data no data no data

Female (B11) Pregnant 7.25 57.5 no dataa no data 23 (11) 77 (37) 

Male (B7) - 5.75 56.8 86 (32) 14 (5) 100 (45) 0 (0)

a

Conversion to acres: 1 ha = 2.47 ac.

b

Bats B9 and B11 were captured the night prior to the burn, so no pre-burn foraging data are available.

c

Bat B10 was not located during nightly foraging in the vicinity of the burn unit.
56 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

bats roosting in cavities and crevices and beneath bark. 

Diameter of roost trees averaged 38.4 ± 4.37 cm and 

ranged from 18.1 to 57.1 cm. Height of roost trees 

averaged 24.3 ± 1.86 m and ranged from 12.2 to 32.0 

m. Height of roosts aboveground averaged 13.4 ± 2.96 

m and ranged from 7.6 to 22.9 m. Maximum size of 

maternity colonies varied from 1 to 39 bats, with an 

average of 15.5 ± 5.41 bats. The lone roost recorded 

for male B7 was a white oak and he was the only bat 

observed exiting the tree.

Day of the burn. We were able to locate roost trees for 

four bats immediately before the burn; however, the 

roost tree of the remaining bat was known to be within 

the burn unit. The male and female bats we tracked 

during ignition operations and the main burning period 

(B7 and B9) displayed similar behavior. The ignition line 

ran within 20 m of roost trees of each bat, and both bats 

exited their roosts within 10 min of ignition near their 

respective roosts (between 1640 and 1650 EST). The two 

observers, one monitoring each bat, were approximately 

30 m from the respective roost tree. Ambient 

temperature was approximately 31 °C (88 °F). Both bats 

flew for about 45 min after initially leaving their roosts, 

then roosted for about 1 hr. They cycled through periods 

of flight and roosting during the burn.

Because of burning conditions and safety constraints, we 

could not determine whether bats returned to their prefire roosts, but they did return to the vicinity. Both bats 

continued with an alternating flying and roosting pattern 

until sunset, when they emerged to forage. The time the 

bats spent roosting increased as the day progressed. While 

in flight, bats concentrated their activity over habitat that 

the fire had not yet reached, such as upland drainages 

that were slow to burn. Moreover, both bats were 

originally roosting on the north side of the burn unit near 

the ignition line; however, they chose to fly in the area 

opposite of the ignition line where the backing fire and 

smoke had not yet reached. We assume that bats were 

attempting to limit their exposure to conditions created 

by fire. At no point did they fly outside of their typical 

home range area, nor did they travel far from the burn 

itself. Although no behavioral data were collected for the 

remaining radiotagged bats, these bats behaved similarly 

to the bats that were monitored, all having switched 

roosts at some point during the fire. A roost tree that had 

been used by female B5 before the fire fell after its base 

was weakened by smoldering combustion; all other roosts 

remained standing. All bats were located within the burn 

unit following the burn.

Days 1 and 2 after the burn. Fire was still spreading 

in some areas of the burn unit the day after the burn 

and smoke was present on the unit and in adjacent 

forest. Peak carbon monoxide (CO) concentrations of 

50-190 parts per million (ppm) were measured at 2.4 

m aboveground at three stations on the second day 

Table 2.—Description of roosts of northern long-eared bats located on the Bear Waller burn unit on the 

Daniel Boone National Forest, KY

Species

Live

vs.

dead

Roost

type

(m)

Roost

height

size

Estimated

colony

(cm)

Tree

diameter

(m)

Tree

height

Quercus prinus live cavity 17.7 29 30.4 22.6

live -

a - 1 57.1 27.4

live crevice 22.9 29 53.5 29.0

Q. coccinea live - - 6 37.3 24.7

live - - 1 49.5 24.4

Q. alba live bark 7.6 1 36.5 32.0

Acer rubrum live - - 1 24.3 21.3

Unknownb dead cavity 7.6 39 18.1 8.5

dead crevice 10.4 18 38.8 12.2

a

Specific roost location could not be identified.

b

Snags were in an advanced stage of 

decay, preventing species identification. 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 57

compared with concentrations of 350 to >400 PPM 

during burning the first day (CO sensors saturated at 

400 PPM on one of three stations). Concentrations 

of CO during the night after ignition approached 

background. Two sensors at 6.1 m failed so only 2.4 

m data are provided as an indication of relative smoke 

concentrations during the second day. All five bats 

roosted near the core of the burn unit on the day after 

the burn. That night we observed very few insects flying 

within the burned area. We observed male B7 foraging 

farther away from where he had been typically foraging, 

moving down-slope, and closer to the burn unit 

boundary near areas that had not burned. Female B5 

foraged normally for the first hour after emergence then 

altered her foraging behavior from previous nights by 

foraging in areas where she had not been recorded. She 

covered a considerable distance, sometimes leaving the 

range of detection. She returned to her usual foraging/

roosting area at 0200 hr. It rained all day the second day 

following the burn and no data were collected.

Days 3-7 after the burn. It rained sporadically throughout 

day 3. Logs and stumps remained burning, with 

continued smoke production and haze. Flying insects 

were scarce. Female B10 shed her transmitter, and no 

signal was received on male B7. Although Female B5 was 

found roosting away from the burn site, we could not 

find the roost tree. That evening, she exited her roost and 

was tracked for about 30 min before we lost her signal. 

She was not recorded again that evening. Steady rain fell 

during days 4 and 5 after the burn and no tracking was 

attempted.

Despite the rain, some downed logs remained 

smoldering on day 6. Flying insects were more prevalent. 

No signal was received from female B5, but she returned 

on the evening of day 7 and foraged in the burn unit and 

surrounding habitats. Male B7 was observed foraging 

downslope near the burn unit boundary on the evenings 

of both days 6 and 7. From our observations, overall 

foraging behavior of all four remaining radiotagged bats 

during the evenings of days 6 and 7 appeared to return 

to pre-burn norms in terms of emergence time, length 

of foraging bouts, and use of the burn unit and adjacent 

habitats.

INDIANA BAT ROOSTING

CHARACTERISTICS

We review studies which report information on roost 

trees in order to better quantify what constitutes a quality 

roost and to assess bat risk during fires relative to the 

aboveground height at which they roost.

Literature Review Methods

We used data available in published studies on summer 

habitat of the Indiana bat to examine frequency 

distributions of roost tree diameter and height and 

the height of roosting sites above ground (sources are 

provided in Lacki et al. 2008). We combined data from 

all habitats across the range of the Indiana bat, though 

lack of data prevented us from comparing maternity 

and other roosts and roosting behavior by gender. We 

evaluated predictive capability of roost characteristics by 

developing regression models of roost height as a function 

of tree diameter and tree height using mean values per 

published study and, where available, for individual roost 

trees (SAS Institute, Inc., Cary, NC, 2003).

Results

Too few data were available for male roosts and roosts 

used by both males and females to allow any comparison 

with female-only roosts. Hereafter, we focus on 

female-only roosts (primary maternity and other roosts 

combined). Individual roost data demonstrated that roost 

trees selected by female Indiana bats exhibited a modal 

peak at 40-cm diameter (Fig. 1a). Bats used trees of a 

wide range of heights, with a mode at 25 m (Fig. 1b). 

Height at which Indiana bats roosted demonstrated a 

distribution that was skewed left, with the modal peak at 

10 m (Fig. 1c). The studies that report individual roost 

information, and which provided data for Figures 1a-c, 

largely included bottomland hardwoods and trees in 

swamps and it is not clear how relevant these data are to 

uplands. To avoid habitat-related bias, mean heights at 

which bats roosted reported in studies from across the 

bat’s range were averaged, providing a mean roosting 

height of 9.12 m (N=13 studies, SD=2.14, 95% CI 

4.92 to 13.3 m). From the few studies in which roosting 

heights were reported (Fig. 1c), the mean roosting height 

was 8.03 m (N=18 studies, SD=3.27, 95% CI 1.62 to 
58 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

0

1

2

3

4

5

6

7

8

9

No. Roosts

< 2.5 5 7.5 10 12.5 15 >15

Roost Height (m)

c 

Figure 1.—Frequency distributions of female Indiana bat roost trees (maternity 

roosts and other) by (a) tree diameter, (b) tree height, and (c) roosting height 

aboveground. Sources for data are provided in Lacki et al. (2008).

0

2

4

6

8

10

12

14

16

18

No. Roosts

< 20 30 40 50 60 70 > 70

Tree Diameter (cm)

0

1

2

3

4

5

6

7

8

9

10

No. Roosts

< 10 15 20 25 30 > 30

Tree Height (m)

1(b) 

1

a

0

2

4

6

8

10

12

14

16

18

No. Roosts

< 20 30 40 50 60 70 > 70

Tree Diameter (cm)

0

1

2

3

4

5

6

7

8

9

10

No. Roosts

< 10 15 20 25 30 > 30

Tree Height (m)

b 

1
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 59

14.4 m). The lowest female roosting heights reported are 

2 m (USFWS 2007b), 3.0 m (Belwood 2002), and 4.0 m 

(Butchkoski and Hassinger 2002).

From the few data that were available, male Indiana bat 

roost diameter averaged 34.0 cm (N=5, range 14-61 cm), 

tree height averaged 21.7 m (N=3), and roost height 

averaged 8.33 m (N=3). The diameter of combined male 

and female roosts averaged 33.2 cm (N=3) and there 

were no data for roost tree height and roosting height.

Regression models predicting the height aboveground of 

Indiana bat roosts demonstrated significant relationships 

with tree diameter and tree height when mean values per 

population were used for analysis (Table 3). Regressions 

based on these independent variables accounted for 

similar percentages of variation in roost height as 

indicated by R2

 values. These relationships did not hold 

up when data from the few studies where individual roost 

tree information was used for analysis, accounting for no 

more than 6 percent of the variation in height of roosts 

aboveground.

Discussion

Short-term Effects of Fires on 

Tree-Roosting Bats

Smoke Effects in Summer Habitat

In prescribed surface fires, bats in roosts are exposed to 

gases and heat in the plume generated by the spreading 

fire. Exposures would depend on how high bats roost 

aboveground, bat physiological condition and flushing 

behavior, behavior of the fire (e.g., fuel consumption 

and fireline intensity), winds, terrain, and whether the 

canopy is leafless. If bats are in torpor or if flightless 

pups are present and too heavy to be carried, one can 

assume full exposure. Hot gases in the plume are mixed 

rapidly into the types of roosting sites (e.g., exfoliating 

bark, crevices) used by Indiana bats; these kinds of 

sites afford little protection (unpublished data, Guelta 

and Balbach 2005). Based on extrapolation from other 

species, incapacitation from carbon monoxide exposure 

would be expected if bats were exposed to >1000 PPM 

concentrations for 25 minutes or more and for shorter 

time periods if concentrations were higher (Spietel 

1996). From our unpublished field data, incapacitating 

exposures are highly unlikely at any height above flames. 

Acting to reduce risk, irritants in smoke (e.g., acrolein, 

formaldehyde) cause an immediate reduction in breathing 

rate and depth (Chang et al. 1981). Elevated CO2

 levels 

would cause the opposite effect, but only if exposures 

were longer than several minutes (Purser 2002). Low 

breathing rates during torpor (e.g., Morris et al. 1994) 

would also reduce bat exposures to harmful gases.

A greater risk for bats might be external (skin) burns, 

which are a function of gas temperatures, their flow 

velocity, and skin properties (e.g., Diller et al. 1991). 

Skin burns could be a significant risk for bats roosting 

close to the ground and for those roosting at average 

heights above fires of intensities on the high end expected 

from prescribed burns (unpublished data). An ongoing 

project is analyzing smoke production and transport 

across burn units and bat toxicology for a range of 

prescribed fire scenarios.

Table 3.—Regression models predicting height of roosts aboveground for Indiana bats based on tree 

diameter (cm) and tree height (m). Models were developed using mean values per population, and data 

for individual roost trees where available. Published sources are from Lacki et al. (2008).

Form of data Regression R2 F-value P-value

Mean values per 

population

Roost height = 

0.163(treediameter) + 2.75

0.27 4.15 0.07

Roost height = 

0.363(treeheight) + 1.77

0.33 5.47 0.04

Data for individual 

roost trees

Roost height = 

-0.04(treediameter) + 9.56

0.01 0.19 0.67

Roost height = 

0.135(treeheight) + 5.67

0.06 0.96 0.34
60 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

From available observations, it seems reasonable to 

assume that bats exposed to smoke would flush if they 

could. All four northern long-eared bats located by radio 

tracking before and after a fire changed roosts during the 

burning period. A male and female bat tracked during 

the fire flushed within 10 minutes of nearby ignition, 

suggesting that both females and males were able to 

emerge from roosting sites in sufficient time (<10 min) to 

avoid direct impacts from heat and smoke produced by 

this prescribed fire conducted on a warm day. Roosting 

heights and roost characteristics for these northern longeared bats were similar to those reported for Indiana 

bats, though most roosts were live trees (compare Table 

2 and Fig. 1; see Lacki et al. 2008). Observations from 

other fires confirm our findings on bat movement during 

fires, for instance Rodrigue et al. (2001) report flushing 

of a roosting Myotis bat. Red bats (Lasiurus borealis) are 

a particular concern because they hibernate in the leaf 

litter during cold weather and have been shown to flush, 

or attempt to flush, from in front of fires (Saugey et al. 

1989, Moorman et al. 1999). Rodrigue et al. (2001) also 

observed two red bats leaving a burn unit during a fire. 

Female bats are able to carry their young for some time 

after birth, which may reduce vulnerability (Carter et al. 

2002). A drawback of flushing from fires is that bats may 

experience increased predation risk (Carter et al. 2002).

Risk Associated with Torpor

Risk to bats should be, in part, dependent on whether 

they are in torpor at the time of the burn and whether 

they can perceive a fire and arouse. Red bats, a species 

that roosts or hibernates on the ground during cold 

periods in oak forests, where fire is frequent, were shown 

to arouse in the laboratory at a 5 °C ambient temperature 

within 10-40 min in response to a combination of the 

sound of fire and smoke exposure (Scesny 2006). Little 

brown bats’ arousal at 5 °C body temperature occurred in 

an average of 44 min (Thomas et al. 1990). Arousal time 

in a small insectivorous marsupial was found to increase 

exponentially as body temperatures tracked declining 

ambient temperatures (Geiser 1986); presumably, a 

similar pattern holds for bats (Carter et al. 2002).

Small mammals that use torpor often use energy available 

in their environment to passively maintain high body 

temperatures and facilitate rewarming (Hamilton 

and Barclay 1995, Lovegrove et al. 1999, Geiser and 

Drury 2003, Geiser et al. 2004). High solar exposure at 

Indiana bat maternity roosts aids in maintaining high 

body temperatures (USFWS 2007a). In contrast, male 

red bats in the Ouachita Mountains of Arkansas were 

found to prefer microsites with low solar exposure (north 

slopes and drainages) during hibernation in leaf litter, 

presumably because of the cooler and more constant 

temperatures they provided (Saugey et al. 1989).

It would be expected that pregnant or lactating female 

Indiana bats would use torpor less often than males and 

nonreproductive females because of a need to sustain 

high metabolic rates. Data from Kurta et al. (1996) 

demonstrated that adult female Indiana bats in Michigan 

sustained body temperatures of 35 o

C for up to 12 hrs 

inside diurnal roosts and some bats sustained temperatures 

at that level for up to 6 consecutive days, suggesting that 

these individuals would be able to respond fairly quickly 

to an oncoming fire. On the other hand, studies on other 

species have demonstrated declines in body temperatures

in reproductively active female bats after diet restriction, 

such as would happen after poor foraging success (Kurta 

1991, Audet and Thomas 1997). Willis et al. (2006) 

demonstrated multi-day bouts of torpor in pregnant 

female bats during spring storms just prior to giving 

birth. Thus, at least periodically, maternity colonies may 

be at increased risk from fire because adult females may 

be in torpor. However, periods during which torpor is 

most likely would seem to coincide often with cool and/

or wet periods and, thus, poor burning conditions.

Field studies found that male and nonreproductive 

female big brown bats (Eptesicus fuscus) select cooler 

roosts than reproductive females (Hamilton and Barclay 

1995) and males enter torpor more regularly than 

reproductive females (Grinevitch et al. 1995). Given that 

male Indiana bats have a tendency to roost in smaller 

trees that are less exposed to solar radiation (Kurta 2005), 

we may assume that male Indiana bats also use torpor 

regularly. More data on roost microclimates and torpor 

dynamics for bats inside tree roosts and their relation to 

prescribed burn restrictions and prescriptions are needed 

to address issues of roost site selection and vulnerability 

of bats to prescribed fire (Boyles 2007).
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 61

Roost Characteristics

Roost characteristics, such as height above ground, snag 

condition, and landscape position, would also influence 

risk from fire. Because plumes radiate heat and mix 

rapidly with ambient air, the higher the roosting location 

on a snag or live tree, the lower the expected exposure to 

heat and gases, given similar fire behavior and ambient 

weather conditions. Our review of studies that provide 

Indiana bat roosting data (above, Lacki et al. 2008), 

particularly studies that compare roosts with random 

potential roosts (see Kurta 2005), support the expectation 

that reproductive and nonreproductive bats prefer larger 

than average, but otherwise suitable, roost trees. For 

fire effects, this preference is potentially important in 

that roosting locations in large trees tend to be higher 

above ground (Table 3, Kurta et al. 2002). Even though 

we found considerable variability in Indiana bat roosttree height, data suggested that a minimum height of 

approximately 10 m is necessary before a live tree or snag 

is sufficiently tall to be desirable as even a secondary roost 

tree. Decay patterns of snags often lead to the loss of the 

top of the stem, reducing the height of the snag (Hunter 

1990).

Fire Behavior

Smoke exposures determined by fire behavior are a 

realm over which the fire manager has substantial 

control through choice of burning conditions and firing 

methods. Fire managers are well versed in using ignition 

to influence fire behavior and fire effects on vegetation. 

In an ongoing fire-monitoring project on Appalachian 

landscapes, we documented the dramatic differences in 

heat and smoke release rates from ridge ignition (where 

the bulk of behavior is low-intensity backing spread) 

and a combination of helicopter ignition and strip head 

firing (where more high-intensity uphill runs occur). On 

flat ground, low heat release rates (where heat release 

rate is proportional to flame length and fireline intensity, 

kW/m) and the presence of wind will result in reduced 

exposures to high temperatures in plumes (Mercer and 

Weber 1994).

Terrain complicates exposures because of upslope flow 

of smoke and potential positive feedbacks between the 

plume and the fire. Smoke rising off burn units in a 

single plume core would be expected to cause increased 

gas and heat exposures in the canopy where the plume is 

centered relative to exposures resulting from smoke that 

is distributed among multiple plume cores (Achtemeier, 

this volume). In hilly landscapes, we would expect plume 

cores to be located along ridgelines above dry slopes and 

result in the greatest smoke exposures in those locations. 

We would expect lower exposures to daytime smoke at 

roosts at lower elevations and in landscape positions that 

provide topographic shading during the fire season (e.g., 

north-facing slopes during the winter and early spring). 

Choice of burning weather and season are well-known 

methods of manipulating fire behavior and, thus, smoke 

exposures. Burning weather, of course, affects fuel 

moisture and winds, both key determinants of smoke 

production rates and transport. Evidence suggests that 

growing-season burns in mixed-oak forests are more 

effective as a tool for control of oak competition than 

dormant-season burns (Brose and Van Lear 1998), and 

should often be less intense because of more fuel shading, 

lower litter loads, and higher humidity. In addition, bats 

in torpor during the growing season may arouse more 

quickly than in the dormant season given higher ambient 

temperatures. An interesting feature of growing-season 

burning relative to smoke exposures will be the effect of 

the canopy, with smoke expected to disperse less readily 

through a leafed-out canopy in general and to exit the 

canopy preferentially through gaps.

Smoke Exposures in Hibernacula

Smoke intrusion into hibernacula is a concern because 

of the potential for inducing arousal in hibernating 

bats. Though no Indiana bats were present, one study 

documented smoke intrusion into hibernacula in 

Missouri, but no arousal was observed (Caviness 2003). 

Except at the northernmost part of the distribution of 

Indiana bats, suitable hibernacula require chimneyeffect airflow and large cold-air traps to maintain ideal 

temperatures, which are below annual mean ambient 

temperature (Tuttle and Kennedy 2002). Chimney-effect 

airflow occurs when two cave or mine entrances are at 

different elevations and outside temperatures fall below 

the annual mean (which is approximated by the cave 

walls); air flows out of the upper entrance and in the 

lower entrance (Tuttle and Taylor 1998). This airflow 

creates the potential for smoke intrusion into hibernacula 
62 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

(Carter et al. 2002) perhaps especially during cold fall, 

winter, and spring nights. Nighttime inversions during 

this period may be of particular concern and inversion 

climatologies, where seasonal climate and landscape 

characteristics are used to determine the potential for 

smoke accumulation (Ferguson et al. 2003), may be 

a good place to start for evaluating risk to individual 

hibernacula.

Fire and Bat Habitat

Fire may have short-term effects on bats through heat 

and gas exposures, but fire also affects bat habitat. 

Habitat effects have been assumed to include increased 

roost availability, facilitation of foraging from reduced 

clutter, and increased insect prey productivity (USDA FS 

2003, USFWS 2007a). Roost availability is dependent on 

both the quality of individual roosts and the population 

dynamics of roosts. For Indiana bats, the epitome of a 

high-quality primary maternity roost appears to be a large 

dead tree, exposed to solar radiation, with large plates 

of sloughing bark (Kurta et al. 1993, Foster and Kurta 

1999, Carter and Feldhamer 2005, Lacki et al. 2008). 

Alternate roosts, including live trees and other snags, 

are also important even though they shelter relatively 

few bats and seemed to be used mostly during periods 

of warm ambient temperatures and high precipitation 

(Humphrey et al. 1977, Gardner et al. 1991, Kurta et al. 

1993, Miller et al. 2002). Maternity colonies may occupy 

one or more primary roosts. Males use smaller trees than 

females, on average (Kurta 2005).

Published data on summer-roosting behavior of Indiana 

bats, including nonreproductive males, suggest that bats 

select roost trees based on size (e.g., diameter) and that 

stands possessing trees exceeding 40 cm diameter at 

breast height (d.b.h.) are more likely to provide adequate 

maternity habitat for this species (Fig. 1). Our literature 

survey results are based on the roost trees that were 

available to bats on the landscapes they use. Given the 

documented preference for larger- than-average roost 

trees (Kurta 2005), it is likely that even larger roost trees 

would have been used if they had been available to bats 

in the published studies. Along these lines, Callahan et 

al. (1997) recommended promoting the development of 

forested stands possessing large-diameter, mature trees to 

provide adequate maternity habitat for the Indiana bat. 

Further, Carter and Feldhamer (2005) suggested that 

snag creation within stands of mature timber may be 

necessary for sustaining maternity habitat of this species 

in perpetuity. An implication of our results showing the 

importance of tree size is that, when calculating potential 

densities of snags and live roosts in forested stands to 

evaluate quality of maternity habitat for Indiana bats, 

managers should place the greatest weight on potential 

roost trees ≥ 40 cm in diameter and ≥ 10 m in height. 

Further, because Indiana bats prefer roosting sites 

beneath exfoliating bark to cavities or crevices (Kurta 

et al. 1993, Carter and Feldhamer 2005, Lacki et al. 

2008), the presence of this habitat characteristic on snags 

should also be used as a criterion for counting a snag as 

potentially suitable.

Boyles and Aubrey (2006) found that reintroduction of 

prescribed fire into mixed-oak forests after decades of fire 

suppression resulted in a striking increase in evening bat 

(Nycticeius humeralis) roosting compared with adjacent 

unburned forest. They attributed the effect on this cavityroosting bat to the high tree mortality after the first burn, 

which increased both the exposure of existing snags and 

the density of snags. MacGregor et al. (1999) found that 

male Indiana bats did not consistently use prescribed 

burned units for roosting in greater than expected 

proportion to their area on the landscape, though it is 

not clear how fires affected snag availability. Two-age 

shelterwoods in the same landscape in which snag and 

live roost retention guidelines were in place showed 

greater-than-expected roosting by male Indiana bats, 

lending support for future studies in which Indiana bat 

responses to shelterwood-burn treatments are analyzed.

Populations of large snags suitable for roosting are the 

result of a balance between canopy tree mortality rates 

and how long snags retain their preferred characteristics. 

In eastern mixed-oak forests, tree mortality rates range 

from 1-3 percent/year, but much of that mortality is of 

smaller, suppressed stems (Parker et al. 1985, Wyckoff 

and Clark 2002). Injury from low-intensity surface fires 

after long periods of fire suppression in southeastern 

Ohio appeared to add incrementally to the mortality 

of large canopy trees that were at risk before burning 

(Yaussy et al. 2004). Reintroduction of fire to long 

unburned stands can cause high rates of overstory 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 63

mortality (Boyles and Aubrey 2006, Anderson and 

Brown 1983) as can high-intensity fires (Regelbrugge 

and Smith 1994, Moser et al. 1996). Although bat 

habitat may be improved over the short term because 

of these often patchy mortality events, the events tend 

to occur on sites that support intense fire behavior (e.g., 

slopes and topographically dry and exposed sites) and a 

return of high quality roosting habitat to those landscape 

positions after snags have become unsuitable for roosting 

would take a very long time. Avoiding high tree mortality 

adjacent to hibernacula would also be prudent, given 

ensuing microclimatic changes that may not be favorable 

to hibernating bats (Carter et al. 2002).

High mortality rates of large, old trees has been 

recognized where fire has been reintroduced into longunburned stands of longleaf pine (Pinus palustris Mill., 

ponderosa pine (Pinus ponderosa), and larch (Larix 

laricina); extensive duff accumulation results in root 

consumption and basal heating (e.g., Varner et al. 2005, 

Kolb et al. 2007). Large, old trees may be inherently 

more susceptible to dying from a given level of injury 

because of their physiological characteristics (see Kolb 

et al. 2007). It is not clear that fire in eastern mixed-oak 

forests would ever lead to preferential mortality of large 

trees, as opposed to small trees, if only because of the 

lack of extensive basal duff accumulation. Efforts to use 

fuel management (e.g., planned felling or redistribution 

of tops during shelterwood operations) and ignition 

strategies to kill individual or small groups of potential 

roosts would merit attention.

Apart from the creation of snags, the longevity of 

suitable snags is also an important determinant of snag 

availability. Studies that follow snags from year to year 

have found that roosts are used from 2-6 years (Kurta 

2005). Of recently dead trees, only a portion will develop 

patches of exfoliating bark suitable for roosting, though 

it is not known what fraction that is and what determines 

the propensity for bark exfoliation. Fires not only create 

snags by killing trees, some of which may be live roosts, 

but also fell snags through the structural weakening 

caused by smoldering combustion (Carter et al. 2002). 

Experience suggests that snags are drier, and smolder 

more readily, during late spring burns (Michael Bowden, 

Ohio Division of Forestry, personal communication). 

Snag loss may be more of a problem in late summer 

and fall burns after dry periods when duff is dry and 

consumes more readily (K. Moore and E.J. Bunzendahl 

Wayne National Forest (KM), Daniel Boone WF (EJB), 

personal communication). Bats using maternity roosts 

in riparian habitat, and the roosts themselves, may be 

least vulnerable to fire because fire intensities in these 

landscape positions tend to be low (Carter et al. 2002).

Snag species composition across the range of the Indiana 

bat suggests that a range of tree species (though not 

all) form suitable snags and local availability largely 

determines which tree species bats use (Kurta 2005, 

USFWS 2007a). Fire-maintained oak-hickory forests 

would be expected to maintain a species composition 

suitable for Indiana bats (USFWS 2007a). Tree species 

that consistently form high quality live roosts include 

shellbark hickory (Carya laciniosa), shagbark hickory (C. 

ovata), and white oak (Quercus alba). Oaks, particularly 

of the white oak group, are favored by low-intensity 

fire (Abrams 2005) while oak and hickory regeneration 

has been shown to be favored by repeated fires below 

open canopies (Iverson et al. 2008). Live roost trees are 

less ephemeral than snags and provide secondary roosts 

for maternity colonies and roosts for nonreproductive 

bats, yet most trees occupied by Indiana bats during the 

summer are snags (Kurta 2005).

A first step to setting targets for potentially suitable 

roosting habitat would be to determine adequate roost 

densities and spatial distribution. Unfortunately, there 

is a paucity of data available on these topics (Lacki et 

al. 2008). However, studies of Indiana bat primary 

and secondary roosting behavior have shown that bats 

show high fidelity to individual roosts. Even though 

they switch roosts roughly 2 days, on average, Indiana 

bats often return to previously used roosts, supporting 

efforts to protect known roost trees until they become 

unsuitable. Indiana bats also show fidelity within and 

among years to roosting areas 1 or more km in extent 

(Gumbert et al. 2002, Kurta et al. 2002). Because bats 

in a single maternity colony are dispersed among various 

roosts at any given time (Kurta 2005) and because of 

across-year fidelity to roosting areas (also see Humphrey 

et al. 1977, Kurta and Murray 2002), the supply of 

primary and secondary roosts must be maintained over 
64 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

areas of tens of square kilometers, an area larger than 

single burn or harvest units.

Fire and Foraging 

Fire may affect foraging habitat in at least two ways: 

through effects on forest structure and through 

effects on insect prey productivity and community 

structure. Foraging habitat, and the effects of fire, may 

be particularly important for maternity and staging 

areas, where bats have high demands for insect prey 

(Carter et al. 2002). Indiana bats are aerial feeders, 

whose short, broad wings, rounded wingtips, and 

echolocation characteristics are suitable for foraging in 

forests (Norberg and Rayner 1987). Indiana bats have 

been observed to feed primarily around tree crowns, not 

within them, occasionally descending into the midstory 

and shrub layers (Humphrey et al. 1977). Lee and 

McCracken (2004) found that, in sympatry with other 

Myotis bats, Indiana bats foraged higher above ground. 

For these reason, it has been hypothesized that Indiana 

bats would prefer foraging in more open stands (e.g., 

USFWS 2005). Historical forest and uneven-age timber 

management prescriptions involving low-intensity fire 

that are being implemented on National Forests in the 

mixed-oak region would reduce understory and midstory clutter (Arthur et al. 1998, Elliott et al. 1999, Blake 

and Schuette 2000, Hutchinson et al. 2005) and, if 

repeated over the long term, would reduce density of the 

upper canopy (e.g., Huddle and Pallardy 1996, Peterson 

and Reich 2001).

Data on Indiana bat foraging casts some doubt on the 

potential benefits of stand thinning by fire, though 

Indiana bat foraging in burned forest has not been 

studied directly. In Appalachian landscapes of West 

Virginia, Indiana bats were found to use forested riparian 

habitats most heavily and, where recorded in uplands 

impacted by a variety of forestry practices, were detected 

most frequently in areas with the highest canopy cover 

(e.g., Owen et al. 2004, Ford et al. 2005). Using sonic 

detectors, Titchenell (2007) found that Myotis bats (no 

identification to species, yet unlikely to have included 

Indiana bats) showed no difference in foraging behavior 

between control and shelterwood stands, yet other bat 

taxa foraged more intensively in shelterwoods. Loeb and 

Waldrop (2008) found overall preference for thinned 

pine stands among non-Myotis bats, and, again, response 

varied among species. Complicating matters, interspecific 

interactions have been shown to affect when and where 

Indiana bats forage (e.g., Lee and McCracken 2004).

Knowledge of the diet of Indiana bats could help provide 

a target for monitoring and management. From a limited 

number of studies, it appears that the diet of Indiana 

bats foraging primarily in upland forests is dominated by 

moths (Lepidoptera) and beetles (Coleoptera, see Brack 

and LaVal 1985, Murray and Kurta 2002). Lepidoptera 

also dominated diets of bats foraging in riparian habitats 

(e.g., Belwood 1979, Lee and McCracken 2004), while 

bats foraging over wetlands in Michigan consumed 

primarily the adult stages of aquatic insects (Kurta 

and Whitaker 1998). Diet studies which concurrently 

sampled both bat diets and nocturnal insect abundances 

indicated a preference for Lepidoptera by Indiana bats as 

opposed to a diet determined solely by random encounter 

rates (e.g., Brack and LaVal 1985, Lee and McCracken 

2004).

Unfortunately, there is a paucity of information on 

insect prey availability for bats in central hardwood 

forests and its relationship with forest management 

activities, including fire (Rieske-Kinney 2006). A study 

of pollinators in oak-dominated stands in the southern 

Appalachians found that a combination of mechanical 

shrub control and fire resulted in greater abundances 

of beetles and butterflies (Lepidoptera) compared with 

burning or mechanical treatments alone or no treatment, 

and that these increases were related to increased 

herbaceous cover where canopy cover was most reduced 

(Campbell et al. 2007). Whether these increases in 

abundance would translate into greater (nocturnal) prey 

availability for bats is not known. Fires in mixed-oak 

forests have a negative effect on litter-dwelling mites and 

collembolans and there have been mixed results in using 

fire to control gypsy moths and acorn-predating weevils 

(see Rieske-Kinney 2006). Low- to moderate-intensity 

fire had no effect on palatability of two overstory tree 

species to gypsy moth larvae (Rieske-Kinney et al. 2002). 

Wildlife managers express concern that prescribed 

fires in the late dormant season and spring reduce bat 

prey abundances during the critical period when bats 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 65

are coming out of hibernation, are migrating, and 

females are pregnant. Unanswered questions include 

the magnitude of reduction in prey abundances, how 

long those abundances remain depressed, and whether 

fire ultimately increases foraging success (through both 

prey availability and improved forest structure for 

Indiana bat foraging). Another open question is whether 

increased water yields from fire-maintained watersheds 

in the central hardwoods would translate into greater 

insect productivity in riparian areas with benefits to bats 

foraging on emerging adults (e.g., Beck et al. 2005).

In light of both the potential negative effects of fires on 

bats over the short term and the potential longer-term 

benefits, it is useful to consider the size of burn units in 

relation to the size of bat home ranges. There is a large 

range in reported mean home ranges, in one review 

spanning 81 to 668 ha (USDA FS 2007). Indiana bats 

may travel long distances to foraging areas, so roosting 

areas may be separated from foraging areas. Burn unit 

sizes are on par with mean home ranges and, if burning 

is done near known maternity colonies, it would be 

prudent to locate burn unit boundaries so that entire 

home ranges are not burned over in a single year or to 

conduct the burns in a way that creates a patchwork of 

burned and unburned areas (e.g., using ridge ignition, 

which leaves mesic areas unburned).

Fire and Bats on National Forests

We reviewed the current forest plans for the National 

Forests that lie within the distributional limit of the 

Indiana bat for information pertaining to standards and 

guidelines relative to the Indiana bat (Table 4). Forest 

Plan standards are attainments that must be reached or 

National Forest State Forest plan 

revision

Standards and 

guidelines

Hibernacula Bat summer status

Allegheny Pennsylvania 2007 Part 3 No Two males captured

Cherokee Tennessee 2004 Chapter 2 No Three post-lactating females documented 

in 2006 (apparently upland roosts)

Daniel Boone Kentucky 2004 Chapter 2 Yes (>15 

w/in Forest)

Seven maternity colonies documented, 90 

total records

George Washington 

and Jefferson 

Virginia 2007 (draft) Chapter 3 Yes (4) No known maternity colonies, no 

mistnetting conducted

Hoosier Indiana 2006 Chapter 3 Yes (1) Two maternity colonies documented, first 

in 2004 (apparently upland)

Huron-Manistee Michigan 2006 Chapter 2 Yes (1 ) Two males captured during swarming

Mark Twain Missouri 2005 Chapter 2 Yes (4) Two known maternity colonies, male 

roosts identified

Monongahela West Virginia 2006 Chapter 2 Yes (15) One known maternity colony

Nantahala-Pisgah North Carolina 1994 Amendment 10

(released in 2000)

No One known maternity colony

Ozark Arkansas 2005 Part 3 Yes (8) >1 maternity colony, females foraging in 

riparian and upland habitat, various male 

bat captures

Shawnee Illinois 2006 Appendix H Yes (2) Two known maternity colonies in 

bottomland hardwoods, male roosts in 

one cave and three mines

Wayne Ohio 2006 Chapter 2 Yes (2) Reproductive females captured, maternity 

colony/colonies assumed present 

Table 4.—National Forests that consider Indiana bats in their forest plans. Presence of hibernacula in a National Forest, or 

within its proclamation boundary, and bat summer status were determined from the latest USFS monitoring report, USFS 

Programmatic Biological Analysis, or USFWS Programmatic Biological Opinion. Number of hibernacula is given in parentheses.
66 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

courses of action that must be followed to mitigate the 

effects of land management activities while guidelines are 

expected to be followed in most circumstances. Forest 

plans are required by the National Forest Management 

Act and are revised periodically and amended as 

needed. Individual projects must go through National 

Environmental Policy Act analysis, including biological 

assessments for project effects on Indiana bats, where 

present. Burn plans further specify how burns will be 

conducted to minimize risk to bats, where applicable.

Since 1994, nearly all National Forests within the range 

of the Indiana bat have requested formal consultation 

with the USFWS relative to their forest plans, resulting 

in the issuance of non-jeopardy biological opinions 

and associated incidental take statements (Krusac and 

Mighton 2002). Formal consultation is a negotiation 

between the land management agency and the USFWS 

that is intended to result in a balance between the need 

to conduct land management activities and the need to 

minimize, but not eliminate, “take” of Indiana bats (e.g., 

mortality and disturbance). Thus, forest plan standards 

and guidelines are not as restrictive as they are when the 

objective is to eliminate all “take.” Many forest plans 

have been revised recently and often include extensive 

consideration of Indiana bats (Table 4). Because forest 

plans are reflective of local conditions and the particular 

interaction between Forest and USFWS field-office staff, 

generalization is difficult.

Private and other public landowners can also enter 

into negotiations with the USFWS to develop Habitat 

Conservation Plans (HCPs) that would allow incidental 

take statements to be issued. The state of Indiana’s 

Division of Forestry is currently developing an HCP for 

Indiana bats and is expected to be the first non-USFS 

land management entity to receive an incidental take 

statement.

A sense of bat abundance on Forests can be obtained 

from monitoring and evaluation reports and biological 

opinions and assessments (Table 4). Monitoring data 

are not collected or reported in a standardized fashion 

across the range and information is often qualitative, 

so comparisons are difficult. Several Forests have 

documented only the presence of male bats and others 

have identified only a few maternity colonies. Maternity 

colonies occur in both uplands and bottomland/

riparian habitat on National Forests. It is apparent from 

monitoring and evaluation reports that there has been 

little attempt to follow sampling designs that would allow 

a Forest to determine whether standards and guidelines 

were leading to improved Indiana bat performance. 

Regardless, the relatively few bats documented in many 

forests would make it difficult to detect effects of habitat 

modification.

Forest plans in and of themselves do not preclude 

growing-season burning outside of occupied roosting 

habitat on most of the National Forests within the range 

of the Indiana bat. Growing-season burning is well 

established on the Ozark National Forest in Arkansas. 

Most Forest Plans prohibit burning in the few known 

maternity areas (areas that include roosts and associated 

foraging habitat) during the roosting period. The 

roosting period, when defined, spans the period from 

May 1 (earliest date is April 15) to late summer or fall 

(the earliest end-date is July 31; the latest is Nov. 15). 

Some Forests require surveys to determine whether bats 

are present before burning can be done in potential 

roosting habitat during the roosting period. The most 

restrictive prescription appears to be that in place for the 

Shawnee National Forest, where no upland burning is 

allowed from May 1 to September 1. Even the May 1 

restriction allows burning during late spring bud burst. 

Before 2006, the Monongahela National Forest (West 

Virginia) was restricted to 120 ha of burning per year 

(USDA FS 2006), but, as with other Forests in the 

region, is working to increase their use of fire for oak 

ecosystem management. Given current restrictions, 

growing-season burning past the bud-burst stage would 

appear to be possible on a handful of forests, at least on 

an experimental basis.

Fire practitioners have expressed concern that date 

restrictions on live tree and snag removal in recent 

biological opinions (e.g., Whitebreast Creek and Fort 

Drum Connector Projects (USFWS 2009b) have been 

set back to March 31 from mid-April and that burn 

restrictions may also be tightened to avoid incidental 

“take” of Indiana bats. Concerns about date restrictions 

highlight the need for focused research on both the 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 67

short-term and long-term effects of fires on bats and their 

habitats so that the negative effects of growing-season 

burning can be balanced against any positive effects of 

such burning on habitat.

Forest plans establish standards and guidelines for 

preventing smoke intrusion into hibernacula. The Wayne 

National Forest Plan prohibits prescribed burning within 

a defined hibernacula zone while the George Washington 

and Jefferson National Forests prohibit burning in a 

hibernacula zone unless it could be assured that no 

impact would occur. The Hoosier, Huron-Manistee, 

and Mark Twain National Forests prohibit burning 

during swarming and staging periods. The Hoosier, Mark 

Twain, Ozark-St. Francis, Shawnee, and Wayne National 

Forests call for best smoke management practices to be 

used relative to hibernacula. No mention of prescribed 

burning and hibernacula is made in the Monongahela 

and Daniel Boone National Forest plans. In these Forests, 

consideration of smoke management around hibernacula 

is left to project planning and burn plans. Forests with 

no known hibernacula (Allegheny, Cherokee, and 

Nantahala-Pisgah National Forests), of course, make no 

mention of hibernacula in reference to burning.

Standards and guidelines governing snags and potential 

live roosts differ among Forests and among silvicultural 

treatments within Forests. Live roost retention (e.g., 

shagbark and shellbark hickory and other trees with 

suitable bark characteristics) varies from retention of all 

shagbark and shellbark hickories (e.g., Allegheny and 

George Washington and Jefferson National Forests) 

to their retention in the context of the availability of 

other live roosts and the silvicultural system being 

employed. The regeneration system of most interest 

relative to burning in mixed-oak forests is some form of 

shelterwood (e.g., Brose et al. 1998, 1999), though there 

is some potential for using fire in clearcuts to benefit 

oaks (Michael Bowden, personal communication). 

Shelterwood standards and guidelines, where provided, 

include provisions for future snags and provide targets 

for snag densities by size class. Often the lower size limit 

on snags is between 10 and 25 cm d.b.h., a size that is 

considerably smaller than the median Indiana bat roost 

(Fig. 1).

Apart from forest plans, forestwide (programmatic) 

biological assessments (e.g., USDA FS 2005) and their 

associated biological opinions (e.g., USFWS 2005) are 

available for Forests and are good places for state and 

private land managers to find information on the Indiana 

bat and land management as they develop their own 

programs. The Indiana Bat Recovery Plan (USFWS 

2007a) has rangewide scope and is also a good source 

of information. The USFWS website dedicated to the 

Indiana bat contains a variety of documents and other 

useful information (USFWS 2009a).

CONCLUSIONS AND

RECOMMENDATIONS

Prescribed fires cause roost-switching behavior in 

tree-roosting bats that would reduce their exposure 

to smoke. Extensive use of torpor by roosting males 

and nonreproductive females would increase their risk 

of smoke exposure, though use of torpor and arousal 

times under typical burning conditions are unknown. 

Reproductive females are generally expected to maintain 

high body temperatures and, thus, be able to respond 

quickly to fires. However, use of torpor by pregnant 

female bats during spring storms has been demonstrated. 

Forest managers can reduce risk to tree-roosting bats 

by reducing fuel consumption, which determines the 

quantity of smoke produced, and fireline intensity, 

which drives smoke transport. Burning under relatively 

high ambient temperatures, for example, from late 

April through May, after bats have dispersed to their 

summer habitat, may also reduce risk, though data on 

the use of torpor are needed. Given demonstrated roost 

switching behavior, the critical risk period for bats may 

not be when maternity colonies are formed, but later, 

when flightless young are present. Further research may 

show that early growing-season burning, as opposed to 

burning during the vegetative dormant season, may be 

done at lower intensities during warmer weather and may 

result in more desirable fire effects on vegetation with 

manageable risks for bats.

Smoke exposures in hibernacula would be expected 

to pose problems if they cause extra arousals, though 

arousal thresholds for hibernating bats are unknown. 

Given treatment of hibernacula as smoke-sensitive 
68 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

targets, and the smoke management efforts that this 

designation entails, it is unlikely that toxicity from 

high gas concentrations themselves will be problematic, 

only arousal from exposures to relatively low smoke 

concentrations. Smoke intrusion into hibernacula of 

species other than Indiana bats has been documented. 

For Indiana bat hibernacula, smoke intrusion is most 

likely when hibernacula are exchanging air under 

conditions when nighttime temperatures drop below the 

annual mean. A better understanding of risk requires 

increased knowledge of arousal response to smoke by 

hibernating Indiana bats and information on air flow in 

individual hibernacula.

Fires in upland mixed-oak forests are expected to 

improve roosting and foraging habitat for Indiana bats 

by increasing the availability of suitable snags, reducing 

canopy clutter, and increasing long-term insect prey 

availability. Unfortunately, the data basis for these 

expectations is poor to mixed. For instance, the longterm tradeoff between snag creation and snag loss in 

mixed-oak forests under burning regimes is unknown. 

Data on foraging activity show Indiana bat preference 

for relatively closed-canopy stands, casting doubt on 

the benefits to foraging that would arise from the stand 

thinning caused by forest burning. Explicit studies on the 

benefits of forest burning on Indiana bat foraging habitat 

are needed.

Fire has been recommended on National Forests in 

two relatively incompatible contexts: as a tool for well 

regulated oak silviculture and as an imperative for oak 

ecosystem restoration and maintenance. Given Indiana 

bat fidelity to roosting and foraging areas, upland 

maternity areas might serve, on an experimental basis 

at first, as focal areas for oak ecosystem restoration and 

maintenance where burning is used to try to increase 

local roosting populations and their reproductive success. 

A regional approach to oak ecosystem conservation 

and monitoring on National Forests has been proposed 

(Yaussy et al. 2008) and, if designed properly, has the 

potential to add to our understanding of Indiana bat 

response to forest thinning and burning. Currently, 

adaptive management relative to Indiana bats is not 

possible because monitoring programs are poorly funded 

and not designed to assess the effects of land management 

activities on bat populations. Furthermore, few research 

projects have addressed the central questions about fire 

and Indiana bat habitat. The current state of knowledge is 

a poor foundation on which to base upland management 

activities and to determine whether existing, or any 

further, date restrictions on burning on National Forests 

are counterproductive for Indiana bat conservation.

ACKNOWLEDGMENTS

We thank Daniel Boone National Forest for access, 

permission, and cooperation during the prescribed burn, 

especially E.J. Bunzendahl for coordination efforts, 

B. Borovicka for assistance with radiotracking, and R. 

Hunter for safety oversight. L. Miller, W. Borovicka, 

A. Bova, and R. Kremens assisted with data collection 

during the burn, and E. Carlisle and J. Adams assisted 

with radiotracking of bats before and after the burn. 

This study was funded by a grant from the Joint Fire 

Science Program, the National Fire Plan, and College of 

Agriculture, University of Kentucky. All methods and 

use of animals associated with this project have been 

approved by the University of Kentucky Animal Care 

and Use Committee (IACUC No. 01039A2006). This 

investigation is connected with a project of the Kentucky 

Agricultural Experiment Station (KAES NO. 08-09-

060) and is published with approval of the director. Two 

anonymous reviewers provided useful feedback on the 

manuscript.

LITERATURE CITED

Abrams, M. 2005. Ecological and ecophysiological 

attributes and responses to fire in eastern oak 

forests. In: Dickinson, M.B., ed. Fire in eastern oak 

forests: delivering science to land managers; 2005 

November 15-17; Columbus, OH. Gen. Tech Rep. 

NRS-P-1. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service: 74-89.

Alexander, H.D.; Arthur, M.; Loftis, D.; Green, S. 

2006. Overstory and seedling response to repeated 

fires in eastern Kentucky. In: Dickinson, M.B., ed. 

Fire in eastern oak forests: delivering science to land 

managers; 2005 November 15-17; Columbus, OH. 

Gen. Tech. Rep. NRS-P-1. Newtown Square, PA: 

U.S. Department of Agriculture, Forest Service: 268.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 69

Anderson, R.C.; Brown, L.E. 1983. Comparative effects 

of fire on trees in a Midwestern savannah and an 

adjacent forest. Bulletin of the Torrey Botanical 

Club. 110(1): 87-90.

Arthur, M.A.; Paratley, R.D.; Blankenship, B.A. 1998. 

Single and repeated fires affect survival and 

regeneration of woody and herbaceous species in 

an oak-pine forest. Journal of the Torrey Botanical 

Society. 125: 225-236.

Audet, D.; Thomas, D.W. 1997. Facultative 

hypothermia as a thermoregulatory strategy in 

the phyllostomid bats Carollia perspicillata and 

Sturnira lilium. Journal of Comparative Physiology 

B. 167: 146-152.

Beck, J.; Wilkinson, R.; Baxter, C. 2005. Burned 

streams produce more aquatic insects and 

consequently higher foraging activity by bats. Bat 

Research News. 46: 177.

Belwood, J.J. 1979. Feeding ecology of an Indiana 

bat community with emphasis on the endangered 

Indiana bat, Myotis sodalis. Gainesville, FL: 

University of Florida. 103 p. M.S. thesis.

Belwood, J.J. 2002. Endangered bats in suburbia: 

observations and concerns for the future. In: Kurta, 

A.; Kennedy, J., eds. The Indiana bat: biology and 

management of an endangered species. Austin, TX: 

Bat Conservation International: 193-198.

Beyer, H.L. 2004. Hawth’s analysis tools for ArcGIS.

Available at www.spatialecology.com/htools. (Accessed 

March 3, 2008.)

Blake, J.G.; Schuette, B. 2000. Restoration of an oak 

forest in east-central Missouri: early effects of 

prescribed burning on woody vegetation. Forest 

Ecology and Management. 139: 109-126.

Boyles, J.G. 2007. Describing roosts used by forest 

bats: the importance of microclimate. Acta 

Chiropterologica. 9: 297-303.

Boyles, J.G.; Aubrey, D.P. 2006. Managing forests with 

prescribed fire: Implications for a cavity-dwelling 

bat species. Forest Ecology and Management. 222(1-

3): 108-115.

Brack, V.; LaVal, R.K. 1985. Food habits of the 

Indiana bat in Missouri. Journal of Mammalogy. 66: 

308-315.

Britzke, E.R.; Harvey, M.J.; Loeb, S.C. 2003. Indiana 

bat, Myotis sodalis, maternity roosts in the southern 

United States. Southeastern Naturalist. 2: 235-242.

Britzke, E.R.; Hicks, A.C.; Von Oettingen, S.L.; Darling, 

S.R. 2006. Description of spring roost trees used 

by female Indiana bats (Myotis sodalis) in the Lake 

Champlain Valley of Vermont and New York. 

American Midland Naturalist. 155: 181-187.

Brose, P.H.; Van Lear, D.H.; Keyser, P.D. 1998.

Responses of hardwood advance regeneration 

to seasonal prescribed fires in oak-dominated 

shelterwood stands. Canadian Journal of Forest 

Research. 28: 331-339.

Brose, P.H.; Van Lear, D.H.; Keyser, P.D. 1999. A 

shelterwood-burn technique for regenerating 

productive upland oak sites in the piedmont region. 

Southern Journal of Applied Forestry. 23(3): 158-162.

Butchkowski, C.M.; Hassinger, J.D. 2002. Ecology of a 

maternity colony roosting in a building. In: Kurta, 

A.; Kennedy, J., eds. The Indiana bat: biology and 

management of an endangered species. Austin, TX: 

Bat Conservation International: 130-142.

Callahan, E.V.; Drobney, R.D.; Clawson, R.L. 1997. 

Selection of summer roosting sites by Indiana bats 

(Myotis sodalis) in Missouri. Journal of Mammalogy. 

78: 818-825.

Campbell, J.W.; Hanula, J.L.; Waldrop, T.A. 2007. 

Effects of prescribed f ire and fire surrogates on 

floral visiting insects of the Blue Ridge province in 

North Carolina. Biological Conservation. 134: 393-

404.
70 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Carter, T.C. 2005. Indiana bats in the Midwest: the 

importance of hydric habitats. The Journal of 

Wildlife Management. 70(5): 1185-1190.

Carter, T.C.; Ford, W.M.; Menzel, M.A. 2002. Fire 

and bats in the southeast and Mid-Atlantic: more 

questions than answers? In: Ford, W.M.; Russell, 

K.R.; Moorman, C.E. Proceedings, the role of fire 

in nongame wildlife management and community 

restoration: traditional uses and new directions; 2000 

September 15; Nashville, TN. Gen. Tech. Rep. 

NE-288. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northeastern Research 

Station: 139-143.

Carter, T.C.; Feldhamer, G.A. 2005. Roost tree use by 

maternity colonies of Indiana bats and northern 

long-eared bats in southern Illinois. Forest Ecology 

and Management. 219: 259-268.

Caughley, G.; Gunn, A. 1995. Conservation biology 

in theory and practice. Cambridge, UK: Blackwell 

Science. 333 p.

Caviness, M. 2003. Effects of prescribed fire on cave 

environment and bat inhabitants. Bat Research 

News. 44(4): 130.

Chang, J.C.F.; Steinhagen, W.H.; Barrow, C.S. 1981. 

Effect of single or repeated formaldehyde exposure 

on minute volume of B6C3F1 mice and F-344 rats.

Toxicology and Applied Pharmacology. 61: 451-495.

Clawson, R.L. 2002. Trends in population size and 

current status. In: Kurta, A.; Kennedy, J., eds. 

The Indiana bat: biology and management of an 

endangered species. Austin, TX: Bat Conservation 

International: 2-8.

Collins, R.F. 1975. A history of the Daniel Boone 

National Forest 1770 -1970. Winchester, KY: U.S. 

Department of Agriculture, Forest Service. 349 p.

Daniel, W.W. 1974. Biostatistics: a foundation for 

analysis in the health sciences. New York, NY: John 

Wiley and Sons, Inc. 448 p.

Dickinson, M.B., ed. 2006. Fire in eastern oak 

forests: delivering science to land Managers; 2005 

November 15-17; Columbus, OH. Gen. Tech. Rep. 

NRS-P-1. Newtown Square, PA: U.S. Department of 

Agriculture, Forest Service, Northern Research Station. 

303 p.

Diller, K.R.; Hayes, L.J.; Blake, G.K. 1991. Analysis 

of alternate models for simulating thermal burns. 

Journal of Burn Care and Rehabilitation. 12: 177-189.

Elliott, K.J.; Hendrick, R.L.; Major, A.E.; Vose, J.M.; 

Swank, W.T. 1999. Vegetation dynamics after 

prescribed fire in the southern Appalachians. Forest 

Ecology and Management. 114: 199-213.

Ferguson, S.A.; McKay, S.J.; Nagel, D.E.; Piepho, 

T.; Rorig, M.L.; Anderson, C.; Kellogg, L. 2003. 

Assessing values of air quality and visibility at 

risk from wildland fires. Res. Pap. PNW-RP-550. 

Portland, OR: U.S. Department of Agriculture, Forest 

Service, Pacific Northwest Research Station. 59 p.

Ford, W.M.; Menzel, M.A.; Rodrigue, J.L.; Menzel, J.M.; 

Jonson, J.B. 2005. Relating bat species presence to 

simple habitat measures in central Appalachian 

Forest. Biological Conservation. 126: 528-539.

Foster, R.W.; Kurta, A. 1999. Roosting ecology of 

the northern bat (Myotis septentrionalis) and 

comparisons with the endangered Indiana bat 

(Myotis sodalis). Journal of Mammalogy. 80: 659-

672.

Gardner, J.E.; Garner, J.D.; Hofmann, J.E. 1991. 

Summer roost selection and roosting behavior of 

Myotis sodalis (Indiana bat) in Illinois. Final Report. 

Urbana-Champaign, IL: Illinois Natural History 

Survey and Illinois Department of Conservation. 56 p.

Gardner, J.E.; Cook, E.A. 2002. Seasonal and 

geographic distribution and quantification of 

potential summer habitat. In: Kurta, A.; Kennedy, 

J., eds. The Indiana bat: biology and management of 

an endangered species. Austin, TX: Bat Conservation 

International: 9-20.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 71

Geiser, F. 1986. Thermoregulation and torpor in 

the Kultarr, Antechinomys laniger (Marsupialia: 

Dasyuridae). Journal of Comparative Physiology B 

(1986). 156: 751-757.

Geiser, F.; Drury, R.L. 2003. Radiant heat affects 

thermoregulation and energy expenditure during 

rewarming from torpor. Journal of Comparative 

Physiology B. 173: 55-60.

Geiser, F.; Drury, R.L.; Körtner, G.; Turbill, C.; Pavey, 

C.R.; Brigham, R.M. 2004. Passive rewarming from 

torpor in mammals and birds: energetic, ecological 

and evolutionary implications. Biological Papers 

of the University of Alaska, No. 27. In: Barnes, 

B.M.; Carey, H.V., eds. Life in the cold: evolution, 

adaptation, and application. Fairbanks, AK: Institute 

of Arctic Biology: 51-62.

Grinevitch, L.; Holroyd, S.L.; Barclay, R.M.R. 1995. 

Sex-differences in the use of daily torpor and 

foraging time by big brown bats (Eptesicus fuscus) 

during the reproductive season. Journal of Zoology 

(London). 235: 301-309.

Guelta, M.; Balbach, H.E. 2005. Modeling fog oil 

obscurant smoke penetration into simulated 

tortoise burrows and bat colony trees. ERDC/

CERL TR-05-31. Champaign, IL: U.S. Army Corps 

of Engineers, Engineer Research and Development 

Center and Construction Engineering Research 

Laboratory. 49 p.

Gumbert, M.W.; O’Keefe, J.M.; MacGregor, J.R. 2002. 

Roost fidelity in Kentucky. In: Kurta, A.; Kennedy, 

J., eds. The Indiana bat: biology and management of 

an endangered species. Austin, TX: Bat Conservation 

International: 143-152.

Hamilton, J.L.; Barclay, R.M.R. 1995. Patterns of daily 

torpor and day roost selection by male and female 

big brown bats (Eptesicus fuscus). Canadian Journal 

of Zoology. 72: 744-749.

Harvey, M.J.; Altenbach, J.S.; Best, T.L. 1999. Bats of 

the United States. Little Rock, AR: Arkansas Game 

and Fish Commission. 64 p.

Huddle, J.A.; Pallardy, S.G. 1996. Effects of long-term 

annual and periodic burning on tree survival and 

growth in a Missouri Ozark oak-hickory forest.

Forest Ecology and Management. 82: 1-9.

Humphrey, S.R.; Richter, A.R.; Cope, J.B. 1977. 

Summer habitat and ecology of the endangered 

Indiana bat, Myotis sodalis. Journal of Mammalogy. 

58: 334-346.

Hunter, M.L., Jr. 1990. Wildlife, forests, and forestry: 

principles of managing forests for biological 

diversity. Englewood Cliffs, NJ: Prentice-Hall. 370 p.

Hutchinson, T.F.; Sutherland, E.K.; Yaussy, D.A. 2005. 

Effects of repeated prescribed fires on the structure, 

composition, and regeneration of mixed-oak forests 

in Ohio. Forest Ecology and Management. 218: 210-

228.

Iverson, L.R.; Hutchinson, T.F.; Prasad, A.M.; Peters, 

M.P. 2008. Thinning, fire, and oak regeneration 

across a heterogeneous landscape in the eastern US: 

7-year results. Forest Ecology and Management. 255: 

3035-3050.

Jones, R.L. 2005. Plant life of Kentucky: an illustrated 

guide to the vascular flora. Lexington, KY: The 

University Press of Kentucky. 856 p.

Kolb, T.E.; Agee, J.K.; Fule, P.Z.; McDowell, 

N.G.; Pearson, K.; Sala, A.; Waring, R.H. 2007. 

Perpetuating old ponderosa pine. Forest Ecology 

and Management. 249: 141-157.

Krusac, D.L.; Mighton, S.R. 2002. Conservation of 

the Indiana bat in National Forests: where we have 

been and where we should be going. In: Kurta, 

A.; Kennedy, J., eds. The Indiana bat: biology and 

management of an endangered species. Austin, TX: 

Bat Conservation International: 55-65.
72 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Kurta, A. 1991. Torpor patterns in food deprived 

Myotis lucifugus (Chiroptera: Vespertilionidae) 

under simulated roost conditions. Canadian Journal 

of Zoology. 69: 255-257.

Kurta, A. 2005. Roosting ecology and behavior of 

Indiana bats (Myotis sodalis) in summer. In Vories, 

K.C.; Harrington, A. eds. Proceedings of the Indiana 

bat and coal mining: a technical interactive forum. 

Alton, IL: Office of Surface Mining, U.S. Department 

of the Interior. Available: www.mcrcc.osmre.gov/

PDF/Forums/Bat%20Indiana/TOC.pdf. (Accessed 

June 24, 2008).

Kurta, A.;, King, D.; Teramino, J.A.; Stribley, J.M.; 

Williams, K.J. 1993. Summer roosts of the 

endangered Indiana bat (Myotis sodalis) on the 

northern edge of its range. American Midland 

Naturalist. 129: 132-138.

Kurta, A.; Murray, S.W. 2002. Philopatry and 

migration of banded Indiana bats (Myotis sodalis) 

and effects of using radio transmitters. Journal of 

Mammalogy. 83: 585-589.

Kurta, A.; Murray, S.W.; Miller, D.H. 2002. Roost 

selection and movements across the summer 

landscape. In: Kurta, A.; Kennedy, J., eds. The 

Indiana bat: biology and management of an 

endangered species. Austin, TX: Bat Conservation 

International: 118-129.

Kurta, A.; Whitaker, J.O. 1998. Diet of the endangered 

Indiana bat (Myotis sodalis) on the northern edge 

of its range. American Midland Naturalist. 140: 280-

-286.

Kurta, A.; Williams, K.J.; Mies, R. 1996. Ecological, 

behavioural, and thermal observations of a 

peripheral population of Indiana bats. In: Barclay, 

R.M.R.; Brigham, R.M., eds. Bats and forests 

symposium. Victoria, BC: British Columbia Ministry 

of Forests, Canada: 102-117.

Lacki, M.J.; Cox, D.R.; Dickinson, M.B. In press. Metaanalysis of summer roosting characteristics of two 

species of Myotis bats. American Midland Naturalist.

Lee, Y.F.; McCracken, G.F. 2004. Flight activity 

and food habits of three species of Myotis bats 

(Chiroptera: Vespertilionidae) in sympatry.

Zoological Studies. 43: 589-597.

Loeb, S.C.; Waldrop, T.A. 2008. Bat activity in relation 

to fire and fire surrogate treatments in southern 

pine stands. Forest Ecology and Management. 255: 

3185-3192.

Lovegrove, B.G.; Körtner, G.; Geiser, F. 1999. The 

energetic cost of arousal from torpor in the 

marsupial Sminthopsis macroura: benefits of 

summer ambient temperature cycles. Journal of 

Comparative Physiology B. 169: 11-18.

Lyons, J.E.; Loucks, E.; Arthur, M.A.; Loftis, D. 

2006. Impacts of repeated prescribed fires on 

fuels in a Central Appalachian hardwood forest.

In: Dickinson, M.B., ed. Fire in eastern oak 

forests: delivering science to land managers; 2005 

November 15-17; Columbus, OH. Gen. Tech. Rep. 

NRS-P-1. Newtown Square, PA: U.S. Department 

of Agriculture, Forest Service, Northern Research 

Station: 284.

Mann, R. 2006. Growing a burning program: 

challenges and opportunities. In: Dickinson, M.B., 

ed. Fire in eastern oak forests: delivering science to 

land Managers; 2005 November 15-17; Columbus, 

OH. Gen. Tech. Rep. NRS-P-1. Newtown Square, 

PA: U.S. Department of Agriculture, Forest Service, 

Northern Research Station: 263-266.

McGrain, P. 1983. The geologic story of Kentucky.

Series XI, Special Publication 8. Lexington, KY; 

Kentucky Geological Survey, University of Kentucky. 

74 p.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 73

MacGregor, J.R.; Kiser, J.D.; Gumbert, M.W.; Reed, 

T.O. 1999. Autumn roosting habitat of male 

Indiana bats (Myotis sodalis) in a managed forest 

setting in Kentucky. In: Stringer, J.W.; Loftis, 

D.L., eds. Proceedings, 12th central hardwood forest 

conference; 1999 February 28-March 2; Lexington, 

KY. Gen. Tech. Rep. SRS-24. Asheville, NC: U.S. 

Department of Agriculture, Forest Service, Southern 

Research Station.: 169-170.

Menzel, M.A.; Menzel, J.M.; Carter, T.C.; Ford, W.M.; 

Edwards, J.W. 2001. Review of the forest habitat 

relationships of the Indiana bat (Myotis sodalis). 

Gen. Tech. Rep. NE-284. Newtown Square, PA: 

U.S. Department of Agriculture, Forest Service, 

Northeastern Research Station. 21 p.

Mercer, G.N.; Weber, R.O. 1994. Plumes above 

fire lines in a cross wind. International Journal of 

Wildland Fire. 4(4): 201-207.

Miller, N.E.; Drobney, R.D.; Clawson, R.L.; Callahan, 

E.V. 2002. Summer habitat in northern Missouri.

In: Kurta, A.; Kennedy, J., eds. The Indiana bat: 

biology and management of an endangered species. 

Austin, TX: Bat Conservation International: 165-171.

Moorman, C.E.; Russell, K.R.; Lohr, S.M.; Ellenberger, 

J.F.; Van Lear, D.H. 1999. Bat roosting in 

deciduous leaf litter. Bat Research News. 40(3): 73-

75.

Morris, S.; Curtin, A.L.; Thompson, M.B. 1994. 

Heterothermy, torpor, respiratory gas exchange, 

water balance and the effect of feeding in Gould’s 

long-eared bat Nyctophilus gouldi. Journal of 

Experimental Biology. 197: 309-335.

Moser, W.K.; Ducey, M.J.; Ashton, P.M.S. 1996. 

Effects of fire intensity on competitive dynamics 

between red and black oaks and mountain laurel.

Northern Journal of Applied Forestry. 13: 119-123.

Murray, S.W.; Kurta, A. 2002. Spatial and temporal 

variation in diet. In: Kurta, A.; Kennedy, J., eds. 

The Indiana bat: biology and management of an 

endangered species. Austin, TX: Bat Conservation 

International: 182-192.

Nams, V.O. 2006. Locate III user’s guide.

Tatamagouche, Nova Scotia, Pacer Computer 

Software, Canada. www.locateiii.com/index.htm. 

(Accessed March 3, 2008.)

Nams, V.O.; Boutin, S. 1991. What is wrong with 

error polygons? Journal of Wildlife Management. 55: 

172-176.

Norberg, U.M., Rayner, J.M.V. 1987. Ecological 

morphology and flight in bats (Mammalia; 

Chiroptera): wing adaptations, flight performance, 

foraging strategy and echolocation. Philosophical 

Transactions of the Royal Society London. B316: 335-

427.

Owen, S.F.; Menzel, M.A.; Edwards, J.W.; Ford, W.M.; 

Menzel, J.M.; Chapman, B.R.; Wood, P.B.; Miller, 

K.V. 2004. Bat activity in harvested and intact 

forest stands in the Allegheny Mountains. Northern 

Journal of Applied Forestry. 21: 154-159.

Parker, G.R.; Leopold, D.J.; Eichenberger, J.K. 1985. 

Tree dynamics in an old-growth, deciduous forest.

Forest Ecology and Management. 11: 31-57.

Peterson, D.W.; Reich, P.B., 2001. Prescribed fire 

in oak savanna: fire frequency effects on stand 

structure and dynamics. Ecological Applications. 11: 

914-927.

Purser, D.A. 2002. Toxicity assessment of combustion 

products. In: The SPFE handbook of fire protection 

engineering, 2nd edition. Section 2: 83-171.

Regelbrugge, J.C.; Smith, D.W. 1994. Postfire tree 

mortality in relation to wildfire severity in mixed 

oak forests in the Blue Ridge of Virginia. Northern 

Journal of Applied Forestry. 11: 90-97.

Rieske-Kinney, L. 2006. Do fire and insects interact 

in eastern forests? In: Dickinson, M.B., ed. Fire 

in eastern oak forests: delivering science to land 
74 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

managers; 2005 November 15-17; Columbus, OH. 

Gen. Tech. Rep. NRS-P-1. Newtown Square, PA: 

U.S. Department of Agriculture, Forest Service, 

Northern Research Station: 152-157.

Rieske-Kinney, L.; Housman, H.H.; Arthur, M.A. 2002. 

Effects of prescribed fire on canopy foliar chemistry 

and suitability for an insect herbivore. Forest 

Ecology and Management. 160: 177-187.

Rodrigue, J.L.; Schuler, T.M.; Menzel, M.A. 2001. 

Observations of bat activity during prescribed 

burning in West Virginia. Bat Research News. 42(2): 

48-49.

Saugey, D.A.; Heath, D.R.; Heldt, G.A. 1989. The bats 

of the Ouachita Mountains. Proceedings Arkansas 

Academy of Science. 43: 71-77.

Scesny, A.A. 2006. Detection of fire by eastern red 

bats (Lasiurus borealis): Arousal from torpor.

Springfield, MO: Missouri State University. 26 p . 

M.S. thesis.

Seaman, D.E.; Millspaugh, J.J.; Kernohan, B.J.; 

Brundige, G.C.; Raedeke, K.J.; Gitzen, R.A. 1999. 

Effects of sample size on kernel home range 

estimates. Journal of Wildlife Management. 63: 739-

747.

Speitel, L.C. 1996. Fractional effective dose model for 

post-crash aircraft survivability. Toxicology. 115: 

167-177.

Thomas, D.W.; Dorais, M.; Bergeron, J.M. 1990. 

Winter energy budgets and cost of arousals for 

hibernating little brown bats, Myotis lucifugus.

Journal of Mammalogy. 71: 475-479.

Titchenell, M.A. 2007. The effects of shelterwood 

harvests on bat populations and forest structure 

in Ohio oak-hickory forests. Columbus, OH: Ohio 

State University. M.S. thesis.

Tuttle, M.D., Kennedy, J. 2002. Thermal requirements 

during hibernation. In: Kurta, A.; Kennedy, J., 

eds. The Indiana bat: biology and management of an 

endangered species. Austin, TX: Bat Conservation 

International: 68-78.

Tuttle, M.D., Taylor, D.A.R. 1998. Bats and mines. Bat 

Conservation International. 50 p.

USDA Forest Service. 2003. Programmatic biological 

assessment for the revised land and resource 

management plan - Daniel Boone National Forest.

Winchester, KY: U.S. Department of Agriculture, 

Forest Service, Region 8. 53 p. http://www.fs.fed.us/

r8/boone/documents/planning/revplan/esa/1baplan.

pdf. (Accessed May 18, 2008).

USDA Forest Service. 2005. Final biological 

assessment on the Wayne National Forest land and 

resource management plan. Nelsonville, OH: U.S. 

Department of Agriculture, Forest Service, Region 9. 

228 p. http://www.fs.fed.us/r9/wayne/planning/2006_

docs/final_eis_docs/Appendix%20F1%20Final%20

BA.pdf. (Accessed May 1, 2008).

USDA Forest Service. 2006. Monongahela National 

Forest final environmental impact statement for 

forest plan revision. Elkins, WV: U.S. Department 

of Agriculture, Forest Service, Eastern Region. 78 p. 

www.wvca.us/envirothon/pdf/dolly-sods%20eis.pdf. 

(Accessed 8 May 2009).

USDA Forest Service. 2007. Biological evaluation 

for the Allegheny National Forest plan revision.

Warren, PA: U.S. Department of Agriculture, Forest 

Service, Region 9. 344 p. http://www.fs.fed.us/r9/

forests/allegheny/projects/forest_plan_revision/

documents/2007_be_final.pdf. (Accessed May 1, 

2008).

U.S. Fish and Wildlife Service. 2005. Final biological 

opinion on the Wayne National Forest land and 

resource management plan. Reynoldsburg, OH: 

U.S. Department of Interior, Fish and Wildlife 

Service, Region 3. 99 p. http://www.fws.gov/

midwest/Endangered/mammals/inba/bos/05_OH_

WNFLRMPProgrmLevl.pdf. (Accessed May 1, 2008).
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 75

U.S. Fish and Wildlife Service. 2007a. Indiana bat 

(Myotis sodalis) draft recovery plan: first revision.

Fort Snelling, MN: U.S. Department of Interior, Fish 

and Wildlife Service, Region 3. 258 p. www.mcrcc.

osmre.gov/Bats/PDF/IN%20BAT%20DRAFT%20

PLAN%20apr07.pdf. (Accessed November 16, 2007).

U.S. Fish and Wildlife Service. 2007b. Revised final 

biological opinion on the Daniel Boone National 

Forest land and resource management plan.

Frankfort, KY: U.S. Department of Interior, Fish 

and Wildlife Service, Region 4. 128 p. http://www.

fs.fed.us/r8/boone/documents/planning/revplan/esa/

bo_revised.pdf. (Accessed May 18, 2008).

U.S. Fish and Wildlife Service. 2008. Ecological 

Services. Washington, DC: U.S. Department of 

Interior, Fish and Wildlife Service. www.fws.gov/

midwest/endangered /index.html. (Accessed 8 May 

2009).

U.S. Fish and Wildlife Service. 2009a. Indiana bat 

Myotis sodalis. Washington, DC: U.S. Department 

of Interior, Fish and Wildlife Service. www.fws.gov/

midwest/endangered /inba/index.html. (Accessed 8 

May 2009).

U.S. Fish and Wildlife Service. 2009b. Indiana bat 

Section 7 consultation; Biological opinions.

Washington, DC: U.S. Department of Interior, 

Fish and Wildlife Service. www.fws.gov/midwest/

endangered /inba/inbaBOs.html. (Accessed 8 May 

2009).

U.S. Fish and Wildlife Service. 2009c. White-nose 

syndrome in bats: Something is killing our bats.

Washington, DC: U.S. Department of Interior, Fish 

and Wildlife Service. www.fws.gov/northeast/white_

nose.html. (Accessed 8 May 2009).

Varner, M.; Gordon, D.R.; Putz, F.E.; Hiers, J.K. 2005. 

Restoring fire to long-unburned Pinus palustris

ecosystems: novel fire effects and consequences for 

long-unburned ecosystems. Restoration Ecology. 13: 

536-544.

Willis, C.K.R.; Brigham, R.M.; Geiser, F. 2006. Deep, 

prolonged torpor by pregnant, free-ranging bats. 

Naturwissenschaften. 93:80-83.

White, G.C.; Garrott, R.A. 1990. Analysis of wildlife 

radio-tracking data. San Diego, CA: Academic Press, 

Inc. 383 p.

Wyckoff, P.H.; Clark, J.S. 2002. The relationship 

between growth and mortality for seven cooccurring tree species in the southern Appalachian 

Mountains. Journal of Ecology. 90: 604-615.

Yaussy, D.A.; Dickinson, M.B.D.; Bova, A.S. 2004. 

Prescribed surface-fire tree mortality in southern 

Ohio: equations based on thermocouple probe 

temperatures. In: Yaussy, D.A.; Hix, D.M.; Long, 

R.P.; Goebel, P.C., eds. Proceedings, 14th central 

hardwood forest conference; 2004 March 16-19; 

Wooster, OH. Gen. Tech. Rep. NE-316. Newtown 

Square, PA: U.S. Department of Agriculture, Forest 

Service, Northeastern Research Station: 67-75.

Yaussy, D.A.; Nowacki, G.J.; Schuler, T.M.; Dey, 

D.C.; DeGayner, E.J. 2008. Developing a 

unified monitoring and reporting system: a key 

to successful restoration of mixed-oak forests 

throughout the central hardwood region. In: 

Proceedings, 2007 national silviculture workshop. 

Gen. Tech. Rep. PNW-733. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific 

Northwest Research Station: 1-6.
76 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 77

modeling tools to support 

fire management and 

planning
78 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

PERFORMANCE OF FIRE BEHAVIOR FUEL MODELS DEVELOPED FOR THE 

ROTHERMEL SURFACE FIRE SPREAD MODEL

Robert Ziel1 and W. Matt Jolly2

1

Fire Management Specialist, Michigan Department of Natural Resources, Marquette, MI 2

Ecologist, U.S. Forest Service, Rocky Mountain Research Station, Fire Sciences Laboratory, Missoula, MT

RZ is corresponding author; to contact, call (906) 249-1497 or email at zielr@michigan.gov

Abstract.—In 2005, 40 new fire behavior fuel models were published for use with the Rothermel Surface 

Fire Spread Model. These new models are intended to augment the original 13 developed in 1972 and 

1976. As a compiled set of quantitative fuel descriptions that serve as input to the Rothermel model, 

the selected fire behavior fuel model has always been critical to the resulting modeled fire behavior. Fuel 

characteristics affect both the heat source and the heat sink factors in the spread model. While the original 

13 models emphasized peak fire-season fuel combinations, the new set establishes a greater role for live 

fuels. Use of live fuel as a variable produces a broad range of modeled fire behavior related to seasonal 

vegetative development, especially for those fuel models that include herbaceous fuel loads. Intending to 

represent “greenup” and late season “curing,” the new fuel models allow the user to transfer herbaceous 

fuels from live to dead. As fuel load transferred increases, the influence of moisture of extinction and wind 

limit produce dramatic changes in modeled spread and intensity. The new models present an important 

opportunity to model fire behavior under a wider range of fuel conditions, including fire use. However, the 

user needs to be aware of the live fuel components in the selected models and manage those inputs carefully.

INTRODUCTION

Wildland fire behavior is frequently described by the 

spread rates and burning intensity as it burns along 

the surface. The primary factors that influence this fire 

behavior are grouped into three categories: weather, 

topography, and fuels. The Rothermel (1972) surface fire 

spread model uses fuel moisture and wind to represent 

weather’s influence, slope, and elevation to characterize 

the topographic factor, and a collection of characteristic 

inputs called fire behavior fuel models as variables 

describing fuel complex characteristics. In support of 

firefighter safety and risk management, the original 13 

fuel models created by Rothermel (1972) and Albini 

(1976) were created to predict fire behavior under peak 

burning conditions. In these “worst-case scenarios,” 

fires predicted are considered to be influenced primarily 

by dead fuels and their characteristics. Though four of 

these 13 models include live fuels, the condition of those 

fuels is generally of secondary importance overall. With 

the increasing interest in fire use under more moderate 

conditions during the growing season and the imperative 

placed on designing fuel management practices to protect 

values in the wildland/urban interface, accurate estimates 

of fire behavior with increased live fuel influence and 

modified fuelbeds require some additional fuel model 

choices. The comments in this paper are intended to 

provide the reader with insights into these 40 new fuel 

models, the opportunities they provide, and the effects of 

some underlying model relationships that they bring out.

PURPOSE OF 40 ADDITIONAL

MODELS

Many of the more moderate conditions associated with 

fire use involve seasons and situations where live fuels 

can serve to reduce fire spread and intensity to varying 

degrees. To reflect these conditions, 27 of the 40 new 

fuel models developed by Scott and Burgan (2005) 

include live fuel loads, which result in a greater range 

of potential fire behavior for any given set of weather 

conditions.

Throughout the United States, most wildland fuelbeds 

need to be fairly dry to support active fire spread. 

However, in areas like the southeastern U.S., some fuels 

will ignite and continue to burn under much higher 

moisture regimes. Whereas the original 13 included 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 79

only two fuel models that emphasized this characteristic, 

the new set of 40 include 14 models designated as 

humid-climate fuels with significantly higher moisture 

of extinction (ME) parameters. ME is the dead fuel 

moisture above which fires cannot actively spread.

In addition to creating two new categories of carrier 

fuels (grass-shrub and timber understory), the new set 

of fuel models includes from four to nine model choices 

within each carrier fuel category. The increased number 

of choices allows for more accurate reflection of the range 

of potential fire behavior among similar fuelbeds. In 

forested situations, models of crown fire potential and 

canopy scorch/mortality use surface fire intensity as a 

primary factor. Without accurate predictions of surface 

fire behavior, users will be unable to accurately evaluate 

the effectiveness of fuel reduction projects that are 

intended to reduce the probability and extent of damage 

to the forest canopy.

With these additional choices, users are more likely to 

find an appropriate fuel model within the carrier category 

that can be related to the vegetative cover on their site. 

More consistent and predictable relationships between 

cover and fuels will allow for more effective use of remote 

sensing techniques and automated updating of fuel 

classifications. The full potential of landscape assessment 

tools such as FARSITE, FLAMMAP, and FSPro will not 

be realized until classifications of fuels are accurate across 

entire landscapes.

FUEL MODEL CHARACTERISTICS

Table 1 lists all 53 fuel models and the characteristic 

model parameters for each. It can be used to make 

comparisons between familiar models among the original 

13 and alternatives that may be considered among the 40 

new models. Intrinsic characteristics of the fuel particles 

include the dead and live heat content and the dead fuel 

ME. Extrinsic characteristics are based on the size, shape, 

quantity, and arrangement of those fuel particles. They 

include the bed depth as well as the fuel loading and 

surface area to volume ratio (SAV) for each fuel size class 

(1-hr, 10-hr, 100-hr) and type (herbaceous and woody).

One new parameter has been added to designate fuel 

models that are dynamic; i.e., with herbaceous fuel loads 

that can be transferred between live and dead categories. 

Fuel models without herbaceous fuels are considered 

static. Figure 1 demonstrates the increased effect of the 

fuel load transfer between live and dead on resulting 

spread and intensity. While the original fuel model 

FB2 (timber grass and understory) shows only a limited 

influence of herbaceous fuel moisture, that influence 

in the new models (GR2, GR4, GR7, GR9) can be 

dramatic.

Each model has a characteristic ME. The 14 new models 

designated for humid climates have a ME of 30 percent 

or higher, allowing fuels to burn under much higher 

moisture content. Figure 2 shows an example of the 

difference between two fuel models with otherwise similar 

characteristics; GR4 has a ME of 15 percent, as compared 

to 40 percent for GR5. At 15 percent 1-hr fuel moisture, 

GR4 exhibits no spread while GR5 shows spread rates of 

40 chains/hour and flame lengths between 8 and 9 feet.

INTERACTIONS WITH THE 

ROTHERMEL SURFACE FIRE 

SPREAD MODEL

Figure 3 depicts the Rothermel (1972) surface fire 

spread model. In the equation, the numerator, identified 

as the “Heat Source,” represents the heat available to 

ignite adjacent fuels, effectively promoting fire spread. 

The denominator, labeled the heat sink, estimates the 

heat needed to remove moisture and raise fuel particles 

to the ignition temperature. The calculations are fairly 

straightforward for wildland fuelbeds that contain 

predominantly dead fuels.

Fire modeling needs to recognize that the moisture 

content of live fuels is higher and varies over a wider 

range than that of dead fuels. Live fuels can burn 

at a higher moisture content but also can serve to 

impede spread. Rothermel’s model accounts for these 

differences by estimating the reaction intensity and heat 

of pre-ignition separately for live and dead fuels, then 

combining them.
80 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Carrier FM # FM

Code Fuel Model Name 1hrLoad

10hr

Load

100hr

Load

Herb

Load

Woody

Load

Total

Load Dynamic 1hrSAV

Herb

SAV

Woody

SAV

Bed

Depth

Moist

Extinct

Dead

Heat

Live

Heat

GR 1 FB1 Short grass 0.7 0.0 0.0 0.0 0.0 0.7 static 3500 9999 9999 1.0 12 8000 8000

GR 2 FB2 Timber grass and understory 2.0 1.0 0.5 0.5 0.0 4.0 static 3000 1500 9999 1.0 15 8000 8000

GR 3 FB3 tall grass 3.0 0.0 0.0 0.0 0.0 3.0 static 1500 9999 9999 2.5 25 8000 8000

GR 101 GR1 Short, sparse dry climate grass 0.1 0.0 0.0 0.3 0.0 0.4 dynamic 2200 2000 9999 0.4 15 8000 8000

GR 102 GR2 Low load dry climate grass 0.1 0.0 0.0 1.0 0.0 1.1 dynamic 2000 1800 9999 1.0 15 8000 8000

GR 103 GR3 Low load very coarse humid climate grass 0.1 0.4 0.0 1.5 0.0 2.0 dynamic 1500 1300 9999 2.0 30 8000 8000

GR 104 GR4 Moderate load dry climate grass 0.3 0.0 0.0 1.9 0.0 2.2 dynamic 2000 1800 9999 2.0 15 8000 8000

GR 105 GR5 low load humid climate grass 0.4 0.0 0.0 2.5 0.0 2.9 dynamic 1800 1600 9999 1.5 40 8000 8000

GR 106 GR6 moderate load humid climate grass 0.1 0.0 0.0 3.4 0.0 3.5 dynamic 2200 2000 9999 1.5 40 9000 9000

GR 107 GR7 High load dry climate grass 1.0 0.0 0.0 5.4 0.0 6.4 dynamic 2000 1800 9999 3.0 15 8000 8000

GR 108 GR8 High load very coarse humid climate grass 0.5 1.0 0.0 7.3 0.0 8.8 dynamic 1500 1300 9999 4.0 30 8000 8000

GR 109 GR9 very high load humid climate grass 1.0 1.0 0.0 9.0 0.0 11.0 dynamic 1800 1600 9999 5.0 40 8000 8000

GS 121 GS1 low load dry climate grass-shrub 0.2 0.0 0.0 0.5 0.7 1.4 dynamic 2000 1800 1800 0.9 15 8000 8000

GS 122 GS2 moderate load dry climate grass-shrub 0.5 0.5 0.0 0.6 1.0 2.6 dynamic 2000 1800 1800 1.5 15 8000 8000

GS 123 GS3 moderate load humid climate grass-shrub 0.3 0.3 0.0 1.5 1.3 3.3 dynamic 1800 1600 1600 1.8 40 8000 8000

GS 124 GS4 high load humid climate grass-shrub 1.9 0.3 0.1 3.4 7.1 12.8 dynamic 1800 1600 1600 2.1 40 8000 8000

SH 4 FB4 chaparral 5.0 4.0 2.0 0.0 5.0 16.0 static 2000 9999 1500 6.0 20 8000 8000

SH 5 FB5 brush 1.0 0.5 0.0 0.0 2.0 3.5 static 2000 9999 1500 2.0 20 8000 8000

SH 6 FB6 dormant brush 1.5 2.5 2.0 0.0 0.0 6.0 static 1750 9999 9999 2.5 25 8000 8000

SH 7 FB7 southern rough 1.1 1.9 1.5 0.0 0.4 4.9 static 1750 9999 1500 2.5 40 8000 8000

SH 141 SH1 low load dry climate shrub 0.3 0.3 0.0 0.2 1.3 2.0 dynamic 2000 1800 1600 1.0 15 8000 8000

SH 142 SH2 moderate load dry climate shrub 1.4 2.4 0.8 0.0 3.9 8.4 static 2000 9999 1600 1.0 15 8000 8000

SH 143 SH3 moderate load humid climate shrub 0.5 3.0 0.0 0.0 6.2 9.7 static 1600 9999 1400 2.4 40 8000 8000

SH 144 SH4 low load humid climate timber-shrub 0.9 1.2 0.2 0.0 2.6 4.8 static 2000 1800 1600 3.0 30 8000 8000

SH 145 SH5 high load dry climate shrub 3.6 2.1 0.0 0.0 2.9 8.6 static 750 9999 1600 6.0 15 8000 8000

SH 146 SH6 low load humid climate shrub 2.9 1.5 0.0 0.0 1.4 5.8 static 750 9999 1600 2.0 30 8000 8000

SH 147 SH7 very high load dry climate shrub 3.5 5.3 2.2 0.0 3.4 14.4 static 750 9999 1600 6.0 15 8000 8000

SH 148 SH8 high load humid climate shrub 2.1 3.4 0.9 0.0 4.4 10.7 static 750 9999 1600 3.0 40 8000 8000

SH 149 SH9 very high load humid climate shrub 4.5 2.5 0.0 1.6 7.0 15.5 dynamic 750 1800 1500 4.4 40 8000 8000

TU 10 FB10 timber litter and understory 3.0 2.0 5.0 0.0 2.0 12.0 static 2000 9999 1500 1.0 25 8000 8000

TU 161 TU1 light load dry climate timber-grass-shrub 0.2 0.9 1.5 0.2 0.9 3.7 dynamic 2000 1800 1600 0.6 20 8000 8000

TU 162 TU2 moderate load humid climate timber-shrub 1.0 1.8 1.3 0.0 0.2 4.2 static 2000 9999 1600 1.0 30 8000 8000

TU 163 TU3 moderate load humid climate timber-grass-shrub 1.1 0.2 0.3 0.7 1.1 3.3 dynamic 1800 1600 1400 1.3 30 8000 8000

TU 164 TU4 dwarf conifer with understory 4.5 0.0 0.0 0.0 2.0 6.5 static 2300 9999 2000 0.5 12 8000 8000

TU 165 TU5 very high load dry climate timber-shrub 4.0 4.0 3.0 0.0 3.0 14.0 static 1500 9999 750 1.0 25 8000 8000

TL 8 FB8 compact timber litter 1.5 1.0 2.5 0.0 0.0 5.0 static 2000 9999 9999 0.2 30 8000 8000

TL 9 FB9 hardwood litter 2.9 0.4 0.2 0.0 0.0 3.5 static 2500 9999 9999 0.2 25 8000 8000

TL 181 TL1 Low load compact conifer litter 1.0 2.2 3.6 0.0 0.0 6.8 static 2000 9999 9999 0.2 30 8000 8000

TL 182 TL2 low load broadleaf litter 1.4 2.3 2.2 0.0 0.0 5.9 static 2000 9999 9999 0.2 25 8000 8000

TL 183 TL3 moderate load conifer litter 0.5 2.2 2.8 0.0 0.0 5.5 static 2000 9999 9999 0.3 20 8000 8000

TL 184 TL4 Small downed logs 0.5 1.5 4.2 0.0 0.0 6.2 static 2000 9999 9999 0.4 25 8000 8000

TL 185 TL5 high load conifer litter 1.2 2.5 4.4 0.0 0.0 8.1 static 2000 9999 1600 0.6 25 8000 8000

TL 186 TL6 moderate load broadleaf litter 2.4 1.2 1.2 0.0 0.0 4.8 static 2000 9999 9999 0.3 25 8000 8000

TL 187 TL7 Large downed logs 0.3 1.4 8.1 0.0 0.0 9.8 static 2000 9999 9999 0.4 25 8000 8000

TL 188 TL8 long-needle litter 5.8 1.4 1.1 0.0 0.0 8.3 static 1800 9999 9999 0.3 35 8000 8000

TL 189 TL9 very high load broadleaf litter 6.7 3.3 4.2 0.0 0.0 14.1 static 1800 9999 1600 0.6 35 8000 8000

SB 11 FB11 light slash 1.5 4.5 5.5 0.0 0.0 11.5 static 1500 9999 9999 1.0 15 8000 8000

SB 12 FB12 medium slash 4.0 14.0 16.5 0.0 0.0 34.6 static 1500 9999 9999 2.3 20 8000 8000

SB 13 FB13 heavy slash 7.0 23.0 28.1 0.0 0.0 58.1 static 1500 9999 9999 3.0 25 8000 8000

SB 201 SB1 low load activity fuel 1.5 3.0 11.0 0.0 0.0 15.5 static 2000 9999 9999 1.0 25 8000 8000

SB 202 SB2 moderate load activity or low load blowdown 4.5 4.3 4.0 0.0 0.0 12.8 static 2000 9999 9999 1.0 25 8000 8000

SB 203 SB3 high load activity fuel or moderate load blowdown 5.5 2.8 3.0 0.0 0.0 11.3 static 2000 9999 9999 1.2 25 8000 8000

SB 204 SB4 high load blowdown 5.3 3.5 5.3 0.0 0.0 14.0 static 2000 9999 9999 2.7 25 8000 8000

Table 1.—Fuel model parameters for use with the Rothermel surface fire spread model; dynamic models are shaded
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 81

1 

Figure 1.—Effect of dynamic fuel load transfer on surface 

fire behavior.

Figure 2.—Moisture of extinction effect on fire behavior.

Figure 3.—Rothermel surface fire spread model.

HERBACEOUS FUEL LOAD

TRANSFER

Grasses and forbs are highly variable as fuels, changing 

continuously from the beginning until the end of 

each fire season. They begin the year as largely dead 

surface fuels remaining from the previous season’s 

growth, develop significant live fuel loading as they 

grow, and then become dead fuels through seasonal 

curing, drought, or frost damage. Until the new fuel 

models were developed, all live fuels were considered 

living, with no way to enter fuel moistures as low as 

those reached by dead fuels. The only way to capture 

the range of conditions described above was to utilize 

different fuel models at different stages in the season. 

For modeling efforts that span only short periods, fuel 

model classifications did not need to change. However, as 

landscape fire behavior models become more widely used 

and managers demand predictions over longer periods 

(weeks or months), fuel models must be responsive to 

these growing-season changes.
82 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

With the original 13 fuel models, the effects of fuel 

characteristics and fuel moisture were related but 

separate, with fuel moisture affecting the moisture 

damping and heat of pre-ignition factors in the model. 

Seventeen of the 27 new models with live fuel loads 

are considered “dynamic.” They include an herbaceous 

fuel load that the user can designate as live, dead, 

or in proportionate combinations of live and dead. 

Of the original 13 models, only FB2 (timber grass 

and understory) has herbaceous loads. It does not 

accommodate herbaceous load transfer between live and 

dead fuels.

This dynamic feature was originally designed to operate 

much the same way that it does in the National Fire 

Danger Rating System (NFDRS), with the fuel load 

transfer determined by the estimated herbaceous 

fuel moisture. Using this method of transfer, the 

entire herbaceous fuel load is considered live when 

the herbaceous fuel moisture (HFM) is at least 120 

percent and entirely dead at an HFM of 30 percent. 

Between those two HFM values, the load is distributed 

proportionately between live and dead.

Andrews et al. (2006) refer to numerous examples of 

grass fuels in Australia and New Zealand as evidence that 

the relationship may not be valid. Despite such criticism, 

most of the software systems that use these dynamic fuel 

models transfer the load automatically based on HFM. 

Table 2 highlights the sensitivity of spread and intensity 

to small changes in HFM. In this example using GR7, if 

HFM is changed from 101 percent to 98 percent, spread 

rate more than doubles from 16 to 34 chains per hour.

As this method of fuel load transfer is used in the 

dynamic models, the effects of fuel moisture extend 

to other parts of the equation and may have some 

unanticipated effects on predicted fire behavior. Several 

of these effects are discussed here.

Windspeed Limit

The most significant impact of the fuel load transfer 

is that associated with the windspeed limit applied by 

the model. Figure 4 (equation from Rothermel [1972]) 

illustrates this limit. For each combination of inputs, 

resulting reaction intensity is compared to the value 

represented by the limit. If it falls below the limit value 

for the input windspeed, the effective windspeed used 

in the spread equation will be based on the wind limit 

function. If it exceeds the limit, the actual windspeed is 

used.

For dynamic models that have relatively high herbaceous 

fuel loads and/or relatively low 1-hr fuel loads, calculated 

reaction intensities for most windspeeds will fall below 

the wind limit. As herbaceous fuel is transferred from 

live to dead, the calculated value will approach the 

limit value. Once the limit is exceeded, the windspeed 

influence increases and results in the rapid shift in spread 

rate and intensity seen in many of the dynamic models. 

Table 2.—Surface fire behavior sensitivity to herbaceous 

load transfer

1

Figure 4.—Reaction intensity and windspeed, with and 

without windspeed limits.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 83

Figure 1 illustrates this relationship, which cannot be 

supported by measurement in the field.

Dead Fuel Characteristics

As herbaceous fuel is transferred from the live category 

to the dead category, its characteristic SAV is retained. 

Fuel models that include significant loads of both 1-hr 

and herbaceous fuels that have different SAV values can 

have their combined dead SAV altered significantly as 

herbaceous load is transferred. In the case of SH9 (Very 

high load, humid climate, shrub), the effect is counterintuitive, with the modeled spread leveling off and 

flame length actually decreasing as the herbaceous fuel 

moisture falls below 120 percent. Figure 5 demonstrates 

this unrealistic result.

Live Fuel Moisture of Extinction

As with the reaction intensity, separate moisture 

damping coefficients are calculated for live and dead 

fuels. Separate values of live and dead Reaction Intensity 

are calculated and then added together to produce an 

overall reaction intensity. Though the calculation is the 

same, there are some important differences. While the 

ME for dead fuels is a fuel model parameter, the live fuel 

ME is calculated from the dead fuel moisture, the dead 

fuel ME, and the ratio of live fuel load to dead fuel load. 

If the HFM determined the fuel load transferred, the 

ratio of live to dead load would decrease with decreasing 

Figure 5.—Linked effect of Live Fuel Moisture on dead fuel 

characteristics.

Figure 6.—Live Fuel Moisture and Live Fuel Moisture of 

Extinction.

herbaceous fuel moisture. The result can be rapidly 

increasing live fuel ME and increased Reaction Intensity 

contributions from live fuels. Figure 6 demonstrates this 

effect with GR3 (low load, very coarse, humid climate, 

grass).

Manual Fuel Load Transfer

Version 4 of BehavePlus allows the user to separate 

herbaceous fuel load transfer from HFM by creating 

an additional input called fuel load transfer portion if 

herbaceous fuels are present in the selected fuel model. 

With this option, the user can directly identify how 

much of the herbaceous fuel load is transferred from live 

(with a higher range of fuel moistures) to dead (with 

much lower fuel moistures possible). Figure 7 shows the 

relationship between two models of similar fuels, the 

static FB3 (tall grass) and the dynamic GR6 (moderate 

load, humid climate, grass). Using dead fuel moistures 

of 5 percent, 6 percent, and 7 percent, herbaceous fuel 

moisture of 100 percent, manual transfer of herbaceous 

load, midflame windspeed of 5 mph, and no slope, we 

can compare modeled spread rates and flame lengths. 

While the two fuel models have similar total fuel loads, 

FB3 loads are entirely in the 1-hr dead fuel class and 

GR6 loads are largely in the herbaceous fuel category. 

Modeled fire behavior converges only as the herbaceous 

fuel load in GR6 is nearly all converted from live to 

dead.
84 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Figure 7.—Manual transfer of herbaceous fuel.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 85

FUEL MODEL DESCRIPTIONS

Within each of the six fuel carrier categories, there are several important distinctions among the fuel models. 

We provide the following classification to help users select a model within each fuel carrier category:

Grass Fuels (GR)

Static

Dry Humid

FB1-Short grass FB3-Tall grass

FB2-Timber grass understory

Dynamic

Dry Humid

GR1-Short & sparse, dry climate, grass GR3-Low load, very coarse, humid climate, grass

GR2-Low load, dry climate, grass GR5-Low load, humid climate, grass

GR4-Moderate load, dry climate, grass GR6-Moderatae load, humid climate, grass

GR7-High load, dry climate, grass GR8-High load, very coarse, humid climate, grass

 GR9-Very high load, humid climate, grass

Grass-Shrub (GS)

All Dynamic

Dry Humid

GS1-Low load, dry climate, grass-shrub GS3-Mod. load, humid climate, grass-shrub

GS2-Mod. load, dry climate, grass-shrub GS4-High load, humid climate, grass-shrub

Shrub (SH)

Static

Dry Humid

FB4-Chaparral FB7-Southern Rough

FB5-Brush

FB6-Dormant brush

SH2-Mod. load, dry climate, shrub SH3-Mod. load, humid climate, shrub

SH5-High load, dry climate, shrub SH4-Low load, humid climate, timber-shrub

SH7-Very high load, dry climate, shrub SH6-Low load, humid climate, shrub

 SH8-High load, humid climate, shrub

Dynamic

Dry Humid

SH1-Low load, dry climate, shrub SH9-Very high load, humid climate, shrub

Timber Understory (TU)

Static

Dry Humid

FB10-Timber litter and understory

TU4-Dwarf conifer with understory TU2-Mod. load, humid climate, timber-shrub

TU5-Very high load, dry climate, timber-shrub

dynamic

Dry Humid

TU1-Low load, dry, timber-grass-shrub TU3-Mod. load, humid, timber-grass-shrub
86 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Timber Litter (TL)

All Static

All have higher ME (25-30 percent).

Conifer Hardwood

FB8-Compact timber litter

TL4-Small downed logs

TL7-Large downed logs

TL1-Low load, compact conifer litter FB9-Hardwood litter

TL3-Mod load, conifer litter TL2-Low load, broadleaf litter

TL5-High load, conifer litter TL6-Mod. load, broadleaf litter

TL8-Long needle litter TL9-Very high load, broadleaf litter

Slash Blowdown (SB)

Original 13 New 40

FB11-Light slash SB1-Low load activity fuel

FB12-Medium slash SB2-Mod. load activity or low load blowdown

FB13-Heavy slash SB3-High load activity or mod. load blowdown,

 SB4-High load blowdown

SELECTING APPROPRIATE 

FUEL MODELS

With 53 fuel models to choose from, making an 

individual selection may seem overwhelming. At this 

point, conventional wisdom suggests that users should 

keep the two sets (the original 13 models and the new 

40) separate. Somewhat differently than outlined by 

Scott and Burgan (2005), we suggest that users consider 

the following issues to narrow the choices:

1) First, determine the primary carrier (grass, grass/

shrub, shrub, timber understory, timber litter, 

or slash/blowdown). If at all possible, use the 

category that matches the vegetative cover type.

2) Evaluate the need to model herbaceous fuel load 

transfer. Such a model would be recommended 

for analyses that span longer periods or that 

include different seasons.

3) Consider moisture of extinction, especially for 

the grass, grass/shrub, and shrub categories. If 

the fuels that are burning continue to spread at 

high dead fuel moisture levels, the humid climate 

fuels should be considered. However, these fuel 

models may not accurately recognize the typical 

cessation of spread during the nighttime hours.

4) Match fuel load distribution, total loading, and 

bed depth. There may be several choices that 

represent a range of fire behavior, and these 

choices are likely to present an appropriate range 

for both spread and intensity outputs.

5) Finally, evaluate the resulting ranges of spread 

rate and fireline intensity based on expected 

weather (represented by wind and dead fuel 

moisture) and live fuel moisture condition. 

Comparing these results with expected/observed 

fire behavior will often make the choice clear. 

Users should examine model outputs for 

the range of possible temperature, relative 

humidity, and wind and slope conditions likely 

to be experienced. For fuel models with live 

fuels, examine the effect of live fuel moisture 

conditions for likely combinations of weather 

and terrain inputs to insure that results are as 

expected.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 87

CONCLUSIONS

With the introduction of 40 additional fuel models, 

users of fire behavior prediction systems are confronted 

with new opportunities and the increased importance 

of several concepts. More fuel models are offered with 

high moisture of extinction distributed across the 

carrier categories. There are additional models with 

live fuel loads, especially herbaceous fuel loads that can 

be transferred from live to dead. This facility, whether 

handled automatically through linkage to the HFM or by 

directly entering a fuel load transfer portion, effectively 

allows the user to create new fuel models as the fuel 

load transferred changes. By selecting a “dynamic” fuel 

model, users who have never created or used custom fuel 

models will be assuming that responsibility. They should 

do so knowing the effects of that choice. Users should 

make fire behavior predictions for a range of anticipated 

or forecasted conditions to insure that the outputs 

effectively represent observed and potential fire behavior. 

BehavePlus can effectively be used to evaluate these 

relationships, especially Version 4, which allows for user 

designated transfer of herbaceous fuel loads.

LITERATURE CITED

Albini, F.A. 1976. Estimating wildfire behavior and 

effects. Gen. Tech. Rep. INT-30. Ogden, Utah: 

U.S. Department of Agriculture, Forest Service, 

Intermountain Forest and Range Experiment Station. 

92 p.

 Andrews, P.L.; Anderson, S.A.J.; Anderson, W.R. 

2006. Evaluation of a dynamic load transfer 

function using grassland curing data. In: Andrews, 

P.L.; Butler, B.W., comps. Proceedings, fuels 

management—how to measure success; 2006 March 

28-30; Portland, OR. Proc. RMRS-P-41. Fort Collins, 

CO: U.S. Department of Agriculture, Forest Service, 

Rocky Mountain Research Station: 381-394.

Rothermel, R.C. 1972. A mathematical model for 

predicting fire spread in wildland fuels. Res. 

Pap. INT-115. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Forest and 

Range Experiment Station. 40 p.

Scott, J.H.; Burgan, R.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.

other resources

Anderson, H.E. 1982. Aids to determining fuel models 

for estimating fire behavior. Gen. Tech. Rep. INT122. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Forest and Range 

Experiment Station. 22 p.

Rothermel, R.C. 1983. How to predict the spread 

and intensity of forest and range fires. Gen. Tech. 

Rep. INT-143. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Intermountain Forest and 

Range Experiment Station. 161 p.

Scott, J.H. 2007. Nomographs for estimating 

surface fire behavior characteristics. Gen. Tech. 

Rep. RMRS-GTR-192. Fort Collins, CO: U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Research Station. 119 p.

Van Wagner, C.E. 1977. Conditions for the start and 

spread of crown fire. Canadian Journal of Forest 

Research. 7: 23-34.
88 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

SMOKE MODELING IN SUPPORT OF MANAGEMENT OF FOREST

LANDSCAPES IN THE EASTERN UNITED STATES

Gary L. Achtemeier1

1

Research Meteorologist, Center for Forest Disturbance Science, U.S. Forest Service, Southern Research Station, Athens, GA

To contact, call (706) 559-4239 or email at gachtemeier@fs.fed.us

Abstract.—The impact of smoke from forest burning on air quality is a threat to the use of prescribed 

fire to manage woodlands in the eastern United States. Population shifts from urban centers to the 

wildland/urban interface have increased human exposures to smoke. Tighter national ambient air 

quality standards restrict the amount of smoke released over an area. This article reviews smoke 

models available prior to 1990 and those currently in use or under development. Models have become 

more sophisticated with advances in computer technology. The outcomes are suites of models that 

can describe smoke from release to vertical transport to dispersion in ways that realistically simulate 

how land managers conduct their burns. The results from the models can inform land managers 

about weather conditions and procedures to do their burns so as to minimize downwind impacts 

of smoke. However, effects of errors that stem from uncertainties in variables ranging from fuel 

loadings to weather forecasts temper optimism about the application of these models to eastern forests.

INTRODUCTION

Prescribed fire is used extensively throughout hardwood 

and pine lands in eastern U.S. forests to achieve a 

number of land management objectives (Wade et al. 

2000, Brose et al. 2005, Wade et al. 2000). One of 

the adverse consequences of prescribed burning is 

degradation of air quality (Ward and Hardy 1991, 

Sandberg et al. 1999, Riebau and Fox 2001). Air 

pollution from smoke raises the need to balance issues 

of human health risks, nuisance smoke, visibility 

impairment, and transportation hazards with issues of 

forest health and safety, wildlife management, ecosystem 

restoration, timber production, and carbon sequestration 

(Achtemeier et al. 1998).

Smoke impacts air quality on two scales. Exposures on 

the local scale are typically high concentrations of short 

duration (hours to a day) from a single prescribed burn. 

Burns are conducted to minimize smoke impacts on 

“sensitive targets”—schools, hospitals, nursing homes, 

airports, urban areas, and highways. These goals are 

not always achieved given local variability of weather 

conditions, especially wind direction. Exposures on the 

regional scale are typically relatively low concentrations 

of smoke (along with other pollutants) of long duration 

(months to years) from numerous sources spread over a 

region and over time.

Smoke management is the action by the land manager 

to minimize the environmental impact of smoke. The 

amount of smoke put into the atmosphere is determined 

by how much of the fuel on a landscape is consumed. 

The rate of transport of smoke into the atmosphere is 

determined by how the manager spreads fire on the 

landscape. Backfires release relatively small amounts of 

smoke per unit time in comparison with stripping, spot 

ignitions, and aerial ignition. How smoke is distributed 

vertically in the atmosphere depends on stability and 

winds during the course of the burn and how much 

heat is released from burning fuels. Where smoke goes is 

determined by wind direction and how far smoke goes 

is determined by wind speed of the air containing the 

smoke. All of the above are factors in a well written burn 

plan as land managers consider potential sensitive targets 

immediately downwind from their proposed burn and 

more distant targets such as urban areas that could be 

impacted by the smoke.

In addition, some states have in place smoke 

management guidelines designed to regulate the amount 

of smoke allowable within an area. Some guidelines are 

defined through simple estimates of the capacity of the 

atmosphere to carry smoke, coupled with experience 

gained through the number of complaints of nuisance 

smoke. Other guidelines regulate smoke in relation 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 89

to the distance to downwind sensitive targets. In the 

future, smoke management guidelines may be linked 

to national ambient air quality standards, with the 

current particulate matter (PM2.5)limit set by the U.S. 

Environmental Protection Agency in 2007 at 35 μg m-3

in a 24-hour period on 98 percent of days. (The annual 

standard remains at 15 μg m-3.)

This paper describes some of the tools that have been 

developed to aid the land manager and the regulator 

in answering the primary questions regarding smoke: 

1) Where will the smoke go?; and 2) How much will 

get there? As the emphasis is on eastern forests, some 

smoke models in application elsewhere will be omitted 

(Sestak and Riebau 1988, Lahm 2006). Some of the early 

smoke management tools developed before 1990 will 

be reviewed. Then the development of plume models 

designed to simulate smoke from individual fires will 

be followed. Furthermore, plume models must link 

with regional-scale air quality models as regional-scale 

air quality is just the sum of local-scale contributions. 

Finally, managing smoke during the night differs from 

managing smoke during the day. This paper will examine 

tools designed to assist the land manager in tracking the 

movement of smoke at night with particular emphasis on 

the problem of smoke/fog impacting roadway visibility.

EARLY SMOKE 

MANAGEMENT TOOLS

Figure 1 shows the widespread distribution of the oakhickory and oak-pine forest types in the eastern U.S. In 

all, eastern forests compose roughly 60 to 70 percent 

of the forest lands of the contiguous United States. 

Figure 2 shows population density classes for the same 

areas. Note the extensive wildland/urban interface (red 

areas) extending from the southern states through the 

northeastern states. Only the forests of the western Great 

Lakes are relatively remote from large population areas.

Because of the extensive blending of population with 

eastern forest lands, managing smoke for local air quality 

has long been a critical component of prescribed fire. 

This necessity is especially the case for the southern 

states—roughly the states south of the Ohio River and 

from Texas eastward—where long growing seasons favor 

rapid fuel buildup, many ecosystems are fire adapted, and 

there is a fire return interval of 2 to 5 years.

Some of the early operational models for estimating 

smoke impacts on air quality were influenced by the 

work of Reiquam (1970), who published a “box model” 

for air pollution. Reiquam divided the lower atmosphere 

Figure 1.—Map showing eastern forests classified 

as oak-hickory (brown) and oak-pine (green). Map 

produced by Daniel Yaussy, U.S. Forest Service.

Figure 2.—Map showing the major wildland/urban 

interface areas in the eastern U.S., where significant 

human populations (red) are collocated with significant 

forest (or other natural vegetation) cover (green).
90 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

into boxes with height defined by the top of the 

boundary layer (mixing height) and length and width 

set large enough to keep the model computationally 

feasible but small enough to carry an easily defined mean 

wind that is representative of the wind throughout the 

box. The concentration of particulate matter within a 

box was a ratio of the sum of emissions within the box 

and particulate matter transported into the box from 

surrounding boxes with the flux of air passing through 

the box.

The box model was considered unrealistic for estimating 

pollution from prescribed fires because of the assumption 

that emissions were uniformly distributed throughout the 

box. Because most particulate matter released in smoke 

is carried to near the top of the mixing layer and then 

mixed down farther downwind, it was judged that the 

box model overestimated smoke concentrations until 

about 100 km from the source of the emissions (Pharo et 

al. 1976).

Nevertheless, the concept of the ratio of emissions to 

volume flux of air passing over a burn site took hold. 

The ventilation index (VI) is defined as the product of 

the mixing height and the mean wind speed through 

the layer of the atmosphere from the surface to the 

mixing height. The crosswind width of the box is a unit 

dimension needed to maintain the concept of volume 

flux.

The transport wind speed and direction, mixing height, 

and VI are routinely transmitted by the National 

Weather Service in its fire weather forecasts. South 

Carolina smoke management guidelines classify VI into 

five “category days” for regulating prescribed burning. 

The amount of land permitted to be burned is restricted 

in each class. No sound scientific data exist to define 

burning limits for the category days. Therefore, these 

limits are arbitrary, set by the number of complaints of 

smoke by the public.

Despite the compelling logic of the ventilation index, 

preliminary results from the Southeastern Smoke 

Project, a 5-year effort measuring fire activity data, PM2.5 

concentrations from a network of up to 22 samplers, 

and concurrent weather data for 56 prescribed burns 

are showing little to no correlation between smoke 

concentrations and the VI. Reasons for the lack of 

correlation remain unclear, but three possibilities stand 

out. First, for operational considerations, a 24-hour 

prediction of the VI was used for the analyses. Mixing 

height and transport wind speed can be difficult to 

predict. Second, smoke plume dynamics may be far 

more complex than assumed in the calculation of the VI. 

Third, VI may be valid at distances from the burns that 

are greater than distances of data collection.

Plume rise equations developed for stack emissions 

(Briggs 1969, 1971, 1972) were tested for applicability 

to prescribed fire by Pharo et al. (1976). One conclusion 

drawn from Briggs’ equations was that plumes from 

most southern prescribed fires are unable to penetrate a 

modest inversion of 1 °C at or above 100 m elevation. 

This conclusion reinforced Reiquam’s use of the mixing 

height as a lid for his box model.

In addition, Pharo et al. (1976) recognized that not 

all smoke is drawn up into the plume even during the 

hottest portion of convective lift phase in southern 

prescribed fires. They suggested a ratio of 60-percent rise 

to 40-percent no rise for a typical burn.

LOCAL SMOKE MODELS – DAYtime

VSMOKE

The above information was incorporated into a 

dispersion model based on Turner’s (1970) Gaussian 

dispersion theory. The outcome was VSMOKE (Lavdas 

1996), a smoke screening model that has been adapted 

for Forest Service applications in the Southeast (Bill 

Jackson, U.S. Forest Service, Asheville, NC, 2008, 

personal communication).

Figure 3 shows the fire activity data needed to input 

emissions data into VSMOKE. Land managers provide 

the area expected to be blackened (not the area to be 

burned) and estimates of the fuels that will be consumed 

(not total fuel loading). These data are input into a 

combustion model that estimates the amount of fuel 

consumed. Then a second model estimates the emissions 

factor (a fraction of the fuel consumed converted into 

fine particulate matter). Fine particulate emissions are 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 91

distributed over the course of the burn by a simple 

emissions production model. The emissions data 

are needed by VSMOKE to calculate downwind 

concentrations as a function of distance from the 

burn. (Note that the processing of fire activity data 

into emissions production estimates is required by 

all smoke models that calculate concentrations. 

Thus plume rise models could be substituted for 

VSMOKE on the last line of Fig. 3.)

Figure 4 shows an example of a VSMOKE-simulated 

Gaussian PM

2.5 concentration pattern for the Brush 

Creek prescribed burn in eastern Tennessee on 

March 18, 2006 (Jackson et al. 2007). As smoke 

spreads downwind (lines diverging from the burn 

site), mass conservation requires reduction in 

concentration. Therefore the highest concentrations 

of smoke and the greatest threat to air quality are 

found close to the location of the burn (dark maroon 

colors). VSMOKE gives land managers a rough 

estimate where smoke will go and how much will 

get there, given planned fire activity and prevailing 

weather.

VSMOKE technically is not a plume rise model. 

The user specifies how much smoke is released at 

the ground and how much smoke is released near 

the top of the mixing layer. In addition to Pharo et 

al.’s (1976) suggested 60-percent rise to the top of 

the mixing layer, a 75/25 percent ratio is also used. 

Therefore, although the assumption that all smoke is 

confined to the mixing layer is workable for the small 

prescribed fires for which the model was developed, it 

is known that plumes from large prescribed fires and 

wildfires rise above the mixing height and sometimes 

by several thousand meters. Consequently, much 

fine particulate matter can be transported above the 

boundary layer and away from ground-level sensitive 

targets. Furthermore, VSMOKE is a steady-state 

model. It does not account for vertical wind shear or 

for changes in wind conditions during the course of 

the burn. The model assumes a spatial steady state 

and therefore is not valid for smoke plumes over 

complex terrain. The outcome is that VSMOKE can 

overestimate smoke concentrations.

Black Area Estimated Estimated

Fuel Loading

Fuel Consumption

Emission Factor

Emission Production

Dispersion/Concentration

Photo series Photo series 

and FCCS and FCCS

Consume 3.0 Consume 3.0

Consume 3.0 Consume 3.0 

and FEPS and FEPS

FEPS

VSMOKE

Figure 3.—Modeling framework required for the input of 

emissions data into VSMOKE.

Figure 4.—Example of a VSMOKE-simulated concentration 

pattern from the Brush Creek prescribed fire in eastern 

Tennessee, March 18, 2006 (from Jackson et al. 2007).

CALPUFF

Of the many plume rise models that have been developed 

over the past several decades, CALPUFF is described 

here because it was selected as the plume rise model for 

the U.S. Forest Service regional-scale smoke production, 

transport, and dispersion framework, BlueSky. (More 

will be presented on BlueSky in the section on long-range 

transport.) CALPUFF removes many of the assumptions 

that limit VSMOKE (Scire 2000). CALPUFF is a non-
92 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

steady state puff model, meaning that emissions are 

injected into the atmosphere as self-contained volumes 

defined as “puffs.” The puff grows as it entrains 

ambient air. Thus, as the puff volume increases, the 

concentration of particulate matter contained in the 

puff decreases as the puff drifts downwind. Each puff 

is independent from all other puffs. This assumption 

makes CALPUFF ideal for simulating smoke transport 

and diffusion in nonsteady flows, including temporally 

and/or spatially varying flow fields due to influences of 

complex terrain, non-uniform land-use patterns, and 

coastal effects. CALPUFF also works for stagnation 

conditions characterized by calm or very low wind 

speeds with variable wind directions.

Daysmoke

Like CALPUFF, Daysmoke removes many of the 

assumptions that limit VSMOKE. Daysmoke is an 

extension of ASHFALL, a plume model developed 

to simulate deposition of ash from sugar cane fires 

(Achtemeier 1998). As adapted for prescribed fire, 

Daysmoke consists of four models: an entraining 

turret model, a detraining particle model, a large eddy 

parameterization for the mixed boundary layer, and a 

relative emissions model that describes the emission 

history of the prescribed burn.

From photogrammetric analysis of video footage of 

smoke plumes from burning sugar cane, Achtemeier and 

Adkins (1997) determined that a rising smoke plume 

could be described by a train of rising turrets of heated 

air that sweep out a three-dimensional volume (the 

plume pathway) as they expand through entrainment of 

surrounding air. The plume pathway can be envisioned as 

an inverted cone bent by the prevailing winds. The plume 

pathway ends where the plume vertical velocity falls 

below a prespecified value (currently 0.5 m s-1).

Daysmoke does not contain all smoke within the plume 

pathway. A stream of particles representing smoke is 

released through the plume pathway. Each particle 

represents a mass of smoke. For example, for current 

applications of Daysmoke, each particle represents 1 kg 

of PM

2.5 particulate matter. As the particles make their 

way up the plume pathway, turbulent mixing represented 

by stochastic equations in the model may place some 

particles outside of the plume. These particles are 

assumed to have been detrained from the plume and are 

subject to circulations within the free atmosphere. Thus, 

a Daysmoke plume can be represented schematically by 

Figure 5. For each plume pathway, three outcomes are 

possible. Smoke may exit the top of the mixing layer 

(dashed line), smoke may remain as a plume within the 

mixing layer, or smoke may be detrained.

Additional time-dependency is built in through the 

relative emissions model. An accurate emissions 

production model must estimate emissions as they 

change during the ramp-up, maximum combustion, and 

ramp-down phases of the burn. Timing of emissions 

production must match the diurnal evolution of the 

depth of the boundary layer so that the discharge of 

particulate matter within and above the mixing layer can 

be simulated with accuracy.

Given emissions and heat production, Daysmoke updates 

the plume pathways every 10 minutes. Furthermore, 

the relative emissions model permits multiple plume 

pathways simultaneously. This feature of Daysmoke 

allows for multiple-core updraft plumes. In comparison 

with single-core updrafts, multiple-core updrafts have 

smaller updraft velocities, are smaller in diameter, are 

more impacted by entrainment, and are therefore less 

efficient in the vertical transport of smoke. Single-core 

updraft plumes would be expected to transport smoke 

The visible plume – what 

the eye sees.

The detrained 

plume- what the PM 

sampler sees.

 Figure 5.—A conceptual model of a “typical” smoke plume 

(darkened area) and a trailing “pall” of detrained particulate 

matter. The top of the mixing layer is given by the dashed line.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 93

higher, more likely penetrating the mixing layer and 

injecting smoke into the free atmosphere, where it can be 

transported downwind with minimal impact on groundlevel targets. Multiple-core updrafts, as less efficient 

transporters of smoke, would be expected to grow less 

high and deposit most of the smoke within the mixing 

layer—where it can more readily impact sensitive targets.

The importance of multiple-core updraft plumes in the 

vertical transport of smoke is demonstrated with the 

Brush Creek prescribed burn on March 18, 2006 (Liu et 

al. 2006, Jackson et al. 2007). This burn caused a smoke 

incident at Asheville, NC, about 50 km from the burn. 

Figure 6 shows the multiple-core updraft structure of the 

plume. Two updraft cores are easily visible in the image. 

An additional one to three updraft cores can be deduced 

from the shape of the surrounding plume. Daysmoke 

was run 10 times for each updraft core number out 

to 10 updraft cores. Figure 7 shows the mean and 

distribution for each updraft core number compared 

with the maximum hourly PM2.5 concentration (dashed 

line) observed at Asheville. A one-core updraft plume 

would have produced PM2.5 concentrations of 45 μg m-3

at Asheville. By contrast a ten-core updraft plume would 

have produced PM2.5 concentrations of approximately 

240 μg m-3 at Asheville. The ten-core concentrations 

are five times greater than the one-core solution. The 

four-core solution produced PM2.5

 concentrations of 

approximately 140 μg m-3 at Asheville—the maximum 

hourly amount observed.

Daysmoke also has informed us on the role of the wind 

speed on the vertical distribution of smoke. When the 

wind speed is relatively strong, the plume pathway will 

be bent over and more smoke will be discharged in the 

mixing layer in comparison with relatively light wind 

speeds. Regarding light wind speeds, heat of combustion 

can organize the plume to stand more erect with a 

greater chance that smoke will be injected into the free 

atmosphere above the mixing height. Figure 8 shows 

the vertical distribution of smoke for two Daysmoke 

simulations for one-core updraft plumes. As Daysmoke 

was coupled with the Community Multiscale Air Quality 

(CMAQ) model for these simulations, the vertical 

coordinate is given by CMAQ layer. The mixing height 

is given by the dashed line and was held constant at 1 

km during the simulations. The left panel shows that 

33 percent of the smoke was injected above the mixing 

height. Smoke within the mixing layer increased toward 

the ground in response to the contribution of weaker 

plumes during the ramp-up and ramp-down phases of 

Figure 6.—Plume from the Brush Creek prescribed burn on March 18, 2006.

Figure 7.—The means and distributions for each updraft 

core number compared with the maximum hourly PM2.5

concentration (dashed line) observed at Asheville, NC.

300

250

200

150

100

50

0

1 2 3 4 5 10

Concentration (μgm-3)

Core Number
94 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

the burn. When the wind speed was cut in half, roughly 

70 percent of the smoke was deposited above the mixing 

height (right panel). The caveat is that smoke injected 

into the free atmosphere during light winds will not 

disperse much and can cause major air quality problems 

should weather conditions change to bring the plume 

back to the ground.

REGIONAL SMOKE MODELS

BlueSky

BlueSky was developed as part of a multi-agency effort 

to simulate and predict smoke from approved or planned 

prescribed fires, agricultural fires, and wildfires (O’Neill 

et al. 2003). It couples off-the-shelf weather, fuels, 

consumption, emissions, and dispersion models in a 

modular framework in order to produce these real-time 

predictions. By gathering and using information on all 

fire activity in a region, BlueSky not only predicts the 

smoke PM

2.5 impacts from a single fire, but also predicts 

cumulative impacts from multiple fires. BlueSky cannot 

be separated from highly complex weather models, as 

it is totally dependent on this input to develop smoke 

simulations for operational application. CALPUFF is the 

plume rise model currently preferred for BlueSky.

Table 1 shows potential uses and users of BlueSky. 

BlueSky is a decision-support tool that predicts smoke 

impacts from wildland fire and delivers these forecasts to 

managers through the Web. Like any complex computerautomated decision support system, BlueSky must 

have data and infrastructure to support its operation. 

In this case, the tool requires significant fire activity 

data and computer resources to operate, and expertise 

to produce meaningful assessments of products. Table 

2 shows implementation locations through the U.S. 

Forest Service Fire Consortia for Advanced Modeling of 

Meteorology and Smoke (FCAMMS) centers. Versions 

of the modeling framework have been available through 

the Web at all FCAMMS sites since 2005. However, 

BlueSky is constantly being upgraded and versions may 

vary from center to center. An example of a BlueSky run 

from the FCAMMS-EAMC (Eastern Area Modeling 

Consortium) is given in Figure 9.

A project was undertaken in 2005 to validate BlueSky for 

wildfires (Riebau at al. 2006). One of the outcomes was 

that BlueSky seems likely to be underestimating nearfield smoke concentrations and potentially overestimating 

far-field smoke concentrations. Subsequent conversations 

Vertical Profile of Particles for Model Burn

(LAT35-3) Normalized by CMAQ Layer

Thickness. Total Particles = 37074

3.55

4.1

3.68

3.42

3.2

3.27

3.65

2.66

2.44

11.35

58.67

0

0

0 20 40 60 80

1

2

3

4

5

6

7

8

9

10

11

12

13

Sigma Level

Percent of Total

Vertical Profile of Particles for Burn (LAT39-3)

 Normalized by CMAQ Layer Thickness.

Total Particles = 37070

8.29

8.74

7.99

7.41

7.58

7.16

7.38

6.33

5.61

18.09

15.42

0

0

0 5 10 15 20

1

2

3

4

5

6

7

8

9

10

11

12

13

Sigma Level

Percent of Total

Vertical Smoke Distribution by 

Daysmoke – Whole Burn

Figure 8.—Left panel: Whole burn distribution of smoke by CMAQ layer for a one-core 

updraft simulation. Right panel: Same as for the left panel except with the wind speed 

cut in half.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 95

a

 Wildland fire use

b

 Geographic Area Coordinating Center

c Incident Management Team

Potential Uses and Users of BlueSky Fires Users Rx WFUa Wildfire Fire Mgrs GACCb

IMTc

Regulators

Air Agencies

Health Agencies

Local Officials

Public

Researchers

Decision-making Support

(e.g., go/no-go, WFU classification)

Fire-fighting Tactics

(e.g., effects of burnouts)

Fire-fighting Resource Deployment

(e.g., aviation)

Improved Knowledge about Emissions, 

Climate

Location of Air Quality Monitors

Public Safety/Transportation

Single and Multiple Fire Impacts

(integrate across boundaries)

Notify Public

(health/nuisance/visibility)

Regulatory – emission inventory/

apportionment/background

After-action Assessments and 

Evaluations, Exceptional Event Analysis

Table 1.—Potential uses and users of BlueSky (after Riebau et al. 2006)

Domain Resolution FCAMMSb Stationc

WildfireRx fireAg fireRAINS

In Operation Since

Northwest 12 km NWRMC PNW * 2002 4 km

N. California 4 km CANSAC PSW 2004

S. California 4 km CANSAC PSW 2004

Northeast 12 km EAMC NRS M 2004

Rocky Mountain 6 km RMC RMRC M 2004

Southeast 12 km SHRMC SRS M

a

2005 4 km a

West (demo) 36 km NWRMC / RMC RMRC M 2005 12 km

M = manual only.

a in progress as of March 2006.

b Fire Consortia for Advanced Modeling of Meteorology and Smoke. NWRMC = Northwest Regional Modeling 

Consortium; CANSAC = California and Nevada Smoke and Air Consortium; EAMC = Eastern Area Modeling 

Consortium; RMC = Rocky Mountain Modeling Consortium; SHRMC = Southern High Resolution Modeling 

Consortium.

c U.S. Forest Service Research Stations, PNW = Pacific Northwest; PSW = Pacific Southwest; NRS = Northern 

Research Station; RMRS = Rocky Mountain Research Station; SRS = Southern Research Station.

Table 2.—BlueSky implementation locations (after Riebau et al. 2006)
96 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

with one of the authors of the study revealed that much 

of the error can be explained by the lack of accounting 

for multiple-core updraft plumes described with reference 

to Daysmoke.

Southern Smoke Simulation System (4S)

The Southern Smoke Simulation System couples the 

contribution of smoke from wildland burning with 

the overall air pollution budget over the southeastern 

United States. An overview of 4S is shown in Figure 10. 

Each box along the blue arrow represents steps needed 

to accomplish the objective of including emissions from 

wildland fires in regional-scale air quality models. The 

first box, Fire Data, gets the Southern High Resolution 

ModelingConsortium (SHRMC)-4S started. Information 

on the size of the tract of land to be burned, the date 

and time of the burn, the location of the burn, plus 

pertinent data on the kinds and state of fuels is supplied 

by the land manager. Fire activity data are processed 

through the software CONSUME and EPM (as does 

BlueSky) to produce emissions inventories for the burns 

(the Emissions Calculation box). The outputs—(the 

fire products)—are hourly productions of heat and the 

masses of gases and particulate compounds. The Sparse 

Figure 9.—Example of BlueSky output for April 10, 2008.

Fire Data

Emissions 

Calculation

SMOKE

CMAQ

Visualization

Weather Data

(MM5)

Figure 10.—An overview of the 4S framework.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 97

Matrix Operator Kernel Emissions Modeling System 

(SMOKE) (Houyoux et al. 2002) processes emission data 

and provides initial and boundary chemical conditions 

for the CMAQ model (Byun and Ching 1999) for 

chemical modeling (Fig. 10, fourth box). A visualization 

method for illustrating modeling results is the last step. 

The National Center for AtmosphericResearch (NCAR)/

Penn State Mesoscale Model (MM5) (Grell et al. 

1994) is used for providing meteorological conditions 

for emission calculation and SMOKE and CMAQ 

simulation.

Daysmoke, as the smoke injector simulator for 4S, allows 

for the representation of multiple-core updraft plumes. 

Figure 11 shows the heights of the smoke plume (plume 

rise) and vertical profiles of smoke PM2.5 

simulated with 

Daysmoke for one-core and ten-core updrafts for the 

course of the Brush Creek burn (Jackson et al. 2007). For 

the one-core updraft (left panels of Fig. 11), plume rise 

is about 1.5 km from 1200 to 1600 LST (local standard 

time) and increases to 2.1 km at 1700 LST. For the 

10-core updraft (right panels of Fig. 11), plume rise is 

about 0.75 km at 1200 LST with the largest percentage 

occurring at about 0.6 km. Plume rise gradually increases 

to 1.1 km at the next hour and remains there until 1700 

LST. It decreases to 0.92 km at 1800 LST.

These results show two differences between modeling 

smoke with one-core and ten-core updrafts. First, 

compared with single-core updrafts, multiple-core 

updraft plumes do not rise as high. Thus, more smoke 

mass is distributed at lower levels in the atmosphere. 

Second, plume rise simulations for one-core updrafts 

place the most smoke higher above the mixing layer 

than do simulations for ten-core updrafts. This 

discrepancy results in significant impacts on the ground 

concentrations when Daysmoke smoke profiles are linked 

to CMAQ.

Figure 12 shows time-height cross sections of PM2.5 

concentrations over Asheville as simulated by Daysmoke/

CMAQ run on a 12-km grid. The plume reaches 

Asheville after 1500 LST. Both simulations show 

two peaks in concentrations (an outcome of a 1-hour 

lapse in aerial ignition), the first arriving at 1600 

LST and the second arriving at 1800 LST. The main 

difference between the one-core and ten-core updraft 

simulations is in the vertical distributions of smoke. 

(a) (b)

Figure 11.—The vertical distribution of smoke particles (in %) at the hours from 1100 throughout 1800 LST (local 

standard time) calculated using Daysmoke; (a) one-core updraft, (b) ten-core updraft (from Liu et al. 2006). The light 

horizontal lines indicate the top of planetary boundary layer.
98 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Large concentrations are found between 1.1 and 1.5 

km above ground for the one-core updraft, and within 

about 1 km above ground for the ten-core updraft. The 

one-core simulation placed most smoke far enough above 

the planetary boundary layer (PBL) that few particles 

were transported to the ground (Fig. 12a). As Figure 

12b shows, most particles are found within the PBL 

for the ten-core updraft simulation and they are nearly 

uniformly distributed from the ground to the top of PBL 

by strong turbulent mixing.

In comparison with concentrations produced directly 

from Daysmoke (Fig. 7), ground-level concentrations 

were much reduced. Figure 13 shows the horizontal 

distribution of ground-level PM2.5 at 1700 LST, when 

largest concentrations were observed at Asheville. 

The smoke plume spreads from the burn site southsoutheastward to the North Carolina-South Carolina 

border. The under-prediction by CMAQ is primarily due 

to the 12-km resolution of the model domain, which 

spreads the plume too widely. The magnitudes of the 

concentrations for the ten-core updraft are about two to 

three times that for the one-core updraft. That ratio is 

five times in Figure 7.

Figure 12.—Time-height across section of PM2.5 concentration (μg m-3) at Asheville simulated with CMAQ with 

plume rise and smoke particle vertical profile specified with Daysmoke; (a) one-core updraft, (b) ten-core updraft 

(from Liu et al. 2006).

Figure 13.—Spatial distribution of ground PM2.5 concentration (μg m-3) at 1700 LST simulated with 

CMAQ using plume rise and smoke particle vertical profile specified with Daysmoke; (a) one-core 

updraft, (b) ten-core updraft (from Liu et al. 2006).
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 99

HYSPLIT

The HYbrid Single-Particle Lagrangian Integrated 

Trajectory (HYSPLIT) model (Draxler and Rolph 

2003, Rolph 2003) is a complete system for computing 

simple air parcel trajectories to complex dispersion 

and deposition simulations. A joint effort between the 

National Oceanic and Atmospheric Administration 

and Australia’s Bureau of Meteorology, the model has 

recently been upgraded to include modules for chemical 

transformations.

The dispersion of a pollutant is calculated by assuming 

either puff or particle dispersion. In the puff model, puffs 

expand until they exceed the size of the meteorological 

grid cell (either horizontally or vertically) and then 

split into several new puffs, each with its share of the 

pollutant mass. In the particle model, a fixed number 

of initial particles are advected about the model domain 

by the mean wind field and a turbulent component. 

The model’s default configuration assumes a puff 

distribution in the horizontal and particle dispersion in 

the vertical direction. In this way, the greater accuracy 

of the vertical dispersion parameterization of the particle 

model is combined with the advantage of having an everexpanding number of particles represent the pollutant 

distribution.

The model can be run interactively on the Web. Figure 

14 shows a sample HYSPLIT run for Nov. 25, 2007 

for a pollutant release from Carbondale, IL. HYSPLIT 

currently does not contain a plume rise model. Therefore, 

releases are done with the assumption of neutral 

buoyancy, but the user can specify the altitude of a 

release.

Full Physics Models

Plume rise models such as CALPUFF and Daysmoke 

represent a class of empirical models in which complex 

physical processes occurring in nature are approximated 

or parameterized by a set of simplifying equations. Some 

of these equations require pre-assigned coefficients. 

Liu (Yongqiang Liu, U.S. Forest Service, Athens 

GA, personal communication) performed a Fourier 

Amplitude Sensitivity Test (FAST) to identify which of 

the 13 parameters in Daysmoke impact plume rise. Table 

3 shows the parameters and the ranges of values assigned. 

Figure 14.—An example of a HYSPLIT simulation of a hypothetical release of pollution at 

Carbondale, IL, on Nov. 25, 2007.
100 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

The analysis included two ambient variables (stability 

and wind speed) that are not pre-assigned coefficients. 

The input parameters, assumed to be mutually 

independent, are varied simultaneously through the 

ranges of values. If Daysmoke were run for 10 values 

within the range for each input parameter, it would 

take 1015 runs to evaluate the impact of the parameters 

on the model. However, only 1,027 runs were required 

using FAST.

Figure 15 show the relative importance of the 15 

parameters to plume rise in Daysmoke. The first eight 

parameters, related to in-plume and atmospheric 

turbulence, are not important in determining plume 

rise. Only four model parameters substantially impact 

plume rise: entrainment coefficient (Pk), the number of 

updraft cores (Nc), the effective plume diameter (Fd), 

and the initial plume temperature (TD). The initial 

plume vertical velocity (Wo) showed little impact on 

plume rise.

Table 3.—Ranges of values assigned for the 13 parameters of Daysmoke and for two 

environmental parameters

Parameter Meaning Range

• Cp Plume turbulence coefficient 0.05-0.1

• Cu Air horizontal turbulence coefficient 0.1-0.2

• Cw Air vertical turbulence coefficient 0.05-0.1

• Kx Thermal horizontal mixing rate 1.0-1.5

• Kz Thermal vertical mixing rate 1.0-1.5

• Wc Plume-to-environ. cutoff velocity 0.2-0.8

• w* Air induced ash downdraft velocity 0.01-0.02

• Wr Maximum rotor velocity 1.0-1.5

• Pk Entrainment coefficient for plume 0.1-0.5

• W0 Initial plume vertical velocity 5.0-15.0

• TD Initial plume temperature anomaly 5.0-15.0

• Fd Effective diameter of flaming area -25%-25%

• Nc Number of core 1-20

• Tm Stability -25%-25%

• Vm Wind -25%-25%

Figure 15.—The relative importance of 13 parameters and two 

environmental variables to plume rise in Daysmoke. (See Table 3 

for definitions of the parameters.)

Impacts on model sensitivity via FAST

0

5

10

15

20

25

30

35

40

CpCu

Cw

KxKz

Wc

w*

Wr

Pk

W0

TD

Fd

Nc

TmVm

Parameter

Contribution (%)

2pm 3pm
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 101

Full physics models have the advantage of few to no 

pre-assigned parameters. Specification of initial plume 

diameters, temperatures, or vertical velocities are not 

required because full physics models develop plumes 

above areas of heat produced by combustion as fire 

spreads through model landscapes.

A full physics plume model that has been applied 

to wildland fire is the active tracer high-resolution 

atmospheric model (ATHAM) (Herzog et al. 1998, 

Oberhuber et al. 1998). Trentmann et al. (2002) 

simulated a prescribed burn in northwestern Washington 

which closely approximated measured elevations and 

concentrations of smoke. Furthermore, Trentmann 

et al. (2006) and Luderer et al. (2006) showed how 

meteorological dynamics coupled with a large wildfire 

in Alberta, Canada, could generate a pyrocumulus that 

reached an altitude of about 13 km. Figure 16 shows the 

100-μgm

-3 iso-surface of aerosol concentration after 40 

min. of integration. The figure gives an example of the 

detail obtainable with full physics models.

One disadvantage of the full physics models is the 

enormous computation time required. These models 

currently are unsuitable for simulating plume rise for 

hundreds of fires daily as required for operational use. 

However, if the increase of computational speed and 

power continues at the rate of the past decade, it is 

conceivable that full physics models may eventually find 

operational application.

LOCAL SMOKE MODELS – NIGHT: 

ROADWAY VISIBILITY AND

SUPERFOG

The environmental impact of smoke is often measured 

in terms of regional-scale concentrations, impacts on 

sensitive targets, and individuals’ respiratory function. 

However, a more deadly smoke impact, in terms of lives 

lost and personal injury, is from local smoke transport 

at night and its effects on roadway visibility. Smoke 

entrapped near the ground in nocturnal inversions 

can drift into populated areas and impact residents, 

particularly those with respiratory problems. Smokeladen air masses can drift across roadways and contribute 

to poor visibility. Smoke and associated fog have been 

implicated in multiple-car pile-ups that have caused 

fatalities, numerous physical injuries, and heavy property 

damage (Mobley 1989).

A particularly deadly smoke/fog incident occurred during 

the early morning of Jan. 9, 2008, when smoke from 

a 1,200-ha wildfire flashed into dense fog and drifted 

across Interstate 4 between Orlando and Tampa, FL. The 

resulting 70-vehicle pile-up killed five and injured 38.

Figure 16.—The smoke plume generated by the ATHAM model for a 

wildfire in Alberta, CAN, on May 29, 2001 (after Luderer et al. 2006).
102 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

The issue of smoke/fog on the highway is a two-part 

problem. The first is predicting where smoke goes. The 

second is understanding the dynamics of superfog – fog 

that reduces visibility to less than 3 m.

PB-Piedmont

Planned Burn-Piedmont (PB-P) (Achtemeier 2005) 

is a very high-resolution meteorological and smoke 

model that answers the question, “Where does smoke 

go at night?” (PB-P does not predict concentrations.) 

The model has been operational in parts of the South 

since 2005 and as of 2008 was modified for application 

anywhere in the United States. The model can be used 

predictively or diagnostically to simulate near-ground 

smoke transport at night over complex interlocking 

ridge-valley systems typical of landforms over much of 

the eastern United States.

Results from a PB-P simulation for smoke movement from 

a prescribed burn conducted at the Piedmont National 

Wildlife Preserve (PNWR) in central Georgia on Jan. 

15, 2003 are shown in Figures 17 and 18. Winds were 

blowing from the northwest during the burn. Figure 17 

shows the PB-P ground-level smoke plume (yellow dots) 

superimposed on local terrain and drifting southeastward 

from the burn site (rectangle) at 1800 EST. The difference 

between highest elevation (white areas) and lowest 

elevations (dark green) is approximately 100 m. The size 

of the area shown is a square 12.6 km on a side.

Weather patterns changed during the night of Jan. 15-

16 so that by morning, winds had shifted to blow from 

the southeast. The combination of southeast winds and 

drainage flows created the complex distribution of smoke 

shown in the PB-P simulation for 0800 EST (Fig. 18). 

Burn crews collected observations of smoke as they drove 

over roads surrounding the burn site. Red circles indicate 

where PB-P correctly located smoke. Triangles (red-smoke; 

green-no smoke) show where the model failed.

Figure 19 shows how PB-P performed for 20 prescribed 

burns at the PNWR. Field crews took observations of 

smoke at various times during the night after the burns. 

They reported smoke by following subjective criteria: no 

smoke, smoke smell, smoke haze, very light smoke, light 

smoke, moderate smoke, and dense smoke. These reports 

were combined into “smoke” and “no smoke” categories 

and were compared with smoke maps generated by PBP. If smoke (yellow dots) simulated by PB-P was located 

close to an observation, that point was designated a “hit” 

(see Fig. 18). Smoke hits and misses and no-smoke hits 

and misses were tabulated into a smoke matrix shown 

Figure 17.—PB-Piedmont simulated ground-level smoke 

plume for 1800 EST Jan. 15, 2003, approximately 15 

minutes after sunset. PB-P map is 12.6 km x 12.6 km.

Figure 18.—PB-Piedmont-simulated smoke at 0800 EST 

Jan. 16, 2003.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 103

in Figure 19. These results show a 77-percent correct 

prediction by PB-P.

Superfog

Kunkel (1984) and Kokkola et al. (2003) have shown 

that heavily polluted conditions can favor the formation 

of dense radiation fogs consisting of large numbers of 

relatively small droplets. Pollutants act in two ways 

to decrease visibility: 1) by increasing the number of 

particles, which increases the extinction coefficient for a 

given liquid water content (LWC); and 2) by decreasing 

droplet size, which decreases mean terminal velocity and 

thus minimizes the fallout of liquid water.

Natural fog LWC seldom reaches levels large enough to 

sustain superfog. Additional moisture is required for the 

formation of superfog. Potter (2005) argued that water 

released during combustion can lead to the development 

of clouds, even precipitating cumulus above some 

wildfires. Water is a product of combustion. For 6.7 

metric tons of fuel consumed per hectare, the chemistry 

of combustion yields 1.4 metric tons of water. To this, 

add in water evaporated from preheated fuels that are 

consumed and water evaporated from the ground and 

fuels not consumed. If the water equivalent released from 

these sources is just 0.025 cm, then the additional water 

released per hectare is 1.0 metric ton, for a total of 2.4 

metric tons. Thus, smoke moisture can be a significant 

source of water for the formation of superfog.

Another factor is how smoke moisture is added to the 

atmosphere. Achtemeier (2006) showed that shallow 

layers of air passing slowly over smoldering combustion 

may accumulate more water per unit mass of air than 

do large masses of air processed through flaming 

combustion. The result is that smoke moisture excesses 

calculated from smoldering fuels can be 10 times larger 

than moisture excesses for flaming combustion.

It is the nongradient mixing (Gerber 1991) of two 

masses of humid air of widely different temperatures that 

makes superfog possible. Achtemeier (2008) developed 

a superfog model that takes into account mixing and 

latent heat released in the fog. If the ambient air is less 

humid, smoke may flash into superfog initially but then 

dissipate by evaporation through additional mixing, 

leaving a plume of particulate matter to disperse. But if 

the ambient air is near saturation (which is most likely 

just before sunrise), smoke may flash into superfog and 

remain superfog as the weight of suspended liquid water 

pulls the plume to the ground.

Figure 20 shows superfog over Interstate 4 on the 

morning of Jan. 9, 2008. Invisible in this image are a sixlane expressway, 70 vehicles, and several burning tractortrailors. This fog was so dense during the night that 

motorists driving into it could not see the light reflected 

from their own headlights. The fog was described as a 

“black wall.”

Smoke Matrix for 20 Burns –

Georgia Piedmont

Smoke Prediction

Yes No

Smoke Observation

No Yes

152

25 55

38 270 observations 

77% correct 

prediction

. 

Figure 19.—Summary table for PB-Piedmont validation.

Figure 20.—Superfog over Interstate 4 on the morning of 

January 9, 2008. The plume of black smoke is from burning 

tractor trailers. (Photo courtesy of the local media.)
104 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

The impact of residual smoke on roadway visibility at night 

remains one of the most difficult smoke hazard prediction 

problems for the land manager. First, PB-Piedmont 

must provide accurate predictions of smoke transport 

within drainage flows over complex terrain. Second, the 

superfog model must accurately identify “flashpoint” 

temperatures—temperatures at which superfog forms 

rapidly. There are accounts of land managers who drove 

over the roads surrounding their burns into the wee 

hours of the morning and saw nothing save for some 

smoldering. Accordingly, they went home--only to learn 

that an accident had occurred in dense fog an hour later.

SUMMARY

The impact of smoke from agricultural and forest 

burning on air quality has been a major research topic 

for many decades not only in the United States but in 

many other places around the world. During this period 

many methods to simulate and predict the transport and 

dispersion of smoke have been developed. Some of these 

methods have never been written up; other methods 

languish, forgotten in obscure reports.

In this paper I have focused on those smoke models that 

have had, are having, and will have impacts on smoke 

management for eastern forests. The caveat is that the list 

includes those models I am aware of. There may be some 

excellent models I have not described.

Of the smoke models I have described, only VSMOKE 

is complete and operational. BlueSky and PB-Piedmont 

are scientific/application models that will undergo 

continuous modification as the science contributing to 

the various components improves. Both are operational, 

however, and can add value to a smoke management 

program. HYSPLIT is operational but needs a plume rise 

component to make it fully applicable for prescribed fire. 

The 4S is still under development.

Significant gaps remain. VSMOKE, designed to predict 

local smoke during daytime from a single prescribed 

burn, is limited by its assumptions. BlueSky is designed 

for regional-scale air quality. PB-Piedmont is designed to 

track smoke on the ground at night over a limited range 

of topographic conditions.

Plans call for Daysmoke to replace VSMOKE. 

Daysmoke removes the assumptions that limit 

VSMOKE. Furthermore, Daysmoke has shown the 

importance of multiple-core updraft plumes in the 

vertical transport of smoke. Neverthless, Daysmoke 

offers no pathways to predicting multiple-core updraft 

structures. This problem is the subject of ongoing 

research.

LITERATURE CITED

Achtemeier, G.L. 1998. Predicting dispersion and 

deposition of ash from burning cane. Sugar Cane. 1: 

17-22.

Achtemeier, G.L. 2005. Planned Burn—Piedmont. A 

local operational numerical meteorological model 

for tracking smoke on the ground at night: model 

development and sensitivity tests. International 

Journal of Wildland Fire. 14: 85-98.

Achtemeier, G.L. 2006. Measurements of moisture in 

smoldering smoke. International Journal of Wildland 

Fire. 15: 517-525.

Achtemeier, G.L. In press. On the formation and 

persistence of superfog in woodland smoke. 

Meteorological Applications.

Achtemeier, G.L.; Adkins, C.W. 1997. Ash and smoke 

plumes produced from burning sugar cane. Sugar 

Cane. 2: 16-21.

Achtemeier, G.L., Jackson, W.; Hawkins, B.; Wade, D.; 

McMahon, C. 1998. The smoke dilemma: a head-on 

collision! Transactions, 63rd North American wildlife 

and natural resources conference; 1998 March 20-24; 

Orlando, FL. Washington, DC: Wildlife Management 

Institute: 415-421.

Briggs, G.A. 1969. Plume rise. Oak Ridge, TN: 

U.S. Atomic Energy Commission, Environmental 

Sciences Service Administration, Air Resour. Atmos. 

Turbulence and Diffusion Laboratory. 81 p.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 105

Briggs, G.A. 1971. Some recent analyses of plume rise 

observations. Academic Press, NY: Proceedings, 2nd

International Clean Air Congress: 1029-1032.

Briggs, G.A. 1972. Discussion, chimney plumes in 

neutral and stable surroundings. Atmospheric 

Environment. 6(7): 507-510.

Brose, P.H.; Shuler, T.M.; Ward, J.S. 2005. Responses 

of oak and other hardwood regeneration to 

prescribed fire: what we know as of 2005. In: 

Dickinson, M.B., ed. Fire in eastern oak forests: 

delivering science to land managers; 15-17 November 

2005; Columbus, OH. Gen. Tech. Rep. GTRNRS-P-1. Newtown Square, PA: U.S. Department 

of Agriculture, Forest Service, Northern Research 

Station: 123-135.

Byun, D.W.; Ching, J. 1999. Science algorithms of the 

EPA Model-3 community multiscale air quality 

(CMAQ) modeling system. EPA/600/R-99/030. 

Research Triangle Park, NC: National Exposure 

Research Laboratory.

Draxler, R.R.; Rolph, G.D. 2003. HYSPLIT (HYbrid 

Single-Particle Lagrangian Integrated Trajectory) 

Model. Silver Spring, MD: NOAA Air Resources 

Laboratory. Available: www.arl.noaa.gov/ready/

hysplit4.html.

Gerber, H. 1991. Supersaturation and droplet spectral 

evolution in fog. Journal of the Atmospheric 

Sciences. 48: 2569-2588.

Grell, A.G.; Dudhia. J.; Stauffer, D.R. 1994. A 

description of the fifth-generation Penn State/

NCAR mesoscale model (MM5). NCAR Tech. Note 

398. Boulder, CO: National Center for Atmospheric 

Research. 122 p.

Herzog, M.; Graf, H.-F.; Textor C.; Oberhuber, J. 

M. 1998. The effect of phase changes of water on 

the development of volcanic plumes. Journal of 

Volcanology and Geothermal Research. 87: 55-74.

Houyoux, M.; Vukovich, J.; Seppanen, C.; Brandmeyer, 

J.E. 2002. SMOKE user’s manual. Chapel Hill, 

NC: University of North Carolina, Center for 

Environmental Modeling for Policy Development.

Jackson, W.A.; Achtemeier, G.L.; Goodrick, S. 2007. 

A technical evaluation of smoke dispersion 

from the Brush Creek prescribed fire and the 

impacts on Asheville, North Carolina. Available: 

http://199.128.173.141/smoke/March06/.

Kokkola, H.;Romakkaniemi, S; Laaksonen, A. 2003. 

On the formation of radiation fogs under heavily 

polluted conditions. Atmospheric Chemistry and 

Physics. 3: 581- 589.

Kunkel, B.A. 1984. Parameterization of droplet 

terminal velocity and extinction coefficient in fog 

models. Journal of Climate and Applied Meteorology. 

23: 34-41.

Lahm, P. 2006. A review of smoke management and 

emission estimation tools. Fire Management Today. 

66: 27-33.

Lavdas, L.G. 1996. Program VSMOKE–users manual.

Gen. Tech. Rep. SRS-6. Asheville, NC: U.S. 

Department of Agriculture, Forest Service. Southern 

Research Station. 156 p.

Liu, Y.Q.; Achtemeier, G.L.; Goodrick, S.; Jackson, W.A. 

2006. Regional air quality effects of Brush Creek 

burning simulated with CMAQ-Daysmoke. 3rd

International fire ecology and management congress; 

2006 November 13-17; San Diego, CA. Pullman, WA: 

Washington State University.

Luderer, G.; Trentmann, J.; Winterrath, T.; Textor, 

C.; Herzog, M.; Graf, H.-F.; Andreae, M.O. 2006. 

Modeling of biomass smoke injection into the 

lower stratosphere by a large forest fire (Part II): 

sensitivity studies. Atmospheric Chemistry and 

Physics. 6: 5261-5277.

Mobley, H E. 1989. Summary of smoke-related 

accidents in the South from prescribed fire (1979-
106 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

1988). American Pulpwood Association Technical 

Release. 90-R-11.

Oberhuber, J.M.; Herzog, M.; Graf, H.-F.; Schwanke, 

K. 1998. Volcanic plume simulation on large scales.

Journal of Volcanology and Geothermal Research. 87: 

29-53.

O’Neill, S.M.; Ferguson, S.A.; Peterson, J.; Wilson, R. 

2003. The BlueSky Smoke Modeling Framework.

Proceedings, 5th symposium on fire and forest 

meteorology; 2003 November; Orlando, FL. Boston, 

MA: American Meteorological Society.

Pharo, J.A.; Lavdas, L.G.; Bailey, P.M. 1976. Smoke 

transport and dispersion. In: Mobley, Hugh E., 

comp. Southern forestry and smoke management 

guidebook. Gen. Tech. Rep. SE-10. Asheville, NC: 

U.S. Department of Agriculture, Forest Service, 

Southeastern Research Station: 45-55.

Potter B. 2005. The role of released moisture in the 

atmospheric dynamics associated with wildland 

fires. International Journal of Wildland Fire. 14: 77-

84.

Reiquam, H. 1970. An atmospheric transport and 

accumulation model for airsheds. Atmospheric 

Environment. 4: 233-247.

Riebau, A.R.; Fox, D. 2001. The new smoke 

management. International Journal of Wildland Fire. 

10: 415-427.

Riebau, A.; Larkin, N.; Pace, T.; Lahm, P.; Haddow, 

D.; Spells, C. 2006. BlueSkyRAINS West (BSRW) 

Demonstration Project, Final Report. www.airfire.

org/pubs/BlueSkyRAINS_West_November_2006.pdf.

Rolph, G.D. 2003. Real-time Environmental 

Applications and Display sYstem (READY). NOAA 

Air Resources Laboratory. www.arl.noaa.gov/ready/

hysplit4.html).

Sandberg, D.V.; Hardy, C.C.; Ottmar, R.D. Snell, 

J.A.K.; Acheson, A; Peterson, J.L.; Seamon, P.; Lahm, 

P.; Wade, D., eds. 1999 National strategy plan: 

modeling and data systems for wildland fire and air 

quality. Gen. Tech. Rep. PNW-GTR-450. Portland, 

OR: U.S. Department of Agriculture, Forest Service, 

Pacific Northwest Research Station. 60 p.

Scire, J.S. 2000. CALPUFF: overview of capabilities.

Technical highlights of EPA’s 7th conference on air 

pollution modeling; 2000 August 1; Raleigh, NC. 

Research Triangle Park, NC: U.S. Environmental 

Protection Agency. 95 p.

Sestak, M.L.; Riebau, A.R. 1988. SASEM, Simple 

approach smoke estimation model. Technical Note 

382. Denver, CO: U.S. Department of Interior, 

Bureau of Land Management. 31 p.

Trentmann, J.; Andreae, M.O.; Graf, H.-F.; Hobbs, 

P.V.; Ottmar, R.D.; Trautmann, T. 2002. Simulation 

of a biomass-burning plume: comparison of model 

results with observations. Journal of Geophysical 

Research. 107(D2): 5-1 – 5-15.

Trentmann, J.; Luderer, G.; Winterrath, T.; Fromm, 

M.D.; Servranckx, R.; Textor, C.; Herzog, M.; Graf, 

G.-F.; Andreae, M.O. 2006. Modeling of biomass 

smoke injection into the lower stratosphere by 

a large forest fire (part I): reference simulation.

Atmospheric Chemistry and Physics. 6: 5247-5260.

Turner, D.B. 1970. Workbook of atmospheric 

dispersion estimates. Publ. No. AP-26. Research 

Triangle Park, NC: U.S. Environmental Protection 

Agency, Office of Air Programs. 84 p.

Wade, D.D.; Brock, B.L.; Brose, P.H.; Grace, J.B.; 

Hoch, G.A.; Patterson, W.A. III. 2000. Fire in 

eastern ecosystems. In: Brown, J.K.; Smith, J.K., 

eds. Wildland fire in ecosystems: effects of fire on 

flora. Gen. Tech. Rep. RMRS-42. U.S.Department of 

Agriculture, Forest Service, Rocky Mountain Research 

Station: 53-96.

Ward, D.E; Hardy; C.C. 1991. Smoke emissions from 

wildland fires. Environment International. 17: 117-

134.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 107

MODELING FIRE AND OTHER DISTURBANCE PROCESSES USING LANDIS

Stephen R. Shifley1, Jian Yang2, and Hong He3

1

Research Forester, U.S. Forest Service, Columbia, MO 2

Post-doctoral Research Associate, University of Nevada-Reno, Reno, NV 3

Associate Professor, University of Missouri, Columbia, MO

SRS is corresponding author; to contact, call (573) 875-5341 or email at sshifley@fs.fed.us

Abstract.—LANDIS is a landscape decision support tool that models spatial relationships to help managers 

and planners examine the large-scale, long-term, cumulative effects of succession, harvesting, wildfire, 

prescribed fire, insects, and disease. It can operate on forest landscapes from a few thousand to a few million 

acres in extent. Fire modeling capabilities in LANDIS are detailed, but intuitive. Modeled fires kill trees 

based on the fire intensity and each tree species’ fire tolerance, and spatially explicit ignition probability 

maps can be incorporated but are not required. As the LANDIS model runs through many annual or 10-

year iterations, it illustrates how and where forest vegetation is expected to change in response to succession, 

fire, harvesting, and other disturbances. LANDIS output can be mapped, summarized, and linked to other 

attributes of interest, such as wildlife habitat suitability. Although it is possible to run the LANDIS model 

using generic or default values, the real benefits come when the model is calibrated to reflect the unique 

conditions associated with a specific forest ecosystem. Applications of LANDIS include analyses of fire 

regimes, separately or in combination with harvesting, on the Mark Twain National Forest (Missouri), the 

Hoosier National Forest (Indiana), and the Chequamegon-Nicolet National Forest (Wisconsin). These 

analyses can guide the selection of long-term management alternatives for forested landscapes. LANDIS has 

also proven useful in more theoretical investigations that compare long-term effects of alternative fire regimes 

on the expected direction and rate of tree species composition change across an array of ecological land types.

INTRODUCTION

Comprehensive forest management requires 

consideration of the long-term, large-scale, cumulative 

effects of management activities and natural disturbances 

on forest commodities, amenities, and services, which 

include forest products (type and quantity over time), 

wildlife habitat (quality by species over time), water 

quality (usually addressed through implementation of 

best management practices), and biodiversity (diversity 

of plant and animal species, diversity of forest age and 

size structure, and diversity of habitats over time). 

Recently, increasing emphasis also has been placed on 

managing forests for ecological services such as carbon 

sequestration.

Foresters are skilled at forecasting the effects of 

management on products, forest size structure, and tree 

species composition at the stand scale. But keeping track 

of those details for thousands or hundreds of thousands 

of acres requires a landscape decision support system, 

which is usually in the form of a landscape computer 

simulation model. There are many forest landscape 

models available. They vary in the details of how they 

operate, but they all provide a means to forecast and 

display expected changes in forest conditions across 

landscapes in response to management and natural 

disturbances caused by wildfire, wind, insects, and 

disease. Forest landscape models are especially useful for 

forecasting expected impacts of wildfires, which, unlike 

harvests, are not constrained by stand boundaries, and 

from year to year vary considerably in location, extent, 

and severity. Modeling fire effects using a landscape 

decision support system provides a mechanism to 

examine average tendencies, expected variation over time, 

and potential impacts of fire mitigation strategies.

Examples of forest landscape models include the Forest 

Vegetation Simulator (Dixon 2003, USDA Forest 

Service 2008), HARVEST (Gustafson and Rasmussen 

2005), the Landscape Management System (University 

of Washington 2008), LANDSUM (Keane et al. 1997, 

2002), SIMPPLLE (Chew et al. 2007), and VDDT/
108 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

TELSA (Beukema and Kurz 1998). They all differ in the 

details of how they operate and in their relative strengths 

and weaknesses (Barrett 2001, Keane et al. 2004). Our 

experience has been with the LANDIS forest landscape 

model (He and Mladenoff 1999, He et al. 2005), 

which has been in use for about 15 years with ongoing 

development and applications in the United States, 

Canada, and Europe.

The following sections draw from previous applications 

of LANDIS to Midwestern forest landscapes to illustrate 

how LANDIS can be used to model fire effects as part 

of a comprehensive analysis system that also includes 

the effects of alternative silvicultural practices on forest 

growth, species succession, and wildlife habitat.

THE LANDIS MODEL

LANDIS Design

LANDIS represents a forest landscape as a mosaic of 

square sites (He et al. 2005) (Fig. 1). In the jargon of 

geographic information systems, the sites can be referred 

to as rasters or pixels. Although the site size can be set 

by the model user, we typically use sites that are about 

a quarter-acre (30 m on each side) or about 0.025 acre 

(10 m on each side). A 0.025-acre site corresponds to 

roughly the canopy size of a mature hardwood tree, so 

it is possible to create highly detailed representations of 

forest landscapes composed of millions of adjacent sites. 

LANDIS projections are made on a 1-year or a 10-year 

time step (iteration), and LANDIS will produce maps 

and summary statistics of forest conditions at each time 

step of a projection that may cover a few decades or a few 

centuries.

At each site, LANDIS tracks which tree species are 

present by age class. In the Midwest we used up to 

18 species groups to describe vegetation in LANDIS. 

Sites are grouped into contiguous stands that can have 

complex age structure and species composition. Stands 

are grouped into management areas that need not be 

contiguous, similar to National Forest management areas 

used in forest planning.

When forecasting forest change, LANDIS modifies trees 

on each site according to a set of succession rules and 

equations. For example, in the absence of disturbance, 

the trees grow older. When trees become older, they have 

an increasing probability of mortality. Shade-tolerant tree 

species can regenerate on sites with older trees, according 

to a set of probabilities. When trees die, they are replaced 

according to a set of regeneration probabilities that differ 

Figure 1.—Schematic of LANDIS design. This diagram illustrates the map and data 

layers used for LANDIS input, processing, and output. Succession and the other 

disturbance processes shown alter the vegetation map layer for each time period of 

a modeled scenario. Additional detail is available from He et al. ( 2005).
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 109

by ecological land type. Rules and probabilities can be 

modified to accommodate conditions for a wide array of 

ecosystems.

Simulated disturbances alter patterns of forest 

development within LANDIS. Simulated harvests can 

be applied to individual stands and entire management 

areas. Users control the type, frequency, and location of 

harvests based on rules that can account for stand age 

(e.g., oldest first), location (e.g., do not harvest adjacent 

stands), desired rotation length, desired species, and 

desired tree age or size. Windthrow is modeled according 

to probabilities indicating the likelihood of damaging 

wind events of various sizes. Usually, many small wind 

events and a few large ones result (Rebertus and Meier 

2001), but users can modify this pattern. The location 

of wind events on the landscape is random, and there is 

greater probability of windthrow for large trees than for 

small trees.

Modeling Fire in LANDIS

Fire modeling in LANDIS consists of three 

subcomponents: fire occurrence, fire spread, and fire 

effect. Fire occurrences on the landscape are modeled as 

a two-stage process (ignition and initiation) in LANDIS 

(He et al. 2005, Yang et al. 2007). In the first stage, fires 

are ignited based on a fire ignition probability map layer. 

Whether an ignition can become a successful fire or not 

is determined by fire initiation probability in the second 

stage. The fire ignition probability map layer can be very 

simple (e.g., every location has the same probability of 

fire ignition), or very complex. Recent analysis of 32 

years of fire records for part of the Mark Twain National 

Forest (Missouri) produced a detailed map showing the 

probability of fire ignition for each location (Fig. 2). 

People cause about 98 percent of fires in that region, 

with 75 percent of fires due to arson. The analysis of 

spatial patterns showed the greatest probability of fire 

Figure 2.—Estimated probability of fire ignition 

based on 32 years of fire records in southern 

Missouri. (See also Yang et al. 2007.)
110 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

ignition is along roads through lands owned by the Mark 

Twain National Forest and near local communities (Yang 

et al. 2007). Similar methods can be applied to other 

regions with long fire records. Alternatively, fire ignition 

probabilities for other ecosystems could be estimated by 

experienced observers using simple relationships based 

on distance from roads, ecological land type, elevation, 

or any other factor believed to be associated with local 

ignition patterns.

The quality and accessibility of historical fire ignition 

data is improving to the point where developing 

ignition probability maps for large areas is possible. 

Once developed, such maps are useful for many years 

and for purposes beyond the application of LANDIS 

(e.g., for distribution of fire suppression resources or 

communication with the public).

After an initiation is simulated, the simulated fire 

spreads across the modeled landscape based on fuel 

load, topography, and prevailing wind direction. Rates 

of fire spread across a site and into an adjacent site are 

computed using the relationships described in FARSITE 

(Finney 1998) and BEHAVE fire models (Anderson 

1982, Andrews et al. 2005). By computing and storing 

the rate of fire spread for all combinations of fuel class, 

slope class, and wind speed for a given landscape, 

LANDIS can efficiently model detailed patterns of fire 

spread. Fires modeled in LANDIS spread until they reach 

a specified area or a specified time to suppression, either 

of which can be based on local experience when such 

information is available.

Tree mortality following a fire is modeled according 

to a set of rules that the LANDIS user can modify. 

Fire intensity for each burned site is classified into 

five categories based on the fuel load at the time of 

the fire. Each tree species and age class combination is 

categorized by fire tolerance. The youngest trees are the 

most susceptible to fire-caused mortality, so for a given 

fire intensity the tree species with lower fire tolerance 

will have older trees killed than will species with higher 

fire tolerance. Following a modeled fire, the fuel load is 

adjusted to a lower value that can be set to match local 

observations.

When the above procedures are used to model wildfires, 

the timing and location of the modeled fire events are 

based on random draws from probability distributions. 

Consequently, for any two separate simulation runs, the 

timing and location of the modeled wildfire events will 

differ. However, the total area affected by wildfire for 

the entire landscape will be similar for both runs. This 

element of randomness does not work well for modeling 

prescribed fires, where the fire location, frequency, 

and intensity are specified as part of a silvicultural 

prescription. However, prescribed fires for specific stands 

and years can be simulated using the flexible set of 

silvicultural treatments available in LANDIS fuel module 

(Gustafson et al. 2000, He et al. 2005).

LANDIS APPLICATIONS

In the Midwest, we have applied LANDIS to investigate 

the outcomes of alternative management scenarios for 

parts of the Mark Twain National Forest, for the entire 

180,000-acre Hoosier National Forest in Indiana, and 

for two Ranger Districts of the Chequamegon-Nicolet 

National Forest in northern Wisconsin (Shifley et al. 

2006, 2008; USDA Forest Service 2006; Rittenhouse 

2008; Zollner et al. 2008). National Forests, like many 

public forest ownerships, often have digital maps, forest 

inventories, wildfire records, and ecological classification 

systems prepared for large areas. Those are valuable assets 

when initializing a forest landscape for use in LANDIS. 

Moreover, managers of public forests have a mandate 

to consider the cumulative effects of their management 

practices on the multiple commodities, amenities, and 

services their forests can provide.

Changes in species composition related to alternative 

fire regimes applied at the landscape scale can be 

examined over time (Fig. 3). As expected, increased 

fire on the landscape pushes the anticipated species 

composition toward fire-adapted species. While that 

general result is not surprising, analysis of fire effects 

using LANDIS provides additional insights about rates 

of change in species composition and age structure over 

time, the effects of different ecological land types (e.g., 

slope, aspect, hydrology) on those changes, the spatial 

distribution of changes, and cumulative effects over space 

and time.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 111

Results can be evaluated for specific landscapes, but 

analyses based on hypothetical landscape conditions 

can also provide important results to guide managers. 

For example, Lafon et al. (2007) created a hypothetical 

landscape with two elevation classes and three ecological 

land types representative of conditions found in the 

southern Appalachian Mountains. They then used 

LANDIS to apply two fire regimes and systematically 

explore the differential effects of each combination on 

changes in tree species composition over time. They 

found that when suitably calibrated, the LANDIS 

predictions were consistent with ecological theory. They 

provided evidence that (1) reintroduction of fire can 

reverse undesirable shifts in biodiversity; (2) species 

responses will differ by land type and elevation; 

(3) there can be interactions involving multiple factors; 

and (4) changes in species composition will occur 

gradually over one to two centuries. These results are 

useful to develop site-specific management plans with 

reasonable expectations about the likely rate of species 

change during restoration efforts. Other applications on 

real landscapes have systematically analyzed the sensitivity 

of LANDIS predictions to differences in fire regimes 

and to simplifying assumptions about seed dispersal 

and species establishment rates. Results for the Georgia 

Piedmont have shown that assumptions about seed 

dispersal and the effect of topographic differences on fire 

regimes have a relatively large effect on LANDIS forecasts 

(Wimberly 2004).

To investigate the long-term effects of fire suppression on 

central hardwood forests in the Missouri Ozarks, Shang 

et al. (2007) examined two management scenarios: (1) a 

fire suppression scenario circa 1990; and (2) a historical 

fire regime scenario prior to fire suppression, with a 

mean fire-return interval of 14 years. They found that 

both fuel and fire hazard increased to a medium-high 

level after a few decades of fire suppression. A century of 

fire suppression could result in more than three-quarters 

of the fires having medium- to high intensity levels, 

uncharacteristic for those Central Hardwood ecosystems. 

Fire suppression could also lead to distinct changes 

in species abundance; the pine and oak-pine forests 

common in the study area prior to fire suppression would 

be replaced by mixed-oak forests.

Forest planning is an important activity in which forest 

landscape models can provide valuable assistance. Using 

LANDIS, Zollner et al. (2008) demonstrated a way to 

evaluate alternative management plans and assess whether 

they are likely to meet the stated, multiple objectives. 

They predicted forest composition and landscape pattern 

under seven alternative forest management plans drafted 

for the Chequamegon-Nicolet National Forest. In most 

cases, the modeled results showed that multiple objectives 

were obtainable without conflict, but in 20 percent of the 

cases, land managers needed to prioritize among eight 

timber and wildlife management objectives. Some desired 

outcomes were obtainable only by mutually exclusive 

management activities.

Figure 3.—LANDIS projection of the proportion of sites 

dominated by major species groups for two management 

alternatives applied to the 200,000-acre Hoosier National 

Forest in southern Indiana. (A) Managed with no prescribed 

burning and no harvest. (B) Managed with a total of 360,000 

acres of prescribed burning and 52,000 acres of harvest 

over the 150-year projection period. (See also USDA Forest 

Service 2006.)
112 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

The predicted outcome of alternative management 

scenarios projected using LANDIS can be displayed 

graphically as well as in tabular summaries (Figs. 3 and 

4). One of the most powerful attributes of LANDIS 

is the ability to simultaneously incorporate multiple, 

spatially explicit disturbance factors (fire, wind, harvest, 

insects, disease) and evaluate the combined effects on 

multiple forest attributes. Figure 4 shows a small subset 

of the information that can be mapped for each decade 

of a scenario. The even-aged management scenario 

illustrates the effects of regenerating 10 percent of the 

forest area per decade via clearcutting. The uneven-aged 

management scenario illustrates the impact of group 

selection harvesting that regenerates about 10 percent 

of the forest area per decade. The mixed management 

scenario blends those two practices to regenerate about 

10 percent of the forest area per decade. In each of 

those scenarios the spatial distribution of vegetation age 

is heavily influenced by the patterns of harvest on the 

landscape. All scenarios included wildfires occurring with 

a mean fire-free interval of approximately 300 years, a 

value that is based on wildfire observations over the prior 

30 years. The effects of wildfire are apparent in the noharvest management scenario, where modeled fire events 

create the largest patches of young forest on the projected 

future forest landscape.

In addition to the forest characteristics illustrated in 

Figure 4, we can use LANDIS output to estimate, 

tabulate, and map habitat suitability for other wildlife 

species, tree species composition, harvest area, harvest 

volume, standing volume, snags, and coarse woody 

debris. Scenarios that have been modeled for the 

Hoosier National Forest mimic the forest management 

alternatives proposed as part of the formal forestplanning process. Forecasts of the cumulative effects of 

Figure 4.—Illustration of the LANDIS results 

for four management alternatives. Darker 

shades indicate older tree age classes 

and greater wildlife habitat suitability. 

Harvest practices, wind disturbance, and 

fire regimes affect tree species composition 

and tree age class, which in turn affect 

estimated wildlife habitat suitability. 

Similar maps or tabular summaries can 

be generated for each decade of each 

modeled scenario (from Shifley et al. 2008).
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 113

forest management (including prescribed fire, wildfire, 

and timber harvest) were factored into the selection of a 

preferred management alternative (USDA Forest Service 

2006).

DISCUSSION AND CONCLUSIONS

LANDIS provides an extremely versatile approach for 

modeling the long-term, large-scale cumulative effects 

of forest management, disturbance, and succession on 

forest landscapes. Modeled landscapes can range from 

a few thousand to a few million acres in extent, and 

the approach has been used to support National Forest 

Planning (USDA Forest Service 2006, Rittenhouse 2008, 

Zollner et al. 2008).

The procedures for simulating fire ignition and spread 

and modeling fire effects on fuel and vegetation have 

been greatly expanded in the most recent revision 

of LANDIS (version 4.0, Yang et al. 2004, He et al. 

2005). Fire spread algorithms are consistent with 

established fire behavior models (Anderson 1982, Finney 

1998, Andrews et al. 2005) and can be adapted to 

accommodate a wide range of fire regimes and detailed 

fire effects. The only drawback of having such versatility 

is the need to actually specify fire ignition probabilities, 

fuel loads, fire spread rates, fuel treatment effects, and 

fire effects on vegetation. The LANDIS fire routines 

can be readily operated using default or generic values 

for these factors, but that approach fails to take full 

advantage of the fire modeling capabilities. For most 

landscapes, our ability to model detailed fire ignition, 

spread, and responses with LANDIS exceeds our ability 

to locally calibrate the model with site-specific data 

on fire occurrence and fire effects. To date, modeling 

fire effects with LANDIS has been hindered primarily 

due to lack of detailed information on (1) the spatial 

distribution of current fuels; (2) fire effects by fire 

intensity class on tree mortality and regeneration; and 

(3) effects of fire and other treatments on residual fuels. 

Other presentations and posters from the Third Fire in 

Eastern Oak Forests Conference (see the remainder of 

this proceedings) provides reassurance that such data are 

being accumulated and will become available to calibrate 

the LANDIS fire models for specific ecosystems.

Modeling fire effects is one reason to apply LANDIS, 

but LANDIS also is a framework for synthesizing 

many forest succession and disturbance processes that 

also include wind, silviculture, regeneration, and land 

use change (e.g., Syphard et al. 2007). Results for 

alternative scenarios can be summarized, illustrated, and/

or mapped through time to show differences in forest 

vegetation structure and composition, wood volume, 

down wood, forest fragmentation, species diversity, and 

wildlife habitat suitability (e.g., Dijak and Rittenhouse 

2008). The ability to analyze landscape-scale forest 

change provides opportunities for foresters, wildlife 

biologists, ecologists, and planners to collaborate and 

examine interactions or tradeoffs of various management 

alternatives on a large forest landscape.

In our experience it can take many months to initialize 

and calibrate LANDIS for a new, large landscape. 

By comparison, running various alternatives through 

LANDIS requires a relatively short time (a few hours or 

a few days), and summarizing results may take a few days 

to a few months depending on the complexity of the 

attributes of interest. For example, summarizing wildlife 

habitat quality for multiple species is notoriously timeconsuming, but some summaries of forest vegetation 

require only a few minutes to summarize and map. 

Although substantial effort can be required to calibrate 

LANDIS for a large landscape, we have discovered large 

benefits from that up-front investment. Each time we 

have initialized a large landscape for use with LANDIS, 

we have attracted new partners with new questions that 

we can explore collaboratively on those same landscapes.

Application of LANDIS is best pursued through a team 

approach that incorporates competencies in a variety 

of specialties such as geographic information systems, 

data processing, programming, forest management/

silviculture, ecology, wildlife biology, fire behavior and 

management, timber and markets, and planning. That 

collaboration makes the process efficient by drawing on 

a diverse array of technical specialists. It also facilitates 

communication across disciplines, and it helps ensure 

that results are practical and relevant for multiple 

purposes.
114 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

ACKNOWLEDGMENTS

Martin Spetich and an anonymous reviewer provided 

comments and suggestions that helped us improve an 

earlier version of this manuscript. William Dijak, Frank 

Thompson, Joseph Fan, Chadwick Rittenhouse, Michael 

Larson, and Josh Millspaugh helped develop material 

used in some of the examples used in the paper. We 

thank them all.

LITERATURE CITED

Anderson, H.E. 1982. Aids to determining fuel models 

for estimating fire behavior. Gen. Tech. Rep. INT122. Ogden, UT: U.S. Department of Agriculture, 

Forest Service, Intermountain Forest and Range 

Experiment Station. 22 p.

Andrews, P.L.; Bevins, C.D.; Seli. R.C. 2005. 

BehavePlus fire modeling system, version 3.0. 

User’s Guide. Gen. Tech. Rep. RMRS-GTR106WWW Revised. Ogden, UT: U.S. Department of 

Agriculture, Forest Service, Rocky Mountain Research 

Station. 132 p.

Barrett, T.M. 2001. Models of vegetation change 

for landscape planning: a comparison of FETM, 

LANDSUM, SIMPPLLE, and VDDT. Gen. Tech. 

Rep. RMRS-GTR-76-WWW. Ogden, UT: U.S. 

Department of Agriculture, Forest Service, Rocky 

Mountain Forest and Range Experiment Station. 14 

p. 

Beukema, S.J.; Kurz, W.A. 1998. Vegetation dynamics 

development tool: user’s guide (v. 3.0). Available 

from: ESSA Technologies Ltd., #300-1765 West 8th 

Avenue, Vancouver, BC V6J 5C6. 104 p.

Chew J.D.; Stalling, C.; Moeller K.; Bella, E.; Schreiner, 

R.; Ahl, R.; Jones, T. 2007. User guide for 

SIMPPLLE, Version 2.5 (Draft). U.S. Department 

of Agriculture, Forest Service. 338 p.

Dijak, W.D.; Rittenhouse. C.D. 2008. Development 

and application of habitat suitability models to 

large landscapes. In: Millspaugh, J.J.; Thompson, 

F.R.III, eds. Models for planning wildlife conservation 

in large landscapes. San Diego, CA: Elsevier Science: 

367-389.

Dixon, G.E., comp. 2003. Essential FVS: a user’s guide 

to the forest vegetation simulator. Internal report, 

Fort Collins, CO: U.S. Department of Agriculture, 

Forest Service, Forest Management Service Center. 

219 p.

Finney, M.A. 1998. FARSITE: Fire area simulatormodel development and evaluation. Res. Pap. RMRS4. Missoula, MT: U.S. Department of Agriculture, 

Forest Service, Rocky Mountain Research Station. 47 p.

Gustafson, E.J.; Rasmussen, L.V. 2005. HARVEST for 

Windows v6.1: user’s guide. St. Paul, MN: U.S. 

Department of Agriculture Forest Service, North 

Central Research Station.

Gustafson, E.J.; Shifley, S.R.; Mladenoff, D.J.; Nimerfro, 

K.K.; He, H.S. 2000. Spatial simulation of forest 

succession and timber harvesting using LANDIS.

Canadian Journal of Forest Research. 30: 32-43.

He, H.S.; Mladenoff, D.J. 1999. Dynamics of fire 

disturbance and succession on a heterogeneous 

forest landscape: a spatially explicit and stochastic 

simulation approach. Ecology. 80: 81-99.

He, H.S.; Li, W.; Sturtevant, B.R.; Yang, J.; Shang, B.Z.; 

Gustafson, E.J.; Mladenoff , D.J. 2005. LANDIS, 

a spatially explicit model of forest landscape 

disturbance, management, and succession—

LANDIS 4.0 User’s guide. Gen. Tech. Rep. NC-263. 

St. Paul, MN: U.S. Department of Agriculture, Forest 

Service. 93 p.

Keane, R.E.; Cary, G.J.; Davies, I.D.; Flannigan M.D.; 

Gardner, R.H.; Lavorel, S.; Lenihan, J.M.; LI, C.; 

Rupp, T.S. 2004. A classification of landscape fire 

succession models: spatial simulations of fire and 

vegetation dynamics. Ecological Modelling. 17: 3-27.

Keane, R.E.; Long, D.; Basford, D.; Levesque, B.A. 

1997. Simulating vegetation dynamics across 

multiple scales to assess alternative management 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 115

strategies. In: Conference proceedings—GIS 97, 

11th annual symposium on geographic information 

systems—integrating spatial information technologies 

for tomorrow. Vancouver, BC: GIS World, Inc.: 310-

315.

Keane, R.E.; Parsons, R.; Hessburg, P. 2002. Estimating 

historical range and variation of landscape patch 

dynamics: limitations of the simulation approach.

Ecological Modeling. 151: 29-49.

Lafon, C.W.; Waldron, J.D.; Cairns, D.M.; Tchakerian, 

M.D.; Coulson, R.N.; Klepzig, K.D. 2007. Modeling 

the effects of fire on the long-term dynamics and 

restoration of yellow pine and oak forests in the 

southern Appalachian Mountains. Restoration 

Ecology. 15(3): 400-411.

Rebertus, A.J.; Meier, A.J. 2001. Blowdown dynamics 

of oak-hickory forests of the Missouri Ozarks.

Journal of the Torrey Botanical Society. 128: 362-

369.

Rittenhouse, C.D. 2008. Wildlife response to spatial 

and temporal changes in forest habitat. Columbia, 

MO: University of Missouri. Ph.D. dissertation.

Shang Z.B.; He, H.S.; Lytle, D.E.; Shifley, R.S; Crow, 

T.C. 2007. Long-term effects of fire suppression 

on Central Hardwood Forests in Missouri Ozarks, 

USA. Forest Ecology and Management. 242: 776-790.

Shifley, S.R.; Thompson, F.R. III; Dijak, W.D.; Fan, 

Z. 2008. Forecasting landscape-scale, cumulative 

effects of forest management on vegetation and 

wildlife habitat: a case study of issues, limitations, 

and opportunities. Forest Ecology and Management. 

254: 474-483.

Shifley, S.R.; Thompson, F.R. III; Dijak, W.D.; Larson, 

M.A.; Millspaugh, J.J. 2006. Simulated effects 

of forest management alternatives on landscape 

structure and habitat suitability in the Midwestern 

United States. Forest Ecology and Management. 229: 

361-377.

Syphard, A.D.; Clarke, K.C.; Franklin, J. 2007. 

Coupling two landscape models to simulate 

frequent fire and urban growth on southern 

California coastal shrublands. Landscape Ecology. 

22: 431-445.

USDA Forest Service. 2008. Forest Vegetation 

Simulator (FVS). Available: www.fs.fed.us/fmsc/fvs/

index.shtml (accessed May 14, 2008).

USDA Forest Service. 2006. Land and resource 

management plan: Hoosier National Forest.

Milwaukee, WI: U.S. Department of Agriculture, 

Forest Service Eastern Region.

University of Washington. 2008. Landscape 

management system. Available: http://lms.cfr.

washington.edu/index.php. (accessed Jan. 12, 2008).

Wimberly , M.C. 2004. Fire and forest landscapes 

in the Georgia Piedmont: an assessment of 

spatial modeling assumptions. Forest Ecology and 

Management. 180: 41-56.

Yang, J.; He, H.S.; Gustafson, E.J. 2004. A hierarchical 

fire frequency model to simulate temporal patterns 

of fire regimes in LANDIS. Ecological Modelling. 

180: 119-133.

Yang, J.; He, H.S.; Shifley, S.R.; Gustafson, E.J. 2007. 

Spatial patterns of modern period human-caused 

fire occurrence in the Missouri Ozark Highlands.

Forest Science. 53: 1-15.

Zollner, P.A.; Roberts, L.J.; Gustafson, E.J.; He, H.S.; 

Radeloff, V.C.; Mladenoff, D.J. 2008. Influence 

of forest management planning alternatives on 

landscape pattern and forest succession in northern 

Wisconsin. Forest Ecology and Management. 254: 

429-444.
116 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 117

fire and 

forest management
118 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

BUILDING A STATE PRESCRIBED FIRE PROGRAM: 

EXPERIENCES AND LESSONS LEARNED IN OHIO

Michael Bowden1

1

Fire Supervisor, Ohio Department of Natural Resources, Division of Forestry, Columbus, OH

To contact, call (614) 265-1088 or email at michael.bowden@dnr.state.oh.us

Abstract.—Science continues to show the need for the use of prescribed fire in oak-dominated forests 

of the eastern United States. Fire is necessary to reduce competition by thin-barked species, allowing 

for the development of oak advance regeneration. Many agencies are beginning to apply this science 

by using prescribed fire to manage their oak forests. This paper examines the development of the Ohio 

Division of Forestry’s prescribed fire management program. It outlines the experiences of the Division 

as it increased use of fire and began burning at the landscape level. Problems, challenges, and lessons 

learned during the growth of Ohio’s prescribed fire program are addressed as well. Although this 

paper does not provide all of the answers for how to develop a prescribed fire program, it does use the 

experiences the Ohio Division of Forestry faced over the past 10 years to provide some idea of what expect.

FIRE AND OHIO’S STATE FORESTS

Ohio’s forests, like many in the eastern United States, 

are made up various species of deciduous trees; oaks 

are the most abundant, especially in the southern and 

eastern portions of the state (Griffith et al. 1993). At 

time of settlement (ca. 1800) the state was estimated 

to be more than 95 percent forested. Settlement and 

western expansion during the 19th century resulted in a 

deforestation that lasted nearly 100 years. During the first 

decade of the 20th century only 10 percent of Ohio was 

forested. This rapid and significant deforestation spurred 

the state government to create a State forest agency in 

1885.

One of the primary missions assigned to the newly 

created Division of Forestry was to address the 

deforestation and prevent a “timber famine.” The 

Division worked on ways to increase forest lands in the 

State. In 1912 the state legislature amended the Ohio 

Constitution to allow for the creation of a forest reserve 

system. Shortly thereafter, the State began to purchase 

lands which became the first State forests. The lands the 

Division acquired had been heavily cut over, burned, 

grazed, and farmed during the late 1800s and early 

1900s. These newly obtained lands were then protected 

from fire and grazing, which resulted in rapid regrowth 

to mostly oak-dominated stands.

Wildland fires continued to burn occasionally through 

these forests, but by the mid-1930s the Division’s fire 

control efforts had dramatically decreased the acreage of 

forest land burned annually (Leete 1938). The decrease 

in wildfires allowed fire-intolerant species such as red 

maple and yellow poplar to move out of their traditional 

locations in the coves and bottomlands and begin to 

establish in the uplands (Hutchinson et al. 2008). Prior 

to the development of an effective fire suppression 

program, these species would be killed during wildfire 

events that occurred, on average, once every 3-10 years 

(McEwan et al. 2007). Without fire burning through 

these stands during the past 70 years, red maple and 

yellow poplar have developed into saplings and polesized stems, creating dense, shaded conditions in the 

understory, which prevents the development of oak 

advance regeneration (Dey and Fan, this volume).

In addition to maintaining forest reserves, or State 

Forests, the Division has a mandate to “take such 

measures as are necessary to bring about a profitable 

growth of timber.” The Division utilizes many 

“measures” to address this charge, including harvesting 

and timber stand improvement practices. The 

high density of red maple and lack of oak advance 

regeneration (large seedlings and saplings) has created 

problems for foresters trying to regenerate oak and 

sustain its dominance in our State forests. Without 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 119

advance oak regeneration present, harvests or significant 

disturbances (e.g., tornadoes, ice storms, or insect 

outbreaks) result in stands that regenerate with an oak 

component greatly reduced from the previous stand.

Studies throughout the eastern United States have 

brought to light the changes that are occurring in oakdominated forests due to the lack of fire; this research 

stresses the important role that fire plays in maintaining 

the oak component in these ecosystems (Abrams 1992, 

Brose and Van Lear 1998, Dey and Fan, this volume). 

The Ohio Division of Forestry has been involved with 

this research through its partnership with the U.S. 

Forest Service, Northern Research Station. 

Northern Research Station scientists based 

in Delaware, OH, have led the efforts 

to study the interaction of fire and fire 

surrogates (i.e., thinning and harvesting) on 

the oak-dominated forests in Ohio (Yaussy 

and Waldrop, this volume). Two of the 

three replications of this long-term national 

study are located on Ohio State Forests, 

Tar Hollow in Ross County and Zaleski in 

Vinton County (Fig. 1).

The rapid increase in number of scientific 

publications suggesting the need for fire to 

sustain oak-dominated ecosystems was a catalyst for 

the Division of Forestry to expand its use of prescribed 

fire during the late 1990s and early 21st century, from 

small sites to larger landscape applications (Fig. 2). This 

increase in the use of prescribed fire has pointed out 

issues that fire managers need to be ready to address 

when building or increasing a prescribed fire program.

The Division of Forestry had been involved with fire 

suppression for more than 70 years and had been 

using prescribed fire for nearly 20 years prior to its 

expansion to the landscape level. Differences between 

the Division’s traditional practice of fire suppression 

and the larger-scale application of prescribed fire quickly 

became apparent. The goal of this paper is to share 

the experiences of the Division of Forestry during the 

expansion of its prescribed fire program.

GROWING A PRESCRIBED

FIRE PROGRAM

Preliminary Considerations

When beginning to grow a prescribed fire program, 

the natural resource manager should consider several 

things before taking action. You should identify the 

goals of using prescribed fire. Burning for ecosystem 

process restoration is different from burning to reduce 

hazardous fuels and will require different tools, training, 

and application. In addition, you need to consider how 

much land you envision treating annually and compare 

Figure 1.—Ohio Division of Forestry crew conducting a burn 

in 2005 on the Fire and Fire Surrogates Study.

Figure 2.—Prescribed fire application by the Ohio Division of Forestry, 

1994 - 2008.
120 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

that amount with your current levels of treatment. 

You should identify the situations, such as weather 

conditions, season of burning, and fuel moistures, in 

which you can treat the landscape with prescribed fire. 

What barriers may impact your implementation of 

prescribed burning? Can these barriers be mitigated or 

overcome? Finally, do you have opportunities to establish 

partnerships with other agencies or organizations 

to increase capacity to burn more acreage? Serious 

consideration of these issues can reduce “growing pains” 

and speed the growth of the program.

During the growth of our prescribed fire program, we 

have realized the importance of making sure that all 

involved, from leadership to firefighters, understand its 

goals. A lack of understanding results in application of 

fire that does not meet the objectives. Additionally, a 

workforce with a long history of fire suppression may not 

understand the goals of prescribed burning, will not fully 

embrace the management technique, and will be less 

willing to implement it.

As a program is being expanded, I recommend starting 

small and gradually increasing capacity. This stepwise 

implementation allows workers to increase their skills 

gradually, gives all participants an opportunity to identify 

practices that are efficient and effective, and prevents 

workers from landing in situations they are not prepared 

for or able to deal with. This approach will result in a 

more effective prescribed fire program in the long run, 

as recovery from a “misstep” when growing too fast is a 

difficult process.

Public Perception and Education

Public perception of prescribed fire will be an issue 

when your organization is developing and growing a 

prescribed fire program. It is critical to recognize the 

public’s role and to be proactive in sharing information 

about the program. Educational materials such as 

Websites, handouts, and displays explaining what and 

why you are conducting burns are important tools to 

prepare in advance of program growth. You should plan 

on spending time talking with local, state, and federal 

elected officials about the importance and need for 

prescribed fire, as constituents will contact their elected 

representatives about your burning efforts.

As prescribed fire programs grow, they often encounter 

vocal minority groups that oppose the use of fire as a 

management tool. These opposition groups can provide a 

serious challenge to a program. They may base arguments 

on emotion rather than science, and will utilize websites, 

letters to the editor, and petitions to promote their 

viewpoint. Many of the opposing arguments focus on 

potential short-term impacts to plants and animals and 

do not consider the long-term benefits to habitat that 

result from the application of prescribed fire.

The majority of the general public will remain silent on 

the issue, even if these individuals support your efforts. 

However, you should expect people to speak up if a burn 

impacts them or others they care about, as in the case of 

a close-to-home fire or one that creates a smoke problem. 

When addressing these concerns, make sure you take 

time to listen and understand the concern. Frame your 

response to address the concern and stress the importance 

of the prescribed fire as a management tool. If there 

are ways to mitigate the concern in the future, be sure 

to acknowledge that you will change your practice to 

accommodate the concern. Not addressing an individual 

concern may result in the formation of a new vocal 

minority group that opposes prescribed fire.

As a prescribed fire program grows, it is important to 

recognize that just because there had been no public 

opposition to burning in one or more areas, this silent 

acquiescence may not hold true as burning begins in new 

areas. Additionally, as the use of fire increases, there will 

be a corresponding need for increasing efforts to reach 

out and educate the public. 

Questions will also come from the public, as well as 

within agencies, on the question of why there is a shift 

from fire suppression to prescribed fire. When addressing 

these questions, as well as other questions on the use of 

fire, be sure that if you say something is “science-based,” 

you have the support of science and scientists. If you are 

using adaptive management to make your decisions, say 

that as well. Finally, when dealing with the public and 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 121

media, you or other fire management personnel may say 

something that can be taken out of context, portraying 

your agency in a bad light. It’s important to think how 

something you might say could be used in a story or on a 

website.

IMPLEMENTATION: 

METHODS AND CHALLENGES

As a prescribed fire program grows, the complexity 

of burns will increase, as will the need for additional 

resources. Along with these changes comes the challenge 

of positioning personnel to perform successfully through 

training. Training of prescribed fire personnel should 

focus on both the operational level and the “state of the 

science.” Understanding the science will better enable your 

personnel to meet the burning objectives because they 

will understand the benefits of prescribed fire more fully.

It is important to recognize that a workforce that has 

extensive fire suppression training and experience may 

lack the knowledge, skills, and abilities to perform 

prescribed burns that meet land management objectives. 

Tactically, the application of fire, or “burning out,” 

during fire suppression is commonly the approach that 

experienced firefighters utilize when implementing 

prescribed burns. In most cases, burning out is rapidly 

performed in order to secure the control lines by 

removing the fuel ahead of the main fire. Many times use 

of the standard burning-out methods results in too much 

heat and negative fire effects (e.g., damage to the stand). 

Training on firing methods such as flanking fire, dot 

firing, and chevron patterns is helpful in addressing this 

issue.

A key point to emphasize to the workforce is that 

prescribed burns are conducted to achieve management 

objectives, not to achieve black acres. To achieve 

management objectives, prescribed fire programs may 

need to look at using different burning practices, 

methods, and tools.

Equipment needs are different for prescribed fire than 

for fire suppression. Instead of emphasis on equipment 

that can put out fire, large-scale prescribed fires require 

emphasis on equipment that can light fire. Efficient 

and effective ignition of prescribed burns requires the 

need for more and specialized equipment. Drip torches 

are the workhorse of any prescribed fire program. It is 

important to have a lot of these in your equipment cache. 

Prepositioning a large stock of torches throughout your 

burn unit will reduce the time spent waiting for torches 

to be refilled. Having more drip torches available also 

increases the number of igniters you can use on a burn. 

Having too few torches often is the limiting factor for 

completing the burn efficiently. In addition to drip 

torches, standard operating procedures should require all 

igniters to carry several fusees, which can be used to keep 

the operation moving when refueling is not possible.

Other useful firing devices are flare guns, Terra Torch®, 

torches mounted on all-terrain vehicles (ATVs), and 

plastic sphere dispensers. Flare guns and plastic sphere 

dispensers are used to facilitate interior ignition. Flare 

guns can launch a highly flammable flare approximately 

100 yards to ignite inaccessible areas. Ground-based 

plastic sphere launchers are also used to facilitate 

interior ignition. These handheld launchers perform 

the same function as aerial-mounted plastic sphere 

dispensers (see below), injecting spheres filled with 

potassium permanganate with ethylene glycol to create an 

exothermic chemical reaction; instead of the ball falling 

from the aircraft to the ground, the ball is launched 

into the fuel bed. These devices are very useful when 

using the spot ignition technique on smaller units and 

when igniting areas that are difficult to reach with other 

ground-based tools (e.g., locations across waterways, areas 

of dense fuel concentrations).

ATV-mounted torches are great tools to use when firing 

on flat ground or where there are roads and trails that 

are ATV-accessible. These torches expedite blacklining 

and lighting from roads and trails. If the burn unit has 

gentle terrain and is fairly open, these devices can be 

used to perform interior ignition as well. The operator 

using an ATV to perform interior ignition needs to be 

an experienced ATV operator as well as an experienced 

igniter. In many incidents during the past several years, 

ATV torch operators have been trapped inside burn units 

because of ATV operation error or lack of good judgment 

on fire behavior.
122 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Terra Torches® are very useful when burning larger fuels 

or for burning during times of higher fuel moistures 

(Fig 3). These devices can be used to blackline prescribed 

burn units due to the long residence time of the gelled 

fuel. These units are also helpful in ignition on roadsides 

and can blacken edges rapidly. The Terra Torch®

requires access to both gasoline and diesel fuel in large 

quantities, gelling powder, and a means of transportation 

for the torch.

Aerial mounted plastic sphere dispensers (PSD) should 

be considered when burning forested areas more than 

200 acres in size. The use of a PSD machine allows the 

prescribed burn manager to spread fire across the unit very 

quickly. The fire intensity can be managed through the 

spacing of the ignition flight lines as well as the distance 

between each sphere within a given line. Each sphere 

creates a single ignition point and hence an individual 

fire. The spacing of these individual fires can be used to 

manipulate how much of the unit is burned with heading, 

backing, and flanking fire intensity. The use of an aerial 

PSD machine has specific requirements that may be 

challenging for some agencies. To use aerial ignition, the 

prescribed burn manager needs access to a helicopter, a 

PSD machine, and personnel trained in the operation 

of the equipment. Although the cost of a helicopter is 

generally in the range of $400-$1000 per hour, the use of 

aerial ignition can dramatically reduce prescribed fire costs, 

especially on larger units, due to the reduction in time and 

personnel needed to complete the burn.

Other tools include ATVs, water units, and portable 

water tanks. ATVs are very useful for patrolling, 

monitoring, and moving supplies throughout your 

burning area. It is important that you use trained and 

skilled operators that recognize where the ATVs can 

travel safely. Prescribed fire managers should not push 

the limitations of the equipment and operators by asking 

them to go places that are not safe. Water units such 

as engines and other utility vehicles with water tanks 

and pumps are very useful during holding and mop-up 

operations. When water units are used, portable water 

tanks strategically placed throughout your burning area 

will be very helpful in providing refill locations.

As a prescribed fire management program grows, 

there will be successful days and days that were not as 

successful. It is critical to document what you did, when 

you did it, why you did it, and what results you got. 

Without these data, it will be difficult to determine what 

works well and more importantly, how to replicate it. 

When determining the effects of a burn, you need to be 

patient: It often takes time for those effects to become 

obvious. When burning, you may need to find out what 

fire intensity is “too hot” and what is “too cool” for your 

objectives and try to burn at an appropriate intermediate 

intensity.

After-action reviews (AAR) should be established as 

a standard operating procedure. These reviews can be 

implemented in many ways without taking too much 

time. The AAR should be done immediately after the 

burn has finished, while the crew still has the events of 

the day in mind. Items that come out of these reviews 

may seem minor, but oftentimes it is the small details 

that get overlooked in the planning process. Paying 

attention to these details can greatly improve the overall 

performance of the burning group. The use of AARs has 

caused the Division of Forestry to place greater emphasis 

on logistical support and planning, such as prepositioned 

drip torches, better communications, and better 

availability of supplies. Periodic program reviews are also 

helpful for looking at organizational issues that may need 

adjustment.

As a prescribed fire program grows, it is important to 

recognize that your people will need to grow as well. 

Figure 3.—The Terra Torch® in use on a Division of Forestry 

prescribed fire.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 123

Utilize the most skilled prescribed fire personnel in 

the most critical roles and locations during burns. 

Make sure that they have someone with them who 

has a mentor and is being nurtured for the future. It is 

important to establish partnerships with other agencies 

and organizations that conduct burns. It can be very 

educational for your personnel to work with these other 

groups to provide a different training experience. In 

addition, helping out on others’ burns is beneficial as 

they will be more likely to reciprocate.

As a program burns more acreage, it is important to 

stay abreast of air quality issues. Air quality regulations 

are developed nationally and enforced locally. It is also 

important to get to know your local air quality regulators 

and to have them observe burns. Once they observe what 

you are doing with fire and understand that you know 

what you are doing, they will be more likely to work with 

you. Many states’ air quality regulations are lumped into 

the general open burning regulations, and showing the 

regulators how prescribed fire is different from general 

open burning is important as well. In areas where smoke 

is a concern, the air quality agency may be able to place 

monitors in these locations to document background 

air quality as well as impacts on the air quality from 

prescribed burns. Smoke management training and 

research carried out during prescribed burns will be 

critical to ensure that smoke does not impact the public 

in undesirable ways and that burning can be allowed to 

continue.

Most importantly, safe burning practices must be stressed 

as programs grow. Escaped prescribed fire could result in 

legislative action that would limit or end the use of this 

important land management tool.

LESSONS LEARNED DURING

IMPLEMENTATION

Fire Behavior and Fire Season

An early lesson that we learned was that the conditions 

on days the Division typically thought of as “fire days” 

are not the most conducive to prescribed burns. The fuel 

and weather conditions on “fire days” are often too dry, 

resulting in intense fire behavior and mortality of larger 

trees, which is not our objective.

The development of burn prescriptions is an art based 

upon science. When developing prescriptions, you 

should be careful not to prescribe yourself out of the 

opportunity to burn. Prescriptions should be developed 

to allow for burning on almost any day that fire will carry 

across the landscape.

The number of days since rain is more critical in the 

early spring than the late spring when vegetation is 

pulling moisture out of the soil; a longer rain-free period 

is necessary in early March as compared to mid-April 

for leaf litter to be dry enough to burn. During the fall, 

burning is successful under higher relative humidities 

than in the spring because autumn leaf litter is less 

compacted. During the spring, when the litter has been 

compacted over the winter, only the top layer of litter 

burns unless the site has experienced an extended rainfree period, generally 5 or more days.

In our region, it is very difficult to manage fire behavior 

on very dry sites that have not had fire exposure in 

several years, especially those with dense thickets of 

greenbriar (Smilax rotundifolia). These sites burn with 

high intensity, regardless of the type of fire (heading, 

backing, or flanking), and some overstory mortality often 

occurs. Conversely, fire may carry across mesic sites, but 

with very low intensity and limited effects. Observations 

of fire behavior on sites that had a mixture of oak (dry 

sites) and yellow-poplar/red maple (mesic or wet sites) 

stands illustrate this difference. Fire behavior in the oak 

stands was moderately intense (3-ft flame lengths) while 

the fire behavior in the yellow poplar/red maple areas was 

minimal and in many places the fire went out (Fig. 4)

Early growing-season burns may be the “wave of the 

future” and should be considered. Research has indicated 

that burning during this season can provide the greatest 

benefit to oak regeneration by having a larger negative 

impact on competing species such as red maple and 

yellow-poplar (Brose and Van Lear 1998). Early growingseason fires are much easier to control because they have 

lower flame lengths, lower rates of spread, and reduced 

potential for escape due to lower probability of ignition 

(Fig. 5). Growing-season burning also extends the spring 

fire season by 3 to 6 weeks. In Ohio, green-up begins 

in mid-April, the traditional end of the prescribed fire 
124 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

season; burning throughout the early growing season 

extends the fire season until mid-May. However, early 

growing-season burns raise questions and concerns 

related to potential negative impacts on animals such as 

turtles, snakes, and ground-nesting birds. More research 

needs to be conducted to determine whether short-term 

negative impacts (if any) are outweighed by long-term 

positive changes to habitat.

Operationally, growing-season burns will be different 

in several ways. The prescribed fire crew is exposed to 

more physically taxing conditions due to higher air 

temperatures. During the typical dormant burning 

season, it is unusual to experience air temperatures over 

75 o

F, but higher temperatures will be common during 

the early growing season. Early growing-season burns 

will also have reduced visibility across the unit due to 

the leaves on the vegetation, reducing the ability to see 

people in the unit and spot fires outside of the unit.

Fire Effects

Many prescribed burns are being conducted in oakdominated forests to reduce the competition to oak 

regeneration by red maple and/or other thin-barked trees. 

A single burn will topkill red maple stems, but abundant 

resprouting will follow. To reduce this competition, 

more than one burn will be needed to be successful. 

Our experience is that fire effects, both desirable and 

undesirable, take at least 2 years to become evident. It is 

important to continue to monitor sites for several years 

after burning to detect these changes.

In general, we observe that burning is reducing the 

low shade and topkilling the fire-intolerant species. 

However, if promotion of oak advance regeneration 

is a management goal, canopy opening will likely be 

required to provide more light to the oak seedlings. In 

locations where we have burned and opened the canopy, 

we are beginning to see the development of vigorous oak 

advance regeneration (Fig. 6).

LITERATURE CITED

Abrams, M.D. 1992. Fire and the development of oak 

forests. BioScience. 42: 346-351.

Brose, P.H.; Van Lear, D.H. 1998. Responses of 

hardwood advance regeneration to seasonal 

prescribed fires in oak-dominated stands. Canadian 

Journal of Forest Research. 28: 331-339.

Dey, D.C.; Fan, Z. 2009. A review of fire and oak 

regeneration and overstory recruitment. In: 

Hutchinson, T.F., ed. Proceedings of the 3rd

 fire 

in eastern oak forests conference; 2008 May 20-

22; Carbondale, IL. Gen. Tech. Rep. NRS-P-46. 

Newtown Square, PA: U.S. Department of 

Figure 4.—Patchy fire coverage on a site dominated by nonoak species.

Figure 5.—An early growing-season burn conducted at the 

Vinton Furnace Experimental Forest, May 6, 2008.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 125

Agriculture, Forest Service, Northern Research 

Station: 3-20.

Griffith, D.M.; DiGiovanni, D.; Witzel, T.L.; Wharton, 

E.H. 1993. Forest statistics for Ohio, 1991. Resour. 

Bull. NE-128. Radnor, PA: U.S. Department of 

Agriculture, Forest Service, Northeastern Forest 

Experiment Station. 169 p.

Hutchinson, T.F.; Long, R.P.; Ford, R.D.; Sutherland, 

E.K. 2008. Fire history and the establishment of 

oaks and maples in second-growth forests. Canadian 

Journal of Forest Research. 38: 1184-1198.

Leete, B.E. 1938. Forest fires in Ohio 1923 to 

1935. Bull. 598. Wooster, OH: Ohio Agricultural 

Experiment Station. 54 p.

McEwan, R.W.; Hutchinson, T.F.; Long, R.P.; Ford, 

R.D.; McCarthy, B.C. 2007. Temporal and spatial 

patterns of fire occurrence during the establishment 

of mixed-oak forests in eastern North America.

Journal of Vegetation Science. 18: 655-664.

Yaussy, D.A.; Waldrop, T.A. 2009. Fire and fire 

surrogates study: annotated highlights from 

oak-dominated sites. In: Hutchinson, T.F., ed. 

Proceedings of the 3rd fire in eastern oak forests 

conference; 2008 May 20-22; Carbondale, IL. Gen. 

Tech. Rep. NRS-P-46 Newtown Square, PA: U.S. 

Department of Agriculture, Forest Service, Northern 

Research Station: 40-50.

Figure 6.—Abundant white oak advance regeneration on 

a burned site in southern Ohio. This site had been burned 

five times from 1996 to 2004, largely eliminating the sapling 

layer of shade-tolerant species. Here, white oak seedlings 

are growing rapidly in a gap caused by the death of several 

dominant and codominant white oaks, part of a regional white 

oak decline event.
126 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

LANDSCAPE-SCALE FIRE RESTORATION ON THE BIG PINEY RANGER

DISTRICT IN THE OZARK HIGHLANDS OF ARKANSAS

John Andre1, McRee Anderson2, Douglas Zollner3, Marie Melnechuk3, and Theo Witsell3

1

Ecologist (retired), Big Piney Ranger District, Ozark-St. Francis National Forest, Hector, AR 2

Fire Restoration Project Manager, Interior Highlands Office, The Nature Conservancy, Jasper, AR

3

Director of Conservation (DZ), and Ecologist (MM), The Nature Conservancy, Little Rock, AR

4

Botanist, Arkansas Natural Heritage Commission, Little Rock, AR

JA is corresponding author: to contact call (870) 496-2445 or email at jandre@hughes.net

Abstract.—The Ozark-St. Francis National Forest, The Nature Conservancy (TNC), the Arkansas 

Natural Heritage Commission, Arkansas Forestry Commission, private landowners, and others are 

currently engaged in a collaborative project to restore the oak-hickory and pine-oak ecosystems of 

the Ozark Highlands on 60,000 acres of the Big Piney Ranger District. Frequent historical fires and 

native grazers (e.g., elk and bison) maintained an open canopy of woodlands and savannas, where oaks, 

hickories, and shortleaf pine dominated. Today, these former woodlands now contain “forest-like” closed 

canopies (dominated by oak-hickory, oak-shortleaf pine, and shortleaf pine) caused by changes in landuse practices, including fire suppression, domestic livestock grazing, and silviculture. Historic records 

indicate that pre-European settlement Ozark woodlands averaged 38-76 trees per acre. Current densities 

average 300-1,000 stems per acre. Oak decline and the red oak borer have affected at least 300,000 

acres of the Ozark National Forest and about 1.5 million acres of the Ozark Highlands. The Big Piney 

Ranger District is implementing a long-term, landscape-scale ecosystem restoration project in a TNC 

conservation priority area. Specific project activities include the application of periodic prescribed fire and 

thinning by commercial and noncommercial methods. The goals of these activities are to improve forest 

health, restore fire-dependent woodland ecosystems, and provide for safety by reducing hazardous fuels 

in the wildland/urban interface. A comprehensive monitoring program documenting ecosystem responses 

to prescribed fire and woodland thinning treatments is currently being implemented. The monitoring 

program includes tracking changes in overstory, understory, and herbaceous plant species, the structure of 

plant communities, fuel loads, nonnative invasive species, and breeding and wintering bird communities. 

INTRODUCTION

Fire has been a dominant force in establishing and 

maintaining woodland ecosystems throughout North 

America (Pyne 1982). Forest health issues in the Ozark 

Mountains of Arkansas mirror changes occurring in other 

forest ecosystems throughout the country. Altered fire 

regimes and past land management activities have led 

to a significant increase in fuel loads and tree densities, 

a shift in species composition, and a decline in forest 

health. Currently, there are substantially more degraded 

woodlands with closed canopies (oak-hickory, oakpine, and shortleaf pine [Pinus echinata Mill.]), and less 

woodlands (oak-pine woodland, oak-hickory woodland, 

and shortleaf pine woodland) than occurred historically 

under a more frequent fire regime (Foti 2004). The 

frequent, low-intensity fire regime under which these 

ecosystems evolved has been disrupted (Guyette and 

Spetich 2003). The woodlands of the Ozark and 

Ouachita Mountains were heavily logged 80-100 years 

ago. By the 1920s and 1930s systematic fire protection 

had been established on National Forest and private 

lands, and the fire frequency was drastically reduced 

(McGuire 1941, Bass 1981, Strausberg and Hough 

1997, Soucy et al. 2005). Historic records indicate that 

presettlement tree density in the Ozark Highlands (Bailey 

1998) ranged from 38-76 trees per acre (Foti 2004). 

Current densities in much of the region range from 

300-1,000 stems per acre. Increased stand density leads 

to increased competition for available nutrients, sunlight, 

and moisture. Fralish (2004) states that in addition to 

densification, woodland communities are shifting from a 

fire-adapted oak-pine dominated community to a more 

fire-intolerant community of red maple (Acer rubrum 

L.), sugar maple (Acer saccharum Marsh.), and American 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 127

beech (Fagus grandifolia Ehrh.). During periods of 

drought, trees already stressed by resource competition 

become more vulnerable to disease and insect attack, 

such as the red oak borer. Fire suppression has greatly 

reduced the once-common oak and pine woodlands on 

National Forest lands; their integrity is at risk.

Dendrochronologists and other researchers have 

investigated the fire history of the Ozark Highland over 

the last 30 years. At three sites on the Big Piney Ranger 

District, Guyette and Spetich (2003) reported mean re 

return intervals of 5-16 years from 1680-1820, 2-3 years 

from 1821-1880, 2-5 years from 1881-1920, and >62 

years (one study site) to 80 years (two study sites) from 

1921-2000. Recent work from three additional sites on 

the Big Piney Ranger District revealed mean re return 

intervals of 1.4-5.4 years from 1810-1920 (Guyette et al. 

2006). Engbring et al. (2008) reported mean fire return 

intervals for a site in north-central Arkansas of 1.9 years 

from 1820-1900, 2.1 years from 1901-1930, and 2.6 

years from 1931-2003. Reduced re frequency beginning 

in the 1920s re ects the implementation of effective fire 

suppression and prevention programs in Arkansas (Bass 

1981).

The Ozark Highlands are biologically important due 

to the diversity provided by a system of fire-adapted, 

wooded, and partially wooded herbaceous plant 

communities. More than 150 species of animals and 

plants are endemic to the Ozark Highlands. Most of 

these species rely in some way upon healthy oak and pine 

ecosystems. Many socially, economically, and ecologically 

important species inhabit these ecosystems, such as 

neotropical migratory birds, white-tailed deer, black bear, 

turkey, and quail.

In 2001 the U.S. Forest Service (USFS) and multiple 

partner groups initiated the largest ecosystem restoration 

project in the USFS Southern Region. The project 

encompasses 60,000 acres of the Big Piney Ranger 

District, Ozark-St. Francis National Forest, in Arkansas. 

The goal of the project is to restore structure, function, 

and ecological processes that will develop and sustain 

oak and pine woodland ecosystems. This paper describes 

project planning, including modeling and quantifying 

desired conditions, and implementation. The use and 

effectiveness of collaborative partnerships at multiple 

levels are also described.

RESTORATION SITE LOCATIONS

Six restoration areas, ranging from 6,000 acres to 12,500 

acres, were established on the Big Piney Ranger District. 

At the time of establishment, the areas were in the 

General Forest Management Area of the 1986 Ozark-St. 

Francis Land and Resource Management Plan. Under the 

Revised Land and Resource Management Plan (USDA 

FS 2005), the areas are in the oak woodland and pine 

woodland management areas. The six sites are primarily 

in the Lower Boston Mountains Subsection. The location 

of each restoration area within this subsection represents 

one or more of the land type associations (LTAs) (USDA 

FS 1997) that occur on the District.

PROJECT DEVELOPMENT

Collaborative Partnerships

Collaborative partnerships at multiple levels have 

formed to address the current state of declining forest 

health throughout the Ozark Highlands. The ecosystem 

restoration project described here is supported by the 

Oak Ecosystem Restoration Team, which includes 

representatives from the Arkansas Wildlife Federation, 

Arkansas Game and Fish Commission, Arkansas Forestry 

Commission, Arkansas Natural Heritage Commission, 

U.S. Fish and Wildlife Service, University of Arkansas 

Cooperative Extension Service, The Nature Conservancy 

(TNC), USFS, and USFS - Southern Research Station. 

The Oak Ecosystem Team has selected the Big Piney 

Ranger District’s Ecosystem Restoration Project as a 

demonstration site for the restoration of fire-adapted 

woodland ecosystems in the Ozark Highlands. The 

partnership uses this demonstration site to host public, 

private, and legislative tours and to provide information 

on current and desired ecological conditions and 

strategies for achieving ecosystem restoration objectives.

The ecosystem restoration project is also part of the Fire 

Learning Network (FLN), a collaborative project between 

the USFS, Department of the Interior, and TNC. The 

FLN promotes the development and testing of creative, 
128 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

adaptive, multi-ownership fire management strategies 

that are compatible with the National Fire Plan goals and 

TNC’s conservation goals. The network strives to achieve 

tangible results at landscape and ecoregional scales. 

Projects within the network have completed ecological 

models, developed spatially explicit maps of current 

and desired future conditions, developed alternative 

management scenarios for ecological restoration, and 

developed broad-based monitoring programs to track 

progress toward achieving desired future conditions.

Landscape Assessment

Based on an analysis of the Government Land Office 

(GLO) records, Foti (2004) concluded that 67 percent 

of the Ozark Highlands presettlement landscape was 

composed of open woodlands, savanna, and prairie. On 

the Big Piney, open woodlands occurred most frequently 

on ridge tops, flats, and south-facing slopes and less 

frequently on upper north-facing slopes, toe slopes, and 

bottoms. Mid and lower north-facing slopes were more 

densely forested. Oak, oak-pine, and pine woodlands 

occurred on about 80 percent of the land area of the 

district during presettlement times.

In 2002 oak and pine woodlands covered less than 6 

percent of the land area. The Big Piney Ranger District 

and its partners identified 60,000 acres in six areas 

(Middlefork-12,200 acres, Rotary Ann-12,500 acres, 

Piney-12,200 acres, Oak Mt.- 6,000 acres, Eastside11,300 acres, Southfork- 6,000 acres) for a long-term 

ecosystem restoration project. Project area boundaries 

adjoin about 14,000 acres of private property; almost 

1,100 acres of private property are inside the designated 

restoration areas, providing opportunities for publicprivate partnerships.

Ecological Models

To develop an understanding of how the ecosystems 

within the project area function, the project team 

and partners collaboratively developed and quantified 

conceptual ecological models using the Vegetation 

Dynamics Development Tool (Beukema et al. 

2003). This process expanded the partners’ ecological 

understanding and aligned alternative treatment options 

with the desired condition (plant community structure 

and species composition) envisioned for the landscape.

Quantifying and Mapping the Current Condition

We used the NatureServe (www.natureserve.org) 

classification system to identify seven cover types: OakHickory Closed Canopy, Oak-Hickory Woodland, OakPine Closed Canopy Forest, Oak-Pine Woodland/Savanna, 

Shortleaf Pine Closed Canopy Forest, Shortleaf Pine 

Woodland/Savanna, and Sandstone Glade. We used these 

cover types and three data sets (land type-associations, 

land types, and USFS Natural Resource Information 

1

Figure 1.—Current condition of a 

degraded oak-hickory woodland.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 129

System FSVeg cover types) to define and map current 

ecological conditions. LTAs (USDA FS 1997) were used 

to qualitatively map the plant communities that occur 

within the project area: the Mesic Morrow Mountain 

Uplands, Bloyd Mountain Valleys, Lower Atoka Hills 

and Mountains, and the Arkansas Valley Hills. Each LTA 

was mapped and overlaid with the current cover types 

derived from ground-truthed orthophoto quads and 

FSVeg data. A land type (subdivision of LTA) combines 

a suite of ecological characteristics (soil type, aspect, 

slope, and climate conditions) that distinguish it from 

other land types. We classified land types as riparian, 

toe slope, south slope (lower, middle, and upper), 

ridge top, and north slope (lower, middle, and upper). 

This information was projected across the project area. 

Current cover types were quantified for the project areas 

(Table 1).

Desired Conditions

Information used to develop the scientific justification 

for the desired condition included historical accounts, 

dendrochronological studies, GLO records, scientific 

literature, and the information inherent to the Ecological 

Classification System. The desired condition of each 

cover type was quantified, described, and delineated 

across the project area using geographic information 

systems. Cover types were mapped to depict their 

locations under the historical fire regime. Once this 

process was completed, the desired conditions were 

presented to the project partners in a collaborative, peerreviewed process (FLN 2002b) to refine the product 

(Table 1).

PROJECT IMPLEMENTATION

We developed a 10-year implementation plan that 

strategically identifies five key areas crucial to the project’s 

success: (1) prescribed fire; (2) public outreach; (3) 

noncommercial mechanical treatments; (4) commercial 

timber sales; and (5) monitoring. The purpose of the 10-

year work plan was to set annual implementation targets 

3

Figure 2.—Desired condition of a 

restored oak-hickory woodland.

Table 1.—Quantification of current and desired conditions

Cover Type Current Condition 

(%)

Desired Condition 

(%)

Oak-Hickory Closed 

Canopy Foresta

75 16 

Oak-Hickory Woodland 1 35

Oak-Pine Closed 

Canopy Forest

8 0

Oak-Pine Woodland/

Savanna

4 38

Shortleaf Pine Closed 

Canopy Forest

10 0

Shortleaf Pine 

Woodland/Savanna

1 10

Glade/Prairie 1 1

a

Includes degraded Oak-Hickory Woodland currently classified as 

Forest.
130 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

for all staff (U.S. Forest Service and partners) working 

on the project and to track progress toward achieving the 

desired condition. Management actions with National 

Environmental Policy Act (NEPA) requirements were 

approved for the Middle Fork area in 2002. By 2004, all 

management action planning and NEPA requirements 

were completed for the remaining five restoration areas. 

Table 2 outlines the management actions planned for 

each restoration area. These actions will significantly 

move the ecosystems toward the desired overstory 

structural condition within 10 years.

Public Relations and Educational 

Strategies

The team developed public relations education strategies 

through the planning process (FLN 2002a). Defining 

these strategies broadens the thinking behind restoration 

implementation by identifying possible barriers and 

by exploring a variety of issues that are generally not 

captured with traditional planning efforts. The FLN team 

identified the need to develop public support for the 

use of prescribed fire and mechanical thinning for this 

ecosystem restoration project and specifically the need to 

deal with the public’s concerns about smoke pollution. 

Furthermore, the team recommended addressing 

credibility issues with the public, enhancing collaborative 

relationships with partners, and developing an outreach 

process to include new partners.

Prescribed Burning

Prescribed fire is crucial in meeting desired ecological 

conditions. The desired fire regime includes a fire return 

interval that ranges from 2 to 5 years with the entire area 

being burned 2 to 4 times during the duration of the 

project (10 years). Both the seasonality and severity of fire 

are adjusted to achieve the desired ecological condition. 

Dormant-season fires are used in parts of the project area 

to reduce fuel loads. A combination of dormant- and 

growing-season fire is used to achieve the desired fire 

effects on plant community structure and composition.

Since the inception of the restoration project in 2002 

through mid-2008, 100,000 acres have been burned 

(some units burned multiple times). Most of these 

large-scale burns have taken place in the dormant or 

early growing season (January-April). The average size 

of a single-day burn is about 2,000 acres. Multiple-day 

burn units are up to 5,500 acres. Less than 5 percent of 

the acreage has been burned in the summer. The largest 

growing-season burn spanned 10 days (June 24- July 4, 

2006), due to the limited availability of a helicopter for 

aerial ignition. The historic fire regime is being restored 

on public and private lands.

Mechanical Treatments

Mechanical treatments are conducted on both public 

and private land. For the public lands, treatments are 

implemented using commercial timber sales, wildlife 

stand improvement thinning, public firewood cuts, and 

salvage sales to remove oak-decline affected trees. For 

private lands, the Forest Land Enhancement Program, 

Stewardship Incentive Program, and the Forest Incentive 

Program are being used. The treatments reduce overstory 

basal area and stem density and move the overstory 

structure and composition toward the desired condition. 

To accomplish a reduction in overstory basal area (BA), 

oak-dominated and mixed oak-pine stands are thinned 

to a BA of 40 to 60 square feet per acre. Pine-dominated 

stands are thinned to a BA of 50 to 70 square feet per 

acre. All thinnings remove the smaller diameter mid-story 

and co-dominant trees. Hardwood leave trees are selected 

to favor the historically dominant white and post oaks. 

As of mid-2008, 12,000 acres have been thinned to the 

desired condition.

Monitoring and Adaptive Management

Collaborative landscape-scale monitoring and adaptive 

management protocols have been developed for the 

restoration project. Monitoring components include 

fire effects on vegetation, fuel loading, and birds. The 

ecological monitoring program was developed by 

Table 2.—Restoration Treatments for 2004-2014

Project Area Prescribed Fire Thinning

Middle Fork 12,200 acres 4,300 acres

Piney 12,000 acres 6,705 acres

Rotary Ann 12,500 acres 4,478 acres

South Fork 6,000 acres 2,830 acres

Oak Mountain 6,000 acres 4,122 acres

East Side 11,300 acres 5,816 acres
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 131

the Big Piney Ranger District, TNC, and Arkansas 

Natural Heritage Commission and reviewed by the Oak 

Ecosystem Restoration Team. The monitoring program 

documents and quantifies movement toward the desired 

condition, fuels reduction, and forest health. Specifically, 

the program includes monitoring goals, project success 

criteria, macro-plots sampling methodology, and nine 

individual monitoring protocols to determine whether 

the project is meeting success criteria defined by all 

partners.

The plant community monitoring component was 

established to answer two questions: (1) Are project 

activities reducing hazardous fuels within the project 

area; and (2) are the treatments moving the project 

area toward the structural and compositional desired 

ecological conditions? The monitoring utilizes a nested 

quadrat method with four, 3.25-ft x 3.25-ft herbaceous 

quadrats and two 11-ft radius shrub quadrats nested 

within one 33-ft radius tree plot. Analyses indicate 

treated areas (one to two prescribed fires) have fewer 

stems per acre, fewer shade-tolerant species, and increased 

herbaceous diversity.

CONCLUSION

The Oak Ecosystem Restoration and Fire Learning 

Network teams and Big Piney Ranger District identified 

60,000 acres for a long-term woodland ecosystem 

restoration project in 2002. This is one of the largest, 

most successful restoration projects in the Forest Service 

Southern Region. It serves as a model for designated Oak 

and Pine Woodland Management Areas (252,333 acres) 

in the Revised Land and Resources Management Plan 

for the Ozark-St. Francis National Forests (USDA Forest 

Service 2005).

Collaborative landscape-scale fire restoration in the 

Ozark Highlands of Arkansas depends on a multi-partner 

approach, a defined project vision, quantification of 

current and desired conditions, information transfer, and 

a monitoring program to track progress toward achieving 

the desired condition. Partners bring expertise from a 

variety of backgrounds with diverse skill sets, resources, 

and expertise and are key to the success in landscapescale restoration projects. A collaboratively developed 

project plan and vision outlining the steps needed to 

achieve the desired ecological outcomes are crucial 

for successful partnerships. This project integrates the 

ecological rationale for restoration with education and 

outreach to the public and a diverse suite of partners. A 

successful partnership has been formed with a common 

vision for sustainable restored ecosystems of oak and pine 

woodlands. Public support for restoring historic fire 

regimes and reducing hazardous fuels has strengthened. 

The project demonstrates the successful restoration of 

ecosystem structure and function in oak and shortleaf 

pine ecosystems within the Ozark - St. Francis National 

Forest and responds to the need to implement landscapescale treatments on woodland ecosystems administered 

by the USFS (USDA FS 2005).

LITERATURE CITED

Bailey, G.A. 1998. Ecoregions: the ecosystem 

geography of the oceans and continents. New York, 

NY: Springer-Verlag. 176 p.

Bass, S.M. 1981. For the trees: an illustrated history of 

the Ozark-St. Francis National Forests 1908-1978.

Atlanta, GA: U.S. Department of Agriculture, Forest 

Service, Southern Region. 171 p.

Beukema, S.J.; Kurz, W.A.; Pinkham, C.B.; Milosheva, 

K.; Frid, L. 2003. Vegetation dynamics development 

tool, user’s guide, version 4.4c. Vancouver, BC: 

ESSA Technologies Ltd. 239 p.

Engbring, B. L.; Heitzman, E.; Spetich, M.A. 2008. 

Ridgetop fire history of an oak-pine forest in 

the Ozark Mountains of Arkansas. Southeastern 

Naturalist. 7(1): 49-60.

Fire Learn Network (FLN). 2002a. Workshop #1 

planning paper. Unpublished document. Arlington, 

VA: The Nature Conservancy. (http://www.tncfire.org/

training_usfln_wrkshps.htm)

Fire Learn Network (FLN). 2002b. Workshop #2 

planning paper. Unpublished document. Arlington, 

VA: The Nature Conservancy. (http://www.tncfire.org/

training_usfln_wrkshps.htm)
132 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Foti, T. 2004. Upland hardwood forests and related 

communities of the Arkansas Ozarks in the early 

19th Century. In: Spetich, M.B., ed. Proceedings, 

upland oak ecology symposium: history, current 

conditions, and sustainability; 2002 October 7-10; 

Fayetteville, AR. Gen. Tech. Rep. SRS-73. U.S. 

Department of Agriculture, Forest Service, Southern 

Research Station: 21-29.

Fralish, J. 2004. The keystone role of oak and hickory 

in the central hardwood forest. In: Spetich, M.B., 

ed. Proceedings, upland oak ecology symposium: 

history, current conditions, and sustainability; 2002 

October 7-10; Fayetteville, AR. Gen. Tech. Rep. SRS73. U.S. Department of Agriculture, Forest Service, 

Southern Research Station: 78-87.

Guyette, R.P.; Spetich, M.A.; Stambaugh, M.C. 2006. 

Historic fire regime dynamics and forcing factors 

in the Boston Mountains, Arkansas, USA. Forest 

Ecology and Management. 234: 293-304.

Guyette, R.P.; Spetich, M.A. 2003. Fire history of 

oak-pine forest in the Lower Boston Mountains, 

Arkansas, USA. Forest Ecology and Management. 

180: 463-474.

McGuire, J.R. 1941. The Sylamore Experimental 

Forest. New Haven, CT: Yale School of Forestry. 156 

p. M.S. thesis.

Pyne, S.J. 1982 Fire in America: a cultural history of 

wildland and rural fire. Princeton, NJ: Princeton 

University Press. 645 p.

Soucy, R.D.; Heitzman, E.; Spetich, M.A. 2005. The 

origin and development of oak forest in the Ozark 

Mountains of Arkansas. Canadian Journal of Forest 

Research. 35: 1790-1797.

Stausberg, S.; Hough, W.A. 1997. The Ouachita and 

Ozark-St. Francis National Forest: a history of the 

lands and USDA Forest Service tenure. Gen. Tech. 

Rep. SO-121. New Orleans, LA: U.S. Department of 

Agriculture, Forest Service. 45 p.

USDA Forest Service. 1997. Ozark-St. Francis National 

Forests ecological classification system land type 

associations. Unpublished report. New Orleans, LA: 

U.S. Department of Agriculture, Forest Service.

USDA Forest Service. 2005. Revised land and resource 

management plan, Ozark-St. Francis National 

Forests, Arkansas. Atlanta, GA: U.S. Department 

of Agriculture, Forest Service, Southern Region.

Management Bulletin R8-MB 125A. 296 p.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 133

RESTORING OAK ECOSYSTEMS ON NATIONAL FOREST SYSTEM LANDS 

IN THE EASTERN REGION: AN ADAPTIVE MANAGEMENT APPROACH

Gregory Nowacki1, Michael Ablutz1, Dan Yaussy2, Thomas Schuler2 , and Dan Dey2

1

Regional Ecologist (GN) and Regional Silviculturist (retired) (MA), U.S. Forest Service, Eastern Region, Milwaukee, WI

2

Research Foresters, U.S. Forest Service, Northern Research Station, Delaware, OH, Parsons, WV, and Columbia, MO

GN is corresponding author: to contact, call (414) 297-1977 or email at gnowacki@fs.fed.us

Abstract.—The U.S. Forest Service has recently completed an ecosystem restoration framework and 

enacted accompanying policy to help guide its nationwide efforts. The Eastern Region is in the midst 

of translating the general guidance set forth in these documents to actual on-the-ground restoration. 

We envision a set of coordinated field demonstrations that will initially focus on oak-dominated 

ecosystems—ecosystems that are greatly imperiled by compositional changes to shade-tolerant trees 

such as maple (Acer) and beech (Fagus) due to long-term fire suppression. In collaboration with 

National Forests and the Northern Research Station, an adaptive management approach (learning 

by doing) is being promoted whereby an experimental design and a set of potential silvicultural 

treatments will be applied to a network of sites regionwide. Land managers, researchers, and the 

general public will all benefit from this “networked” field demonstration, which employs a uniform 

science-based method for project design, treatment selection and installation, and monitoring efforts.

INTRODUCTION

Land management continues to become increasingly 

complex with time as our ecological knowledge, 

environmental awareness, and demand for resources 

grow. Ecosystem restoration is one of a long list of 

new items that land managers now have to consider. 

Ecosystem restoration has a disproportional influence 

on land management as it embodies and simultaneously 

benefits many other resource endeavors, including 

improved biodiversity, forest health, and wildlife 

habitat conditions; increased representation of natural 

communities (including old growth) and threatened 

and endangered species; and the reduction of nonnative 

invasive species. The challenge of integrating a new 

mandate into land management warrants a well thoughtout approach. The objectives of this paper are to do 

just that by 1) providing a brief history of ecosystem 

restoration as it pertains specifically to the U.S. Forest 

Service (USFS); and 2) proffering the use of adaptive 

management principles to design a network of integrated 

field experiments for learning and demonstration across 

National Forests of the Eastern Region.

NATIONAL ECOSYSTEM 

RESTORATION FRAMEWORK

Public interest in ecosystem restoration has burgeoned 

across America, bolstered in part by catastrophic wildfires 

of the western United States. Growing public concern 

helped galvanize and propel support for political action. 

Legislation followed in the form of the President’s 

Healthy Forests Initiative (2002) and the Healthy Forests 

Restoration Act (2003). Attempting to implement this 

legislation underscored the need for a more holistic, 

overarching approach involving ecosystem restoration. 

This realization, in turn, spurred the need for clear 

language on the subject; specifically, what is ecosystem 

restoration and how can it be attained?

Although the USFS has had a long history of 

rehabilitating degraded lands (in particular the “lands 

that nobody wanted” in the eastern United States 

[Shands and Healy 1977]), actual policy and direction 

on ecosystem restoration were lacking. In response, 

the USFS established a team to help formulate the 

necessary steps to guide ecosystem restoration efforts on 

National Forests and Grasslands (Day et al. 2006 ). The 
134 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

resulting framework adopted a pre-existing definition 

for ecosystem restoration (the process of assisting the 

recovery of an ecosystem that has been degraded, 

damaged, or destroyed [SER 2004]) and provided the 

following guiding principles:

1) Seek and set goals for restoration only as societal 

choices; public involvement is key.

2) Make operational decisions at the lowest possible 

levels in an organization.

3) Consider the effects of restoration at local and 

landscape levels.

4) Give priority to restoring ecosystem processes, 

such as hydrologic pulses for rivers and streams 

or prescribed burning for fire-dependent 

ecosystems.

5) Establish objectives for the long term.

6) Recognize that ecosystems are dynamic and that 

change is inevitable; avoid “static endpoint” 

thinking.

7) Use multiple sources of relevant information, 

such as historical records, scientific studies, 

practical experience, and indigenous knowledge 

to set targets/benchmarks for evaluating progress 

based on monitoring.

8) Deal with uncertainty by using adaptive 

approaches to restoration.

9) Design and implement monitoring as part of 

restoration.

10)Learn as you go—use the feedback loop not 

only to modify treatments but also to modify 

objectives to incorporate new information or 

changing social or ecological needs.

The framework is purposefully general for application 

across a wide variety of ecosystems managed by the 

USFS. As such, it is meant to serve as a foundation to 

which information and strategies of increasing resolution 

can be added to help National Forests and Grasslands 

implement ecosystem restoration on the ground. 

The USFS’s dedication to this effort has been further 

demonstrated by its recent adoption of official restoration 

policy (USDA FS 2008).

EASTERN REGION

PLANNING FOUNDATION

Land and resource management plans guide activities 

that take place on individual National Forests and 

Grasslands. It is through these management plans that 

opportunities for ecosystem restoration are identified 

and eventually implemented at the project level. The 

release of the ecosystem restoration framework and 

ensuing policy was fortuitous for the Eastern Region, 

where many National Forests/Grasslands had recently 

revised their individual land management plans (Fig. 1). 

As such, the Eastern Region was well positioned to begin 

restoration efforts with framework guidance, policy, and 

new management plans. A basic question ensued: “How 

can management and research at the Regional level best 

help eastern National Forests/Grasslands in their quest to 

restore ecosystems?”

IMPLEMENTATION OF

RESTORATION THROUGH 

ADAPTIVE MANAGEMENT

A key role of USFS Regional Offices is to bring a broader 

perspective to issues, initiatives, or projects, especially 

those that span multiple National Forests and Grasslands 

or involve multiple partners or ownerships. Ecosystem 

restoration is a prime example – a multifaceted topic 

requiring broad integration for success. So, how best to 

embark on ecosystem restoration? One promising way 

is by taking an adaptive management approach (Walters 

and Holling 1990, Stankey et al. 2005). This approach 

is ideal in situations where high levels of uncertainty 

exist, which is indeed the case in restoring eastern U.S. 

ecosystems long affected by human manipulation (e.g., 

cutting, overgrazing, drainage, and introduction of 

nonnative pathogens and plants).

Adaptive management is founded on a formalized 

learning process that links directly to decision-making. 

Basically, it treats on-the-ground actions and policies as 

hypotheses from which we gain learning, which then 

provides the basis for modifying subsequent actions and 

policies (Stankey et al. 2005). A four-phase management 

cycle has been proffered that embraces learning, helping 

speed the acquisition and transfer of new knowledge 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 135

1

Figure 1.—The U.S. Forest Service Eastern Region and component National Forests and Grasslands.

Figure 2.—The adaptive management cycle.

to management action (Fig. 2). In the first cycle, plans 

are constructed on existing knowledge, experience, and 

organizational goals. Actions are initiated on the ground 

and their effects monitored with scientific guidance (e.g., 

experimental design and layout, measured variables, 

appropriate data analyses). Monitoring results are 

evaluated in the final phase, which might trigger the 

cycle to reinitiate if existing practices are not meeting 

expectations. Practices failing to meet expectations can be 

dropped, reformulated, or replaced with new promising 

ones during the planning phase of the next cycle. 

Long-term commitment from all parties is essential to 

successfully carry out adaptive management and accrue 

its benefits (Bormann et al. 2007).
136 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Employing an adaptive management approach for 

ecosystem restoration requires many steps, some of which 

run concurrently. First, the agency’s intention to pursue 

ecosystem restoration must be conveyed to employees, 

potential partners, and the general public. Management 

opportunities for ecosystem restoration must be 

identified by National Forest/Grassland staff according 

to individual land management plans and affiliated 

field projects. Relevant research must be identified and 

interested scientists contacted to ensure best available 

science is used in all stages of planning, implementation, 

and monitoring.

Efficiencies can be maximized by developing an 

integrated network of study sites using a uniform 

experiment design and data collection methods (Yaussy 

et al. 2008). This unified approach allows for a preferred 

set of treatments to be identified and evaluated across 

a wide variety of conditions, forming a network of 

demonstration sites (for education) that meets scientific 

rigor (for true learning). Further efficiencies would be 

attained by pooling data for improved statistical analysis 

and trend detection. Some flexibility in treatments is 

acceptable, perhaps even desirable, so long as data sharing 

and analysis are not compromised. A strong research-land 

management partnership is required to ensure ecosystem 

restoration success, which by necessity requires a longterm commitment. Joint discussions should be held 

among researchers, land managers, resource specialists, 

and partners, whereby the above steps (and personnel 

carrying out those steps) are clarified to achieve ecosystem 

restoration.

ECOSYSTEM SELECTION FOR

FIELD DEMONSTRATION

Ecosystem restoration is best demonstrated in the 

field. Fortunately, many individual restoration projects 

are already underway as National Forests/Grasslands 

implement their new land management plans. By 

linking these and future restoration projects across 

multiple Forests and Grasslands, we can demonstrate the 

advantages of taking a broader view through regionalscale analysis and evaluation. However, networking sites 

for data pooling and joint analysis requires focus on a 

single forest type or ecosystem. Selecting a representative 

ecosystem in which to employ this networked approach 

is difficult as the Eastern Region comprises a diverse 

number (from tallgrass prairies to sub-boreal conifer 

forests) with a variety of restoration needs. Indeed, all 

ecosystems are important and many are in dire need of 

recovery. For instance, red spruce forests in Appalachia 

have been severely affected by exploitive logging and 

wildfires of the late nineteenth and early twentieth 

centuries; only 12,000 ha of the original 600,000 ha 

currently remain in West Virginia (Rentch et al. 2007). 

Tallgrass prairies and associated oak savannas are 

considered the most severely degraded ecosystems on the 

North American continent, with virtually no original 

prairie land left in a pristine state (Nuzzo 1986, Packard 

and Mutel 1997).

Ultimately, it made sense to concentrate efforts on an 

ecosystem having a large geographic extent (to maximize 

the number of demonstration sites and applicability 

across the Region) with a well documented history of 

ecological alteration or degradation. To aid this endeavor 

as well as to help define reference conditions, we created 

a literature database of more than 500 articles that 

cataloged presettlement composition, structure, and 

disturbance regimes and post-settlement land-use impacts 

for the entire eastern United States. While compiling this 

database, which included information from historical, 

paleoecological, dendrochronological, fire-scar, and land 

survey records, we identified three broadly distributed 

ecosystems that stood out as having been heavily altered 

by European activity: 1) the loss of hemlock (Tsuga 

canadensis) and eastern white pine (Pinus strobus) in 

former conifer-northern hardwoods (Thompson et al. 

2006, Schulte et al. 2007); 2) the near elimination of 

the tallgrass prairie-oak (Quercus) savanna mosaic in 

the Midwest (Transeau’s [1935] “Prairie Peninsula,” 

Anderson 1998); and 3) the ongoing conversion of oakdominated systems to maple, beech, and other shadetolerant trees (Nowacki and Abrams 2008).

The following logic was employed in ecosystem selection. 

In regards to the restoration of conifer-northern 

hardwoods, the prospects of re-establishing the conifer 

component look quite dim, especially for hemlock 

(Gustafson et al. 2007). First, thinning treatments 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 137

would be needed to reduce hardwood (especially maple) 

competition in both the overstory and understory 

so that growing space would be made available for 

conifer regeneration. The lack of local seed sources 

due to preferential conifer removal by past logging 

and fire would require planting nursery stock in many 

locations—a substantial undertaking and expense. 

Moreover, even if conifer regeneration were successfully 

established, overbrowsing by white-tailed deer 

(Odocoileus virginianus) would threaten conifer growth 

and advancement in many areas (Alverson et al. 1988), 

necessitating additional control costs (e.g., fenced deer 

exclosures). Lastly, present-day investments into hemlock 

are questionable in light of the uncontrolled spread of 

the highly lethal hemlock woolly adelgid (Adelges tsugae) 

(Orwig and Foster 1998). In spite of these challenges, 

conifer restoration into northern hardwood forests is 

taking place on some National Forests where feasible.

Because of ownership patterns, the USFS’s ability to 

effect change on the tallgrass prairie-oak savanna mosaic 

is largely limited to the Midewin National Tallgrass 

Prairie (Illinois) and Mark Twain National Forest 

(Missouri). Moreover, these units are already actively 

pursuing prairie-oak savanna restoration through 

prescribed burning.

Given the above situation, the expansive oak-dominated 

woodland-forest complex, which covers a sizable portion 

of the Eastern Region, is the logical choice for a multisite restoration project. The benefits of restoring oak 

systems would be vast, greatly aiding mast-dependent 

wildlife populations and the rejuvenation of allied 

shrubs and ground flora requiring high-light conditions 

(Packard and Mutel 1997, McShea and Healy 2002). 

Research indicates that the near-universal conversion to 

shade-tolerant species is largely preventable through the 

intervention of silvicultural treatments, especially the 

reintroduction of fire (Brose et al. 2001; see also Dey and 

Fan this volume). Even in the presence of overabundant 

deer populations, it is ultimately the lack of understory 

light that causes the mortality of oak regeneration and 

associated ground flora (Anderson and Schwegman 

1991, Oswalt et al. 2006, Yuska et al. 2008). A variety of 

silvicultural treatments look promising to improve light 

conditions and reduce competition, including thinning, 

prescribed burning, and herbicide treatment, either singly 

or in combination (Brose and Van Lear 1998, 1999; also 

Dey this volume).

CONCLUSION

The recently published ecosystem restoration 

framework and policy reaffirms the U.S. Forest Service’s 

commitment to restoring ecosystems (Day et al. 2005, 

USDA FS 2008). With the recent completion of most 

Land Management Plans in the Eastern Region, National 

Forests and Grasslands are poised to initiate restoration 

efforts using framework guidance and policy. Since 

ecosystem restoration entails scientific knowledge, a 

broader landscape perspective, and multiple ownerships, 

the Eastern Regional Office has partnered with the 

Northern Research Station and The Nature Conservancy 

to facilitate these efforts. An adaptive management 

approach is envisioned whereby National Forests and 

Grasslands can collectively benefit through project 

networking. Specifically, by employing standardized 

methods of project layout and data collection, 

participants can test and compare different restoration 

techniques through shared data for a given forest type. 

Researchers will help in the experimental design and 

monitoring protocols, USFS ecologists and silviculturists 

will pool their knowledge to select the most promising 

restoration treatments, and resource specialists will 

implement and monitor treatments at the field level. 

We envision participants from both within and outside 

the agency learning to overcome significant challenges 

together as we restore oak ecosystems on the National 

Forests and Grasslands of the Eastern Region.

LITERATURE CITED

Alverson, W.S.; Waller, D.M.;. Solheim, S.L. 1988. 

Forests too deer: edge effects in northern 

Wisconsin. Conservation Biology. 2: 348-358.

Anderson, R.C. 1998. Overview of Midwestern oak 

savanna. Transactions of the Wisconsin Academy of 

Sciences, Arts, and Letters. 86 :1-18.

Anderson, R.C.;. Schwegman, J.E. 1991. Twenty years 

of vegetational change on a southern Illinois 

barren. Natural Areas Journal. 11: 100-107.
138 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Bormann, B.T.; Haynes, R.W.; Martin, J.R. 2007. 

Adaptive management of forest ecosystems: did 

some rubber hit the road? BioScience. 57: 186-191.

Brose, P.H.; Van Lear, D.H. 1998. Responses of 

hardwood advance regeneration to seasonal 

prescribed fires in oak-dominated shelterwood 

stands. Canadian Journal of Forest Research. 28: 331-

339.

Brose, P.H.; Van Lear, D.H. 1999. Effects of seasonal 

prescribed fires on residual overstory trees in oakdominated shelterwood stands. Southern Journal of 

Applied Forestry. 23: 88-93.

Brose, P.; Schuler, T; Van Lear, D.; Berst, J. 2001. 

Bringing fire back: The changing regimes of the 

Appalachian mixed-oak forests. Journal of Forestry. 

99: 30-35.

Day, K.; Berg, J.; Brown, H.; Crow, T; Morrison, J.; 

Nowacki, G.; Puckett, D.; Sallee, R.; Schneck, T.; 

Wood, B. 2006. Ecosystem restoration: a framework 

for restoring and maintaining the National Forests 

and Grasslands. Washington, DC: U.S. Forest Service 

unpublished report. (Available: fsweb.wo.fs.fed.us/

restoration/documents/RestFramework_final_010606.

pdf)

Dey, D.C.; Fan, Z. 2009. A review of fire and oak 

regeneration and overstory recruitment. In: 

Hutchinson, T.F., ed. Proceedings of the 3rd fire in 

eastern oak forests conference; 2008 May 20-22; 

Carbondale, IL. Gen. Tech. Rep. NRS-P-46. Newtown 

Square, PA: U.S. Department of Agriculture, Forest 

Service, Northern Research Station: 3-20.

Gustafson, E.J.; Lytle, D.E.; Swaty, R.; Loehle, C. 2007. 

Simulating the cumulative effects of multiple forest 

management strategies on landscape measures of 

forest sustainability. Landscape Ecology. 22: 141-156.

McShea, W.J.; Healy, W.M., eds. 2002. Oak forest 

ecosystems: ecology and management for wildlife.

Baltimore, MD: Johns Hopkins University Press. 

448 p.

Nowacki, G.J.; Abrams, M.D. 2008. The demise of 

fire and “mesophication” of forests in the eastern 

United States. BioScience. 58: 123-138.

Nuzzo, V.A. 1986. Extent and status of Midwest oak 

savanna: Presettlement and 1985. Natural Areas 

Journal. 6: 6-36.

Orwig, D.A.; Foster, D.R. 1998. Forest response to 

hemlock woolly adelgid in southern New England.

Journal of the Torrey Botanical Society. 125: 60-73.

Oswalt, C.M.; Clatterbuck, W.K.; Houston, A.E. 2006. 

Impacts of deer herbivory and visual grading on 

the early performance of high-quality oak planting 

stock in Tennessee, USA. Forest Ecology and 

Management. 229: 128-135.

Packard, S.; Mutel, C.F.. 1997. Tallgrass restoration 

handbook: For prairies, savannas, and woodlands.

Washington, D.C.: Island Press. 463 p.

Rentch, J.S., T.M. Schuler, W.M. Ford, and G.J. 

Nowacki. 2007. Red spruce stand dynamics, 

simulations, and restoration opportunities in the 

central Appalachians. Restoration Ecology. 15: 440-

452.

Schulte, L.A.; Mladenoff, D.J.; Crow, T.R.; Merrick, 

L.C.; Cleland, D.T. 2007. Homogenization of 

northern U.S. Great Lakes forests due to land use.

Landscape Ecology. 22: 1089-1103.

SER (Society for Ecological Restoration International, 

Science and Policy Working Group). 2004. The SER 

international primer on ecological restoration.

Tucson, AZ: SER. www.ser.org/content/ecological 

restoration primer.asp.

Shands, W.E.; Healy, R.G. 1977. The lands nobody 

wanted: Policy for National Forests in the eastern 

United States. Washington, D.C.: The Conservation 

Foundation. 282 p.

Stankey, G.H.; Clark, R.N.; Bormann, B.T. 2005. 

Adaptive management of natural resources: theory, 
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 139

concepts, and management institutions. Gen. 

Tech. Rep. PNW-GTR-654. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific 

Northwest Research Station. 73 p.

Thompson, I.D.; Simard, J.H.; Titman, R.D. 2006. 

Historical changes in white pine (Pinus strobus L.) 

density in Algonquin Park, Ontario, during the 19th

century. Natural Areas Journal. 26: 61-71.

Transeau, E.N. 1935. The prairie peninsula. Ecology. 

16: 423-427.

USDA Forest Service. 2008. Ecological restoration 

and resilience. Forest Service Manual, Chapter 2020. 

Washington, DC: U.S. Department of Agriculture, 

Forest Service.

Walters, C.J.; Holling, C.S. 1990. Large-scale 

management experiments and learning by doing.

Ecology. 71: 2060-2068.

Yaussy, D.A.; Nowacki, D.J.; Schuler, T.M.; Dey, 

D.C.; DeGayner, E.J. 2008. Developing a 

unified monitoring and reporting system: a key 

to successful restoration of mixed-oak forests 

throughout the Central Hardwood region. In: Deal, 

R.L., ed. Proceedings of the 2007 national silviculture 

workshop; 2007 May 7-11; Ketchikan, AK. Gen. 

Tech. Rep. PNW-GTR-733. Portland, OR: U.S. 

Department of Agriculture, Forest Service, Pacific 

Northwest Research Station: 281-286.

Yuska, A.M.; Steiner, K.C.; Finley, J.C. 2008. Effects 

of deer exclosures on oak regeneration in closedcanopy stands. In: Jacobs, D.F.; Michler, C.H., eds. 

Proceedings, 16th central hardwood forest conference; 

2008 April 8-9; West Lafayette, IN. Gen.Tech. Rep. 

NRS-P-24. Newtown Square, PA: U.S. Department 

of Agriculture, Forest Service, Northern Research 

Station: 91-99.
140 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 141

poster abstracts
142 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

RESPONSE OF UPLAND OAK AND CO-OCCURRING COMPETITOR

SEEDLINGS FOLLOWING SINGLE AND REPEATED PRESCRIBED FIRES

Heather D. Alexander1, Mary Arthur1, David Loftis2, and Stephanie Green3

1

Ph.D. Candidate (HDA) and Professor (MA), University of Kentucky, Forestry Department, Lexington, KY 2

Project Leader, U.S. Forest Service, Bent Creek Experimental Forest, Asheville, NC 3

Senior Land Management Specialist, Southwest Florida Water Management District, Brooksville, FL

HDA is corresponding author; to contact, call (859) 257-2806 or email at heather.alexander@uky.edu

Studies within and outside the United States indicate recurring oak (Quercus spp.) regeneration problems. 

In deciduous forests of the eastern U.S., a prevailing explanation for this trend is that fire suppression 

leads to high competitor abundance and low understory light. In response, prescribed fire is increasingly 

used as a management tool to remedy these conditions and encourage future oak establishment and 

growth. Within eastern Kentucky, we implemented single and repeated (3x) prescribed fires over a 

6-yr period (2002-2007). Pre- and post-burn, we quantified canopy cover and oak seedling survival 

and growth compared to other woody seedlings deemed potential competitors, primarily red maple 

(Acer rubrum L.) and sassafras (Sassafras albidum [Nutt.] Nees.). Burning temporarily decreased canopy 

cover 3-10 percent, but cover rebounded the subsequent growing season. Repeated burning ultimately 

produced canopy cover about 6 percent lower than sites unburned and burned once, suggesting a 

cumulative effect on understory light. Red maple exhibited low survival (40 percent) following single 

and repeated burns, but growth remained similar to unburned seedlings. Burning had little impact on 

sassafras survival and led to total height and basal diameters two times greater than unburned seedlings. 

A single burn had no impact on red oak (Erythrobalanus spp.) survival and increased height and basal 

diameters 25-30 percent, but this positive growth response was driven by seedlings on several plots that 

experienced high burn temperatures and consequently high overstory mortality. White oaks (Leucobalanus

spp.), however, exhibited twice the mortality of those unburned, with no change in growth parameters. 

Repeated burning negatively impacted survival and growth of both oak groups compared to unburned 

seedlings, and among both burn regimes, oaks with smaller pre-burn basal diameters exhibited the 

lowest postburn survival. Thus, despite the ability of prescribed burns to increase understory light and 

reduce red maple survival, neither single or repeated burns placed oaks in an improved competitive 

position. These findings result from a combination of highly variable yet interdependent factors including 

1) the life history traits of oaks compared to their co-occurring competitors; 2) pre-burn stature of 

pre-existing oak seedlings; and 3) variability in fire temperature and effects on overstory structure.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 143

FIRST-YEAR RESULTS OF A PRESCRIBED BURN IN

A HIGH-ELEVATION RED OAK STAND

Peter Bates1 and Dean Simon2

1

Associate Professor, Department of Geosciences and Natural Resources, Western Carolina University, Cullowhee, NC 2

Western Region Wildlife Forester, North Carolina Wildlife Resources Commission, Lawndale, NC

PB is corresponding author; to contact, call (828) 227-3914 or email at bates@email.wcu.edu

In March 2007, a prescribed burn was conducted on approximately 70 acres in a high-elevation red oak 

stand located on the Cold Mountain Game Land in western North Carolina. This burn was the first in 

a series of treatments designed to increase oak and hickory regeneration in this stand. Other treatments 

will include an herbicide application, a second prescribed burn, and a shelterwood harvest. Fifty-two, 1/10-

acre, fixed-radius forest data collection plots were established prior to the burn. Thirty of these plots were 

within the prescribed burn area and 22 were outside of the burn. Vegetative conditions in these plots were 

remeasured in the year following the burn. Fuel loads were measured at each of the 52 plots immediately 

before the burn and in the 30 burn plots immediately after the burn. Fire intensity was estimated at each 

burn plot by hanging ceramic tiles with temperature-sensitive paint 20 inches above the ground. Data were 

collected to evaluate and compare the first-year effects of the fire (and fire intensity) on the following stand 

characteristics: (1) regeneration density of oaks, hickories, maples, and other species; (2) crown damage 

and mortality in overstory trees; and (3) hard mast production. Permanent photo points established at 

each plot provide a visual evaluation and comparison of preburn, postburn, and unburned plot conditions.
144 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

Modeling the protection afforded by burrows, cavities, and 

roosts during wildland surface fires

Anthony Bova and Matthew Dickinson1

1

Physical Scientist (AB), and Research Ecologist (MD), U.S. Forest Service, Northern Research Station, Delaware, OH

AB is corresponding author; to contact, call (740) 368-0093 or email at abova@fs.fed.us

Wildland surface fires produce many toxic and irritating compounds, such as formaldehyde and 

acrolein, and harmful gases such as carbon monoxide. Several factors influence the degree of 

protection offered by animal shelters against combustion products and heat. Prominent among 

these variables are shelter configuration, the velocity of the prevailing wind, and time of exposure. 

We employed Fire Dynamics Simulator software, available from the National Institute of Standards 

and Technology, to model the mixing of smoke and gases in an assortment of animal shelters, 

including bark flaps, burrows, and tree cavities. Preliminary results are presented, and we discuss the 

possibility of developing a comparatively simple general relationship to estimate shelter vulnerability.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 145

PRESCRIBED FIRE RESEARCH IN PENNSYLVANIA

Patrick Brose1

1

Research Forester, U.S. Forest Service, Northern Research Station, Irvine, PA

To contact, call (814) 563-1040 or email at pbrose@fs.fed.us

Prescribed fire in Pennsylvania is a relatively new forestry practice because of the State’s adverse 

experience with highly destructive wildfires in the early 1900s. The recent introduction of 

prescribed fire raises a myriad of questions regarding its correct and safe use. This poster briefly 

describes the prescribed fire research projects of the Forestry Sciences Lab located at Irvine, PA.

One of the primary reasons prescribed fire is becoming increasingly popular with land managers is its ability 

to benefit oak regeneration at the expense of other hardwood reproduction. Earlier research identified 

four principal factors that determine whether an advanced regeneration stem sprouts after being top-killed 

by a fire. Those factors are: season-of-burn, fire intensity, size of the stem’s root collar, and depth of the 

root collar in the forest floor. The Post-Fire Sprouting Probability Project seeks to further understand 

this complex relationship by linking a fire’s seasonality and total heat output to the sprouting response 

of the advance regeneration of 10 common hardwood species. This linkage is done on 6-ft circular plots 

by 1) determining litter and woody fuels loadings before and after a prescribed fire; 2) measuring heat 

output of the passing flame front with a datalogger/thermocoupler; and 3) tagging advanced regeneration 

of different hardwood species and excavating dead and sprouting hardwood advanced regeneration 

several weeks after the burn. These data will be developed into predictive models that land managers 

can use to better plan and implement prescribed fires to aid in regenerating Pennsylvania’s oak forests.

Closely related to the above project is the Shelterwood—Burn Applicability Study done in 

cooperation with the Allegheny National Forest (ANF). This project seeks to ascertain whether a 

forestry practice that originated in the Piedmont Region can work in northern Pennsylvania, given 

the differences in forest conditions. From 2002 through 2004, extensive preburn data were collected 

on four fenced oak shelterwood stands on the ANF. In May 2005, half of each shelterwood stand 

was burned with a moderately intense prescribed fire to release the oak regeneration from competing 

hardwood reproduction. Initial post-fire data collection in 2006 indicated that the fires had done 

their job; densities of competing hardwood regeneration, primarily black birch (Betula lenta) 

and red maple (Acer rubrum L.), were reduced and nearly all the oak reproduction had sprouted. 

Another inventory is scheduled for summer 2008 and results will be published in a forestry journal.

One of the arguments against burning shelterwood stands is the distinct possibility of killing a 

high value tree or damaging the butt log. Post-fire mortality models have existed for decades for 

predicting whether a tree is likely to die within 3 years of being injured by a fire. Unfortunately, 

these models are limited to oaks and do not take into account the other high-value species, 

such as black cherry (Prunus serotina Ehrh.), sugar maple (Acer saccharum Marsh.), and yellowpoplar (Liriodendron tulipfera L.), that are often important associates in a mixed oak forest.

The Residual Tree Damage Project is being undertaken to fill that knowledge gap. Before a partially 

cut stand is burned, it is scouted for residual trees with excessive fuel loadings near their bases. These 

fuels are inventoried and the tree base and fuels photographed. The fuels are reinventoried after 
146 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

the fire and the tree is monitored for survival for 3 years. Preliminary results indicate only woody 

fuels exceeding 10 tons/acre that lie within 5 ft of a tree’s base pose a threat of killing that tree.

A key part of any prescribed fire program is having and using fuel models to aid in predicting fire behavior. 

However, hardwood fuel models are few in number, are broad and general in terms of application, and have 

not been rigorously tested. Since 2002, the Eastern Fuel Models Project has been underway to evaluate 

the existing hardwood fuel models, develop new models for unrepresented fuel types, and disseminate this 

knowledge to forest managers in a photo series. Early results indicate that Fuel Model 9 (loose leaf litter) is 

reasonably accurate for oak-dominated forests in fall and spring; Fuel Model 8 (compacted litter) is appropriate 

for Allegheny hardwood and northern hardwood forests in spring; and no model seems to consistently 

work well for heath shrubs (e.g., blueberry, huckleberry, and mountain laurel) and hardwood slash.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 147

Red maple (Acer rubrum) response to prescribed burning on 

the William B. Bankhead National Forest, Alabama

Stacy L. Clark and Callie J. Schweitzer1

1

Research Foresters, U.S. Forest Service, Southern Research Station, Huntsville, AL

SLC is corresponding author; to contact, call (256) 585-0652 or email at stacyclark@fs.fed.us

Prescribed burning is part of Land and Resource Management Plans on National Forest System lands 

throughout the southeastern United States, and is sometimes implemented to achieve a desired future 

condition of oak-dominated forest or woodland habitat. However, effects of burning on oak (Quercus

spp.) competitors, such as red maple (Acer rubrum L.) are not well understood. In this study, we 

documented red maple seedling and sapling response to prescribed burns at both large (stand-level) 

and small (0.01-acre plot level) scales, and we examined relationships between fire behavior and red 

maple response. The study was implemented in 2005 within a larger replicated silvicultural study on 

the William B. Bankhead National Forest in Lawrence County, AL. At the stand-level scale, prescribed 

burning had no effect on red maple sapling mortality, sprouting, or diameter growth in the largest size 

class (1.5- to 5.4-inch diameter at breast height [d.b.h.]). Burned stands showed a significant increase in 

red maple seedlings (< 4.6 ft height) and a significant decrease in small saplings (> 4.5 ft height, < 1.5 inch 

d.b.h.) compared to unburned stands. At the plot-level scale, neither maximum recorded temperature 

or heat index (duration of temperature > 90 °F) of the fire could significantly explain the variation in 

sapling density changes, sapling sprouting occurrence, sapling diameter growth, or changes in seedling 

density. Results indicate that one dormant-season prescribed burn was not effective at decreasing oak 

competition of red maple in the midstory but did increase red maple competitors in the understory.
148 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

SURFACE FIRE EFFECTS ON CONIFER AND HARDWOOD CROWNS—

APPLICATIONS OF AN INTEGRAL PLUME MODEL

Matthew Dickinson1, Anthony Bova1, Kathleen Kavanagh2, Antoine Randolph3, and Lawrence Band3

1 Research Ecologist (MD), Physical Scientist (AB), U.S. Forest Service, Northern Research Station, Delaware, OH 2

Associate Professor, Department of Forest Resources, University of Idaho, Moscow, ID 3

Graduate Student (AR), Professor (LB), Department of Geography, University of North Carolina, Chapel Hill, NC

MB is corresponding author; to contact, call (740) 368-0096 or email at mbdickinson@fs.fed.us

An integral plume model was applied to the problems of tree death from canopy injury in dormantseason hardwoods and branch embolism in Douglas fir (Pseudotsuga menziesii) crowns. Our purpose was 

to generate testable hypotheses. We used the integral plume models to relate crown injury to bole injury 

and to explore the effects of variation in fire behavior.

For dormant-season hardwoods, effects of the plume on the crown were modeled by a branch necrosis 

routine involving heat transfer and thermal tolerance. If a stem was predicted to survive stem heating from 

flames, aggregate branch death from plume heating determined proportional crown loss, which, in turn, 

determined tree allocation to spring refoliation. Hardwood mortality occurred as a function of subsequent 

growth. Differences in bark thickness among hardwood species led to large differences in susceptibility to 

modeled girdling from flames. For trees predicted to survive flame effects, branch diameter contributed 

significantly to differences in height of branch kill. A parametric equation based on multiple model 

simulations is provided to describe branch kill height as a function of fire behavior and crown characteristics. 

Branch embolism in Douglas fir is hypothesized to occur in response to foliage exposures to high 

vapor pressure deficits within the plume occurring on a time scale too short for stomatal response. 

We speculate that the resulting branch embolism may be a pervasive effect of surface fires on Douglas 

fir during periods when stomata are open. Cuticular water loss was not sufficient to cause embolism.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 149

FIRE HISTORY AND THE ESTABLISHMENT OF OAKS AND MAPLES IN

SECOND-GROWTH FORESTS

Todd Hutchinson1, Robert Long1, Robert Ford1, and Elaine Kennedy Sutherland2

1

Research Ecologist (TH), Research Plant Pathologist (RL), Forestry Technician (retired) (RF), U.S. Forest Service, 

Northern Research Station, Delaware, OH 2

Supervisory Research Biologist, U.S. Forest Service, Rocky Mountain Research Station

TH is corresponding author; to contact, call (740) 368-0064 or email at thutchinson@fs.fed.us

We used dendrochronology to examine the influence of past fires on oak and maple establishment. Six study 

units were located in southern Ohio, where organized fire control began in 1923. After stand thinning in 

2000, we collected basal cross sections from cut stumps of oak (n = 137) and maple (n = 204). The fire 

history of each unit was developed from the oaks, and both oak and maple establishment were examined 

in relation to fire history. Twenty-six fires were documented from 1870 to1933; thereafter, only two fires 

were identified. Weibull median fire-return intervals ranged from 9.1 to 11.3 years for the period ending 

in 1935; mean fire occurrence probabilities (years/fires) for the same period ranged from 11.6 to 30.7 

years. Among units, stand initiation began ca. 1845 to 1900 and virtually no oak recruitment was recorded 

after 1925. Most maples established after the cessation of fires. In several units, the last significant fire 

was followed immediately by a large pulse of maple establishment and the cessation of oak recruitment, 

indicating a direct relationship between fire cessation and a shift from oak to maple establishment.
150 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

FIRE HISTORY AND AGE STRUCTURE ANALYSIS IN THE SHERBURNE 

NATIONAL WILDLIFE REFUGE, MINNESOTA: ESTABLISHING REFERENCE 

CONDITIONS IN A REMNANT OAK SAVANNA WOODLAND

 Kurt F. Kipfmueller1 and Tim Hepola2

1

 Assistant Professor, Department of Geography, University of Minnesota

2 Regional Fire Ecologist, U.S. Fish and Wildlife Service, Ft. Snelling, MN

TH is corresponding author; to contact, call (612) 713-5479 or email at tim_hepola@fws.gov

Oak savanna woodlands were once a dominant ecotone in southwestern Minnesota and throughout the 

upper Midwest. These ecosystems represented a transitional zone between prairie communities to the west 

that eventually graded into Big Woods forest. Most of the oak savanna landscape of southern Minnesota 

(and indeed most of the Midwest) were extensively homesteaded and farmed during the middle 1800s 

and few intact savanna landscapes remain today. The structure, origin, and factors that have maintained 

presettlement oak savanna have not been well documented or established. Fires, perhaps ignited by 

Native Americans, are thought to have maintained these landscapes, but the disturbance regime of these 

landscapes prior to widespread Euro-American impact remains elusive. Given the current interest in 

preserving, maintaining, and restoring these systems, it is imperative that the natural factors that have 

shaped these areas be investigated. Prescribed fires have become an important tool in this regard, but fire 

management activities can be better implemented if the natural role of fire is uncovered. Reconstructing 

the historic fire regime in oak savanna woodlands is challenging because few people are of sufficient 

age to extend to periods before appreciable impacts by human activities. However, this information is 

critical for establishing reference conditions that can be utilized to guide restoration activities and initiate 

management activities. This research will investigate the potential of developing reference conditions 

in a relatively intact oak savanna in the Sherburne National Wildlife Refuge (Minnesota). Vegetation 

plots will be established throughout the remnant to determine the variability in savanna structure and 

composition. Fire scars will be collected throughout the remnant to determine the variability in fire 

frequency and associated changes in savanna age-structure and composition related to fire activity. This 

research will provide a context for current management activities centered on maintaining and restoring 

oak savanna ecosystems. The principal questions to be answered include: What is the fire frequency of 

the oak savanna remnant and how much variation exists over space? How has fire frequency changed over 

time? Are there particular time periods when fire was more/less prominent? Are forest compositional and 

structural characteristics related to fire frequency? Has the seasonality of fire changed over time? Identifying 

the historic fire regime of oak savanna landscapes, the associated forest structures, and spatial variations 

is critical to developing sound management guidelines for the restoration of these landscapes. Since the 

proposed study area is one of the few old-growth remnants of this ecosystem in the refuge, information 

developed in this study will be useful in managing other parts of the refuge. Few detailed investigations 

of oak savanna fire history and age structure have been completed. This research will add substantially to 

our understanding of the vegetation dynamics and disturbance regime that characterize this landscape.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 151

OAK REGENERATION ACROSS A HETEROGENEOUS LANDSCAPE IN OHIO: 

SOME LIMITED SUCCESS AFTER THINNING, TWO FIRES, 

AND SEVEN YEARS

Louis Iverson1, Todd Hutchinson1, Anantha Prasad1, and Matthew Peters1

1

Research Landscape Ecologist (LI), Research Ecologist (TH), Ecologist (AP), GIS Specialist (MP), U.S. Forest Service, 

Northern Research Station, Delaware, OH

LI is corresponding author; to contact, call (740) 368-0097 or email at liverson@fs.fed.us

We document an increase in oak and hickory advance regeneration, depending on landscape position, 

in the sixth year (2006) after mechanical thinning (2000) and repeated prescribed fires (2001 and 2005) 

across two sites (Raccoon Ecological Management Area and Zaleski State Forest) in southern Ohio. Each of 

four 20+ ha units (two controls and two thin plus burn twice) were modeled and mapped into a long-term 

moisture regime (integrated moisture index [IMI]) and plots were established at each of 242 points on a 

50-m grid. Plots were monitored for light and vegetation in 2000, 2001, 2004, and 2006. From these data, 

we developed two simple models: (1) a model of oak “competitiveness,” based on advance regeneration of 

oaks and their competitors; and (2) a model estimating the probability of a plot’s becoming “competitive 

for oak” based on canopy openness, IMI class, and number of oak and hickory seedlings present. For dry 

or intermediate (not mesic) sites with at least 5,000 oak and hickory seedlings/ha, opening the canopy to 

8.5-19 percent, followed by at least two fires, should allow oak and hickory to be “competitive” over about 

50 percent of the area. Overall, these results suggest promise for partial harvesting and repeated fires as a 

management strategy to reverse the accelerating loss of oak dominance in the central hardwoods region. 
152 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

PRESCRIBED FIRE AND OAK SEEDLING DEVELOPMENT IN

AN APPALACHIAN FOREST

Jacob Royse1, Mary Arthur1, and David Loftis2

1

Graduate student (JR) and Professor (MA), Department of Forestry, University of Kentucky, Lexington, KY 2

Research Forester, U.S. Forest Service, Southern Research Station, Asheville, NC

JR is corresponding author; to contact, call (859) 257-8289 or email at Jacob.Royse@uky.edu

In recent decades considerable research has focused on the use of prescribed fire in oak-dominated 

forests with the management objective of promoting oak regeneration for future overstory dominance. 

These studies typically focus on the response of oak seedlings and saplings already in place when 

experimental prescribed fires are set because it is difficult to time fires to coincide with the production 

of an acorn mast crop. We examined the development of white oak (Quercus alba) and chestnut oak 

(Q. prinus) seedlings growing from seed after a mast crop in 2005. At the time the mast crop occurred, 

an experiment was already in place with three treatments: Fire-excluded (control), 1x-burn (burned in 

2003), and 3x-burn (burned in 2003 and 2004, with an additional fire in 2006 when acorns were on 

the ground). We tracked seedling survival and growth over two growing seasons, in 2006 and 2007. 

Litter depth and percentage open sky were significant predictors of oak seedling mortality after the first 

and second growing seasons. As litter depth increased, so did oak seedling mortality. In contrast, as 

percent open sky increased, mortality decreased. White oak seedlings growing in low-light conditions 

(5 to 10 percent canopy openness) had higher mortality rates than did chestnut oak. Higher litter 

depth associated with fire-excluded and 1x-burn treatment led to greater stem lengths during the first 

growing season, likely due to excess stem elongation to breach the litter layer for available light. However, 

relative growth rate of stem length after 2 years revealed that oak seedlings on three-burn treatments far 

exceeded that of seedlings on fire-excluded treatments. Percent open sky and oak seedling diameter were 

positively correlated, and basal diameter of oak seedlings on three-burn and one-burn treatments had 

significantly greater diameters than fire-excluded seedlings after the second growing season. This study 

reveals the importance of light and litter depth on the early survival and growth of oak seedlings. Newly 

developing oak seedlings originating from acorns on recently burned sites displayed greater survival 

and growth rates than seedlings growing under the nearly closed canopy found on fire-excluded sites.
Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46 153

PREDICTING FIRE SCARS IN OZARK TIMBER SPECIES 

FOLLOWING PRESCRIBED BURNING

Aaron P. Stevenson1, Richard P. Guyette2, Rose-Marie Muzika2

1

Forest Community Ecologist, Missouri Department of Conservation, West Plains, MO 2

Research Professor (RG), Associate Professor (RMM), Department of Forestry, University of Missouri, Columbia, MO

APS is corresponding author; to contact, call (417) 255-9561 ext 272 or email at Aaron.Stevenson@mcd.mo.gov

A potential consequence of using prescribed fire is heat-related injury to timber trees. Scars formed following 

fire injuries are often associated with extensive decay in hardwoods. The ability to predict scarring caused by 

prescribed fire is important when multiple management goals are incorporated on a single forest site. We 

evaluated the size and frequency of prescribed fire scars for six tree species in the Missouri Ozark Highlands. 

Tree species chosen for evaluation were hickories (Carya spp.), shortleaf pine (Pinus echinata), white oak 

(Quercus alba), scarlet oak (Q. coccinea), post oak (Q. stellata), and black oak (Q. velutina). We established 

plots on upland forest sites managed with prescribed fire and examined 3,945 trees for fire scars on these 

sites. Scarred trees were tallied and the largest scars were measured for each plot. Post-fire scarring models 

indicate bark char, a proxy for fire intensity, is the most important predictor of scar frequency and scar size. 

Other important predictors of scarring include tree size, aspect, and fetch. Species-specific scarring models 

developed from this study may be used to predict the extent of fire scars caused by prescribed burning.
154 Proceedings of the 3rd Fire in Eastern Oak Forests Conference GTR-NRS-P-46

AIRBORNE FIRE MONITORING—EXTRACTION OF ACTIVE FIRE FRONTS 

FROM TIME-SEQUENCE IMAGING OF THE ARCH ROCK FIRE IN

SOUTHEAST OHIO

Loredana Suciu1,Anthony S. Bova2, Matthew B. Dickinson2, Jim Dyer1, Robert Kremens3, 

and Valerie L. Young4

1

M.S. candidate (LS) and Associate Professor (JD), Ohio University, Athens OH 2

Physical Scientist (ASB) and Research Ecologist (MBD), U.S. Forest Service, Northern Research Station, Delaware, OH 3

Senior Research Scientist, Rochester Institute of Technology, Rochester, NY 4

Associate Professor, Ohio University, Athens, OH

MBD is corresponding author; to contact, call (740) 368-0096 or email at mbdickinson@fs.fed.us

This project investigates a prescribed fire in southeastern Ohio through remote sensing measurements of 

emitted radiance. Time-sequence airborne imaging consisted of multiple over-flights with a repeat interval 

of 3-6 minutes performed by an aircraft equipped with an infrared camera. Images were processed and 

analyzed to extract the active fire fronts and estimate the direction of fire propagation, rate of spread, 

fuel consumption, and fire intensity. Using airborne high-resolution infrared imagery provides an 

unprecedented opportunity to accurately estimate fuel consumption and fire intensity over large burn 

units. The resulting fire behavior information can then be used to determine the fire’s ecological effects.
Printed on Recycled Paper

The U.S. Department of Agriculture (USDA) prohibits discrimination in all its programs and activities on 

the basis of race, color, national origin, age, disability, and where applicable, sex, marital status, familial 

status, parental status, religion, sexual orientation, genetic information, political beliefs, reprisal, or because 

all or part of an individual’s income is derived from any public assistance program. (Not all prohibited 

bases apply to all programs.) Persons with disabilities who require alternate means for communication 

of program information (Braille, large print, audiotape, etc.) should contact USDA’s TARGET Center at 

(202)720-2600 (voice and TDD). To file a complaint of discrimination, write to USDA, Director, Office 

of Civil Rights, 1400 Independence Avenue, S.W., Washington, DC 20250-9410, or call (800)795-3272 

(voice) or (202)720-6382 (TDD). USDA is an equal opportunity provider and employer. 

Hutchinson, Todd F., ed. 2009. Proceedings of the 3rd fire in eastern oak forests 

conference; 2008 May 20-22; Carbondale, IL. Gen. Tech. Rep. NRS-P-46. 

Newtown Square, PA: U.S. Department of Agriculture, Forest Service, Northern 

Research Station. 154 p.

Contains 10 full-length papers and 12 abstracts of posters that were presented at the 

3rd Fire in Eastern Oak Forests conference, held in Carbondale, IL, May 20-22, 2008. 

The conference was attended by over 200 people from a variety of groups, including 

federal and state agencies, nongovernmental organizations, universities, and private 

citizens.

KEY WORDS: fire, eastern forests, forest management, oak
Capitalizing on the strengths of existing science 

capacity in the Northeast and Midwest to attain a more 

integrated, cohesive, landscape-scale research program

www.nrs.fs.fed.us